Toward a cognitive task analysis for biomedical query mediation.

PubMed

Hruby, Gregory W; Cimino, James J; Patel, Vimla; Weng, Chunhua

2014-01-01

In many institutions, data analysts use a Biomedical Query Mediation (BQM) process to facilitate data access for medical researchers. However, understanding of the BQM process is limited in the literature. To bridge this gap, we performed the initial steps of a cognitive task analysis using 31 BQM instances conducted between one analyst and 22 researchers in one academic department. We identified five top-level tasks, i.e., clarify research statement, explain clinical process, identify related data elements, locate EHR data element, and end BQM with either a database query or unmet, infeasible information needs, and 10 sub-tasks. We evaluated the BQM task model with seven data analysts from different clinical research institutions. Evaluators found all the tasks completely or semi-valid. This study contributes initial knowledge towards the development of a generalizable cognitive task representation for BQM.

Aligning Event Logs to Task-Time Matrix Clinical Pathways in BPMN for Variance Analysis.

PubMed

Yan, Hui; Van Gorp, Pieter; Kaymak, Uzay; Lu, Xudong; Ji, Lei; Chiau, Choo Chiap; Korsten, Hendrikus H M; Duan, Huilong

2018-03-01

Clinical pathways (CPs) are popular healthcare management tools to standardize care and ensure quality. Analyzing CP compliance levels and variances is known to be useful for training and CP redesign purposes. Flexible semantics of the business process model and notation (BPMN) language has been shown to be useful for the modeling and analysis of complex protocols. However, in practical cases one may want to exploit that CPs often have the form of task-time matrices. This paper presents a new method parsing complex BPMN models and aligning traces to the models heuristically. A case study on variance analysis is undertaken, where a CP from the practice and two large sets of patients data from an electronic medical record (EMR) database are used. The results demonstrate that automated variance analysis between BPMN task-time models and real-life EMR data are feasible, whereas that was not the case for the existing analysis techniques. We also provide meaningful insights for further improvement.

Skill sharing and delegation practice in two Queensland regional allied health cancer care services: a comparison of tasks.

PubMed

Passfield, Juanine; Nielsen, Ilsa; Brebner, Neil; Johnstone, Cara

2017-07-24

Objective Delegation and skill sharing are emerging service strategies for allied health (AH) professionals working in Queensland regional cancer care services. The aim of the present study was to describe the consistency between two services for the types and frequency of tasks provided and the agreement between teams in the decision to delegate or skill share clinical tasks, thereby determining the potential applicability to other services. Methods Datasets provided by two similar services were collated. Descriptive statistical analyses were used to assess the extent of agreement. Results In all, 214 tasks were identified as being undertaken by the services (92% agreement). Across the services, 70 tasks were identified as high frequency (equal to or more frequently than weekly) and 29 as not high frequency (46% agreement). Of the 68 tasks that were risk assessed, agreement was 66% for delegation and 60% for skill sharing, with high-frequency and intervention tasks more likely to be delegated. Conclusions Strong consistency was apparent for the clinical tasks undertaken by the two cancer care AH teams, with moderate agreement for the frequency of tasks performed. The proportion of tasks considered appropriate for skill sharing and/or delegation was similar, although variation at the task level was apparent. Further research is warranted to examine the range of factors that affect the decision to skill share or delegate. What is known about the topic? There is limited research evidence regarding the use of skill sharing and delegation service models for AH in cancer care services. In particular, the extent to which decisions about task safety and appropriateness for delegation or skill sharing can be generalised across services has not been investigated. What does this paper add? This study investigated the level of clinical task consistency between two similar AH cancer care teams in regional centres. It also examined the level of agreement with regard to delegation and skill sharing to provide an indication of the level of local service influence on workforce and service model decisions. What are the implications for practitioners? Local factors have a modest influence on delegation and skill sharing decisions of AH teams. Practitioners need to be actively engaged in decision making at the local level to ensure the clinical service model meets local needs. However, teams should also capitalise on commonalities between settings to limit duplication of training and resource development through collaborative networks.

The Integrated Clinical Anatomy Program at Alfaisal University: An Innovative Model of Teaching Clinically Applied Functional Anatomy in a Hybrid Curriculum

ERIC Educational Resources Information Center

Yaqinuddin, Ahmed; Ikram, Muhammad Faisal; Zafar, Muhammad; Eldin, Nivin Sharaf; Mazhar, Muhammad Atif; Qazi, Sadia; Shaikh, Aftab Ahmed; Obeidat, Akef; Al-Kattan, Khaled; Ganguly, Paul

2016-01-01

Anatomy has historically been a cornerstone in medical education regardless of specialty. It is essential for physicians to be able to perform a variety of tasks, including performing invasive procedures, examining radiological images, performing a physical examination of a patient, etc. Medical students have to be prepared for such tasks, and we…

Cancer Model Development Centers

Cancer.gov

The Cancer Model Development Centers (CMDCs) are the NCI-funded contributors to the HCMI. They are tasked with producing next-generation cancer models from clinical samples. The cancer models will encompass tumor types that are rare, originate from patients from underrepresented populations, or lack precision therapy. These models will be annotated with clinical and genomic data and will become a community resource.

Leadership support for ward managers in acute mental health inpatient settings.

PubMed

Bonner, Gwen; McLaughlin, Sue

2014-05-01

This article shares findings of work undertaken with a group of mental health ward managers to consider their roles through workshops using an action learning approach. The tensions between the need to balance the burden of administrative tasks and act as clinical role models, leaders and managers are considered in the context of providing recovery-focused services. The group reviewed their leadership styles, broke down the administrative elements of their roles using activity logs, reviewed their working environments and considered how recovery focused they believed their wards to be. Findings support the notion that the ward manager role in acute inpatient settings is at times unmanageable. Administration is one aspect of the role for which ward managers feel unprepared and the high number of administrative tasks take them away from front line clinical care, leading to frustration. Absence from clinical areas reduces opportunities for role modeling good clinical practice to other staff. Despite the frustrations of administrative tasks, overall the managers thought they were supportive to their staff and that their wards were recovery focused.

Use of Decision Models in the Development of Evidence-Based Clinical Preventive Services Recommendations: Methods of the U.S. Preventive Services Task Force.

PubMed

Owens, Douglas K; Whitlock, Evelyn P; Henderson, Jillian; Pignone, Michael P; Krist, Alex H; Bibbins-Domingo, Kirsten; Curry, Susan J; Davidson, Karina W; Ebell, Mark; Gillman, Matthew W; Grossman, David C; Kemper, Alex R; Kurth, Ann E; Maciosek, Michael; Siu, Albert L; LeFevre, Michael L

2016-10-04

The U.S. Preventive Services Task Force (USPSTF) develops evidence-based recommendations about preventive care based on comprehensive systematic reviews of the best available evidence. Decision models provide a complementary, quantitative approach to support the USPSTF as it deliberates about the evidence and develops recommendations for clinical and policy use. This article describes the rationale for using modeling, an approach to selecting topics for modeling, and how modeling may inform recommendations about clinical preventive services. Decision modeling is useful when clinical questions remain about how to target an empirically established clinical preventive service at the individual or program level or when complex determinations of magnitude of net benefit, overall or among important subpopulations, are required. Before deciding whether to use decision modeling, the USPSTF assesses whether the benefits and harms of the preventive service have been established empirically, assesses whether there are key issues about applicability or implementation that modeling could address, and then defines the decision problem and key questions to address through modeling. Decision analyses conducted for the USPSTF are expected to follow best practices for modeling. For chosen topics, the USPSTF assesses the strengths and limitations of the systematically reviewed evidence and the modeling analyses and integrates the results of each to make preventive service recommendations.

A Natural Language Processing-based Model to Automate MRI Brain Protocol Selection and Prioritization.

PubMed

Brown, Andrew D; Marotta, Thomas R

2017-02-01

Incorrect imaging protocol selection can contribute to increased healthcare cost and waste. To help healthcare providers improve the quality and safety of medical imaging services, we developed and evaluated three natural language processing (NLP) models to determine whether NLP techniques could be employed to aid in clinical decision support for protocoling and prioritization of magnetic resonance imaging (MRI) brain examinations. To test the feasibility of using an NLP model to support clinical decision making for MRI brain examinations, we designed three different medical imaging prediction tasks, each with a unique outcome: selecting an examination protocol, evaluating the need for contrast administration, and determining priority. We created three models for each prediction task, each using a different classification algorithm-random forest, support vector machine, or k-nearest neighbor-to predict outcomes based on the narrative clinical indications and demographic data associated with 13,982 MRI brain examinations performed from January 1, 2013 to June 30, 2015. Test datasets were used to calculate the accuracy, sensitivity and specificity, predictive values, and the area under the curve. Our optimal results show an accuracy of 82.9%, 83.0%, and 88.2% for the protocol selection, contrast administration, and prioritization tasks, respectively, demonstrating that predictive algorithms can be used to aid in clinical decision support for examination protocoling. NLP models developed from the narrative clinical information provided by referring clinicians and demographic data are feasible methods to predict the protocol and priority of MRI brain examinations. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Standardizing clinical trials workflow representation in UML for international site comparison.

PubMed

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M O; Rodrigues, Maria J; Shah, Jatin; Loures, Marco R; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-11-09

With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows.

Standardizing Clinical Trials Workflow Representation in UML for International Site Comparison

PubMed Central

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M. O.; Rodrigues, Maria J.; Shah, Jatin; Loures, Marco R.; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-01-01

Background With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Methods Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Results Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. Conclusions This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows. PMID:21085484

Benchmarking Deep Learning Models on Large Healthcare Datasets.

PubMed

Purushotham, Sanjay; Meng, Chuizheng; Che, Zhengping; Liu, Yan

2018-06-04

Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learning models with respect to the state-of-the-art machine learning models and prognostic scoring systems on publicly available healthcare datasets. In this paper, we present the benchmarking results for several clinical prediction tasks such as mortality prediction, length of stay prediction, and ICD-9 code group prediction using Deep Learning models, ensemble of machine learning models (Super Learner algorithm), SAPS II and SOFA scores. We used the Medical Information Mart for Intensive Care III (MIMIC-III) (v1.4) publicly available dataset, which includes all patients admitted to an ICU at the Beth Israel Deaconess Medical Center from 2001 to 2012, for the benchmarking tasks. Our results show that deep learning models consistently outperform all the other approaches especially when the 'raw' clinical time series data is used as input features to the models. Copyright © 2018 Elsevier Inc. All rights reserved.

Assessing the similarity of mental models of operating room team members and implications for patient safety: a prospective, replicated study.

PubMed

Nakarada-Kordic, Ivana; Weller, Jennifer M; Webster, Craig S; Cumin, David; Frampton, Christopher; Boyd, Matt; Merry, Alan F

2016-08-31

Patient safety depends on effective teamwork. The similarity of team members' mental models - or their shared understanding-regarding clinical tasks is likely to influence the effectiveness of teamwork. Mental models have not been measured in the complex, high-acuity environment of the operating room (OR), where professionals of different backgrounds must work together to achieve the best surgical outcome for each patient. Therefore, we aimed to explore the similarity of mental models of task sequence and of responsibility for task within multidisciplinary OR teams. We developed a computer-based card sorting tool (Momento) to capture the information on mental models in 20 six-person surgical teams, each comprised of three subteams (anaesthesia, surgery, and nursing) for two simulated laparotomies. Team members sorted 20 cards depicting key tasks according to when in the procedure each task should be performed, and which subteam was primarily responsible for each task. Within each OR team and subteam, we conducted pairwise comparisons of scores to arrive at mean similarity scores for each task. Mean similarity score for task sequence was 87 % (range 57-97 %). Mean score for responsibility for task was 70 % (range = 38-100 %), but for half of the tasks was only 51 % (range = 38-69 %). Participants believed their own subteam was primarily responsible for approximately half the tasks in each procedure. We found differences in the mental models of some OR team members about responsibility for and order of certain tasks in an emergency laparotomy. Momento is a tool that could help elucidate and better align the mental models of OR team members about surgical procedures and thereby improve teamwork and outcomes for patients.

From guideline modeling to guideline execution: defining guideline-based decision-support services.

PubMed Central

Tu, S. W.; Musen, M. A.

2000-01-01

We describe our task-based approach to defining the guideline-based decision-support services that the EON system provides. We categorize uses of guidelines in patient-specific decision support into a set of generic tasks--making of decisions, specification of work to be performed, interpretation of data, setting of goals, and issuance of alert and reminders--that can be solved using various techniques. Our model includes constructs required for representing the knowledge used by these techniques. These constructs form a toolkit from which developers can select modeling solutions for guideline task. Based on the tasks and the guideline model, we define a guideline-execution architecture and a model of interactions between a decision-support server and clients that invoke services provided by the server. These services use generic interfaces derived from guideline tasks and their associated modeling constructs. We describe two implementations of these decision-support services and discuss how this work can be generalized. We argue that a well-defined specification of guideline-based decision-support services will facilitate sharing of tools that implement computable clinical guidelines. PMID:11080007

Compensatory Limb Use and Behavioral Assessment of Motor Skill Learning Following Sensorimotor Cortex Injury in a Mouse Model of Ischemic Stroke

PubMed Central

Kerr, Abigail L.; Tennant, Kelly A.

2014-01-01

Mouse models have become increasingly popular in the field of behavioral neuroscience, and specifically in studies of experimental stroke. As models advance, it is important to develop sensitive behavioral measures specific to the mouse. The present protocol describes a skilled motor task for use in mouse models of stroke. The Pasta Matrix Reaching Task functions as a versatile and sensitive behavioral assay that permits experimenters to collect accurate outcome data and manipulate limb use to mimic human clinical phenomena including compensatory strategies (i.e., learned non-use) and focused rehabilitative training. When combined with neuroanatomical tools, this task also permits researchers to explore the mechanisms that support behavioral recovery of function (or lack thereof) following stroke. The task is both simple and affordable to set up and conduct, offering a variety of training and testing options for numerous research questions concerning functional outcome following injury. Though the task has been applied to mouse models of stroke, it may also be beneficial in studies of functional outcome in other upper extremity injury models. PMID:25045916

Stochastic model predicts evolving preferences in the Iowa gambling task

PubMed Central

Fuentes, Miguel A.; Lavín, Claudio; Contreras-Huerta, L. Sebastián; Miguel, Hernan; Rosales Jubal, Eduardo

2014-01-01

Learning under uncertainty is a common task that people face in their daily life. This process relies on the cognitive ability to adjust behavior to environmental demands. Although the biological underpinnings of those cognitive processes have been extensively studied, there has been little work in formal models seeking to capture the fundamental dynamic of learning under uncertainty. In the present work, we aimed to understand the basic cognitive mechanisms of outcome processing involved in decisions under uncertainty and to evaluate the relevance of previous experiences in enhancing learning processes within such uncertain context. We propose a formal model that emulates the behavior of people playing a well established paradigm (Iowa Gambling Task - IGT) and compare its outcome with a behavioral experiment. We further explored whether it was possible to emulate maladaptive behavior observed in clinical samples by modifying the model parameter which controls the update of expected outcomes distributions. Results showed that the performance of the model resembles the observed participant performance as well as IGT performance by healthy subjects described in the literature. Interestingly, the model converges faster than some subjects on the decks with higher net expected outcome. Furthermore, the modified version of the model replicated the trend observed in clinical samples performing the task. We argue that the basic cognitive component underlying learning under uncertainty can be represented as a differential equation that considers the outcomes of previous decisions for guiding the agent to an adaptive strategy. PMID:25566043

Stochastic model predicts evolving preferences in the Iowa gambling task.

PubMed

Fuentes, Miguel A; Lavín, Claudio; Contreras-Huerta, L Sebastián; Miguel, Hernan; Rosales Jubal, Eduardo

2014-01-01

Learning under uncertainty is a common task that people face in their daily life. This process relies on the cognitive ability to adjust behavior to environmental demands. Although the biological underpinnings of those cognitive processes have been extensively studied, there has been little work in formal models seeking to capture the fundamental dynamic of learning under uncertainty. In the present work, we aimed to understand the basic cognitive mechanisms of outcome processing involved in decisions under uncertainty and to evaluate the relevance of previous experiences in enhancing learning processes within such uncertain context. We propose a formal model that emulates the behavior of people playing a well established paradigm (Iowa Gambling Task - IGT) and compare its outcome with a behavioral experiment. We further explored whether it was possible to emulate maladaptive behavior observed in clinical samples by modifying the model parameter which controls the update of expected outcomes distributions. Results showed that the performance of the model resembles the observed participant performance as well as IGT performance by healthy subjects described in the literature. Interestingly, the model converges faster than some subjects on the decks with higher net expected outcome. Furthermore, the modified version of the model replicated the trend observed in clinical samples performing the task. We argue that the basic cognitive component underlying learning under uncertainty can be represented as a differential equation that considers the outcomes of previous decisions for guiding the agent to an adaptive strategy.

Advanced practice nursing role delineation in acute and critical care: application of the strong model of advanced practice.

PubMed

Mick, D J; Ackerman, M H

2000-01-01

This purpose of this study was to differentiate between the roles of clinical nurse specialists and acute care nurse practitioners. Hypothesized blending of the clinical nurse specialist and acute care nurse practitioner roles is thought to result in an acute care clinician who integrates the clinical skills of the nurse practitioner with the systems knowledge, educational commitment, and leadership ability of the clinical nurse specialist. Ideally, this role blending would facilitate excellence in both direct and indirect patient care. The Strong Model of Advanced Practice, which incorporates practice domains of direct comprehensive care, support of systems, education, research, and publication and professional leadership, was tested to search for practical evidence of role blending. This descriptive, exploratory, pilot study included subjects (N = 18) solicited from an academic medical center and from an Internet advanced practice listserv. Questionnaires included self-ranking of expertise in practice domains, as well as valuing of role-related tasks. Content validity was judged by an expert panel of advanced practice nurses. Analyses of descriptive statistics revealed that clinical nurse specialists, who had more experience both as registered nurses and in the advanced practice nurse role, self-ranked their expertise higher in all practice domains. Acute care nurse practitioners placed higher importance on tasks related to direct comprehensive care, including conducting histories and physicals, diagnosing, and performing diagnostic procedures, whereas clinical nurse specialists assigned greater importance to tasks related to education, research, and leadership. Levels of self-assessed clinical expertise as well as valuing of role-related tasks differed among this sample of clinical nurse specialists and acute care nurse practitioners. Groundwork has been laid for continuing exploration into differentiation in advanced practice nursing roles. As the clinical nurse specialist role changes and the acute care nurse practitioner role emerges, it is imperative that advanced practice nurses describe their contribution to health care. Associating advanced practice nursing activities with outcomes will help further characterize these 2 advanced practice roles.

A web-based data-querying tool based on ontology-driven methodology and flowchart-based model.

PubMed

Ping, Xiao-Ou; Chung, Yufang; Tseng, Yi-Ju; Liang, Ja-Der; Yang, Pei-Ming; Huang, Guan-Tarn; Lai, Feipei

2013-10-08

Because of the increased adoption rate of electronic medical record (EMR) systems, more health care records have been increasingly accumulating in clinical data repositories. Therefore, querying the data stored in these repositories is crucial for retrieving the knowledge from such large volumes of clinical data. The aim of this study is to develop a Web-based approach for enriching the capabilities of the data-querying system along the three following considerations: (1) the interface design used for query formulation, (2) the representation of query results, and (3) the models used for formulating query criteria. The Guideline Interchange Format version 3.5 (GLIF3.5), an ontology-driven clinical guideline representation language, was used for formulating the query tasks based on the GLIF3.5 flowchart in the Protégé environment. The flowchart-based data-querying model (FBDQM) query execution engine was developed and implemented for executing queries and presenting the results through a visual and graphical interface. To examine a broad variety of patient data, the clinical data generator was implemented to automatically generate the clinical data in the repository, and the generated data, thereby, were employed to evaluate the system. The accuracy and time performance of the system for three medical query tasks relevant to liver cancer were evaluated based on the clinical data generator in the experiments with varying numbers of patients. In this study, a prototype system was developed to test the feasibility of applying a methodology for building a query execution engine using FBDQMs by formulating query tasks using the existing GLIF. The FBDQM-based query execution engine was used to successfully retrieve the clinical data based on the query tasks formatted using the GLIF3.5 in the experiments with varying numbers of patients. The accuracy of the three queries (ie, "degree of liver damage," "degree of liver damage when applying a mutually exclusive setting," and "treatments for liver cancer") was 100% for all four experiments (10 patients, 100 patients, 1000 patients, and 10,000 patients). Among the three measured query phases, (1) structured query language operations, (2) criteria verification, and (3) other, the first two had the longest execution time. The ontology-driven FBDQM-based approach enriched the capabilities of the data-querying system. The adoption of the GLIF3.5 increased the potential for interoperability, shareability, and reusability of the query tasks.

Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case.

PubMed

Martínez-Costa, Catalina; Cornet, Ronald; Karlsson, Daniel; Schulz, Stefan; Kalra, Dipak

2015-05-01

To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information. Our approach is based on a semantic layer that consists of: (1) a set of ontologies supported by (2) a set of semantic patterns. The first aspect of the semantic layer helps standardize the clinical information modeling task and the second shields modelers from the complexity of ontology modeling. We applied this approach to heterogeneous representations of an excerpt of a heart failure summary. Using a set of finite top-level patterns to derive semantic patterns, we demonstrate that those patterns, or compositions thereof, can be used to represent information from clinical models. Homogeneous querying of the same or similar information, when represented according to heterogeneous clinical models, is feasible. Our approach focuses on the meaning embedded in EHRs, regardless of their structure. This complex task requires a clear ontological commitment (ie, agreement to consistently use the shared vocabulary within some context), together with formalization rules. These requirements are supported by semantic patterns. Other potential uses of this approach, such as clinical models validation, require further investigation. We show how an ontology-based representation of a clinical summary, guided by semantic patterns, allows homogeneous querying of heterogeneous information structures. Whether there are a finite number of top-level patterns is an open question. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Application development environment for advanced digital workstations

NASA Astrophysics Data System (ADS)

Valentino, Daniel J.; Harreld, Michael R.; Liu, Brent J.; Brown, Matthew S.; Huang, Lu J.

1998-06-01

One remaining barrier to the clinical acceptance of electronic imaging and information systems is the difficulty in providing intuitive access to the information needed for a specific clinical task (such as reaching a diagnosis or tracking clinical progress). The purpose of this research was to create a development environment that enables the design and implementation of advanced digital imaging workstations. We used formal data and process modeling to identify the diagnostic and quantitative data that radiologists use and the tasks that they typically perform to make clinical decisions. We studied a diverse range of radiology applications, including diagnostic neuroradiology in an academic medical center, pediatric radiology in a children's hospital, screening mammography in a breast cancer center, and thoracic radiology consultation for an oncology clinic. We used object- oriented analysis to develop software toolkits that enable a programmer to rapidly implement applications that closely match clinical tasks. The toolkits support browsing patient information, integrating patient images and reports, manipulating images, and making quantitative measurements on images. Collectively, we refer to these toolkits as the UCLA Digital ViewBox toolkit (ViewBox/Tk). We used the ViewBox/Tk to rapidly prototype and develop a number of diverse medical imaging applications. Our task-based toolkit approach enabled rapid and iterative prototyping of workstations that matched clinical tasks. The toolkit functionality and performance provided a 'hands-on' feeling for manipulating images, and for accessing textual information and reports. The toolkits directly support a new concept for protocol based-reading of diagnostic studies. The design supports the implementation of network-based application services (e.g., prefetching, workflow management, and post-processing) that will facilitate the development of future clinical applications.

Evaluating topic model interpretability from a primary care physician perspective.

PubMed

Arnold, Corey W; Oh, Andrea; Chen, Shawn; Speier, William

2016-02-01

Probabilistic topic models provide an unsupervised method for analyzing unstructured text. These models discover semantically coherent combinations of words (topics) that could be integrated in a clinical automatic summarization system for primary care physicians performing chart review. However, the human interpretability of topics discovered from clinical reports is unknown. Our objective is to assess the coherence of topics and their ability to represent the contents of clinical reports from a primary care physician's point of view. Three latent Dirichlet allocation models (50 topics, 100 topics, and 150 topics) were fit to a large collection of clinical reports. Topics were manually evaluated by primary care physicians and graduate students. Wilcoxon Signed-Rank Tests for Paired Samples were used to evaluate differences between different topic models, while differences in performance between students and primary care physicians (PCPs) were tested using Mann-Whitney U tests for each of the tasks. While the 150-topic model produced the best log likelihood, participants were most accurate at identifying words that did not belong in topics learned by the 100-topic model, suggesting that 100 topics provides better relative granularity of discovered semantic themes for the data set used in this study. Models were comparable in their ability to represent the contents of documents. Primary care physicians significantly outperformed students in both tasks. This work establishes a baseline of interpretability for topic models trained with clinical reports, and provides insights on the appropriateness of using topic models for informatics applications. Our results indicate that PCPs find discovered topics more coherent and representative of clinical reports relative to students, warranting further research into their use for automatic summarization. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluating Topic Model Interpretability from a Primary Care Physician Perspective

PubMed Central

Arnold, Corey W.; Oh, Andrea; Chen, Shawn; Speier, William

2015-01-01

Background and Objective Probabilistic topic models provide an unsupervised method for analyzing unstructured text. These models discover semantically coherent combinations of words (topics) that could be integrated in a clinical automatic summarization system for primary care physicians performing chart review. However, the human interpretability of topics discovered from clinical reports is unknown. Our objective is to assess the coherence of topics and their ability to represent the contents of clinical reports from a primary care physician’s point of view. Methods Three latent Dirichlet allocation models (50 topics, 100 topics, and 150 topics) were fit to a large collection of clinical reports. Topics were manually evaluated by primary care physicians and graduate students. Wilcoxon Signed-Rank Tests for Paired Samples were used to evaluate differences between different topic models, while differences in performance between students and primary care physicians (PCPs) were tested using Mann-Whitney U tests for each of the tasks. Results While the 150-topic model produced the best log likelihood, participants were most accurate at identifying words that did not belong in topics learned by the 100-topic model, suggesting that 100 topics provides better relative granularity of discovered semantic themes for the data set used in this study. Models were comparable in their ability to represent the contents of documents. Primary care physicians significantly outperformed students in both tasks. Conclusion This work establishes a baseline of interpretability for topic models trained with clinical reports, and provides insights on the appropriateness of using topic models for informatics applications. Our results indicate that PCPs find discovered topics more coherent and representative of clinical reports relative to students, warranting further research into their use for automatic summarization. PMID:26614020

Formal Derivation of Lotka-Volterra-Haken Amplitude Equations of Task-Related Brain Activity in Multiple, Consecutively Performed Tasks

NASA Astrophysics Data System (ADS)

Frank, T. D.

The Lotka-Volterra-Haken equations have been frequently used in ecology and pattern formation. Recently, the equations have been proposed by several research groups as amplitude equations for task-related patterns of brain activity. In this theoretical study, the focus is on the circular causality aspect of pattern formation systems as formulated within the framework of synergetics. Accordingly, the stable modes of a pattern formation system inhibit the unstable modes, whereas the unstable modes excite the stable modes. Using this circular causality principle it is shown that under certain conditions the Lotka-Volterra-Haken amplitude equations can be derived from a general model of brain activity akin to the Wilson-Cowan model. The model captures the amplitude dynamics for brain activity patterns in experiments involving several consecutively performed multiple-choice tasks. This is explicitly demonstrated for two-choice tasks involving grasping and walking. A comment on the relevance of the theoretical framework for clinical psychology and schizophrenia is given as well.

Choice Impulsivity: Definitions, Measurement Issues, and Clinical Implications

PubMed Central

Hamilton, Kristen R.; Mitchell, Marci R.; Wing, Victoria C.; Balodis, Iris M.; Bickel, Warren K.; Fillmore, Mark; Lane, Scott D.; Lejuez, C. W.; Littlefield, Andrew K.; Luijten, Maartje; Mathias, Charles W.; Mitchell, Suzanne H.; Napier, T. Celeste; Reynolds, Brady; Schütz, Christian G.; Setlow, Barry; Sher, Kenneth J.; Swann, Alan C.; Tedford, Stephanie E.; White, Melanie J.; Winstanley, Catharine A.; Yi, Richard; Potenza, Marc N.; Moeller, F. Gerard

2015-01-01

Background Impulsivity critically relates to many psychiatric disorders. Given the multi-faceted construct that impulsivity represents, defining core aspects of impulsivity is vital for the assessment and understanding of clinical conditions. Choice impulsivity (CI), involving the preferential selection of smaller sooner rewards over larger later rewards, represents one important type of impulsivity. Method The International Society for Research on Impulsivity (InSRI) convened to discuss the definition and assessment of CI and provide recommendations regarding measurement across species. Results Commonly used preclinical and clinical CI behavioral tasks are described, and considerations for each task are provided to guide CI task selection. Differences in assessment of CI (self-report, behavioral) and calculating CI indices (e.g., area-under-the-curve, indifference point, steepness of discounting curve) are discussed along with properties of specific behavioral tasks used in preclinical and clinical settings. Conclusions The InSRI group recommends inclusion of measures of CI in human studies examining impulsivity. Animal studies examining impulsivity should also include assessments of CI and these measures should be harmonized in accordance with human studies of the disorders being modeled in the preclinical investigations. The choice of specific CI measures to be included should be based on the goals of the study and existing preclinical and clinical literature using established CI measures. PMID:25867841

Situational theory of leadership.

PubMed

Waller, D J; Smith, S R; Warnock, J T

1989-11-01

The situational theory of leadership and the LEAD instruments for determining leadership style are explained, and the application of the situational leadership theory to the process of planning for and implementing organizational change is described. Early studies of leadership style identified two basic leadership styles: the task-oriented autocratic style and the relationship-oriented democratic style. Subsequent research found that most leaders exhibited one of four combinations of task and relationship behaviors. The situational leadership theory holds that the difference between the effectiveness and ineffectiveness of the four leadership styles is the appropriateness of the leader's behavior to the particular situation in which it is used. The task maturity of the individual or group being led must also be accounted for; follower readiness is defined in terms of the capacity to set high but attainable goals, willingness or ability to accept responsibility, and possession of the necessary education or experience for a specific task. A person's leadership style, range, and adaptability can be determined from the LEADSelf and LEADOther questionnaires. By applying the principles of the situational leadership theory and adapting their managerial styles to specific tasks and levels of follower maturity, the authors were successful in implementing 24-hour pharmacokinetic dosing services provided by staff pharmacists with little previous experience in clinical services. The situational leadership model enables a leader to identify a task, set goals, determine the task maturity of the individual or group, select an appropriate leadership style, and modify the style as change occurs. Pharmacy managers can use this model when implementing clinical pharmacy services.

Recommendations from the Investigational New Drug/Investigational Device Exemption Task Force of the clInical and Translational Science Award Consortium: developing and implementing a sponsor-investigators training program.

PubMed

Holbein, M E Blair; Berglund, Jelena Petrovic; O'Reilly, Erin K; Hartman, Karen; Speicher, Lisa A; Adamo, Joan E; O'Riordan, Gerri; Brown, Jennifer Swanton; Schuff, Kathryn G

2014-06-01

The objective of this study was to provide recommendations for provision of training for sponsor and investigators at Academic Health Centers. A subgroup of the Investigational New Drug/Investigational Device Exemption (IND/IDE) Task Force of the Clinical and Translational Science Award (CTSA) program Regulatory Knowledge Key Function Committee was assembled to specifically address how clinical investigators who hold an IND/IDE and thus assume the role of sponsor-investigators are adequately trained to meet the additional regulatory requirements of this role. The participants who developed the recommendations were representatives of institutions with IND/IDE support programs. Through an informal survey, the task force determined that a variety and mix of models are used to provide support for IND/IDE holders within CTSA institutions. In addition, a CTSA consortium-wide resources survey was used. The participants worked from the models and survey results to develop consensus recommendations to address institutional support, training content, and implementation. The CTSA IND/IDE Task Force recommendations are as follows: (1) Institutions should assess the scope of Food and Drug Administration-regulated research, perform a needs analysis, and provide resources to implement a suitable training program; (2) The model of training program should be tailored to each institution; (3) The training should specifically address the unique role of sponsor-investigators, and the effectiveness of training should be evaluated regularly by methods that fit the model adopted by the institution; and (4) Institutional leadership should mandate sponsor-investigator training and effectively communicate the necessity and availability of training.

Putative cognitive enhancers in preclinical models related to schizophrenia: the search for an elusive target.

PubMed

Barak, Segev; Weiner, Ina

2011-08-01

Several developments have converged to drive what may be called "the cognitive revolution" in drug discovery in schizophrenia (SCZ), including the emphasis on cognitive deficits as a core disabling aspect of SCZ, the increasing consensus that cognitive deficits are not treated satisfactorily by the available antipsychotic drugs (APDs), and the failure of animal models to predict drug efficacy for cognitive deficits in clinical trials. Consequently, in recent years, a paradigm shift has been encouraged in animal modeling, triggered by the NIMH sponsored Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative, and intended to promote the development and use of behavioral measures in animals that can generate valid (clinically relevant) measures of cognition and thus promote the identification of cognition enhancers for SCZ. Here, we provide a non-exhaustive survey of the effects of putative cognition enhancers (PCEs) representing 10 pharmacological targets as well as antipsychotic drugs (APDs), on SCZ-mimetic drugs (NMDA antagonists, muscarinic antagonist scopolamine and dopaminergic agonist amphetamine), in several tasks considered to measure cognitive processes/domains that are disrupted in SCZ (the five choice serial reaction time task, sustain attention task, working and/or recognition memory (delayed (non)matching to sample, delayed alternation task, radial arm maze, novel object recognition), reversal learning, attentional set shifting, latent inhibition and spatial learning and memory). We conclude that most of the available models have no capacity to distinguish between PCEs and APDs and that there is a need to establish models based on tasks whose perturbations lead to performance impairments that are resistant to APDs, and/or to accept APDs as a "weak gold standard". Several directions derived from the surveyed data are suggested. Copyright © 2011 Elsevier Inc. All rights reserved.

Fractional Brownian motion and long term clinical trial recruitment

PubMed Central

Zhang, Qiang; Lai, Dejian

2015-01-01

Prediction of recruitment in clinical trials has been a challenging task. Many methods have been studied, including models based on Poisson process and its large sample approximation by Brownian motion (BM), however, when the independent incremental structure is violated for BM model, we could use fractional Brownian motion to model and approximate the underlying Poisson processes with random rates. In this paper, fractional Brownian motion (FBM) is considered for such conditions and compared to BM model with illustrated examples from different trials and simulations. PMID:26347306

Fractional Brownian motion and long term clinical trial recruitment.

PubMed

Zhang, Qiang; Lai, Dejian

2011-05-01

Prediction of recruitment in clinical trials has been a challenging task. Many methods have been studied, including models based on Poisson process and its large sample approximation by Brownian motion (BM), however, when the independent incremental structure is violated for BM model, we could use fractional Brownian motion to model and approximate the underlying Poisson processes with random rates. In this paper, fractional Brownian motion (FBM) is considered for such conditions and compared to BM model with illustrated examples from different trials and simulations.

A new contribution to the classification of stressors affecting nursing professionals

PubMed Central

Puerto, Jesús Cremades; Soler, Loreto Maciá; Montesinos, Maria José López; Marcos, Azucena Pedraz; Chorda, Víctor Manuel González

2017-01-01

Objective: to identify and classify the most important occupational stressors affecting nursing professionals in the medical units within a hospital. Method: quantitative-qualitative, descriptive and prospective study performed with Delphi technique in the medical units of a general university hospital, with a sample of 30 nursing professionals. Results: the stressors were work overload, frequent interruptions in the accomplishment of their tasks, night working, simultaneity of performing different tasks, not having enough time to give emotional support to the patient or lack of time for some patients who need it, among others. Conclusion: the most consensual stressors were ranked as work overload, frequent interruptions in the accomplishment of their tasks, night working and, finally, simultaneity of performing different tasks. These results can be used as a tool in the clinical management of hospital units, aiming to improve the quality of life of nursing professionals, organizational models and, in addition, continuous improvement in clinical treatment. PMID:28562702

A Web-Based Data-Querying Tool Based on Ontology-Driven Methodology and Flowchart-Based Model

PubMed Central

Ping, Xiao-Ou; Chung, Yufang; Liang, Ja-Der; Yang, Pei-Ming; Huang, Guan-Tarn; Lai, Feipei

2013-01-01

Background Because of the increased adoption rate of electronic medical record (EMR) systems, more health care records have been increasingly accumulating in clinical data repositories. Therefore, querying the data stored in these repositories is crucial for retrieving the knowledge from such large volumes of clinical data. Objective The aim of this study is to develop a Web-based approach for enriching the capabilities of the data-querying system along the three following considerations: (1) the interface design used for query formulation, (2) the representation of query results, and (3) the models used for formulating query criteria. Methods The Guideline Interchange Format version 3.5 (GLIF3.5), an ontology-driven clinical guideline representation language, was used for formulating the query tasks based on the GLIF3.5 flowchart in the Protégé environment. The flowchart-based data-querying model (FBDQM) query execution engine was developed and implemented for executing queries and presenting the results through a visual and graphical interface. To examine a broad variety of patient data, the clinical data generator was implemented to automatically generate the clinical data in the repository, and the generated data, thereby, were employed to evaluate the system. The accuracy and time performance of the system for three medical query tasks relevant to liver cancer were evaluated based on the clinical data generator in the experiments with varying numbers of patients. Results In this study, a prototype system was developed to test the feasibility of applying a methodology for building a query execution engine using FBDQMs by formulating query tasks using the existing GLIF. The FBDQM-based query execution engine was used to successfully retrieve the clinical data based on the query tasks formatted using the GLIF3.5 in the experiments with varying numbers of patients. The accuracy of the three queries (ie, “degree of liver damage,” “degree of liver damage when applying a mutually exclusive setting,” and “treatments for liver cancer”) was 100% for all four experiments (10 patients, 100 patients, 1000 patients, and 10,000 patients). Among the three measured query phases, (1) structured query language operations, (2) criteria verification, and (3) other, the first two had the longest execution time. Conclusions The ontology-driven FBDQM-based approach enriched the capabilities of the data-querying system. The adoption of the GLIF3.5 increased the potential for interoperability, shareability, and reusability of the query tasks. PMID:25600078

Speech and nonspeech: What are we talking about?

PubMed

Maas, Edwin

2017-08-01

Understanding of the behavioural, cognitive and neural underpinnings of speech production is of interest theoretically, and is important for understanding disorders of speech production and how to assess and treat such disorders in the clinic. This paper addresses two claims about the neuromotor control of speech production: (1) speech is subserved by a distinct, specialised motor control system and (2) speech is holistic and cannot be decomposed into smaller primitives. Both claims have gained traction in recent literature, and are central to a task-dependent model of speech motor control. The purpose of this paper is to stimulate thinking about speech production, its disorders and the clinical implications of these claims. The paper poses several conceptual and empirical challenges for these claims - including the critical importance of defining speech. The emerging conclusion is that a task-dependent model is called into question as its two central claims are founded on ill-defined and inconsistently applied concepts. The paper concludes with discussion of methodological and clinical implications, including the potential utility of diadochokinetic (DDK) tasks in assessment of motor speech disorders and the contraindication of nonspeech oral motor exercises to improve speech function.

Evaluation of Clinically Relevant Prognostic Indicators in a Model of Mild TBI/Concussion

DTIC Science & Technology

2017-10-01

memory task at either 1 month or 3 months following PCI (Fig. 8). Experiment 1.2.3 Anxiety and Motivation : Anxiety behavior was assessed...The Morris water maze task will be used to assess memory dysfunction at 1 and 3 months following injury. Experiment 2.2.3 Anxiety and Motivation ...The elevated plus maze task will be utilized to evaluate anxiety and motivation at 1, 3, and 6 months post injury. Experiment 2.2.4 Correlation

Using task analysis to improve the requirements elicitation in health information system.

PubMed

Teixeira, Leonor; Ferreira, Carlos; Santos, Beatriz Sousa

2007-01-01

This paper describes the application of task analysis within the design process of a Web-based information system for managing clinical information in hemophilia care, in order to improve the requirements elicitation and, consequently, to validate the domain model obtained in a previous phase of the design process (system analysis). The use of task analysis in this case proved to be a practical and efficient way to improve the requirements engineering process by involving users in the design process.

Psychodynamic group psychotherapy: impact of group length and therapist professional characteristics on development of therapeutic alliance.

PubMed

Lorentzen, Steinar; Bakali, Jan Vegard; Hersoug, Anne Grete; Hagtvet, Knut A; Ruud, Torleif; Høglend, Per

2012-09-01

Little research has been done on therapeutic alliance in group psychotherapy, especially the impact of treatment duration and therapist professional characteristics. Therapeutic alliance was rated by patients on the Working Alliance Inventory-Short Form at three time points (sessions 3, 10 and 17) in a randomized controlled trial of short-term and long-term psychodynamic group psychotherapy. As predictors we selected therapist clinical experience and length of didactic training, which have demonstrated ambiguous results in previous research. Linear latent variable growth curve models (structural equation modeling) were developed for the three Working Alliance Inventory-Short Form subscales bond, task and goal. We found a significant variance in individual growth curves (intercepts and slopes) but no differential development due to group length. Longer therapist formal training had a negative impact on early values of subscale task in both treatments. There was an interaction between length of the therapists' clinical experience and group length on early bond, task and goal: therapists with longer clinical experience were rated lower on initial bond in the long-term group but less so in the short-term group. Longer clinical experience influenced initial task and goal positively in the short-term group but was unimportant for task or significantly negative for goal in the long-term group. There was no mean development of alliance, and group length did not differentially impact the alliance during 6 months. Early ratings of the three Working Alliance Inventory-Short Form subscales partly reflected different preparations of patients in the two group formats, partly therapist characteristics, but more research is needed to see how these aspects impact alliance development and outcome. Therapists should pay attention to all three aspects of the alliance, when they prepare patients for group therapy. In psychodynamic groups, length of therapy does not differentiate the overall level or the development of member-leader alliance. Within psychodynamic groups, each individual appear to have their unique perception of the member-leader alliance. Therapists with longer formal psychotherapy training may be less successful in establishing early agreement with patients on the tasks of psychodynamic group psychotherapy. Patients perceive a somewhat lower degree of early emotional bonding with the more clinically experienced therapists in long-term psychodynamics groups. Therapists with more clinical experience may contribute to a stronger degree of initial agreement with patients on the tasks and goals of short-term group psychotherapy. Copyright © 2011 John Wiley & Sons, Ltd.

Activities of daily living measured by the Harvard Automated Phone Task track with cognitive decline over time in non-demented elderly.

PubMed

Marshall, Gad A; Aghjayan, Sarah L; Dekhtyar, Maria; Locascio, Joseph J; Jethwani, Kamal; Amariglio, Rebecca E; Johnson, Keith A; Sperling, Reisa A; Rentz, Dorene M

2017-01-01

Impairment in activities of daily living is a major burden to both patients and caregivers. Mild impairment in instrumental activities of daily living is often seen at the stage of mild cognitive impairment. The field of Alzheimer's disease is moving toward earlier diagnosis and intervention and more sensitive and ecologically valid assessments of instrumental or complex activities of daily living are needed. The Harvard Automated Phone Task, a novel performance-based activities of daily living instrument, has the potential to fill this gap. To further validate the Harvard Automated Phone Task by assessing its longitudinal relationship to global cognition and specific cognitive domains in clinically normal elderly and individuals with mild cognitive impairment. In a longitudinal study, the Harvard Automated Phone Task was associated with cognitive measures using mixed effects models. The Harvard Automated Phone Task's ability to discriminate across diagnostic groups at baseline was also assessed. Academic clinical research center. Two hundred and seven participants (45 young normal, 141 clinically normal elderly, and 21 mild cognitive impairment) were recruited from the community and the memory disorders clinics at Brigham and Women's Hospital and Massachusetts General Hospital. Participants performed the three tasks of the Harvard Automated Phone Task, which consist of navigating an interactive voice response system to refill a prescription (APT-Script), select a new primary care physician (APT-PCP), and make a bank account transfer and payment (APT-Bank). The 3 tasks were scored based on time, errors, repetitions, and correct completion of the task. The primary outcome measure used for each of the tasks was total time adjusted for correct completion. The Harvard Automated Phone Task discriminated well between young normal, clinically normal elderly, and mild cognitive impairment participants (APT-Script: p<0.001; APT-PCP: p<0.001; APT-Bank: p=0.04). Worse baseline Harvard Automated Phone Task performance or worsening Harvard Automated Phone Task performance over time tracked with overall worse performance or worsening performance over time in global cognition, processing speed, executive function, and episodic memory. Prior cross-sectional and current longitudinal analyses have demonstrated the utility of the Harvard Automated Phone Task, a new performance-based activities of daily living instrument, in the assessment of early changes in complex activities of daily living in non-demented elderly at risk for Alzheimer's disease. Future studies will focus on cross-validation with other sensitive activities of daily living tests and Alzheimer's disease biomarkers.

Resting-State Functional Magnetic Resonance Imaging for Language Preoperative Planning

PubMed Central

Branco, Paulo; Seixas, Daniela; Deprez, Sabine; Kovacs, Silvia; Peeters, Ronald; Castro, São L.; Sunaert, Stefan

2016-01-01

Functional magnetic resonance imaging (fMRI) is a well-known non-invasive technique for the study of brain function. One of its most common clinical applications is preoperative language mapping, essential for the preservation of function in neurosurgical patients. Typically, fMRI is used to track task-related activity, but poor task performance and movement artifacts can be critical limitations in clinical settings. Recent advances in resting-state protocols open new possibilities for pre-surgical mapping of language potentially overcoming these limitations. To test the feasibility of using resting-state fMRI instead of conventional active task-based protocols, we compared results from fifteen patients with brain lesions while performing a verb-to-noun generation task and while at rest. Task-activity was measured using a general linear model analysis and independent component analysis (ICA). Resting-state networks were extracted using ICA and further classified in two ways: manually by an expert and by using an automated template matching procedure. The results revealed that the automated classification procedure correctly identified language networks as compared to the expert manual classification. We found a good overlay between task-related activity and resting-state language maps, particularly within the language regions of interest. Furthermore, resting-state language maps were as sensitive as task-related maps, and had higher specificity. Our findings suggest that resting-state protocols may be suitable to map language networks in a quick and clinically efficient way. PMID:26869899

Preclinical endoscopic training using a part-task simulator: learning curve assessment and determination of threshold score for advancement to clinical endoscopy.

PubMed

Jirapinyo, Pichamol; Abidi, Wasif M; Aihara, Hiroyuki; Zaki, Theodore; Tsay, Cynthia; Imaeda, Avlin B; Thompson, Christopher C

2017-10-01

Preclinical simulator training has the potential to decrease endoscopic procedure time and patient discomfort. This study aims to characterize the learning curve of endoscopic novices in a part-task simulator and propose a threshold score for advancement to initial clinical cases. Twenty novices with no prior endoscopic experience underwent repeated endoscopic simulator sessions using the part-task simulator. Simulator scores were collected; their inverse was averaged and fit to an exponential curve. The incremental improvement after each session was calculated. Plateau was defined as the session after which incremental improvement in simulator score model was less than 5%. Additionally, all participants filled out questionnaires regarding simulator experience after sessions 1, 5, 10, 15, and 20. A visual analog scale and NASA task load index were used to assess levels of comfort and demand. Twenty novices underwent 400 simulator sessions. Mean simulator scores at sessions 1, 5, 10, 15, and 20 were 78.5 ± 5.95, 176.5 ± 17.7, 275.55 ± 23.56, 347 ± 26.49, and 441.11 ± 38.14. The best fit exponential model was [time/score] = 26.1 × [session #] -0.615 ; r 2  = 0.99. This corresponded to an incremental improvement in score of 35% after the first session, 22% after the second, 16% after the third and so on. Incremental improvement dropped below 5% after the 12th session corresponding to the predicted score of 265. Simulator training was related to higher comfort maneuvering an endoscope and increased readiness for supervised clinical endoscopy, both plateauing between sessions 10 and 15. Mental demand, physical demand, and frustration levels decreased with increased simulator training. Preclinical training using an endoscopic part-task simulator appears to increase comfort level and decrease mental and physical demand associated with endoscopy. Based on a rigorous model, we recommend that novices complete a minimum of 12 training sessions and obtain a simulator score of at least 265 to be best prepared for clinical endoscopy.

Activities of daily living measured by the Harvard Automated Phone Task track with cognitive decline over time in non-demented elderly

PubMed Central

Marshall, Gad A.; Aghjayan, Sarah L.; Dekhtyar, Maria; Locascio, Joseph J.; Jethwani, Kamal; Amariglio, Rebecca E.; Johnson, Keith A.; Sperling, Reisa A.; Rentz, Dorene M.

2017-01-01

Background Impairment in activities of daily living is a major burden to both patients and caregivers. Mild impairment in instrumental activities of daily living is often seen at the stage of mild cognitive impairment. The field of Alzheimer’s disease is moving toward earlier diagnosis and intervention and more sensitive and ecologically valid assessments of instrumental or complex activities of daily living are needed. The Harvard Automated Phone Task, a novel performance-based activities of daily living instrument, has the potential to fill this gap. Objective To further validate the Harvard Automated Phone Task by assessing its longitudinal relationship to global cognition and specific cognitive domains in clinically normal elderly and individuals with mild cognitive impairment. Design In a longitudinal study, the Harvard Automated Phone Task was associated with cognitive measures using mixed effects models. The Harvard Automated Phone Task’s ability to discriminate across diagnostic groups at baseline was also assessed. Setting Academic clinical research center. Participants Two hundred and seven participants (45 young normal, 141 clinically normal elderly, and 21 mild cognitive impairment) were recruited from the community and the memory disorders clinics at Brigham and Women’s Hospital and Massachusetts General Hospital. Measurements Participants performed the three tasks of the Harvard Automated Phone Task, which consist of navigating an interactive voice response system to refill a prescription (APT-Script), select a new primary care physician (APT-PCP), and make a bank account transfer and payment (APT-Bank). The 3 tasks were scored based on time, errors, repetitions, and correct completion of the task. The primary outcome measure used for each of the tasks was total time adjusted for correct completion. Results The Harvard Automated Phone Task discriminated well between young normal, clinically normal elderly, and mild cognitive impairment participants (APT-Script: p<0.001; APT-PCP: p<0.001; APT-Bank: p=0.04). Worse baseline Harvard Automated Phone Task performance or worsening Harvard Automated Phone Task performance over time tracked with overall worse performance or worsening performance over time in global cognition, processing speed, executive function, and episodic memory. Conclusions Prior cross-sectional and current longitudinal analyses have demonstrated the utility of the Harvard Automated Phone Task, a new performance-based activities of daily living instrument, in the assessment of early changes in complex activities of daily living in non-demented elderly at risk for Alzheimer’s disease. Future studies will focus on cross-validation with other sensitive activities of daily living tests and Alzheimer’s disease biomarkers. PMID:29124043

Clinical Reasoning Tasks and Resident Physicians: What Do They Reason About?

PubMed

McBee, Elexis; Ratcliffe, Temple; Goldszmidt, Mark; Schuwirth, Lambert; Picho, Katherine; Artino, Anthony R; Masel, Jennifer; Durning, Steven J

2016-07-01

A framework of clinical reasoning tasks thought to occur in a clinical encounter was recently developed. It proposes that diagnostic and therapeutic reasoning comprise 24 tasks. The authors of this current study used this framework to investigate what internal medicine residents reason about when they approach straightforward clinical cases. Participants viewed three video-recorded clinical encounters portraying common diagnoses. After each video, participants completed a post encounter form and think-aloud protocol. Two authors analyzed transcripts from the think-aloud protocols using a constant comparative approach. They conducted iterative coding of the utterances, classifying each according to the framework of clinical reasoning tasks. They evaluated the type, number, and sequence of tasks the residents used. Ten residents participated in the study in 2013-2014. Across all three cases, the residents employed 14 clinical reasoning tasks. Nearly all coded tasks were associated with framing the encounter or diagnosis. The order in which residents used specific tasks varied. The average number of tasks used per case was as follows: Case 1, 4.4 (range 1-10); Case 2, 4.6 (range 1-6); and Case 3, 4.7 (range 1-7). The residents used some tasks repeatedly; the average number of task utterances was 11.6, 13.2, and 14.7 for, respectively, Case 1, 2, and 3. Results suggest that the use of clinical reasoning tasks occurs in a varied, not sequential, process. The authors provide suggestions for strengthening the framework to more fully encompass the spectrum of reasoning tasks that occur in residents' clinical encounters.

Non-Categorical Preschool Model Program.

ERIC Educational Resources Information Center

Bolen, Jacqueline M.; And Others

Special education teachers at the graduate level developed a model noncategorical preschool program for five normal or severely handicapped children which incorporated parent training and behavioral research. The staff assumed such tasks as designing classroom/clinic/observation areas, arranging for materials, training parents, and attending…

The effect of improving task representativeness on capturing nurses’ risk assessment judgements: a comparison of written case simulations and physical simulations

PubMed Central

2013-01-01

Background The validity of studies describing clinicians’ judgements based on their responses to paper cases is questionable, because - commonly used - paper case simulations only partly reflect real clinical environments. In this study we test whether paper case simulations evoke similar risk assessment judgements to the more realistic simulated patients used in high fidelity physical simulations. Methods 97 nurses (34 experienced nurses and 63 student nurses) made dichotomous assessments of risk of acute deterioration on the same 25 simulated scenarios in both paper case and physical simulation settings. Scenarios were generated from real patient cases. Measures of judgement ‘ecology’ were derived from the same case records. The relationship between nurses’ judgements, actual patient outcomes (i.e. ecological criteria), and patient characteristics were described using the methodology of judgement analysis. Logistic regression models were constructed to calculate Lens Model Equation parameters. Parameters were then compared between the modeled paper-case and physical-simulation judgements. Results Participants had significantly less achievement (ra) judging physical simulations than when judging paper cases. They used less modelable knowledge (G) with physical simulations than with paper cases, while retaining similar cognitive control and consistency on repeated patients. Respiration rate, the most important cue for predicting patient risk in the ecological model, was weighted most heavily by participants. Conclusions To the extent that accuracy in judgement analysis studies is a function of task representativeness, improving task representativeness via high fidelity physical simulations resulted in lower judgement performance in risk assessments amongst nurses when compared to paper case simulations. Lens Model statistics could prove useful when comparing different options for the design of simulations used in clinical judgement analysis. The approach outlined may be of value to those designing and evaluating clinical simulations as part of education and training strategies aimed at improving clinical judgement and reasoning. PMID:23718556

Optimizing spectral CT parameters for material classification tasks

NASA Astrophysics Data System (ADS)

Rigie, D. S.; La Rivière, P. J.

2016-06-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.

Optimizing Spectral CT Parameters for Material Classification Tasks

PubMed Central

Rigie, D. S.; La Rivière, P. J.

2017-01-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies. PMID:27227430

Intraoperative Noise Increases Perceived Task Load and Fatigue in Anesthesiology Residents: A Simulation-Based Study.

PubMed

McNeer, Richard R; Bennett, Christopher L; Dudaryk, Roman

2016-02-01

Operating rooms are identified as being one of the noisiest of clinical environments, and intraoperative noise is associated with adverse effects on staff and patient safety. Simulation-based experiments would offer controllable and safe venues for investigating this noise problem. However, realistic simulation of the clinical auditory environment is rare in current simulators. Therefore, we retrofitted our operating room simulator to be able to produce immersive auditory simulations with the use of typical sound sources encountered during surgeries. Then, we tested the hypothesis that anesthesia residents would perceive greater task load and fatigue while being given simulated lunch breaks in noisy environments rather than in quiet ones. As a secondary objective, we proposed and tested the plausibility of a novel psychometric instrument for the assessment of stress. In this simulation-based, randomized, repeated-measures, crossover study, 2 validated psychometric survey instruments, the NASA Task Load Index (NASA-TLX), composed of 6 items, and the Swedish Occupational Fatigue Inventory (SOFI), composed of 5 items, were used to assess perceived task load and fatigue, respectively, in first-year anesthesia residents. Residents completed the psychometric instruments after being given lunch breaks in quiet and noisy intraoperative environments (soundscapes). The effects of soundscape grouping on the psychometric instruments and their comprising items were analyzed with a split-plot analysis. A model for a new psychometric instrument for measuring stress that combines the NASA-TLX and SOFI instruments was proposed, and a factor analysis was performed on the collected data to determine the model's plausibility. Twenty residents participated in this study. Multivariate analysis of variance showed an effect of soundscape grouping on the combined NASA-TLX and SOFI instrument items (P = 0.003) and the comparisons of univariate item reached significance for the NASA Temporal Demand item (P = 0.0004) and the SOFI Lack of Energy item (P = 0.001). Factor analysis extracted 4 factors, which were assigned the following construct names for model development: Psychological Task Load, Psychological Fatigue, Acute Physical Load, and Performance-Chronic Physical Load. Six of the 7 fit tests used in the partial confirmatory factor analysis were positive when we fitted the data to the proposed model, suggesting that further validation is warranted. This study provides evidence that noise during surgery can increase feelings of stress, as measured by perceived task load and fatigue levels, in anesthesiologists and adds to the growing literature pointing to an overall adverse impact of clinical noise on caregivers and patient safety. The psychometric model proposed in this study for assessing perceived stress is plausible based on factor analysis and will be useful for characterizing the impact of the clinical environment on subject stress levels in future investigations.

PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models.

PubMed

Glueck, Michael; Naeini, Mahdi Pakdaman; Doshi-Velez, Finale; Chevalier, Fanny; Khan, Azam; Wigdor, Daniel; Brudno, Michael

2018-01-01

PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes-each with its own temporally evolving prevalence and co-occurrence of phenotypes-without requiring aligned longitudinal phenotype data for all patients. However, the dimensionality of topic models makes interpretation challenging, and de facto analyses provide little intuition regarding phenotype relevance or phenotype interrelationships. PhenoLines enables one to compare phenotype prevalence within and across disease subtype topics, thus supporting subtype characterization, a task that involves identifying a proposed subtype's dominant phenotypes, ages of effect, and clinical validity. We contribute a data transformation workflow that employs the Human Phenotype Ontology to hierarchically organize phenotypes and aggregate the evolving probabilities produced by topic models. We introduce a novel measure of phenotype relevance that can be used to simplify the resulting topology. The design of PhenoLines was motivated by formative interviews with machine learning and clinical experts. We describe the collaborative design process, distill high-level tasks, and report on initial evaluations with machine learning experts and a medical domain expert. These results suggest that PhenoLines demonstrates promising approaches to support the characterization and optimization of topic models.

Embedded performance validity testing in neuropsychological assessment: Potential clinical tools.

PubMed

Rickards, Tyler A; Cranston, Christopher C; Touradji, Pegah; Bechtold, Kathleen T

2018-01-01

The article aims to suggest clinically-useful tools in neuropsychological assessment for efficient use of embedded measures of performance validity. To accomplish this, we integrated available validity-related and statistical research from the literature, consensus statements, and survey-based data from practicing neuropsychologists. We provide recommendations for use of 1) Cutoffs for embedded performance validity tests including Reliable Digit Span, California Verbal Learning Test (Second Edition) Forced Choice Recognition, Rey-Osterrieth Complex Figure Test Combination Score, Wisconsin Card Sorting Test Failure to Maintain Set, and the Finger Tapping Test; 2) Selecting number of performance validity measures to administer in an assessment; and 3) Hypothetical clinical decision-making models for use of performance validity testing in a neuropsychological assessment collectively considering behavior, patient reporting, and data indicating invalid or noncredible performance. Performance validity testing helps inform the clinician about an individual's general approach to tasks: response to failure, task engagement and persistence, compliance with task demands. Data-driven clinical suggestions provide a resource to clinicians and to instigate conversation within the field to make more uniform, testable decisions to further the discussion, and guide future research in this area.

Impact of number of repeated scans on model observer performance for a low-contrast detection task in computed tomography.

PubMed

Ma, Chi; Yu, Lifeng; Chen, Baiyu; Favazza, Christopher; Leng, Shuai; McCollough, Cynthia

2016-04-01

Channelized Hotelling observer (CHO) models have been shown to correlate well with human observers for several phantom-based detection/classification tasks in clinical computed tomography (CT). A large number of repeated scans were used to achieve an accurate estimate of the model's template. The purpose of this study is to investigate how the experimental and CHO model parameters affect the minimum required number of repeated scans. A phantom containing 21 low-contrast objects was scanned on a 128-slice CT scanner at three dose levels. Each scan was repeated 100 times. For each experimental configuration, the low-contrast detectability, quantified as the area under receiver operating characteristic curve, [Formula: see text], was calculated using a previously validated CHO with randomly selected subsets of scans, ranging from 10 to 100. Using [Formula: see text] from the 100 scans as the reference, the accuracy from a smaller number of scans was determined. Our results demonstrated that the minimum number of repeated scans increased when the radiation dose level decreased, object size and contrast level decreased, and the number of channels increased. As a general trend, it increased as the low-contrast detectability decreased. This study provides a basis for the experimental design of task-based image quality assessment in clinical CT using CHO.

Security from Within: Independent Review of the Washington Navy Yard Shooting

DTIC Science & Technology

2013-11-01

2012 report, the Defense Science Board (DSB) Task Force reviewing the Fort Hood shooting recommended “a threat management approach employing...mental health research findings into clinical practice. 103 The field of implementation science offers several models for establishing and supporting...December 29, 2008, http://www.dhs.gov/xlibrary/assets/privacy/privacy_policyguide_2008-01.pdf. 47 Defense Science Board. “Task Force Report

A neurocomputational account of cognitive deficits in Parkinson’s disease

PubMed Central

Hélie, Sébastien; Paul, Erick J.; Ashby, F. Gregory

2014-01-01

Parkinson’s disease (PD) is caused by the accelerated death of dopamine (DA) producing neurons. Numerous studies documenting cognitive deficits of PD patients have revealed impairments in a variety of tasks related to memory, learning, visuospatial skills, and attention. While there have been several studies documenting cognitive deficits of PD patients, very few computational models have been proposed. In this article, we use the COVIS model of category learning to simulate DA depletion and show that the model suffers from cognitive symptoms similar to those of human participants affected by PD. Specifically, DA depletion in COVIS produced deficits in rule-based categorization, non-linear information-integration categorization, probabilistic classification, rule maintenance, and rule switching. These were observed by simulating results from younger controls, older controls, PD patients, and severe PD patients in five well-known tasks. Differential performance among the different age groups and clinical populations was modeled simply by changing the amount of DA available in the model. This suggests that COVIS may not only be an adequate model of the simulated tasks and phenomena but also more generally of the role of DA in these tasks and phenomena. PMID:22683450

Implementing Sustainable Data Collection for a Cardiac Outcomes Registry in an Australian Public Hospital.

PubMed

Cox, Nicholas; Brennan, Angela; Dinh, Diem; Brien, Rita; Cowie, Kath; Stub, Dion; Reid, Christopher M; Lefkovits, Jeffrey

2018-04-01

Clinical outcome registries are an increasingly vital component of ensuring quality and safety of patient care. However, Australian hospitals rarely have additional resources or the capacity to fund the additional staff time to complete the task of data collection and entry. At the same time, registry funding models do not support staff for the collection of data at the site but are directed towards the central registry tasks of data reporting, managing and quality monitoring. The sustainability of a registry is contingent on building efficiencies into data management and collection. We describe the methods used in a large Victorian public hospital to develop a sustainable data collection system for the Victorian Cardiac Outcomes Registry (VCOR), using existing staff and resources common to many public hospitals. We describe the features of the registry and the hospital specific strategies that allowed us to do this as part of our routine business of providing good quality cardiac care. All clinical staff involved in patient care were given some data collection task with the entry of these data embedded into the staff's daily workflow. A senior cardiology registrar was empowered to allocate data entry tasks to colleagues when data were found to be incomplete. The task of 30-day follow-up proved the most onerous part of data collection. Cath-lab nursing staff were allocated this role. With hospital accreditation and funding models moving towards performance based quality indicators, collection of accurate and reliable information is crucial. Our experience demonstrates the successful implementation of clinical outcome registry data collection in a financially constrained public hospital environment utilising existing resources. Copyright © 2017. Published by Elsevier B.V.

Developing a unified list of physicians' reasoning tasks during clinical encounters.

PubMed

Goldszmidt, Mark; Minda, John Paul; Bordage, Georges

2013-03-01

The clinical reasoning literature focuses on how physicians reason while making decisions, rather than on what they reason about while performing their clinical tasks. In an attempt to provide a common language for discussing, teaching, and researching clinical reasoning, the authors undertook the task of developing a unified list of physicians' reasoning tasks, or what they reason about, during clinical encounters. The authors compiled an initial list of 20 reasoning tasks based on the literature from four content areas--clinical reasoning, communications, medical errors, and clinical guidelines. In the summer and fall of 2010, they surveyed a purposive sample of 46 international experts in clinical reasoning and communications. From the results of the first survey, the authors refined their list of reasoning tasks, then resurveyed 22 of the original participants. From the results of the second survey, they further refined their list and validated the inclusion of the reasoning tasks. Twenty-four of 46 (52%) and 15 of 22 (65%) participants completed the first- and second-round surveys, respectively. Following the second-round survey, the authors' list included 24 reasoning tasks, and a clinical example corresponding to each, that fell into four broad categories: framing the encounter (3), diagnosis (8), management (11), and self-reflection (2). The development of this unified list represents a first step in offering a vocabulary for discussing, reflecting on, teaching, and studying physicians' reasoning tasks during clinical encounters.

Conveying Clinical Reasoning Based on Visual Observation via Eye-Movement Modelling Examples

ERIC Educational Resources Information Center

Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nystrom, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit

2012-01-01

Complex perceptual tasks, like clinical reasoning based on visual observations of patients, require not only conceptual knowledge about diagnostic classes but also the skills to visually search for symptoms and interpret these observations. However, medical education so far has focused very little on how visual observation skills can be…

Time savings--realized and potential--and fair compensation for community health workers in Kenyan health facilities: a mixed-methods approach.

PubMed

Sander, Laura D; Holtzman, David; Pauly, Mark; Cohn, Jennifer

2015-01-30

Sub-Saharan Africa faces a severe health worker shortage, which community health workers (CHWs) may fill. This study describes tasks shifted from clinicians to CHWs in Kenya, places monetary valuations on CHWs' efforts, and models effects of further task shifting on time demands of clinicians and CHWs. Mixed methods were used for this study. Interviews were conducted with 28 CHWs and 19 clinicians in 17 health facilities throughout Kenya focusing on task shifting involving CHWs, time savings for clinicians as a result of task shifting, barriers and enabling factors to CHWs' work, and appropriate CHW compensation. Twenty CHWs completed task diaries over a 14-day period to examine current CHW tasks and the amount of time spent performing them. A modeling exercise was conducted examining a current task-shifting example and another scenario in which additional task shifting to CHWs has occurred. CHWs worked an average of 5.3 hours per day and spent 36% of their time performing tasks shifted from clinicians. We estimated a monthly valuation of US$ 117 per CHW. The modeling exercise demonstrated that further task shifting would reduce the number of clinicians needed while maintaining clinic productivity by significantly increasing the number of CHWs. CHWs are an important component of healthcare delivery in Kenya. Our monetary estimates of current CHW contributions provide starting points for further discussion, research and planning regarding CHW compensation and programs. Additional task shifting to CHWs may further offload overworked clinicians while maintaining overall productivity.

Speculation detection for Chinese clinical notes: Impacts of word segmentation and embedding models.

PubMed

Zhang, Shaodian; Kang, Tian; Zhang, Xingting; Wen, Dong; Elhadad, Noémie; Lei, Jianbo

2016-04-01

Speculations represent uncertainty toward certain facts. In clinical texts, identifying speculations is a critical step of natural language processing (NLP). While it is a nontrivial task in many languages, detecting speculations in Chinese clinical notes can be particularly challenging because word segmentation may be necessary as an upstream operation. The objective of this paper is to construct a state-of-the-art speculation detection system for Chinese clinical notes and to investigate whether embedding features and word segmentations are worth exploiting toward this overall task. We propose a sequence labeling based system for speculation detection, which relies on features from bag of characters, bag of words, character embedding, and word embedding. We experiment on a novel dataset of 36,828 clinical notes with 5103 gold-standard speculation annotations on 2000 notes, and compare the systems in which word embeddings are calculated based on word segmentations given by general and by domain specific segmenters respectively. Our systems are able to reach performance as high as 92.2% measured by F score. We demonstrate that word segmentation is critical to produce high quality word embedding to facilitate downstream information extraction applications, and suggest that a domain dependent word segmenter can be vital to such a clinical NLP task in Chinese language. Copyright © 2016 Elsevier Inc. All rights reserved.

Characterizing attention with predictive network models

PubMed Central

Rosenberg, M. D.; Finn, E. S.; Scheinost, D.; Constable, R. T.; Chun, M. M.

2017-01-01

Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals’ attentional abilities. Some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that (1) attention is a network property of brain computation, (2) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task, and (3) this architecture supports a general attentional ability common to several lab-based tasks and impaired in attention deficit hyperactivity disorder. Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. PMID:28238605

Decomposing mechanisms of abnormal saccade generation in schizophrenia patients: Contributions of volitional initiation, motor preparation, and fixation release.

PubMed

Reuter, Benedikt; Elsner, Björn; Möllers, David; Kathmann, Norbert

2016-11-01

Clinical and theoretical models suggest deficient volitional initiation of action in schizophrenia patients. Recent research provided an experimental model of testing this assumption using saccade tasks. However, inconsistent findings necessitate a specification of conditions on which the deficit may occur. The present study sought to detect mechanisms that may contribute to poor performance. Sixteen schizophrenia patients and 16 healthy control participants performed visually guided and two types of volitional saccade tasks. All tasks varied as to whether the initial fixation stimulus disappeared (fixation stimulus offset) or continued during saccade initiation, and whether a direction cue allowed motor preparation of the specific saccade. Saccade latencies of the two groups were differentially affected by task type, fixation stimulus offset, and cueing, suggesting abnormal volitional saccade generation, fixation release, and motor preparation in schizophrenia. However, substantial performance deficits may only occur if all affected processes are required in a task. © 2016 Society for Psychophysiological Research.

A Holistic Model for Wellness and Prevention over the Life Span.

ERIC Educational Resources Information Center

Witmer, J. Melvin; Sweeney, Thomas J.

1992-01-01

Presents integrated paradigm for wellness and prevention over the life span for purpose of theory building, research, clinical application, education, advocacy, and consciousness raising. Model described includes 11 characteristics desirable for optimal health and functioning. Notes characteristics are expressed through five life tasks of…

Clinical Applications of 3D Printing: Primer for Radiologists.

PubMed

Ballard, David H; Trace, Anthony Paul; Ali, Sayed; Hodgdon, Taryn; Zygmont, Matthew E; DeBenedectis, Carolynn M; Smith, Stacy E; Richardson, Michael L; Patel, Midhir J; Decker, Summer J; Lenchik, Leon

2018-01-01

Three-dimensional (3D) printing refers to a number of manufacturing technologies that create physical models from digital information. Radiology is poised to advance the application of 3D printing in health care because our specialty has an established history of acquiring and managing the digital information needed to create such models. The 3D Printing Task Force of the Radiology Research Alliance presents a review of the clinical applications of this burgeoning technology, with a focus on the opportunities for radiology. Topics include uses for treatment planning, medical education, and procedural simulation, as well as patient education. Challenges for creating custom implantable devices including financial and regulatory processes for clinical application are reviewed. Precedent procedures that may translate to this new technology are discussed. The task force identifies research opportunities needed to document the value of 3D printing as it relates to patient care. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Development of a Novel Ultrasound-guided Peritonsillar Abscess Model for Simulation Training.

PubMed

Ng, Vivienne; Plitt, Jennifer; Biffar, David

2018-01-01

Peritonsillar abscess (PTA) is the most common deep space infection of the head and neck presenting to emergency departments.1 No commercial PTA task trainer exists for simulation training. Thus, resident physicians often perform their first PTA needle aspiration in the clinical setting, knowing that carotid artery puncture and hemorrhage are serious and devastating complications. While several low-fidelity PTA task trainers have been previously described, none allow for ultrasound image acquisition.6-9 We sought to create a cost-effective and realistic task trainer that allows trainees to acquire both diagnostic ultrasound and needle aspiration skills while draining a peritonsillar abscess. We built the task trainer with low-cost, replaceable, and easily cleanable materials. A damaged airway headskin was repurposed to build the model. A mesh wire cylinder attached to a wooden base was fashioned to provide infrastructure. PTAs were simulated with a water and lotion solution inside a water balloon that was glued to the bottom of a paper cup. The balloon was fully submerged with ordnance gelatin to facilitate ultrasound image acquisition, and an asymmetric soft palate and deviated uvula were painted on top after setting. PTA cups were replaced after use. We spent eight hours constructing three task trainers and used 50 PTA cups for a total cost <$110. Forty-six emergency medicine (EM) residents performed PTA needle aspirations using the task trainers and were asked to rate ultrasound image realism, task trainer realism, and trainer ease of use on a five-point visual analog scale, with five being very realistic and easy. Sixteen of 46 (35%) residents completed the survey and reported that ultrasound images were representative of real PTAs (mean 3.41). They found the model realistic (mean 3.73) and easy to use (mean 4.08). Residents rated their comfort with the drainage procedure as 2.07 before and 3.64 after practicing on the trainer. This low-cost, easy-to-construct simulator allows for ultrasound image acquisition while performing PTA needle aspirations and is the first reported of its kind. Educators from EM and otolaryngology can use this model to educate inexperienced trainees, thus ultimately improving patient safety in the clinical setting.

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

PubMed

Xiao, Cao; Choi, Edward; Sun, Jimeng

2018-06-08

To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoing research and identify open challenges in building deep learning models of EHRs. We searched PubMed and Google Scholar for papers on deep learning studies using EHR data published between January 1, 2010, and January 31, 2018. We summarize them according to these axes: types of analytics tasks, types of deep learning model architectures, special challenges arising from health data and tasks and their potential solutions, as well as evaluation strategies. We surveyed and analyzed multiple aspects of the 98 articles we found and identified the following analytics tasks: disease detection/classification, sequential prediction of clinical events, concept embedding, data augmentation, and EHR data privacy. We then studied how deep architectures were applied to these tasks. We also discussed some special challenges arising from modeling EHR data and reviewed a few popular approaches. Finally, we summarized how performance evaluations were conducted for each task. Despite the early success in using deep learning for health analytics applications, there still exist a number of issues to be addressed. We discuss them in detail including data and label availability, the interpretability and transparency of the model, and ease of deployment.

Delegation of clinical dietetic tasks in military and civilian hospitals: implications for practice.

PubMed

Myers, M E; Gregoire, M B; Spears, M C

1991-12-01

The purposes of our research were two-fold: to determine perceptions of the quality of task performance and to identify dietetic personnel currently performing clinical dietetic tasks in military and civilian hospitals. Questionnaires were returned from 309 dietitians and 208 dietetic support personnel at 151 military and civilian hospitals (73% response overall). For tasks completed by support personnel, no task was rated as having optimum quality, 1 was rated as highly acceptable, 6 as acceptable, 19 as somewhat unacceptable, and 4 as unacceptable. Current performance ratings indicated that 1 task was performed solely by dietitians, 21 were completed by dietitians with assistance, 6 were completed jointly by dietitians and support personnel, 2 were completed by support personnel with supervision by dietitians, and no task was completed independently by support personnel. Tasks were grouped into four categories: basic clinical dietetics (11 tasks), intermediate and in-depth clinical dietetics (12 tasks), outpatient nutrition clinic (5 tasks), and nutrition education (community) (4 tasks). Quality scores for the US Air Force (USAF) hospitals were higher for all task categories except intermediate and in-depth clinical dietetic tasks. The quality scores of support personnel were higher than those of dietitians for all task categories. The USAF performance scores indicated significantly more involvement of support personnel. Generally, the performance scores of dietitians increased with experience; the scores of support personnel decreased with experience. Correlations between quality and performance ratings for individual tasks revealed low to moderate relationships. Our results suggest that additional delegation of tasks to dietetic support personnel may be possible without negatively affecting perceptions of the quality of task outcome.(ABSTRACT TRUNCATED AT 250 WORDS)

Using a contextualized sensemaking model for interaction design: A case study of tumor contouring.

PubMed

Aselmaa, Anet; van Herk, Marcel; Laprie, Anne; Nestle, Ursula; Götz, Irina; Wiedenmann, Nicole; Schimek-Jasch, Tanja; Picaud, Francois; Syrykh, Charlotte; Cagetti, Leonel V; Jolnerovski, Maria; Song, Yu; Goossens, Richard H M

2017-01-01

Sensemaking theories help designers understand the cognitive processes of a user when he/she performs a complicated task. This paper introduces a two-step approach of incorporating sensemaking support within the design of health information systems by: (1) modeling the sensemaking process of physicians while performing a task, and (2) identifying software interaction design requirements that support sensemaking based on this model. The two-step approach is presented based on a case study of the tumor contouring clinical task for radiotherapy planning. In the first step of the approach, a contextualized sensemaking model was developed to describe the sensemaking process based on the goal, the workflow and the context of the task. In the second step, based on a research software prototype, an experiment was conducted where three contouring tasks were performed by eight physicians respectively. Four types of navigation interactions and five types of interaction sequence patterns were identified by analyzing the gathered interaction log data from those twenty-four cases. Further in-depth study on each of the navigation interactions and interaction sequence patterns in relation to the contextualized sensemaking model revealed five main areas for design improvements to increase sensemaking support. Outcomes of the case study indicate that the proposed two-step approach was beneficial for gaining a deeper understanding of the sensemaking process during the task, as well as for identifying design requirements for better sensemaking support. Copyright © 2016. Published by Elsevier Inc.

Comparsion analysis of data mining models applied to clinical research in traditional Chinese medicine.

PubMed

Zhao, Yufeng; Xie, Qi; He, Liyun; Liu, Baoyan; Li, Kun; Zhang, Xiang; Bai, Wenjing; Luo, Lin; Jing, Xianghong; Huo, Ruili

2014-10-01

To help researchers selecting appropriate data mining models to provide better evidence for the clinical practice of Traditional Chinese Medicine (TCM) diagnosis and therapy. Clinical issues based on data mining models were comprehensively summarized from four significant elements of the clinical studies: symptoms, symptom patterns, herbs, and efficacy. Existing problems were further generalized to determine the relevant factors of the performance of data mining models, e.g. data type, samples, parameters, variable labels. Combining these relevant factors, the TCM clinical data features were compared with regards to statistical characters and informatics properties. Data models were compared simultaneously from the view of applied conditions and suitable scopes. The main application problems were the inconsistent data type and the small samples for the used data mining models, which caused the inappropriate results, even the mistake results. These features, i.e. advantages, disadvantages, satisfied data types, tasks of data mining, and the TCM issues, were summarized and compared. By aiming at the special features of different data mining models, the clinical doctors could select the suitable data mining models to resolve the TCM problem.

Effects of Gait Self-Efficacy and Lower-Extremity Physical Function on Dual-Task Performance in Older Adults

PubMed Central

Banducci, Sarah E.; Daugherty, Ana M.; Fanning, Jason; Awick, Elizabeth A.; Porter, Gwenndolyn C.; Burzynska, Agnieszka; Shen, Sa; Kramer, Arthur F.; McAuley, Edward

2017-01-01

Objectives. Despite evidence of self-efficacy and physical function's influences on functional limitations in older adults, few studies have examined relationships in the context of complex, real-world tasks. The present study tested the roles of self-efficacy and physical function in predicting older adults' street-crossing performance in single- and dual-task simulations. Methods. Lower-extremity physical function, gait self-efficacy, and street-crossing success ratio were assessed in 195 older adults (60–79 years old) at baseline of a randomized exercise trial. During the street-crossing task, participants walked on a self-propelled treadmill in a virtual reality environment. Participants crossed the street without distraction (single-task trials) and conversed on a cell phone (dual-task trials). Structural equation modeling was used to test hypothesized associations independent of demographic and clinical covariates. Results. Street-crossing performance was better on single-task trials when compared with dual-task trials. Direct effects of self-efficacy and physical function on success ratio were observed in dual-task trials only. The total effect of self-efficacy was significant in both conditions. The indirect path through physical function was evident in the dual-task condition only. Conclusion. Physical function can predict older adults' performance on high fidelity simulations of complex, real-world tasks. Perceptions of function (i.e., self-efficacy) may play an even greater role. The trial is registered with United States National Institutes of Health ClinicalTrials.gov (ID: NCT01472744; Fit & Active Seniors Trial). PMID:28255557

Assessing Measurement Invariance for Spanish Sentence Repetition and Morphology Elicitation Tasks.

PubMed

Kapantzoglou, Maria; Thompson, Marilyn S; Gray, Shelley; Restrepo, M Adelaida

2016-04-01

The purpose of this study was to evaluate evidence supporting the construct validity of two grammatical tasks (sentence repetition, morphology elicitation) included in the Spanish Screener for Language Impairment in Children (Restrepo, Gorin, & Gray, 2013). We evaluated if the tasks measured the targeted grammatical skills in the same way across predominantly Spanish-speaking children with typical language development and those with primary language impairment. A multiple-group, confirmatory factor analytic approach was applied to examine factorial invariance in a sample of 307 predominantly Spanish-speaking children (177 with typical language development; 130 with primary language impairment). The 2 newly developed grammatical tasks were modeled as measures in a unidimensional confirmatory factor analytic model along with 3 well-established grammatical measures from the Clinical Evaluation of Language Fundamentals-Fourth Edition, Spanish (Wiig, Semel, & Secord, 2006). Results suggest that both new tasks measured the construct of grammatical skills for both language-ability groups in an equivalent manner. There was no evidence of bias related to children's language status for the Spanish Screener for Language Impairment in Children Sentence Repetition or Morphology Elicitation tasks. Results provide support for the validity of the new tasks as measures of grammatical skills.

[New calculation algorithms in brachytherapy for iridium 192 treatments].

PubMed

Robert, C; Dumas, I; Martinetti, F; Chargari, C; Haie-Meder, C; Lefkopoulos, D

2018-05-18

Since 1995, the brachytherapy dosimetry protocols follow the methodology recommended by the Task Group 43. This methodology, which has the advantage of being fast, is based on several approximations that are not always valid in clinical conditions. Model-based dose calculation algorithms have recently emerged in treatment planning stations and are considered as a major evolution by allowing for consideration of the patient's finite dimensions, tissue heterogeneities and the presence of high atomic number materials in applicators. In 2012, a report from the American Association of Physicists in Medicine Radiation Therapy Task Group 186 reviews these models and makes recommendations for their clinical implementation. This review focuses on the use of model-based dose calculation algorithms in the context of iridium 192 treatments. After a description of these algorithms and their clinical implementation, a summary of the main questions raised by these new methods is performed. Considerations regarding the choice of the medium used for the dose specification and the recommended methodology for assigning materials characteristics are especially described. In the last part, recent concrete examples from the literature illustrate the capabilities of these new algorithms on clinical cases. Copyright © 2018 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Isolation Rearing Effects on Probabilistic Learning and Cognitive Flexibility in Rats

PubMed Central

AMITAI, Nurith; YOUNG, Jared W.; HIGA, Kerin; SHARP, Richard F.; GEYER, Mark A.; POWELL, Susan B.

2013-01-01

Isolation rearing is a neurodevelopmental manipulation that produces neurochemical, structural, and behavioral alterations in rodents that have consistencies with schizophrenia. Symptoms induced by isolation rearing that mirror clinically relevant aspects of schizophrenia, such as cognitive deficits, open up the possibility of testing putative therapeutics in isolation-reared animals prior to clinical development. We investigated what effect isolation rearing would have on cognitive flexibility, a cognitive function characteristically disrupted in schizophrenia. For this purpose, we assessed cognitive flexibility using between- and within-session probabilistic reversal-learning tasks based on clinical tests. Isolation-reared rats required more sessions, though not more task trials, to acquire criterion performance in the reversal phase of the task and were slower to adjust their task strategy after reward contingencies were switched. Isolation-reared rats also completed fewer trials and exhibited lower levels of overall activity in the probabilistic reversal-learning task compared to socially reared rats. This finding contrasted with the elevated levels of unconditioned investigatory activity and reduced levels of locomotor habituation that isolation-reared rats displayed in the behavioral pattern monitor. Finally, isolation-reared rats also exhibited sensorimotor gating deficits, reflected by decreased prepulse inhibition of the startle response, consistent with previous studies. We conclude that isolation rearing constitutes a valuable, noninvasive manipulation for modeling schizophrenia-like cognitive deficits and assessing putative therapeutics. PMID:23943516

DeepInfer: open-source deep learning deployment toolkit for image-guided therapy

NASA Astrophysics Data System (ADS)

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-03-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research work ows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy.

PubMed

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A; Kapur, Tina; Wells, William M; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-02-11

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research workflows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy

PubMed Central

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-01-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research workflows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose “DeepInfer” – an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections. PMID:28615794

The use of decision analysis to examine ethical decision making by critical care nurses.

PubMed

Hughes, K K; Dvorak, E M

1997-01-01

To examine the extent to which critical care staff nurses make ethical decisions that coincide with those recommended by a decision analytic model. Nonexperimental, ex post facto. Midwestern university-affiliated 500 bed tertiary care medical center. One hundred critical care staff nurses randomly selected from seven critical care units. Complete responses were obtained from 82 nurses (for a final response rate of 82%). The dependent variable--consistent decision making--was measured as staff nurses' abilities to make ethical decisions that coincided with those prescribed by the decision model. Subjects completed two instruments, the Ethical Decision Analytic Model, a computer-administered instrument designed to measure staff nurses' abilities to make consistent decisions about a chemically-impaired colleague; and a Background Inventory. The results indicate marked consensus among nurses when informal methods were used. However, there was little consistency between the nurses' informal decisions and those recommended by the decision analytic model. Although 50% (n = 41) of all nurses chose a course of action that coincided with the model's least optimal alternative, few nurses agreed with the model as to the most optimal course of action. The findings also suggest that consistency was unrelated (p > 0.05) to the nurses' educational background or years of clinical experience; that most subjects reported receiving little or no education in decision making during their basic nursing education programs; but that exposure to decision-making strategies was related to years of nursing experience (p < 0.05). The findings differ from related studies that have found a moderate degree of consistency between nurses and decision analytic models for strictly clinical decision tasks, especially when those tasks were less complex. However, the findings partially coincide with other findings that decision analysis may not be particularly well-suited to the critical care environment. Additional research is needed to determine whether critical care nurses use the same decision-making methods as do other nurses; and to clarify the effects of decision task (clinical versus ethical) on nurses' decision making. It should not be assumed that methods used to study nurses' clinical decision making are applicable for all nurses or all types of decisions, including ethical decisions.

Clinical Predictive Modeling Development and Deployment through FHIR Web Services.

PubMed

Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

2015-01-01

Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.

Clinical Predictive Modeling Development and Deployment through FHIR Web Services

PubMed Central

Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

2015-01-01

Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction. PMID:26958207

Using 3D Printing (Additive Manufacturing) to Produce Low-Cost Simulation Models for Medical Training.

PubMed

Lichtenberger, John P; Tatum, Peter S; Gada, Satyen; Wyn, Mark; Ho, Vincent B; Liacouras, Peter

2018-03-01

This work describes customized, task-specific simulation models derived from 3D printing in clinical settings and medical professional training programs. Simulation models/task trainers have an array of purposes and desired achievements for the trainee, defining that these are the first step in the production process. After this purpose is defined, computer-aided design and 3D printing (additive manufacturing) are used to create a customized anatomical model. Simulation models then undergo initial in-house testing by medical specialists followed by a larger scale beta testing. Feedback is acquired, via surveys, to validate effectiveness and to guide or determine if any future modifications and/or improvements are necessary. Numerous custom simulation models have been successfully completed with resulting task trainers designed for procedures, including removal of ocular foreign bodies, ultrasound-guided joint injections, nerve block injections, and various suturing and reconstruction procedures. These task trainers have been frequently utilized in the delivery of simulation-based training with increasing demand. 3D printing has been integral to the production of limited-quantity, low-cost simulation models across a variety of medical specialties. In general, production cost is a small fraction of a commercial, generic simulation model, if available. These simulation and training models are customized to the educational need and serve an integral role in the education of our military health professionals.

78 FR 23261 - Solicitation for Nominations for Members of the U.S. Preventive Services Task Force (USPSTF)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-18

... during conference calls and via email discussions. Member duties include prioritizing topics, designing... their expertise in methodological issues such as meta-analysis, analytic modeling or clinical...

Model-based query language for analyzing clinical processes.

PubMed

Barzdins, Janis; Barzdins, Juris; Rencis, Edgars; Sostaks, Agris

2013-01-01

Nowadays large databases of clinical process data exist in hospitals. However, these data are rarely used in full scope. In order to perform queries on hospital processes, one must either choose from the predefined queries or develop queries using MS Excel-type software system, which is not always a trivial task. In this paper we propose a new query language for analyzing clinical processes that is easily perceptible also by non-IT professionals. We develop this language based on a process modeling language which is also described in this paper. Prototypes of both languages have already been verified using real examples from hospitals.

The Bobath concept in contemporary clinical practice.

PubMed

Graham, Julie Vaughan; Eustace, Catherine; Brock, Kim; Swain, Elizabeth; Irwin-Carruthers, Sheena

2009-01-01

Future development in neurorehabilitation depends upon bringing together the endeavors of basic science and clinical practice. The Bobath concept is widely utilized in rehabilitation following stroke and other neurological conditions. This concept was first developed in the 1950s, based on the neuroscience knowledge of those times. The theoretical basis of the Bobath concept is redefined based on contemporary neuroscience and rehabilitation science. The framework utilized in the Bobath concept for the analysis of movement and movement dysfunction is described. This framework focuses on postural control for task performance, the ability to move selectively, the ability to produce coordinated sequences of movement and vary movement patterns to fit a task, and the role of sensory input in motor behaviour and learning. The article describes aspects of clinical practice that differentiate this approach from other models of practice. Contemporary practice in the Bobath concept utilizes a problem-solving approach to the individual's clinical presentation and personal goals. Treatment is focused toward remediation, where possible, and guiding the individual towards efficient movement strategies for task performance. The aim of this article is to provide a theoretical framework on which future research into the Bobath concept can be based.

Impact of number of repeated scans on model observer performance for a low-contrast detection task in computed tomography

PubMed Central

Ma, Chi; Yu, Lifeng; Chen, Baiyu; Favazza, Christopher; Leng, Shuai; McCollough, Cynthia

2016-01-01

Abstract. Channelized Hotelling observer (CHO) models have been shown to correlate well with human observers for several phantom-based detection/classification tasks in clinical computed tomography (CT). A large number of repeated scans were used to achieve an accurate estimate of the model’s template. The purpose of this study is to investigate how the experimental and CHO model parameters affect the minimum required number of repeated scans. A phantom containing 21 low-contrast objects was scanned on a 128-slice CT scanner at three dose levels. Each scan was repeated 100 times. For each experimental configuration, the low-contrast detectability, quantified as the area under receiver operating characteristic curve, Az, was calculated using a previously validated CHO with randomly selected subsets of scans, ranging from 10 to 100. Using Az from the 100 scans as the reference, the accuracy from a smaller number of scans was determined. Our results demonstrated that the minimum number of repeated scans increased when the radiation dose level decreased, object size and contrast level decreased, and the number of channels increased. As a general trend, it increased as the low-contrast detectability decreased. This study provides a basis for the experimental design of task-based image quality assessment in clinical CT using CHO. PMID:27284547

ACC Neuro-over-Connectivity Is Associated with Mathematically Modeled Additional Encoding Operations of Schizophrenia Stroop-Task Performance

PubMed Central

Taylor, Reggie; Théberge, Jean; Williamson, Peter C.; Densmore, Maria; Neufeld, Richard W. J.

2016-01-01

Functional magnetic resonance imaging at 7.0 Tesla was undertaken among Schizophrenia participants (Sz), and clinical (major mood disorder; MDD) and healthy controls (HC), during performance of the Stoop task. Stroop conditions included congruent and incongruent word color items, color-only items, and word-only items. Previous modeling results extended to this most widely used selective-attention task. All groups executed item-encoding operations (subprocesses of the item encoding process) at the same rate (performance accuracy being similarly high throughout), thus displaying like processing capacity; Sz participants, however, employed more subprocesses for item completions than did the MDD participants, who in turn used more subprocesses than the HC group. The reduced efficiency in deploying cognitive-workload capacity among the Sz participants was paralleled by more diffuse neuroconnectivity (Blood-Oxygen-Level-Dependent co-activation) with the anterior cingulate cortex (ACC) (Broadman Area 32), spreading away from this encoding-intensive region; and by less evidence of network dissociation across Stroop conditions. Estimates of cognitive work done to accomplish item completion were greater for the Sz participants, as were estimates of entropy in both the modeled trial-latency distribution, and its associated neuro-circuitry. Findings are held to be symptom and assessment significant, and to have potential implications for clinical intervention. PMID:27695425

Motivation and value influences in the relative balance of goal-directed and habitual behaviours in obsessive-compulsive disorder.

PubMed

Voon, V; Baek, K; Enander, J; Worbe, Y; Morris, L S; Harrison, N A; Robbins, T W; Rück, C; Daw, N

2015-11-03

Our decisions are based on parallel and competing systems of goal-directed and habitual learning, systems which can be impaired in pathological behaviours. Here we focus on the influence of motivation and compare reward and loss outcomes in subjects with obsessive-compulsive disorder (OCD) on model-based goal-directed and model-free habitual behaviours using the two-step task. We further investigate the relationship with acquisition learning using a one-step probabilistic learning task. Forty-eight OCD subjects and 96 healthy volunteers were tested on a reward and 30 OCD subjects and 53 healthy volunteers on the loss version of the two-step task. Thirty-six OCD subjects and 72 healthy volunteers were also tested on a one-step reversal task. OCD subjects compared with healthy volunteers were less goal oriented (model-based) and more habitual (model-free) to reward outcomes with a shift towards greater model-based and lower habitual choices to loss outcomes. OCD subjects also had enhanced acquisition learning to loss outcomes on the one-step task, which correlated with goal-directed learning in the two-step task. OCD subjects had greater stay behaviours or perseveration in the one-step task irrespective of outcome. Compulsion severity was correlated with habitual learning in the reward condition. Obsession severity was correlated with greater switching after loss outcomes. In healthy volunteers, we further show that greater reward magnitudes are associated with a shift towards greater goal-directed learning further emphasizing the role of outcome salience. Our results highlight an important influence of motivation on learning processes in OCD and suggest that distinct clinical strategies based on valence may be warranted.

Inhibitory Control in Mind and Brain: An Interactive Race Model of Countermanding Saccades

ERIC Educational Resources Information Center

Boucher, Leanne; Palmeri, Thomas J.; Logan, Gordon D.; Schall, Jeffrey D.

2007-01-01

The stop-signal task has been used to study normal cognitive control and clinical dysfunction. Its utility is derived from a race model that accounts for performance and provides an estimate of the time it takes to stop a movement. This model posits a race between go and stop processes with stochastically independent finish times. However,…

Synonym extraction and abbreviation expansion with ensembles of semantic spaces.

PubMed

Henriksson, Aron; Moen, Hans; Skeppstedt, Maria; Daudaravičius, Vidas; Duneld, Martin

2014-02-05

Terminologies that account for variation in language use by linking synonyms and abbreviations to their corresponding concept are important enablers of high-quality information extraction from medical texts. Due to the use of specialized sub-languages in the medical domain, manual construction of semantic resources that accurately reflect language use is both costly and challenging, often resulting in low coverage. Although models of distributional semantics applied to large corpora provide a potential means of supporting development of such resources, their ability to isolate synonymy from other semantic relations is limited. Their application in the clinical domain has also only recently begun to be explored. Combining distributional models and applying them to different types of corpora may lead to enhanced performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. A combination of two distributional models - Random Indexing and Random Permutation - employed in conjunction with a single corpus outperforms using either of the models in isolation. Furthermore, combining semantic spaces induced from different types of corpora - a corpus of clinical text and a corpus of medical journal articles - further improves results, outperforming a combination of semantic spaces induced from a single source, as well as a single semantic space induced from the conjoint corpus. A combination strategy that simply sums the cosine similarity scores of candidate terms is generally the most profitable out of the ones explored. Finally, applying simple post-processing filtering rules yields substantial performance gains on the tasks of extracting abbreviation-expansion pairs, but not synonyms. The best results, measured as recall in a list of ten candidate terms, for the three tasks are: 0.39 for abbreviations to long forms, 0.33 for long forms to abbreviations, and 0.47 for synonyms. This study demonstrates that ensembles of semantic spaces can yield improved performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. This notion, which merits further exploration, allows different distributional models - with different model parameters - and different types of corpora to be combined, potentially allowing enhanced performance to be obtained on a wide range of natural language processing tasks.

Synonym extraction and abbreviation expansion with ensembles of semantic spaces

PubMed Central

2014-01-01

Background Terminologies that account for variation in language use by linking synonyms and abbreviations to their corresponding concept are important enablers of high-quality information extraction from medical texts. Due to the use of specialized sub-languages in the medical domain, manual construction of semantic resources that accurately reflect language use is both costly and challenging, often resulting in low coverage. Although models of distributional semantics applied to large corpora provide a potential means of supporting development of such resources, their ability to isolate synonymy from other semantic relations is limited. Their application in the clinical domain has also only recently begun to be explored. Combining distributional models and applying them to different types of corpora may lead to enhanced performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. Results A combination of two distributional models – Random Indexing and Random Permutation – employed in conjunction with a single corpus outperforms using either of the models in isolation. Furthermore, combining semantic spaces induced from different types of corpora – a corpus of clinical text and a corpus of medical journal articles – further improves results, outperforming a combination of semantic spaces induced from a single source, as well as a single semantic space induced from the conjoint corpus. A combination strategy that simply sums the cosine similarity scores of candidate terms is generally the most profitable out of the ones explored. Finally, applying simple post-processing filtering rules yields substantial performance gains on the tasks of extracting abbreviation-expansion pairs, but not synonyms. The best results, measured as recall in a list of ten candidate terms, for the three tasks are: 0.39 for abbreviations to long forms, 0.33 for long forms to abbreviations, and 0.47 for synonyms. Conclusions This study demonstrates that ensembles of semantic spaces can yield improved performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. This notion, which merits further exploration, allows different distributional models – with different model parameters – and different types of corpora to be combined, potentially allowing enhanced performance to be obtained on a wide range of natural language processing tasks. PMID:24499679

An Integrative Social-Cognitive Developmental Model of Supervision for Substance Abuse Counselors-in-Training

ERIC Educational Resources Information Center

Sias, Shari M.; Lambie, Glenn W.

2008-01-01

Substance abuse counselors (SACs) at higher levels of social-cognitive maturity manage complex situations and perform counselor-related tasks more effectively than individuals at lower levels of development. This article presents an integrative clinical supervision model designed to promote the social-cognitive maturity (ego development;…

A probabilistic topic model for clinical risk stratification from electronic health records.

PubMed

Huang, Zhengxing; Dong, Wei; Duan, Huilong

2015-12-01

Risk stratification aims to provide physicians with the accurate assessment of a patient's clinical risk such that an individualized prevention or management strategy can be developed and delivered. Existing risk stratification techniques mainly focus on predicting the overall risk of an individual patient in a supervised manner, and, at the cohort level, often offer little insight beyond a flat score-based segmentation from the labeled clinical dataset. To this end, in this paper, we propose a new approach for risk stratification by exploring a large volume of electronic health records (EHRs) in an unsupervised fashion. Along this line, this paper proposes a novel probabilistic topic modeling framework called probabilistic risk stratification model (PRSM) based on Latent Dirichlet Allocation (LDA). The proposed PRSM recognizes a patient clinical state as a probabilistic combination of latent sub-profiles, and generates sub-profile-specific risk tiers of patients from their EHRs in a fully unsupervised fashion. The achieved stratification results can be easily recognized as high-, medium- and low-risk, respectively. In addition, we present an extension of PRSM, called weakly supervised PRSM (WS-PRSM) by incorporating minimum prior information into the model, in order to improve the risk stratification accuracy, and to make our models highly portable to risk stratification tasks of various diseases. We verify the effectiveness of the proposed approach on a clinical dataset containing 3463 coronary heart disease (CHD) patient instances. Both PRSM and WS-PRSM were compared with two established supervised risk stratification algorithms, i.e., logistic regression and support vector machine, and showed the effectiveness of our models in risk stratification of CHD in terms of the Area Under the receiver operating characteristic Curve (AUC) analysis. As well, in comparison with PRSM, WS-PRSM has over 2% performance gain, on the experimental dataset, demonstrating that incorporating risk scoring knowledge as prior information can improve the performance in risk stratification. Experimental results reveal that our models achieve competitive performance in risk stratification in comparison with existing supervised approaches. In addition, the unsupervised nature of our models makes them highly portable to the risk stratification tasks of various diseases. Moreover, patient sub-profiles and sub-profile-specific risk tiers generated by our models are coherent and informative, and provide significant potential to be explored for the further tasks, such as patient cohort analysis. We hypothesize that the proposed framework can readily meet the demand for risk stratification from a large volume of EHRs in an open-ended fashion. Copyright © 2015 Elsevier Inc. All rights reserved.

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inhibiting reactions to emotional versus non-emotional response cues in schizophrenia: Insights from a motor-process paradigm.

PubMed

Patrick, Regan E; Christensen, Bruce K; Smolewska, Kathy

2016-03-01

Recent models of schizophrenia suggest deficient use of contextual response cues when confronted with countermanding emotional cues. It is important to clinically validate these models by testing patients diagnosed with schizophrenia on tasks with competing emotional and contextual response determinants. Control and schizophrenia groups completed a novel task that elicited motor responses consistent with, or in opposition to, pre-potent emotional actions (i.e., approach vs. avoidance). An analogous non-emotional task was also used to examine cue-conflict impairment more generally. The groups demonstrated statistically equivalent performance decrements on incongruent versus congruent trials on both tasks. However, within the schizophrenia group, the incongruency effect was significantly greater in the emotional versus non-emotional task. These data suggest that, while patients with schizophrenia were able to employ contextual response cues to override competing emotional responses, they were slower to resolve emotional versus non-emotional response conflict. When patients were subdivided according to the presence or absence of disorganized symptoms, this effect was confined to patients with disorganized symptoms. © 2014 The British Psychological Society.

Cognitive control processes in paranoia: the impact of threat induction on strategic cognition and self-focused attention.

PubMed

Flower, Laura; Newman-Taylor, Katherine; Stopa, Lusia

2015-01-01

Current clinical models emphasize certain cognitive processes in the maintenance of distressing paranoia. While a number of these processes have been examined in detail, the role of strategic cognition and self-focused attention remain under-researched. This study examined the deployment of cognitive strategies and self-focused attention in people with non-clinical paranoia. An experimental design was used to examine the impact of a threat activation task on these processes, in participants with high and low non-clinical paranoia. Twenty-eight people were recruited to each group, and completed measures of anxiety, paranoid cognition, strategic cognition and self-focused attention. The threat activation task was effective in increasing anxiety in people with high and low non-clinical paranoia. The high paranoia group experienced more paranoid cognitions following threat activation. This group also reported greater use of thought suppression, punishment and worry, and less use of social control strategies when under threat. No differences were found between the groups on measures of self-focused attention. This study shows that the threat activation task increased anxiety in people with high non-clinical paranoia, leading to increased paranoid thinking. The use of strategic cognition following threat activation varied dependent on level of non-clinical paranoia. If these differences are replicated in clinical groups, the strategies may be implicated in the maintenance of distressing psychosis, and may therefore be a valuable target for therapeutic intervention.

Comparison of gesture and conventional interaction techniques for interventional neuroradiology.

PubMed

Hettig, Julian; Saalfeld, Patrick; Luz, Maria; Becker, Mathias; Skalej, Martin; Hansen, Christian

2017-09-01

Interaction with radiological image data and volume renderings within a sterile environment is a challenging task. Clinically established methods such as joystick control and task delegation can be time-consuming and error-prone and interrupt the workflow. New touchless input modalities may have the potential to overcome these limitations, but their value compared to established methods is unclear. We present a comparative evaluation to analyze the value of two gesture input modalities (Myo Gesture Control Armband and Leap Motion Controller) versus two clinically established methods (task delegation and joystick control). A user study was conducted with ten experienced radiologists by simulating a diagnostic neuroradiological vascular treatment with two frequently used interaction tasks in an experimental operating room. The input modalities were assessed using task completion time, perceived task difficulty, and subjective workload. Overall, the clinically established method of task delegation performed best under the study conditions. In general, gesture control failed to exceed the clinical input approach. However, the Myo Gesture Control Armband showed a potential for simple image selection task. Novel input modalities have the potential to take over single tasks more efficiently than clinically established methods. The results of our user study show the relevance of task characteristics such as task complexity on performance with specific input modalities. Accordingly, future work should consider task characteristics to provide a useful gesture interface for a specific use case instead of an all-in-one solution.

Feasibility of nurse-led antidepressant medication management of depression in an HIV clinic in Tanzania.

PubMed

Adams, Julie L; Almond, Maria L G; Ringo, Edward J; Shangali, Wahida H; Sikkema, Kathleen J

2012-01-01

Sub-Saharan Africa has the highest HIV prevalence worldwide and depression is highly prevalent among those infected. The negative impact of depression on HIV outcomes highlights the need to identify and treat it in this population. A model for doing this in lower-resourced settings involves task-shifting depression treatment to primary care; however, HIV-infected individuals are often treated in a parallel HIV specialty setting. We adapted a model of task-shifting, measurement-based care (MBC), for an HIV clinic setting and tested its feasibility in Tanzania. MBC involves measuring depressive symptoms at meaningful intervals and adjusting antidepressant medication treatment based on the measure of illness. Twenty adults presenting for care at an outpatient HIV clinic in Tanzania were enrolled and followed by a nurse care manager who measured depressive symptoms at baseline and every 4 weeks for 12 weeks. An algorithm-based decision-support tool was utilized by the care manager to recommend individualized antidepressant medication doses to participants' HIV providers at each visit. Retention was high and fidelity of the care manager to the MBC protocol was exceptional. Follow through of antidepressant prescription dosing recommendations by the prescriber was low. Limited availability of antidepressants was also noted. Despite challenges, baseline depression scores decreased over the 12-week period. Overall, the model of algorithm-based nursing support of prescription decisions was feasible. Future studies should address implementation issues of medication supply and dosing. Further task-shifting to relatively more abundant and lower-skilled health workers, such as nurses' aides, warrants examination.

Developing a case-mix model for PPS.

PubMed

Goldberg, H B; Delargy, D

2000-01-01

Agencies are pinning hopes for success under PPS on an accurate case-mix adjustor. The Health Care Financing Administration (HCFA) tasked Abt Associates Inc. to develop a system to accurately predict the volume and type of home health services each patient requires, based on his or her characteristics (not the service actually received). HCFA wanted this system to be feasible, clinically logical, and valid and accurate. Authors Goldberg and Delargy explain how Abt approached this daunting task.

Autobiographical Memory Task in Assessing Dementia

PubMed Central

Dreyfus, Denise Maue; Roe, Catherine M.; Morris, John C.

2009-01-01

Objective To appraise the relationship of a task assessing memory for recent autobiographical events and those of two commonly used brief memory tasks with the results of a clinical assessment for dementia. Design, Setting, and Participants We compared correlations between a task assessing recall of recent autobiographical events and two frequently-used brief clinical memory measures with dementia ratings by clinicians. Participants were enrolled in Washington University Alzheimer’s Disease Research Center studies, were aged 60 years or above, and took part in assessments between May 2002 and August 2005 (N=425). Main Outcome Measures Nonparametric, rank-based Spearman correlations, adjusted for age and education, between the Clinical Dementia Rating Sum of Boxes (CDR-SB) and scores on the autobiographical recall query and two clinical memory tasks taken from the Mini-Mental State Exam and the Short Blessed Test. Results The autobiographical recall task and each of the other brief clinical measures correlated significantly with the CDR-SB (p<.0001). The autobiographical recall task had a significantly higher correlation (p<.0001) with the CDR-SB than the two commonly-used clinical memory measures. Conclusions Clinicians may find autobiographical memories an important indicator of clinical memory function and the autobiographical query a useful tool when assessing for dementia. PMID:20625094

Selective effect of neurocognition on different theory of mind domains in first-episode psychosis.

PubMed

Fernandez-Gonzalo, Sol; Jodar, Merce; Pousa, Esther; Turon, Marc; Garcia, Rebeca; Rambla, Carla Hernandez; Palao, Diego

2014-08-01

The aim of this study was to investigate the influence of neurocognition on affective and cognitive theory of mind (ToM) tasks in early phases of psychosis. In a cross-sectional study of 60 first-episode schizophrenia/schizoaffective disorder patients, the implication of neurocognition in first- and second-order ToM stories, Hinting Task, and Reading the Mind in the Eyes Test (RMET) was analyzed. Regression models were used, controlling for clinical symptoms and antipsychotic dose. Spatial span backward (odds ratio [OR], 0.34; p = 0.01) and intrusions in the Rey Auditory Verbal Learning Test (OR, 4.86; p = 0.04) were the best factors to predict second-order ToM failure. Trail Making Test B (B = 0.01; p = 0.04) and negative symptoms (B = 0.09; p = 0.01) predicted Hinting task performance while Block design (B = 0.1; p = 0.04) was related to RMET outcome. Executive functions and clinical symptoms were related to ToM performance in first-episode schizophrenia patients, although different patterns of relationship were observed in each ToM task.

First of all: Do not harm! Use of simulation for the training of regional anaesthesia techniques: Which skills can be trained without the patient as substitute for a mannequin.

PubMed

Sujatta, Susanne

2015-03-01

Character of clinical skills training is always influenced by technical improvement and cultural changes. Over the last years, two trends have changed the way of traditional apprenticeship-style training in regional anaesthesia: firstly, the development in ultrasound-guided regional anaesthesia, and secondly, the reduced acceptance of using patients as mannequins for invasive techniques. Against this background, simulation techniques are explored, ranging from simple low-fidelity part-task training models to train skills in needle application, to highly sophisticated virtual reality models – the full range is covered. This review tries to discuss all available options with benefits and neglects. The task in clinical practice will be in choosing the right level of sophistication for the desired approach and trainee level. However, the transfer of simulated skills to clinical practice has not been evaluated. It has to be proven whether simulation-trained skills could, as a last consequence, reduce the risk to patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

Usability Evaluation of an Unstructured Clinical Document Query Tool for Researchers.

PubMed

Hultman, Gretchen; McEwan, Reed; Pakhomov, Serguei; Lindemann, Elizabeth; Skube, Steven; Melton, Genevieve B

2018-01-01

Natural Language Processing - Patient Information Extraction for Researchers (NLP-PIER) was developed for clinical researchers for self-service Natural Language Processing (NLP) queries with clinical notes. This study was to conduct a user-centered analysis with clinical researchers to gain insight into NLP-PIER's usability and to gain an understanding of the needs of clinical researchers when using an application for searching clinical notes. Clinical researcher participants (n=11) completed tasks using the system's two existing search interfaces and completed a set of surveys and an exit interview. Quantitative data including time on task, task completion rate, and survey responses were collected. Interviews were analyzed qualitatively. Survey scores, time on task and task completion proportions varied widely. Qualitative analysis indicated that participants found the system to be useful and usable in specific projects. This study identified several usability challenges and our findings will guide the improvement of NLP-PIER 's interfaces.

BioStar models of clinical and genomic data for biomedical data warehouse design

PubMed Central

Wang, Liangjiang; Ramanathan, Murali

2008-01-01

Biomedical research is now generating large amounts of data, ranging from clinical test results to microarray gene expression profiles. The scale and complexity of these datasets give rise to substantial challenges in data management and analysis. It is highly desirable that data warehousing and online analytical processing technologies can be applied to biomedical data integration and mining. The major difficulty probably lies in the task of capturing and modelling diverse biological objects and their complex relationships. This paper describes multidimensional data modelling for biomedical data warehouse design. Since the conventional models such as star schema appear to be insufficient for modelling clinical and genomic data, we develop a new model called BioStar schema. The new model can capture the rich semantics of biomedical data and provide greater extensibility for the fast evolution of biological research methodologies. PMID:18048122

A meta-analytic review of the impact of intranasal oxytocin administration on cortisol concentrations during laboratory tasks: moderation by method and mental health.

PubMed

Cardoso, Christopher; Kingdon, Danielle; Ellenbogen, Mark A

2014-11-01

A large body of research has examined the acute effects of intranasal oxytocin administration on social cognition and stress-regulation. While progress has been made with respect to understanding the effect of oxytocin administration on social cognition in clinical populations (e.g. autism, schizophrenia), less is known about its impact on the functioning of the hypothalamic-pituitary-adrenal (HPA) axis among individuals with a mental disorder. We conducted a meta-analysis on the acute effect of intranasal oxytocin administration on the cortisol response to laboratory tasks. The search yielded eighteen studies employing a randomized, placebo-controlled design (k=18, N=675). Random-effects models and moderator analyses were performed using the metafor package for the statistical program R. The overall effect size estimate was modest and not statistically significant (Hedges g=-0.151, p=0.11) with moderate heterogeneity in this effect across studies (I(2)=31%). Controlling for baseline differences in cortisol concentrations, moderation analyses revealed that this effect was larger in response to challenging laboratory tasks that produced a robust stimulation of the HPA-axis (Hedges g=-0.433, 95% CI[-0.841, -0.025]), and in clinical populations relative to healthy controls (Hedges g=-0.742, 95% CI[-1.405, -0.078]). Overall, oxytocin administration showed greater attenuation of the cortisol response to laboratory tasks that strongly activated the HPA-axis, relative to tasks that did not. The effect was more robust among clinical populations, suggesting possible increased sensitivity to oxytocin among those with a clinical diagnosis and concomitant social difficulties. These data support the view that oxytocin may play an important role in HPA dysfunction associated with psychopathology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Building gold standard corpora for medical natural language processing tasks.

PubMed

Deleger, Louise; Li, Qi; Lingren, Todd; Kaiser, Megan; Molnar, Katalin; Stoutenborough, Laura; Kouril, Michal; Marsolo, Keith; Solti, Imre

2012-01-01

We present the construction of three annotated corpora to serve as gold standards for medical natural language processing (NLP) tasks. Clinical notes from the medical record, clinical trial announcements, and FDA drug labels are annotated. We report high inter-annotator agreements (overall F-measures between 0.8467 and 0.9176) for the annotation of Personal Health Information (PHI) elements for a de-identification task and of medications, diseases/disorders, and signs/symptoms for information extraction (IE) task. The annotated corpora of clinical trials and FDA labels will be publicly released and to facilitate translational NLP tasks that require cross-corpora interoperability (e.g. clinical trial eligibility screening) their annotation schemas are aligned with a large scale, NIH-funded clinical text annotation project.

A study of active learning methods for named entity recognition in clinical text.

PubMed

Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

2015-12-01

Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random sampling, the best uncertainty based method saved 42% annotations in words. But the best diversity based method reduced only 7% annotation effort. In the simulated setting, AL methods, particularly uncertainty-sampling based approaches, seemed to significantly save annotation cost for the clinical NER task. The actual benefit of active learning in clinical NER should be further evaluated in a real-time setting. Copyright © 2015 Elsevier Inc. All rights reserved.

Characterizing Attention with Predictive Network Models.

PubMed

Rosenberg, M D; Finn, E S; Scheinost, D; Constable, R T; Chun, M M

2017-04-01

Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. Copyright © 2017 Elsevier Ltd. All rights reserved.

The use of kernel local Fisher discriminant analysis for the channelization of the Hotelling model observer

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.

2015-03-01

It is resource-intensive to conduct human studies for task-based assessment of medical image quality and system optimization. Thus, numerical model observers have been developed as a surrogate for human observers. The Hotelling observer (HO) is the optimal linear observer for signal-detection tasks, but the high dimensionality of imaging data results in a heavy computational burden. Channelization is often used to approximate the HO through a dimensionality reduction step, but how to produce channelized images without losing significant image information remains a key challenge. Kernel local Fisher discriminant analysis (KLFDA) uses kernel techniques to perform supervised dimensionality reduction, which finds an embedding transformation that maximizes betweenclass separability and preserves within-class local structure in the low-dimensional manifold. It is powerful for classification tasks, especially when the distribution of a class is multimodal. Such multimodality could be observed in many practical clinical tasks. For example, primary and metastatic lesions may both appear in medical imaging studies, but the distributions of their typical characteristics (e.g., size) may be very different. In this study, we propose to use KLFDA as a novel channelization method. The dimension of the embedded manifold (i.e., the result of KLFDA) is a counterpart to the number of channels in the state-of-art linear channelization. We present a simulation study to demonstrate the potential usefulness of KLFDA for building the channelized HOs (CHOs) and generating reliable decision statistics for clinical tasks. We show that the performance of the CHO with KLFDA channels is comparable to that of the benchmark CHOs.

Towards a Generalizable Time Expression Model for Temporal Reasoning in Clinical Notes

PubMed Central

Velupillai, Sumithra; Mowery, Danielle L.; Abdelrahman, Samir; Christensen, Lee; Chapman, Wendy W

2015-01-01

Accurate temporal identification and normalization is imperative for many biomedical and clinical tasks such as generating timelines and identifying phenotypes. A major natural language processing challenge is developing and evaluating a generalizable temporal modeling approach that performs well across corpora and institutions. Our long-term goal is to create such a model. We initiate our work on reaching this goal by focusing on temporal expression (TIMEX3) identification. We present a systematic approach to 1) generalize existing solutions for automated TIMEX3 span detection, and 2) assess similarities and differences by various instantiations of TIMEX3 models applied on separate clinical corpora. When evaluated on the 2012 i2b2 and the 2015 Clinical TempEval challenge corpora, our conclusion is that our approach is successful – we achieve competitive results for automated classification, and we identify similarities and differences in TIMEX3 modeling that will be informative in the development of a simplified, general temporal model. PMID:26958265

Manual therapy as an effective treatment for fibrosis in a rat model of upper extremity overuse injury

PubMed Central

Bove, Geoffrey M.; Harris, Michele Y; Zhao, Huaqing; Barbe, Mary F.

2016-01-01

Key clinical features of carpal tunnel syndrome and other types of cumulative trauma disorders of the hand and wrist include pain and functional disabilities. Mechanistic details remain under investigation but may involve tissue inflammation and/or fibrosis. We examined the effectiveness of modeled manual therapy (MMT) as a treatment for sensorimotor behavior declines and increased fibrogenic processes occurring in forearm tissues of rats performing an high repetition high force (HRHF) reaching and grasping task for 12 weeks. Young adult, female rats were examined: food restricted control rats (FRC, n=12); rats that were trained for 6 weeks before performing the HRHF task for 12 weeks with no treatment (HRHF-CON, n=11); and HRHF task rats received modeled manual therapy (HRHF-MMT, n=5) for 5 days/week for the duration of the 12-week of task. Rats receiving the MMT expressed fewer discomfort-related behaviors, and performed progressively better in the HRHF task. Grip strength, while decreased after training, improved following MMT. Fibrotic nerve and connective tissue changes (increased collagen and TGF-β1 deposition) present in 12-week HRHF-CON rats were significantly decreased in 12-week HRHF-MMT rats. These observations support the investigation of manual therapy as a preventative for repetitive motion disorders. PMID:26810536

Optimising experimental research in respiratory diseases: an ERS statement.

PubMed

Bonniaud, Philippe; Fabre, Aurélie; Frossard, Nelly; Guignabert, Christophe; Inman, Mark; Kuebler, Wolfgang M; Maes, Tania; Shi, Wei; Stampfli, Martin; Uhlig, Stefan; White, Eric; Witzenrath, Martin; Bellaye, Pierre-Simon; Crestani, Bruno; Eickelberg, Oliver; Fehrenbach, Heinz; Guenther, Andreas; Jenkins, Gisli; Joos, Guy; Magnan, Antoine; Maitre, Bernard; Maus, Ulrich A; Reinhold, Petra; Vernooy, Juanita H J; Richeldi, Luca; Kolb, Martin

2018-05-01

Experimental models are critical for the understanding of lung health and disease and are indispensable for drug development. However, the pathogenetic and clinical relevance of the models is often unclear. Further, the use of animals in biomedical research is controversial from an ethical perspective.The objective of this task force was to issue a statement with research recommendations about lung disease models by facilitating in-depth discussions between respiratory scientists, and to provide an overview of the literature on the available models. Focus was put on their specific benefits and limitations. This will result in more efficient use of resources and greater reduction in the numbers of animals employed, thereby enhancing the ethical standards and translational capacity of experimental research.The task force statement addresses general issues of experimental research (ethics, species, sex, age, ex vivo and in vitro models, gene editing). The statement also includes research recommendations on modelling asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, lung infections, acute lung injury and pulmonary hypertension.The task force stressed the importance of using multiple models to strengthen validity of results, the need to increase the availability of human tissues and the importance of standard operating procedures and data quality. Copyright ©ERS 2018.

The Harvard Automated Phone Task: new performance-based activities of daily living tests for early Alzheimer's disease.

PubMed

Marshall, Gad A; Dekhtyar, Maria; Bruno, Jonathan M; Jethwani, Kamal; Amariglio, Rebecca E; Johnson, Keith A; Sperling, Reisa A; Rentz, Dorene M

2015-12-01

Impairment in activities of daily living is a major burden for Alzheimer's disease dementia patients and caregivers. Multiple subjective scales and a few performance-based instruments have been validated and proven to be reliable in measuring instrumental activities of daily living in Alzheimer's disease dementia but less so in amnestic mild cognitive impairment and preclinical Alzheimer's disease. To validate the Harvard Automated Phone Task, a new performance-based activities of daily living test for early Alzheimer's disease, which assesses high level tasks that challenge seniors in daily life. In a cross-sectional study, the Harvard Automated Phone Task was associated with demographics and cognitive measures through univariate and multivariate analyses; ability to discriminate across diagnostic groups was assessed; test-retest reliability with the same and alternate versions was assessed in a subset of participants; and the relationship with regional cortical thickness was assessed in a subset of participants. Academic clinical research center. One hundred and eighty two participants were recruited from the community (127 clinically normal elderly and 45 young normal participants) and memory disorders clinics at Brigham and Women's Hospital and Massachusetts General Hospital (10 participants with mild cognitive impairment). As part of the Harvard Automated Phone Task, participants navigated an interactive voice response system to refill a prescription (APT-Script), select a new primary care physician (APT-PCP), and make a bank account transfer and payment (APT-Bank). The 3 tasks were scored based on time, errors, and repetitions from which composite z-scores were derived, as well as a separate report of correct completion of the task. We found that the Harvard Automated Phone Task discriminated well between diagnostic groups (APT-Script: p=0.002; APT-PCP: p<0.001; APT-Bank: p=0.02), had an incremental level of difficulty, and had excellent test-retest reliability (Cronbach's α values of 0.81 to 0.87). Within the clinically normal elderly, there were significant associations in multivariate models between performance on the Harvard Automated Phone Task and executive function (APT-PCP: p<0.001), processing speed (APT-Script: p=0.005), and regional cortical atrophy (APT-PCP: p=0.001; no significant association with APT-Script) independent of hearing acuity, motor speed, age, race, education, and premorbid intelligence. Our initial experience with the Harvard Automated Phone Task, which consists of ecologically valid, easily-administered measures of daily activities, suggests that these tasks could be useful for screening and tracking the earliest functional alterations in preclinical and early prodromal AD.

Reflections in the clinical practice.

PubMed

Borrell-Carrió, F; Hernández-Clemente, J C

2014-03-01

The purpose of this article is to analyze some models of expert decision and their impact on the clinical practice. We have analyzed decision-making considering the cognitive aspects (explanatory models, perceptual skills, analysis of the variability of a phenomenon, creating habits and inertia of reasoning and declarative models based on criteria). We have added the importance of emotions in decision making within highly complex situations, such as those occurring within the clinical practice. The quality of the reflective act depends, among other factors, on the ability of metacognition (thinking about what we think). Finally, we propose an educational strategy based on having a task supervisor and rectification scenarios to improve the quality of medical decision making. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Relating UMLS semantic types and task-based ontology to computer-interpretable clinical practice guidelines.

PubMed

Kumar, Anand; Ciccarese, Paolo; Quaglini, Silvana; Stefanelli, Mario; Caffi, Ezio; Boiocchi, Lorenzo

2003-01-01

Medical knowledge in clinical practice guideline (GL) texts is the source of task-based computer-interpretable clinical guideline models (CIGMs). We have used Unified Medical Language System (UMLS) semantic types (STs) to understand the percentage of GL text which belongs to a particular ST. We also use UMLS semantic network together with the CIGM-specific ontology to derive a semantic meaning behind the GL text. In order to achieve this objective, we took nine GL texts from the National Guideline Clearinghouse (NGC) and marked up the text dealing with a particular ST. The STs we took into consideration were restricted taking into account the requirements of a task-based CIGM. We used DARPA Agent Markup Language and Ontology Inference Layer (DAML + OIL) to create the UMLS and CIGM specific semantic network. For the latter, as a bench test, we used the 1999 WHO-International Society of Hypertension Guidelines for the Management of Hypertension. We took into consideration the UMLS STs closest to the clinical tasks. The percentage of the GL text dealing with the ST "Health Care Activity" and subtypes "Laboratory Procedure", "Diagnostic Procedure" and "Therapeutic or Preventive Procedure" were measured. The parts of text belonging to other STs or comments were separated. A mapping of terms belonging to other STs was done to the STs under "HCA" for representation in DAML + OIL. As a result, we found that the three STs under "HCA" were the predominant STs present in the GL text. In cases where the terms of related STs existed, they were mapped into one of the three STs. The DAML + OIL representation was able to describe the hierarchy in task-based CIGMs. To conclude, we understood that the three STs could be used to represent the semantic network of the task-bases CIGMs. We identified some mapping operators which could be used for the mapping of other STs into these.

Improving our understanding of multi-tasking in healthcare: Drawing together the cognitive psychology and healthcare literature.

PubMed

Douglas, Heather E; Raban, Magdalena Z; Walter, Scott R; Westbrook, Johanna I

2017-03-01

Multi-tasking is an important skill for clinical work which has received limited research attention. Its impacts on clinical work are poorly understood. In contrast, there is substantial multi-tasking research in cognitive psychology, driver distraction, and human-computer interaction. This review synthesises evidence of the extent and impacts of multi-tasking on efficiency and task performance from health and non-healthcare literature, to compare and contrast approaches, identify implications for clinical work, and to develop an evidence-informed framework for guiding the measurement of multi-tasking in future healthcare studies. The results showed healthcare studies using direct observation have focused on descriptive studies to quantify concurrent multi-tasking and its frequency in different contexts, with limited study of impact. In comparison, non-healthcare studies have applied predominantly experimental and simulation designs, focusing on interleaved and concurrent multi-tasking, and testing theories of the mechanisms by which multi-tasking impacts task efficiency and performance. We propose a framework to guide the measurement of multi-tasking in clinical settings that draws together lessons from these siloed research efforts. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Task sharing within a managed clinical network to improve child health in Malawi.

PubMed

O'Hare, Bernadette; Phiri, Ajib; Lang, Hans-Joerg; Friesen, Hanny; Kennedy, Neil; Kawaza, Kondwani; Jana, Collins E; Chirambo, George; Mulwafu, Wakisa; Heikens, Geert T; Mipando, Mwapatsa

2015-07-21

Eighty per cent of Malawi's 8 million children live in rural areas, and there is an extensive tiered health system infrastructure from village health clinics to district hospitals which refers patients to one of the four central hospitals. The clinics and district hospitals are staffed by nurses, non-physician clinicians and recently qualified doctors. There are 16 paediatric specialists working in two of the four central hospitals which serve the urban population as well as accepting referrals from district hospitals. In order to provide expert paediatric care as close to home as possible, we describe our plan to task share within a managed clinical network and our hypothesis that this will improve paediatric care and child health. Managed clinical networks have been found to improve equity of care in rural districts and to ensure that the correct care is provided as close to home as possible. A network for paediatric care in Malawi with mentoring of non-physician clinicians based in a district hospital by paediatricians based at the central hospitals will establish and sustain clinical referral pathways in both directions. Ultimately, the plan envisages four managed paediatric clinical networks, each radiating from one of Malawi's four central hospitals and covering the entire country. This model of task sharing within four hub-and-spoke networks may facilitate wider dissemination of scarce expertise and improve child healthcare in Malawi close to the child's home. Funding has been secured to train sufficient personnel to staff all central and district hospitals in Malawi with teams of paediatric specialists in the central hospitals and specialist non-physician clinicians in each government district hospital. The hypothesis will be tested using a natural experiment model. Data routinely collected by the Ministry of Health will be corroborated at the district. This will include case fatality rates for common childhood illness, perinatal mortality and process indicators. Data from different districts will be compared at baseline and annually until 2020 as the specialists of both cadres take up posts. If a managed clinical network improves child healthcare in Malawi, it may be a potential model for the other countries in sub-Saharan Africa with similar cadres in their healthcare system and face similar challenges in terms of scarcity of specialists.

Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.

PubMed

Rios, Anthony; Kavuluru, Ramakanth

2017-11-01

The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes our methods, results, and experiences based on our participation in the second track of the shared task. Classical methods of text classification usually fall into one of three problem types: binary, multi-class, and multi-label classification. In this effort, we study ordinal regression problems with text data where misclassifications are penalized differently based on how far apart the ground truth and model predictions are on the ordinal scale. Specifically, we present our entries (methods and results) in the N-GRID shared task in predicting research domain criteria (RDoC) positive valence ordinal symptom severity scores (absent, mild, moderate, and severe) from psychiatric notes. We propose a novel convolutional neural network (CNN) model designed to handle ordinal regression tasks on psychiatric notes. Broadly speaking, our model combines an ordinal loss function, a CNN, and conventional feature engineering (wide features) into a single model which is learned end-to-end. Given interpretability is an important concern with nonlinear models, we apply a recent approach called locally interpretable model-agnostic explanation (LIME) to identify important words that lead to instance specific predictions. Our best model entered into the shared task placed third among 24 teams and scored a macro mean absolute error (MMAE) based normalized score (100·(1-MMAE)) of 83.86. Since the competition, we improved our score (using basic ensembling) to 85.55, comparable with the winning shared task entry. Applying LIME to model predictions, we demonstrate the feasibility of instance specific prediction interpretation by identifying words that led to a particular decision. In this paper, we present a method that successfully uses wide features and an ordinal loss function applied to convolutional neural networks for ordinal text classification specifically in predicting psychiatric symptom severity scores. Our approach leads to excellent performance on the N-GRID shared task and is also amenable to interpretability using existing model-agnostic approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

The Association of Clinic-Based Mobility Tasks and Measures of Community Performance and Risk.

PubMed

Callisaya, Michele L; Verghese, Joe

2018-01-10

Gait speed is recognized as an important predictor of adverse outcomes in older people. However, it is unknown whether other more complex mobility tasks are better predictors of such outcomes. To examine a range of clinic-based mobility tests and determine which were most strongly associated with measures of community performance and risk (CP&R). Cross-sectional study. Central Control Mobility and Aging Study, Westchester County, New York. Aged ≥65 years (n = 424). Clinic-based mobility measures included gait speed measured during normal and dual-task conditions, the Floor Maze Immediate and Delay tasks, and stair ascending and descending. CP&R measures were self-reported by the use of standardized questionnaires and classified into measures of performance (distance walked, travel outside one's home [life space], activities of daily living, and participation in cognitive leisure activities) or risk (balance confidence, fear of falling, and past falls). Linear and logistic regression were used to examine associations between the clinic-based mobility measures and CP&R measures adjusting for covariates. The mean age of the sample was 77.8 (SD 6.4) years, and 55.2% (n = 234) were female. In final models, faster normal walking speed was most strongly associated with 5 of the 7 community measures (greater distance walked, greater life space, better activities of daily living function, higher balance confidence, and less fear of falling; all P < .05). More complex tasks (walking while talking and maze immediate) were associated with cognitive leisure activity (P < .05), and ascending stairs was the only measure associated with a history of falls (P < .05). Normal walking speed is a simple and inexpensive clinic-based mobility test that is associated with a wide range of CP&R measures. In addition, poorer performance ascending stairs may assist in identifying those at risk of falls. Poorer performance in more complex mobility tasks (walking while talking and maze immediate) may suggest inability to participate in cognitive leisure activities. III. Copyright © 2018 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Emotion dysregulation and autonomic responses to film, rumination, and body awareness: Extending psychophysiological research to a naturalistic clinical setting and a chemically dependent female sample.

PubMed

Crowell, Sheila E; Price, Cynthia J; Puzia, Megan E; Yaptangco, Mona; Cheng, Sunny Chieh

2017-05-01

Substance use is a complex clinical problem characterized by emotion dysregulation and daily challenges that can interfere with laboratory research. Thus, few psychophysiological studies examine autonomic and self-report measures of emotion dysregulation with multidiagnostic, chemically dependent samples or extend this work into naturalistic settings. In this study, we used a within-subject design to examine changes in respiratory sinus arrhythmia (RSA), electrodermal activity (EDA), and self-reported affect across three tasks designed to elicit distinct psychophysiological and emotional response patterns. We also examined emotion dysregulation as a moderator of psychophysiological responses. Participants include 116 women with multiple comorbid mental health conditions enrolled in substance use treatment, many of whom also reported high emotion dysregulation. Participants were assessed in the treatment setting and completed three tasks: watching a sad movie clip, rumination on a stressful event, and a mindful interoceptive awareness meditation. Multilevel models were used to examine changes from resting baselines to the tasks. During the film, results indicate a significant decrease in RSA and an increase in EDA. For the rumination task, participants showed a decrease in RSA but no EDA response. For the body awareness task, there was an increase in RSA and a decrease in EDA. Emotion dysregulation was associated with differences in baseline RSA but not with EDA or with the slope of response patterns across tasks. Self-reported affect was largely consistent with autonomic patterns. Findings add to the literature on emotion dysregulation, substance use, and the translation of psychophysiological measurements into clinical settings with complex samples. © 2017 Society for Psychophysiological Research.

Kinematic measures of Arm-trunk movements during unilateral and bilateral reaching predict clinically important change in perceived arm use in daily activities after intensive stroke rehabilitation.

PubMed

Chen, Hao-ling; Lin, Keh-chung; Liing, Rong-jiuan; Wu, Ching-yi; Chen, Chia-ling

2015-09-21

Kinematic analysis has been used to objectively evaluate movement patterns, quality, and strategies during reaching tasks. However, no study has investigated whether kinematic variables during unilateral and bilateral reaching tasks predict a patient's perceived arm use during activities of daily living (ADL) after an intensive intervention. Therefore, this study investigated whether kinematic measures during unilateral and bilateral reaching tasks before an intervention can predict clinically meaningful improvement in perceived arm use during ADL after intensive poststroke rehabilitation. The study was a secondary analysis of 120 subjects with chronic stroke who received 90-120 min of intensive intervention every weekday for 3-4 weeks. Reaching kinematics during unilateral and bilateral tasks and the Motor Activity Log (MAL) were evaluated before and after the intervention. Kinematic variables explained 22 and 11 % of the variance in actual amount of use (AOU) and quality of movement (QOM), respectively, of MAL improvement during unilateral reaching tasks. Kinematic variables also explained 21 and 31 % of the variance in MAL-AOU and MAL-QOM, respectively, during bilateral reaching tasks. Selected kinematic variables, including endpoint variables, trunk involvement, and joint recruitment and interjoint coordination, were significant predictors for improvement in perceived arm use during ADL (P < 0.05). Arm-trunk kinematics may be used to predict clinically meaningful improvement in perceived arm use during ADL after intensive rehabilitation. Involvement of interjoint coordination and trunk control variables as predictors in bilateral reaching models indicates that a high level of motor control (i.e., multijoint coordination) and trunk stability may be important in obtaining treatment gains in arm use, especially for bilateral daily activities, in intensive rehabilitation after stroke.

Interpretable Deep Models for ICU Outcome Prediction

PubMed Central

Che, Zhengping; Purushotham, Sanjay; Khemani, Robinder; Liu, Yan

2016-01-01

Exponential surge in health care data, such as longitudinal data from electronic health records (EHR), sensor data from intensive care unit (ICU), etc., is providing new opportunities to discover meaningful data-driven characteristics and patterns ofdiseases. Recently, deep learning models have been employedfor many computational phenotyping and healthcare prediction tasks to achieve state-of-the-art performance. However, deep models lack interpretability which is crucial for wide adoption in medical research and clinical decision-making. In this paper, we introduce a simple yet powerful knowledge-distillation approach called interpretable mimic learning, which uses gradient boosting trees to learn interpretable models and at the same time achieves strong prediction performance as deep learning models. Experiment results on Pediatric ICU dataset for acute lung injury (ALI) show that our proposed method not only outperforms state-of-the-art approaches for morality and ventilator free days prediction tasks but can also provide interpretable models to clinicians. PMID:28269832

Open Globe Injury Patient Identification in Warfare Clinical Notes1

PubMed Central

Apostolova, Emilia; White, Helen A.; Morris, Patty A.; Eliason, David A.; Velez, Tom

2017-01-01

The aim of this study is to utilize the Defense and Veterans Eye Injury and Vision Registry clinical data derived from DoD and VA medical systems which include documentation of care while in combat, and develop methods for comprehensive and reliable Open Globe Injury (OGI) patient identification. In particular, we focus on the use of free-form clinical notes, since structured data, such as diagnoses or procedure codes, as found in early post-trauma clinical records, may not be a comprehensive and reliable indicator of OGIs. The challenges of the task include low incidence rate (few positive examples), idiosyncratic military ophthalmology vocabulary, extreme brevity of notes, specialized abbreviations, typos and misspellings. We modeled the problem as a text classification task and utilized a combination of supervised learning (SVMs) and word embeddings learnt in a unsupervised manner, achieving a precision of 92.50% and a recall of89.83%o. The described techniques are applicable to patient cohort identification with limited training data and low incidence rate. PMID:29854104

Using narrative as a bridge: linking language processing models with real-life communication.

PubMed

Whitworth, Anne

2010-02-01

In chronic aphasia, maximizing generalization of improved language abilities from clinical tasks to everyday communication can require the same systematic planning process as the early stages of therapy, often drawing on additional areas of knowledge and successes from other clinical populations. The use of narrative structure is shown here to be a useful framework for building on the developments within sentence processing impairments in aphasia and creating a bridge to more real-life language tasks. An intervention based on narrative structure is described with two people with different language profiles and at different stages of the chronic aphasia spectrum. The insights gained in assessing language ability, underpinning intervention, and capturing therapeutic changes are demonstrated. Thieme Medical Publishers.

Decision Analysis of the Benefits and Costs of Screening for Prostate Cancer

DTIC Science & Technology

2014-08-01

waiting (WW) as experienced in the PIVOT study or active surveillance (AS), radical prostatectomy (RP), radiation therapy (IMRT), and brachytherapy...strategies for low-risk, clinically localized prostate cancer. In the initial iteration of this model, the strategies studied included active surveillance...with regard to modeling PSA kinetics. Task 1.4 Calibrate the model using data from published studies of the natural history of conservatively- treated

A model to teach concomitant patient communication during psychomotor skill development.

PubMed

Nicholls, Delwyn; Sweet, Linda; Muller, Amanda; Hyett, Jon

2018-01-01

Many health professionals use psychomotor or task-based skills in clinical practice that require concomitant communication with a conscious patient. Verbally engaging with the patient requires highly developed verbal communication skills, enabling the delivery of patient-centred care. Historically, priority has been given to learning the psychomotor skills essential to clinical practice. However, there has been a shift towards also ensuring competent communication with the patient during skill performance. While there is literature outlining the steps to teach and learn verbal communication skills, little is known about the most appropriate instructional approach to teach how to verbally engage with the patient when also learning to perform a task. A literature review was performed and it identified that there was no model or proven approach which could be used to integrate the learning of both psychomotor and communication skills. This paper reviews the steps to teach a communication skill and provides a suggested model to guide the acquisition and development of the concomitant -communication skills required with a patient at the time a psychomotor skill is performed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Individuals with clinically significant insomnia symptoms are characterised by a negative sleep-related expectancy bias: Results from a cognitive-experimental assessment.

PubMed

Courtauld, Hannah; Notebaert, Lies; Milkins, Bronwyn; Kyle, Simon D; Clarke, Patrick J F

2017-08-01

Cognitive models of insomnia consistently suggest that negative expectations regarding the consequences of poor sleep contribute to the maintenance of insomnia. To date, however, no research has sought to determine whether insomnia is indeed characterised by such a negative sleep-related expectancy bias, using objective cognitive assessment tasks which are more immune to response biases than questionnaire assessments. Therefore, the current study employed a reaction-time task assessing biased expectations among a group with clinically significant insomnia symptoms (n = 30) and a low insomnia symptoms group (n = 40). The task involved the presentation of scenarios describing the consequences of poor sleep, and non-sleep related activities, which could be resolved in a benign or a negative manner. The results demonstrated that the high insomnia symptoms group were disproportionately fast to resolve sleep-related scenarios in line with negative outcomes, as compared to benign outcomes, relative to the low insomnia symptoms group. The two groups did not differ in their pattern of resolving non-sleep related scenarios. This pattern of findings is entirely consistent with a sleep-specific expectancy bias operating in individuals with clinically significant insomnia symptoms, and highlights the potential of cognitive-experimental assessment tasks to objectively index patterns of biased cognition in insomnia. Copyright © 2017 Elsevier Ltd. All rights reserved.

Measuring treatment effects on dual-task performance: a framework for research and clinical practice

PubMed Central

Plummer, Prudence; Eskes, Gail

2015-01-01

The relevance of dual-task walking to everyday ambulation is widely acknowledged, and numerous studies have demonstrated that dual-task interference can significantly impact recovery of functional walking in people with neurological disorders. The magnitude and direction of dual-task interference is influenced by the interaction between the two tasks, including how individuals spontaneously prioritize their attention. Therefore, to accurately interpret and characterize dual-task interference and identify changes over time, it is imperative to evaluate single and dual-task performance in both tasks, as well as the tasks relative to each other. Yet, reciprocal dual-task effects (DTE) are frequently ignored. The purpose of this perspective paper is to present a framework for measuring treatment effects on dual-task interference, specifically taking into account the interactions between the two tasks and how this can provide information on whether overall dual-task capacity has improved or a different attentional strategy has been adopted. In discussing the clinical implications of using this framework, we provide specific examples of using this method and provide some explicit recommendations for research and clinical practice. PMID:25972801

Blackboard architecture for medical image interpretation

NASA Astrophysics Data System (ADS)

Davis, Darryl N.; Taylor, Christopher J.

1991-06-01

There is a growing interest in using sophisticated knowledge-based systems for biomedical image interpretation. We present a principled attempt to use artificial intelligence methodologies in interpreting lateral skull x-ray images. Such radiographs are routinely used in cephalometric analysis to provide quantitative measurements useful to clinical orthodontists. Manual and interactive methods of analysis are known to be error prone and previous attempts to automate this analysis typically fail to capture the expertise and adaptability required to cope with the variability in biological structure and image quality. An integrated model-based system has been developed which makes use of a blackboard architecture and multiple knowledge sources. A model definition interface allows quantitative models, of feature appearance and location, to be built from examples as well as more qualitative modelling constructs. Visual task definition and blackboard control modules allow task-specific knowledge sources to act on information available to the blackboard in a hypothesise and test reasoning cycle. Further knowledge-based modules include object selection, location hypothesis, intelligent segmentation, and constraint propagation systems. Alternative solutions to given tasks are permitted.

XML-based scripting of multimodality image presentations in multidisciplinary clinical conferences

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Allada, Vivekanand; Dahlbom, Magdalena; Marcus, Phillip; Fine, Ian; Lapstra, Lorelle

2002-05-01

We developed a multi-modality image presentation software for display and analysis of images and related data from different imaging modalities. The software is part of a cardiac image review and presentation platform that supports integration of digital images and data from digital and analog media such as videotapes, analog x-ray films and 35 mm cine films. The software supports standard DICOM image files as well as AVI and PDF data formats. The system is integrated in a digital conferencing room that includes projections of digital and analog sources, remote videoconferencing capabilities, and an electronic whiteboard. The goal of this pilot project is to: 1) develop a new paradigm for image and data management for presentation in a clinically meaningful sequence adapted to case-specific scenarios, 2) design and implement a multi-modality review and conferencing workstation using component technology and customizable 'plug-in' architecture to support complex review and diagnostic tasks applicable to all cardiac imaging modalities and 3) develop an XML-based scripting model of image and data presentation for clinical review and decision making during routine clinical tasks and multidisciplinary clinical conferences.

Holistic rubric vs. analytic rubric for measuring clinical performance levels in medical students.

PubMed

Yune, So Jung; Lee, Sang Yeoup; Im, Sun Ju; Kam, Bee Sung; Baek, Sun Yong

2018-06-05

Task-specific checklists, holistic rubrics, and analytic rubrics are often used for performance assessments. We examined what factors evaluators consider important in holistic scoring of clinical performance assessment, and compared the usefulness of applying holistic and analytic rubrics respectively, and analytic rubrics in addition to task-specific checklists based on traditional standards. We compared the usefulness of a holistic rubric versus an analytic rubric in effectively measuring the clinical skill performances of 126 third-year medical students who participated in a clinical performance assessment conducted by Pusan National University School of Medicine. We conducted a questionnaire survey of 37 evaluators who used all three evaluation methods-holistic rubric, analytic rubric, and task-specific checklist-for each student. The relationship between the scores on the three evaluation methods was analyzed using Pearson's correlation. Inter-rater agreement was analyzed by Kappa index. The effect of holistic and analytic rubric scores on the task-specific checklist score was analyzed using multiple regression analysis. Evaluators perceived accuracy and proficiency to be major factors in objective structured clinical examinations evaluation, and history taking and physical examination to be major factors in clinical performance examinations evaluation. Holistic rubric scores were highly related to the scores of the task-specific checklist and analytic rubric. Relatively low agreement was found in clinical performance examinations compared to objective structured clinical examinations. Meanwhile, the holistic and analytic rubric scores explained 59.1% of the task-specific checklist score in objective structured clinical examinations and 51.6% in clinical performance examinations. The results show the usefulness of holistic and analytic rubrics in clinical performance assessment, which can be used in conjunction with task-specific checklists for more efficient evaluation.

Assessment of CT image quality using a Bayesian approach

NASA Astrophysics Data System (ADS)

Reginatto, M.; Anton, M.; Elster, C.

2017-08-01

One of the most promising approaches for evaluating CT image quality is task-specific quality assessment. This involves a simplified version of a clinical task, e.g. deciding whether an image belongs to the class of images that contain the signature of a lesion or not. Task-specific quality assessment can be done by model observers, which are mathematical procedures that carry out the classification task. The most widely used figure of merit for CT image quality is the area under the ROC curve (AUC), a quantity which characterizes the performance of a given model observer. In order to estimate AUC from a finite sample of images, different approaches from classical statistics have been suggested. The goal of this paper is to introduce task-specific quality assessment of CT images to metrology and to propose a novel Bayesian estimation of AUC for the channelized Hotelling observer (CHO) applied to the task of detecting a lesion at a known image location. It is assumed that signal-present and signal-absent images follow multivariate normal distributions with the same covariance matrix. The Bayesian approach results in a posterior distribution for the AUC of the CHO which provides in addition a complete characterization of the uncertainty of this figure of merit. The approach is illustrated by its application to both simulated and experimental data.

Information technology resource management in radiation oncology.

PubMed

Siochi, R Alfredo; Balter, Peter; Bloch, Charles D; Bushe, Harry S; Mayo, Charles S; Curran, Bruce H; Feng, Wenzheng; Kagadis, George C; Kirby, Thomas H; Stern, Robin L

2009-09-02

The ever-increasing data demands in a radiation oncology (RO) clinic require medical physicists to have a clearer understanding of the information technology (IT) resource management issues. Clear lines of collaboration and communication among administrators, medical physicists, IT staff, equipment service engineers and vendors need to be established. In order to develop a better understanding of the clinical needs and responsibilities of these various groups, an overview of the role of IT in RO is provided. This is followed by a list of IT related tasks and a resource map. The skill set and knowledge required to implement these tasks are described for the various RO professionals. Finally, various models for assessing one's IT resource needs are described. The exposition of ideas in this white paper is intended to be broad, in order to raise the level of awareness of the RO community; the details behind these concepts will not be given here and are best left to future task group reports.

A report from the pediatric formulations task force: perspectives on the state of child-friendly oral dosage forms.

PubMed

Zajicek, Anne; Fossler, Michael J; Barrett, Jeffrey S; Worthington, Jeffrey H; Ternik, Robert; Charkoftaki, Georgia; Lum, Susan; Breitkreutz, Jörg; Baltezor, Mike; Macheras, Panos; Khan, Mansoor; Agharkar, Shreeram; MacLaren, David Douglas

2013-10-01

Despite the fact that a significant percentage of the population is unable to swallow tablets and capsules, these dosage forms continue to be the default standard. These oral formulations fail many patients, especially children, because of large tablet or capsule size, poor palatability, and lack of correct dosage strength. The clinical result is often lack of adherence and therapeutic failure. The American Association of Pharmaceutical Scientists formed a Pediatric Formulations Task Force, consisting of members with various areas of expertise including pediatrics, formulation development, clinical pharmacology, and regulatory science, in order to identify pediatric, manufacturing, and regulatory issues and areas of needed research and regulatory guidance. Dosage form and palatability standards for all pediatric ages, relative bioavailability requirements, and small batch manufacturing capabilities and creation of a viable economic model were identified as particular needs. This assessment is considered an important first step for a task force seeking creative approaches to providing more appropriate oral formulations for children.

Ambulatory Antibiotic Stewardship through a Human Factors Engineering Approach: A Systematic Review.

PubMed

Keller, Sara C; Tamma, Pranita D; Cosgrove, Sara E; Miller, Melissa A; Sateia, Heather; Szymczak, Julie; Gurses, Ayse P; Linder, Jeffrey A

2018-01-01

In the United States, most antibiotics are prescribed in ambulatory settings. Human factors engineering, which explores interactions between people and the place where they work, has successfully improved quality of care. However, human factors engineering models have not been explored to frame what is known about ambulatory antibiotic stewardship (AS) interventions and barriers and facilitators to their implementation. We conducted a systematic review and searched OVID MEDLINE, Embase, Scopus, Web of Science, and CINAHL to identify controlled interventions and qualitative studies of ambulatory AS and determine whether and how they incorporated principles from a human factors engineering model, the Systems Engineering Initiative for Patient Safety 2.0 model. This model describes how a work system (ambulatory clinic) contributes to a process (antibiotic prescribing) that leads to outcomes. The work system consists of 5 components, tools and technology, organization, person, tasks, and environment, within an external environment. Of 1,288 abstracts initially identified, 42 quantitative studies and 17 qualitative studies met inclusion criteria. Effective interventions focused on tools and technology (eg, clinical decision support and point-of-care testing), the person (eg, clinician education), organization (eg, audit and feedback and academic detailing), tasks (eg, delayed antibiotic prescribing), the environment (eg, commitment posters), and the external environment (media campaigns). Studies have not focused on clinic-wide approaches to AS. A human factors engineering approach suggests that investigating the role of the clinic's processes or physical layout or external pressures' role in antibiotic prescribing may be a promising way to improve ambulatory AS. © Copyright 2018 by the American Board of Family Medicine.

Predictors of Processing-Based Task Performance in Bilingual and Monolingual Children

PubMed Central

Buac, Milijana; Gross, Megan; Kaushanskaya, Margarita

2016-01-01

In the present study we examined performance of bilingual Spanish-English-speaking and monolingual English-speaking school-age children on a range of processing-based measures within the framework of Baddeley’s working memory model. The processing-based measures included measures of short-term memory, measures of working memory, and a novel word-learning task. Results revealed that monolinguals outperformed bilinguals on the short-term memory tasks but not the working memory and novel word-learning tasks. Further, children’s vocabulary skills and socioeconomic status (SES) were more predictive of processing-based task performance in the bilingual group than the monolingual group. Together, these findings indicate that processing-based tasks that engage verbal working memory rather than short-term memory may be better-suited for diagnostic purposes with bilingual children. However, even verbal working memory measures are sensitive to bilingual children’s language-specific knowledge and demographic characteristics, and therefore may have limited clinical utility. PMID:27179914

Developing a business-practice model for pharmacy services in ambulatory settings.

PubMed

Harris, Ila M; Baker, Ed; Berry, Tricia M; Halloran, Mary Ann; Lindauer, Kathleen; Ragucci, Kelly R; McGivney, Melissa Somma; Taylor, A Thomas; Haines, Stuart T

2008-02-01

A business-practice model is a guide, or toolkit, to assist managers and clinical pharmacy practitioners in the exploration, proposal, development and implementation of new clinical pharmacy services and/or the enhancement of existing services. This document was developed by the American College of Clinical Pharmacy Task Force on Ambulatory Practice to assist clinical pharmacy practitioners and administrators in the development of business-practice models for new and existing clinical pharmacy services in ambulatory settings. This document provides detailed instructions, examples, and resources on conducting a market assessment and a needs assessment, types of clinical services, operations, legal and regulatory issues, marketing and promotion, service development and exit plan, evaluation of service outcomes, and financial considerations in the development of a clinical pharmacy service in the ambulatory environment. Available literature is summarized, and an appendix provides valuable citations and resources. As ambulatory care practices continue to evolve, there will be increased knowledge of how to initiate and expand the services. This document is intended to serve as an essential resource to assist in the growth and development of clinical pharmacy services in the ambulatory environment.

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

PubMed Central

Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

Influence of study design on digital pathology image quality evaluation: the need to define a clinical task

PubMed Central

Platiša, Ljiljana; Brantegem, Leen Van; Kumcu, Asli; Ducatelle, Richard; Philips, Wilfried

2017-01-01

Abstract. Despite the current rapid advance in technologies for whole slide imaging, there is still no scientific consensus on the recommended methodology for image quality assessment of digital pathology slides. For medical images in general, it has been recommended to assess image quality in terms of doctors’ success rates in performing a specific clinical task while using the images (clinical image quality, cIQ). However, digital pathology is a new modality, and already identifying the appropriate task is difficult. In an alternative common approach, humans are asked to do a simpler task such as rating overall image quality (perceived image quality, pIQ), but that involves the risk of nonclinically relevant findings due to an unknown relationship between the pIQ and cIQ. In this study, we explored three different experimental protocols: (1) conducting a clinical task (detecting inclusion bodies), (2) rating image similarity and preference, and (3) rating the overall image quality. Additionally, within protocol 1, overall quality ratings were also collected (task-aware pIQ). The experiments were done by diagnostic veterinary pathologists in the context of evaluating the quality of hematoxylin and eosin-stained digital pathology slides of animal tissue samples under several common image alterations: additive noise, blurring, change in gamma, change in color saturation, and JPG compression. While the size of our experiments was small and prevents drawing strong conclusions, the results suggest the need to define a clinical task. Importantly, the pIQ data collected under protocols 2 and 3 did not always rank the image alterations the same as their cIQ from protocol 1, warning against using conventional pIQ to predict cIQ. At the same time, there was a correlation between the cIQ and task-aware pIQ ratings from protocol 1, suggesting that the clinical experiment context (set by specifying the clinical task) may affect human visual attention and bring focus to their criteria of image quality. Further research is needed to assess whether and for which purposes (e.g., preclinical testing) task-aware pIQ ratings could substitute cIQ for a given clinical task. PMID:28653011

Influence of study design on digital pathology image quality evaluation: the need to define a clinical task.

PubMed

Platiša, Ljiljana; Brantegem, Leen Van; Kumcu, Asli; Ducatelle, Richard; Philips, Wilfried

2017-04-01

Despite the current rapid advance in technologies for whole slide imaging, there is still no scientific consensus on the recommended methodology for image quality assessment of digital pathology slides. For medical images in general, it has been recommended to assess image quality in terms of doctors' success rates in performing a specific clinical task while using the images (clinical image quality, cIQ). However, digital pathology is a new modality, and already identifying the appropriate task is difficult. In an alternative common approach, humans are asked to do a simpler task such as rating overall image quality (perceived image quality, pIQ), but that involves the risk of nonclinically relevant findings due to an unknown relationship between the pIQ and cIQ. In this study, we explored three different experimental protocols: (1) conducting a clinical task (detecting inclusion bodies), (2) rating image similarity and preference, and (3) rating the overall image quality. Additionally, within protocol 1, overall quality ratings were also collected (task-aware pIQ). The experiments were done by diagnostic veterinary pathologists in the context of evaluating the quality of hematoxylin and eosin-stained digital pathology slides of animal tissue samples under several common image alterations: additive noise, blurring, change in gamma, change in color saturation, and JPG compression. While the size of our experiments was small and prevents drawing strong conclusions, the results suggest the need to define a clinical task. Importantly, the pIQ data collected under protocols 2 and 3 did not always rank the image alterations the same as their cIQ from protocol 1, warning against using conventional pIQ to predict cIQ. At the same time, there was a correlation between the cIQ and task-aware pIQ ratings from protocol 1, suggesting that the clinical experiment context (set by specifying the clinical task) may affect human visual attention and bring focus to their criteria of image quality. Further research is needed to assess whether and for which purposes (e.g., preclinical testing) task-aware pIQ ratings could substitute cIQ for a given clinical task.

Usability assessment of an electronic health record in a comprehensive dental clinic.

PubMed

Suebnukarn, Siriwan; Rittipakorn, Pawornwan; Thongyoi, Budsara; Boonpitak, Kwanwong; Wongsapai, Mansuang; Pakdeesan, Panu

2013-12-01

In this paper we present the development and usability of an electronic health record (EHR) system in a comprehensive dental clinic.The graphic user interface of the system was designed to consider the concept of cognitive ergonomics.The cognitive task analysis was used to evaluate the user interface of the EHR by identifying all sub-tasks and classifying them into mental or physical operators, and to predict task execution time required to perform the given task. We randomly selected 30 cases that had oral examinations for routine clinical care in a comprehensive dental clinic. The results were based on the analysis of 4 prototypical tasks performed by ten EHR users. The results showed that on average a user needed to go through 27 steps to complete all tasks for one case. To perform all 4 tasks of 30 cases, they spent about 91 min (independent of system response time) for data entry, of which 51.8 min were spent on more effortful mental operators. In conclusion, the user interface can be improved by reducing the percentage of mental effort required for the tasks.

Bordetella pseudohinzii spp. nov. infects C57Bl6 mice

USDA-ARS?s Scientific Manuscript database

Clinical studies rely heavily on mouse models of infection. Precise identification and control of contaminating pathogens that circulate in mouse colonies is an important task. Over the past decade, there have been several reports documenting the isolation of Bordetella spp. from purported pathog...

Is clinical cognition binary or continuous?

PubMed

Norman, Geoffrey; Monteiro, Sandra; Sherbino, Jonathan

2013-08-01

A dominant theory of clinical reasoning is the so-called "dual processing theory," in which the diagnostic process may proceed through a rapid, unconscious, intuitive process (System 1) or a slow, conceptual, analytical process (System 2). Diagnostic errors are thought to arise primarily from cognitive biases originating in System 1. In this issue, Custers points out that this model is unnecessarily restrictive and that it is more likely that diagnostic tasks may proceed through a variety of mental strategies ranging from "analytical" to "intuitive."The authors of this commentary agree that the notion that System 1 and System 2 processes are somehow in competition and will necessarily lead to different conclusions is unnecessarily restrictive. On the other hand, they argue that there is substantial evidence in support of a dual processing model, and that most objections to dual processing theory can be easily accommodated by simply presuming that both processes operate in concertand that solving any task may rely to varying degrees on both processes.

Dual tasking and stuttering: from the laboratory to the clinic.

PubMed

Metten, Christine; Bosshardt, Hans-Georg; Jones, Mark; Eisenhuth, John; Block, Susan; Carey, Brenda; O'Brian, Sue; Packman, Ann; Onslow, Mark; Menzies, Ross

2011-01-01

The aim of the three studies in this article was to develop a way to include dual tasking in speech restructuring treatment for persons who stutter (PWS). It is thought that this may help clients maintain the benefits of treatment in the real world, where attentional resources are frequently diverted away from controlling fluency by the demands of other tasks. In Part 1, 17 PWS performed a story-telling task and a computer semantic task simultaneously. Part 2 reports the incorporation of the Part 1 protocol into a handy device for use in a clinical setting (the Dual Task and Stuttering Device, DAS-D). Part 3 is a proof of concept study in which three PWS reported on their experiences of using the device during treatment. In Part 1, stuttering frequency and errors on the computer task both increased under dual task conditions, indicating that the protocol would be appropriate for use in a clinical setting. All three participants in Part 3 reported positively on their experiences using the DAS-D. Dual tasking during treatment using the DAS-D appears to be a viable clinical procedure. Further research is required to establish effectiveness.

Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making

PubMed Central

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2016-01-01

Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019

Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

PubMed

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2014-09-01

Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

Promoting the self-regulation of clinical reasoning skills in nursing students.

PubMed

Kuiper, R; Pesut, D; Kautz, D

2009-10-02

The purpose of this paper is to describe the research surrounding the theories and models the authors united to describe the essential components of clinical reasoning in nursing practice education. The research was conducted with nursing students in health care settings through the application of teaching and learning strategies with the Self-Regulated Learning Model (SRL) and the Outcome-Present-State-Test (OPT) Model of Reflective Clinical Reasoning. Standardized nursing languages provided the content and clinical vocabulary for the clinical reasoning task. This descriptive study described the application of the OPT model of clinical reasoning, use of nursing language content, and reflective journals based on the SRL model with 66 undergraduate nursing students over an 8 month period of time. The study tested the idea that self-regulation of clinical reasoning skills can be developed using self-regulation theory and the OPT model. This research supports a framework for effective teaching and learning methods to promote and document learner progress in mastering clinical reasoning skills. Self-regulated Learning strategies coupled with the OPT model suggest benefits of self-observation and self-monitoring during clinical reasoning activities, and pinpoints where guidance is needed for the development of cognitive and metacognitive awareness. Thinking and reasoning about the complexities of patient care needs requires attention to the content, processes and outcomes that make a nursing care difference. These principles and concepts are valuable to clinical decision making for nurses globally as they deal with local, regional, national and international health care issues.

Versatile clinical information system design for emergency departments.

PubMed

Amouh, Teh; Gemo, Monica; Macq, Benoît; Vanderdonckt, Jean; El Gariani, Abdul Wahed; Reynaert, Marc S; Stamatakis, Lambert; Thys, Frédéric

2005-06-01

Compared to other hospital units, the emergency department presents some distinguishing characteristics of its own. Emergency health-care delivery is a collaborative process involving the contribution of several individuals who accomplish their tasks while working autonomously under pressure and sometimes with limited resources. Effective computerization of the emergency department information system presents a real challenge due to the complexity of the scenario. Current computerized support suffers from several problems, including inadequate data models, clumsy user interfaces, and poor integration with other clinical information systems. To tackle such complexity, we propose an approach combining three points of view, namely the transactions (in and out of the department), the (mono and multi) user interfaces and data management. Unlike current systems, we pay particular attention to the user-friendliness and versatility of our system. This means that intuitive user interfaces have been conceived and specific software modeling methodologies have been applied to provide our system with the flexibility and adaptability necessary for the individual and group coordinated tasks. Our approach has been implemented by prototyping a web-based, multiplatform, multiuser, and versatile clinical information system built upon multitier software architecture, using the Java programming language.

Deep Learning: A Primer for Radiologists.

PubMed

Chartrand, Gabriel; Cheng, Phillip M; Vorontsov, Eugene; Drozdzal, Michal; Turcotte, Simon; Pal, Christopher J; Kadoury, Samuel; Tang, An

2017-01-01

Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance. These models are multilayer artificial neural networks, loosely inspired by biologic neural systems. Weighted connections between nodes (neurons) in the network are iteratively adjusted based on example pairs of inputs and target outputs by back-propagating a corrective error signal through the network. For computer vision tasks, convolutional neural networks (CNNs) have proven to be effective. Recently, several clinical applications of CNNs have been proposed and studied in radiology for classification, detection, and segmentation tasks. This article reviews the key concepts of deep learning for clinical radiologists, discusses technical requirements, describes emerging applications in clinical radiology, and outlines limitations and future directions in this field. Radiologists should become familiar with the principles and potential applications of deep learning in medical imaging. © RSNA, 2017.

A model for critical thinking measurement of dental student performance.

PubMed

Johnsen, David C; Finkelstein, Michael W; Marshall, Teresa A; Chalkley, Yvonne M

2009-02-01

The educational application of critical thinking has increased in the last twenty years with programs like problem-based learning. Performance measurement related to the dental student's capacity for critical thinking remains elusive, however. This article offers a model now in use to measure critical thinking applied to patient assessment and treatment planning across the four years of the dental school curriculum and across clinical disciplines. Two elements of the model are described: 1) a critical thinking measurement "cell," and 2) a list of minimally essential steps in critical thinking for patient assessment and treatment planning. Issues pertaining to this model are discussed: adaptations on the path from novice to expert, the role of subjective measurement, variations supportive of the model, and the correlation of individual and institutional assessment. The critical thinking measurement cell consists of interacting performance tasks and measures. The student identifies the step in the process (for example, chief complaint) with objective measurement; the student then applies the step to a patient or case with subjective measurement; the faculty member then combines the objective and subjective measurements into an evaluation on progress toward competence. The activities in the cell are then repeated until all the steps in the process have been addressed. A next task is to determine consistency across the four years and across clinical disciplines.

The Harvard Automated Phone Task: new performance-based activities of daily living tests for early Alzheimer’s disease

PubMed Central

Marshall, Gad A.; Dekhtyar, Maria; Bruno, Jonathan M.; Jethwani, Kamal; Amariglio, Rebecca E.; Johnson, Keith A.; Sperling, Reisa A.; Rentz, Dorene M.

2015-01-01

Background Impairment in activities of daily living is a major burden for Alzheimer’s disease dementia patients and caregivers. Multiple subjective scales and a few performance-based instruments have been validated and proven to be reliable in measuring instrumental activities of daily living in Alzheimer’s disease dementia but less so in amnestic mild cognitive impairment and preclinical Alzheimer’s disease. Objective To validate the Harvard Automated Phone Task, a new performance-based activities of daily living test for early Alzheimer’s disease, which assesses high level tasks that challenge seniors in daily life. Design In a cross-sectional study, the Harvard Automated Phone Task was associated with demographics and cognitive measures through univariate and multivariate analyses; ability to discriminate across diagnostic groups was assessed; test-retest reliability with the same and alternate versions was assessed in a subset of participants; and the relationship with regional cortical thickness was assessed in a subset of participants. Setting Academic clinical research center. Participants One hundred and eighty two participants were recruited from the community (127 clinically normal elderly and 45 young normal participants) and memory disorders clinics at Brigham and Women’s Hospital and Massachusetts General Hospital (10 participants with mild cognitive impairment). Measurements As part of the Harvard Automated Phone Task, participants navigated an interactive voice response system to refill a prescription (APT-Script), select a new primary care physician (APT-PCP), and make a bank account transfer and payment (APT-Bank). The 3 tasks were scored based on time, errors, and repetitions from which composite z-scores were derived, as well as a separate report of correct completion of the task. Results We found that the Harvard Automated Phone Task discriminated well between diagnostic groups (APT-Script: p=0.002; APT-PCP: p<0.001; APT-Bank: p=0.02), had an incremental level of difficulty, and had excellent test-retest reliability (Cronbach’s α values of 0.81 to 0.87). Within the clinically normal elderly, there were significant associations in multivariate models between performance on the Harvard Automated Phone Task and executive function (APT-PCP: p<0.001), processing speed (APT-Script: p=0.005), and regional cortical atrophy (APT-PCP: p=0.001; no significant association with APT-Script) independent of hearing acuity, motor speed, age, race, education, and premorbid intelligence. Conclusions Our initial experience with the Harvard Automated Phone Task, which consists of ecologically valid, easily-administered measures of daily activities, suggests that these tasks could be useful for screening and tracking the earliest functional alterations in preclinical and early prodromal AD. PMID:26665121

Selecting Paradigms From Cognitive Neuroscience for Translation into Use in Clinical Trials: Proceedings of the Third CNTRICS Meeting

PubMed Central

Barch, Deanna M.; Carter, Cameron S.; Arnsten, Amy; Buchanan, Robert W.; Cohen, Jonathan D.; Geyer, Mark; Green, Michael F.; Krystal, John H.; Nuechterlein, Keith; Robbins, Trevor; Silverstein, Steven; Smith, Edward E.; Strauss, Milton; Wykes, Til; Heinssen, Robert

2009-01-01

This overview describes the goals and objectives of the third conference conducted as part of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) initiative. This third conference was focused on selecting specific paradigms from cognitive neuroscience that measured the constructs identified in the first CNTRICS meeting, with the goal of facilitating the translation of these paradigms into use in clinical trials contexts. To identify such paradigms, we had an open nomination process in which the field was asked to nominate potentially relevant paradigms and to provide information on several domains relevant to selecting the most promising tasks for each construct (eg, construct validity, neural bases, psychometrics, availability of animal models). Our goal was to identify 1–2 promising tasks for each of the 11 constructs identified at the first CNTRICS meeting. In this overview article, we describe the on-line survey used to generate nominations for promising tasks, the criteria that were used to select the tasks, the rationale behind the criteria, and the ways in which breakout groups worked together to identify the most promising tasks from among those nominated. This article serves as an introduction to the set of 6 articles included in this special issue that provide information about the specific tasks discussed and selected for the constructs from each of 6 broad domains (working memory, executive control, attention, long-term memory, perception, and social cognition). PMID:19023126

Automated concept-level information extraction to reduce the need for custom software and rules development.

PubMed

D'Avolio, Leonard W; Nguyen, Thien M; Goryachev, Sergey; Fiore, Louis D

2011-01-01

Despite at least 40 years of promising empirical performance, very few clinical natural language processing (NLP) or information extraction systems currently contribute to medical science or care. The authors address this gap by reducing the need for custom software and rules development with a graphical user interface-driven, highly generalizable approach to concept-level retrieval. A 'learn by example' approach combines features derived from open-source NLP pipelines with open-source machine learning classifiers to automatically and iteratively evaluate top-performing configurations. The Fourth i2b2/VA Shared Task Challenge's concept extraction task provided the data sets and metrics used to evaluate performance. Top F-measure scores for each of the tasks were medical problems (0.83), treatments (0.82), and tests (0.83). Recall lagged precision in all experiments. Precision was near or above 0.90 in all tasks. Discussion With no customization for the tasks and less than 5 min of end-user time to configure and launch each experiment, the average F-measure was 0.83, one point behind the mean F-measure of the 22 entrants in the competition. Strong precision scores indicate the potential of applying the approach for more specific clinical information extraction tasks. There was not one best configuration, supporting an iterative approach to model creation. Acceptable levels of performance can be achieved using fully automated and generalizable approaches to concept-level information extraction. The described implementation and related documentation is available for download.

A systematic review of the psychological literature on interruption and its patient safety implications.

PubMed

Li, Simon Y W; Magrabi, Farah; Coiera, Enrico

2012-01-01

To understand the complex effects of interruption in healthcare. As interruptions have been well studied in other domains, the authors undertook a systematic review of experimental studies in psychology and human-computer interaction to identify the task types and variables influencing interruption effects. 63 studies were identified from 812 articles retrieved by systematic searches. On the basis of interruption profiles for generic tasks, it was found that clinical tasks can be distinguished into three broad types: procedural, problem-solving, and decision-making. Twelve experimental variables that influence interruption effects were identified. Of these, six are the most important, based on the number of studies and because of their centrality to interruption effects, including working memory load, interruption position, similarity, modality, handling strategies, and practice effect. The variables are explained by three main theoretical frameworks: the activation-based goal memory model, prospective memory, and multiple resource theory. This review provides a useful starting point for a more comprehensive examination of interruptions potentially leading to an improved understanding about the impact of this phenomenon on patient safety and task efficiency. The authors provide some recommendations to counter interruption effects. The effects of interruption are the outcome of a complex set of variables and should not be considered as uniformly predictable or bad. The task types, variables, and theories should help us better to identify which clinical tasks and contexts are most susceptible and assist in the design of information systems and processes that are resilient to interruption.

Microanalytic Assessment of Self-Regulated Learning During Clinical Reasoning Tasks: Recent Developments and Next Steps.

PubMed

Cleary, Timothy J; Durning, Steven J; Artino, Anthony R

2016-11-01

Helping medical educators obtain and use assessment data to assist medical students, residents, and physicians in reducing diagnostic errors and other forms of ineffective clinical practice is of critical importance. Self-Regulated Learning-Microanalytic Assessment and Training is an assessment-to-intervention framework designed to address this need by generating data about trainees' strategic processes (e.g., focusing on clinical task procedures), regulatory processes (e.g., planning how to do a task), and motivational processes (e.g., increasing confidence for performing a task) as they perform clinical activities. In this article, the authors review several studies that have used an innovative assessment approach, called self-regulated learning (SRL) microanalysis, to generate data about how trainees regulate their thinking and actions during clinical reasoning tasks. Across the studies, initial findings revealed that medical students often do not exhibit strategic thinking and action during clinical reasoning practice tasks even though some regulatory processes (e.g., planning) are predictive of important medical education outcomes. Further, trainees' motivation beliefs, strategic thinking, and self-evaluative judgments tend to shift rapidly during clinical skills practice and may also vary across different parts of a patient encounter. Collectively, these findings underscore the value of dynamically assessing trainees' SRL as they complete clinical tasks. The findings also set the stage for exploring how medical educators can best use SRL microanalytic assessment data to guide remedial practices and the provision of feedback to trainees. Implications and future research directions for connecting assessments to intervention in medical education are discussed.

Training models and status of clinical neuropsychologists in Europe: results of a survey on 30 countries.

PubMed

Hokkanen, Laura; Lettner, Sandra; Barbosa, Fernando; Constantinou, Marios; Harper, Lauren; Kasten, Erich; Mondini, Sara; Persson, Bengt; Varako, Nataliya; Hessen, Erik

2018-06-20

The aims of the study were to analyze the current European situation of specialist education and training within clinical neuropsychology, and the legal and professional status of clinical neuropsychologists in different European countries. An online survey was prepared in 2016 by a Task Force established by the European Federation of Psychological Associations, and representatives of 30 countries gave their responses. Response rate was 76%. Only three countries were reported to regulate the title of clinical neuropsychologist as well as the education and practice of clinical neuropsychologists by law. The most common university degree required to practice clinical neuropsychology was the master's degree; a doctoral degree was required in two countries. The length of the specialist education after the master's degree varied between 12 and 60 months. In one third of the countries, no commonly agreed upon model for specialist education existed. A more systematic training model and a longer duration of training were associated with independence in the work of clinical neuropsychologists. As legal regulation is mostly absent and training models differ, those actively practicing clinical neuropsychology in Europe have a very heterogeneous educational background and skill level. There is a need for a European standardization of specialist training in clinical neuropsychology. Guiding principles for establishing the common core requirements are presented.

Improving Sensitivity to Detect Mild Cognitive Impairment: Cognitive Load Dual-Task Gait Speed Assessment.

PubMed

MacAulay, Rebecca K; Wagner, Mark T; Szeles, Dana; Milano, Nicholas J

2017-07-01

Longitudinal research indicates that cognitive load dual-task gait assessment is predictive of cognitive decline and thus might provide a sensitive measure to screen for mild cognitive impairment (MCI). However, research among older adults being clinically evaluated for cognitive concerns, a defining feature of MCI, is lacking. The present study investigated the effect of performing a cognitive task on normal walking speed in patients presenting to a memory clinic with cognitive complaints. Sixty-one patients with a mean age of 68 years underwent comprehensive neuropsychological testing, clinical interview, and gait speed (simple- and dual-task conditions) assessments. Thirty-four of the 61 patients met criteria for MCI. Repeated measure analyses of covariance revealed that greater age and MCI both significantly associated with slower gait speed, ps<.05. Follow-up analysis indicated that the MCI group had significantly slower dual-task gait speed but did not differ in simple-gait speed. Multivariate linear regression across groups found that executive attention performance accounted for 27.4% of the variance in dual-task gait speed beyond relevant demographic and health risk factors. The present study increases the external validity of dual-task gait assessment of MCI. Differences in dual-task gait speed appears to be largely attributable to executive attention processes. These findings have clinical implications as they demonstrate expected patterns of gait-brain behavior relationships in response to a cognitive dual task within a clinically representative population. Cognitive load dual-task gait assessment may provide a cost efficient and sensitive measure to detect older adults at high risk of a dementia disorder. (JINS, 2017, 23, 493-501).

A model for technology assessment as applied to closed loop infusion systems. Technology Assessment Task Force of the Society of Critical Care Medicine.

PubMed

Jastremski, M; Jastremski, C; Shepherd, M; Friedman, V; Porembka, D; Smith, R; Gonzales, E; Swedlow, D; Belzberg, H; Crass, R

1995-10-01

To test a model for the assessment of critical care technology on closed loop infusion control, a technology that is in its early stages of development and testing on human subjects. A computer-assisted search of the English language literature and reviews of the gathered data by experts in the field of closed loop infusion control systems. Studies relating to closed loop infusion control that addressed one or more of the questions contained in our technology assessment template were analyzed. Study design was not a factor in article selection. However, the lack of well-designed clinical outcome studies was an important factor in determining our conclusions. A focus person summarized the data from the selected studies that related to each of the assessment questions. The preliminary data summary developed by the focus person was further analyzed and refined by the task force. Experts in closed loop systems were then added to the group to review the summary provided by the task force. These experts' comments were considered by the task force and this final consensus report was developed. Closed loop system control is a technological concept that may be applicable to several aspects of critical care practice. This is a technology in the early stages of evolution and much more research and data are needed before its introduction into usual clinical practice. Furthermore, each specific application and each device for each application (e.g., nitroprusside infusion, ventilator adjustment), although based on the same technological concept, are sufficiently different in terms of hardware and computer algorithms to require independent validation studies. Closed loop infusion systems may have a role in critical care practice. However, for most applications, further development is required to move this technology from the innovation phase to the point where it can be evaluated so that its role in critical car practice can be defined. Each application of closed loop infusion systems must be independently validated by appropriately designed research studies. Users should be provided with the clinical parameters driving each closed loop system so that they can ensure that it agrees with their opinion of acceptable medical practice. Clinical researchers and leaders in industry should collaborate to perform the scientifically valid, outcome-based research that is necessary to evaluate the effect of this new technology. The original model we developed for technology assessment required the addition of several more questions to produce a complete analysis of an emerging technology. An emerging technology should be systematically assessed (using a model such as the model developed by the Society of Critical Care Medicine), before its introduction into clinical practice in order to provide a focus for human outcome validation trials and to minimize the possibility of widespread use of an unproven technology.

Perception Measurement in Clinical Trials of Schizophrenia: Promising Paradigms From CNTRICS

PubMed Central

Green, Michael F.; Butler, Pamela D.; Chen, Yue; Geyer, Mark A.; Silverstein, Steven; Wynn, Jonathan K.; Yoon, Jong H.; Zemon, Vance

2009-01-01

The third meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) focused on selecting promising measures for each of the cognitive constructs selected in the first CNTRICS meeting. In the domain of perception, the 2 constructs of interest were gain control and visual integration. CNTRICS received 5 task nominations for gain control and three task nominations for visual integration. The breakout group for perception evaluated the degree to which each of these tasks met prespecified criteria. For gain control, the breakout group for perception believed that 2 of the tasks (prepulse inhibition of startle and mismatch negativity) were already mature and in the process of being incorporated into multisite clinical trials. However, the breakout group recommended that steady-state visual-evoked potentials be combined with contrast sensitivity to magnocellular vs parvocellular biased stimuli and that this combined task and the contrast-contrast effect task be recommended for translation for use in clinical trial contexts in schizophrenia research. For visual integration, the breakout group recommended the Contour Integration and Coherent Motion tasks for translation for use in clinical trials. This manuscript describes the ways in which each of these tasks met the criteria used by the breakout group to evaluate and recommend tasks for further development. PMID:19023123

Developing an appropriate staff mix for anticoagulation clinics: functional job analysis approach

NASA Astrophysics Data System (ADS)

Hailemariam, Desta A.; Shan, Xiaojun; Chung, Sung H.; Khasawneh, Mohammad T.; Lukesh, William; Park, Angela; Rose, Adam

2018-05-01

Anticoagulation clinics (ACCs) are specialty clinics that manage patients with blood clotting problems. Since labor costs usually account for a substantial portion of a healthcare organization's budget, optimizing the number and types of staff required was often the focus, especially for ACCs, where labor-intensive staff-patient interactions occur. A significant portion of tasks performed by clinical pharmacists might be completed by clinical pharmacist technicians, which are less-expensive resources. While nurse staffing models for a hospital inpatient unit are well established, these models are not readily applicable to staffing ACCs. Therefore, the objective of this paper is to develop a framework for determining the right staff mix of clinical pharmacists and clinical pharmacy technicians that increases the efficiency of care delivery process and improves the productivity of ACC staff. A framework is developed and applied to build a semi-automated full-time equivalent (FTE) calculator and compare various staffing scenarios using a simulation model. The FTE calculator provides the right staff mix for a given staff utilization target. Data collected from the ACCs at VA Boston Healthcare System is used to illustrate the FTE calculator and the simulation model. The result of the simulation model can be used by ACC managers to easily determine the number of FTEs of clinical pharmacists and clinical pharmacy technicians required to reach the target utilization and the corresponding staffing cost.

The effect of auditory verbal imagery on signal detection in hallucination-prone individuals

PubMed Central

Moseley, Peter; Smailes, David; Ellison, Amanda; Fernyhough, Charles

2016-01-01

Cognitive models have suggested that auditory hallucinations occur when internal mental events, such as inner speech or auditory verbal imagery (AVI), are misattributed to an external source. This has been supported by numerous studies indicating that individuals who experience hallucinations tend to perform in a biased manner on tasks that require them to distinguish self-generated from non-self-generated perceptions. However, these tasks have typically been of limited relevance to inner speech models of hallucinations, because they have not manipulated the AVI that participants used during the task. Here, a new paradigm was employed to investigate the interaction between imagery and perception, in which a healthy, non-clinical sample of participants were instructed to use AVI whilst completing an auditory signal detection task. It was hypothesized that AVI-usage would cause participants to perform in a biased manner, therefore falsely detecting more voices in bursts of noise. In Experiment 1, when cued to generate AVI, highly hallucination-prone participants showed a lower response bias than when performing a standard signal detection task, being more willing to report the presence of a voice in the noise. Participants not prone to hallucinations performed no differently between the two conditions. In Experiment 2, participants were not specifically instructed to use AVI, but retrospectively reported how often they engaged in AVI during the task. Highly hallucination-prone participants who retrospectively reported using imagery showed a lower response bias than did participants with lower proneness who also reported using AVI. Results are discussed in relation to prominent inner speech models of hallucinations. PMID:26435050

The NEWMEDS rodent touchscreen test battery for cognition relevant to schizophrenia.

PubMed

Hvoslef-Eide, M; Mar, A C; Nilsson, S R O; Alsiö, J; Heath, C J; Saksida, L M; Robbins, T W; Bussey, T J

2015-11-01

The NEWMEDS initiative (Novel Methods leading to New Medications in Depression and Schizophrenia, http://www.newmeds-europe.com ) is a large industrial-academic collaborative project aimed at developing new methods for drug discovery for schizophrenia. As part of this project, Work package 2 (WP02) has developed and validated a comprehensive battery of novel touchscreen tasks for rats and mice for assessing cognitive domains relevant to schizophrenia. This article provides a review of the touchscreen battery of tasks for rats and mice for assessing cognitive domains relevant to schizophrenia and highlights validation data presented in several primary articles in this issue and elsewhere. The battery consists of the five-choice serial reaction time task and a novel rodent continuous performance task for measuring attention, a three-stimulus visual reversal and the serial visual reversal task for measuring cognitive flexibility, novel non-matching to sample-based tasks for measuring spatial working memory and paired-associates learning for measuring long-term memory. The rodent (i.e. both rats and mice) touchscreen operant chamber and battery has high translational value across species due to its emphasis on construct as well as face validity. In addition, it offers cognitive profiling of models of diseases with cognitive symptoms (not limited to schizophrenia) through a battery approach, whereby multiple cognitive constructs can be measured using the same apparatus, enabling comparisons of performance across tasks. This battery of tests constitutes an extensive tool package for both model characterisation and pre-clinical drug discovery.

Assessing young children's intention-reading in authentic communicative contexts: preliminary evidence and clinical utility.

PubMed

Greenslade, Kathryn J; Coggins, Truman E

2014-01-01

Identifying what a communication partner is looking at (referential intention) and why (social intention) is essential to successful social communication, and may be challenging for children with social communication deficits. This study explores a clinical task that assesses these intention-reading abilities within an authentic context. To gather evidence of the task's reliability and validity, and to discuss its clinical utility. The intention-reading task was administered to twenty 4-7-year-olds with typical development (TD) and ten with autism spectrum disorder (ASD). Task items were embedded in an authentic activity, and they targeted the child's ability to identify the examiner's referential and social intentions, which were communicated through joint attention behaviours. Reliability and construct validity evidence were addressed using established psychometric methods. Reliability and validity evidence supported the use of task scores for identifying children whose intention-reading warranted concern. Evidence supported the reliability of task administration and coding, and item-level codes were highly consistent with overall task performance. Supporting task validity, group differences aligned with predictions, with children with ASD exhibiting poorer and more variable task scores than children with TD. Also, as predicted, task scores correlated significantly with verbal mental age and ratings of parental concerns regarding social communication abilities. The evidence provides preliminary support for the reliability and validity of the clinical task's scores in assessing young children's real-time intention-reading abilities, which are essential for successful interactions in school and beyond. © 2014 Royal College of Speech and Language Therapists.

Mobile and fixed computer use by doctors and nurses on hospital wards: multi-method study on the relationships between clinician role, clinical task, and device choice.

PubMed

Andersen, Pia; Lindgaard, Anne-Mette; Prgomet, Mirela; Creswick, Nerida; Westbrook, Johanna I

2009-08-04

Selecting the right mix of stationary and mobile computing devices is a significant challenge for system planners and implementers. There is very limited research evidence upon which to base such decisions. We aimed to investigate the relationships between clinician role, clinical task, and selection of a computer hardware device in hospital wards. Twenty-seven nurses and eight doctors were observed for a total of 80 hours as they used a range of computing devices to access a computerized provider order entry system on two wards at a major Sydney teaching hospital. Observers used a checklist to record the clinical tasks completed, devices used, and location of the activities. Field notes were also documented during observations. Semi-structured interviews were conducted after observation sessions. Assessment of the physical attributes of three devices-stationary PCs, computers on wheels (COWs) and tablet PCs-was made. Two types of COWs were available on the wards: generic COWs (laptops mounted on trolleys) and ergonomic COWs (an integrated computer and cart device). Heuristic evaluation of the user interfaces was also carried out. The majority (93.1%) of observed nursing tasks were conducted using generic COWs. Most nursing tasks were performed in patients' rooms (57%) or in the corridors (36%), with a small percentage at a patient's bedside (5%). Most nursing tasks related to the preparation and administration of drugs. Doctors on ward rounds conducted 57.3% of observed clinical tasks on generic COWs and 35.9% on tablet PCs. On rounds, 56% of doctors' tasks were performed in the corridors, 29% in patients' rooms, and 3% at the bedside. Doctors not on a ward round conducted 93.6% of tasks using stationary PCs, most often within the doctors' office. Nurses and doctors were observed performing workarounds, such as transcribing medication orders from the computer to paper. The choice of device was related to clinical role, nature of the clinical task, degree of mobility required, including where task completion occurs, and device design. Nurses' work, and clinical tasks performed by doctors during ward rounds, require highly mobile computer devices. Nurses and doctors on ward rounds showed a strong preference for generic COWs over all other devices. Tablet PCs were selected by doctors for only a small proportion of clinical tasks. Even when using mobile devices clinicians completed a very low proportion of observed tasks at the bedside. The design of the devices and ward space configurations place limitations on how and where devices are used and on the mobility of clinical work. In such circumstances, clinicians will initiate workarounds to compensate. In selecting hardware devices, consideration should be given to who will be using the devices, the nature of their work, and the physical layout of the ward.

Mobile and Fixed Computer Use by Doctors and Nurses on Hospital Wards: Multi-method Study on the Relationships Between Clinician Role, Clinical Task, and Device Choice

PubMed Central

Andersen, Pia; Lindgaard, Anne-Mette; Prgomet, Mirela; Creswick, Nerida

2009-01-01

Background Selecting the right mix of stationary and mobile computing devices is a significant challenge for system planners and implementers. There is very limited research evidence upon which to base such decisions. Objective We aimed to investigate the relationships between clinician role, clinical task, and selection of a computer hardware device in hospital wards. Methods Twenty-seven nurses and eight doctors were observed for a total of 80 hours as they used a range of computing devices to access a computerized provider order entry system on two wards at a major Sydney teaching hospital. Observers used a checklist to record the clinical tasks completed, devices used, and location of the activities. Field notes were also documented during observations. Semi-structured interviews were conducted after observation sessions. Assessment of the physical attributes of three devices—stationary PCs, computers on wheels (COWs) and tablet PCs—was made. Two types of COWs were available on the wards: generic COWs (laptops mounted on trolleys) and ergonomic COWs (an integrated computer and cart device). Heuristic evaluation of the user interfaces was also carried out. Results The majority (93.1%) of observed nursing tasks were conducted using generic COWs. Most nursing tasks were performed in patients’ rooms (57%) or in the corridors (36%), with a small percentage at a patient’s bedside (5%). Most nursing tasks related to the preparation and administration of drugs. Doctors on ward rounds conducted 57.3% of observed clinical tasks on generic COWs and 35.9% on tablet PCs. On rounds, 56% of doctors’ tasks were performed in the corridors, 29% in patients’ rooms, and 3% at the bedside. Doctors not on a ward round conducted 93.6% of tasks using stationary PCs, most often within the doctors’ office. Nurses and doctors were observed performing workarounds, such as transcribing medication orders from the computer to paper. Conclusions The choice of device was related to clinical role, nature of the clinical task, degree of mobility required, including where task completion occurs, and device design. Nurses’ work, and clinical tasks performed by doctors during ward rounds, require highly mobile computer devices. Nurses and doctors on ward rounds showed a strong preference for generic COWs over all other devices. Tablet PCs were selected by doctors for only a small proportion of clinical tasks. Even when using mobile devices clinicians completed a very low proportion of observed tasks at the bedside. The design of the devices and ward space configurations place limitations on how and where devices are used and on the mobility of clinical work. In such circumstances, clinicians will initiate workarounds to compensate. In selecting hardware devices, consideration should be given to who will be using the devices, the nature of their work, and the physical layout of the ward. PMID:19674959

What every teacher needs to know about clinical reasoning.

PubMed

Eva, Kevin W

2005-01-01

One of the core tasks assigned to clinical teachers is to enable students to sort through a cluster of features presented by a patient and accurately assign a diagnostic label, with the development of an appropriate treatment strategy being the end goal. Over the last 30 years there has been considerable debate within the health sciences education literature regarding the model that best describes how expert clinicians generate diagnostic decisions. The purpose of this essay is to provide a review of the research literature on clinical reasoning for frontline clinical teachers. The strengths and weaknesses of different approaches to clinical reasoning will be examined using one of the core divides between various models (that of analytic (i.e. conscious/controlled) versus non-analytic (i.e. unconscious/automatic) reasoning strategies) as an orienting framework. Recent work suggests that clinical teachers should stress the importance of both forms of reasoning, thereby enabling students to marshal reasoning processes in a flexible and context-specific manner. Specific implications are drawn from this overview for clinical teachers.

Sex differences in visual-spatial working memory: A meta-analysis.

PubMed

Voyer, Daniel; Voyer, Susan D; Saint-Aubin, Jean

2017-04-01

Visual-spatial working memory measures are widely used in clinical and experimental settings. Furthermore, it has been argued that the male advantage in spatial abilities can be explained by a sex difference in visual-spatial working memory. Therefore, sex differences in visual-spatial working memory have important implication for research, theory, and practice, but they have yet to be quantified. The present meta-analysis quantified the magnitude of sex differences in visual-spatial working memory and examined variables that might moderate them. The analysis used a set of 180 effect sizes from healthy males and females drawn from 98 samples ranging in mean age from 3 to 86 years. Multilevel meta-analysis was used on the overall data set to account for non-independent effect sizes. The data also were analyzed in separate task subgroups by means of multilevel and mixed-effects models. Results showed a small but significant male advantage (mean d = 0.155, 95 % confidence interval = 0.087-0.223). All the tasks produced a male advantage, except for memory for location, where a female advantage emerged. Age of the participants was a significant moderator, indicating that sex differences in visual-spatial working memory appeared first in the 13-17 years age group. Removing memory for location tasks from the sample affected the pattern of significant moderators. The present results indicate a male advantage in visual-spatial working memory, although age and specific task modulate the magnitude and direction of the effects. Implications for clinical applications, cognitive model building, and experimental research are discussed.

The Effects of Focused Attention on Inhibition and State Regulation in Children with and without Attention Deficit Hyperactivity Disorder

ERIC Educational Resources Information Center

Ketch, Karen M.; Brodeur, Darlene A.; McGee, Robin

2009-01-01

This study investigated the effects of response rate and attention focusing on performance of ADHD, clinical-control (CRNA) and non-clinical control children in response inhibition tasks. All children completed the "Go-NoGo" task, a computer-based task of attention and impulsivity. Focused attention on this task was manipulated using a priming…

The feasibility of using UML to compare the impact of different brands of computer system on the clinical consultation.

PubMed

Kumarapeli, Pushpa; de Lusignan, Simon; Koczan, Phil; Jones, Beryl; Sheeler, Ian

2007-01-01

UK general practice is universally computerised, with computers used in the consulting room at the point of care. Practices use a range of different brands of computer system, which have developed organically to meet the needs of general practitioners and health service managers. Unified Modelling Language (UML) is a standard modelling and specification notation widely used in software engineering. To examine the feasibility of UML notation to compare the impact of different brands of general practice computer system on the clinical consultation. Multi-channel video recordings of simulated consultation sessions were recorded on three different clinical computer systems in common use (EMIS, iSOFT Synergy and IPS Vision). User action recorder software recorded time logs of keyboard and mouse use, and pattern recognition software captured non-verbal communication. The outputs of these were used to create UML class and sequence diagrams for each consultation. We compared 'definition of the presenting problem' and 'prescribing', as these tasks were present in all the consultations analysed. Class diagrams identified the entities involved in the clinical consultation. Sequence diagrams identified common elements of the consultation (such as prescribing) and enabled comparisons to be made between the different brands of computer system. The clinician and computer system interaction varied greatly between the different brands. UML sequence diagrams are useful in identifying common tasks in the clinical consultation, and for contrasting the impact of the different brands of computer system on the clinical consultation. Further research is needed to see if patterns demonstrated in this pilot study are consistently displayed.

Exploring clinical reasoning in novices: a self-regulated learning microanalytic assessment approach

PubMed Central

Artino, Anthony R; Cleary, Timothy J; Dong, Ting; Hemmer, Paul A; Durning, Steven J

2014-01-01

Objectives The primary objectives of this study were to examine the regulatory processes of medical students as they completed a diagnostic reasoning task and to examine whether the strategic quality of these regulatory processes were related to short-term and longer-term medical education outcomes. Methods A self-regulated learning (SRL) microanalytic assessment was administered to 71 second-year medical students while they read a clinical case and worked to formulate the most probable diagnosis. Verbal responses to open-ended questions targeting forethought and performance phase processes of a cyclical model of SRL were recorded verbatim and subsequently coded using a framework from prior research. Descriptive statistics and hierarchical linear regression models were used to examine the relationships between the SRL processes and several outcomes. Results Most participants (90%) reported focusing on specific diagnostic reasoning strategies during the task (metacognitive monitoring), but only about one-third of students referenced these strategies (e.g. identifying symptoms, integration) in relation to their task goals and plans for completing the task. After accounting for prior undergraduate achievement and verbal reasoning ability, strategic planning explained significant additional variance in course grade (ΔR2 = 0.15, p < 0.01), second-year grade point average (ΔR2 = 0.14, p < 0.01), United States Medical Licensing Examination Step 1 score (ΔR2 = 0.08, p < 0.05) and National Board of Medical Examiner subject examination score in internal medicine (ΔR2 = 0.10, p < 0.05). Conclusions These findings suggest that most students in the formative stages of learning diagnostic reasoning skills are aware of and think about at least one key diagnostic reasoning process or strategy while solving a clinical case, but a substantially smaller percentage set goals or develop plans that incorporate such strategies. Given that students who developed more strategic plans achieved better outcomes, the potential importance of forethought regulatory processes is underscored. PMID:24528463

Promoting the Self-Regulation of Clinical Reasoning Skills in Nursing Students

PubMed Central

Kuiper, R; Pesut, D; Kautz, D

2009-01-01

Aim: The purpose of this paper is to describe the research surrounding the theories and models the authors united to describe the essential components of clinical reasoning in nursing practice education. The research was conducted with nursing students in health care settings through the application of teaching and learning strategies with the Self-Regulated Learning Model (SRL) and the Outcome-Present-State-Test (OPT) Model of Reflective Clinical Reasoning. Standardized nursing languages provided the content and clinical vocabulary for the clinical reasoning task. Materials and Methods: This descriptive study described the application of the OPT model of clinical reasoning, use of nursing language content, and reflective journals based on the SRL model with 66 undergraduate nursing students over an 8 month period of time. The study tested the idea that self-regulation of clinical reasoning skills can be developed using self-regulation theory and the OPT model. Results: This research supports a framework for effective teaching and learning methods to promote and document learner progress in mastering clinical reasoning skills. Self-regulated Learning strategies coupled with the OPT model suggest benefits of self-observation and self-monitoring during clinical reasoning activities, and pinpoints where guidance is needed for the development of cognitive and metacognitive awareness. Recommendations and Conclusions: Thinking and reasoning about the complexities of patient care needs requires attention to the content, processes and outcomes that make a nursing care difference. These principles and concepts are valuable to clinical decision making for nurses globally as they deal with local, regional, national and international health care issues. PMID:19888432

Negation’s Not Solved: Generalizability Versus Optimizability in Clinical Natural Language Processing

PubMed Central

Wu, Stephen; Miller, Timothy; Masanz, James; Coarr, Matt; Halgrim, Scott; Carrell, David; Clark, Cheryl

2014-01-01

A review of published work in clinical natural language processing (NLP) may suggest that the negation detection task has been “solved.” This work proposes that an optimizable solution does not equal a generalizable solution. We introduce a new machine learning-based Polarity Module for detecting negation in clinical text, and extensively compare its performance across domains. Using four manually annotated corpora of clinical text, we show that negation detection performance suffers when there is no in-domain development (for manual methods) or training data (for machine learning-based methods). Various factors (e.g., annotation guidelines, named entity characteristics, the amount of data, and lexical and syntactic context) play a role in making generalizability difficult, but none completely explains the phenomenon. Furthermore, generalizability remains challenging because it is unclear whether to use a single source for accurate data, combine all sources into a single model, or apply domain adaptation methods. The most reliable means to improve negation detection is to manually annotate in-domain training data (or, perhaps, manually modify rules); this is a strategy for optimizing performance, rather than generalizing it. These results suggest a direction for future work in domain-adaptive and task-adaptive methods for clinical NLP. PMID:25393544

Item Dependency in an Objective Structured Clinical Examination

ERIC Educational Resources Information Center

Iramaneerat, Cherdsak; Myford, Carol M.; Yudkowsky, Rachel

2006-01-01

An Objective Structured Clinical Examination (OSCE) is an assessment approach employed in medical education, in which residents rotate through multiple stations of standardized clinical tasks to evaluate their clinical competence. Because items used to evaluate residents' performance in each OSCE station are linked to the same task and are rated…

A Clinically Realistic Large Animal Model of Intra-Articular Fracture

DTIC Science & Technology

2013-10-01

Model of Intra-Articular Fracture PRINCIPAL INVESTIGATOR: Jessica E. Goetz, Ph D CONTRACTING ORGANIZATION: The University of Iowa...5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Jessica E. Goetz, Ph D 5d. PROJECT NUMBER 5e. TASK NUMBER E-Mail...short-term survival study investigating the effects of therapeutic treatment which was initiated during PY3 will be completed. 15. SUBJECT TERMS post

Medical team interdependence as a determinant of use of clinical resources.

PubMed Central

Sicotte, C; Pineault, R; Lambert, J

1993-01-01

OBJECTIVE. Our objective, based on organization theory, is to examine whether interdependence among physicians leads to coordination problems that in turn may explain variations observed in the use of clinical resources. DATA SOURCES/STUDY SETTING. Secondary data about episodes of in-hospital care were collected over a 14-month period in two midsize acute care hospitals located in two suburbs of Montreal, Quebec. STUDY DESIGN. Hierarchical regression analysis was used to assess the marginal effect of medical team interdependence on clinical resource utilization after taking into account the effect attributable to the nature of several morbidities taken as specific and distinct tasks. PRINCIPAL FINDINGS. Medical team interdependence is found within medical specialties as well as between specialties. The largest portion of resource utilization was explained by morbidity characteristics, whereas team interdependence had a weaker, but systematic effect for all morbidities studied (15 regression models out of 18 performed). Task coordination was found to become more difficult as the number of physicians coming from different specialties increased in the context of teamwork. CONCLUSIONS. Results suggest that team practice does not entirely overcome coordination problems inherent to task (morbidity) interdependence. In considering the individual (especially the attending) physician as the main factor responsible for resource utilization, other factors related to team practice may too readily be overlooked. PMID:8270423

SU-E-I-46: Sample-Size Dependence of Model Observers for Estimating Low-Contrast Detection Performance From CT Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reiser, I; Lu, Z

2014-06-01

Purpose: Recently, task-based assessment of diagnostic CT systems has attracted much attention. Detection task performance can be estimated using human observers, or mathematical observer models. While most models are well established, considerable bias can be introduced when performance is estimated from a limited number of image samples. Thus, the purpose of this work was to assess the effect of sample size on bias and uncertainty of two channelized Hotelling observers and a template-matching observer. Methods: The image data used for this study consisted of 100 signal-present and 100 signal-absent regions-of-interest, which were extracted from CT slices. The experimental conditions includedmore » two signal sizes and five different x-ray beam current settings (mAs). Human observer performance for these images was determined in 2-alternative forced choice experiments. These data were provided by the Mayo clinic in Rochester, MN. Detection performance was estimated from three observer models, including channelized Hotelling observers (CHO) with Gabor or Laguerre-Gauss (LG) channels, and a template-matching observer (TM). Different sample sizes were generated by randomly selecting a subset of image pairs, (N=20,40,60,80). Observer performance was quantified as proportion of correct responses (PC). Bias was quantified as the relative difference of PC for 20 and 80 image pairs. Results: For n=100, all observer models predicted human performance across mAs and signal sizes. Bias was 23% for CHO (Gabor), 7% for CHO (LG), and 3% for TM. The relative standard deviation, σ(PC)/PC at N=20 was highest for the TM observer (11%) and lowest for the CHO (Gabor) observer (5%). Conclusion: In order to make image quality assessment feasible in the clinical practice, a statistically efficient observer model, that can predict performance from few samples, is needed. Our results identified two observer models that may be suited for this task.« less

Clinical utility of resting-state functional connectivity magnetic resonance imaging for mood and cognitive disorders.

PubMed

Takamura, T; Hanakawa, T

2017-07-01

Although functional magnetic resonance imaging (fMRI) has long been used to assess task-related brain activity in neuropsychiatric disorders, it has not yet become a widely available clinical tool. Resting-state fMRI (rs-fMRI) has been the subject of recent attention in the fields of basic and clinical neuroimaging research. This method enables investigation of the functional organization of the brain and alterations of resting-state networks (RSNs) in patients with neuropsychiatric disorders. Rs-fMRI does not require participants to perform a demanding task, in contrast to task fMRI, which often requires participants to follow complex instructions. Rs-fMRI has a number of advantages over task fMRI for application with neuropsychiatric patients, for example, although applications of task fMR to participants for healthy are easy. However, it is difficult to apply these applications to patients with psychiatric and neurological disorders, because they may have difficulty in performing demanding cognitive task. Here, we review the basic methodology and analysis techniques relevant to clinical studies, and the clinical applications of the technique for examining neuropsychiatric disorders, focusing on mood disorders (major depressive disorder and bipolar disorder) and dementia (Alzheimer's disease and mild cognitive impairment).

Towards the unification of inference structures in medical diagnostic tasks.

PubMed

Mira, J; Rives, J; Delgado, A E; Martínez, R

1998-01-01

The central purpose of artificial intelligence applied to medicine is to develop models for diagnosis and therapy planning at the knowledge level, in the Newell sense, and software environments to facilitate the reduction of these models to the symbol level. The usual methodology (KADS, Common-KADS, GAMES, HELIOS, Protégé, etc) has been to develop libraries of generic tasks and reusable problem-solving methods with explicit ontologies. The principal problem which clinicians have with these methodological developments concerns the diversity and complexity of new terms whose meaning is not sufficiently clear, precise, unambiguous and consensual for them to be accessible in the daily clinical environment. As a contribution to the solution of this problem, we develop in this article the conjecture that one inference structure is enough to describe the set of analysis tasks associated with medical diagnoses. To this end, we first propose a modification of the systematic diagnostic inference scheme to obtain an analysis generic task and then compare it with the monitoring and the heuristic classification task inference schemes using as comparison criteria the compatibility of domain roles (data structures), the similarity in the inferences, and the commonality in the set of assumptions which underlie the functionally equivalent models. The equivalences proposed are illustrated with several examples. Note that though our ongoing work aims to simplify the methodology and to increase the precision of the terms used, the proposal presented here should be viewed more in the nature of a conjecture.

Efficacy of Selective PDE4D Negative Allosteric Modulators in the Object Retrieval Task in Female Cynomolgus Monkeys (Macaca fascicularis)

PubMed Central

Sutcliffe, Jane S.; Beaumont, Vahri; Watson, James M.; Chew, Chang Sing; Beconi, Maria; Hutcheson, Daniel M.; Dominguez, Celia; Munoz-Sanjuan, Ignacio

2014-01-01

Cyclic adenosine monophosphate (cAMP) signalling plays an important role in synaptic plasticity and information processing in the hippocampal and basal ganglia systems. The augmentation of cAMP signalling through the selective inhibition of phosphodiesterases represents a viable strategy to treat disorders associated with dysfunction of these circuits. The phosphodiesterase (PDE) type 4 inhibitor rolipram has shown significant pro-cognitive effects in neurological disease models, both in rodents and primates. However, competitive non-isoform selective PDE4 inhibitors have a low therapeutic index which has stalled their clinical development. Here, we demonstrate the pro-cognitive effects of selective negative allosteric modulators (NAMs) of PDE4D, D159687 and D159797 in female Cynomolgous macaques, in the object retrieval detour task. The efficacy displayed by these NAMs in a primate cognitive task which engages the corticostriatal circuitry, together with their suitable pharmacokinetic properties and safety profiles, suggests that clinical development of these allosteric modulators should be considered for the treatment of a variety of brain disorders associated with cognitive decline. PMID:25050979

Temporal data representation, normalization, extraction, and reasoning: A review from clinical domain

PubMed Central

Madkour, Mohcine; Benhaddou, Driss; Tao, Cui

2016-01-01

Background and Objective We live our lives by the calendar and the clock, but time is also an abstraction, even an illusion. The sense of time can be both domain-specific and complex, and is often left implicit, requiring significant domain knowledge to accurately recognize and harness. In the clinical domain, the momentum gained from recent advances in infrastructure and governance practices has enabled the collection of tremendous amount of data at each moment in time. Electronic Health Records (EHRs) have paved the way to making these data available for practitioners and researchers. However, temporal data representation, normalization, extraction and reasoning are very important in order to mine such massive data and therefore for constructing the clinical timeline. The objective of this work is to provide an overview of the problem of constructing a timeline at the clinical point of care and to summarize the state-of-the-art in processing temporal information of clinical narratives. Methods This review surveys the methods used in three important area: modeling and representing of time, Medical NLP methods for extracting time, and methods of time reasoning and processing. The review emphasis on the current existing gap between present methods and the semantic web technologies and catch up with the possible combinations. Results the main findings of this review is revealing the importance of time processing not only in constructing timelines and clinical decision support systems but also as a vital component of EHR data models and operations. Conclusions Extracting temporal information in clinical narratives is a challenging task. The inclusion of ontologies and semantic web will lead to better assessment of the annotation task and, together with medical NLP techniques, will help resolving granularity and co-reference resolution problems. PMID:27040831

Building surgical capacity in low-resource countries: a qualitative analysis of task shifting from surgeon volunteers' perspectives.

PubMed

Aliu, Oluseyi; Corlew, Scott D; Heisler, Michele E; Pannucci, Christopher J; Chung, Kevin C

2014-01-01

Surgical volunteer organizations (SVOs) focus considerable resources on addressing the backlog of cases in low-resource countries. This model of service may perpetuate dependency. Efforts should focus on models that establish independence in providing surgical care. Independence could be achieved through surgical capacity building. However, there has been scant discussion in literature on SVO involvement in surgical capacity building. Using qualitative methods, we evaluated the perspectives of surgeons with extensive volunteer experience in low-resource countries. We collected data through in-depth interviews that centered on SVOs using task shifting as a tool for surgical capacity building. Some of the key themes from our analysis include the ethical ramifications of task shifting, the challenges of addressing technical and clinical education in capacity building for low-resource settings, and the allocation of limited volunteer resources toward surgical capacity building. These themes will be the foundation of subsequent studies that will focus on other stakeholders in surgical capacity building including host communities and SVO administrators.

Clinical Correlates of Carbon Dioxide Hypersensitivity in Children.

PubMed

Rappaport, Lance M; Sheerin, Christina; Carney, Dever M; Towbin, Kenneth E; Leibenluft, Ellen; Pine, Daniel S; Brotman, Melissa A; Roberson-Nay, Roxann; Hettema, John M

2017-12-01

Hypersensitivity to carbon dioxide (CO 2 )-enriched air may be a promising risk marker for anxiety disorders. Among adult and adolescent samples, heterogeneity in distress response to the CO 2 challenge task indexes 3 underlying classes of individuals, which distinguish between sustained and acute threat response as markers for internalizing disorders, broadly, and anxiety disorders, specifically. The present study examines latent classes in children's response to the CO 2 challenge task to clarify the association of CO 2 hypersensitivity with anxiety and internalizing symptomatology in childhood. Healthy children from a community twin sample (N = 538; age 9-13 years) rated anxious distress every 2 minutes while breathing air enriched to 7.5% CO 2 for 8 minutes. Latent growth mixture modeling evaluated potential classes of individuals with characteristic trajectories of distress during the task to clarify the association with internalizing disorder symptoms and related traits (e.g., anxiety sensitivity, irritability). Although all participants reported increased distress during the task, interindividual heterogeneity in distress indexed 3 underlying classes: a consistently low class ("low"), a consistently high class ("high"), and participants who demonstrated markedly increased acute distress ("acute"). Compared to the low class, the high class reported greater internalizing psychopathology, whereas membership in the acute class was associated with experiencing a panic-like event during the task. As in older individuals, 3 distinct trajectories emerged to capture interindividual heterogeneity in children's distress during the CO 2 challenge task. These classes were distinguished by clinical validators that reinforce the association of CO 2 hypersensitivity and internalizing disorder phenotypes in children. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. All rights reserved.

Clinical assessment of organizational strategy: An examination of healthy adults.

PubMed

Banerjee, Pia; White, Desirée A

2015-06-01

During the assessment of patients with cognitive difficulties, clinicians often examine strategic processing, particularly the ability to use organization-based strategies to efficiently complete various tasks. Several commonly used neuropsychological tasks are currently thought to provide measures of organizational strategic processing, but empirical evidence for the construct validity of these strategic measures is needed before interpreting them as measuring the same underlying ability. This is particularly important for the assessment of organizational strategic processing because the measures span cognitive domains (e.g., memory strategy, language strategy) as well as types of organization. In the present study, 200 adults were administered cognitive tasks commonly used in clinical practice to assess organizational strategic processing. Factor analysis was used to examine whether these measures of organizational strategic processing, which involved different cognitive domains and types of organization, could be operationalized as measuring a unitary construct. A very good-fitting model of the data demonstrated no significant shared variance among any of the strategic variables from different tasks (root mean square error of approximation < .0001, standardized root-mean-square residual = .045, comparative fit index = 1.000). These findings suggest that organizational strategic processing is highly specific to the demands and goals of individual tasks even when tasks share commonalities such as involving the same cognitive domain. In the design of neuropsychological batteries involving the assessment of organizational strategic processing, it is recommended that various strategic measures across cognitive domains and types of organizational processing are selected as guided by each patient's individual cognitive difficulties. (c) 2015 APA, all rights reserved).

[Translational medicine].

PubMed

Antal, János; Timár, Attila

2011-11-20

Translational medicine is the emerging scientific discipline of the last decade which will set the benchmark for the pharmaceutical industry research and development, integrates inputs from the basic sciences of computer modeling and laboratory research through the pre-clinical and clinical phases of human research to the assimilation of new therapies and treatments into everyday practice of patient care and prevention. With this brief insight authors tried in their humble way to summarize the underlying basis, the present and the potential future of this emerging view, to draw attention to some of the challenges and tasks it faces and to highlight some of the promising approaches, trends and model developments and applications.

Building an automated SOAP classifier for emergency department reports.

PubMed

Mowery, Danielle; Wiebe, Janyce; Visweswaran, Shyam; Harkema, Henk; Chapman, Wendy W

2012-02-01

Information extraction applications that extract structured event and entity information from unstructured text can leverage knowledge of clinical report structure to improve performance. The Subjective, Objective, Assessment, Plan (SOAP) framework, used to structure progress notes to facilitate problem-specific, clinical decision making by physicians, is one example of a well-known, canonical structure in the medical domain. Although its applicability to structuring data is understood, its contribution to information extraction tasks has not yet been determined. The first step to evaluating the SOAP framework's usefulness for clinical information extraction is to apply the model to clinical narratives and develop an automated SOAP classifier that classifies sentences from clinical reports. In this quantitative study, we applied the SOAP framework to sentences from emergency department reports, and trained and evaluated SOAP classifiers built with various linguistic features. We found the SOAP framework can be applied manually to emergency department reports with high agreement (Cohen's kappa coefficients over 0.70). Using a variety of features, we found classifiers for each SOAP class can be created with moderate to outstanding performance with F(1) scores of 93.9 (subjective), 94.5 (objective), 75.7 (assessment), and 77.0 (plan). We look forward to expanding the framework and applying the SOAP classification to clinical information extraction tasks. Copyright © 2011. Published by Elsevier Inc.

The implication of transcultural psychiatry for clinical practice.

PubMed

Moldavsky, Daniel

2003-01-01

This article deals with the main concepts of Transcultural Psychiatry and their applications to everyday psychiatric practice. Transcultural psychiatry has undergone a conceptual reformulation in the last two decades. Having started with a comparative approach, which focused on the diverse manifestations of mental disorders among different societies, it broadened its scope, aiming at present to incorporate social and cultural aspects of illness into the clinical framework. Therefore, transcultural psychiatry now focuses more on what is called the illness experience than on the disease process, the latter understood as illness as it is viewed by health practitioners. Western medicine, of which psychiatry is a part, is grounded in positivist epistemological principles that stress the biological processes of disease. The intention of the paper is to develop an interest in alternative but also complementary ways of thinking. Modern transcultural psychiatry interprets some epidemiological and clinical aspects of major mental disorders (such as schizophrenia and depression) in a different light. However, it also distances itself from the absolute relativism of antipsychiatry, centering on clinical facts and helping clinicians in their primary task of alleviating suffering. An important contribution in addressing this task is the formulation of a cultural axis within the DSM model of multiaxial evaluation. A clinical vignette of a cultural formulation applied to a clinical discussion of a case is described.

Design & control of a 3D stroke rehabilitation platform.

PubMed

Cai, Z; Tong, D; Meadmore, K L; Freeman, C T; Hughes, A M; Rogers, E; Burridge, J H

2011-01-01

An upper limb stroke rehabilitation system is developed which combines electrical stimulation with mechanical arm support, to assist patients performing 3D reaching tasks in a virtual reality environment. The Stimulation Assistance through Iterative Learning (SAIL) platform applies electrical stimulation to two muscles in the arm using model-based control schemes which learn from previous trials of the task. This results in accurate movement which maximises the therapeutic effect of treatment. The principal components of the system are described and experimental results confirm its efficacy for clinical use in upper limb stroke rehabilitation. © 2011 IEEE

A novel personal health system with integrated decision support and guidance for the management of chronic liver disease.

PubMed

Kiefer, Stephan; Schäfer, Michael; Bransch, Marco; Brimmers, Peter; Bartolomé, Diego; Baños, Janie; Orr, James; Jones, Dave; Jara, Maximilian; Stockmann, Martin

2014-01-01

A personal health system platform for the management of patients with chronic liver disease that incorporates a novel approach to integrate decision support and guidance through care pathways for patients and their doctors is presented in this paper. The personal health system incorporates an integrated decision support engine that guides patients and doctors through the management of the disease by issuing tasks and providing recommendations to both the care team and the patient and by controlling the execution of a Care Flow Plan based on the results of tasks and the monitored health status of the patient. This Care Flow Plan represents a formal, business process based model of disease management designed off-line by domain experts on the basis of clinical guidelines, knowledge of care pathways and an organisational model for integrated, patient-centred care. In this way, remote monitoring and treatment are dynamically adapted to the patient's actual condition and clinical symptoms and allow flexible delivery of care with close integration of specialists, therapists and care-givers.

Fully convolutional networks with double-label for esophageal cancer image segmentation by self-transfer learning

NASA Astrophysics Data System (ADS)

Xue, Di-Xiu; Zhang, Rong; Zhao, Yuan-Yuan; Xu, Jian-Ming; Wang, Ya-Lei

2017-07-01

Cancer recognition is the prerequisite to determine appropriate treatment. This paper focuses on the semantic segmentation task of microvascular morphological types on narrowband images to aid clinical examination of esophageal cancer. The most challenge for semantic segmentation is incomplete-labeling. Our key insight is to build fully convolutional networks (FCNs) with double-label to make pixel-wise predictions. The roi-label indicating ROIs (region of interest) is introduced as extra constraint to guild feature learning. Trained end-to-end, the FCN model with two target jointly optimizes both segmentation of sem-label (semantic label) and segmentation of roi-label within the framework of self-transfer learning based on multi-task learning theory. The learning representation ability of shared convolutional networks for sem-label is improved with support of roi-label via achieving a better understanding of information outside the ROIs. Our best FCN model gives satisfactory segmentation result with mean IU up to 77.8% (pixel accuracy > 90%). The results show that the proposed approach is able to assist clinical diagnosis to a certain extent.

Beyond the Dedicated Education Unit: Using Cognitive Load Theory to Guide Clinical Placement.

PubMed

Mulcock, Pamela McPhie; Grassley, Jane; Davis, Michael; White, Kathryn

2017-02-01

Navigating multiple instructors and clinical agencies can impair students' learning by increasing their cognitive load and perceived stress. This study used cognitive load theory to guide the home base clinical model (HBCM), which assigned students to the same faculty and hospital unit for two consecutive medical-surgical clinical courses. The study used a quasi-experimental three-group design to evaluate the effects of the HBCM on students' perceived stress, compared with groups who changed hospital or instructor. A 10-point visual analog scale measured students' perceived stress on nine clinical tasks. The study recruited 140 participants. Reductions in mean stress were greater for the HBCM groups than the other two groups. The study findings challenge the current practice of placing students with changing faculty and facilities. The HBCM demonstrates potential as an effective model for increasing students' ability to learn by decreasing their cognitive load and subsequent stress in their clinical placements. [J Nurs Educ. 2017;56(2):105-109.]. Copyright 2017, SLACK Incorporated.

MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, G; Pan, X; Stayman, J

2014-06-15

Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within themore » reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical applications. Learning Objectives: Learn the general methodologies associated with model-based 3D image reconstruction. Learn the potential advantages in image quality and dose associated with model-based image reconstruction. Learn the challenges associated with computational load and image quality assessment for such reconstruction methods. Learn how imaging task can be incorporated as a means to drive optimal image acquisition and reconstruction techniques. Learn how model-based reconstruction methods can incorporate prior information to improve image quality, ease sampling requirements, and reduce dose.« less

A Novel Method for Assessing Task Complexity in Outpatient Clinical-Performance Measures.

PubMed

Hysong, Sylvia J; Amspoker, Amber B; Petersen, Laura A

2016-04-01

Clinical-performance measurement has helped improve the quality of health-care; yet success in attaining high levels of quality across multiple domains simultaneously still varies considerably. Although many sources of variability in care quality have been studied, the difficulty required to complete the clinical work itself has received little attention. We present a task-based methodology for evaluating the difficulty of clinical-performance measures (CPMs) by assessing the complexity of their component requisite tasks. Using Functional Job Analysis (FJA), subject-matter experts (SMEs) generated task lists for 17 CPMs; task lists were rated on ten dimensions of complexity, and then aggregated into difficulty composites. Eleven outpatient work SMEs; 133 VA Medical Centers nationwide. Clinical Performance: 17 outpatient CPMs (2000-2008) at 133 VA Medical Centers nationwide. Measure Difficulty: for each CPM, the number of component requisite tasks and the average rating across ten FJA complexity scales for the set of tasks comprising the measure. Measures varied considerably in the number of component tasks (M = 10.56, SD = 6.25, min = 5, max = 25). Measures of chronic care following acute myocardial infarction exhibited significantly higher measure difficulty ratings compared to diabetes or screening measures, but not to immunization measures ([Formula: see text] = 0.45, -0.04, -0.05, and -0.06 respectively; F (3, 186) = 3.57, p = 0.015). Measure difficulty ratings were not significantly correlated with the number of component tasks (r = -0.30, p = 0.23). Evaluating the difficulty of achieving recommended CPM performance levels requires more than simply counting the tasks involved; using FJA to assess the complexity of CPMs' component tasks presents an alternate means of assessing the difficulty of primary-care CPMs and accounting for performance variation among measures and performers. This in turn could be used in designing performance reward programs, or to match workflow to clinician time and effort.

Shoulder Arthroscopy Simulator Training Improves Shoulder Arthroscopy Performance in a Cadaver Model

PubMed Central

Henn, R. Frank; Shah, Neel; Warner, Jon J.P.; Gomoll, Andreas H.

2013-01-01

Purpose The purpose of this study was to quantify the benefits of shoulder arthroscopy simulator training with a cadaver model of shoulder arthroscopy. Methods Seventeen first year medical students with no prior experience in shoulder arthroscopy were enrolled and completed this study. Each subject completed a baseline proctored arthroscopy on a cadaveric shoulder, which included controlling the camera and completing a standard series of tasks using the probe. The subjects were randomized, and nine of the subjects received training on a virtual reality simulator for shoulder arthroscopy. All subjects then repeated the same cadaveric arthroscopy. The arthroscopic videos were analyzed in a blinded fashion for time to task completion and subjective assessment of technical performance. The two groups were compared with students t-tests, and change over time within groups was analyzed with paired t-tests. Results There were no observed differences between the two groups on the baseline evaluation. The simulator group improved significantly from baseline with respect to time to completion and subjective performance (p<0.05). Time to completion was significantly faster in the simulator group compared to controls at final evaluation (p<0.05). No difference was observed between the groups on the subjective scores at final evaluation (p=0.98). Conclusions Shoulder arthroscopy simulator training resulted in significant benefits in clinical shoulder arthroscopy time to task completion in this cadaver model. This study provides important additional evidence of the benefit of simulators in orthopaedic surgical training. Clinical Relevance There may be a role for simulator training in shoulder arthroscopy education. PMID:23591380

Task-Driven Orbit Design and Implementation on a Robotic C-Arm System for Cone-Beam CT.

PubMed

Ouadah, S; Jacobson, M; Stayman, J W; Ehtiati, T; Weiss, C; Siewerdsen, J H

2017-03-01

This work applies task-driven optimization to the design of non-circular orbits that maximize imaging performance for a particular imaging task. First implementation of task-driven imaging on a clinical robotic C-arm system is demonstrated, and a framework for orbit calculation is described and evaluated. We implemented a task-driven imaging framework to optimize orbit parameters that maximize detectability index d '. This framework utilizes a specified Fourier domain task function and an analytical model for system spatial resolution and noise. Two experiments were conducted to test the framework. First, a simple task was considered consisting of frequencies lying entirely on the f z -axis (e.g., discrimination of structures oriented parallel to the central axial plane), and a "circle + arc" orbit was incorporated into the framework as a means to improve sampling of these frequencies, and thereby increase task-based detectability. The orbit was implemented on a robotic C-arm (Artis Zeego, Siemens Healthcare). A second task considered visualization of a cochlear implant simulated within a head phantom, with spatial frequency response emphasizing high-frequency content in the ( f y , f z ) plane of the cochlea. An optimal orbit was computed using the task-driven framework, and the resulting image was compared to that for a circular orbit. For the f z -axis task, the circle + arc orbit was shown to increase d ' by a factor of 1.20, with an improvement of 0.71 mm in a 3D edge-spread measurement for edges located far from the central plane and a decrease in streak artifacts compared to a circular orbit. For the cochlear implant task, the resulting orbit favored complementary views of high tilt angles in a 360° orbit, and d ' was increased by a factor of 1.83. This work shows that a prospective definition of imaging task can be used to optimize source-detector orbit and improve imaging performance. The method was implemented for execution of non-circular, task-driven orbits on a clinical robotic C-arm system. The framework is sufficiently general to include both acquisition parameters (e.g., orbit, kV, and mA selection) and reconstruction parameters (e.g., a spatially varying regularizer).

Task-driven orbit design and implementation on a robotic C-arm system for cone-beam CT

NASA Astrophysics Data System (ADS)

Ouadah, S.; Jacobson, M.; Stayman, J. W.; Ehtiati, T.; Weiss, C.; Siewerdsen, J. H.

2017-03-01

Purpose: This work applies task-driven optimization to the design of non-circular orbits that maximize imaging performance for a particular imaging task. First implementation of task-driven imaging on a clinical robotic C-arm system is demonstrated, and a framework for orbit calculation is described and evaluated. Methods: We implemented a task-driven imaging framework to optimize orbit parameters that maximize detectability index d'. This framework utilizes a specified Fourier domain task function and an analytical model for system spatial resolution and noise. Two experiments were conducted to test the framework. First, a simple task was considered consisting of frequencies lying entirely on the fz-axis (e.g., discrimination of structures oriented parallel to the central axial plane), and a "circle + arc" orbit was incorporated into the framework as a means to improve sampling of these frequencies, and thereby increase task-based detectability. The orbit was implemented on a robotic C-arm (Artis Zeego, Siemens Healthcare). A second task considered visualization of a cochlear implant simulated within a head phantom, with spatial frequency response emphasizing high-frequency content in the (fy, fz) plane of the cochlea. An optimal orbit was computed using the task-driven framework, and the resulting image was compared to that for a circular orbit. Results: For the fz-axis task, the circle + arc orbit was shown to increase d' by a factor of 1.20, with an improvement of 0.71 mm in a 3D edge-spread measurement for edges located far from the central plane and a decrease in streak artifacts compared to a circular orbit. For the cochlear implant task, the resulting orbit favored complementary views of high tilt angles in a 360° orbit, and d' was increased by a factor of 1.83. Conclusions: This work shows that a prospective definition of imaging task can be used to optimize source-detector orbit and improve imaging performance. The method was implemented for execution of non-circular, task-driven orbits on a clinical robotic C-arm system. The framework is sufficiently general to include both acquisition parameters (e.g., orbit, kV, and mA selection) and reconstruction parameters (e.g., a spatially varying regularizer).

Word sense disambiguation in the clinical domain: a comparison of knowledge-rich and knowledge-poor unsupervised methods

PubMed Central

Chasin, Rachel; Rumshisky, Anna; Uzuner, Ozlem; Szolovits, Peter

2014-01-01

Objective To evaluate state-of-the-art unsupervised methods on the word sense disambiguation (WSD) task in the clinical domain. In particular, to compare graph-based approaches relying on a clinical knowledge base with bottom-up topic-modeling-based approaches. We investigate several enhancements to the topic-modeling techniques that use domain-specific knowledge sources. Materials and methods The graph-based methods use variations of PageRank and distance-based similarity metrics, operating over the Unified Medical Language System (UMLS). Topic-modeling methods use unlabeled data from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC II) database to derive models for each ambiguous word. We investigate the impact of using different linguistic features for topic models, including UMLS-based and syntactic features. We use a sense-tagged clinical dataset from the Mayo Clinic for evaluation. Results The topic-modeling methods achieve 66.9% accuracy on a subset of the Mayo Clinic's data, while the graph-based methods only reach the 40–50% range, with a most-frequent-sense baseline of 56.5%. Features derived from the UMLS semantic type and concept hierarchies do not produce a gain over bag-of-words features in the topic models, but identifying phrases from UMLS and using syntax does help. Discussion Although topic models outperform graph-based methods, semantic features derived from the UMLS prove too noisy to improve performance beyond bag-of-words. Conclusions Topic modeling for WSD provides superior results in the clinical domain; however, integration of knowledge remains to be effectively exploited. PMID:24441986

Load-dependent dysfunction of the putamen during attentional processing in patients with clinically isolated syndrome suggestive of multiple sclerosis.

PubMed

Tortorella, C; Romano, R; Direnzo, V; Taurisano, P; Zoccolella, S; Iaffaldano, P; Fazio, L; Viterbo, R; Popolizio, T; Blasi, G; Bertolino, A; Trojano, M

2013-08-01

Load-related functional magnetic resonance imaging (fMRI) abnormalities of brain activity during performance of attention tasks have been described in definite multiple sclerosis (MS). No data are available in clinically isolated syndrome (CIS) suggestive of MS. The objective of this research is to evaluate in CIS patients the fMRI pattern of brain activation during an attention task and to explore the effect of increasing task load demand on neurofunctional modifications. Twenty-seven untreated CIS patients and 32 age- and sex-matched healthy controls (HCs) underwent fMRI while performing the Variable Attentional Control (VAC) task, a cognitive paradigm requiring increasing levels of attentional control processing. Random-effects models were used for statistical analyses of fMRI data. CIS patients had reduced accuracy and greater reaction time at the VAC task compared with HCs (p=0.007). On blood oxygenation level-dependent (BOLD)-fMRI, CIS patients had greater activity in the right parietal cortex (p=0.0004) compared with HCs. Furthermore, CIS patients had greater activity at the lower (p=0.05) and reduced activity at the greater (p=0.04) level of attentional control demand in the left putamen, compared with HCs. This study demonstrates the failure of attentional control processing in CIS. The load-related fMRI dysfunction of the putamen supports the role of basal ganglia in the failure of attention observed at the earliest stage of MS.

Cost-effectiveness analysis alongside clinical trials II-An ISPOR Good Research Practices Task Force report.

PubMed

Ramsey, Scott D; Willke, Richard J; Glick, Henry; Reed, Shelby D; Augustovski, Federico; Jonsson, Bengt; Briggs, Andrew; Sullivan, Sean D

2015-03-01

Clinical trials evaluating medicines, medical devices, and procedures now commonly assess the economic value of these interventions. The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. As decision makers increasingly demand evidence of economic value for health care interventions, conducting high-quality economic analyses alongside clinical studies is desirable because they broaden the scope of information available on a particular intervention, and can efficiently provide timely information with high internal and, when designed and analyzed properly, reasonable external validity. In 2005, ISPOR published the Good Research Practices for Cost-Effectiveness Analysis Alongside Clinical Trials: The ISPOR RCT-CEA Task Force report. ISPOR initiated an update of the report in 2014 to include the methodological developments over the last 9 years. This report provides updated recommendations reflecting advances in several areas related to trial design, selecting data elements, database design and management, analysis, and reporting of results. Task force members note that trials should be designed to evaluate effectiveness (rather than efficacy) when possible, should include clinical outcome measures, and should obtain health resource use and health state utilities directly from study subjects. Collection of economic data should be fully integrated into the study. An incremental analysis should be conducted with an intention-to-treat approach, complemented by relevant subgroup analyses. Uncertainty should be characterized. Articles should adhere to established standards for reporting results of cost-effectiveness analyses. Economic studies alongside trials are complementary to other evaluations (e.g., modeling studies) as information for decision makers who consider evidence of economic value along with clinical efficacy when making resource allocation decisions. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

A model for technology assessment applied to pulse oximetry. The Technology Assessment Task Force of the Society of Critical Care Medicine.

PubMed

1993-04-01

To test a model for the assessment of critical care technology. To develop practice guidelines for the use of pulse oximetry. A computer-assisted search of the English language literature and interviews with recognized experts in the field of pulse oximetry. Those studies that addressed one or more of the seven questions contained in our technology assessment template were analyzed. Study design was not a factor in article selection. However, the lack of well-designed clinical outcome studies was an important factor in determining the method of practice policy development we utilized. A focus person summarized the data from the selected studies that related to each of the seven assessment questions. The preliminary data summary developed by the focus person was further analyzed and refined by the task force and then sent to 16 expert reviewers for comment. These expert comments were considered by the task force, and this final consensus report was developed. Pulse oximetry combines the principles of spectrophotometry and plethysmography to noninvasively measure oxygen saturation with a high degree of accuracy over the range of 80% to 100% saturation, assuming the device is being used according to the manufacturer's instructions and without any adverse operating conditions. The appropriate clinical uses of pulse oximetry fall into one of two broad categories: as a warning system based on continuous real-time measurement of arterial desaturation, or as an end-point for titration of therapeutic interventions. There are no published studies that allow for definitive, outcome-based conclusions concerning either the clinical impact or cost-benefit ratio of pulse oximetry. The model developed for technology assessment proved to be appropriate for assessing pulse oximetry. The available data have allowed us to develop an evidence-based practice policy for the use of pulse oximetry in critical care. Critical care clinicians, researchers, and industry have a shared responsibility to provide valid outcome and efficacy studies of new technologies.

Guidelines for Guidelines: Are They Up to the Task? A Comparative Assessment of Clinical Practice Guideline Development Handbooks

PubMed Central

Ansari, Shabnam; Rashidian, Arash

2012-01-01

Objectives We conducted a comparative review of clinical practice guideline development handbooks. We aimed to identify the main guideline development tasks, assign weights to the importance of each task using expert opinions and identify the handbooks that provided a comprehensive coverage of the tasks. Methods We systematically searched and included handbooks published (in English language) by national, international or professional bodies responsible for evidenced-based guideline development. We reviewed the handbooks to identify the main guideline development tasks and scored each handbook for each task from 0 (the handbook did not mention the task) to 2 (the task suitably addressed and explained), and calculated a weighted score for each handbook. The tasks included in over 75% of the handbooks were considered as ‘necessary’ tasks. Result Nineteen guideline development handbooks and twenty seven main tasks were identified. The guideline handbooks’ weighted scores ranged from 100 to 220. Four handbooks scored over 80% of the maximum possible score, developed by the National Institute for Health and Clinical Excellence, Swiss Centre for International Health, Scottish Intercollegiate Guidelines Network and World Health Organization. Necessary tasks were: selecting the guideline topic, determining the guideline scope, identifying relevant existing guidelines, involving the consumers, forming guideline development group,, developing clinical questions, systematic search for evidence, selecting relevant evidence, appraising identifies research evidence, making group decision, grading available evidence, creating recommendations, final stakeholder consultation, guideline implementation strategies, updating recommendations and correcting potential errors. Discussion Adequate details for evidence based development of guidelines were still lacking from many handbooks. The tasks relevant to ethical issues and piloting were missing in most handbooks. The findings help decision makers in identifying the necessary tasks for guideline development, provide an updated comparative list of guideline development handbooks, and provide a checklist to assess the comprehensiveness of guideline development processes. PMID:23189167

Elucidating Poor Decision-Making in a Rat Gambling Task

PubMed Central

Seriès, Peggy; Marchand, Alain R.; Dellu-Hagedorn, Françoise

2013-01-01

Although poor decision-making is a hallmark of psychiatric conditions such as attention deficit/hyperactivity disorder, pathological gambling or substance abuse, a fraction of healthy individuals exhibit similar poor decision-making performances in everyday life and specific laboratory tasks such as the Iowa Gambling Task. These particular individuals may provide information on risk factors or common endophenotypes of these mental disorders. In a rodent version of the Iowa gambling task – the Rat Gambling Task (RGT), we identified a population of poor decision makers, and assessed how these rats scored for several behavioral traits relevant to executive disorders: risk taking, reward seeking, behavioral inflexibility, and several aspects of impulsivity. First, we found that poor decision-making could not be well predicted by single behavioral and cognitive characteristics when considered separately. By contrast, a combination of independent traits in the same individual, namely risk taking, reward seeking, behavioral inflexibility, as well as motor impulsivity, was highly predictive of poor decision-making. Second, using a reinforcement-learning model of the RGT, we confirmed that only the combination of extreme scores on these traits could induce maladaptive decision-making. Third, the model suggested that a combination of these behavioral traits results in an inaccurate representation of rewards and penalties and inefficient learning of the environment. Poor decision-making appears as a consequence of the over-valuation of high-reward-high-risk options in the task. Such a specific psychological profile could greatly impair clinically healthy individuals in decision-making tasks and may predispose to mental disorders with similar symptoms. PMID:24339988

Elucidating poor decision-making in a rat gambling task.

PubMed

Rivalan, Marion; Valton, Vincent; Seriès, Peggy; Marchand, Alain R; Dellu-Hagedorn, Françoise

2013-01-01

Although poor decision-making is a hallmark of psychiatric conditions such as attention deficit/hyperactivity disorder, pathological gambling or substance abuse, a fraction of healthy individuals exhibit similar poor decision-making performances in everyday life and specific laboratory tasks such as the Iowa Gambling Task. These particular individuals may provide information on risk factors or common endophenotypes of these mental disorders. In a rodent version of the Iowa gambling task--the Rat Gambling Task (RGT), we identified a population of poor decision makers, and assessed how these rats scored for several behavioral traits relevant to executive disorders: risk taking, reward seeking, behavioral inflexibility, and several aspects of impulsivity. First, we found that poor decision-making could not be well predicted by single behavioral and cognitive characteristics when considered separately. By contrast, a combination of independent traits in the same individual, namely risk taking, reward seeking, behavioral inflexibility, as well as motor impulsivity, was highly predictive of poor decision-making. Second, using a reinforcement-learning model of the RGT, we confirmed that only the combination of extreme scores on these traits could induce maladaptive decision-making. Third, the model suggested that a combination of these behavioral traits results in an inaccurate representation of rewards and penalties and inefficient learning of the environment. Poor decision-making appears as a consequence of the over-valuation of high-reward-high-risk options in the task. Such a specific psychological profile could greatly impair clinically healthy individuals in decision-making tasks and may predispose to mental disorders with similar symptoms.

Job analysis and student assessment tool: perfusion education clinical preceptor.

PubMed

Riley, Jeffrey B

2007-09-01

The perfusion education system centers on the cardiac surgery operating room and the perfusionist teacher who serves as a preceptor for the perfusion student. One method to improve the quality of perfusion education is to create a valid method for perfusion students to give feedback to clinical teachers. The preceptor job analysis consisted of a literature review and interviews with preceptors to list their critical tasks, critical incidents, and cognitive and behavioral competencies. Behaviorally anchored rating traits associated with the preceptors' tasks were identified. Students voted to validate the instrument items. The perfusion instructor rating instrument with a 0-4, "very weak" to "very strong" Likert rating scale was used. The five preceptor traits for student evaluation of clinical instruction (SECI) are as follows: The clinical instructor (1) encourages self-learning, (2) encourages clinical reasoning, (3) meets student's learning needs, (4) gives continuous feedback, and (5) represents a good role model. Scores from 430 student-preceptor relationships for 28 students rotating at 24 affiliate institutions with 134 clinical instructors were evaluated. The mean overall good preceptor average (GPA) was 3.45 +/- 0.76 and was skewed to the left, ranging from 0.0 to 4.0 (median = 3.8). Only 21 of the SECI relationships earned a GPA < 2.0. Analyzing the role of the clinical instructor and performing SECI are methods to provide valid information to improve the quality of a perfusion education program.

Effects of L-histidine depletion and L-tyrosine/L-phenylalanine depletion on sensory and motor processes in healthy volunteers

PubMed Central

van Ruitenbeek, P; Sambeth, A; Vermeeren, A; Young, SN; Riedel, WJ

2009-01-01

Background and purpose: Animal studies show that histamine plays a role in cognitive functioning and that histamine H3-receptor antagonists, which increase histaminergic function through presynaptic receptors, improve cognitive performance in models of clinical cognitive deficits. In order to test such new drugs in humans, a model for cognitive impairments induced by low histaminergic functions would be useful. Studies with histamine H1-receptor antagonists have shown limitations as a model. Here we evaluated whether depletion of L-histidine, the precursor of histamine, was effective in altering measures associated with histamine in humans and the behavioural and electrophysiological (event-related-potentials) effects. Experimental approach: Seventeen healthy volunteers completed a three-way, double-blind, crossover study with L-histidine depletion, L-tyrosine/L-phenylalanine depletion (active control) and placebo as treatments. Interactions with task manipulations in a choice reaction time task were studied. Task demands were increased using visual stimulus degradation and increased response complexity. In addition, subjective and objective measures of sedation and critical tracking task performance were assessed. Key results: Measures of sedation and critical tracking task performance were not affected by treatment. L-histidine depletion was effective and enlarged the effect of response complexity as measured with the response-locked lateralized readiness potential onset latency. Conclusions and implications: L-histidine depletion affected response- but not stimulus-related processes, in contrast to the effects of H1-receptor antagonists which were previously found to affect primarily stimulus-related processes. L-histidine depletion is promising as a model for histamine-based cognitive impairment. However, these effects need to be confirmed by further studies. PMID:19413574

Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.

PubMed

Yang, Zhongliang; Huang, Yongfeng; Jiang, Yiran; Sun, Yuxi; Zhang, Yu-Jin; Luo, Pengcheng

2018-04-20

Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67% accuracy and 96.02% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.

Factor Analysis of the Community Balance and Mobility Scale in Individuals with Knee Osteoarthritis.

PubMed

Takacs, Judit; Krowchuk, Natasha M; Goldsmith, Charles H; Hunt, Michael A

2017-10-01

The clinical assessment of balance is an important first step in characterizing the risk of falls. The Community Balance and Mobility Scale (CB&M) is a test of balance and mobility that was designed to assess performance on advanced tasks necessary for independence in the community. However, other factors that can affect balancing ability may also be present during performance of the real-world tasks on the CB&M. It is important for clinicians to understand fully what other modifiable factors the CB&M may encompass. The purpose of this study was to evaluate the underlying constructs in the CB&M in individuals with knee osteoarthritis (OA). This was an observational study, with a single testing session. Participants with knee OA aged 50 years and older completed the CB&M, a clinical test of balance and mobility. Confirmatory factor analysis was then used to examine whether the tasks on the CB&M measure distinct factors. Three a priori theory-driven models with three (strength, balance, mobility), four (range of motion added) and six (pain and fear added) constructs were evaluated using multiple fit indices. A total of 131 participants (mean [SD] age 66.3 [8.5] years, BMI 27.3 [5.2] kg m -2 ) participated. A three-factor model in which all tasks loaded on these three factors explained 65% of the variance and yielded the most optimal model, as determined using scree plots, chi-squared values and explained variance. The first factor accounted for 49% of the variance and was interpreted as lower limb muscle strength. The second and third factors were interpreted as mobility and balance, respectively. The CB&M demonstrated the measurement of three distinct factors, interpreted as lower limb strength, balance and mobility, supporting the use of the CB&M with people with knee OA for evaluation of these important factors in falls risk and functional mobility. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Overgeneral autobiographical memory bias in clinical and non-clinical voice hearers.

PubMed

Jacobsen, Pamela; Peters, Emmanuelle; Ward, Thomas; Garety, Philippa A; Jackson, Mike; Chadwick, Paul

2018-03-14

Hearing voices can be a distressing and disabling experience for some, whilst it is a valued experience for others, so-called 'healthy voice-hearers'. Cognitive models of psychosis highlight the role of memory, appraisal and cognitive biases in determining emotional and behavioural responses to voices. A memory bias potentially associated with distressing voices is the overgeneral memory bias (OGM), namely the tendency to recall a summary of events rather than specific occasions. It may limit access to autobiographical information that could be helpful in re-appraising distressing experiences, including voices. We investigated the possible links between OGM and distressing voices in psychosis by comparing three groups: (1) clinical voice-hearers (N = 39), (2) non-clinical voice-hearers (N = 35) and (3) controls without voices (N = 77) on a standard version of the autobiographical memory test (AMT). Clinical and non-clinical voice-hearers also completed a newly adapted version of the task, designed to assess voices-related memories (vAMT). As hypothesised, the clinical group displayed an OGM bias by retrieving fewer specific autobiographical memories on the AMT compared with both the non-clinical and control groups, who did not differ from each other. The clinical group also showed an OGM bias in recall of voice-related memories on the vAMT, compared with the non-clinical group. Clinical voice-hearers display an OGM bias when compared with non-clinical voice-hearers on both general and voices-specific recall tasks. These findings have implications for the refinement and targeting of psychological interventions for psychosis.

Improving Dual-Task Control With a Posture-Second Strategy in Early-Stage Parkinson Disease.

PubMed

Huang, Cheng-Ya; Chen, Yu-An; Hwang, Ing-Shiou; Wu, Ruey-Meei

2018-03-31

To examine the task prioritization effects on postural-suprapostural dual-task performance in patients with early-stage Parkinson disease (PD) without clinically observed postural symptoms. Cross-sectional study. Participants performed a force-matching task while standing on a mobile platform, and were instructed to focus their attention on either the postural task (posture-first strategy) or the force-matching task (posture-second strategy). University research laboratory. Individuals (N=16) with early-stage PD who had no clinically observed postural symptoms. Not applicable. Dual-task change (DTC; percent change between single-task and dual-task performance) of posture error, posture approximate entropy (ApEn), force error, and reaction time (RT). Positive DTC values indicate higher postural error, posture ApEn, force error, and force RT during dual-task conditions compared with single-task conditions. Compared with the posture-first strategy, the posture-second strategy was associated with smaller DTC of posture error and force error, and greater DTC of posture ApEn. In contrast, greater DTC of force RT was observed under the posture-second strategy. Contrary to typical recommendations, our results suggest that the posture-second strategy may be an effective dual-task strategy in patients with early-stage PD who have no clinically observed postural symptoms in order to reduce the negative effect of dual tasking on performance and facilitate postural automaticity. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Factorial Validity of the Movement Assessment Battery for Children-2nd Edition (MABC-2) in 7-16-Year-Olds.

PubMed

Psotta, Rudolf; Abdollahipour, Reza

2017-12-01

The Movement Assessment Battery for Children-2nd Edition (MABC-2) is a test of motor development, widely used in clinical and research settings. To address which motor abilities are actually captured by the motor tasks in the two age versions of the MABC-2, the AB2 for 7- 10-year-olds and the AB3 for 11- 16-year-olds, we examined AB2 and AB3 factorial validity. We conducted confirmatory factor analysis (SPSS AMOS 22.0) on data from the test's standardization samples of children aged 7-10, n = 483, and 11-16, n = 674, in order to find the best fitting models. The covariance matrix of AB2 and AB3 fit a three-factor model that included tasks of manual dexterity, aiming and catching, and balance. However, factor analytic models fitting AB2 and AB3 did not involve the dynamic balance tasks of hopping with the better leg and hopping with the other leg; and the drawing trail showed very low factor validity. In sum, both AB2 and AB3 of the MABC-2 test are able to discriminate between the three specific motor abilities; but due to questionable psychometric quality, the drawing trail and hopping tasks should be modified to improve the construct validity for both age versions of the MABC-2.

Pre-test and post-test evaluation of students' perceptions of a collaborative clinical education model on the learning environment.

PubMed

Henderson, Amanda; Heel, Alison; Twentyman, Michelle; Lloyd, Belinda

2006-01-01

This study investigated the impact of a collaborative clinical education model on students' perception of the psycho-social learning environment. A pre-test and post-test quasi experimental design. A tertiary referral centre. Second and third year undergraduate nursing students were asked to rate their perceptions of the psycho-social learning environment at the completion of the clinical practicum. TOOL: The tool used to measure psycho-social perceptions of the clinical learning environment was the Clinical Learning Environment Inventory previously validated in Australian health care contexts. A collaborative arrangement with the university and ward staff where eight students are placed on a ward and a ward staff member is paid by the university to be 'off-line' from a clinical workload to supervise the students. This is in contrast to the standard facilitation model where students are placed with registered nurses in different localities under the supervision of a 'roving' registered nurse paid by the university. No significant differences were found in pre-test mean scores when comparing wards. Significant differences in post-test scores for the intervention group were identified in the sub scales of Student Involvement, Satisfaction, Personalisation and Task Orientation. The adoption of a collaborative clinical education model where students are integrated into the ward team and the team is responsible for student learning can positively enhance capacity for student learning during their clinical practicum.

Comparison between magnetic anchoring and guidance system camera-assisted laparoendoscopic single-site surgery nephrectomy and conventional laparoendoscopic single-site surgery nephrectomy in a porcine model: focus on ergonomics and workload profiles.

PubMed

Han, Woong Kyu; Tan, Yung K; Olweny, Ephrem O; Yin, Gang; Liu, Zhuo-Wei; Faddegon, Stephen; Scott, Daniel J; Cadeddu, Jeffrey A

2013-04-01

To compare surgeon-assessed ergonomic and workload demands of magnetic anchoring and guidance system (MAGS) laparoendoscopic single-site surgery (LESS) nephrectomy with conventional LESS nephrectomy in a porcine model. Participants included two expert and five novice surgeons who each performed bilateral LESS nephrectomy in two nonsurvival animals using either the MAGS camera or conventional laparoscope. Task difficulty and workload demands of the surgeon and camera driver were assessed using the validated National Aeronautics and Space Administration Task Load Index (NASA-TLX) questionnaire. Surgeons were also asked to score 6 parameters on a Likert scale (range 1=low/easy to 5=high/hard): procedure-associated workload, ergonomics, technical challenge, visualization, accidental events, and instrument handling. Each step of the nephrectomy was also timed and instrument clashing was quantified. Scores for each parameter on the Likert scale were significantly lower for MAGS-LESS nephrectomy. Mean number of internal and external clashes were significantly lower for the MAGS camera (p<0.001). Mean task times for each procedure were shorter for experts than for novices, but this was not statistically significant. NASA-TLX workload ratings by the surgeon and camera driver showed that MAGS resulted in a significantly lower workload than the conventional laparoscope during LESS nephrectomy (p<0.05). The use of the MAGS camera during LESS nephrectomy lowers the task workload for both the surgeon and camera driver when compared to conventional laparoscope use. Subjectively, it appears to also improve surgeons' impressions of ergonomics and technical challenge. Pending approval for clinical use, further evaluation in the clinical setting is warranted.

Developing a Very Low Vision Orientation and Mobility Test Battery (O&M-VLV).

PubMed

Finger, Robert P; Ayton, Lauren N; Deverell, Lil; O'Hare, Fleur; McSweeney, Shane C; Luu, Chi D; Fenwick, Eva K; Keeffe, Jill E; Guymer, Robyn H; Bentley, Sharon A

2016-09-01

This study aimed to determine the feasibility of an assessment of vision-related orientation and mobility (O&M) tasks in persons with severe vision loss. These tasks may be used for future low vision rehabilitation clinical assessments or as outcome measures in vision restoration trials. Forty legally blind persons (mean visual acuity logMAR 2.3, or hand movements) with advanced retinitis pigmentosa participated in the Orientation & Mobility-Very Low Vision (O&M-VLV) subtests from the Low Vision Assessment of Daily Activities (LoVADA) protocol. Four categories of tasks were evaluated: route travel in three indoor hospital environments, a room orientation task (the "cafe"), a visual exploration task (the "gallery"), and a modified version of the Timed Up and Go (TUG) test, which assesses re-orientation and route travel. Spatial cognition was assessed using the Stuart Tactile Maps test. Visual acuity and visual fields were measured. A generalized linear regression model showed that a number of measures in the O&M-VLV tasks were related to residual visual function. The percentage of preferred walking speed without an aid on three travel routes was associated with visual field (p < 0.01 for all routes) whereas the number of contacts with obstacles during route travel was associated with acuity (p = 0.001). TUG-LV task time was associated with acuity (p = 0.003), as was the cafe time and distance traveled (p = 0.006 and p < 0.001, respectively). The gallery score was the only measure that was significantly associated with both residual acuity and fields (p < 0.001 and p = 0.001, respectively). The O&M-VLV was designed to capture key elements of O&M performance in persons with severe vision loss, which is a population not often studied previously. Performance on these tasks was associated with both binocular visual acuity and visual field. This new protocol includes assessments of orientation, which may be of benefit in vision restoration clinical trials.

Overlooking the obvious: a meta-analytic comparison of digit symbol coding tasks and other cognitive measures in schizophrenia.

PubMed

Dickinson, Dwight; Ramsey, Mary E; Gold, James M

2007-05-01

In focusing on potentially localizable cognitive impairments, the schizophrenia meta-analytic literature has overlooked the largest single impairment: on digit symbol coding tasks. To compare the magnitude of the schizophrenia impairment on coding tasks with impairments on other traditional neuropsychological instruments. MEDLINE and PsycINFO electronic databases and reference lists from identified articles. English-language studies from 1990 to present, comparing performance of patients with schizophrenia and healthy controls on coding tasks and cognitive measures representing at least 2 other cognitive domains. Of 182 studies identified, 40 met all criteria for inclusion in the meta-analysis. Means, standard deviations, and sample sizes were extracted for digit symbol coding and 36 other cognitive variables. In addition, we recorded potential clinical moderator variables, including chronicity/severity, medication status, age, and education, and potential study design moderators, including coding task variant, matching, and study publication date. Main analyses synthesized data from 37 studies comprising 1961 patients with schizophrenia and 1444 comparison subjects. Combination of mean effect sizes across studies by means of a random effects model yielded a weighted mean effect for digit symbol coding of g = -1.57 (95% confidence interval, -1.66 to -1.48). This effect compared with a grand mean effect of g = -0.98 and was significantly larger than effects for widely used measures of episodic memory, executive functioning, and working memory. Moderator variable analyses indicated that clinical and study design differences between studies had little effect on the coding task effect. Comparison with previous meta-analyses suggested that current results were representative of the broader literature. Subsidiary analysis of data from relatives of patients with schizophrenia also suggested prominent coding task impairments in this group. The 5-minute digit symbol coding task, reliable and easy to administer, taps an information processing inefficiency that is a central feature of the cognitive deficit in schizophrenia and deserves systematic investigation.

A Temporal Pattern Mining Approach for Classifying Electronic Health Record Data

PubMed Central

Batal, Iyad; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2013-01-01

We study the problem of learning classification models from complex multivariate temporal data encountered in electronic health record systems. The challenge is to define a good set of features that are able to represent well the temporal aspect of the data. Our method relies on temporal abstractions and temporal pattern mining to extract the classification features. Temporal pattern mining usually returns a large number of temporal patterns, most of which may be irrelevant to the classification task. To address this problem, we present the Minimal Predictive Temporal Patterns framework to generate a small set of predictive and non-spurious patterns. We apply our approach to the real-world clinical task of predicting patients who are at risk of developing heparin induced thrombocytopenia. The results demonstrate the benefit of our approach in efficiently learning accurate classifiers, which is a key step for developing intelligent clinical monitoring systems. PMID:25309815

Clinical judgment research on economic topics: Role of congruence of tasks in clinical practice.

PubMed

Huttin, Christine C

2017-01-01

This paper discusses what can ensure the performance of judgment studies with an information design that integrates economics of medical systems, in the context of digitalization of healthcare. It is part of a series of 5 methodological papers on statistical procedures and problems to implement judgment research designs and decision models, especially to address cost of care, and ways to measure conversation on cost of care between physicians and patients, with unstructured data such as economic narratives to complement billing and financial information (e.g. cost cognitive cues in conjoint or reversed conjoint designs). The paper discusses how congruence of tasks can increase the reliability of data. It uses some results of two Meta reviews of judgment studies in different fields of applications: psychology, business, medical sciences and education. It compares tests for congruence in judgment studies and efficiency tests in econometric studies.

Workplace learning through peer groups in medical school clerkships.

PubMed

Chou, Calvin L; Teherani, Arianne; Masters, Dylan E; Vener, Margo; Wamsley, Maria; Poncelet, Ann

2014-01-01

Purpose When medical students move from the classroom into clinical practice environments, their roles and learning challenges shift dramatically from a formal curricular approach to a workplace learning model. Continuity among peers during clinical clerkships may play an important role in this different mode of learning. We explored students' perceptions about how they achieved workplace learning in the context of intentionally formed or ad hoc peer groups. Method We invited students in clerkship program models with continuity (CMCs) and in traditional block clerkships (BCs) to complete a survey about peer relationships with open-ended questions based on a workplace learning framework, including themes of workplace-based relationships, the nature of work practices, and selection of tasks and activities. We conducted qualitative content analysis to characterize students' experiences. Results In both BCs and CMCs, peer groups provided rich resources, including anticipatory guidance about clinical expectations of students, best practices in interacting with patients and supervisors, helpful advice in transitioning between rotations, and information about implicit rules of clerkships. Students also used each other as benchmarks for gauging strengths and deficits in their own knowledge and skills. Conclusions Students achieve many aspects of workplace learning in clerkships through formal or informal workplace-based peer groups. In these groups, peers provide accessible, real-time, and relevant resources to help each other navigate transitions, clarify roles and tasks, manage interpersonal challenges, and decrease isolation. Medical schools can support effective workplace learning for medical students by incorporating continuity with peers in the main clinical clerkship year.

Workplace learning through peer groups in medical school clerkships.

PubMed

Chou, Calvin L; Teherani, Arianne; Masters, Dylan E; Vener, Margo; Wamsley, Maria; Poncelet, Ann

2014-01-01

When medical students move from the classroom into clinical practice environments, their roles and learning challenges shift dramatically from a formal curricular approach to a workplace learning model. Continuity among peers during clinical clerkships may play an important role in this different mode of learning. We explored students' perceptions about how they achieved workplace learning in the context of intentionally formed or ad hoc peer groups. We invited students in clerkship program models with continuity (CMCs) and in traditional block clerkships (BCs) to complete a survey about peer relationships with open-ended questions based on a workplace learning framework, including themes of workplace-based relationships, the nature of work practices, and selection of tasks and activities. We conducted qualitative content analysis to characterize students' experiences. In both BCs and CMCs, peer groups provided rich resources, including anticipatory guidance about clinical expectations of students, best practices in interacting with patients and supervisors, helpful advice in transitioning between rotations, and information about implicit rules of clerkships. Students also used each other as benchmarks for gauging strengths and deficits in their own knowledge and skills. Students achieve many aspects of workplace learning in clerkships through formal or informal workplace-based peer groups. In these groups, peers provide accessible, real-time, and relevant resources to help each other navigate transitions, clarify roles and tasks, manage interpersonal challenges, and decrease isolation. Medical schools can support effective workplace learning for medical students by incorporating continuity with peers in the main clinical clerkship year.

Official Positions for FRAX® clinical regarding falls and frailty: can falls and frailty be used in FRAX®? From Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

PubMed

Masud, Tahir; Binkley, Neil; Boonen, Steven; Hannan, Marian T

2011-01-01

Risk factors for fracture can be purely skeletal, e.g., bone mass, microarchitecture or geometry, or a combination of bone and falls risk related factors such as age and functional status. The remit of this Task Force was to review the evidence and consider if falls should be incorporated into the FRAX® model or, alternatively, to provide guidance to assist clinicians in clinical decision-making for patients with a falls history. It is clear that falls are a risk factor for fracture. Fracture probability may be underestimated by FRAX® in individuals with a history of frequent falls. The substantial evidence that various interventions are effective in reducing falls risk was reviewed. Targeting falls risk reduction strategies towards frail older people at high risk for indoor falls is appropriate. This Task Force believes that further fracture reduction requires measures to reduce falls risk in addition to bone directed therapy. Clinicians should recognize that patients with frequent falls are at higher fracture risk than currently estimated by FRAX® and include this in decision-making. However, quantitative adjustment of the FRAX® estimated risk based on falls history is not currently possible. In the long term, incorporation of falls as a risk factor in the FRAX® model would be ideal. Copyright © 2011 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Deception and false belief in paranoia: modelling theory of mind stories.

PubMed

Shryane, Nick M; Corcoran, Rhiannon; Rowse, Georgina; Moore, Rosanne; Cummins, Sinead; Blackwood, Nigel; Howard, Robert; Bentall, Richard P

2008-01-01

This study used Item Response Theory (IRT) to model the psychometric properties of a Theory of Mind (ToM) stories task. The study also aimed to determine whether the ability to understand states of false belief in others and the ability to understand another's intention to deceive are separable skills, and to establish which is more sensitive to the presence of paranoia. A large and diverse clinical and nonclinical sample differing in levels of depression and paranoid ideation performed a ToM stories task measuring false belief and deception at first and second order. A three-factor IRT model was found to best fit the data, consisting of first- and second-order deception factors and a single false-belief factor. The first-order deception and false-belief factors had good measurement properties at low trait levels, appropriate for samples with reduced ToM ability. First-order deception and false beliefs were both sensitive to paranoid ideation with IQ predicting performance on false belief items. Separable abilities were found to underlie performance on verbal ToM tasks. However, paranoia was associated with impaired performance on both false belief and deception understanding with clear impairment at the simplest level of mental state attribution.

Lifespan development of pro- and anti-saccades: multiple regression models for point estimates.

PubMed

Klein, Christoph; Foerster, Friedrich; Hartnegg, Klaus; Fischer, Burkhart

2005-12-07

The comparative study of anti- and pro-saccade task performance contributes to our functional understanding of the frontal lobes, their alterations in psychiatric or neurological populations, and their changes during the life span. In the present study, we apply regression analysis to model life span developmental effects on various pro- and anti-saccade task parameters, using data of a non-representative sample of 327 participants aged 9 to 88 years. Development up to the age of about 27 years was dominated by curvilinear rather than linear effects of age. Furthermore, the largest developmental differences were found for intra-subject variability measures and the anti-saccade task parameters. Ageing, by contrast, had the shape of a global linear decline of the investigated saccade functions, lacking the differential effects of age observed during development. While these results do support the assumption that frontal lobe functions can be distinguished from other functions by their strong and protracted development, they do not confirm the assumption of disproportionate deterioration of frontal lobe functions with ageing. We finally show that the regression models applied here to quantify life span developmental effects can also be used for individual predictions in applied research contexts or clinical practice.

Are Physicians Likely to Adopt Emerging Mobile Technologies? Attitudes and Innovation Factors Affecting Smartphone Use in the Southeastern United States

PubMed Central

Putzer, Gavin J; Park, Yangil

2012-01-01

The smartphone has emerged as an important technological device to assist physicians with medical decision making, clinical tasks, and other computing functions. A smartphone is a device that combines mobile telecommunication with Internet accessibility as well as word processing. Moreover, smartphones have additional features such as applications pertinent to clinical medicine and practice management. The purpose of this study was to investigate the innovation factors that affect a physician's decision to adopt an emerging mobile technological device such as a smartphone. The study sample consisted of 103 physicians from community hospitals and academic medical centers in the southeastern United States. Innovation factors are elements that affect an individual's attitude toward using and adopting an emerging technology. In our model, the innovation characteristics of compatibility, job relevance, the internal environment, observability, personal experience, and the external environment were all significant predictors of attitude toward using a smartphone. These influential innovation factors presumably are salient predictors of a physician's attitude toward using a smartphone to assist with clinical tasks. Health information technology devices such as smartphones offer promise as a means to improve clinical efficiency, medical quality, and care coordination and possibly reduce healthcare costs. PMID:22737094

Internal working models and adjustment of physically abused children: the mediating role of self-regulatory abilities.

PubMed

Hawkins, Amy L; Haskett, Mary E

2014-01-01

Abused children's internal working models (IWM) of relationships are known to relate to their socioemotional adjustment, but mechanisms through which negative representations increase vulnerability to maladjustment have not been explored. We sought to expand the understanding of individual differences in IWM of abused children and investigate the mediating role of self-regulation in links between IWM and adjustment. Cluster analysis was used to subgroup 74 physically abused children based on their IWM. Internal working models were identified by children's representations, as measured by a narrative story stem task. Self-regulation was assessed by teacher report and a behavioral task, and adjustment was measured by teacher report. Cluster analyses indicated two subgroups of abused children with distinct patterns of IWMs. Cluster membership predicted internalizing and externalizing problems. Associations between cluster membership and adjustment were mediated by children's regulation, as measured by teacher reports of many aspects of regulation. There was no support for mediation when regulation was measured by a behavioral task that tapped more narrow facets of regulation. Abused children exhibit clinically relevant individual differences in their IWMs; these models are linked to adjustment in the school setting, possibly through children's self-regulation. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

Improving performance of natural language processing part-of-speech tagging on clinical narratives through domain adaptation.

PubMed

Ferraro, Jeffrey P; Daumé, Hal; Duvall, Scott L; Chapman, Wendy W; Harkema, Henk; Haug, Peter J

2013-01-01

Natural language processing (NLP) tasks are commonly decomposed into subtasks, chained together to form processing pipelines. The residual error produced in these subtasks propagates, adversely affecting the end objectives. Limited availability of annotated clinical data remains a barrier to reaching state-of-the-art operating characteristics using statistically based NLP tools in the clinical domain. Here we explore the unique linguistic constructions of clinical texts and demonstrate the loss in operating characteristics when out-of-the-box part-of-speech (POS) tagging tools are applied to the clinical domain. We test a domain adaptation approach integrating a novel lexical-generation probability rule used in a transformation-based learner to boost POS performance on clinical narratives. Two target corpora from independent healthcare institutions were constructed from high frequency clinical narratives. Four leading POS taggers with their out-of-the-box models trained from general English and biomedical abstracts were evaluated against these clinical corpora. A high performing domain adaptation method, Easy Adapt, was compared to our newly proposed method ClinAdapt. The evaluated POS taggers drop in accuracy by 8.5-15% when tested on clinical narratives. The highest performing tagger reports an accuracy of 88.6%. Domain adaptation with Easy Adapt reports accuracies of 88.3-91.0% on clinical texts. ClinAdapt reports 93.2-93.9%. ClinAdapt successfully boosts POS tagging performance through domain adaptation requiring a modest amount of annotated clinical data. Improving the performance of critical NLP subtasks is expected to reduce pipeline error propagation leading to better overall results on complex processing tasks.

Biomarker and Clinical Trial Design Support for Disease-Modifying Therapies: Report of a Survey of the EU/US: Alzheimer's Disease Task Force.

PubMed

Cummings, J; Fox, N; Vellas, B; Aisen, P; Shan, G

2018-01-01

Disease-modifying therapies are urgently needed for the treatment of Alzheimer's disease (AD). The European Union/United States (EU/US) Task Force represents a broad range of stakeholders including biopharma industry personnel, academicians, and regulatory authorities. The EU/US Task Force represents a community of knowledgeable individuals who can inform views of evidence supporting disease modification and the development of disease-modifying therapies (DMTs). We queried their attitudes toward clinical trial design and biomarkers in support of DMTs. A survey of members of the EU/US Alzheimer's Disease Task Force was conducted. Ninety-three members (87%) responded. The details were analyzed to understand what clinical trial design and biomarker data support disease modification. Task Force members favored the parallel group design compared to delayed start or staggered withdrawal clinical trial designs to support disease modification. Amyloid biomarkers were regarded as providing mild support for disease modification while tau biomarkers were regarded as providing moderate support. Combinations of biomarkers, particularly combinations of tau and neurodegeneration, were regarded as providing moderate to marked support for disease modification and combinations of all three classes of biomarkers were regarded by a majority as providing marked support for disease modification. Task Force members considered that evidence derived from clinical trials and biomarkers supports clinical meaningfulness of an intervention, and when combined with a single clinical trial outcome, nearly all regarded the clinical trial design or biomarker evidence as supportive of disease modification. A minority considered biomarker evidence by itself as indicative of disease modification in prevention trials. Levels of evidence (A,B,C) were constructed based on these observations. The survey indicates the view of knowledgeable stakeholders regarding evidence derived from clinical trial design and biomarkers in support of disease modification. Results of this survey can assist in designing clinical trials of DMTs.

"It's Harder Than We Thought It Would Be": A Comparative Case Study of Expert-Novice Experimentation Strategies.

ERIC Educational Resources Information Center

Hmelo-Silver, Cindy E.; Nagarajan, Anandi; Day, Roger S.

2002-01-01

Compares a group of expert cancer researchers with four groups of fourth year medical students (the "novice" groups) engaged in the task of designing a clinical trial to test a new cancer drug using a computer-based modeling tool, the Oncology Thinking Cap. (Contains 24 references.) (Author/YDS)

Technical and Practical Issues in the Structure and Clinical Invariance of the Wechsler Scales: A Rejoinder to Commentaries

ERIC Educational Resources Information Center

Weiss, Lawrence G.; Keith, Timothy Z.; Zhu, Jianjun; Chen, Hsinyi

2013-01-01

This discussion article addresses issues related to expansion of the Wechsler model from four to five factors; multiple broad CHC abilities measured by the Arithmetic subtest; advantages and disadvantages of including complex tasks requiring integration of multiple broad abilities when measuring intelligence; limitations of factor analysis, which…

The impact of interoperability of electronic health records on ambulatory physician practices: a discrete-event simulation study.

PubMed

Zhou, Yuan; Ancker, Jessica S; Upadhye, Mandar; McGeorge, Nicolette M; Guarrera, Theresa K; Hegde, Sudeep; Crane, Peter W; Fairbanks, Rollin J; Bisantz, Ann M; Kaushal, Rainu; Lin, Li

2013-01-01

The effect of health information technology (HIT) on efficiency and workload among clinical and nonclinical staff has been debated, with conflicting evidence about whether electronic health records (EHRs) increase or decrease effort. None of this paper to date, however, examines the effect of interoperability quantitatively using discrete event simulation techniques. To estimate the impact of EHR systems with various levels of interoperability on day-to-day tasks and operations of ambulatory physician offices. Interviews and observations were used to collect workflow data from 12 adult primary and specialty practices. A discrete event simulation model was constructed to represent patient flows and clinical and administrative tasks of physicians and staff members. High levels of EHR interoperability were associated with reduced time spent by providers on four tasks: preparing lab reports, requesting lab orders, prescribing medications, and writing referrals. The implementation of an EHR was associated with less time spent by administrators but more time spent by physicians, compared with time spent at paper-based practices. In addition, the presence of EHRs and of interoperability did not significantly affect the time usage of registered nurses or the total visit time and waiting time of patients. This paper suggests that the impact of using HIT on clinical and nonclinical staff work efficiency varies, however, overall it appears to improve time efficiency more for administrators than for physicians and nurses.

Implementation of Task-Tracking Software for Clinical IT Management.

PubMed

Purohit, Anne-Maria; Brutscheck, Clemens; Prokosch, Hans-Ulrich; Ganslandt, Thomas; Schneider, Martin

2017-01-01

Often in clinical IT departments, many different methods and IT systems are used for task-tracking and project organization. Based on managers' personal preferences and knowledge about project management methods, tools differ from team to team and even from employee to employee. This causes communication problems, especially when tasks need to be done in cooperation with different teams. Monitoring tasks and resources becomes impossible: there are no defined deliverables, which prevents reliable deadlines. Because of these problems, we implemented task-tracking software which is now in use across all seven teams at the University Hospital Erlangen. Over a period of seven months, a working group defined types of tasks (project, routine task, etc.), workflows, and views to monitor the tasks of the 7 divisions, 20 teams and 340 different IT services. The software has been in use since December 2016.

Role of self-efficacy and anxiety among pre-clinically disabled older adults when using compensatory strategies to complete daily tasks

PubMed Central

Higgins, Torrance J.; Janelle, Christopher M.; Naugle, Kelly M.; Knaggs, Jeffrey; Hoover, Brian M.; Marsiske, Michael; Manini, Todd M.

2012-01-01

Classic developmental theory suggests that aging is associated with using compensatory strategies to prolong independence. While compensatory strategies are typically considered positive adaptations, they also signify an early phase in the disablement process — commonly known as pre-clinical disability. To build a better understanding of psychological constructs related to these early signs of disability, we examined the contribution of self-efficacy and state anxiety on using compensatory strategies among pre-clinically disabled older adults. Compensatory strategies were observed during performance of daily activities in 257 pre-clinically disabled older adults (67.6 ± 7.04), and self-efficacy and state anxiety were evaluated prior to performing each task. In univariate models, lower self-efficacy and higher anxiety were associated with more compensation (Spearman correlations: 0.15-0.48, p < 0.05). Multivariate logistic regression indicated that low self-efficacy [Odds Ratio (OR): 1.70; 95% Confidence Interval (CI): 1.40-2.08) and high anxiety (OR: 1.34; 95% CI: 1.10-1.63) were positively associated with using ≥ 6 compensatory strategies – a level signifying substantial compensation. When considered jointly with self-efficacy, the association with anxiety was reversed— higher anxiety demonstrated a lower likelihood of using compensation (OR: 0.70-0.73; 95% CI: 0.50-0.99). The addition of self-efficacy might remove the self-defeating cognitions characterizing anxiety allowing the remaining arousal component to appear beneficial. In conclusion, lower self-efficacy and higher anxiety are associated with using compensation to complete daily tasks among pre-clinically disabled older adults. Such psychological constructs may contribute to the use of compensatory strategies and represent future intervention targets to help reduce early signs of disability. PMID:22770713

Common data elements for preclinical epilepsy research: Standards for data collection and reporting. A TASK3 report of the AES/ILAE Translational Task Force of the ILAE.

PubMed

Harte-Hargrove, Lauren C; French, Jacqueline A; Pitkänen, Asla; Galanopoulou, Aristea S; Whittemore, Vicky; Scharfman, Helen E

2017-11-01

The major objective of preclinical translational epilepsy research is to advance laboratory findings toward clinical application by testing potential treatments in animal models of seizures and epilepsy. Recently there has been a focus on the failure of preclinical discoveries to translate reliably, or even to be reproduced in different laboratories. One potential cause is a lack of standardization in preclinical data collection. The resulting difficulties in comparing data across studies have led to high cost and missed opportunity, which in turn impede clinical trials and advances in medical care. Preclinical epilepsy research has successfully brought numerous antiseizure treatments into the clinical practice, yet the unmet clinical needs have prompted the reconsideration of research strategies to optimize epilepsy therapy development. In the field of clinical epilepsy there have been successful steps to improve such problems, such as generation of common data elements (CDEs) and case report forms (CRFs and standards of data collection and reporting) by a team of leaders in the field. Therefore, the Translational Task Force was appointed by the International League Against Epilepsy (ILAE) and the American Epilepsy Society (AES), in partnership with the National Institute of Neurological Disorders and Stroke (NINDS) and the National Institutes of Health (NIH) to define CDEs for animal epilepsy research studies and prepare guidelines for data collection and experimental procedures. If adopted, the preclinical CDEs could facilitate collaborative epilepsy research, comparisons of data across different laboratories, and promote rigor, transparency, and impact, particularly in therapy development. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Using linear programming to minimize the cost of nurse personnel.

PubMed

Matthews, Charles H

2005-01-01

Nursing personnel costs make up a major portion of most hospital budgets. This report evaluates and optimizes the utility of the nurse personnel at the Internal Medicine Outpatient Clinic of Wake Forest University Baptist Medical Center. Linear programming (LP) was employed to determine the effective combination of nurses that would allow for all weekly clinic tasks to be covered while providing the lowest possible cost to the department. Linear programming is a standard application of standard spreadsheet software that allows the operator to establish the variables to be optimized and then requires the operator to enter a series of constraints that will each have an impact on the ultimate outcome. The application is therefore able to quantify and stratify the nurses necessary to execute the tasks. With the report, a specific sensitivity analysis can be performed to assess just how sensitive the outcome is to the stress of adding or deleting a nurse to or from the payroll. The nurse employee cost structure in this study consisted of five certified nurse assistants (CNA), three licensed practicing nurses (LPN), and five registered nurses (RN). The LP revealed that the outpatient clinic should staff four RNs, three LPNs, and four CNAs with 95 percent confidence of covering nurse demand on the floor. This combination of nurses would enable the clinic to: 1. Reduce annual staffing costs by 16 percent; 2. Force each level of nurse to be optimally productive by focusing on tasks specific to their expertise; 3. Assign accountability more efficiently as the nurses adhere to their specific duties; and 4. Ultimately provide a competitive advantage to the clinic as it relates to nurse employee and patient satisfaction. Linear programming can be used to solve capacity problems for just about any staffing situation, provided the model is indeed linear.

Requirements and design aspects of a data model for a data dictionary in paediatric oncology.

PubMed

Merzweiler, A; Knaup, P; Creutzig, U; Ehlerding, H; Haux, R; Mludek, V; Schilling, F H; Weber, R; Wiedemann, T

2000-01-01

German children suffering from cancer are mostly treated within the framework of multicentre clinical trials. An important task of conducting these trials is an extensive information and knowledge exchange, which has to be based on a standardised documentation. To support this effort, it is the aim of a nationwide project to define a standardised terminology that should be used by clinical trials for therapy documentation. In order to support terminology maintenance we are currently developing a data dictionary. In this paper we describe requirements and design aspects of the data model used for the data dictionary as first results of our research. We compare it with other terminology systems.

Anxiety Evokes Hypofrontality and Disrupts Rule-Relevant Encoding by Dorsomedial Prefrontal Cortex Neurons.

PubMed

Park, Junchol; Wood, Jesse; Bondi, Corina; Del Arco, Alberto; Moghaddam, Bita

2016-03-16

Anxiety is a debilitating symptom of most psychiatric disorders, including major depression, post-traumatic stress disorder, schizophrenia, and addiction. A detrimental aspect of anxiety is disruption of prefrontal cortex (PFC)-mediated executive functions, such as flexible decision making. Here we sought to understand how anxiety modulates PFC neuronal encoding of flexible shifting between behavioral strategies. We used a clinically substantiated anxiogenic treatment to induce sustained anxiety in rats and recorded from dorsomedial PFC (dmPFC) and orbitofrontal cortex (OFC) neurons while they were freely moving in a home cage and while they performed a PFC-dependent task that required flexible switches between rules in two distinct perceptual dimensions. Anxiety elicited a sustained background "hypofrontality" in dmPFC and OFC by reducing the firing rate of spontaneously active neuronal subpopulations. During task performance, the impact of anxiety was subtle, but, consistent with human data, behavior was selectively impaired when previously correct conditions were presented as conflicting choices. This impairment was associated with reduced recruitment of dmPFC neurons that selectively represented task rules at the time of action. OFC rule representation was not affected by anxiety. These data indicate that a neural substrate of the decision-making deficits in anxiety is diminished dmPFC neuronal encoding of task rules during conflict-related actions. Given the translational relevance of the model used here, the data provide a neuronal encoding mechanism for how anxiety biases decision making when the choice involves overcoming a conflict. They also demonstrate that PFC encoding of actions, as opposed to cues or outcome, is especially vulnerable to anxiety. A debilitating aspect of anxiety is its impact on decision making and flexible control of behavior. These cognitive constructs depend on proper functioning of the prefrontal cortex (PFC). Understanding how anxiety affects PFC encoding of cognitive events is of great clinical and evolutionary significance. Using a clinically valid experimental model, we find that, under anxiety, decision making may be skewed by salient and conflicting environmental stimuli at the expense of flexible top-down guided choices. We also find that anxiety suppresses spontaneous activity of PFC neurons, and weakens encoding of task rules by dorsomedial PFC neurons. These data provide a neuronal encoding scheme for how anxiety disengages PFC during decision making. Copyright © 2016 the authors 0270-6474/16/363322-14$15.00/0.

Theory of Mind in Schizophrenia: Associations With Clinical and Cognitive Insight Controlling for Levels of Psychopathology.

PubMed

Popolo, Raffaele; Dimaggio, Giancarlo; Luther, Lauren; Vinci, Giancarlo; Salvatore, Giampaolo; Lysaker, Paul H

2016-03-01

Poor insight in schizophrenia is a risk factor for both poor outcomes and treatment adherence. Accordingly, interest in identifying causes of poor insight has increased. This study explored whether theory of mind (ToM) impairments are linked to poor clinical and cognitive insight independent of psychopathology. Participants with schizophrenia (n = 37) and control subjects (n = 40) completed assessments of ToM with the Hinting Task and the Brüne Picture Sequencing Task, clinical insight and psychopathology with the Positive and Negative Syndrome Scale, and cognitive insight with the Beck Cognitive Insight Scale. Results indicated that the schizophrenia group had greater impairments in ToM relative to control subjects. In the schizophrenia group, the Hinting Task performance was related to both cognitive and clinical insight, with only the relationship with cognitive insight persisting after controlling for psychopathology. Picture Sequencing Task performance was related to cognitive insight only. Future research directions and clinical implications are discussed.

Mirror Therapy and Task-Oriented Training for People With a Paretic Upper Extremity.

PubMed

Bondoc, Salvador; Booth, Julie; Budde, Grace; Caruso, Katelyn; DeSousa, Michelle; Earl, Brittany; Hammerton, Kaitlynn; Humphreys, Jill

This study investigates the effect of mirror therapy and task-oriented training on the paretic upper extremity function and occupational performance of people with stroke. This study used a repeated-measures, case-series design in which 4 participants completed a 4-wk intervention consisting of mirror therapy and task-specific training. The intervention was conducted 2×/wk in the clinic and 4×/wk at home. All participants displayed clinically meaningful improvements in self-identified goals at the end of the intervention and at follow-up. Three participants showed clinically meaningful changes in motor function. Although only 1 participant improved in his reported amount of use, all participants showed clinically meaningful improvements in perceived movement quality at varying points of assessment. Mirror therapy, when used as priming for task-oriented training, can produce clinical improvements in upper extremity function and occupational performance in people with hemiparesis. Copyright © 2018 by the American Occupational Therapy Association, Inc.

Human Research Program (HRP) Exploration Medical Capability (ExMC) Standing Review Panel (SRP)

NASA Technical Reports Server (NTRS)

Cintron, Nitza; Dutson, Eric; Friedl, Karl; Hyman, William; Jemison, Mae; Klonoff, David

2009-01-01

The SRP believes strongly that regularly performed in-flight crew assessments are needed in order to identify a change in health status before a medical condition becomes clinically apparent. It is this early recognition in change that constitutes the foundation of the "occupational health model" expounded in the HRP Requirements Document as a key component of the HRP risk mitigation strategy that will enable its objective of "prevention and mitigation of human health and performance risks". A regular crew status examination of physiological and clinical performance is needed. This can be accomplished through instrumented monitoring of routine embedded tasks. The SRP recommends addition of a new gap to address this action under Category 3.0 Mitigate the Risk. This new gap is closely associated with Task 4.19 which addresses the lack of adequate biomedical monitoring capabilities for performing periodic clinical status evaluations and contingency medical monitoring. A corollary to these gaps is the critical emphasis on preventive medicine, not only during pre- and post-flight phases of a mission as is the current practice, but continued into the in-flight phases of exploration class missions.

Electrophysiological Repetition Effects in Persons with Mild Cognitive Impairment depend upon Working Memory Demand.

PubMed

Broster, Lucas S; Jenkins, Shonna L; Holmes, Sarah D; Edwards, Matthew G; Jicha, Gregory A; Jiang, Yang

2018-05-07

Forms of implicit memory, including repetition effects, are preserved relative to explicit memory in clinical Alzheimer's disease. Consequently, cognitive interventions for persons with Alzheimer's disease have been developed that leverage this fact. However, despite the clinical robustness of behavioral repetition effects, altered neural mechanisms of repetition effects are studied as biomarkers of both clinical Alzheimer's disease and pre-morbid Alzheimer's changes in the brain. We hypothesized that the clinical preservation of behavioral repetition effects results in part from concurrent operation of discrete memory systems. We developed two experiments that included probes of emotional repetition effects differing in that one included an embedded working memory task. We found that neural repetition effects manifested in patients with amnestic mild cognitive impairment, the earliest form of clinical Alzheimer's disease, during emotional working memory tasks, but they did not manifest during the task that lacked the embedded working memory manipulation. Specifically, the working memory task evoked neural repetition effects in the P600 time-window, but the same neural mechanism was only minimally implicated in the task without a working memory component. We also found that group differences in behavioral repetition effects were smaller in the experiment with a working memory task. We suggest that cross-domain cognitive challenge can expose "defunct" neural capabilities of individuals with amnestic mild cognitive impairment. Copyright © 2018. Published by Elsevier Ltd.

Models of inhibitory control

PubMed Central

Logan, Gordon D.

2017-01-01

We survey models of response inhibition having different degrees of mathematical, computational and neurobiological specificity and generality. The independent race model accounts for performance of the stop-signal or countermanding task in terms of a race between GO and STOP processes with stochastic finishing times. This model affords insights into neurophysiological mechanisms that are reviewed by other authors in this volume. The formal link between the abstract GO and STOP processes and instantiating neural processes is articulated through interactive race models consisting of stochastic accumulator GO and STOP units. This class of model provides quantitative accounts of countermanding performance and replicates the dynamics of neural activity producing that performance. The interactive race can be instantiated in a network of biophysically plausible spiking excitatory and inhibitory units. Other models seek to account for interactions between units in frontal cortex, basal ganglia and superior colliculus. The strengths, weaknesses and relationships of the different models will be considered. We will conclude with a brief survey of alternative modelling approaches and a summary of problems to be addressed including accounting for differences across effectors, species, individuals, task conditions and clinical deficits. This article is part of the themed issue ‘Movement suppression: brain mechanisms for stopping and stillness’. PMID:28242727

Effort-Based Decision Making: A Novel Approach for Assessing Motivation in Schizophrenia

PubMed Central

Green, Michael F.; Horan, William P.; Barch, Deanna M.; Gold, James M.

2015-01-01

Because negative symptoms, including motivational deficits, are a critical unmet need in schizophrenia, there are many ongoing efforts to develop new pharmacological and psychosocial interventions for these impairments. A common challenge of these studies involves how to evaluate and select optimal endpoints. Currently, all studies of negative symptoms in schizophrenia depend on ratings from clinician-conducted interviews. Effort-based decision-making tasks may provide a more objective, and perhaps more sensitive, endpoint for trials of motivational negative symptoms. These tasks assess how much effort a person is willing to exert for a given level of reward. This area has been well-studied with animal models of effort and motivation, and effort-based decision-making tasks have been adapted for use in humans. Very recently, several studies have examined physical and cognitive types of effort-based decision-making tasks in cross-sectional studies of schizophrenia, providing evidence for effort-related impairment in this illness. This article covers the theoretical background on effort-based decision-making tasks to provide a context for the subsequent articles in this theme section. In addition, we review the existing literature of studies using these tasks in schizophrenia, consider some practical challenges in adapting them for use in clinical trials in schizophrenia, and discuss interpretive challenges that are central to these types of tasks. PMID:26089350

Prologue: Reading Comprehension Is Not a Single Ability.

PubMed

Catts, Hugh W; Kamhi, Alan G

2017-04-20

In this initial article of the clinical forum on reading comprehension, we argue that reading comprehension is not a single ability that can be assessed by one or more general reading measures or taught by a small set of strategies or approaches. We present evidence for a multidimensional view of reading comprehension that demonstrates how it varies as a function of reader ability, text, and task. The implications of this view for instruction of reading comprehension are considered. Reading comprehension is best conceptualized with a multidimensional model. The multidimensionality of reading comprehension means that instruction will be more effective when tailored to student performance with specific texts and tasks.

Model observer design for multi-signal detection in the presence of anatomical noise

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.; Park, Subok

2017-02-01

As psychophysical studies are resource-intensive to conduct, model observers are commonly used to assess and optimize medical imaging quality. Model observers are typically designed to detect at most one signal. However, in clinical practice, there may be multiple abnormalities in a single image set (e.g. multifocal multicentric (MFMC) breast cancer), which can impact treatment planning. Prevalence of signals can be different across anatomical regions, and human observers do not know the number or location of signals a priori. As new imaging techniques have the potential to improve multiple-signal detection (e.g. digital breast tomosynthesis may be more effective for diagnosis of MFMC than mammography), image quality assessment approaches addressing such tasks are needed. In this study, we present a model observer to detect multiple signals in an image dataset. A novel implementation of partial least squares (PLS) was developed to estimate different sets of efficient channels directly from the images. The PLS channels are adaptive to the characteristics of signals and the background, and they capture the interactions among signal locations. Corresponding linear decision templates are employed to generate both image-level and location-specific scores on the presence of signals. Our results show that: (1) the model observer can achieve high performance with a reasonably small number of channels; (2) the model observer with PLS channels outperforms that with benchmark modified Laguerre-Gauss channels, especially when realistic signal shapes and complex background statistics are involved; (3) the tasks of clinical interest, and other constraints such as sample size would alter the optimal design of the model observer.

Dual-task testing to predict falls in community-dwelling older adults: a systematic review.

PubMed

Muir-Hunter, S W; Wittwer, J E

2016-03-01

Cognitive impairment increases fall risk in older adults. Dual-task testing is an accepted way to assess the interaction between cognition and mobility; however, there is a lack of evidence-based recommendations for dual-task testing to evaluate fall risk in clinical practice. To evaluate the association between dual-task testing protocols and future fall risk, and to identify the specific dual-task test protocols associated with elevated risk. MEDLINE, Pubmed and EMBASE electronic databases were searched from January 1988 to September 2013. Two independent raters identified prospective cohort studies (duration of at least 1 year) of dual-task assessment in community-dwelling participants aged ≥60 years, with 'falls' as the primary outcome. Methodological quality was scored independently by two raters using a published checklist of criteria for evaluating threats to the validity of observational studies. Deterioration in gait during dual-task testing compared with single-task performance was associated with increased fall risk. Shortcomings within the literature significantly limit knowledge translation of dual-task gait protocols into clinical practice. There is a paucity of prospective studies on the association of dual-task gait assessment with fall risk. Changes in gait under dual-task testing are associated with future fall risk, and this association is stronger than that for single-task conditions. Limitations in the available literature preclude development of detailed recommendations for dual-task gait testing procedures in clinical practice to identify and stratify fall risk in older adults. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

The relationship between organizational climate and quality of chronic disease management.

PubMed

Benzer, Justin K; Young, Gary; Stolzmann, Kelly; Osatuke, Katerine; Meterko, Mark; Caso, Allison; White, Bert; Mohr, David C

2011-06-01

To test the utility of a two-dimensional model of organizational climate for explaining variation in diabetes care between primary care clinics. Secondary data were obtained from 223 primary care clinics in the Department of Veterans Affairs health care system. Organizational climate was defined using the dimensions of task and relational climate. The association between primary care organizational climate and diabetes processes and intermediate outcomes were estimated for 4,539 patients in a cross-sectional study. All data were collected from administrative datasets. The climate data were drawn from the 2007 VA All Employee Survey, and the outcomes data were collected as part of the VA External Peer Review Program. Climate data were aggregated to the facility level of analysis and merged with patient-level data. Relational climate was related to an increased likelihood of diabetes care process adherence, with significant but small effects for adherence to intermediate outcomes. Task climate was generally not shown to be related to adherence. The role of relational climate in predicting the quality of chronic care was supported. Future research should examine the mediators and moderators of relational climate and further investigate task climate. © Health Research and Educational Trust.

Observing health professionals' workflow patterns for diabetes care - First steps towards an ontology for EHR services.

PubMed

Schweitzer, M; Lasierra, N; Hoerbst, A

2015-01-01

Increasing the flexibility from a user-perspective and enabling a workflow based interaction, facilitates an easy user-friendly utilization of EHRs for healthcare professionals' daily work. To offer such versatile EHR-functionality, our approach is based on the execution of clinical workflows by means of a composition of semantic web-services. The backbone of such architecture is an ontology which enables to represent clinical workflows and facilitates the selection of suitable services. In this paper we present the methods and results after running observations of diabetes routine consultations which were conducted in order to identify those workflows and the relation among the included tasks. Mentioned workflows were first modeled by BPMN and then generalized. As a following step in our study, interviews will be conducted with clinical personnel to validate modeled workflows.

Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations.

PubMed

Neylon, J; Min, Y; Kupelian, P; Low, D A; Santhanam, A

2017-04-01

In this paper, a multi-GPU cloud-based server (MGCS) framework is presented for dose calculations, exploring the feasibility of remote computing power for parallelization and acceleration of computationally and time intensive radiotherapy tasks in moving toward online adaptive therapies. An analytical model was developed to estimate theoretical MGCS performance acceleration and intelligently determine workload distribution. Numerical studies were performed with a computing setup of 14 GPUs distributed over 4 servers interconnected by a 1 Gigabits per second (Gbps) network. Inter-process communication methods were optimized to facilitate resource distribution and minimize data transfers over the server interconnect. The analytically predicted computation time predicted matched experimentally observations within 1-5 %. MGCS performance approached a theoretical limit of acceleration proportional to the number of GPUs utilized when computational tasks far outweighed memory operations. The MGCS implementation reproduced ground-truth dose computations with negligible differences, by distributing the work among several processes and implemented optimization strategies. The results showed that a cloud-based computation engine was a feasible solution for enabling clinics to make use of fast dose calculations for advanced treatment planning and adaptive radiotherapy. The cloud-based system was able to exceed the performance of a local machine even for optimized calculations, and provided significant acceleration for computationally intensive tasks. Such a framework can provide access to advanced technology and computational methods to many clinics, providing an avenue for standardization across institutions without the requirements of purchasing, maintaining, and continually updating hardware.

Curriculum Recommendations of the AACP-PSSC Task Force on Caring for the Underserved

PubMed Central

Roche, Victoria F.; Assemi, Mitra; Conry, John M.; Shane-McWhorter, Laura; Sorensen, Todd D.

2008-01-01

A task force was convened by the American Association of Colleges of Pharmacy (AACP) and the Pharmaceutical Services Support Center (PSSC) and charged with the development of a curriculum framework to guide pharmacy programs in educating students on caring for the underserved. Utilizing a literature-based model, the task force constructed a framework that delineated evidence-based practice, clinical prevention and health promotion, health systems and policy, and community aspects of practice. Specific learning outcomes tailored to underserved populations were crafted and linked to resources readily available to the academy. The AACP-PSSC curriculum framework was shared with the academy in 2007. Schools and Colleges are urged to share experiences with implementation so that the impact of the tool can be evaluated. The task force recommends that the AACP Institutional Research Advisory Committee be involved in gathering assessment data. Implementation of the curriculum framework can help the academy fulfill the professional mandate to proactively provide the highest quality care to all, including underserved populations. PMID:18698398

The reliability and validity of a portfolio designed as a programmatic assessment of performance in an integrated clinical placement.

PubMed

Roberts, Chris; Shadbolt, Narelle; Clark, Tyler; Simpson, Phillip

2014-09-20

Little is known about the technical adequacy of portfolios in reporting multiple complex academic and performance-based assessments. We explored, first, the influencing factors on the precision of scoring within a programmatic assessment of student learning outcomes within an integrated clinical placement. Second, the degree to which validity evidence supported interpretation of student scores. Within generalisability theory, we estimated the contribution that each wanted factor (i.e. student capability) and unwanted factors (e.g. the impact of assessors) made to the variation in portfolio task scores. Relative and absolute standard errors of measurement provided a confidence interval around a pre-determined pass/fail standard for all six tasks. Validity evidence was sought through demonstrating the internal consistency of the portfolio and exploring the relationship of student scores with clinical experience. The mean portfolio mark for 257 students, across 372 raters, based on six tasks, was 75.56 (SD, 6.68). For a single student on one assessment task, 11% of the variance in scores was due to true differences in student capability. The most significant interaction was context specificity (49%), the tendency for one student to engage with one task and not engage with another task. Rater subjectivity was 29%. An absolute standard error of measurement of 4.74%, gave a 95% CI of +/- 9.30%, and a 68% CI of +/- 4.74% around a pass/fail score of 57%. Construct validity was supported by demonstration of an assessment framework, the internal consistency of the portfolio tasks, and higher scores for students who did the clinical placement later in the academic year. A portfolio designed as a programmatic assessment of an integrated clinical placement has sufficient evidence of validity to support a specific interpretation of student scores around passing a clinical placement. It has modest precision in assessing students' achievement of a competency standard. There were identifiable areas for reducing measurement error and providing more certainty around decision-making. Reducing the measurement error would require engaging with the student body on the value of the tasks, more focussed academic and clinical supervisor training, and revisiting the rubric of the assessment in the light of feedback.

Task-technology fit of video telehealth for nurses in an outpatient clinic setting.

PubMed

Cady, Rhonda G; Finkelstein, Stanley M

2014-07-01

Incorporating telehealth into outpatient care delivery supports management of consumer health between clinic visits. Task-technology fit is a framework for understanding how technology helps and/or hinders a person during work processes. Evaluating the task-technology fit of video telehealth for personnel working in a pediatric outpatient clinic and providing care between clinic visits ensures the information provided matches the information needed to support work processes. The workflow of advanced practice registered nurse (APRN) care coordination provided via telephone and video telehealth was described and measured using a mixed-methods workflow analysis protocol that incorporated cognitive ethnography and time-motion study. Qualitative and quantitative results were merged and analyzed within the task-technology fit framework to determine the workflow fit of video telehealth for APRN care coordination. Incorporating video telehealth into APRN care coordination workflow provided visual information unavailable during telephone interactions. Despite additional tasks and interactions needed to obtain the visual information, APRN workflow efficiency, as measured by time, was not significantly changed. Analyzed within the task-technology fit framework, the increased visual information afforded by video telehealth supported the assessment and diagnostic information needs of the APRN. Telehealth must provide the right information to the right clinician at the right time. Evaluating task-technology fit using a mixed-methods protocol ensured rigorous analysis of fit within work processes and identified workflows that benefit most from the technology.

Temporal abstraction and temporal Bayesian networks in clinical domains: a survey.

PubMed

Orphanou, Kalia; Stassopoulou, Athena; Keravnou, Elpida

2014-03-01

Temporal abstraction (TA) of clinical data aims to abstract and interpret clinical data into meaningful higher-level interval concepts. Abstracted concepts are used for diagnostic, prediction and therapy planning purposes. On the other hand, temporal Bayesian networks (TBNs) are temporal extensions of the known probabilistic graphical models, Bayesian networks. TBNs can represent temporal relationships between events and their state changes, or the evolution of a process, through time. This paper offers a survey on techniques/methods from these two areas that were used independently in many clinical domains (e.g. diabetes, hepatitis, cancer) for various clinical tasks (e.g. diagnosis, prognosis). A main objective of this survey, in addition to presenting the key aspects of TA and TBNs, is to point out important benefits from a potential integration of TA and TBNs in medical domains and tasks. The motivation for integrating these two areas is their complementary function: TA provides clinicians with high level views of data while TBNs serve as a knowledge representation and reasoning tool under uncertainty, which is inherent in all clinical tasks. Key publications from these two areas of relevance to clinical systems, mainly circumscribed to the latest two decades, are reviewed and classified. TA techniques are compared on the basis of: (a) knowledge acquisition and representation for deriving TA concepts and (b) methodology for deriving basic and complex temporal abstractions. TBNs are compared on the basis of: (a) representation of time, (b) knowledge representation and acquisition, (c) inference methods and the computational demands of the network, and (d) their applications in medicine. The survey performs an extensive comparative analysis to illustrate the separate merits and limitations of various TA and TBN techniques used in clinical systems with the purpose of anticipating potential gains through an integration of the two techniques, thus leading to a unified methodology for clinical systems. The surveyed contributions are evaluated using frameworks of respective key features. In addition, for the evaluation of TBN methods, a unifying clinical domain (diabetes) is used. The main conclusion transpiring from this review is that techniques/methods from these two areas, that so far are being largely used independently of each other in clinical domains, could be effectively integrated in the context of medical decision-support systems. The anticipated key benefits of the perceived integration are: (a) during problem solving, the reasoning can be directed at different levels of temporal and/or conceptual abstractions since the nodes of the TBNs can be complex entities, temporally and structurally and (b) during model building, knowledge generated in the form of basic and/or complex abstractions, can be deployed in a TBN. Copyright © 2014 Elsevier B.V. All rights reserved.

What physicians reason about during admission case review.

PubMed

Juma, Salina; Goldszmidt, Mark

2017-08-01

Research suggests that physicians perform multiple reasoning tasks beyond diagnosis during patient review. However, these remain largely theoretical. The purpose of this study was to explore reasoning tasks in clinical practice during patient admission review. The authors used a constant comparative approach-an iterative and inductive process of coding and recoding-to analyze transcripts from 38 audio-recorded case reviews between junior trainees and their senior residents or attendings. Using a previous list of reasoning tasks, analysis focused on what tasks were performed, when they occurred, and how they related to the other tasks. All 24 tasks were observed in at least one review with a mean of 17.9 (Min = 15, Max = 22) distinct tasks per review. Two new tasks-assess illness severity and patient decision-making capacity-were identified, thus 26 tasks were examined. Three overarching tasks were identified-assess priorities, determine and refine the most likely diagnosis and establish and refine management plans-that occurred throughout all stages of the case review starting from patient identification and continuing through to assessment and plan. A fourth possible overarching task-reflection-was also identified but only observed in four instances across three cases. The other 22 tasks appeared to be context dependent serving to support, expand, and refine one or more overarching tasks. Tasks were non-sequential and the same supporting task could serve more than one overarching task. The authors conclude that these findings provide insight into the 'what' and 'when' of physician reasoning during case review that can be used to support professional development, clinical training and patient care. In particular, they draw attention to the iterative way in which each task is addressed during a case review and how this finding may challenge conventional ways of teaching and assessing clinical communication and reasoning. They also suggest that further research is needed to explore how physicians decide why a supporting task is required in a particular context.

Variability sensitivity of dynamic texture based recognition in clinical CT data

NASA Astrophysics Data System (ADS)

Kwitt, Roland; Razzaque, Sharif; Lowell, Jeffrey; Aylward, Stephen

2014-03-01

Dynamic texture recognition using a database of template models has recently shown promising results for the task of localizing anatomical structures in Ultrasound video. In order to understand its clinical value, it is imperative to study the sensitivity with respect to inter-patient variability as well as sensitivity to acquisition parameters such as Ultrasound probe angle. Fully addressing patient and acquisition variability issues, however, would require a large database of clinical Ultrasound from many patients, acquired in a multitude of controlled conditions, e.g., using a tracked transducer. Since such data is not readily attainable, we advocate an alternative evaluation strategy using abdominal CT data as a surrogate. In this paper, we describe how to replicate Ultrasound variabilities by extracting subvolumes from CT and interpreting the image material as an ordered sequence of video frames. Utilizing this technique, and based on a database of abdominal CT from 45 patients, we report recognition results on an organ (kidney) recognition task, where we try to discriminate kidney subvolumes/videos from a collection of randomly sampled negative instances. We demonstrate that (1) dynamic texture recognition is relatively insensitive to inter-patient variation while (2) viewing angle variability needs to be accounted for in the template database. Since naively extending the template database to counteract variability issues can lead to impractical database sizes, we propose an alternative strategy based on automated identification of a small set of representative models.

Rational drug therapy education in clinical phase carried out by task-based learning

PubMed Central

Bilge, S. Sırrı; Akyüz, Bahar; Ağrı, Arzu Erdal; Özlem, Mıdık

2017-01-01

Objectives: Irrational drug use results in drug interactions, treatment noncompliance, and drug resistance. Rational pharmacotherapy education is being implemented in many faculties of medicine. Our aim is to introduce rational pharmacotherapy education by clinicians and to evaluate task-based rational drug therapy education in the clinical context. Methods: The Kirkpatrick's evaluation model was used for the evaluation of the program. The participants evaluated the program in terms of constituents of the program, utilization, and contribution to learning. Voluntary participants responded to the evaluation forms after the educational program. Data are evaluated using both quantitative and qualitative tools. SPSS (version 21) used for quantitative data for determining mean and standard deviation values. Descriptive qualitative analysis approach is used for the analysis of open-ended questions. Results: It was revealed that the program and its components have been favorable. A total 95.9% of the students consider the education to be beneficial. Simulated patients practice and personal drug choice/problem-based learning sessions were appreciated by the students in particular. 93.9% of the students stated that all students of medicine should undergo this educational program. Among the five presentations contained in the program, “The Principles of Prescribing” received the highest points (9 ± 1.00) from participating students in general evaluation of the educational program. Conclusion: This study was carried out to improve task-based rational drug therapy education. According to feedback from the students concerning content, method, resource, assessment, and program design; some important changes, especially in number of facilitators and indications, are made in rational pharmacotherapy education in clinical task-based learning program. PMID:28458432

Sex differences in behavioral outcome following neonatal hypoxia ischemia: insights from a clinical meta-analysis and a rodent model of induced hypoxic ischemic brain injury.

PubMed

Smith, Amanda L; Alexander, Michelle; Rosenkrantz, Ted S; Sadek, Mona Lisa; Fitch, R Holly

2014-04-01

Hypoxia ischemia (HI; reduced oxygen and/or blood flow to the brain) is one of the most common injuries among preterm infants and term infants with birth complications. Both populations show cognitive/behavioral deficits, including impairments in sensory, learning/memory, and attention domains. Clinical data suggests a sex difference in HI outcomes, with males exhibiting more severe cognitive/behavioral deficits relative to matched females. Our laboratory has also reported more severe behavioral deficits among male rats with induced HI relative to females with comparable injury (Hill et al., 2011a,b). The current study initially examined published clinical studies from the past 20years where long-term IQ outcome scores for matched groups of male and female premature infants were reported separately (IQ being the most common outcome measure). A meta-analysis revealed a female "advantage," as indicated by significantly better scores on performance and full scale IQ (but not verbal IQ) for premature females. We then utilized a rodent model of neonatal HI injury to assess sham and postnatal day 7 (P7) HI male and female rats on a battery of behavioral tasks. Results showed expected deficits in HI male rats, but also showed task-dependent sex differences, with HI males having significantly larger deficits than HI females on some tasks but equivalent deficits on other tasks. In contrast to behavioral results, post mortem neuropathology associated with HI was comparable across sex. These findings suggest: 1) neonatal female "protection" in some behavioral domains, as indexed by superior outcome following early injury relative to males; and 2) female protection may entail sex-specific plasticity or compensation, rather than a reduction in gross neuropathology. Further exploration of the mechanisms underlying this sex effect could aid in neuroprotection efforts for at-risk neonates in general, and males in particular. Moreover, our current report of comparable anatomical damage coupled with differences in cognitive outcomes (by sex) provides a framework for future studies to examine neural mechanisms underlying sex differences in cognition and behavior in general. Copyright © 2014. Published by Elsevier Inc.

Exploring clinical reasoning in novices: a self-regulated learning microanalytic assessment approach.

PubMed

Artino, Anthony R; Cleary, Timothy J; Dong, Ting; Hemmer, Paul A; Durning, Steven J

2014-03-01

The primary objectives of this study were to examine the regulatory processes of medical students as they completed a diagnostic reasoning task and to examine whether the strategic quality of these regulatory processes were related to short-term and longer-term medical education outcomes. A self-regulated learning (SRL) microanalytic assessment was administered to 71 second-year medical students while they read a clinical case and worked to formulate the most probable diagnosis. Verbal responses to open-ended questions targeting forethought and performance phase processes of a cyclical model of SRL were recorded verbatim and subsequently coded using a framework from prior research. Descriptive statistics and hierarchical linear regression models were used to examine the relationships between the SRL processes and several outcomes. Most participants (90%) reported focusing on specific diagnostic reasoning strategies during the task (metacognitive monitoring), but only about one-third of students referenced these strategies (e.g. identifying symptoms, integration) in relation to their task goals and plans for completing the task. After accounting for prior undergraduate achievement and verbal reasoning ability, strategic planning explained significant additional variance in course grade (ΔR(2 ) = 0.15, p < 0.01), second-year grade point average (ΔR(2) = 0.14, p < 0.01), United States Medical Licensing Examination Step 1 score (ΔR(2) = 0.08, p < 0.05) and National Board of Medical Examiner subject examination score in internal medicine (ΔR(2) = 0.10, p < 0.05). These findings suggest that most students in the formative stages of learning diagnostic reasoning skills are aware of and think about at least one key diagnostic reasoning process or strategy while solving a clinical case, but a substantially smaller percentage set goals or develop plans that incorporate such strategies. Given that students who developed more strategic plans achieved better outcomes, the potential importance of forethought regulatory processes is underscored. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Medical Education published by John Wiley & Sons Ltd.

Lack of sex effect on brain activity during a visuomotor response task: functional MR imaging study.

PubMed

Mikhelashvili-Browner, Nina; Yousem, David M; Wu, Colin; Kraut, Michael A; Vaughan, Christina L; Oguz, Kader Karli; Calhoun, Vince D

2003-03-01

As more individuals are enrolled in clinical functional MR imaging (fMRI) studies, an understanding of how sex may influence fMRI-measured brain activation is critical. We used fixed- and random-effects models to study the influence of sex on fMRI patterns of brain activation during a simple visuomotor reaction time task in the group of 26 age-matched men and women. We evaluated the right visual, left visual, left primary motor, left supplementary motor, and left anterior cingulate areas. Volumes of activations did not significantly differ between the groups in any defined regions. Analysis of variance failed to show any significant correlations between sex and volumes of brain activation in any location studied. Mean percentage signal-intensity changes for all locations were similar between men and women. A two-way t test of brain activation in men and women, performed as a part of random-effects modeling, showed no significant difference at any site. Our results suggest that sex seems to have little influence on fMRI brain activation when we compared performance on the simple reaction-time task. The need to control for sex effects is not critical in the analysis of this task with fMRI.

Assessing Mobile Health Capacity and Task Shifting Strategies to Improve Hypertension Among Ghanaian Stroke Survivors.

PubMed

Nichols, Michelle; Sarfo, Fred Stephen; Singh, Arti; Qanungo, Suparna; Treiber, Frank; Ovbiagele, Bruce; Saulson, Raelle; Patel, Sachin; Jenkins, Carolyn

2017-12-01

There has been a tremendous surge in stroke prevalence in sub-Saharan Africa. Hypertension (HTN), the most potent, modifiable risk factor for stroke, is a particular challenge in sub-Saharan Africa. Culturally sensitive, efficacious HTN control programs that are timely and sustainable are needed, especially among stroke survivors. Mobile health (mHealth) technology and task-shifting offer promising approaches to address this need. Using a concurrent triangulation design, we collected data from stroke survivors, caregivers, community leaders, clinicians and hospital personnel to explore the barriers, facilitators and perceptions toward mHealth related to HTN management among poststroke survivors in Ghana. Exploration included perceptions of a nurse-led navigational model to facilitate care delivery and willingness of stroke survivors and caregivers to use mHealth technology. Two hundred stroke survivors completed study surveys while focus groups (n = 4) were conducted with stroke survivors, caregivers and community leaders (n = 28). Key informant interviews were completed with clinicians and hospital personnel (n = 10). A total of 93% of survey respondents had HTN (60% uncontrolled). Findings support mHealth strategies for poststroke care delivery and HTN management and for task-shifting through a nurse-led model. Of survey and focus group participants, 76% and 78.6%, respectively, have access to mobile phones and 90% express comfort in using mobile phones and conveyed assurance that task-shifting through a nurse-led model could facilitate management of HTN. Findings also identified barriers to care delivery and medication adherence across all levels of the social ecological model. Participants strongly supported enhanced care delivery through mobile health and were receptive toward a nurse-led navigational model. Copyright © 2017 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

A chain-retrieval model for voluntary task switching.

PubMed

Vandierendonck, André; Demanet, Jelle; Liefooghe, Baptist; Verbruggen, Frederick

2012-09-01

To account for the findings obtained in voluntary task switching, this article describes and tests the chain-retrieval model. This model postulates that voluntary task selection involves retrieval of task information from long-term memory, which is then used to guide task selection and task execution. The model assumes that the retrieved information consists of acquired sequences (or chains) of tasks, that selection may be biased towards chains containing more task repetitions and that bottom-up triggered repetitions may overrule the intended task. To test this model, four experiments are reported. In Studies 1 and 2, sequences of task choices and the corresponding transition sequences (task repetitions or switches) were analyzed with the help of dependency statistics. The free parameters of the chain-retrieval model were estimated on the observed task sequences and these estimates were used to predict autocorrelations of tasks and transitions. In Studies 3 and 4, sequences of hand choices and their transitions were analyzed similarly. In all studies, the chain-retrieval model yielded better fits and predictions than statistical models of event choice. In applications to voluntary task switching (Studies 1 and 2), all three parameters of the model were needed to account for the data. When no task switching was required (Studies 3 and 4), the chain-retrieval model could account for the data with one or two parameters clamped to a neutral value. Implications for our understanding of voluntary task selection and broader theoretical implications are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Factors That May Explain Differences between Home and Clinic Meal Preparation Task Assessments in Frail Older Adults

ERIC Educational Resources Information Center

Provencher, Veronique; Demers, Louise; Gelinas, Isabelle

2012-01-01

Meal preparation assessments conducted in clinical environments (such as rehabilitation settings) might not reflect frail patients' performance at home. In addition, factors that may explain differences in performance between settings remain unknown. The aim of this study was to compare home and clinic performance on meal preparation tasks in…

Interpretation and use of FRAX in clinical practice - position paper of the International Osteoporosis Foundation and the International Society for Clinical Densitometry

USDA-ARS?s Scientific Manuscript database

The International Osteoporosis Foundation (IOF) and the International Society for Clinical Densitometry (ISCD) appointed a joint Task Force to develop resource documents in order to make recommendations on how to improve FRAX and better inform clinicians who use FRAX. The Task Force met in November...

Challenges and practical approaches with word sense disambiguation of acronyms and abbreviations in the clinical domain.

PubMed

Moon, Sungrim; McInnes, Bridget; Melton, Genevieve B

2015-01-01

Although acronyms and abbreviations in clinical text are used widely on a daily basis, relatively little research has focused upon word sense disambiguation (WSD) of acronyms and abbreviations in the healthcare domain. Since clinical notes have distinctive characteristics, it is unclear whether techniques effective for acronym and abbreviation WSD from biomedical literature are sufficient. The authors discuss feature selection for automated techniques and challenges with WSD of acronyms and abbreviations in the clinical domain. There are significant challenges associated with the informal nature of clinical text, such as typographical errors and incomplete sentences; difficulty with insufficient clinical resources, such as clinical sense inventories; and obstacles with privacy and security for conducting research with clinical text. Although we anticipated that using sophisticated techniques, such as biomedical terminologies, semantic types, part-of-speech, and language modeling, would be needed for feature selection with automated machine learning approaches, we found instead that simple techniques, such as bag-of-words, were quite effective in many cases. Factors, such as majority sense prevalence and the degree of separateness between sense meanings, were also important considerations. The first lesson is that a comprehensive understanding of the unique characteristics of clinical text is important for automatic acronym and abbreviation WSD. The second lesson learned is that investigators may find that using simple approaches is an effective starting point for these tasks. Finally, similar to other WSD tasks, an understanding of baseline majority sense rates and separateness between senses is important. Further studies and practical solutions are needed to better address these issues.

Job Analysis and Student Assessment Tool: Perfusion Education Clinical Preceptor

PubMed Central

Riley, Jeffrey B.

2007-01-01

Abstract: The perfusion education system centers on the cardiac surgery operating room and the perfusionist teacher who serves as a preceptor for the perfusion student. One method to improve the quality of perfusion education is to create a valid method for perfusion students to give feedback to clinical teachers. The preceptor job analysis consisted of a literature review and interviews with preceptors to list their critical tasks, critical incidents, and cognitive and behavioral competencies. Behaviorally anchored rating traits associated with the preceptors’ tasks were identified. Students voted to validate the instrument items. The perfusion instructor rating instrument with a 0–4, “very weak” to “very strong” Likert rating scale was used. The five preceptor traits for student evaluation of clinical instruction (SECI) are as follows: The clinical instructor (1) encourages self-learning, (2) encourages clinical reasoning, (3) meets student’s learning needs, (4) gives continuous feedback, and (5) represents a good role model. Scores from 430 student–preceptor relationships for 28 students rotating at 24 affiliate institutions with 134 clinical instructors were evaluated. The mean overall good preceptor average (GPA) was 3.45 ± 0.76 and was skewed to the left, ranging from 0.0 to 4.0 (median = 3.8). Only 21 of the SECI relationships earned a GPA <2.0. Analyzing the role of the clinical instructor and performing SECI are methods to provide valid information to improve the quality of a perfusion education program. PMID:17972453

Non-invasive brain stimulation and computational models in post-stroke aphasic patients: single session of transcranial magnetic stimulation and transcranial direct current stimulation. A randomized clinical trial.

PubMed

Santos, Michele Devido Dos; Cavenaghi, Vitor Breseghello; Mac-Kay, Ana Paula Machado Goyano; Serafim, Vitor; Venturi, Alexandre; Truong, Dennis Quangvinh; Huang, Yu; Boggio, Paulo Sérgio; Fregni, Felipe; Simis, Marcel; Bikson, Marom; Gagliardi, Rubens José

2017-01-01

Patients undergoing the same neuromodulation protocol may present different responses. Computational models may help in understanding such differences. The aims of this study were, firstly, to compare the performance of aphasic patients in naming tasks before and after one session of transcranial direct current stimulation (tDCS), transcranial magnetic stimulation (TMS) and sham, and analyze the results between these neuromodulation techniques; and secondly, through computational model on the cortex and surrounding tissues, to assess current flow distribution and responses among patients who received tDCS and presented different levels of results from naming tasks. Prospective, descriptive, qualitative and quantitative, double blind, randomized and placebo-controlled study conducted at Faculdade de Ciências Médicas da Santa Casa de São Paulo. Patients with aphasia received one session of tDCS, TMS or sham stimulation. The time taken to name pictures and the response time were evaluated before and after neuromodulation. Selected patients from the first intervention underwent a computational model stimulation procedure that simulated tDCS. The results did not indicate any statistically significant differences from before to after the stimulation.The computational models showed different current flow distributions. The present study did not show any statistically significant difference between tDCS, TMS and sham stimulation regarding naming tasks. The patients'responses to the computational model showed different patterns of current distribution.

Immunological Targeting of Tumor Initiating Prostate Cancer Cells

DTIC Science & Technology

2014-10-01

clinically using well-accepted immuno-competent animal models. 2) Keywords: Prostate Cancer, Lymphocyte, Vaccine, Antibody 3) Overall Project Summary...castrate animals . Task 1: Identify and verify antigenic targets from CAstrate Resistant Luminal Epithelial Cells (CRLEC) (months 1-16... animals per group will be processed to derive sufficient RNA for microarray analysis; the experiment will be repeated x 3. Microarray analysis will

Altered attentional processing in male and female rats in a prenatal valproic acid exposure model of autism spectrum disorder.

PubMed

Anshu, Kumari; Nair, Ajay Kumar; Kumaresan, U D; Kutty, Bindu M; Srinath, Shoba; Laxmi, T Rao

2017-12-01

Attention is foundational to efficient perception and optimal goal driven behavior. Intact attentional processing is crucial for the development of social and communication skills. Deficits in attention are therefore likely contributors to the core pathophysiology of autism spectrum disorder (ASD). Clinical evidence in ASD is suggestive of impairments in attention and its control, but the underlying mechanisms remain elusive. We examined sustained, spatially divided attention in a prenatal valproic acid (VPA) model of ASD using the 5-choice serial reaction time task (5-CSRTT). As compared to controls, male and female VPA rats had progressively lower accuracy and higher omissions with increasing attentional demands during 5-CSRTT training, and showed further performance decrements when subjected to parametric task manipulations. It is noteworthy that although VPA exposure induced attentional deficits in both sexes, there were task parameter specific sex differences. Importantly, we did not find evidence of impulsivity or motivational deficits in VPA rats but we did find reduced social preference, as well as sensorimotor deficits that suggest pre-attentional information processing impairments. Importantly, with fixed rules, graded difficulty levels, and more time, VPA rats could be successfully trained on the attentional task. To the best of our knowledge, this is the first study examining attentional functions in a VPA model. Our work underscores the need for studying both sexes in ASD animal models and validates the use of the VPA model in the quest for mechanistic understanding of aberrant attentional functions and for evaluating suitable therapeutic targets. Autism Res 2017, 10: 1929-1944. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. We studied rats prenatally exposed to valproic acid (VPA), an established rodent model of autism. Both male and female VPA rats had a range of attentional impairments with sex-specific characteristics. Importantly, with fixed rules, graded difficulty levels, and more time, VPA rats could be successfully trained on the attentional task. Our work validates the use of the VPA model in the quest for evaluating suitable therapeutic targets for improving attentional performance. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Three-dimensional high-definition neuroendoscopic surgery: a controlled comparative laboratory study with two-dimensional endoscopy and clinical application.

PubMed

Inoue, Daisuke; Yoshimoto, Koji; Uemura, Munenori; Yoshida, Masaki; Ohuchida, Kenoki; Kenmotsu, Hajime; Tomikawa, Morimasa; Sasaki, Tomio; Hashizume, Makoto

2013-11-01

The purpose of this research was to investigate the usefulness of three-dimensional (3D) endoscopy compared with two-dimensional (2D) endoscopy in neuroendoscopic surgeries in a comparative study and to test the clinical applications. Forty-three examinees were divided into three groups according to their endoscopic experience: novice, beginner, or expert. Examinees performed three separate tasks using 3D and 2D endoscopy. A recently developed 3D high-definition (HD) neuroendoscope, 4.7 mm in diameter (Shinko Optical Co., Ltd., Tokyo, Japan) was used. In one of the three tasks, we developed a full-sized skull model of acrylic-based plastic using a 3D printer and a patient's thin slice computed tomography data, and evaluated the execution time and total path length of the tip of the pointer using an optical tracking system. Sixteen patients underwent endoscopic transnasal transsphenoidal pituitary surgery using both 3D and 2D endoscopy. Horizontal motion was evaluated using task 1, and anteroposterior motion was evaluated with task 3. Execution time and total path length in task 3 using the 3D system in both novice and beginner groups were significantly shorter than with the 2D system (p < 0.05), although no significant difference between 2D and 3D systems in task 1 was seen. In both the novice and beginner groups, the 3D system was better for depth perception than horizontal motion. No difference was seen in the expert group in this regard. The 3D HD endoscope was used for the pituitary surgery and was found very useful to identify the spatial relationship of carotid arteries and bony structures. The use of a 3D neuroendoscope improved depth perception and task performance. Our results suggest that 3D endoscopes could shorten the learning curve of young neurosurgeons and play an important role in both general surgery and neurosurgery. Georg Thieme Verlag KG Stuttgart · New York.

Redesign of a university hospital preanesthesia evaluation clinic using a queuing theory approach.

PubMed

Zonderland, Maartje E; Boer, Fredrik; Boucherie, Richard J; de Roode, Annemiek; van Kleef, Jack W

2009-11-01

Changes in patient length of stay (the duration of 1 clinic visit) as a result of the introduction of an electronic patient file system forced an anesthesia department to change its outpatient clinic organization. In this study, we sought to demonstrate how the involvement of essential employees combined with mathematical techniques to support the decision-making process resulted in a successful intervention. The setting is the preanesthesia evaluation clinic (PAC) of a university hospital, where patients consult several medical professionals, either by walk-in or appointment. Queuing theory was used to model the initial set-up of the clinic, and later to model possible alternative designs. With the queuing model, possible improvements in efficiency could be investigated. Inputs to the model were patient arrival rates and expected service times with clinic employees, collected from the clinic's logging system and by observation. The performance measures calculated with the model were patient length of stay and employee utilization rate. Supported by the model outcomes, a working group consisting of representatives of all clinic employees decided whether the initial design should be maintained or an intervention was needed. The queuing model predicted that 3 of the proposed alternatives would result in better performance. Key points in the intervention were the rescheduling of appointments and the reallocation of tasks. The intervention resulted in a shortening of the time the anesthesiologist needed to decide upon approving the patient for surgery. Patient arrivals increased sharply over 1 yr by more than 16%; however, patient length of stay at the clinic remained essentially unchanged. If the initial set-up of the clinic would have been maintained, the patient length of stay would have increased dramatically. Queuing theory provides robust methods to evaluate alternative designs for the organization of PACs. In this article, we show that queuing modeling is an adequate approach for redesigning processes in PACs.

Identifying adverse drug event information in clinical notes with distributional semantic representations of context.

PubMed

Henriksson, Aron; Kvist, Maria; Dalianis, Hercules; Duneld, Martin

2015-10-01

For the purpose of post-marketing drug safety surveillance, which has traditionally relied on the voluntary reporting of individual cases of adverse drug events (ADEs), other sources of information are now being explored, including electronic health records (EHRs), which give us access to enormous amounts of longitudinal observations of the treatment of patients and their drug use. Adverse drug events, which can be encoded in EHRs with certain diagnosis codes, are, however, heavily underreported. It is therefore important to develop capabilities to process, by means of computational methods, the more unstructured EHR data in the form of clinical notes, where clinicians may describe and reason around suspected ADEs. In this study, we report on the creation of an annotated corpus of Swedish health records for the purpose of learning to identify information pertaining to ADEs present in clinical notes. To this end, three key tasks are tackled: recognizing relevant named entities (disorders, symptoms, drugs), labeling attributes of the recognized entities (negation, speculation, temporality), and relationships between them (indication, adverse drug event). For each of the three tasks, leveraging models of distributional semantics - i.e., unsupervised methods that exploit co-occurrence information to model, typically in vector space, the meaning of words - and, in particular, combinations of such models, is shown to improve the predictive performance. The ability to make use of such unsupervised methods is critical when faced with large amounts of sparse and high-dimensional data, especially in domains where annotated resources are scarce. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

EHR-based phenotyping: Bulk learning and evaluation.

PubMed

Chiu, Po-Hsiang; Hripcsak, George

2017-06-01

In data-driven phenotyping, a core computational task is to identify medical concepts and their variations from sources of electronic health records (EHR) to stratify phenotypic cohorts. A conventional analytic framework for phenotyping largely uses a manual knowledge engineering approach or a supervised learning approach where clinical cases are represented by variables encompassing diagnoses, medicinal treatments and laboratory tests, among others. In such a framework, tasks associated with feature engineering and data annotation remain a tedious and expensive exercise, resulting in poor scalability. In addition, certain clinical conditions, such as those that are rare and acute in nature, may never accumulate sufficient data over time, which poses a challenge to establishing accurate and informative statistical models. In this paper, we use infectious diseases as the domain of study to demonstrate a hierarchical learning method based on ensemble learning that attempts to address these issues through feature abstraction. We use a sparse annotation set to train and evaluate many phenotypes at once, which we call bulk learning. In this batch-phenotyping framework, disease cohort definitions can be learned from within the abstract feature space established by using multiple diseases as a substrate and diagnostic codes as surrogates. In particular, using surrogate labels for model training renders possible its subsequent evaluation using only a sparse annotated sample. Moreover, statistical models can be trained and evaluated, using the same sparse annotation, from within the abstract feature space of low dimensionality that encapsulates the shared clinical traits of these target diseases, collectively referred to as the bulk learning set. Copyright © 2017 Elsevier Inc. All rights reserved.

A break-even analysis of optimum faculty assignment for ambulatory primary care training.

PubMed

Xakellis, G C; Gjerde, C L; Xakellis, M G; Klitgaard, D

1996-12-01

The increased demand that faculty teach residents in ambulatory clinics necessitates the development of ambulatory care teaching models that are both educationally effective and financially viable. This study was designed to identify the resident-to-faculty ratios needed to provide financially viable faculty supervision of residents while maintaining acceptable resident waiting times for teaching. A computer simulation was developed to estimate the number of residents one or two faculty teachers could supervise in a university-based primary care teaching clinic. The number of residents was calculated for three waiting-time constraints and three scenarios of faculty tasks. A financial analysis of each model was performed. With no non-teaching tasks, two teachers were able to supervise 11 residents and keep waiting times under two minutes, while one teacher was able to supervise only three residents with this waiting-time constraint. The financial break-even point was achieved by all of the two-teacher models, but by none of the one-teacher models. In all three scenarios, using two teachers resulted in more than double the number of residents supervised and in higher utilization of faculty time (higher productivity) than did using one teacher. The two-teacher models of ambulatory supervision allowed for sufficient numbers of residents to be supervised so that teaching costs could be covered from patient care revenues; the one-teacher models did not break even financially. These simulations offer a viable option for academic institutions that are struggling to maintain teaching quality in the face of financial constraints.

A Chain-Retrieval Model for Voluntary Task Switching

ERIC Educational Resources Information Center

Vandierendonck, Andre; Demanet, Jelle; Liefooghe, Baptist; Verbruggen, Frederick

2012-01-01

To account for the findings obtained in voluntary task switching, this article describes and tests the chain-retrieval model. This model postulates that voluntary task selection involves retrieval of task information from long-term memory, which is then used to guide task selection and task execution. The model assumes that the retrieved…

Practice management based on risk assessment.

PubMed

Sandberg, Hans

2004-01-01

The management of a dental practice is most often focused on what clinicians do (production of items), and not so much on what is achieved in terms of oral health. The main reason for this is probably that it is easier to measure production and more difficult to measure health outcome. This paper presents a model based on individual risk assessment that aims to achieve a financially sound economy and good oral health. The close-to-the-clinic management tool, the HIDEP Model (Health Improvement in a DEntal Practice) was pioneered initially in Sweden at the end of 1980s. The experience over a 15-year period with different elements of the model is presented, including: the basis of examination and risk assessment; motivation; task delegation and leadership issues; health-finance evaluations; and quality development within a dental clinic. DentiGroupXL, a software program designed to support the work based on the model, is also described.

Development of job standards for clinical nutrition therapy for dyslipidemia patients.

PubMed

Kang, Min-Jae; Seo, Jung-Sook; Kim, Eun-Mi; Park, Mi-Sun; Woo, Mi-Hye; Ju, Dal-Lae; Wie, Gyung-Ah; Lee, Song-Mi; Cha, Jin-A; Sohn, Cheong-Min

2015-04-01

Dyslipidemia has significantly contributed to the increase of death and morbidity rates related to cardiovascular diseases. Clinical nutrition service provided by dietitians has been reported to have a positive effect on relief of medical symptoms or reducing the further medical costs. However, there is a lack of researches to identify key competencies and job standard for clinical dietitians to care patients with dyslipidemia. Therefore, the purpose of this study was to analyze the job components of clinical dietitian and develop the standard for professional practice to provide effective nutrition management for dyslipidemia patients. The current status of clinical nutrition therapy for dyslipidemia patients in hospitals with 300 or more beds was studied. After duty tasks and task elements of nutrition care process for dyslipidemia clinical dietitians were developed by developing a curriculum (DACUM) analysis method. The developed job standards were pretested in order to evaluate job performance, difficulty, and job standards. As a result, the job standard included four jobs, 18 tasks, and 53 task elements, and specific job description includes 73 basic services and 26 recommended services. When clinical dietitians managing dyslipidemia patients performed their practice according to this job standard for 30 patients the job performance rate was 68.3%. Therefore, the job standards of clinical dietitians for clinical nutrition service for dyslipidemia patients proposed in this study can be effectively used by hospitals.

Task Models in the Digital Ocean

ERIC Educational Resources Information Center

DiCerbo, Kristen E.

2014-01-01

The Task Model is a description of each task in a workflow. It defines attributes associated with that task. The creation of task models becomes increasingly important as the assessment tasks become more complex. Explicitly delineating the impact of task variables on the ability to collect evidence and make inferences demands thoughtfulness from…

Can we teach core clinical obstetrics and gynaecology skills using low fidelity simulation in an interprofessional setting?

PubMed

Kumar, Arunaz; Gilmour, Carole; Nestel, Debra; Aldridge, Robyn; McLelland, Gayle; Wallace, Euan

2014-12-01

Core clinical skills acquisition is an essential component of undergraduate medical and midwifery education. Although interprofessional education is an increasingly common format for learning efficient teamwork in clinical medicine, its value in undergraduate education is less clear. We present a collaborative effort from the medical and midwifery schools of Monash University, Melbourne, towards the development of an educational package centred around a core skills-based workshop using low fidelity simulation models in an interprofessional setting. Detailed feedback on the package was positive with respect to the relevance of the teaching content, whether the topic was well taught by task trainers and simulation models used, pitch of level of teaching and perception of confidence gained in performing the skill on a real patient after attending the workshop. Overall, interprofessional core skills training using low fidelity simulation models introduced at an undergraduate level in medicine and midwifery had a good acceptance. © 2014 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

CLT and CLS job responsibilities: current distinctions and updates.

PubMed

Doig, K; Beck, S J; Kolenc, K

2001-01-01

This study was undertaken to address the following questions: 1. What tasks distinguish the job of a clinical laboratory scientist (CLS) from that of a clinical laboratory technician (CLT)? 2. What changes in role distinctions, have occurred for entry-level CLS and CLT practitioners over the five-year period 1993-98? 3. What tasks have been deleted from the CLT and CLS content outlines because they were not frequently performed or not considered entry-level? 4. What changes in practice are reflected in the current job analyses? A national job analysis of tasks constituting the job of clinical laboratory scientists (CLSs) and clinical laboratory technicians (CLTs) was conducted in 1998-99 as part of a standard setting process for the certifying examinations of the National Credentialing Agency for Laboratory Personnel (NCA). The job analyses relied upon mail surveys to 1200 individuals for each job level asking respondents to identify tasks significant to effective practice at job entry. The task lists resulting from statistical analysis of those surveys were examined to answer the study questions. The sample for each survey included 1200 practitioners, educators and laboratory managers selected at random from membership in professional organizations or from NCA certificant lists. Sampling was stratified to insure adequate practitioner representation. The mean rating on a four point scale for each item on the surveys was evaluated for overall significance as well as significance across geographic regions. The tasks meeting specified criteria were retained in the final task lists. Tasks were counted and their content evaluated to compare CLS and CLT job tasks. The response rates to the surveys were 33% for CLT and 21% for CLS. Reliability was judged based on average intraclass correlation coefficients of .86 and .82 for the CLT and CLS surveys, respectively. There were 952 tasks retained on the CLS content outline and 725 retained on the CLT content outline of the 1151 tasks on the original survey. Seven hundred and twenty two tasks were found on content outlines of both job levels, representing a 76% overlap. Tasks found only on the CLS outline included advanced technical tasks, a few management tasks, and more communication tasks. The jobs of CLS and CLT practitioners are distinct at job entry level with CLSs performing a broader array of technical and communication tasks as well as some management tasks. Though CLS staff uses few management skills at job entry, those tasks are performed by CLS staff in the laboratory and curricula must help prepare graduates for these tasks expected of experienced staff. CLTs perform tasks requiring problem solving and high level reasoning. CLT curricula must address the need for CLTs to perform these tasks.

Clinical learning experiences of nursing students using an innovative clinical partnership model: A non-randomized controlled trial.

PubMed

Chan, Aileen W K; Tang, Fiona W K; Choi, Kai Chow; Liu, Ting; Taylor-Piliae, Ruth E

2018-06-05

Clinical practicum is a major learning component for pre-registration nursing students. Various clinical practicum models have been used to facilitate students' clinical learning experiences, employing both university-based and hospital-based clinical teachers. Considering the strengths and limitations of these clinical practicum models, along with nursing workforce shortages, we developed and tested an innovative clinical partnership model (CPM) in Hong Kong. To evaluate an innovative CPM among nursing students actual and preferred clinical learning environment, compared with a conventional facilitation model (CFM). A non-randomized controlled trial examining students' clinical experiences, comparing the CPM (supervised by hospital clinical teacher) with the CFM (supervised by university clinical teacher). One university in Hong Kong. Pre-registration nursing students (N = 331), including bachelor of nursing (n = 246 year three-BN) and masters-entry nursing (n = 85 year one-MNSP). Students were assigned to either the CPM (n = 48 BN plus n = 85 MNSP students) or the CFM (n = 198 BN students) for their clinical practice experiences in an acute medical-surgical ward. Clinical teachers supervised between 6 and 8 students at a time, during these clinical practicums (duration = 4-6 weeks). At the end of the clinical practicum, students were invited to complete the Clinical Learning Environment Inventory (CLEI). Analysis of covariance was used to compare groups; adjusted for age, gender and prior work experience. A total of 259 students (mean age = 22 years, 76% female, 81% prior work experience) completed the CLEI (78% response rate). Students had higher scores on preferred versus actual experiences, in all domains of the CLEI. CPM student experiences indicated a higher preferred task orientation (p = 0.004), while CFM student experiences indicated a higher actual (p < 0.001) and preferred individualization (p = 0.005). No significant differences were noted in the other domains. The CPM draws on the strengths of existing clinical learning models and provides complementary methods to facilitate clinical learning for pre-registration nursing students. Additional studies examining this CPM with longer duration of clinical practicum are recommended. Copyright © 2018 Elsevier Ltd. All rights reserved.

Lessons from a pilot project in cognitive task analysis: the potential role of intermediates in preclinical teaching in dental education.

PubMed

Walker, Judith; von Bergmann, HsingChi

2015-03-01

The purpose of this study was to explore the use of cognitive task analysis to inform the teaching of psychomotor skills and cognitive strategies in clinical tasks in dental education. Methods used were observing and videotaping an expert at one dental school thinking aloud while performing a specific preclinical task (in a simulated environment), interviewing the expert to probe deeper into his thinking processes, and applying the same procedures to analyze the performance of three second-year dental students who had recently learned the analyzed task and who represented a spectrum of their cohort's ability to undertake the procedure. The investigators sought to understand how experts (clinical educators) and intermediates (trained students) overlapped and differed at points in the procedure that represented the highest cognitive load, known as "critical incidents." Findings from this study and previous research identified possible limitations of current clinical teaching as a result of expert blind spots. These findings coupled with the growing evidence of the effectiveness of peer teaching suggest the potential role of intermediates in helping novices learn preclinical dentistry tasks.

Using task analysis in healthcare design to improve clinical efficiency.

PubMed

Lu, Jun; Hignett, Sue

2009-01-01

To review the functionality of the proposed soiled workroom design for efficient and safe clinical activities. As part of a hospital refurbishment program, the planning team of a United Kingdom National Health Service hospital requested a review of a proposed standardized room design. A 7-day observational study was conducted in five clinical departments at three hospitals. Link analysis was used to record and analyze the movements among components, i.e., nursing staff, equipment/devices, and furniture. Fifty-four observations were recorded for 18 clinical tasks. The most frequent tasks were the disposal of urine and used urine bottles, and returning used commode chairs. Minor recommendations were made to improve the proposed design, and major revisions were suggested to address functionality problems. It was found that the proposed design did not offer the optimal layout for efficient and safe clinical activities. Link analysis was found to be effective for plotting the movements of the staff and accounting for the complexity of tasks. This ergonomic method, in combination with observational field studies, provided a simple and effective way to determine functional space requirements for clinical activities and should be used in all healthcare building design projects.

A systematic review of interventions conducted in clinical or community settings to improve dual-task postural control in older adults.

PubMed

Agmon, Maayan; Belza, Basia; Nguyen, Huong Q; Logsdon, Rebecca G; Kelly, Valerie E

2014-01-01

Injury due to falls is a major problem among older adults. Decrements in dual-task postural control performance (simultaneously performing two tasks, at least one of which requires postural control) have been associated with an increased risk of falling. Evidence-based interventions that can be used in clinical or community settings to improve dual-task postural control may help to reduce this risk. THE AIMS OF THIS SYSTEMATIC REVIEW ARE: 1) to identify clinical or community-based interventions that improved dual-task postural control among older adults; and 2) to identify the key elements of those interventions. Studies were obtained from a search conducted through October 2013 of the following electronic databases: PubMed, CINAHL, PsycINFO, and Web of Science. Randomized and nonrandomized controlled studies examining the effects of interventions aimed at improving dual-task postural control among community-dwelling older adults were selected. All studies were evaluated based on methodological quality. Intervention characteristics including study purpose, study design, and sample size were identified, and effects of dual-task interventions on various postural control and cognitive outcomes were noted. Twenty-two studies fulfilled the selection criteria and were summarized in this review to identify characteristics of successful interventions. The ability to synthesize data was limited by the heterogeneity in participant characteristics, study designs, and outcome measures. Dual-task postural control can be modified by specific training. There was little evidence that single-task training transferred to dual-task postural control performance. Further investigation of dual-task training using standardized outcome measurements is needed.

Social Cognition Psychometric Evaluation: Results of the Initial Psychometric Study

PubMed Central

Pinkham, Amy E.; Penn, David L.; Green, Michael F.; Harvey, Philip D.

2016-01-01

Measurement of social cognition in treatment trials remains problematic due to poor and limited psychometric data for many tasks. As part of the Social Cognition Psychometric Evaluation (SCOPE) study, the psychometric properties of 8 tasks were assessed. One hundred and seventy-nine stable outpatients with schizophrenia and 104 healthy controls completed the battery at baseline and a 2–4-week retest period at 2 sites. Tasks included the Ambiguous Intentions Hostility Questionnaire (AIHQ), Bell Lysaker Emotion Recognition Task (BLERT), Penn Emotion Recognition Task (ER-40), Relationships Across Domains (RAD), Reading the Mind in the Eyes Task (Eyes), The Awareness of Social Inferences Test (TASIT), Hinting Task, and Trustworthiness Task. Tasks were evaluated on: (i) test-retest reliability, (ii) utility as a repeated measure, (iii) relationship to functional outcome, (iv) practicality and tolerability, (v) sensitivity to group differences, and (vi) internal consistency. The BLERT and Hinting task showed the strongest psychometric properties across all evaluation criteria and are recommended for use in clinical trials. The ER-40, Eyes Task, and TASIT showed somewhat weaker psychometric properties and require further study. The AIHQ, RAD, and Trustworthiness Task showed poorer psychometric properties that suggest caution for their use in clinical trials. PMID:25943125

The relationship between maternal self-efficacy and parenting practices: implications for parent training.

PubMed

Sanders, M R; Woolley, M L

2005-01-01

The present study examined the relationship between maternal self-efficacy, dysfunctional discipline practices and child conduct problems. Specifically, three levels of self-efficacy, global, domain and task-specific self-efficacy, were assessed in mothers of 2- to 8-year-old children with conduct problems (clinic group, n=45) and non-clinic mothers from the community (non-clinic group, n=79). Measures of global, domain and task-specific self-efficacy were completed by mothers. Clinic mothers reported significantly lower self-efficacy than non-clinic mothers for all but one of the parenting tasks assessed. Both groups of mothers reported lowest self-efficacy for similar parenting tasks. In the sample as a whole self-efficacy measures were significant predictors of maternal discipline style after controlling for other parent, child and risk factors. Of the self-efficacy variables behavioural self-efficacy was the best predictor of mothers discipline style. The findings support the importance of developing parenting strategies that enable parents to generalize their parenting skills to a diverse range of diverse parenting contexts both in the home and in the community.

[Emotional regulation and motivation in children with ADHD].

PubMed

Høvik, Marie Farstad; Plessen, Kerstin J

2010-12-02

Impaired cognitive control functions have long been regarded as the main problem in the development of Attention-Deficit/Hyperactivity Disorder (ADHD). A more recent model emphasizes the importance of emotional and motivational problems. We have reviewed the evidence for this model, which may have important implications for clinical practice. The article is based on literature identified through a non-systematic search in PubMed. Although limited research was carried out in this topic earlier, studies are currently emerging. Persons with ADHD react differently than controls on tasks that include rewards and on tasks that stress their capacity to regulate emotions. Abnormal signals during examination with electroencephalography (EEG) and anatomical and functional magnetic resonance imaging (fMRI) reflect problems with emotional regulation in patients with ADHD. Neurobiological research supports a model that includes emotional and motivational problems in the development of ADHD. Increased knowledge about emotional and motivational problems may improve treatment of these patients through development of more individually adapted therapy.

Handpiece and bur skills evaluation during an introductory Clinical Skills Programme in a graduate-entry dental school: a pilot study.

PubMed

Foley, J I; Drummie, J

2012-06-01

To assess the effect of an introductory Clinical Skills Program on the development of two tasks aimed at teaching a Class II cavity preparation technique. A prospective, observational study. Twenty three first year students (F: 19; M: 4) were asked to complete two cavities on a Frasaco(®) tooth 46 using a FG 565 pear-shaped diamond bur. Task One: A groove was cut from the central fissure area to within 1mm of the marginal ridge which was 5mm in length, 2mm in width and 2mm in depth. Task Two: As for Task One and in addition, a slot was cut vertically downward at the marginal ridge to create a box 2mm in length, 2mm in width and 3mm in depth. Both tasks were undertaken at the start of an introductory Clinical Skills course and two months later after further skills practice. Cavity dimensions were measured using a digital caliper with a depth gauge. Data were analysed using a two-sample t-test (MINITAB(®) 15.1). Regarding Task One, a statistically-significant improvement in groove width was noted (p=0.001). Concerning Task Two, both the groove width and the box width improved and both were statistically significant p=0.023 and p=0.049, respectively). A Clinical Skills Program would appear to result in an improvement in cavity preparation, particularly in relation to cavity width.

An Infinite Mixture Model for Coreference Resolution in Clinical Notes

PubMed Central

Liu, Sijia; Liu, Hongfang; Chaudhary, Vipin; Li, Dingcheng

2016-01-01

It is widely acknowledged that natural language processing is indispensable to process electronic health records (EHRs). However, poor performance in relation detection tasks, such as coreference (linguistic expressions pertaining to the same entity/event) may affect the quality of EHR processing. Hence, there is a critical need to advance the research for relation detection from EHRs. Most of the clinical coreference resolution systems are based on either supervised machine learning or rule-based methods. The need for manually annotated corpus hampers the use of such system in large scale. In this paper, we present an infinite mixture model method using definite sampling to resolve coreferent relations among mentions in clinical notes. A similarity measure function is proposed to determine the coreferent relations. Our system achieved a 0.847 F-measure for i2b2 2011 coreference corpus. This promising results and the unsupervised nature make it possible to apply the system in big-data clinical setting. PMID:27595047

The assessment and treatment of prosodic disorders and neurological theories of prosody.

PubMed

Diehl, Joshua J; Paul, Rhea

2009-08-01

In this article, we comment on specific aspects of Peppé (Peppé, 2009). In particular, we address the assessment and treatment of prosody in clinical settings and discuss current theory on neurological models of prosody. We argue that in order for prosodic assessment instruments and treatment programs to be clinical effective, we need assessment instruments that: (1) have a representative normative comparison sample and strong psychometric properties; (2) are based on empirical information regarding the typical sequence of prosodic acquisition and are sensitive to developmental change; (3) meaningfully subcategorize various aspects of prosody; (4) use tasks that have ecological validity; and (5) have clinical properties, such as length and ease of administration, that allow them to become part of standard language assessment batteries. In addition, we argue that current theories of prosody processing in the brain are moving toward network models that involve multiple brain areas and are crucially dependent on cortical communication. The implications of these observations for future research and clinical practice are outlined.

Affective Biases in Humans and Animals.

PubMed

Robinson, E S J; Roiser, J P

Depression is one of the most common but poorly understood psychiatric conditions. Although drug treatments and psychological therapies are effective in some patients, many do not achieve full remission and some patients receive no apparent benefit. Developing new improved treatments requires a better understanding of the aetiology of symptoms and evaluation of novel therapeutic targets in pre-clinical studies. Recent developments in our understanding of the basic cognitive processes that may contribute to the development of depression and its treatment offer new opportunities for both clinical and pre-clinical research. This chapter discusses the clinical evidence supporting a cognitive neuropsychological model of depression and antidepressant efficacy, and how this information may be usefully translated to pre-clinical investigation. Studies using neuropsychological tests in depressed patients and at risk populations have revealed basic negative emotional biases and disrupted reward and punishment processing, which may also impact on non-affective cognition. These affective biases are sensitive to antidepressant treatments with early onset effects observed, suggesting an important role in recovery. This clinical work into affective biases has also facilitated back-translation to animals and the development of assays to study affective biases in rodents. These animal studies suggest that, similar to humans, rodents in putative negative affective states exhibit negative affective biases on decision-making and memory tasks. Antidepressant treatments also induce positive biases in these rodent tasks, supporting the translational validity of this approach. Although still in the early stages of development and validation, affective biases in depression have the potential to offer new insights into the clinical condition, as well as facilitating the development of more translational approaches for pre-clinical studies.

Association of Dual-Task Gait With Incident Dementia in Mild Cognitive Impairment: Results From the Gait and Brain Study.

PubMed

Montero-Odasso, Manuel M; Sarquis-Adamson, Yanina; Speechley, Mark; Borrie, Michael J; Hachinski, Vladimir C; Wells, Jennie; Riccio, Patricia M; Schapira, Marcelo; Sejdic, Ervin; Camicioli, Richard M; Bartha, Robert; McIlroy, William E; Muir-Hunter, Susan

2017-07-01

Gait performance is affected by neurodegeneration in aging and has the potential to be used as a clinical marker for progression from mild cognitive impairment (MCI) to dementia. A dual-task gait test evaluating the cognitive-motor interface may predict dementia progression in older adults with MCI. To determine whether a dual-task gait test is associated with incident dementia in MCI. The Gait and Brain Study is an ongoing prospective cohort study of community-dwelling older adults that enrolled 112 older adults with MCI. Participants were followed up for 6 years, with biannual visits including neurologic, cognitive, and gait assessments. Data were collected from July 2007 to March 2016. Incident all-cause dementia was the main outcome measure, and single- and dual-task gait velocity and dual-task gait costs were the independent variables. A neuropsychological test battery was used to assess cognition. Gait velocity was recorded under single-task and 3 separate dual-task conditions using an electronic walkway. Dual-task gait cost was defined as the percentage change between single- and dual-task gait velocities: ([single-task gait velocity - dual-task gait velocity]/ single-task gait velocity) × 100. Cox proportional hazard models were used to estimate the association between risk of progression to dementia and the independent variables, adjusted for age, sex, education, comorbidities, and cognition. Among 112 study participants with MCI, mean (SD) age was 76.6 (6.9) years, 55 were women (49.1%), and 27 progressed to dementia (24.1%), with an incidence rate of 121 per 1000 person-years. Slow single-task gait velocity (<0.8 m/second) was not associated with progression to dementia (hazard ratio [HR], 3.41; 95% CI, 0.99-11.71; P = .05)while high dual-task gait cost while counting backward (HR, 3.79; 95% CI, 1.57-9.15; P = .003) and naming animals (HR, 2.41; 95% CI, 1.04-5.59; P = .04) were associated with dementia progression (incidence rate, 155 per 1000 person-years). The models remained robust after adjusting by baseline cognition except for dual-task gait cost when dichotomized. Dual-task gait is associated with progression to dementia in patients with MCI. Dual-task gait testing is easy to administer and may be used by clinicians to decide further biomarker testing, preventive strategies, and follow-up planning in patients with MCI. clinicaltrials.gov: NCT03020381.

Validating archetypes for the Multiple Sclerosis Functional Composite.

PubMed

Braun, Michael; Brandt, Alexander Ulrich; Schulz, Stefan; Boeker, Martin

2014-08-03

Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time-consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions.This case study provides evidence that both community- and tool-enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model.

Validating archetypes for the Multiple Sclerosis Functional Composite

PubMed Central

2014-01-01

Background Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. Methods A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Results Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time-consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. Conclusions The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions. This case study provides evidence that both community- and tool-enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model. PMID:25087081

Structured cues or modafinil for fatigue amelioration in clinicians? A double-blind, randomized controlled trial of critical clinical information recall in fatigued clinicians.

PubMed

Flindall, Ian; Leff, Daniel Richard; Goodship, Jonathan; Sugden, Colin; Darzi, Ara

2016-04-01

To evaluate the impact of modafinil on "free" and "cued" recall of clinical information in fatigued but nonsleep-deprived clinicians. Despite attempts to minimize sleep deprivation through redesign of the roster of residents and staff surgeons, evidence suggests that fatigue remains prevalent. The wake-promoting agent modafinil improves cognition in the sleep-deprived fatigued state and may improve information recall in fatigued nonsleep-deprived clinicians. Twenty-four medical undergraduates participated in a double-blind, parallel, randomized controlled trial (modafinil-200 mg:placebo). Medication was allocated 2 hours before a 90-minute fatigue-inducing, continuous performance task (dual 2-back task). A case history memorization task was then performed. Clinical information recall was assessed as "free"(no cognitive aids) and "cued"(using aid memoirs). Open and closed cues represent information of increasing specificity to aid the recall of clinical information. Fatigue was measured objectively using the psychomotor vigilance task at induction, before and after the dual 2-back task. Modafinil decreased false starts and lapses (modafinil = 0.50, placebo = 9.83, P < .05) and improved psychomotor vigilance task performance (Decreased Performance, modafinil = 0.006, placebo = 0.098, P < .05). Modafinil improved free information recall (modafinil = 137.8, placebo = 106.0, P < .01). There was no significant difference between groups in the amount of information recalled with open (modafinil = 62.3, placebo = 52.8, P = .1) and closed cues (modafinil = 80.1, placebo = 75.9, P = .3). Modafinil attenuated fatigue and improved free recall of clinical information without improving cue-based recall under the design of our experimental conditions. Memory cues to aid retrieval of clinical information are convenient interventions that could decrease fatigue-related error without adverse effects of the neuropharmacology. Copyright © 2016 Elsevier Inc. All rights reserved.

Applicability Evaluation of Job Standards for Diabetes Nutritional Management by Clinical Dietitian.

PubMed

Baek, Young Jin; Oh, Na Gyeong; Sohn, Cheong-Min; Woo, Mi-Hye; Lee, Seung Min; Ju, Dal Lae; Seo, Jung-Sook

2017-04-01

This study was conducted to evaluate applicability of job standards for diabetes nutrition management by hospital clinical dietitians. In order to promote the clinical nutrition services, it is necessary to present job standards of clinical dietitian and to actively apply these standardized tasks to the medical institution sites. The job standard of clinical dietitians for diabetic nutrition management was distributed to hospitals over 300 beds. Questionnaire was collected from 96 clinical dietitians of 40 tertiary hospitals, 47 general hospitals, and 9 hospitals. Based on each 5-point scale, the importance of overall duty was 4.4 ± 0.5, performance was 3.6 ± 0.8, and difficulty was 3.1 ± 0.7. 'Nutrition intervention' was 4.5 ± 0.5 for task importance, 'nutrition assessment' was 4.0 ± 0.7 for performance, and 'nutrition diagnosis' was 3.4 ± 0.9 for difficulty. These 3 items were high in each category. Based on the grid diagram, the tasks of both high importance and high performance were 'checking basic information,' 'checking medical history and therapy plan,' 'decision of nutritional needs,' 'supply of foods and nutrients,' and 'education of nutrition and self-management.' The tasks with high importance but low performance were 'derivation of nutrition diagnosis,' 'planning of nutrition intervention,' 'monitoring of nutrition intervention process.' The tasks of both high importance and high difficulty were 'derivation of nutrition diagnosis,' 'planning of nutrition intervention,' 'supply of foods and nutrients,' 'education of nutrition and self-management,' and 'monitoring of nutrition intervention process.' The tasks of both high performance and high difficulty were 'documentation of nutrition assessment,' 'supply of foods and nutrients,' and 'education of nutrition and self-management.'

NK1 receptor antagonism and emotional processing in healthy volunteers.

PubMed

Chandra, P; Hafizi, S; Massey-Chase, R M; Goodwin, G M; Cowen, P J; Harmer, C J

2010-04-01

The neurokinin-1 (NK(1)) receptor antagonist, aprepitant, showed activity in several animal models of depression; however, its efficacy in clinical trials was disappointing. There is little knowledge of the role of NK(1) receptors in human emotional behaviour to help explain this discrepancy. The aim of the current study was to assess the effects of a single oral dose of aprepitant (125 mg) on models of emotional processing sensitive to conventional antidepressant drug administration in 38 healthy volunteers, randomly allocated to receive aprepitant or placebo in a between groups double blind design. Performance on measures of facial expression recognition, emotional categorisation, memory and attentional visual-probe were assessed following the drug absorption. Relative to placebo, aprepitant improved recognition of happy facial expressions and increased vigilance to emotional information in the unmasked condition of the visual probe task. In contrast, aprepitant impaired emotional memory and slowed responses in the facial expression recognition task suggesting possible deleterious effects on cognition. These results suggest that while antagonism of NK(1) receptors does affect emotional processing in humans, its effects are more restricted and less consistent across tasks than those of conventional antidepressants. Human models of emotional processing may provide a useful means of assessing the likely therapeutic potential of new treatments for depression.

WITH: a system to write clinical trials using XML and RDBMS.

PubMed Central

Fazi, Paola; Luzi, Daniela; Manco, Mariarosaria; Ricci, Fabrizio L.; Toffoli, Giovanni; Vignetti, Marco

2002-01-01

The paper illustrates the system WITH (Write on Internet clinical Trials in Haematology) which supports the writing of a clinical trial (CT) document. The requirements of this system have been defined analysing the writing process of a CT and then modelling the content of its sections together with their logical and temporal relationships. The system WITH allows: a) editing the document text; b) re-using the text; and c) facilitating the cooperation and the collaborative writing. It is based on XML mark-up language, and on a RDBMS. This choice guarantees: a) process standardisation; b) process management; c) efficient delivery of information-based tasks; and d) explicit focus on process design. PMID:12463823

FRAX(®) Clinical Task Force of the 2010 Joint International Society for Clinical Densitometry & International Osteoporosis Foundation Position Development Conference.

PubMed

McCloskey, Eugene V; Binkley, Neil

2011-01-01

The World Health Organization fracture risk assessment tool, FRAX(®), is an advance in clinical care that can assist in clinical decision-making. However, with increasing clinical utilization, numerous questions have arisen regarding how to best estimate fracture risk in an individual patient. Recognizing the need to assist clinicians in optimal use of FRAX(®), the International Osteoporosis Foundation (IOF) in conjunction with the International Society for Clinical Densitometry (ISCD) assembled an international panel of experts that ultimately developed joint Official Positions of the ISCD and IOF advising clinicians regarding FRAX(®) usage. As part of the process, the charge of the FRAX(®) Clinical Task Force was to review and synthesize data surrounding a number of recognized clinical risk factors including rheumatoid arthritis, smoking, alcohol, prior fracture, falls, bone turnover markers and glucocorticoid use. This synthesis was presented to the expert panel and constitutes the data on which the subsequent Official Positions are predicated. A summary of the Clinical Task Force composition and charge is presented here. Copyright © 2011. Published by Elsevier Inc.

Building a Framework for a Dual Task Taxonomy

PubMed Central

McIsaac, Tara L.; Lamberg, Eric M.; Muratori, Lisa M.

2015-01-01

The study of dual task interference has gained increasing attention in the literature for the past 35 years, with six MEDLINE citations in 1979 growing to 351 citations indexed in 2014 and a peak of 454 cited papers in 2013. Increasingly, researchers are examining dual task cost in individuals with pathology, including those with neurodegenerative diseases. While the influence of these papers has extended from the laboratory to the clinic, the field has evolved without clear definitions of commonly used terms and with extreme variations in experimental procedures. As a result, it is difficult to examine the interference literature as a single body of work. In this paper we present a new taxonomy for classifying cognitive-motor and motor-motor interference within the study of dual task behaviors that connects traditional concepts of learning and principles of motor control with current issues of multitasking analysis. As a first step in the process we provide an operational definition of dual task, distinguishing it from a complex single task. We present this new taxonomy, inclusive of both cognitive and motor modalities, as a working model; one that we hope will generate discussion and create a framework from which one can view previous studies and develop questions of interest. PMID:25961027

The Effect of Prior Concussion History on Dual-Task Gait following a Concussion.

PubMed

Howell, David R; Beasley, Michael; Vopat, Lisa; Meehan, William P

2017-02-15

Sustaining repeated concussions has been associated with worse outcomes after additional injuries. This effect has been identified using symptom inventories and neurocognitive tests; however, few investigations have examined how a prior concussion history affects gait soon after a subsequent concussion. We examined the gait characteristics of athletes with no documented concussion history (n = 31), athletes recovering from their first lifetime concussion (n = 15), and athletes recovering from their second or greater lifetime concussion (n = 22). All participants completed a single-task and dual-task gait examination, a medical history questionnaire, and a postconcussion symptom scale. Multivariate analyses of covariance (MANCOVA) models were used to evaluate mean gait differences among groups, and Spearman's ρ analyses were used to assess correlations between the number of lifetime concussions and gait characteristics. Patients reporting to the clinic with their second or greater lifetime concussion demonstrated smaller stride lengths than healthy control participants during dual-task walking (p = 0.01; d = 0.70). A moderate but insignificant correlation was detected between dual-task gait speed and the number of prior concussions (ρ = 0.41, p = 0.07). These results indicate that a cumulative effect of concussions across the lifetime may contribute to worsening dual-task dynamic motor function after concussion.

A functional neuroimaging study of the clinical reasoning of medical students.

PubMed

Chang, Hyung-Joo; Kang, June; Ham, Byung-Joo; Lee, Young-Mee

2016-12-01

As clinical reasoning is a fundamental competence of physicians for good clinical practices, medical academics have endeavored to teach reasoning skills to undergraduate students. However, our current understanding of student-level clinical reasoning is limited, mainly because of the lack of evaluation tools for this internal cognitive process. This functional magnetic resonance imaging (fMRI) study aimed to examine the clinical reasoning processes of medical students in response to problem-solving questions. We recruited 24 2nd-year medical students who had completed their preclinical curriculum. They answered 40 clinical vignette-based multiple-choice questions during fMRI scanning. We compared the imaging data for 20 problem-solving questions (reasoning task) and 20 recall questions (recall task). Compared to the recall task, the reasoning task resulted in significantly greater activation in nine brain regions, including the dorsolateral prefrontal cortex and inferior parietal cortex, which are known to be associated with executive function and deductive reasoning. During the recall task, significant activation was observed in the brain regions that are related to memory and emotions, including the amygdala and ventromedial prefrontal cortex. Our results support that medical students mainly solve clinical questions with deductive reasoning involving prior knowledge structures and executive functions. The problem-solving questions induced the students to utilize higher cognitive functions compared with the recall questions. Interestingly, the results suggested that the students experienced some emotional distress while they were solving the recall questions. In addition, these results suggest that fMRI is a promising research tool for investigating students' cognitive processes.

Combining the ‘bottom up’ and ‘top down’ approaches in pharmacokinetic modelling: fitting PBPK models to observed clinical data

PubMed Central

Tsamandouras, Nikolaos; Rostami-Hodjegan, Amin; Aarons, Leon

2015-01-01

Pharmacokinetic models range from being entirely exploratory and empirical, to semi-mechanistic and ultimately complex physiologically based pharmacokinetic (PBPK) models. This choice is conditional on the modelling purpose as well as the amount and quality of the available data. The main advantage of PBPK models is that they can be used to extrapolate outside the studied population and experimental conditions. The trade-off for this advantage is a complex system of differential equations with a considerable number of model parameters. When these parameters cannot be informed from in vitro or in silico experiments they are usually optimized with respect to observed clinical data. Parameter estimation in complex models is a challenging task associated with many methodological issues which are discussed here with specific recommendations. Concepts such as structural and practical identifiability are described with regards to PBPK modelling and the value of experimental design and sensitivity analyses is sketched out. Parameter estimation approaches are discussed, while we also highlight the importance of not neglecting the covariance structure between model parameters and the uncertainty and population variability that is associated with them. Finally the possibility of using model order reduction techniques and minimal semi-mechanistic models that retain the physiological-mechanistic nature only in the parts of the model which are relevant to the desired modelling purpose is emphasized. Careful attention to all the above issues allows us to integrate successfully information from in vitro or in silico experiments together with information deriving from observed clinical data and develop mechanistically sound models with clinical relevance. PMID:24033787

Decision Making Impairment: A Shared Vulnerability in Obesity, Gambling Disorder and Substance Use Disorders?

PubMed Central

Mallorquí-Bagué, Nuria; Fagundo, Ana B.; Jimenez-Murcia, Susana; de la Torre, Rafael; Baños, Rosa M.; Botella, Cristina; Casanueva, Felipe F.; Crujeiras, Ana B.; Fernández-García, Jose C.; Fernández-Real, Jose M.; Frühbeck, Gema; Granero, Roser; Rodríguez, Amaia; Tolosa-Sola, Iris; Ortega, Francisco J.; Tinahones, Francisco J.; Alvarez-Moya, Eva; Ochoa, Cristian; Menchón, Jose M.

2016-01-01

Introduction Addictions are associated with decision making impairments. The present study explores decision making in Substance use disorder (SUD), Gambling disorder (GD) and Obesity (OB) when assessed by Iowa Gambling Task (IGT) and compares them with healthy controls (HC). Methods For the aims of this study, 591 participants (194 HC, 178 GD, 113 OB, 106 SUD) were assessed according to DSM criteria, completed a sociodemographic interview and conducted the IGT. Results SUD, GD and OB present impaired decision making when compared to the HC in the overall task and task learning, however no differences are found for the overall performance in the IGT among the clinical groups. Results also reveal some specific learning across the task patterns within the clinical groups: OB maintains negative scores until the third set where learning starts but with a less extend to HC, SUD presents an early learning followed by a progressive although slow improvement and GD presents more random choices with no learning. Conclusions Decision making impairments are present in the studied clinical samples and they display individual differences in the task learning. Results can help understanding the underlying mechanisms of OB and addiction behaviors as well as improve current clinical treatments. PMID:27690367

The effect of priming a thin ideal on the subsequent perception of conceptually related body image words.

PubMed

Markis, Teresa A; McLennan, Conor T

2011-09-01

Our research examined the effects of thin ideal priming on the perception of body image words in participants without an eating disorder. Half of the participants were primed by viewing thin models, and half were primed with gender-neutral shoes. Subsequently, all participants (N=56) completed a Stroop task for three categories of words: neutral (BOOKS), shoe (CLOGS), and body (THIGHS). Lastly, all participants completed a body dissatisfaction questionnaire. We predicted that body dissatisfaction scores would be correlated with the Stroop effect. We found a significant correlation between body dissatisfaction and the body effect of slower color naming times for the body related words compared to the neutral words. Our study demonstrates that body dissatisfaction and a brief priming with thin models results in subsequent differences in performing a Stroop task in a non clinical population of female participants. Copyright © 2011 Elsevier Ltd. All rights reserved.

How age affects memory task performance in clinically normal hearing persons.

PubMed

Vercammen, Charlotte; Goossens, Tine; Wouters, Jan; van Wieringen, Astrid

2017-05-01

The main objective of this study is to investigate memory task performance in different age groups, irrespective of hearing status. Data are collected on a short-term memory task (WAIS-III Digit Span forward) and two working memory tasks (WAIS-III Digit Span backward and the Reading Span Test). The tasks are administered to young (20-30 years, n = 56), middle-aged (50-60 years, n = 47), and older participants (70-80 years, n = 16) with normal hearing thresholds. All participants have passed a cognitive screening task (Montreal Cognitive Assessment (MoCA)). Young participants perform significantly better than middle-aged participants, while middle-aged and older participants perform similarly on the three memory tasks. Our data show that older clinically normal hearing persons perform equally well on the memory tasks as middle-aged persons. However, even under optimal conditions of preserved sensory processing, changes in memory performance occur. Based on our data, these changes set in before middle age.

Alliance ruptures and rupture resolution in cognitive-behavior therapy: a preliminary task analysis.

PubMed

Aspland, Helen; Llewelyn, Susan; Hardy, Gillian E; Barkham, Michael; Stiles, William

2008-11-01

An initial ideal, rational model of alliance rupture and rupture resolution provided by cognitive-behavioral therapy (CBT) experts was assessed and compared with empirical observations of ruptures and their resolution in two cases of successful CBT. The initial rational model emphasized nondefensive acknowledgment and exploration of the rupture. Results indicated differences between what therapists think they should do to resolve ruptures and what they actually do and suggested that the rational model should be expanded to emphasize client validation and empowerment. Therapists' ability to attend to ruptures emerged as an important clinical skill.

On the ontological assumptions of the medical model of psychiatry: philosophical considerations and pragmatic tasks

PubMed Central

2010-01-01

A common theme in the contemporary medical model of psychiatry is that pathophysiological processes are centrally involved in the explanation, evaluation, and treatment of mental illnesses. Implied in this perspective is that clinical descriptors of these pathophysiological processes are sufficient to distinguish underlying etiologies. Psychiatric classification requires differentiation between what counts as normality (i.e.- order), and what counts as abnormality (i.e.- disorder). The distinction(s) between normality and pathology entail assumptions that are often deeply presupposed, manifesting themselves in statements about what mental disorders are. In this paper, we explicate that realism, naturalism, reductionism, and essentialism are core ontological assumptions of the medical model of psychiatry. We argue that while naturalism, realism, and reductionism can be reconciled with advances in contemporary neuroscience, essentialism - as defined to date - may be conceptually problematic, and we pose an eidetic construct of bio-psychosocial order and disorder based upon complex systems' dynamics. However we also caution against the overuse of any theory, and claim that practical distinctions are important to the establishment of clinical thresholds. We opine that as we move ahead toward both a new edition of the Diagnostic and Statistical Manual, and a proposed Decade of the Mind, the task at hand is to re-visit nosologic and ontologic assumptions pursuant to a re-formulation of diagnostic criteria and practice. PMID:20109176

Bimanual Force Coordination in Parkinson’s Disease Patients with Bilateral Subthalamic Deep Brain Stimulation

PubMed Central

Gorniak, Stacey L.; McIntyre, Cameron C.; Alberts, Jay L.

2013-01-01

Objective Studies of bimanual actions similar to activities of daily living (ADLs) are currently lacking in evaluating fine motor control in Parkinson’s disease patients implanted with bilateral subthalamic deep brain stimulators. We investigated basic time and force characteristics of a bimanual task that resembles performance of ADLs in a group of bilateral subthalamic deep brain stimulation (DBS) patients. Methods Patients were evaluated in three different DBS parameter conditions off stimulation, on clinically derived stimulation parameters, and on settings derived from a patient-specific computational model. Model-based parameters were computed as a means to minimize spread of current to non-motor regions of the subthalamic nucleus via Cicerone Deep Brain Stimulation software. Patients were evaluated off parkinsonian medications in each stimulation condition. Results The data indicate that DBS parameter state does not affect most aspects of fine motor control in ADL-like tasks; however, features such as increased grip force and grip symmetry varied with the stimulation state. In the absence of DBS parameters, patients exhibited significant grip force asymmetry. Overall UPDRS-III and UPDRS-III scores associated with hand function were lower while patients were experiencing clinically-derived or model-based parameters, as compared to the off-stimulation condition. Conclusion While bilateral subthalamic DBS has been shown to alleviate gross motor dysfunction, our results indicate that DBS may not provide the same magnitude of benefit to fine motor coordination. PMID:24244388

How Do Clinical Information Systems Affect the Cognitive Demands of General Practitioners?: Usability Study with a Focus on Cognitive Workload.

PubMed

Ariza, Ferran; Kalra, Dipak; Potts, Henry Ww

2015-11-20

Clinical information systems in the National Health Service do not need to conform to any explicit usability requirements. Poor usability can increase the mental workload experienced by clinicians and cause fatigue, increase error rates and impact the overall patient safety. Mental workload can be used as a measure of usability. To assess the subjective cognitive workload experienced by general practitioners (GPs) with their systems. To raise awareness of the importance of usability in system design among users, designers, developers and policymakers. We used a modified version of the NASA Task Load Index, adapted for web. We developed a set of common clinical scenarios and computer tasks on an online survey. We emailed the study link to 199 clinical commissioning groups and 1,646 GP practices in England. Sixty-seven responders completed the survey. The respondents had spent an average of 17 years in general practice, had experience of using a mean of 1.5 GP computer systems and had used their current system for a mean time of 6.7 years. The mental workload score was not different among systems. There were significant differences among the task scores, but these differences were not specific to particular systems. The overall score and task scores were related to the length of experience with their present system. Four tasks imposed a higher mental workload on GPs: 'repeat prescribing', 'find episode', 'drug management' and 'overview records'. Further usability studies on GP systems should focus on these tasks. Users, policymakers, designers and developers should remain aware of the importance of usability in system design.What does this study add?• Current GP systems in England do not need to conform to explicit usability requirements. Poor usability can increase the mental workload of clinicians and lead to errors.• Some clinical computer tasks incur more cognitive workload than others and should be considered carefully during the design of a system.• GPs did not report overall very high levels of subjective cognitive workload when undertaking common clinical tasks with their systems.• Further usability studies on GP systems should focus on the tasks incurring higher cognitive workload.• Users, policymakers, and designers and developers should remain aware of the importance of usability in system design.

Combined Socio-Behavioral Evaluation Improves the Differential Diagnosis Between the Behavioral Variant of Frontotemporal Dementia and Alzheimer's Disease: In Search of Neuropsychological Markers.

PubMed

Dodich, Alessandra; Cerami, Chiara; Cappa, Stefano F; Marcone, Alessandra; Golzi, Valeria; Zamboni, Michele; Giusti, Maria Cristina; Iannaccone, Sandro

2018-01-01

Current diagnostic criteria for behavioral variant of frontotemporal dementia (bvFTD) and typical Alzheimer's disease (AD) include a differential pattern of neuropsychological impairments (episodic memory deficit in typical AD and dysexecutive syndrome in bvFTD). There is, however, large evidence of a frequent overlap in neuropsychological features, making the differential diagnosis extremely difficult. In this retrospective study, we evaluated the diagnostic value of different cognitive and neurobehavioral markers in bvFTD and AD patient groups. We included 95 dementia patients with a clinical and biomarker evidence of bvFTD (n = 48) or typical AD (n = 47) pathology. A clinical 2-year follow-up confirmed clinical classification. Performances at basic cognitive tasks (memory, executive functions, visuo-spatial, language) as well as social cognition skills and neurobehavioral profiles have been recorded. A stepwise logistic regression model compared the neuropsychological profiles between groups and assessed the accuracy of cognitive and neurobehavioral markers in discriminating bvFTD from AD. Statistical comparison between patient groups proved social cognition and episodic memory impairments as main cognitive signatures of bvFTD and AD neuropsychological profiles, respectively. Only half of bvFTD patients showed attentive/executive deficits, questioning their role as cognitive marker of bvFTD. Notably, the large majority of bvFTD sample (i.e., 70%) poorly performed at delayed recall tasks. Logistic regression analysis identified social cognition performances, Frontal Behavioral Inventory and Mini-Mental State Examination scores as the best combination in distinguishing bvFTD from AD. Social cognition tasks and socio-behavioral questionnaires are recommended in clinical settings to improve the accuracy of early diagnosis of bvFTD.

The use and QA of biologically related models for treatment planning: short report of the TG-166 of the therapy physics committee of the AAPM.

PubMed

Allen Li, X; Alber, Markus; Deasy, Joseph O; Jackson, Andrew; Ken Jee, Kyung-Wook; Marks, Lawrence B; Martel, Mary K; Mayo, Charles; Moiseenko, Vitali; Nahum, Alan E; Niemierko, Andrzej; Semenenko, Vladimir A; Yorke, Ellen D

2012-03-01

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

Methodological factors affecting joint moments estimation in clinical gait analysis: a systematic review.

PubMed

Camomilla, Valentina; Cereatti, Andrea; Cutti, Andrea Giovanni; Fantozzi, Silvia; Stagni, Rita; Vannozzi, Giuseppe

2017-08-18

Quantitative gait analysis can provide a description of joint kinematics and dynamics, and it is recognized as a clinically useful tool for functional assessment, diagnosis and intervention planning. Clinically interpretable parameters are estimated from quantitative measures (i.e. ground reaction forces, skin marker trajectories, etc.) through biomechanical modelling. In particular, the estimation of joint moments during motion is grounded on several modelling assumptions: (1) body segmental and joint kinematics is derived from the trajectories of markers and by modelling the human body as a kinematic chain; (2) joint resultant (net) loads are, usually, derived from force plate measurements through a model of segmental dynamics. Therefore, both measurement errors and modelling assumptions can affect the results, to an extent that also depends on the characteristics of the motor task analysed (i.e. gait speed). Errors affecting the trajectories of joint centres, the orientation of joint functional axes, the joint angular velocities, the accuracy of inertial parameters and force measurements (concurring to the definition of the dynamic model), can weigh differently in the estimation of clinically interpretable joint moments. Numerous studies addressed all these methodological aspects separately, but a critical analysis of how these aspects may affect the clinical interpretation of joint dynamics is still missing. This article aims at filling this gap through a systematic review of the literature, conducted on Web of Science, Scopus and PubMed. The final objective is hence to provide clear take-home messages to guide laboratories in the estimation of joint moments for the clinical practice.

Collaborative learning using nursing student dyads in the clinical setting.

PubMed

Austria, Mary Jean; Baraki, Katie; Doig, Alexa K

2013-05-04

Formal pairing of student nurses to work collaboratively on one patient assignment is a strategy for improving the quality and efficiency of clinical instruction while better utilizing the limited resources at clinical agencies. The aim of this qualitative study was to explore the student nurse and patient experiences of collaborative learning when peer dyads are used in clinical nursing education. Interviews were conducted with 11 students and 9 patients. Students described the process of collaborative learning as information sharing, cross-checking when making clinical decisions, and group processing when assessing the outcomes of nursing interventions. Positive outcomes reported by students and patients included reduced student anxiety, increased confidence and task efficiency. Students' primary concern was reduced opportunity to perform hands-on skills which had to be negotiated within each dyad. Meeting the present and future challenges of educating nurses will require innovative models of clinical instruction such as collaborative learning using student peer dyads.

Research Challenges and Opportunities for Clinically Oriented Academic Radiology Departments.

PubMed

Decker, Summer J; Grajo, Joseph R; Hazelton, Todd R; Hoang, Kimberly N; McDonald, Jennifer S; Otero, Hansel J; Patel, Midhir J; Prober, Allen S; Retrouvey, Michele; Rosenkrantz, Andrew B; Roth, Christopher G; Ward, Robert J

2016-01-01

Between 2004 and 2012, US funding for the biomedical sciences decreased to historic lows. Health-related research was crippled by receiving only 1/20th of overall federal scientific funding. Despite the current funding climate, there is increased pressure on academic radiology programs to establish productive research programs. Whereas larger programs have resources that can be utilized at their institutions, small to medium-sized programs often struggle with lack of infrastructure and support. To address these concerns, the Association of University Radiologists' Radiology Research Alliance developed a task force to explore any untapped research productivity potential in these smaller radiology departments. We conducted an online survey of faculty at smaller clinically funded programs and found that while they were interested in doing research and felt it was important to the success of the field, barriers such as lack of resources and time were proving difficult to overcome. One potential solution proposed by this task force is a collaborative structured research model in which multiple participants from multiple institutions come together in well-defined roles that allow for an equitable distribution of research tasks and pooling of resources and expertise. Under this model, smaller programs will have an opportunity to share their unique perspective on how to address research topics and make a measureable impact on the field of radiology as a whole. Through a health services focus, projects are more likely to succeed in the context of limited funding and infrastructure while simultaneously providing value to the field. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Task-oriented evaluation of electronic medical records systems: development and validation of a questionnaire for physicians

PubMed Central

2004-01-01

Background Evaluation is a challenging but necessary part of the development cycle of clinical information systems like the electronic medical records (EMR) system. It is believed that such evaluations should include multiple perspectives, be comparative and employ both qualitative and quantitative methods. Self-administered questionnaires are frequently used as a quantitative evaluation method in medical informatics, but very few validated questionnaires address clinical use of EMR systems. Methods We have developed a task-oriented questionnaire for evaluating EMR systems from the clinician's perspective. The key feature of the questionnaire is a list of 24 general clinical tasks. It is applicable to physicians of most specialties and covers essential parts of their information-oriented work. The task list appears in two separate sections, about EMR use and task performance using the EMR, respectively. By combining these sections, the evaluator may estimate the potential impact of the EMR system on health care delivery. The results may also be compared across time, site or vendor. This paper describes the development, performance and validation of the questionnaire. Its performance is shown in two demonstration studies (n = 219 and 80). Its content is validated in an interview study (n = 10), and its reliability is investigated in a test-retest study (n = 37) and a scaling study (n = 31). Results In the interviews, the physicians found the general clinical tasks in the questionnaire relevant and comprehensible. The tasks were interpreted concordant to their definitions. However, the physicians found questions about tasks not explicitly or only partially supported by the EMR systems difficult to answer. The two demonstration studies provided unambiguous results and low percentages of missing responses. In addition, criterion validity was demonstrated for a majority of task-oriented questions. Their test-retest reliability was generally high, and the non-standard scale was found symmetric and ordinal. Conclusion This questionnaire is relevant for clinical work and EMR systems, provides reliable and interpretable results, and may be used as part of any evaluation effort involving the clinician's perspective of an EMR system. PMID:15018620

Task-oriented evaluation of electronic medical records systems: development and validation of a questionnaire for physicians.

PubMed

Laerum, Hallvard; Faxvaag, Arild

2004-02-09

Evaluation is a challenging but necessary part of the development cycle of clinical information systems like the electronic medical records (EMR) system. It is believed that such evaluations should include multiple perspectives, be comparative and employ both qualitative and quantitative methods. Self-administered questionnaires are frequently used as a quantitative evaluation method in medical informatics, but very few validated questionnaires address clinical use of EMR systems. We have developed a task-oriented questionnaire for evaluating EMR systems from the clinician's perspective. The key feature of the questionnaire is a list of 24 general clinical tasks. It is applicable to physicians of most specialties and covers essential parts of their information-oriented work. The task list appears in two separate sections, about EMR use and task performance using the EMR, respectively. By combining these sections, the evaluator may estimate the potential impact of the EMR system on health care delivery. The results may also be compared across time, site or vendor. This paper describes the development, performance and validation of the questionnaire. Its performance is shown in two demonstration studies (n = 219 and 80). Its content is validated in an interview study (n = 10), and its reliability is investigated in a test-retest study (n = 37) and a scaling study (n = 31). In the interviews, the physicians found the general clinical tasks in the questionnaire relevant and comprehensible. The tasks were interpreted concordant to their definitions. However, the physicians found questions about tasks not explicitly or only partially supported by the EMR systems difficult to answer. The two demonstration studies provided unambiguous results and low percentages of missing responses. In addition, criterion validity was demonstrated for a majority of task-oriented questions. Their test-retest reliability was generally high, and the non-standard scale was found symmetric and ordinal. This questionnaire is relevant for clinical work and EMR systems, provides reliable and interpretable results, and may be used as part of any evaluation effort involving the clinician's perspective of an EMR system.

The effect of environment and task on gait parameters after stroke: A randomized comparison of measurement conditions.

PubMed

Lord, Susan E; Rochester, Lynn; Weatherall, Mark; McPherson, Kathryn M; McNaughton, Harry K

2006-07-01

To assess the effect of environment and a secondary task on gait parameters in community ambulant stroke survivors and to assess the contribution of clinical symptoms to gait performance. A 2x3 randomized factorial design with 2 main factors: task (no task, motor task, cognitive task) and environment (clinic, suburban street, shopping mall). Subjects were assessed in 1 of 3 settings: 2 in the community (a suburban street and shopping mall) and 1 clinical environment. Twenty-seven people with stroke (mean age, 61+/-11.6y; mean time since stroke onset, 45.8+/-34.2mo), living at home, were recruited from community stroke groups and from a local rehabilitation unit. Selection criteria included the following: ability to give informed consent, unilateral first ever or recurrent stroke at least 6 months previously, walking independently in the community, a gait speed between 24 and 50 m/min, Mini-Mental State Examination score of 24 or higher, and no severe comorbidity. Not applicable. Gait speed (in m/min), cadence, and step length were assessed by using an accelerometer with adjustable thresholds. Clinical measures hypothesized to influence gait parameters in community environments were also assessed including fatigue, anxiety and depression, and attentional deficit. Twenty-seven people with a mean baseline gait speed of 42.2+/-5.9 m/min were randomly allocated to 1 of 9 conditions in which the setting and distraction were manipulated. Analysis of variance showed a significant main effect for environment (P = .046) but not for task (P = .37). The interaction between task and environment was not significant (P = .73). Adjusting for baseline gait speed, people walked on average 8.8m/min faster in the clinic (95% confidence interval, 0.3-17.3m/min) than in the mall. Scores for fatigue, anxiety and depression, and attentional deficit were higher than normative values but did not influence gait performance. This study suggests that people with chronic stroke cope well with the challenges of varied environments and can maintain their gait speed while performing a secondary task. Despite moderate levels of gait impairment, gait automaticity may be restored over time to a functional level.

Six principles to enhance health workforce flexibility.

PubMed

Nancarrow, Susan A

2015-04-07

This paper proposes approaches to break down the boundaries that reduce the ability of the health workforce to respond to population needs, or workforce flexibility. Accessible health services require sufficient numbers and types of skilled workers to meet population needs. However, there are several reasons that the health workforce cannot or does not meet population needs. These primarily stem from workforce shortages. However, the health workforce can also be prevented from responding appropriately and efficiently because of restrictions imposed by professional boundaries, funding models or therapeutic partitions. These boundaries limit the ability of practitioners to effectively diagnose and treat patients by restricting access to specific skills, technologies and services. In some cases, these boundaries not only reduce workforce flexibility, but they introduce inefficiencies in the form of additional clinical transactions and costs, further detracting from workforce responsiveness. Several new models of care are being developed to enhance workforce flexibility by enabling existing staff to work to their full scope of practice, extend their roles or by introducing new workers. Expanding on these concepts, this theoretical paper proposes six principles that have the potential to enhance health workforce flexibility, specifically: 1. Measure health system performance from the perspective of the patient. 2. Minimise training times. 3. Regulate tasks (competencies), not professions. 4. Match rewards and indemnity to the levels of skill and risk required to perform a particular task, not professional title. 5. Ensure that practitioners have all the skills they need to perform the tasks required to work in the environment in which they work 6. Enable practitioners to work to their full scope of practice delegate tasks where required These proposed principles will challenge some of the existing social norms around health-care delivery; however, many of these principles are already being applied, albeit on a small scale. This paper discusses the implications of these reforms. 1. Is person-centred care at odds with professional monopolies? 2. Should the state regulate professions and, by doing so, protect professional monopolies or, instead, regulate tasks or competencies? 3. Can health-care efficiency be enhanced by reducing the number of clinical transactions required to meet patient needs?

Test-Retest Reliability of Measures Commonly Used to Measure Striatal Dysfunction across Multiple Testing Sessions: A Longitudinal Study.

PubMed

Palmer, Clare E; Langbehn, Douglas; Tabrizi, Sarah J; Papoutsi, Marina

2017-01-01

Cognitive impairment is common amongst many neurodegenerative movement disorders such as Huntington's disease (HD) and Parkinson's disease (PD) across multiple domains. There are many tasks available to assess different aspects of this dysfunction, however, it is imperative that these show high test-retest reliability if they are to be used to track disease progression or response to treatment in patient populations. Moreover, in order to ensure effects of practice across testing sessions are not misconstrued as clinical improvement in clinical trials, tasks which are particularly vulnerable to practice effects need to be highlighted. In this study we evaluated test-retest reliability in mean performance across three testing sessions of four tasks that are commonly used to measure cognitive dysfunction associated with striatal impairment: a combined Simon Stop-Signal Task; a modified emotion recognition task; a circle tracing task; and the trail making task. Practice effects were seen between sessions 1 and 2 across all tasks for the majority of dependent variables, particularly reaction time variables; some, but not all, diminished in the third session. Good test-retest reliability across all sessions was seen for the emotion recognition, circle tracing, and trail making test. The Simon interference effect and stop-signal reaction time (SSRT) from the combined-Simon-Stop-Signal task showed moderate test-retest reliability, however, the combined SSRT interference effect showed poor test-retest reliability. Our results emphasize the need to use control groups when tracking clinical progression or use pre-baseline training on tasks susceptible to practice effects.

Social Cognition Psychometric Evaluation: Results of the Final Validation Study.

PubMed

Pinkham, Amy E; Harvey, Philip D; Penn, David L

2018-06-06

Social cognition is increasingly recognized as an important treatment target in schizophrenia; however, the dearth of well-validated measures that are suitable for use in clinical trials remains a significant limitation. The Social Cognition Psychometric Evaluation (SCOPE) study addresses this need by systematically evaluating the psychometric properties of promising measures. In this final phase of SCOPE, eight new or modified tasks were evaluated. Stable outpatients with schizophrenia (n = 218) and healthy controls (n = 154) completed the battery at baseline and 2-4 weeks later across three sites. Tasks included the Bell Lysaker Emotion Recognition Task (BLERT), Penn Emotion Recognition Task (ER-40), Reading the Mind in the Eyes Task (Eyes), The Awareness of Social Inferences Test (TASIT), Hinting Task, Mini Profile of Nonverbal Sensitivity (MiniPONS), Social Attribution Task-Multiple Choice (SAT-MC), and Intentionality Bias Task (IBT). BLERT and ER-40 modifications included response time and confidence ratings. The Eyes task was modified to include definitions of terms and TASIT to include response time. Hinting was scored with more stringent criteria. MiniPONS, SAT-MC, and IBT were new to this phase. Tasks were evaluated on (1) test-retest reliability, (2) utility as a repeated measure, (3) relationship to functional outcome, (4) practicality and tolerability, (5) sensitivity to group differences, and (6) internal consistency. Hinting, BLERT, and ER-40 showed the strongest psychometric properties and are recommended for use in clinical trials. Eyes, TASIT, and IBT showed somewhat weaker psychometric properties and require further study. MiniPONS and SAT-MC showed poorer psychometric properties that suggest caution for their use in clinical trials.

Human-centric predictive model of task difficulty for human-in-the-loop control tasks

PubMed Central

Majewicz Fey, Ann

2018-01-01

Quantitatively measuring the difficulty of a manipulation task in human-in-the-loop control systems is ill-defined. Currently, systems are typically evaluated through task-specific performance measures and post-experiment user surveys; however, these methods do not capture the real-time experience of human users. In this study, we propose to analyze and predict the difficulty of a bivariate pointing task, with a haptic device interface, using human-centric measurement data in terms of cognition, physical effort, and motion kinematics. Noninvasive sensors were used to record the multimodal response of human user for 14 subjects performing the task. A data-driven approach for predicting task difficulty was implemented based on several task-independent metrics. We compare four possible models for predicting task difficulty to evaluated the roles of the various types of metrics, including: (I) a movement time model, (II) a fusion model using both physiological and kinematic metrics, (III) a model only with kinematic metrics, and (IV) a model only with physiological metrics. The results show significant correlation between task difficulty and the user sensorimotor response. The fusion model, integrating user physiology and motion kinematics, provided the best estimate of task difficulty (R2 = 0.927), followed by a model using only kinematic metrics (R2 = 0.921). Both models were better predictors of task difficulty than the movement time model (R2 = 0.847), derived from Fitt’s law, a well studied difficulty model for human psychomotor control. PMID:29621301

IVHS Countermeasures for Rear-End Collisions, Task 1 Vol. III: 1991 NASS CDS Case Analysis

DOT National Transportation Integrated Search

1994-02-15

This report is from the NHTSA sponsored program, "IVHS Countermeasures for Rear-End Collisions". The Task 1 Interim Report consists of six volumes. This Volume, Volume III, 1991 NASS CDS Clinical Case Analysis presents the results of a clinical case ...

Standards for data acquisition and software-based analysis of in vivo electroencephalography recordings from animals. A TASK1-WG5 report of the AES/ILAE Translational Task Force of the ILAE.

PubMed

Moyer, Jason T; Gnatkovsky, Vadym; Ono, Tomonori; Otáhal, Jakub; Wagenaar, Joost; Stacey, William C; Noebels, Jeffrey; Ikeda, Akio; Staley, Kevin; de Curtis, Marco; Litt, Brian; Galanopoulou, Aristea S

2017-11-01

Electroencephalography (EEG)-the direct recording of the electrical activity of populations of neurons-is a tremendously important tool for diagnosing, treating, and researching epilepsy. Although standard procedures for recording and analyzing human EEG exist and are broadly accepted, there are no such standards for research in animal models of seizures and epilepsy-recording montages, acquisition systems, and processing algorithms may differ substantially among investigators and laboratories. The lack of standard procedures for acquiring and analyzing EEG from animal models of epilepsy hinders the interpretation of experimental results and reduces the ability of the scientific community to efficiently translate new experimental findings into clinical practice. Accordingly, the intention of this report is twofold: (1) to review current techniques for the collection and software-based analysis of neural field recordings in animal models of epilepsy, and (2) to offer pertinent standards and reporting guidelines for this research. Specifically, we review current techniques for signal acquisition, signal conditioning, signal processing, data storage, and data sharing, and include applicable recommendations to standardize collection and reporting. We close with a discussion of challenges and future opportunities, and include a supplemental report of currently available acquisition systems and analysis tools. This work represents a collaboration on behalf of the American Epilepsy Society/International League Against Epilepsy (AES/ILAE) Translational Task Force (TASK1-Workgroup 5), and is part of a larger effort to harmonize video-EEG interpretation and analysis methods across studies using in vivo and in vitro seizure and epilepsy models. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

A usability evaluation of four commercial dental computer-based patient record systems

PubMed Central

Thyvalikakath, Thankam P.; Monaco, Valerie; Thambuganipalle, Hima Bindu; Schleyer, Titus

2008-01-01

Background The usability of dental computer-based patient record (CPR) systems has not been studied, despite early evidence that poor usability is a problem for dental CPR system users at multiple levels. Methods The authors conducted formal usability tests of four dental CPR systems by using a purposive sample of four groups of five novice users. The authors measured task outcomes (correctly completed, incorrectly completed and incomplete) in each CPR system while the participants performed nine clinical documentation tasks, as well as the number of usability problems identified in each CPR system and their potential relationship to task outcomes. The authors reviewed the software application design aspects responsible for these usability problems. Results The range for correctly completed tasks was 16 to 64 percent, for incorrectly completed tasks 18 to 38 percent and for incomplete tasks 9 to 47 percent. The authors identified 286 usability problems. The main types were three unsuccessful attempts, negative affect and task incorrectly completed. They also identified six problematic interface and interaction designs that led to usability problems. Conclusion The four dental CPR systems studied have significant usability problems for novice users, resulting in a steep learning curve and potentially reduced system adoption. Clinical Implications The significant number of data entry errors raises concerns about the quality of documentation in clinical practice. PMID:19047669

The effect of video game "warm-up" on performance of laparoscopic surgery tasks.

PubMed

Rosser, James C; Gentile, Douglas A; Hanigan, Kevin; Danner, Omar K

2012-01-01

Performing laparoscopic procedures requires special training and has been documented as a significant source of surgical errors. "Warming up" before performing a task has been shown to enhance performance. This study investigates whether surgeons benefit from "warming up" using select video games immediately before performing laparoscopic partial tasks and clinical tasks. This study included 303 surgeons (249 men and 54 women). Participants were split into a control (n=180) and an experimental group (n=123). The experimental group played 3 previously validated video games for 6 minutes before task sessions. The Cobra Rope partial task and suturing exercises were performed immediately after the warm-up sessions. Surgeons who played video games prior to the Cobra Rope drill were significantly faster on their first attempt and across all 10 trials. The experimental and control groups were significantly different in their total suturing scores (t=2.28, df=288, P<.05). The overall Top Gun score showed that the experimental group performed marginally better overall. This study demonstrates that subjects completing "warming-up" sessions with select video games prior to performing laparoscopic partial and clinical tasks (intracorporeal suturing) were faster and had fewer errors than participants not engaging in "warm-up." More study is needed to determine whether this translates into superior procedural execution in the clinical setting.

A systematic review of interventions conducted in clinical or community settings to improve dual-task postural control in older adults

PubMed Central

Agmon, Maayan; Belza, Basia; Nguyen, Huong Q; Logsdon, Rebecca G; Kelly, Valerie E

2014-01-01

Background Injury due to falls is a major problem among older adults. Decrements in dual-task postural control performance (simultaneously performing two tasks, at least one of which requires postural control) have been associated with an increased risk of falling. Evidence-based interventions that can be used in clinical or community settings to improve dual-task postural control may help to reduce this risk. Purpose The aims of this systematic review are: 1) to identify clinical or community-based interventions that improved dual-task postural control among older adults; and 2) to identify the key elements of those interventions. Data sources Studies were obtained from a search conducted through October 2013 of the following electronic databases: PubMed, CINAHL, PsycINFO, and Web of Science. Study selection Randomized and nonrandomized controlled studies examining the effects of interventions aimed at improving dual-task postural control among community-dwelling older adults were selected. Data extraction All studies were evaluated based on methodological quality. Intervention characteristics including study purpose, study design, and sample size were identified, and effects of dual-task interventions on various postural control and cognitive outcomes were noted. Data synthesis Twenty-two studies fulfilled the selection criteria and were summarized in this review to identify characteristics of successful interventions. Limitations The ability to synthesize data was limited by the heterogeneity in participant characteristics, study designs, and outcome measures. Conclusion Dual-task postural control can be modified by specific training. There was little evidence that single-task training transferred to dual-task postural control performance. Further investigation of dual-task training using standardized outcome measurements is needed. PMID:24741296

Task shifting to clinical officer-led echocardiography screening for detecting rheumatic heart disease in Malawi, Africa.

PubMed

Sims Sanyahumbi, Amy; Sable, Craig A; Karlsten, Melissa; Hosseinipour, Mina C; Kazembe, Peter N; Minard, Charles G; Penny, Daniel J

2017-08-01

Echocardiographic screening for rheumatic heart disease in asymptomatic children may result in early diagnosis and prevent progression. Physician-led screening is not feasible in Malawi. Task shifting to mid-level providers such as clinical officers may enable more widespread screening. Hypothesis With short-course training, clinical officers can accurately screen for rheumatic heart disease using focussed echocardiography. A total of eight clinical officers completed three half-days of didactics and 2 days of hands-on echocardiography training. Clinical officers were evaluated by performing screening echocardiograms on 20 children with known rheumatic heart disease status. They indicated whether children should be referred for follow-up. Referral was indicated if mitral regurgitation measured more than 1.5 cm or there was any measurable aortic regurgitation. The κ statistic was calculated to measure referral agreement with a paediatric cardiologist. Sensitivity and specificity were estimated using a generalised linear mixed model, and were calculated on the basis of World Heart Federation diagnostic criteria. The mean κ statistic comparing clinical officer referrals with the paediatric cardiologist was 0.72 (95% confidence interval: 0.62, 0.82). The κ value ranged from a minimum of 0.57 to a maximum of 0.90. For rheumatic heart disease diagnosis, sensitivity was 0.91 (95% confidence interval: 0.86, 0.95) and specificity was 0.65 (95% confidence interval: 0.57, 0.72). There was substantial agreement between clinical officers and paediatric cardiologists on whether to refer. Clinical officers had a high sensitivity in detecting rheumatic heart disease. With short-course training, clinical officer-led echo screening for rheumatic heart disease is a viable alternative to physician-led screening in resource-limited settings.

2013 Review and Update of the Genetic Counseling Practice Based Competencies by a Task Force of the Accreditation Council for Genetic Counseling.

PubMed

Doyle, Debra Lochner; Awwad, Rawan I; Austin, Jehannine C; Baty, Bonnie J; Bergner, Amanda L; Brewster, Stephanie J; Erby, Lori A H; Franklin, Cathi Rubin; Greb, Anne E; Grubs, Robin E; Hooker, Gillian W; Noblin, Sarah Jane; Ormond, Kelly E; Palmer, Christina G; Petty, Elizabeth M; Singletary, Claire N; Thomas, Matthew J; Toriello, Helga; Walton, Carol S; Uhlmann, Wendy R

2016-10-01

The first practice based competencies (PBCs) for the field of genetic counseling were adopted by the American Board of Genetic Counseling (ABGC), 1996. Since that time, there has been significant growth in established and new work settings (clinical and non-clinical) and changes in service delivery models and the roles of genetic counselors. These changes prompted the ABGC to appoint a PBC Task Force in 2011 to review the PBCs with respect to their current relevance and to revise and update them as necessary. There are four domains in the revised PBCs: (I) Genetics Expertise and Analysis (II) Interpersonal, Psychosocial and Counseling Skills (III) Education and (IV) Professional Development and Practice. There are 22 competencies, each clarified with learning objectives or samples of activities and skills; a glossary is included. New competencies were added that address genomics, genetic testing and genetic counselors' roles in risk assessment, education, supervision, conducting research and presenting research options to patients. With PBCs serving as the pre-defined abilities or outcomes of training, graduating genetic counselors will be well prepared to enter the field with a minimum level of skills and abilities. A description of the Task Force's work, key changes and the 2013 PBCs are presented herein.

The Relationship between Organizational Climate and Quality of Chronic Disease Management

PubMed Central

Benzer, Justin K; Young, Gary; Stolzmann, Kelly; Osatuke, Katerine; Meterko, Mark; Caso, Allison; White, Bert; Mohr, David C

2011-01-01

Objective To test the utility of a two-dimensional model of organizational climate for explaining variation in diabetes care between primary care clinics. Data Sources/Study Setting Secondary data were obtained from 223 primary care clinics in the Department of Veterans Affairs health care system. Study Design Organizational climate was defined using the dimensions of task and relational climate. The association between primary care organizational climate and diabetes processes and intermediate outcomes were estimated for 4,539 patients in a cross-sectional study. Data Collection/Extraction Methods All data were collected from administrative datasets. The climate data were drawn from the 2007 VA All Employee Survey, and the outcomes data were collected as part of the VA External Peer Review Program. Climate data were aggregated to the facility level of analysis and merged with patient-level data. Principal Findings Relational climate was related to an increased likelihood of diabetes care process adherence, with significant but small effects for adherence to intermediate outcomes. Task climate was generally not shown to be related to adherence. Conclusions The role of relational climate in predicting the quality of chronic care was supported. Future research should examine the mediators and moderators of relational climate and further investigate task climate. PMID:21210799

The Stroop test as a measure of performance validity in adults clinically referred for neuropsychological assessment.

PubMed

Erdodi, Laszlo A; Sagar, Sanya; Seke, Kristian; Zuccato, Brandon G; Schwartz, Eben S; Roth, Robert M

2018-06-01

This study was designed to develop performance validity indicators embedded within the Delis-Kaplan Executive Function Systems (D-KEFS) version of the Stroop task. Archival data from a mixed clinical sample of 132 patients (50% male; M Age = 43.4; M Education = 14.1) clinically referred for neuropsychological assessment were analyzed. Criterion measures included the Warrington Recognition Memory Test-Words and 2 composites based on several independent validity indicators. An age-corrected scaled score ≤6 on any of the 4 trials reliably differentiated psychometrically defined credible and noncredible response sets with high specificity (.87-.94) and variable sensitivity (.34-.71). An inverted Stroop effect was less sensitive (.14-.29), but comparably specific (.85-90) to invalid performance. Aggregating the newly developed D-KEFS Stroop validity indicators further improved classification accuracy. Failing the validity cutoffs was unrelated to self-reported depression or anxiety. However, it was associated with elevated somatic symptom report. In addition to processing speed and executive function, the D-KEFS version of the Stroop task can function as a measure of performance validity. A multivariate approach to performance validity assessment is generally superior to univariate models. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Kinematics effectively delineate accomplished users of endovascular robotics with a physical training model.

PubMed

Duran, Cassidy; Estrada, Sean; O'Malley, Marcia; Lumsden, Alan B; Bismuth, Jean

2015-02-01

Endovascular robotics systems, now approved for clinical use in the United States and Europe, are seeing rapid growth in interest. Determining who has sufficient expertise for safe and effective clinical use remains elusive. Our aim was to analyze performance on a robotic platform to determine what defines an expert user. During three sessions, 21 subjects with a range of endovascular expertise and endovascular robotic experience (novices <2 hours to moderate-extensive experience with >20 hours) performed four tasks on a training model. All participants completed a 2-hour training session on the robot by a certified instructor. Completion times, global rating scores, and motion metrics were collected to assess performance. Electromagnetic tracking was used to capture and to analyze catheter tip motion. Motion analysis was based on derivations of speed and position including spectral arc length and total number of submovements (inversely proportional to proficiency of motion) and duration of submovements (directly proportional to proficiency). Ninety-eight percent of competent subjects successfully completed the tasks within the given time, whereas 91% of noncompetent subjects were successful. There was no significant difference in completion times between competent and noncompetent users except for the posterior branch (151 s:105 s; P = .01). The competent users had more efficient motion as evidenced by statistically significant differences in the metrics of motion analysis. Users with >20 hours of experience performed significantly better than those newer to the system, independent of prior endovascular experience. This study demonstrates that motion-based metrics can differentiate novice from trained users of flexible robotics systems for basic endovascular tasks. Efficiency of catheter movement, consistency of performance, and learning curves may help identify users who are sufficiently trained for safe clinical use of the system. This work will help identify the learning curve and specific movements that translate to expert robotic navigation. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Clinical quality needs complex adaptive systems and machine learning.

PubMed

Marsland, Stephen; Buchan, Iain

2004-01-01

The vast increase in clinical data has the potential to bring about large improvements in clinical quality and other aspects of healthcare delivery. However, such benefits do not come without cost. The analysis of such large datasets, particularly where the data may have to be merged from several sources and may be noisy and incomplete, is a challenging task. Furthermore, the introduction of clinical changes is a cyclical task, meaning that the processes under examination operate in an environment that is not static. We suggest that traditional methods of analysis are unsuitable for the task, and identify complexity theory and machine learning as areas that have the potential to facilitate the examination of clinical quality. By its nature the field of complex adaptive systems deals with environments that change because of the interactions that have occurred in the past. We draw parallels between health informatics and bioinformatics, which has already started to successfully use machine learning methods.

Beads task vs. box task: The specificity of the jumping to conclusions bias.

PubMed

Balzan, Ryan P; Ephraums, Rachel; Delfabbro, Paul; Andreou, Christina

2017-09-01

Previous research involving the probabilistic reasoning 'beads task' has consistently demonstrated a jumping-to-conclusions (JTC) bias, where individuals with delusions make decisions based on limited evidence. However, recent studies have suggested that miscomprehension may be confounding the beads task. The current study aimed to test the conventional beads task against a conceptually simpler probabilistic reasoning "box task" METHODS: One hundred non-clinical participants completed both the beads task and the box task, and the Peters et al. Delusions Inventory (PDI) to assess for delusion-proneness. The number of 'draws to decision' was assessed for both tasks. Additionally, the total amount of on-screen evidence was manipulated for the box task, and two new box task measures were assessed (i.e., 'proportion of evidence requested' and 'deviation from optimal solution'). Despite being conceptually similar, the two tasks did not correlate, and participants requested significantly less information on the beads task relative to the box task. High-delusion-prone participants did not demonstrate hastier decisions on either task; in fact, for box task, this group was observed to be significantly more conservative than low-delusion-prone group. Neither task was incentivized; results need replication with a clinical sample. Participants, and particularly those identified as high-delusion-prone, displayed a more conservative style of responding on the novel box task, relative to the beads task. The two tasks, whilst conceptually similar, appear to be tapping different cognitive processes. The implications of these results are discussed in relation to the JTC bias and the theoretical mechanisms thought to underlie it. Copyright © 2016 Elsevier Ltd. All rights reserved.

Issues in transferring preclinical skill learning to the clinical context.

PubMed

Chambers, D W

1987-05-01

The relationship between student performance in preclinical technique laboratory courses and in clinic is not straightforward. While American dental education in the preclinical courses is effective in teaching mastery of fundamentals to most students and identifying those who should not proceed to patient care, the prediction from technique laboratory performance of who will do well in clinic is weak. Factors accounting for this poor correlation include differences in the mix of skills required in the two contexts, failure to teach for transfer of skills to new settings, and laboratory education practices that create clinically dysfunctional habits. As a means of understanding the transfer issue, a distinction is made among task as given by the instructor, task as interpreted by the student, and task as negotiated in the interpersonal context of dental education.

A cognitive psychometric model for the psychodiagnostic assessment of memory-related deficits.

PubMed

Alexander, Gregory E; Satalich, Timothy A; Shankle, W Rodman; Batchelder, William H

2016-03-01

Clinical tests used for psychodiagnostic purposes, such as the well-known Alzheimer's Disease Assessment Scale: Cognitive subscale (ADAS-Cog), include a free-recall task. The free-recall task taps into latent cognitive processes associated with learning and memory components of human cognition, any of which might be impaired with the progression of Alzheimer's disease (AD). A Hidden Markov model of free recall is developed to measure latent cognitive processes used during the free-recall task. In return, these cognitive measurements give us insight into the degree to which normal cognitive functions are differentially impaired by medical conditions, such as AD and related disorders. The model is used to analyze the free-recall data obtained from healthy elderly participants, participants diagnosed as having mild cognitive impairment, and participants diagnosed with early AD. The model is specified hierarchically to handle item differences because of the serial position curve in free recall, as well as within-group individual differences in participants' recall abilities. Bayesian hierarchical inference is used to estimate the model. The model analysis suggests that the impaired patients have the following: (1) long-term memory encoding deficits, (2) short-term memory (STM) retrieval deficits for all but very short time intervals, (3) poorer transfer into long-term memory for items successfully retrieved from STM, and (4) poorer retention of items encoded into long-term memory after longer delays. Yet, impaired patients appear to have no deficit in immediate recall of encoded words in long-term memory or for very short time intervals in STM. (c) 2016 APA, all rights reserved).

Design, fabrication, and implementation of voxel-based 3D printed textured phantoms for task-based image quality assessment in CT

NASA Astrophysics Data System (ADS)

Solomon, Justin; Ba, Alexandre; Diao, Andrew; Lo, Joseph; Bier, Elianna; Bochud, François; Gehm, Michael; Samei, Ehsan

2016-03-01

In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influence of background texture on image quality. The purpose of this study was to design and implement anatomically informed textured phantoms for task-based assessment of low-contrast detection. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find the CLB parameters that were most reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, a cylinder phantom (165 mm in diameter and 30 mm height) was designed, containing 20 low-contrast spherical signals (6 mm in diameter at targeted contrast levels of ~3.2, 5.2, 7.2, 10, and 14 HU, 4 repeats per signal). The phantom was voxelized and input into a commercial multi-material 3D printer (Object Connex 350), with custom software for voxel-based printing. Using principles of digital half-toning and dithering, the 3D printer was programmed to distribute two base materials (VeroWhite and TangoPlus, nominal voxel size of 42x84x30 microns) to achieve the targeted spatial distribution of x-ray attenuation properties. The phantom was used for task-based image quality assessment of a clinically available iterative reconstruction algorithm (Sinogram Affirmed Iterative Reconstruction, SAFIRE) using a channelized Hotelling observer paradigm. Images of the textured phantom and a corresponding uniform phantom were acquired at six dose levels and observer model performance was estimated for each condition (5 contrasts x 6 doses x 2 reconstructions x 2 backgrounds = 120 total conditions). Based on the observer model results, the dose reduction potential of SAFIRE was computed and compared between the uniform and textured phantom. The dose reduction potential of SAFIRE was found to be 23% based on the uniform phantom and 17% based on the textured phantom. This discrepancy demonstrates the need to consider background texture when assessing non-linear reconstruction algorithms.

Unpacking the Complexity of Patient Handoffs Through the Lens of Cognitive Load Theory.

PubMed

Young, John Q; Ten Cate, Olle; O'Sullivan, Patricia S; Irby, David M

2016-01-01

The transfer of a patient from one clinician to another is a high-risk event. Errors are common and lead to patient harm. More effective methods for learning how to give and receive sign-out is an important public health priority. Performing a handoff is a complex task. Trainees must simultaneously apply and integrate clinical, communication, and systems skills into one time-limited and highly constrained activity. The task demands can easily exceed the information-processing capacity of the trainee, resulting in impaired learning and performance. Appreciating the limits of working memory can help identify the challenges that instructional techniques and research must then address. Cognitive load theory (CLT) identifies three types of load that impact working memory: intrinsic (task-essential), extraneous (not essential to task), and germane (learning related). The authors generated a list of factors that affect a trainee's learning and performance of a handoff based on CLT. The list was revised based on feedback from experts in medical education and in handoffs. By consensus, the authors associated each factor with the type of cognitive load it primarily effects. The authors used this analysis to build a conceptual model of handoffs through the lens of CLT. The resulting conceptual model unpacks the complexity of handoffs and identifies testable hypotheses for educational research and instructional design. The model identifies features of a handoff that drive extraneous, intrinsic, and germane load for both the sender and the receiver. The model highlights the importance of reducing extraneous load, matching intrinsic load to the developmental stage of the learner and optimizing germane load. Specific CLT-informed instructional techniques for handoffs are explored. Intrinsic and germane load are especially important to address and include factors such as knowledge of the learner, number of patients, time constraints, clinical uncertainties, overall patient/panel complexity, interacting comorbidities or therapeutics, experience or specialty gradients between the sender and receiver, the maturity of the evidence base for the patient's disease, and the use of metacognitive techniques. Research that identifies which cognitive load factors most significantly affect the learning and performance of handoffs can lead to novel, contextually adapted instructional techniques and handoff protocols. The application of CLT to handoffs may also help with the further development of CLT as a learning theory.

Clinical Laboratory Helper.

ERIC Educational Resources Information Center

Szucs, Susan C.; And Others

This curriculum guide provides competencies and tasks for the position of clinical laboratory helper; it serves as both a career exploration experience and/or entry-level employment training. A list of 25 validated competencies and tasks covers careers from entry level to those that must be mastered to earn an associate degree in clinical…

Comprehending Comprehension: Selected Possibilities for Clinical Practice Within a Multidimensional Model.

PubMed

Wallach, Geraldine P; Ocampo, Alaine

2017-04-20

In this discussion as part of a response to Catts and Kamhi's "Prologue: Reading Comprehension Is Not a Single Activity" (2017), the authors provide selected examples from 4th-, 5th-, and 6th-grade texts to demonstrate, in agreement with Catts and Kamhi, that reading comprehension is a multifaceted and complex ability. The authors were asked to provide readers with evidence-based practices that lend support to applications of a multidimensional model of comprehension. We present examples from the reading comprehension literature that support the notion that reading is a complex set of abilities that include a reader's ability, especially background knowledge; the type of text the reader is being asked to comprehend; and the task or technique used in assessment or intervention paradigms. An intervention session from 6th grade serves to demonstrate how background knowledge, a text's demands, and tasks may come together in the real world as clinicians and educators aim to help students comprehend complex material. The authors agree with the conceptual framework proposed by Catts and Kamhi that clinicians and educators should consider the multidimensional nature of reading comprehension (an interaction of reader, text, and task) when creating assessment and intervention programs. The authors might depart slightly by considering, more closely, those reading comprehension strategies that might facilitate comprehension across texts and tasks with an understanding of students' individual needs at different points in time.

Improving accuracy and power with transfer learning using a meta-analytic database.

PubMed

Schwartz, Yannick; Varoquaux, Gaël; Pallier, Christophe; Pinel, Philippe; Poline, Jean-Baptiste; Thirion, Bertrand

2012-01-01

Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on analysis of previous work, sometimes formalized in a so-called meta-analysis. In brain imaging, this approach underlies the specification of regions of interest (ROIs) that are usually selected on the basis of the coordinates of previously detected effects. In this paper, we propose to use a database of images, rather than coordinates, and frame the problem as transfer learning: learning a discriminant model on a reference task to apply it to a different but related new task. To facilitate statistical analysis of small cohorts, we use a sparse discriminant model that selects predictive voxels on the reference task and thus provides a principled procedure to define ROIs. The benefits of our approach are twofold. First it uses the reference database for prediction, i.e., to provide potential biomarkers in a clinical setting. Second it increases statistical power on the new task. We demonstrate on a set of 18 pairs of functional MRI experimental conditions that our approach gives good prediction. In addition, on a specific transfer situation involving different scanners at different locations, we show that voxel selection based on transfer learning leads to higher detection power on small cohorts.

Job Analysis Techniques for Restructuring Health Manpower Education and Training in the Navy Medical Department. Attachment 4. Clinic QPCB Task Sort for Clinical Physician Assistants--Dermatology, ENT, Opththalmology, Orthopedics, and Urology.

ERIC Educational Resources Information Center

Technomics, Inc., McLean, VA.

This publication is Attachment 4 of a set of 16 computer listed QPCB task sorts, by career level, for the entire Hospital Corps and Dental Technician fields. Statistical data are presented in tabular form for a detailed listing of job duties for clinical physician assistants. (BT)

Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model

PubMed Central

Tan, Maxine; Pu, Jiantao; Zheng, Bin

2014-01-01

Purpose: Improving radiologists’ performance in classification between malignant and benign breast lesions is important to increase cancer detection sensitivity and reduce false-positive recalls. For this purpose, developing computer-aided diagnosis (CAD) schemes has been attracting research interest in recent years. In this study, we investigated a new feature selection method for the task of breast mass classification. Methods: We initially computed 181 image features based on mass shape, spiculation, contrast, presence of fat or calcifications, texture, isodensity, and other morphological features. From this large image feature pool, we used a sequential forward floating selection (SFFS)-based feature selection method to select relevant features, and analyzed their performance using a support vector machine (SVM) model trained for the classification task. On a database of 600 benign and 600 malignant mass regions of interest (ROIs), we performed the study using a ten-fold cross-validation method. Feature selection and optimization of the SVM parameters were conducted on the training subsets only. Results: The area under the receiver operating characteristic curve (AUC) = 0.805±0.012 was obtained for the classification task. The results also showed that the most frequently-selected features by the SFFS-based algorithm in 10-fold iterations were those related to mass shape, isodensity and presence of fat, which are consistent with the image features frequently used by radiologists in the clinical environment for mass classification. The study also indicated that accurately computing mass spiculation features from the projection mammograms was difficult, and failed to perform well for the mass classification task due to tissue overlap within the benign mass regions. Conclusions: In conclusion, this comprehensive feature analysis study provided new and valuable information for optimizing computerized mass classification schemes that may have potential to be useful as a “second reader” in future clinical practice. PMID:24664267

Evaluation of a task-based community oriented teaching model in family medicine for undergraduate medical students in Iraq.

PubMed

Al-Dabbagh, Samim A; Al-Taee, Waleed G

2005-08-22

The inclusion of family medicine in medical school curricula is essential for producing competent general practitioners. The aim of this study is to evaluate a task-based, community oriented teaching model of family medicine for undergraduate students in Iraqi medical schools. An innovative training model in family medicine was developed based upon tasks regularly performed by family physicians providing health care services at the Primary Health Care Centre (PHCC) in Mosul, Iraq. Participants were medical students enrolled in their final clinical year. Students were assigned to one of two groups. The implementation group (28 students) was exposed to the experimental model and the control group (56 students) received the standard teaching curriculum. The study took place at the Mosul College of Medicine and at the Al-Hadba PHCC in Mosul, Iraq, during the academic year 1999-2000. Pre- and post-exposure evaluations comparing the intervention group with the control group were conducted using a variety of assessment tools. The primary endpoints were improvement in knowledge of family medicine and development of essential performance skills. Results showed that the implementation group experienced a significant increase in knowledge and performance skills after exposure to the model and in comparison with the control group. Assessment of the model by participating students revealed a high degree of satisfaction with the planning, organization, and implementation of the intervention activities. Students also highly rated the relevancy of the intervention for future work. A model on PHCC training in family medicine is essential for all Iraqi medical schools. The model is to be implemented by various relevant departments until Departments of Family medicine are established.

Task-focused modeling in automated agriculture

NASA Astrophysics Data System (ADS)

Vriesenga, Mark R.; Peleg, K.; Sklansky, Jack

1993-01-01

Machine vision systems analyze image data to carry out automation tasks. Our interest is in machine vision systems that rely on models to achieve their designed task. When the model is interrogated from an a priori menu of questions, the model need not be complete. Instead, the machine vision system can use a partial model that contains a large amount of information in regions of interest and less information elsewhere. We propose an adaptive modeling scheme for machine vision, called task-focused modeling, which constructs a model having just sufficient detail to carry out the specified task. The model is detailed in regions of interest to the task and is less detailed elsewhere. This focusing effect saves time and reduces the computational effort expended by the machine vision system. We illustrate task-focused modeling by an example involving real-time micropropagation of plants in automated agriculture.

Diffusion Decision Model: Current Issues and History

PubMed Central

Ratcliff, Roger; Smith, Philip L.; Brown, Scott D.; McKoon, Gail

2016-01-01

There is growing interest in diffusion models to represent the cognitive and neural processes of speeded decision making. Sequential-sampling models like the diffusion model have a long history in psychology. They view decision making as a process of noisy accumulation of evidence from a stimulus. The standard model assumes that evidence accumulates at a constant rate during the second or two it takes to make a decision. This process can be linked to the behaviors of populations of neurons and to theories of optimality. Diffusion models have been used successfully in a range of cognitive tasks and as psychometric tools in clinical research to examine individual differences. In this article, we relate the models to both earlier and more recent research in psychology. PMID:26952739

Are we under-utilizing the talents of primary care personnel? A job analytic examination

PubMed Central

Hysong, Sylvia J; Best, Richard G; Moore, Frank I

2007-01-01

Background Primary care staffing decisions are often made unsystematically, potentially leading to increased costs, dissatisfaction, turnover, and reduced quality of care. This article aims to (1) catalogue the domain of primary care tasks, (2) explore the complexity associated with these tasks, and (3) examine how tasks performed by different job titles differ in function and complexity, using Functional Job Analysis to develop a new tool for making evidence-based staffing decisions. Methods Seventy-seven primary care personnel from six US Department of Veterans Affairs (VA) Medical Centers, representing six job titles, participated in two-day focus groups to generate 243 unique task statements describing the content of VA primary care. Certified job analysts rated tasks on ten dimensions representing task complexity, skills, autonomy, and error consequence. Two hundred and twenty-four primary care personnel from the same clinics then completed a survey indicating whether they performed each task. Tasks were catalogued using an adaptation of an existing classification scheme; complexity differences were tested via analysis of variance. Results Objective one: Task statements were categorized into four functions: service delivery (65%), administrative duties (15%), logistic support (9%), and workforce management (11%). Objective two: Consistent with expectations, 80% of tasks received ratings at or below the mid-scale value on all ten scales. Objective three: Service delivery and workforce management tasks received higher ratings on eight of ten scales (multiple functional complexity dimensions, autonomy, human error consequence) than administrative and logistic support tasks. Similarly, tasks performed by more highly trained job titles received higher ratings on six of ten scales than tasks performed by lower trained job titles. Contrary to expectations, the distribution of tasks across functions did not significantly vary by job title. Conclusion Primary care personnel are not being utilized to the extent of their training; most personnel perform many tasks that could reasonably be performed by personnel with less training. Primary care clinics should use evidence-based information to optimize job-person fit, adjusting clinic staff mix and allocation of work across staff to enhance efficiency and effectiveness. PMID:17397534

Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use.

PubMed

Harlé, Katia M; Stewart, Jennifer L; Zhang, Shunan; Tapert, Susan F; Yu, Angela J; Paulus, Martin P

2015-11-01

Bayesian ideal observer models quantify individuals' context- and experience-dependent beliefs and expectations about their environment, which provides a powerful approach (i) to link basic behavioural mechanisms to neural processing; and (ii) to generate clinical predictors for patient populations. Here, we focus on (ii) and determine whether individual differences in the neural representation of the need to stop in an inhibitory task can predict the development of problem use (i.e. abuse or dependence) in individuals experimenting with stimulants. One hundred and fifty-seven non-dependent occasional stimulant users, aged 18-24, completed a stop-signal task while undergoing functional magnetic resonance imaging. These individuals were prospectively followed for 3 years and evaluated for stimulant use and abuse/dependence symptoms. At follow-up, 38 occasional stimulant users met criteria for a stimulant use disorder (problem stimulant users), while 50 had discontinued use (desisted stimulant users). We found that those individuals who showed greater neural responses associated with Bayesian prediction errors, i.e. the difference between actual and expected need to stop on a given trial, in right medial prefrontal cortex/anterior cingulate cortex, caudate, anterior insula, and thalamus were more likely to exhibit problem use 3 years later. Importantly, these computationally based neural predictors outperformed clinical measures and non-model based neural variables in predicting clinical status. In conclusion, young adults who show exaggerated brain processing underlying whether to 'stop' or to 'go' are more likely to develop stimulant abuse. Thus, Bayesian cognitive models provide both a computational explanation and potential predictive biomarkers of belief processing deficits in individuals at risk for stimulant addiction. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Using Semantic Components to Represent Dynamics of an Interdisciplinary Healthcare Team in a Multi-Agent Decision Support System.

PubMed

Wilk, Szymon; Kezadri-Hamiaz, Mounira; Rosu, Daniela; Kuziemsky, Craig; Michalowski, Wojtek; Amyot, Daniel; Carrier, Marc

2016-02-01

In healthcare organizations, clinical workflows are executed by interdisciplinary healthcare teams (IHTs) that operate in ways that are difficult to manage. Responding to a need to support such teams, we designed and developed the MET4 multi-agent system that allows IHTs to manage patients according to presentation-specific clinical workflows. In this paper, we describe a significant extension of the MET4 system that allows for supporting rich team dynamics (understood as team formation, management and task-practitioner allocation), including selection and maintenance of the most responsible physician and more complex rules of selecting practitioners for the workflow tasks. In order to develop this extension, we introduced three semantic components: (1) a revised ontology describing concepts and relations pertinent to IHTs, workflows, and managed patients, (2) a set of behavioral rules describing the team dynamics, and (3) an instance base that stores facts corresponding to instances of concepts from the ontology and to relations between these instances. The semantic components are represented in first-order logic and they can be automatically processed using theorem proving and model finding techniques. We employ these techniques to find models that correspond to specific decisions controlling the dynamics of IHT. In the paper, we present the design of extended MET4 with a special focus on the new semantic components. We then describe its proof-of-concept implementation using the WADE multi-agent platform and the Z3 solver (theorem prover/model finder). We illustrate the main ideas discussed in the paper with a clinical scenario of an IHT managing a patient with chronic kidney disease.

Different models to mobilize peer support to improve diabetes self-management and clinical outcomes: evidence, logistics, evaluation considerations and needs for future research.

PubMed

Heisler, Michele

2010-06-01

Much of diabetes care needs to be carried out by patients between office visits with their health care providers. Yet, many patients face difficulties carrying out these tasks. In addition, many adults with diabetes cannot count on effective support from their families and friends to help them with their self-management. Peer support programmes are a promising approach to enhance social and emotional support, assist patients in daily management and living with diabetes and promote linkages to clinical care. This background paper provides a brief overview of different approaches to mobilize peer support for diabetes self-management support, discusses evidence to date on the effectiveness of each of these models, highlights logistical and evaluation issues for each model and concludes with a discussion of directions for future research in this area.

Different models to mobilize peer support to improve diabetes self-management and clinical outcomes: evidence, logistics, evaluation considerations and needs for future research

PubMed Central

2010-01-01

Much of diabetes care needs to be carried out by patients between office visits with their health care providers. Yet, many patients face difficulties carrying out these tasks. In addition, many adults with diabetes cannot count on effective support from their families and friends to help them with their self-management. Peer support programmes are a promising approach to enhance social and emotional support, assist patients in daily management and living with diabetes and promote linkages to clinical care. This background paper provides a brief overview of different approaches to mobilize peer support for diabetes self-management support, discusses evidence to date on the effectiveness of each of these models, highlights logistical and evaluation issues for each model and concludes with a discussion of directions for future research in this area. PMID:19293400

Generalized PSF modeling for optimized quantitation in PET imaging.

PubMed

Ashrafinia, Saeed; Mohy-Ud-Din, Hassan; Karakatsanis, Nicolas A; Jha, Abhinav K; Casey, Michael E; Kadrmas, Dan J; Rahmim, Arman

2017-06-21

Point-spread function (PSF) modeling offers the ability to account for resolution degrading phenomena within the PET image generation framework. PSF modeling improves resolution and enhances contrast, but at the same time significantly alters image noise properties and induces edge overshoot effect. Thus, studying the effect of PSF modeling on quantitation task performance can be very important. Frameworks explored in the past involved a dichotomy of PSF versus no-PSF modeling. By contrast, the present work focuses on quantitative performance evaluation of standard uptake value (SUV) PET images, while incorporating a wide spectrum of PSF models, including those that under- and over-estimate the true PSF, for the potential of enhanced quantitation of SUVs. The developed framework first analytically models the true PSF, considering a range of resolution degradation phenomena (including photon non-collinearity, inter-crystal penetration and scattering) as present in data acquisitions with modern commercial PET systems. In the context of oncologic liver FDG PET imaging, we generated 200 noisy datasets per image-set (with clinically realistic noise levels) using an XCAT anthropomorphic phantom with liver tumours of varying sizes. These were subsequently reconstructed using the OS-EM algorithm with varying PSF modelled kernels. We focused on quantitation of both SUV mean and SUV max , including assessment of contrast recovery coefficients, as well as noise-bias characteristics (including both image roughness and coefficient of-variability), for different tumours/iterations/PSF kernels. It was observed that overestimated PSF yielded more accurate contrast recovery for a range of tumours, and typically improved quantitative performance. For a clinically reasonable number of iterations, edge enhancement due to PSF modeling (especially due to over-estimated PSF) was in fact seen to lower SUV mean bias in small tumours. Overall, the results indicate that exactly matched PSF modeling does not offer optimized PET quantitation, and that PSF overestimation may provide enhanced SUV quantitation. Furthermore, generalized PSF modeling may provide a valuable approach for quantitative tasks such as treatment-response assessment and prognostication.

OARSI Clinical Trials Recommendations: Design and conduct of clinical trials of rehabilitation interventions for osteoarthritis.

PubMed

Fitzgerald, G K; Hinman, R S; Zeni, J; Risberg, M A; Snyder-Mackler, L; Bennell, K L

2015-05-01

A Task Force of the Osteoarthritis Research Society International (OARSI) has previously published a set of guidelines for the conduct of clinical trials in osteoarthritis (OA) of the hip and knee. Limited material available on clinical trials of rehabilitation in people with OA has prompted OARSI to establish a separate Task Force to elaborate guidelines encompassing special issues relating to rehabilitation of OA. The Task Force identified three main categories of rehabilitation clinical trials. The categories included non-operative rehabilitation trials, post-operative rehabilitation trials, and trials examining the effectiveness of devices (e.g., assistive devices, bracing, physical agents, electrical stimulation, etc.) that are used in rehabilitation of people with OA. In addition, the Task Force identified two main categories of outcomes in rehabilitation clinical trials, which include outcomes related to symptoms and function, and outcomes related to disease modification. The guidelines for rehabilitation clinical trials provided in this report encompass these main categories. The report provides guidelines for conducting and reporting on randomized clinical trials. The topics include considerations for entering patients into trials, issues related to conducting trials, considerations for selecting outcome measures, and recommendations for statistical analyses and reporting of results. The focus of the report is on rehabilitation trials for hip, knee and hand OA, however, we believe the content is broad enough that it could be applied to rehabilitation trials for other regions as well. Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Time Sharing Between Robotics and Process Control: Validating a Model of Attention Switching.

PubMed

Wickens, Christopher Dow; Gutzwiller, Robert S; Vieane, Alex; Clegg, Benjamin A; Sebok, Angelia; Janes, Jess

2016-03-01

The aim of this study was to validate the strategic task overload management (STOM) model that predicts task switching when concurrence is impossible. The STOM model predicts that in overload, tasks will be switched to, to the extent that they are attractive on task attributes of high priority, interest, and salience and low difficulty. But more-difficult tasks are less likely to be switched away from once they are being performed. In Experiment 1, participants performed four tasks of the Multi-Attribute Task Battery and provided task-switching data to inform the role of difficulty and priority. In Experiment 2, participants concurrently performed an environmental control task and a robotic arm simulation. Workload was varied by automation of arm movement and both the phases of environmental control and existence of decision support for fault management. Attention to the two tasks was measured using a head tracker. Experiment 1 revealed the lack of influence of task priority and confirmed the differing roles of task difficulty. In Experiment 2, the percentage attention allocation across the eight conditions was predicted by the STOM model when participants rated the four attributes. Model predictions were compared against empirical data and accounted for over 95% of variance in task allocation. More-difficult tasks were performed longer than easier tasks. Task priority does not influence allocation. The multiattribute decision model provided a good fit to the data. The STOM model is useful for predicting cognitive tunneling given that human-in-the-loop simulation is time-consuming and expensive. © 2016, Human Factors and Ergonomics Society.

Evolution of Novel 3D Culture Systems for Studies of Human Liver Function and Assessments of the Hepatotoxicity of Drugs and Drug Candidates.

PubMed

Andersson, Tommy B

2017-10-01

The pharmaceutical industry urgently needs reliable pre-clinical models to evaluate the efficacy and safety of new chemical entities before they enter the clinical trials. Development of in vitro model systems that emulate the functions of the human liver organ has been an elusive task. Cell lines exhibit a low drug-metabolizing capacity and primary liver cells rapidly dedifferentiate in culture, which restrict their usefulness substantially. Recently, the development of hepatocyte spheroid cultures has shown promising results. The proteome and transcriptome in the spheroids were similar to the liver tissue, and hepatotoxicity of selected substances was detected at in vivo-relevant concentrations. © 2017 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

Rapid-Response Impulsivity: Definitions, Measurement Issues, and Clinical Implications

PubMed Central

Hamilton, Kristen R.; Littlefield, Andrew K.; Anastasio, Noelle C.; Cunningham, Kathryn A.; Fink, Latham H.; Wing, Victoria C.; Mathias, Charles W.; Lane, Scott D.; Schutz, Christian; Swann, Alan C.; Lejuez, C.W.; Clark, Luke; Moeller, F. Gerard; Potenza, Marc N.

2015-01-01

Impulsivity is a multi-faceted construct that is a core feature of multiple psychiatric conditions and personality disorders. However, progress in understanding and treating impulsivity in the context of these conditions is limited by a lack of precision and consistency in its definition and assessment. Rapid-response-impulsivity (RRI) represents a tendency toward immediate action that occurs with diminished forethought and is out of context with the present demands of the environment. Experts from the International Society for Research on Impulsivity (InSRI) met to discuss and evaluate RRI-measures in terms of reliability, sensitivity, and validity with the goal of helping researchers and clinicians make informed decisions about the use and interpretation of findings from RRI-measures. Their recommendations are described in this manuscript. Commonly-used clinical and preclinical RRI-tasks are described, and considerations are provided to guide task selection. Tasks measuring two conceptually and neurobiologically distinct types of RRI, “refraining from action initiation” (RAI) and “stopping an ongoing action” (SOA) are described. RAI and SOA-tasks capture distinct aspects of RRI that may relate to distinct clinical outcomes. The InSRI group recommends that: 1) selection of RRI-measures should be informed by careful consideration of the strengths, limitations, and practical considerations of the available measures; 2) researchers use both RAI and SOA tasks in RRI studies to allow for direct comparison of RRI types and examination of their associations with clinically relevant measures; and, 3) similar considerations should be made for human and non-human studies in an effort to harmonize and integrate pre-clinical and clinical research. PMID:25867840

Final Report: Demographic Tools for Climate Change and Environmental Assessments

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Neill, Brian

2017-01-24

This report summarizes work over the course of a three-year project (2012-2015, with one year no-cost extension to 2016). The full proposal detailed six tasks: Task 1: Population projection model Task 2: Household model Task 3: Spatial population model Task 4: Integrated model development Task 5: Population projections for Shared Socio-economic Pathways (SSPs) Task 6: Population exposure to climate extremes We report on all six tasks, provide details on papers that have appeared or been submitted as a result of this project, and list selected key presentations that have been made within the university community and at professional meetings.

Real-time tracking and virtual endoscopy in cone-beam CT-guided surgery of the sinuses and skull base in a cadaver model.

PubMed

Prisman, Eitan; Daly, Michael J; Chan, Harley; Siewerdsen, Jeffrey H; Vescan, Allan; Irish, Jonathan C

2011-01-01

Custom software was developed to integrate intraoperative cone-beam computed tomography (CBCT) images with endoscopic video for surgical navigation and guidance. A cadaveric head was used to assess the accuracy and potential clinical utility of the following functionality: (1) real-time tracking of the endoscope in intraoperative 3-dimensional (3D) CBCT; (2) projecting an orthogonal reconstructed CBCT image, at or beyond the endoscope, which is parallel to the tip of the endoscope corresponding to the surgical plane; (3) virtual reality fusion of endoscopic video and 3D CBCT surface rendering; and (4) overlay of preoperatively defined contours of anatomical structures of interest. Anatomical landmarks were contoured in CBCT of a cadaveric head. An experienced endoscopic surgeon was oriented to the software and asked to rate the utility of the navigation software in carrying out predefined surgical tasks. Utility was evaluated using a rating scale for: (1) safely completing the task; and (2) potential for surgical training. Surgical tasks included: (1) uncinectomy; (2) ethmoidectomy; (3) sphenoidectomy/pituitary resection; and (4) clival resection. CBCT images were updated following each ablative task. As a teaching tool, the software was evaluated as "very useful" for all surgical tasks. Regarding safety and task completion, the software was evaluated as "no advantage" for task (1), "minimal" for task (2), and "very useful" for tasks (3) and (4). Landmark identification for structures behind bone was "very useful" for both categories. The software increased surgical confidence in safely completing challenging ablative tasks by presenting real-time image guidance for highly complex ablative procedures. In addition, such technology offers a valuable teaching aid to surgeons in training. Copyright © 2011 American Rhinologic Society-American Academy of Otolaryngic Allergy, LLC.

Agent-based modeling of the interaction between CD8+ T cells and Beta cells in type 1 diabetes.

PubMed

Ozturk, Mustafa Cagdas; Xu, Qian; Cinar, Ali

2018-01-01

We propose an agent-based model for the simulation of the autoimmune response in T1D. The model incorporates cell behavior from various rules derived from the current literature and is implemented on a high-performance computing system, which enables the simulation of a significant portion of the islets in the mouse pancreas. Simulation results indicate that the model is able to capture the trends that emerge during the progression of the autoimmunity. The multi-scale nature of the model enables definition of rules or equations that govern cellular or sub-cellular level phenomena and observation of the outcomes at the tissue scale. It is expected that such a model would facilitate in vivo clinical studies through rapid testing of hypotheses and planning of future experiments by providing insight into disease progression at different scales, some of which may not be obtained easily in clinical studies. Furthermore, the modular structure of the model simplifies tasks such as the addition of new cell types, and the definition or modification of different behaviors of the environment and the cells with ease.

The Montana State University Conceptual Model of Complementary and Alternative Medicine Health Literacy

PubMed Central

Shreffler-Grant, Jean; Nichols, Elizabeth; Weinert, Clarann; Ide, Bette

2016-01-01

This article aims to present and describe a model of complementary and alternative medicine (CAM) health literacy. The model is the conceptual basis for CAM health literacy, which is operationally defined as the information about CAM needed to make informed self-management decisions regarding health. Improving health literacy is a national priority, and widespread use of CAM has added to the complexity of this task. There are no currently available models or measures of health literacy regarding CAM. The authors developed the model using an iterative process of deriving concepts, constructs, and empirical indicators from the literature and the author’s prior work, review and critique by experts, and revision. The model of CAM health literacy can serve as the basis for future research on the use and efficacy of CAM and the constructs and concepts within it can be used to identify points of intervention for research or for clinical practice. It is anticipated that the model will have scientific and clinical application for assessing health literacy in other self care decision-making situations. PMID:23889542

The Montana State University conceptual model of complementary and alternative medicine health literacy.

PubMed

Shreffler-Grant, Jean; Nichols, Elizabeth; Weinert, Clarann; Ide, Bette

2013-01-01

This article aims to present and describe a model of complementary and alternative medicine (CAM) health literacy. The model is the conceptual basis for CAM health literacy, which is operationally defined as the information about CAM needed to make informed self-management decisions regarding health. Improving health literacy is a national priority, and widespread use of CAM has added to the complexity of this task. There are no currently available models or measures of health literacy regarding CAM. The authors developed the model using an iterative process of deriving concepts, constructs, and empirical indicators from the literature and the author's prior work, review and critique by experts, and revision. The model of CAM health literacy can serve as the basis for future research on the use and efficacy of CAM and the constructs and concepts within it can be used to identify points of intervention for research or for clinical practice. It is anticipated that the model will have scientific and clinical application for assessing health literacy in other self care decision-making situations.

Individual differences in emotionality and peri-traumatic processing.

PubMed

Logan, Shanna; O'Kearney, Richard

2012-06-01

Recent cognitive models propose that intrusive trauma memories arise and persist because high levels of emotional arousal triggered by the trauma disrupt conceptual processing of elements of the event, while enhancing sensory/perceptual processing. A trauma film analogue design was used to investigate if the predicted facilitating effects on intrusions from inhibiting conceptual processing and predicted attenuating effects on intrusions from inhibiting sensory processing are moderated by individual differences in emotionality. One hundred and five non-clinical participants viewed a traumatic film while undertaking a conceptual interference task, a sensory interference task, or no interference task. Participants recorded the frequency and intensity of intrusions over the following week. There was no facilitating effect for the conceptual interference task compared to no interference task. A significant attenuation of the frequency of intrusions was evident for those undertaking sensory interference (ŋ(2) = .04). This effect, however, was only present for those with high trait anxiety (d = .82) and not for those with low trait anxiety (d = .08). Relative to high trait anxious controls, high anxious participants who undertook sensory interference also reported lower intensity of intrusions (d = .66). This is the first trauma film analogue study to show that the attenuating effect of concurrent sensory/perceptual processing on the frequency and intensity of subsequent intrusions is evident only for people with high trait anxiety. The results have implications for conceptual models of intrusion development and for their application to the prevention of post traumatic distress. Copyright © 2011 Elsevier Ltd. All rights reserved.

An investigation of a novel transdiagnostic model of delusions in a group with positive schizotypal symptoms.

PubMed

Cameron, Clare; Kaplan, Ryan A; Rossell, Susan L

2014-01-01

Although several theories of delusions have been put forward, most do not offer a comprehensive diagnosis-independent explanation of delusion aetiology. This study used a non-clinical sample to provide empirical support for a novel transdiagnostic model of delusions that implicates aberrant semantic memory and emotion perception processes as key factors in delusion formation and maintenance. It was hypothesised that among a non-clinical sample, people high in schizotypy would demonstrate differences in semantic memory and emotion perception, relative to people low in schizotypy. Using the Cognitive Disorganisation subscale of the Oxford-Liverpool Inventory of Feelings and Experiences, 41 healthy participants were separated into high and low schizotypy groups and completed facial emotion perception and semantic priming tasks. As expected, participants in the high schizotypy group demonstrated different performance on the semantic priming task and reduced facial affect accuracy for the emotion anger, and reaction time differences to fearful faces. These findings suggest that such processes may be involved in the development of the sorts of unusual beliefs which underlie delusions. Investigation of how emotion perception and semantic memory may interrelate in the aetiology of delusions would be of value in furthering our understanding of their role in delusion formation.

Developing non-technical ward-round skills.

PubMed

Harvey, Rachel; Mellanby, Edward; Dearden, Effie; Medjoub, Karima; Edgar, Simon

2015-10-01

Conducting clinical 'rounds' is one of the most onerous and important duties that every junior doctor is expected to perform. There is evidence that newly qualified doctors are not adequately prepared by their undergraduate experiences for this task. The aim of this study was to analyse the challenges pertaining to non-technical skills that students would face during ward rounds, and to create a model that facilitates the transition from medical student to doctor. A total of 217 final-year medical students completed a simulated ward round. Free-text responses were analysed using template analysis applying an a priori template developed from the literature by the research team. This drew on the generic categories of non-technical skills suggested by Flin et al. Ninety-seven per cent of students agreed or strongly agreed that the simulated ward round improved their insight into the challenges of ward rounds and their perceived ability to work efficiently as an active member of the ward round. The responding students (206) submitted written feedback describing the learning that they planned to use: 800 learning points were recorded, and all could be categorised into one of seven non-technical skills. Conducting clinical 'rounds' is one of the most onerous and important duties that every junior doctor is expected to perform We believe that improved task efficiency and insight into the challenges of the ward round gained by medical students will lead to an enhancement in performance during clinical rounds, and will have a positive impact on patient safety. We would suggest that undergraduate medical schools consider this model in the preparation for the clinical practice element of the curriculum. © 2015 John Wiley & Sons Ltd.

Model Minority Stereotype: Influence on Perceived Mental Health Needs of Asian Americans.

PubMed

Cheng, Alice W; Chang, Janet; O'Brien, Janine; Budgazad, Marc S; Tsai, Jack

2017-06-01

This study examined the influence of the model minority stereotype on the perceived mental health functioning of Asian Americans. It was hypothesized that college students would perceive Asian Americans as having fewer mental health problems and clinical symptoms than Whites due to the model minority stereotype. Four hundred and twenty-five undergraduate students from a predominately White college campus in the American northeast were randomly exposed to one of four conditions: (1) a clinical vignette describing a White college student suffering from adjustment disorder; (2) the same vignette describing an Asian American college student; (3) a newspaper article describing a success story of Whites and the White clinical vignette; (4) the same newspaper article and clinical vignette describing an Asian American. Following exposure to one of the conditions, participants completed a memory recall task and measures of colorblindness, attitudes towards Asian Americans, attitudes towards out-group members, and perceived mental health functioning. Participants exposed to the vignettes primed with the positive/model minority stereotype perceived the target regardless of race/ethnicity as having better mental health functioning and less clinical symptoms than the condition without the stereotype. Additionally, the stereotype primer was found to be a modest predictor for the perception of mental health functioning in Asian American vignettes. Results shed light on the impact of the model minority stereotype on the misperception of Asian Americans' mental health status, contributing to the invisibility or neglect of this minority group's mental health needs.

Describing and Modeling Workflow and Information Flow in Chronic Disease Care

PubMed Central

Unertl, Kim M.; Weinger, Matthew B.; Johnson, Kevin B.; Lorenzi, Nancy M.

2009-01-01

Objectives The goal of the study was to develop an in-depth understanding of work practices, workflow, and information flow in chronic disease care, to facilitate development of context-appropriate informatics tools. Design The study was conducted over a 10-month period in three ambulatory clinics providing chronic disease care. The authors iteratively collected data using direct observation and semi-structured interviews. Measurements The authors observed all aspects of care in three different chronic disease clinics for over 150 hours, including 157 patient-provider interactions. Observation focused on interactions among people, processes, and technology. Observation data were analyzed through an open coding approach. The authors then developed models of workflow and information flow using Hierarchical Task Analysis and Soft Systems Methodology. The authors also conducted nine semi-structured interviews to confirm and refine the models. Results The study had three primary outcomes: models of workflow for each clinic, models of information flow for each clinic, and an in-depth description of work practices and the role of health information technology (HIT) in the clinics. The authors identified gaps between the existing HIT functionality and the needs of chronic disease providers. Conclusions In response to the analysis of workflow and information flow, the authors developed ten guidelines for design of HIT to support chronic disease care, including recommendations to pursue modular approaches to design that would support disease-specific needs. The study demonstrates the importance of evaluating workflow and information flow in HIT design and implementation. PMID:19717802

The incorporation of focused history in checklist for early recognition and treatment of acute illness and injury.

PubMed

Jayaprakash, Namita; Ali, Rashid; Kashyap, Rahul; Bennett, Courtney; Kogan, Alexander; Gajic, Ognjen

2016-08-31

Diagnostic error and delay are critical impediments to the safety of critically ill patients. Checklist for early recognition and treatment of acute illness and injury (CERTAIN) has been developed as a tool that facilitates timely and error-free evaluation of critically ill patients. While the focused history is an essential part of the CERTAIN framework, it is not clear how best to choreograph this step in the process of evaluation and treatment of the acutely decompensating patient. An un-blinded crossover clinical simulation study was designed in which volunteer critical care clinicians (fellows and attendings) were randomly assigned to start with either obtaining a focused history choreographed in series (after) or in parallel to the primary survey. A focused history was obtained using the standardized SAMPLE model that is incorporated into American College of Trauma Life Support (ATLS) and Pediatric Advanced Life Support (PALS). Clinicians were asked to assess six acutely decompensating patients using pre - determined clinical scenarios (three in series choreography, three in parallel). Once the initial choreography was completed the clinician would crossover to the alternative choreography. The primary outcome was the cognitive burden assessed through the NASA task load index. Secondary outcome was time to completion of a focused history. A total of 84 simulated cases (42 in parallel, 42 in series) were tested on 14 clinicians. Both the overall cognitive load and time to completion improved with each successive practice scenario, however no difference was observed between the series versus parallel choreographies. The median (IQR) overall NASA TLX task load index for series was 39 (17 - 58) and for parallel 43 (27 - 52), p = 0.57. The median (IQR) time to completion of the tasks in series was 125 (112 - 158) seconds and in parallel 122 (108 - 158) seconds, p = 0.92. In this clinical simulation study assessing the incorporation of a focused history into the primary survey of a non-trauma critically ill patient, there was no difference in cognitive burden or time to task completion when using series choreography (after the exam) compared to parallel choreography (concurrent with the primary survey physical exam). However, with repetition of the task both overall task load and time to completion improved in each of the choreographies.

Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial

PubMed Central

2013-01-01

Background Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD. Methods/Design The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n = 102), test the findings in the second half, and then extend the analyses to the total sample. Trial registration International Study to Predict Optimized Treatment - in Depression (iSPOT-D). ClinicalTrials.gov, NCT00693849. PMID:23866851

Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial.

PubMed

Grieve, Stuart M; Korgaonkar, Mayuresh S; Etkin, Amit; Harris, Anthony; Koslow, Stephen H; Wisniewski, Stephen; Schatzberg, Alan F; Nemeroff, Charles B; Gordon, Evian; Williams, Leanne M

2013-07-18

Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD. The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n=102), test the findings in the second half, and then extend the analyses to the total sample. International Study to Predict Optimized Treatment--in Depression (iSPOT-D). ClinicalTrials.gov, NCT00693849.

The Dot Pattern Expectancy Task: Reliability and Replication of Deficits in Schizophrenia

ERIC Educational Resources Information Center

Jones, Jessica A. H.; Sponheim, Scott R.; MacDonald, Angus W., III

2010-01-01

The dot pattern expectancy (DPX) task was created to efficiently assess context-processing deficits in patients with schizophrenia. Three studies investigated the characteristics of the DPX relevant for clinical applications. To answer questions regarding the psychometric properties of the task, performance on this task was studied in 2 healthy…

The effect of student self-video of performance on clinical skill competency: a randomised controlled trial.

PubMed

Maloney, Stephen; Storr, Michael; Morgan, Prue; Ilic, Dragan

2013-03-01

Emerging technologies and student information technology literacy are enabling new methods of teaching and learning for clinical skill performance. Facilitating experiential practice and reflection on performance through student self-video, and exposure to peer benchmarks, may promote greater levels of skill competency. This study examines the impact of student self-video on the attainment of clinical skills. A total of 60 Physiotherapy students (100%) consented to participate in the randomised controlled trial. One group (50%) was taught a complex clinical skill with regular practical tutoring, whilst the other group (50%) supplemented the tutoring with a self-video task aimed at promoting reflection on performance. Student skill performance was measured in an objective structured clinical examination (OSCE). Students also completed an anonymous questionnaire, which explored their perception of their learning experiences. Students received significantly higher scores in the OSCE when the examined clinical skill had been supplemented with a self-video of performance task (P = 0.048). Descriptive analysis of the questionnaires relating to student perceptions on the teaching methods identified that the self-video of performance task utilised contributed to improvement in their clinical performance and their confidence for future clinical practice. Students identified a number of aspects of the submission process that contributed to this perception of educational value. The novel results of this study demonstrate that greater clinical skill competency is achieved when traditional tutoring methods are supplemented with student self-video of performance tasks. Additional benefits included the ability of staff and students to monitor longitudinal performance, and an increase in feedback opportunities.

Evaluation of uncertainty in the adjustment of fundamental constants

NASA Astrophysics Data System (ADS)

Bodnar, Olha; Elster, Clemens; Fischer, Joachim; Possolo, Antonio; Toman, Blaza

2016-02-01

Combining multiple measurement results for the same quantity is an important task in metrology and in many other areas. Examples include the determination of fundamental constants, the calculation of reference values in interlaboratory comparisons, or the meta-analysis of clinical studies. However, neither the GUM nor its supplements give any guidance for this task. Various approaches are applied such as weighted least-squares in conjunction with the Birge ratio or random effects models. While the former approach, which is based on a location-scale model, is particularly popular in metrology, the latter represents a standard tool used in statistics for meta-analysis. We investigate the reliability and robustness of the location-scale model and the random effects model with particular focus on resulting coverage or credible intervals. The interval estimates are obtained by adopting a Bayesian point of view in conjunction with a non-informative prior that is determined by a currently favored principle for selecting non-informative priors. Both approaches are compared by applying them to simulated data as well as to data for the Planck constant and the Newtonian constant of gravitation. Our results suggest that the proposed Bayesian inference based on the random effects model is more reliable and less sensitive to model misspecifications than the approach based on the location-scale model.

Reestablishing Clinical Psychology's Subjective Core

ERIC Educational Resources Information Center

Hunsberger, Peter Hume

2007-01-01

Comments on the report by the APA Presidential Task Force on Evidence-Based Practice (see record 2006-05893-001) entitled Evidence-based practice in psychology. The Task Force is to be commended for their report valuing evidence from "clinical expertise" on a par with "research data" (p. 272) in guiding psychological practices. The current author…

Sentence Repetition: What Does the Task Measure?

ERIC Educational Resources Information Center

Polišenská, Kamila; Chiat, Shula; Roy, Penny

2015-01-01

Background: Sentence repetition is gaining increasing attention as a source of information about children's sentence-level abilities in clinical assessment, and as a clinical marker of specific language impairment. However, it is widely debated what the task is testing and therefore how informative it is. Aims: (1) To evaluate the effects of…

Using Nonword Repetition Tasks for the Identification of Language Impairment in Spanish-English Speaking Children: Does the Language of Assessment Matter?

PubMed Central

Gutiérrez-Clellen, Vera F.; Simon-Cereijido, Gabriela

2012-01-01

The purpose of this study was twofold: (a) to evaluate the clinical utility of a verbal working memory measure, specifically, a nonword repetition task, with a sample of Spanish-English bilingual children and (b) to determine the extent to which individual differences in relative language skills and language use had an effect on the clinical differentiation of these children by the measures. A total of 144 Latino children (95 children with typical language development and 49 children with language impairment) were tested using nonword lists developed for each language. The results show that the clinical accuracy of nonword repetition tasks varies depending on the language(s) tested. Test performance appeared related to individual differences in language use and exposure. The findings do not support a monolingual approach to the assessment of bilingual children with nonword repetition tasks, even if children appear fluent speakers in the language of testing. Nonword repetition may assist in the screening of Latino children if used bilingually and in combination with other clinical measures. PMID:22707854

Lessons learned from a pharmacy practice model change at an academic medical center.

PubMed

Knoer, Scott J; Pastor, John D; Phelps, Pamela K

2010-11-01

The development and implementation of a new pharmacy practice model at an academic medical center are described. Before the model change, decentralized pharmacists responsible for order entry and verification and clinical specialists were both present on the care units. Staff pharmacists were responsible for medication distribution and sterile product preparation. The decentralized pharmacists handling orders were not able to use their clinical training, the practice model was inefficient, and few clinical services were available during evenings and weekends. A task force representing all pharmacy department roles developed a process and guiding principles for the model change, collected data, and decided on a model. Teams consisting of decentralized pharmacists, decentralized pharmacy technicians, and team leaders now work together to meet patients' pharmacy needs and further departmental safety, quality, and cost-saving goals. Decentralized service hours have been expanded through operational efficiencies, including use of automation (e.g., computerized provider order entry, wireless computers on wheels used during rounds with physician teams). Nine clinical specialist positions were replaced by five team leader positions and four pharmacists functioning in decentralized roles. Additional staff pharmacist positions were shifted into decentralized roles, and the hospital was divided into areas served by teams including five to eight pharmacists. Technicians are directly responsible for medication distribution. No individual's job was eliminated. The new practice model allowed better alignment of staff with departmental goals, expanded pharmacy hours and services, more efficient medication distribution, improved employee engagement, and a staff succession plan.

Task Equivalence for Model and Human-Observer Comparisons in SPECT Localization Studies

NASA Astrophysics Data System (ADS)

Sen, Anando; Kalantari, Faraz; Gifford, Howard C.

2016-06-01

While mathematical model observers are intended for efficient assessment of medical imaging systems, their findings should be relevant for human observers as the primary clinical end users. We have investigated whether pursuing equivalence between the model and human-observer tasks can help ensure this goal. A localization receiver operating characteristic (LROC) study tested prostate lesion detection in simulated In-111 SPECT imaging with anthropomorphic phantoms. The test images were 2D slices extracted from reconstructed volumes. The iterative ordered sets expectation-maximization (OSEM) reconstruction algorithm was used with Gaussian postsmoothing. Variations in the number of iterations and the level of postfiltering defined the test strategies in the study. Human-observer performance was compared with that of a visual-search (VS) observer, a scanning channelized Hotelling observer, and a scanning channelized nonprewhitening (CNPW) observer. These model observers were applied with precise information about the target regions of interest (ROIs). ROI knowledge was a study variable for the human observers. In one study format, the humans read the SPECT image alone. With a dual-modality format, the SPECT image was presented alongside an anatomical image slice extracted from the density map of the phantom. Performance was scored by area under the LROC curve. The human observers performed significantly better with the dual-modality format, and correlation with the model observers was also improved. Given the human-observer data from the SPECT study format, the Pearson correlation coefficients for the model observers were 0.58 (VS), -0.12 (CH), and -0.23 (CNPW). The respective coefficients based on the human-observer data from the dual-modality study were 0.72, 0.27, and -0.11. These results point towards the continued development of the VS observer for enhancing task equivalence in model-observer studies.

An investigation of the development of the topological spatial structures in elementary school students

NASA Astrophysics Data System (ADS)

Everett, Susan Ann

1999-09-01

In this study the relationships among the topological spatial structures were examined in students in kindergarten, second, and fourth grades. These topological spatial structures are part of the three major types of spatial thinking: topological, projective, and Euclidean (as defined by Jean Piaget and associates). According to Piaget's model of spatial thinking, the spatial structures enable humans to think about spatial relationships at a conceptual or representational level rather than only at a simpler, perceptual level. The clinical interview technique was used to interact individually with 72 children to assess the presence of each of the different topological spatial structures. This was accomplished through the use of seven task protocols and simple objects which are familiar to young children. These task protocols allowed the investigator to interact with each child in a consistent manner. The results showed that most of the children in this study (97.2%) had not developed all of the topological spatial structures. The task scores, were analyzed using non-parametric statistical tests due to the ordinal nature of the data. From the data the following results were obtained: (1) the spatial structures did not develop in random order based on the task scores but developed in the sequence expected from Piaget's model, (2) task performance improved with grade level with fourth grade students outperforming second graders and kindergartners on each of the seven tasks, and (3) no significant differences on task performance due to gender were found. Based on these results, young elementary children are beginning to develop topological spatial thinking. This is critical since it provides the foundation for the other types of spatial thinking, projective and Euclidean. Since spatial thinking is not a "gift" but can be developed, educators need to provide more opportunities for students to increase their level of spatial thinking since it is necessary for conceptual understanding of many different topics in math and science.

Task-related fMRI in hemiplegic cerebral palsy-A systematic review.

PubMed

Gaberova, Katerina; Pacheva, Iliyana; Ivanov, Ivan

2018-04-27

Functional magnetic resonance imaging (fMRI) is used widely to study reorganization after early brain injuries. Unilateral cerebral palsy (UCP) is an appealing model for studying brain plasticity by fMRI. To summarize the results of task-related fMRI studies in UCP in order to get better understanding of the mechanism of neuroplasticity of the developing brain and its reorganization potential and better translation of this knowledge to clinical practice. A systematic search was conducted on the PubMed database by keywords: "cerebral palsy", "congenital hemiparesis", "unilateral", "Magnetic resonance imaging" , "fMRI", "reorganization", and "plasticity" The exclusion criteria were as follows: case reports; reviews; studies exploring non-UCP patients; and studies with results of rehabilitation. We found 7 articles investigated sensory tasks; 9 studies-motor tasks; 12 studies-speech tasks. Ipsilesional reorganization is dominant in sensory tasks (in 74/77 patients), contralesional-in only 3/77. In motor tasks, bilateral activation is found in 64/83, only contralesional-in 11/83, and only ipsilesional-8/83. Speech perception is bilateral in 35/51, only or dominantly ipsilesional (left-sided) in 8/51, and dominantly contralesional (right-sided) in 8/51. Speech production is only or dominantly contralesional (right-sided) in 88/130, bilateral-26/130, and only or dominantly ipsilesional (left-sided)-in 16/130. The sensory system is the most "rigid" to reorganization probably due to absence of ipsilateral (contralesional) primary somatosensory representation. The motor system is more "flexible" due to ipsilateral (contralesional) motor pathways. The speech perception and production show greater flexibility resulting in more bilateral or contralateral activation. The models of reorganization are variable, depending on the development and function of each neural system and the extent and timing of the damage. The plasticity patterns may guide therapeutic intervention and prognostics, thus proving the fruitiness of the translational approach in neurosciences. © 2018 John Wiley & Sons, Ltd.

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

PubMed

Fedorov, Andriy; Clunie, David; Ulrich, Ethan; Bauer, Christian; Wahle, Andreas; Brown, Bartley; Onken, Michael; Riesmeier, Jörg; Pieper, Steve; Kikinis, Ron; Buatti, John; Beichel, Reinhard R

2016-01-01

Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM(®)) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.

Mapping to Estimate Health-State Utility from Non-Preference-Based Outcome Measures: An ISPOR Good Practices for Outcomes Research Task Force Report.

PubMed

Wailoo, Allan J; Hernandez-Alava, Monica; Manca, Andrea; Mejia, Aurelio; Ray, Joshua; Crawford, Bruce; Botteman, Marc; Busschbach, Jan

2017-01-01

Economic evaluation conducted in terms of cost per quality-adjusted life-year (QALY) provides information that decision makers find useful in many parts of the world. Ideally, clinical studies designed to assess the effectiveness of health technologies would include outcome measures that are directly linked to health utility to calculate QALYs. Often this does not happen, and even when it does, clinical studies may be insufficient for a cost-utility assessment. Mapping can solve this problem. It uses an additional data set to estimate the relationship between outcomes measured in clinical studies and health utility. This bridges the evidence gap between available evidence on the effect of a health technology in one metric and the requirement for decision makers to express it in a different one (QALYs). In 2014, ISPOR established a Good Practices for Outcome Research Task Force for mapping studies. This task force report provides recommendations to analysts undertaking mapping studies, those that use the results in cost-utility analysis, and those that need to critically review such studies. The recommendations cover all areas of mapping practice: the selection of data sets for the mapping estimation, model selection and performance assessment, reporting standards, and the use of results including the appropriate reflection of variability and uncertainty. This report is unique because it takes an international perspective, is comprehensive in its coverage of the aspects of mapping practice, and reflects the current state of the art. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Estimating Health-State Utility for Economic Models in Clinical Studies: An ISPOR Good Research Practices Task Force Report.

PubMed

Wolowacz, Sorrel E; Briggs, Andrew; Belozeroff, Vasily; Clarke, Philip; Doward, Lynda; Goeree, Ron; Lloyd, Andrew; Norman, Richard

Cost-utility models are increasingly used in many countries to establish whether the cost of a new intervention can be justified in terms of health benefits. Health-state utility (HSU) estimates (the preference for a given state of health on a cardinal scale where 0 represents dead and 1 represents full health) are typically among the most important and uncertain data inputs in cost-utility models. Clinical trials represent an important opportunity for the collection of health-utility data. However, trials designed primarily to evaluate efficacy and safety often present challenges to the optimal collection of HSU estimates for economic models. Careful planning is needed to determine which of the HSU estimates may be measured in planned trials; to establish the optimal methodology; and to plan any additional studies needed. This report aimed to provide a framework for researchers to plan the collection of health-utility data in clinical studies to provide high-quality HSU estimates for economic modeling. Recommendations are made for early planning of health-utility data collection within a research and development program; design of health-utility data collection during protocol development for a planned clinical trial; design of prospective and cross-sectional observational studies and alternative study types; and statistical analyses and reporting. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

The safer clinical systems project in renal care.

PubMed

Weale, Andy R

2013-09-01

Current systems in place in healthcare are designed to detect harm after it has happened (e.g critical incident reports) and make recommendations based on an assessment of that event. Safer Clinical Systems, a Health Foundation funded project, is designed to proactively search for risk within systems, rather than being reactive to harm. The aim of the Safer Clinical Systems project in Renal Care was to reduce the risks associated with shared care for patients who are undergoing surgery but are looked after peri-operatively by nephrology teams on nephrology wards. This report details our findings of the diagnostic phase of Safer Clinical Systems: the proactive search for risk. We have evaluated the current system of care using a set of risk evaluation and process mapping tools (Failure Modes and Effects Analysis (FMEA) and Hierarchical Task Analysis HTA). We have engaged staff with the process mapping and risk assessment tools. We now understand our system and understand where the highest risk tasks are undertaken during a renal in-patient stay during which a patient has an operation. These key tasks occur across the perioperaive period and are not confined to one aspect of care. A measurement strategy and intervention plan have been designed around these tasks. Safer Clinical Systems has identified high risk, low reliability tasks in our system. We look forward to fully reporting these data in 2014. © 2013 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Task-Driven Comparison of Topic Models.

PubMed

Alexander, Eric; Gleicher, Michael

2016-01-01

Topic modeling, a method of statistically extracting thematic content from a large collection of texts, is used for a wide variety of tasks within text analysis. Though there are a growing number of tools and techniques for exploring single models, comparisons between models are generally reduced to a small set of numerical metrics. These metrics may or may not reflect a model's performance on the analyst's intended task, and can therefore be insufficient to diagnose what causes differences between models. In this paper, we explore task-centric topic model comparison, considering how we can both provide detail for a more nuanced understanding of differences and address the wealth of tasks for which topic models are used. We derive comparison tasks from single-model uses of topic models, which predominantly fall into the categories of understanding topics, understanding similarity, and understanding change. Finally, we provide several visualization techniques that facilitate these tasks, including buddy plots, which combine color and position encodings to allow analysts to readily view changes in document similarity.

Differences in day and night shift clinical performance in anesthesiology.

PubMed

Cao, Caroline G L; Weinger, Matthew B; Slagle, Jason; Zhou, Chuan; Ou, Jennie; Gillin, Shakha; Sheh, Bryant; Mazzei, William

2008-04-01

This study examined whether anesthesia residents (physicians in training) performed clinical duties in the operating room differently during the day versus at night. Fatigue from sleep deprivation and working through the night is common for physicians, particularly during residency training. Using a repeated-measures design, we studied 13 pairs of day-night matched anesthesia cases. Dependent measures included task times, workload ratings, response to an alarm light latency task, and mood. Residents spent significantly less time on manual tasks and more time on monitoring tasks during the maintenance phase at night than during the day. Residents reported more negative mood at night than during the day, both pre- and postoperation. However, time of day had no effect on the mood change between pre- and postoperation. Workload ratings and the response time to an alarm light latency task were not significantly different between night and day cases. Because night shift residents had been awake and working for more than 16 hr, the observed differences in task performance and mood may be attributed to fatigue. The changes in task distribution during night shift work may represent compensatory strategies to maintain patient care quality while keeping perceived workload at a manageable level. Fatigue effects during night shifts should be considered when designing work-rest schedules for clinicians. This matched-case control scheme can also be applied to study other phenomena associated with patient safety in the actual clinical environment.

Perceptual Measurement in Schizophrenia: Promising Electrophysiology and Neuroimaging Paradigms From CNTRICS

PubMed Central

Butler, Pamela D.; Chen, Yue; Ford, Judith M.; Geyer, Mark A.; Silverstein, Steven M.; Green, Michael F.

2012-01-01

The sixth meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) focused on selecting promising imaging paradigms for each of the cognitive constructs selected in the first CNTRICS meeting. In the domain of perception, the 2 constructs of interest were “gain control” and “visual integration.” CNTRICS received 6 task nominations for imaging paradigms for gain control and 3 task nominations for integration. The breakout group for perception evaluated the degree to which each of these tasks met prespecified criteria. For gain control, the breakout group believed that one task (mismatch negativity) was already mature and was being incorporated into multisite clinical trials. The breakout group recommended that 1 visual task (steady-state visual evoked potentials to magnocellular- vs parvocellular-biased stimuli) and 2 auditory measures (an event-related potential (ERP) measure of corollary discharge and a functional magnetic resonance imaging (fMRI) version of prepulse inhibition of startle) be adapted for use in clinical trials in schizophrenia research. For visual integration, the breakout group recommended that fMRI and ERP versions of a contour integration test and an fMRI version of a coherent motion test be adapted for use in clinical trials. This manuscript describes the ways in which each of these tasks met the criteria used in the breakout group to evaluate and recommend tasks for further development. PMID:21890745

[Features of dual--postural and calculation--task performance in patients with consequences of traumatic brain injury].

PubMed

Zharikova, A V; Zhavoronkova, L A; Maksakova, O A; Kuptsova, S V

2012-01-01

Dual tasks with voluntary postural control and calculation have been done by 14 patients (25.7 +/- 4.7 yo.) after traumatic brain injury and 40 healthy volunteers (29.8 +/- 2.5 y.o.). Complex clinical (MMSE, FIM, MPAI-3 and Berg scales) and stabilographic evaluation has been performed. According to clinical evaluation 8 patients were included into group 1 with less severe functional deficit and 6 patients formed group 2 with more severe deficit. Parameters of motor and especially cognitive sub-tasks in patients were lower than in healthy subjects in both separate and dual tasks. In group 2 these parameters were lower than in group 1. Certain types of dual task where the quality of sub-tasks, especially of the motor-one increased in healthy subjects and patients of the first group were revealed. The complex of stabilographic parameters which could be used for estimation of quality of sub-tasks performance has been revealed. Dual tasks could be an additional method of evaluation of patients' adaptive possibilities and certain type of dual task could become a promising approach to recovery at late period of rehabilitation.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

Efficiency achievements from a user-developed real-time modifiable clinical information system.

PubMed

Bishop, Roderick O; Patrick, Jon; Besiso, Ali

2015-02-01

This investigation was initiated after the introduction of a new information system into the Nepean Hospital Emergency Department. A retrospective study determined that the problems introduced by the new system led to reduced efficiency of the clinical staff, demonstrated by deterioration in the emergency department's (ED's) performance. This article is an investigation of methods to improve the design and implementation of clinical information systems for an ED by using a process of clinical team-led design and a technology built on a radically new philosophy denoted as emergent clinical information systems. The specific objectives were to construct a system, the Nepean Emergency Department Information Management System (NEDIMS), using a combination of new design methods; determine whether it provided any reduction in time and click burden on the user in comparison to an enterprise proprietary system, Cerner FirstNet; and design and evaluate a model of the effect that any reduction had on patient throughput in the department. The methodology for conducting a direct comparison between the 2 systems used the 6 activity centers in the ED of clerking, triage, nursing assessments, fast track, acute care, and nurse unit manager. A quantitative study involved the 2 systems being measured for their efficiency on 17 tasks taken from the activity centers. A total of 332 task instances were measured for duration and number of mouse clicks in live usage on Cerner FirstNet and in reproduction of the same Cerner FirstNet work on NEDIMS as an off-line system. The results showed that NEDIMS is at least 41% more efficient than Cerner FirstNet (95% confidence interval 21.6% to 59.8%). In some cases, the NEDIMS tasks were remodeled to demonstrate the value of feedback to create improvements and the speed and economy of design revision in the emergent clinical information systems approach. The cost of the effort in remodeling the designs showed that the time spent on remodeling is recovered within a few days in time savings to clinicians. An analysis of the differences between Cerner FirstNet and NEDIMS for sequences of patient journeys showed an average difference of 127 seconds and 15.2 clicks. A simulation model of workflows for typical patient journeys for a normal daily attendance of 165 patients showed that NEDIMS saved 23.9 hours of staff time per day compared with Cerner FirstNet. The results of this investigation show that information systems that are designed by a clinical team using a technology that enables real-time adaptation provides much greater efficiency for the ED. Staff consider that a point-and-click user interface constantly interrupts their train of thought in a way that does not happen when writing on paper. This is partially overcome by the reduction of cognitive load that arises from minimizing the number of clicks to complete a task in the context of global versus local workflow optimization. Copyright © 2014 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Rasch analysis on OSCE data : An illustrative example.

PubMed

Tor, E; Steketee, C

2011-01-01

The Objective Structured Clinical Examination (OSCE) is a widely used tool for the assessment of clinical competence in health professional education. The goal of the OSCE is to make reproducible decisions on pass/fail status as well as students' levels of clinical competence according to their demonstrated abilities based on the scores. This paper explores the use of the polytomous Rasch model in evaluating the psychometric properties of OSCE scores through a case study. The authors analysed an OSCE data set (comprised of 11 stations) for 80 fourth year medical students based on the polytomous Rasch model in an effort to answer two research questions: (1) Do the clinical tasks assessed in the 11 OSCE stations map on to a common underlying construct, namely clinical competence? (2) What other insights can Rasch analysis offer in terms of scaling, item analysis and instrument validation over and above the conventional analysis based on classical test theory? The OSCE data set has demonstrated a sufficient degree of fit to the Rasch model (Χ(2) = 17.060, DF=22, p=0.76) indicating that the 11 OSCE station scores have sufficient psychometric properties to form a measure for a common underlying construct, i.e. clinical competence. Individual OSCE station scores with good fit to the Rasch model (p > 0.1 for all Χ(2) statistics) further corroborated the characteristic of unidimensionality of the OSCE scale for clinical competence. A Person Separation Index (PSI) of 0.704 indicates sufficient level of reliability for the OSCE scores. Other useful findings from the Rasch analysis that provide insights, over and above the analysis based on classical test theory, are also exemplified using the data set. The polytomous Rasch model provides a useful and supplementary approach to the calibration and analysis of OSCE examination data.

Applicability Evaluation of Job Standards for Diabetes Nutritional Management by Clinical Dietitian

PubMed Central

2017-01-01

This study was conducted to evaluate applicability of job standards for diabetes nutrition management by hospital clinical dietitians. In order to promote the clinical nutrition services, it is necessary to present job standards of clinical dietitian and to actively apply these standardized tasks to the medical institution sites. The job standard of clinical dietitians for diabetic nutrition management was distributed to hospitals over 300 beds. Questionnaire was collected from 96 clinical dietitians of 40 tertiary hospitals, 47 general hospitals, and 9 hospitals. Based on each 5-point scale, the importance of overall duty was 4.4 ± 0.5, performance was 3.6 ± 0.8, and difficulty was 3.1 ± 0.7. ‘Nutrition intervention’ was 4.5 ± 0.5 for task importance, ‘nutrition assessment’ was 4.0 ± 0.7 for performance, and ‘nutrition diagnosis’ was 3.4 ± 0.9 for difficulty. These 3 items were high in each category. Based on the grid diagram, the tasks of both high importance and high performance were ‘checking basic information,’ ‘checking medical history and therapy plan,’ ‘decision of nutritional needs,’ ‘supply of foods and nutrients,’ and ‘education of nutrition and self-management.’ The tasks with high importance but low performance were ‘derivation of nutrition diagnosis,’ ‘planning of nutrition intervention,’ ‘monitoring of nutrition intervention process.’ The tasks of both high importance and high difficulty were ‘derivation of nutrition diagnosis,’ ‘planning of nutrition intervention,’ ‘supply of foods and nutrients,’ ‘education of nutrition and self-management,’ and ‘monitoring of nutrition intervention process.’ The tasks of both high performance and high difficulty were ‘documentation of nutrition assessment,’ ‘supply of foods and nutrients,’ and ‘education of nutrition and self-management.’ PMID:28503506

Repeated cognitive stimulation alleviates memory impairments in an Alzheimer's disease mouse model.

PubMed

Martinez-Coria, Hilda; Yeung, Stephen T; Ager, Rahasson R; Rodriguez-Ortiz, Carlos J; Baglietto-Vargas, David; LaFerla, Frank M

2015-08-01

Alzheimer's disease is a neurodegenerative disease associated with progressive memory and cognitive decline. Previous studies have identified the benefits of cognitive enrichment on reducing disease pathology. Additionally, epidemiological and clinical data suggest that repeated exercise, and cognitive and social enrichment, can improve and/or delay the cognitive deficiencies associated with aging and neurodegenerative diseases. In the present study, 3xTg-AD mice were exposed to a rigorous training routine beginning at 3 months of age, which consisted of repeated training in the Morris water maze spatial recognition task every 3 months, ending at 18 months of age. At the conclusion of the final Morris water maze training session, animals subsequently underwent testing in another hippocampus-dependent spatial task, the Barnes maze task, and on the more cortical-dependent novel object recognition memory task. Our data show that periodic cognitive enrichment throughout aging, via multiple learning episodes in the Morris water maze task, can improve the memory performance of aged 3xTg-AD mice in a separate spatial recognition task, and in a preference memory task, when compared to naïve aged matched 3xTg-AD mice. Furthermore, we observed that the cognitive enrichment properties of Morris water maze exposer, was detectable in repeatedly trained animals as early as 6 months of age. These findings suggest early repeated cognitive enrichment can mitigate the diverse cognitive deficits observed in Alzheimer's disease. Published by Elsevier Inc.

Contextual Social Cognition Impairments in Schizophrenia and Bipolar Disorder

PubMed Central

Villarin, Lilian; Theil, Donna; Gonzalez-Gadea, María Luz; Gomez, Pedro; Mosquera, Marcela; Huepe, David; Strejilevich, Sergio; Vigliecca, Nora Silvana; Matthäus, Franziska; Decety, Jean; Manes, Facundo; Ibañez, Agustín M.

2013-01-01

Background The ability to integrate contextual information with social cues to generate social meaning is a key aspect of social cognition. It is widely accepted that patients with schizophrenia and bipolar disorders have deficits in social cognition; however, previous studies on these disorders did not use tasks that replicate everyday situations. Methodology/Principal Findings This study evaluates the performance of patients with schizophrenia and bipolar disorders on social cognition tasks (emotional processing, empathy, and social norms knowledge) that incorporate different levels of contextual dependence and involvement of real-life scenarios. Furthermore, we explored the association between social cognition measures, clinical symptoms and executive functions. Using a logistic regression analysis, we explored whether the involvement of more basic skills in emotional processing predicted performance on empathy tasks. The results showed that both patient groups exhibited deficits in social cognition tasks with greater context sensitivity and involvement of real-life scenarios. These deficits were more severe in schizophrenic than in bipolar patients. Patients did not differ from controls in tasks involving explicit knowledge. Moreover, schizophrenic patients’ depression levels were negatively correlated with performance on empathy tasks. Conclusions/Significance Overall performance on emotion recognition predicted performance on intentionality attribution during the more ambiguous situations of the empathy task. These results suggest that social cognition deficits could be related to a general impairment in the capacity to implicitly integrate contextual cues. Important implications for the assessment and treatment of individuals with schizophrenia and bipolar disorders, as well as for neurocognitive models of these pathologies are discussed. PMID:23520477

Effort-Based Decision Making: A Novel Approach for Assessing Motivation in Schizophrenia.

PubMed

Green, Michael F; Horan, William P; Barch, Deanna M; Gold, James M

2015-09-01

Because negative symptoms, including motivational deficits, are a critical unmet need in schizophrenia, there are many ongoing efforts to develop new pharmacological and psychosocial interventions for these impairments. A common challenge of these studies involves how to evaluate and select optimal endpoints. Currently, all studies of negative symptoms in schizophrenia depend on ratings from clinician-conducted interviews. Effort-based decision-making tasks may provide a more objective, and perhaps more sensitive, endpoint for trials of motivational negative symptoms. These tasks assess how much effort a person is willing to exert for a given level of reward. This area has been well-studied with animal models of effort and motivation, and effort-based decision-making tasks have been adapted for use in humans. Very recently, several studies have examined physical and cognitive types of effort-based decision-making tasks in cross-sectional studies of schizophrenia, providing evidence for effort-related impairment in this illness. This article covers the theoretical background on effort-based decision-making tasks to provide a context for the subsequent articles in this theme section. In addition, we review the existing literature of studies using these tasks in schizophrenia, consider some practical challenges in adapting them for use in clinical trials in schizophrenia, and discuss interpretive challenges that are central to these types of tasks. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Assessing hemispheric specialization for processing arithmetic skills in adults: A functional transcranial doppler ultrasonography (fTCD) study.

PubMed

Connaughton, Veronica M; Amiruddin, Azhani; Clunies-Ross, Karen L; French, Noel; Fox, Allison M

2017-05-01

A major model of the cerebral circuits that underpin arithmetic calculation is the triple-code model of numerical processing. This model proposes that the lateralization of mathematical operations is organized across three circuits: a left-hemispheric dominant verbal code; a bilateral magnitude representation of numbers and a bilateral Arabic number code. This study simultaneously measured the blood flow of both middle cerebral arteries using functional transcranial Doppler ultrasonography to assess hemispheric specialization during the performance of both language and arithmetic tasks. The propositions of the triple-code model were assessed in a non-clinical adult group by measuring cerebral blood flow during the performance of multiplication and subtraction problems. Participants were 17 adults aged between 18-27 years. We obtained laterality indices for each type of mathematical operation and compared these in participants with left-hemispheric language dominance. It was hypothesized that blood flow would lateralize to the left hemisphere during the performance of multiplication operations, but would not lateralize during the performance of subtraction operations. Hemispheric blood flow was significantly left lateralized during the multiplication task, but was not lateralized during the subtraction task. Compared to high spatial resolution neuroimaging techniques previously used to measure cerebral lateralization, functional transcranial Doppler ultrasonography is a cost-effective measure that provides a superior temporal representation of arithmetic cognition. These results provide support for the triple-code model of arithmetic processing and offer complementary evidence that multiplication operations are processed differently in the adult brain compared to subtraction operations. Copyright © 2017 Elsevier B.V. All rights reserved.

A three-talk model for shared decision making: multistage consultation process

PubMed Central

Durand, Marie Anne; Song, Julia; Aarts, Johanna; Barr, Paul J; Berger, Zackary; Cochran, Nan; Frosch, Dominick; Galasiński, Dariusz; Gulbrandsen, Pål; Han, Paul K J; Härter, Martin; Kinnersley, Paul; Lloyd, Amy; Mishra, Manish; Perestelo-Perez, Lilisbeth; Scholl, Isabelle; Tomori, Kounosuke; Trevena, Lyndal; Witteman, Holly O; Van der Weijden, Trudy

2017-01-01

Objectives To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement. Design Multistage consultation process. Setting Key informant group, communities of interest, and survey of clinical specialties. Participants 19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties. Results After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on “team talk,” “option talk,” and “decision talk,” to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals. Conclusions The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences. PMID:29109079

Performance Enhancements Under Dual-task Conditions

NASA Technical Reports Server (NTRS)

Kramer, A. F.; Wickens, C. D.; Donchin, E.

1984-01-01

Research on dual-task performance has been concerned with delineating the antecedent conditions which lead to dual-task decrements. Capacity models of attention, which propose that a hypothetical resource structure underlies performance, have been employed as predictive devices. These models predict that tasks which require different processing resources can be more successfully time shared than tasks which require common resources. The conditions under which such dual-task integrality can be fostered were assessed in a study in which three factors likely to influence the integrality between tasks were manipulated: inter-task redundancy, the physical proximity of tasks and the task relevant objects. Twelve subjects participated in three experimental sessions in which they performed both single and dual-tasks. The primary task was a pursuit step tracking task. The secondary tasks required the discrimination between different intensities or different spatial positions of a stimulus. The results are discussed in terms of a model of dual-task integrality.

Task shifting HIV care in rural district hospitals in Cameroon: evidence of comparable antiretroviral treatment-related outcomes between nurses and physicians in the Stratall ANRS/ESTHER trial.

PubMed

Boullé, Charlotte; Kouanfack, Charles; Laborde-Balen, Gabrièle; Carrieri, Maria Patrizia; Dontsop, Marlise; Boyer, Sylvie; Aghokeng, Avelin Fobang; Spire, Bruno; Koulla-Shiro, Sinata; Delaporte, Eric; Laurent, Christian

2013-04-15

Task shifting to nurses for antiretroviral therapy (ART) is promoted by the World Health Organization to compensate for the severe shortage of physicians in Africa. We assessed the effectiveness of task shifting from physicians to nurses in rural district hospitals in Cameroon. We performed a cohort study using data from the Stratall trial, designed to assess monitoring strategies in 2006-2010. ART-naive patients were followed up for 24 months after treatment initiation. Clinical visits were performed by nurses or physicians. We assessed the associations between the consultant ratio (ie, the ratio of the number of nurse-led visits to the number of physician-led visits) and HIV virological success, CD4 recovery, mortality, and disease progression to death or to the World Health Organization clinical stage 4 in multivariate analyses. Of the 4141 clinical visits performed in 459 patients (70.6% female, median age 37 years), a quarter was task shifted to nurses. The consultant ratio was not significantly associated with virological success [odds ratio 1.00, 95% confidence interval (CI): 0.59 to 1.72, P = 0.990], CD4 recovery (coefficient -3.6, 95% CI: -35.6; 28.5, P = 0.827), mortality (time ratio 1.39, 95% CI: 0.27 to 7.06, P = 0.693), or disease progression (time ratio 1.60, 95% CI: 0.35 to 7.37, P = 0.543). This study brings important evidence about the comparability of ART-related outcomes between HIV models of care based on physicians or nurses in resource-limited settings. Investing in nursing resources for the management of noncomplex patients should help reduce costs and patient waiting lists while freeing up physician time for the management of complex cases, for mentoring and supervision activities, and for other health interventions.

Intensive care unit nurses' information needs and recommendations for integrated displays to improve nurses' situation awareness.

PubMed

Koch, Sven H; Weir, Charlene; Haar, Maral; Staggers, Nancy; Agutter, Jim; Görges, Matthias; Westenskow, Dwayne

2012-01-01

Fatal errors can occur in intensive care units (ICUs). Researchers claim that information integration at the bedside may improve nurses' situation awareness (SA) of patients and decrease errors. However, it is unclear which information should be integrated and in what form. Our research uses the theory of SA to analyze the type of tasks, and their associated information gaps. We aimed to provide recommendations for integrated, consolidated information displays to improve nurses' SA. Systematic observations methods were used to follow 19 ICU nurses for 38 hours in 3 clinical practice settings. Storyboard methods and concept mapping helped to categorize the observed tasks, the associated information needs, and the information gaps of the most frequent tasks by SA level. Consensus and discussion of the research team was used to propose recommendations to improve information displays at the bedside based on information deficits. Nurses performed 46 different tasks at a rate of 23.4 tasks per hour. The information needed to perform the most common tasks was often inaccessible, difficult to see at a distance or located on multiple monitoring devices. Current devices at the ICU bedside do not adequately support a nurse's information-gathering activities. Medication management was the most frequent category of tasks. Information gaps were present at all levels of SA and across most of the tasks. Using a theoretical model to understand information gaps can aid in designing functional requirements. Integrated information that enhances nurses' Situation Awareness may decrease errors and improve patient safety in the future.

Intensive care unit nurses' information needs and recommendations for integrated displays to improve nurses' situation awareness

PubMed Central

Weir, Charlene; Haar, Maral; Staggers, Nancy; Agutter, Jim; Görges, Matthias; Westenskow, Dwayne

2012-01-01

Objective Fatal errors can occur in intensive care units (ICUs). Researchers claim that information integration at the bedside may improve nurses' situation awareness (SA) of patients and decrease errors. However, it is unclear which information should be integrated and in what form. Our research uses the theory of SA to analyze the type of tasks, and their associated information gaps. We aimed to provide recommendations for integrated, consolidated information displays to improve nurses' SA. Materials and Methods Systematic observations methods were used to follow 19 ICU nurses for 38 hours in 3 clinical practice settings. Storyboard methods and concept mapping helped to categorize the observed tasks, the associated information needs, and the information gaps of the most frequent tasks by SA level. Consensus and discussion of the research team was used to propose recommendations to improve information displays at the bedside based on information deficits. Results Nurses performed 46 different tasks at a rate of 23.4 tasks per hour. The information needed to perform the most common tasks was often inaccessible, difficult to see at a distance or located on multiple monitoring devices. Current devices at the ICU bedside do not adequately support a nurse's information-gathering activities. Medication management was the most frequent category of tasks. Discussion Information gaps were present at all levels of SA and across most of the tasks. Using a theoretical model to understand information gaps can aid in designing functional requirements. Conclusion Integrated information that enhances nurses' Situation Awareness may decrease errors and improve patient safety in the future. PMID:22437074

Model for prioritization of Graduate Medical Education funding at a university setting - Engagement of GME committee with the Clinical Enterprise.

PubMed

Are, Chandrakanth; Suh, Melissa; Carpenter, Lauren; Stoddard, Hugh; Hamm, Vicki; DeVries, Matthew; Goldner, Whitney; Jarzynka, Kimberly; Parker, Jennifer; Simonson, Jean; Talmon, Geoffrey; Vokoun, Chad; Gold, Jeffrey; Mercer, David; Wadman, Michael

2017-07-19

Funding for graduate medical education (GME) is becoming scarce and is likely to worsen. There is a higher degree of accountability and return on investment demanded from public funds dedicated to GME. Academic centers (AC) partnered with clinical enterprises (CE) are finding it increasingly difficult to retain sustainable funding streams for GME activities. To develop and implement a novel algorithmic funding model at one AC in symbiotic partnership with the CE for all 50 GME programs with nearly 500 residents. A new GME Finance and Workforce Committee was convened which was tasked with developing the novel algorithmic financial model to prioritize GME funding. Early outcomes measures that were monitored consisted of: satisfaction of all stakeholders and financial savings. The model was presented to all the stakeholders and was well received and approved. Early signs, demonstrated AC and CE satisfaction with the model, financial savings and increased efficiency. This GME funding model may serve as a template for other academic centers with tailored modifications to suit their local needs, demands and constraints. Copyright © 2017. Published by Elsevier Inc.

Topical Review: Translating Translational Research in Behavioral Science.

PubMed

Hommel, Kevin A; Modi, Avani C; Piazza-Waggoner, Carrie; Myers, James D

2015-01-01

To present a model of translational research for behavioral science that communicates the role of behavioral research at each phase of translation. A task force identified gaps in knowledge regarding behavioral translational research processes and made recommendations regarding advancement of knowledge. A comprehensive model of translational behavioral research was developed. This model represents T1, T2, and T3 research activities, as well as Phase 1, 2, 3, and 4 clinical trials. Clinical illustrations of translational processes are also offered as support for the model. Behavioral science has struggled with defining a translational research model that effectively articulates each stage of translation and complements biomedical research. Our model defines key activities at each phase of translation from basic discovery to dissemination/implementation. This should be a starting point for communicating the role of behavioral science in translational research and a catalyst for better integration of biomedical and behavioral research. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Test-retest reliability of cognitive EEG

NASA Technical Reports Server (NTRS)

McEvoy, L. K.; Smith, M. E.; Gevins, A.

2000-01-01

OBJECTIVE: Task-related EEG is sensitive to changes in cognitive state produced by increased task difficulty and by transient impairment. If task-related EEG has high test-retest reliability, it could be used as part of a clinical test to assess changes in cognitive function. The aim of this study was to determine the reliability of the EEG recorded during the performance of a working memory (WM) task and a psychomotor vigilance task (PVT). METHODS: EEG was recorded while subjects rested quietly and while they performed the tasks. Within session (test-retest interval of approximately 1 h) and between session (test-retest interval of approximately 7 days) reliability was calculated for four EEG components: frontal midline theta at Fz, posterior theta at Pz, and slow and fast alpha at Pz. RESULTS: Task-related EEG was highly reliable within and between sessions (r0.9 for all components in WM task, and r0.8 for all components in the PVT). Resting EEG also showed high reliability, although the magnitude of the correlation was somewhat smaller than that of the task-related EEG (r0.7 for all 4 components). CONCLUSIONS: These results suggest that under appropriate conditions, task-related EEG has sufficient retest reliability for use in assessing clinical changes in cognitive status.

Anatomy of an Error: A Bidirectional State Model of Task Engagement/Disengagement and Attention-Related Errors

ERIC Educational Resources Information Center

Cheyne, J. Allan; Solman, Grayden J. F.; Carriere, Jonathan S. A.; Smilek, Daniel

2009-01-01

We present arguments and evidence for a three-state attentional model of task engagement/disengagement. The model postulates three states of mind-wandering: occurrent task inattention, generic task inattention, and response disengagement. We hypothesize that all three states are both causes and consequences of task performance outcomes and apply…

Defining and reconstructing clinical processes based on IHE and BPMN 2.0.

PubMed

Strasser, Melanie; Pfeifer, Franz; Helm, Emmanuel; Schuler, Andreas; Altmann, Josef

2011-01-01

This paper describes the current status and the results of our process management system for defining and reconstructing clinical care processes, which contributes to compare, analyze and evaluate clinical processes and further to identify high cost tasks or stays. The system is founded on IHE, which guarantees standardized interfaces and interoperability between clinical information systems. At the heart of the system there is BPMN, a modeling notation and specification language, which allows the definition and execution of clinical processes. The system provides functionality to define healthcare information system independent clinical core processes and to execute the processes in a workflow engine. Furthermore, the reconstruction of clinical processes is done by evaluating an IHE audit log database, which records patient movements within a health care facility. The main goal of the system is to assist hospital operators and clinical process managers to detect discrepancies between defined and actual clinical processes and as well to identify main causes of high medical costs. Beyond that, the system can potentially contribute to reconstruct and improve clinical processes and enhance cost control and patient care quality.

Identifying balance and fall risk in community-dwelling older women: the effect of executive function on postural control.

PubMed

Muir-Hunter, Susan W; Clark, Jennifer; McLean, Stephanie; Pedlow, Sam; Van Hemmen, Alysia; Montero Odasso, Manuel; Overend, Tom

2014-01-01

The mechanisms linking cognition, balance function, and fall risk among older adults are not fully understood. An evaluation of the effect of cognition on balance tests commonly used in clinical practice to assess community-dwelling older adults could enhance the identification of at-risk individuals. The study aimed to determine (1) the association between cognition and clinical tests of balance and (2) the relationship between executive function (EF) and balance under single- and dual-task testing. Participants (24 women, mean age of 76.18 [SD 16.45] years) completed six clinical balance tests, four cognitive tests, and two measures of physical function. Poor balance function was associated with poor performance on cognitive testing of EF. In addition, the association with EF was strongest under the dual-task timed up-and-go (TUG) test and the Fullerton Advanced Balance Scale. Measures of global cognition were associated only with the dual-task performance of the TUG. Postural sway measured with the Standing Balance Test, under single- or dual-task test conditions, was not associated with cognition. Decreased EF was associated with worse performance on functional measures of balance. The relationship between EF and balance was more pronounced with dual-task testing using a complex cognitive task combined with the TUG.

Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller.

PubMed

Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin

2014-06-01

Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance--competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.

Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller

NASA Astrophysics Data System (ADS)

Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin

2014-06-01

Objective. Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. Approach. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Main results. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance—competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. Significance. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

PubMed

Gehrmann, Sebastian; Dernoncourt, Franck; Li, Yeran; Carlson, Eric T; Wu, Joy T; Welt, Jonathan; Foote, John; Moseley, Edward T; Grant, David W; Tyler, Patrick D; Celi, Leo A

2018-01-01

In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.

AAPM Task Group 103 report on peer review in clinical radiation oncology physics

PubMed Central

Halvorsen, Per H.; Das, Indra J.; Fraser, Martin; Freedman, D. Jay; Rice, Robert E.; Ibbott, Geoffrey S.; Parsai, E. Ishmael; Robin, T. Tydings; Thomadsen, Bruce R.

2005-01-01

This report provides guidelines for a peer review process between two clinical radiation oncology physicists. While the Task Group's work was primarily focused on ensuring timely and productive independent reviews for physicists in solo practice, these guidelines may also be appropriate for physicists in a group setting, particularly when dispersed over multiple separate clinic locations. To ensure that such reviews enable a collegial exchange of professional ideas and productive critique of the entire clinical physics program, the reviews should not be used as an employee evaluation instrument by the employer. Such use is neither intended nor supported by this Task Group. Detailed guidelines are presented on the minimum content of such reviews, as well as a recommended format for reporting the findings of a review. In consideration of the full schedules faced by most clinical physicists, the process outlined herein was designed to be completed in one working day. PACS numbers: 87.53.Xd, 87.90.+y PMID:16421500

Use of task-shifting to rapidly scale-up HIV treatment services: experiences from Lusaka, Zambia

PubMed Central

Morris, Mary B; Chapula, Bushimbwa Tambatamba; Chi, Benjamin H; Mwango, Albert; Chi, Harmony F; Mwanza, Joyce; Manda, Handson; Bolton, Carolyn; Pankratz, Debra S; Stringer, Jeffrey SA; Reid, Stewart E

2009-01-01

The World Health Organization advocates task-shifting, the process of delegating clinical care functions from more specialized to less specialized health workers, as a strategy to achieve the United Nations Millennium Development Goals. However, there is a dearth of literature describing task shifting in sub-Saharan Africa, where services for antiretroviral therapy (ART) have scaled up rapidly in the face of generalized human resource crises. As part of ART services expansion in Lusaka, Zambia, we implemented a comprehensive task-shifting program among existing health providers and community-based workers. Training begins with didactic sessions targeting specialized skill sets. This is followed by an intensive period of practical mentorship, where providers are paired with trainers before working independently. We provide on-going quality assessment using key indicators of clinical care quality at each site. Program performance is reviewed with clinic-based staff quarterly. When problems are identified, clinic staff members design and implement specific interventions to address targeted areas. From 2005 to 2007, we trained 516 health providers in adult HIV treatment; 270 in pediatric HIV treatment; 341 in adherence counseling; 91 in a specialty nurse "triage" course, and 93 in an intensive clinical mentorship program. On-going quality assessment demonstrated improvement across clinical care quality indicators, despite rapidly growing patient volumes. Our task-shifting strategy was designed to address current health care worker needs and to sustain ART scale-up activities. While this approach has been successful, long-term solutions to the human resource crisis are also urgently needed to expand the number of providers and to slow staff migration out of the region. PMID:19134202

Detecting fast, online reasoning processes in clinical decision making.

PubMed

Flores, Amanda; Cobos, Pedro L; López, Francisco J; Godoy, Antonio

2014-06-01

In an experiment that used the inconsistency paradigm, experienced clinical psychologists and psychology students performed a reading task using clinical reports and a diagnostic judgment task. The clinical reports provided information about the symptoms of hypothetical clients who had been previously diagnosed with a specific mental disorder. Reading times of inconsistent target sentences were slower than those of control sentences, demonstrating an inconsistency effect. The results also showed that experienced clinicians gave different weights to different symptoms according to their relevance when fluently reading the clinical reports provided, despite the fact that all the symptoms were of equal diagnostic value according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000). The diagnostic judgment task yielded a similar pattern of results. In contrast to previous findings, the results of the reading task may be taken as direct evidence of the intervention of reasoning processes that occur very early, rapidly, and online. We suggest that these processes are based on the representation of mental disorders and that these representations are particularly suited to fast retrieval from memory and to making inferences. They may also be related to the clinicians' causal reasoning. The implications of these results for clinician training are also discussed.

The relevance of "non-criteria" clinical manifestations of antiphospholipid syndrome: 14th International Congress on Antiphospholipid Antibodies Technical Task Force Report on Antiphospholipid Syndrome Clinical Features.

PubMed

Abreu, Mirhelen M; Danowski, Adriana; Wahl, Denis G; Amigo, Mary-Carmen; Tektonidou, Maria; Pacheco, Marcelo S; Fleming, Norma; Domingues, Vinicius; Sciascia, Savino; Lyra, Julia O; Petri, Michelle; Khamashta, Munther; Levy, Roger A

2015-05-01

The purpose of this task force was to critically analyze nine non-criteria manifestations of APS to support their inclusion as APS classification criteria. The Task Force Members selected the non-criteria clinical manifestations according to their clinical relevance, that is, the patient-important outcome from clinician perspective. They included superficial vein thrombosis, thrombocytopenia, renal microangiopathy, heart valve disease, livedo reticularis, migraine, chorea, seizures and myelitis, which were reviewed by this International Task Force collaboration, in addition to the seronegative APS (SN-APS). GRADE system was used to evaluate the quality of evidence of medical literature of each selected item. This critical appraisal exercise aimed to support the debate regarding the clinical picture of APS. We found that the overall GRADE analysis was very low for migraine and seizures, low for superficial venous thrombosis, thrombocytopenia, chorea, longitudinal myelitis and the so-called seronegative APS and moderate for APS nephropathy, heart valve lesions and livedo reticularis. The next step can be a critical redefinition of an APS gold standard, for instance derived from the APS ACTION registry that will include not only current APS patients but also those with antiphospholipid antibodies not meeting current classification criteria. Copyright © 2015 Elsevier B.V. All rights reserved.

Diffusion Decision Model: Current Issues and History.

PubMed

Ratcliff, Roger; Smith, Philip L; Brown, Scott D; McKoon, Gail

2016-04-01

There is growing interest in diffusion models to represent the cognitive and neural processes of speeded decision making. Sequential-sampling models like the diffusion model have a long history in psychology. They view decision making as a process of noisy accumulation of evidence from a stimulus. The standard model assumes that evidence accumulates at a constant rate during the second or two it takes to make a decision. This process can be linked to the behaviors of populations of neurons and to theories of optimality. Diffusion models have been used successfully in a range of cognitive tasks and as psychometric tools in clinical research to examine individual differences. In this review, we relate the models to both earlier and more recent research in psychology. Copyright © 2016. Published by Elsevier Ltd.

Requirements for clinical information modelling tools.

PubMed

Moreno-Conde, Alberto; Jódar-Sánchez, Francisco; Kalra, Dipak

2015-07-01

This study proposes consensus requirements for clinical information modelling tools that can support modelling tasks in medium/large scale institutions. Rather than identify which functionalities are currently available in existing tools, the study has focused on functionalities that should be covered in order to provide guidance about how to evolve the existing tools. After identifying a set of 56 requirements for clinical information modelling tools based on a literature review and interviews with experts, a classical Delphi study methodology was applied to conduct a two round survey in order to classify them as essential or recommended. Essential requirements are those that must be met by any tool that claims to be suitable for clinical information modelling, and if we one day have a certified tools list, any tool that does not meet essential criteria would be excluded. Recommended requirements are those more advanced requirements that may be met by tools offering a superior product or only needed in certain modelling situations. According to the answers provided by 57 experts from 14 different countries, we found a high level of agreement to enable the study to identify 20 essential and 21 recommended requirements for these tools. It is expected that this list of identified requirements will guide developers on the inclusion of new basic and advanced functionalities that have strong support by end users. This list could also guide regulators in order to identify requirements that could be demanded of tools adopted within their institutions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The dissemination of clinical practice guidelines over an intranet: an evaluation.

PubMed Central

Stolte, J. J.; Ash, J.; Chin, H.

1999-01-01

This study compares two clinical practice guideline dissemination systems. It was hypothesized that placing guidelines on an intranet would make this information easier to retrieve. Retrieval time, retrieval accuracy, and ease of use were empirically evaluated. Sixteen clinicians from Kaiser Permanente volunteered to complete tasks that measured these variables. Time values were significantly longer for tasks completed with intranet guidelines (Intranet = 6.7 minutes, Paper = 5.7 minutes). Tasks completed with paper guidelines had a significantly higher percentage of perfect scores than those completed with the intranet (Paper = 85%, Intranet = 59%). There was no significant difference in reported ease of use. Simply placing clinical information on an electronic system does not guarantee that the information will be easier to retrieve. Such information needs to be fully integrated into the clinical decision making process. Computerizing guidelines may provide a necessary initial step toward this goal, but it does not represent the final solution. PMID:10566503

Object and event recognition for stroke rehabilitation

NASA Astrophysics Data System (ADS)

Ghali, Ahmed; Cunningham, Andrew S.; Pridmore, Tony P.

2003-06-01

Stroke is a major cause of disability and health care expenditure around the world. Existing stroke rehabilitation methods can be effective but are costly and need to be improved. Even modest improvements in the effectiveness of rehabilitation techniques could produce large benefits in terms of quality of life. The work reported here is part of an ongoing effort to integrate virtual reality and machine vision technologies to produce innovative stroke rehabilitation methods. We describe a combined object recognition and event detection system that provides real time feedback to stroke patients performing everyday kitchen tasks necessary for independent living, e.g. making a cup of coffee. The image plane position of each object, including the patient"s hand, is monitored using histogram-based recognition methods. The relative positions of hand and objects are then reported to a task monitor that compares the patient"s actions against a model of the target task. A prototype system has been constructed and is currently undergoing technical and clinical evaluation.

Usefulness of near-infrared spectroscopy to detect brain dysfunction in children with autism spectrum disorder when inferring the mental state of others.

PubMed

Iwanaga, Ryoichiro; Tanaka, Goro; Nakane, Hideyuki; Honda, Sumihisa; Imamura, Akira; Ozawa, Hiroki

2013-05-01

The purpose of this study was to examine the usefulness of near-infrared spectroscopy (NIRS) for identifying abnormalities in prefrontal brain activity in children with autism spectrum disorders (ASD) as they inferred the mental states of others. The subjects were 16 children with ASD aged between 8 and 14 years and 16 age-matched healthy control children. Oxygenated hemoglobin concentration was measured in the subject's prefrontal brain region on NIRS during tasks expressing a person's mental state (MS task) and expressing an object's characteristics (OC task). There was a significant main effect of group (ASD vs control), with the control group having more activity than the ASD group. But there was no significant main effect of task (MS task vs OC task) or hemisphere (right vs left). Significant interactions of task and group were found, with the control group showing more activity than the ASD group during the MS task relative to the OC task. NIRS showed that there was lower activity in the prefrontal brain area when children with ASD performed MS tasks. Therefore, clinicians might be able to use NIRS and these tasks for conveniently detecting brain dysfunction in children with ASD related to inferring mental states, in the clinical setting. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

Strategies and challenges for communicating the diagnosis of cancer in cross-cultural clinical settings-Perspectives from South African healthcare professionals.

PubMed

Brown, Ottilia; Goliath, Veonna; van Rooyen, Dalena R M; Aldous, Colleen; Marais, Leonard Charles

2017-01-01

Communicating the diagnosis of cancer in cross-cultural clinical settings is a complex task. This qualitative research article describes the content and process of informing Zulu patients in South Africa of the diagnosis of cancer, using osteosarcoma as the index diagnosis. We used a descriptive research design with census sampling and focus group interviews. We used an iterative thematic data analysis process and Guba's model of trustworthiness to ensure scientific rigor. Our results reinforced the use of well-accepted strategies for communicating the diagnosis of cancer. In addition, new strategies emerged which may be useful in other cross-cultural settings. These strategies included using the stages of cancer to explain the disease and its progression and instilling hope using a multidisciplinary team care model. We identified several patients, professionals, and organizational factors that complicate cross-cultural communication. We conclude by recommending the development of protocols for communication in these cross-cultural clinical settings.

FRAX(®) Bone Mineral Density Task Force of the 2010 Joint International Society for Clinical Densitometry & International Osteoporosis Foundation Position Development Conference.

PubMed

Lewiecki, E Michael; Compston, Juliet E; Miller, Paul D; Adachi, Jonathan D; Adams, Judith E; Leslie, William D; Kanis, John A

2011-01-01

FRAX(®) is a fracture risk assessment algorithm developed by the World Health Organization in cooperation with other medical organizations and societies. Using easily available clinical information and femoral neck bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA), when available, FRAX(®) is used to predict the 10-year probability of hip fracture and major osteoporotic fracture. These values may be included in country specific guidelines to aid clinicians in determining when fracture risk is sufficiently high that the patient is likely to benefit from pharmacological therapy to reduce that risk. Since the introduction of FRAX(®) into clinical practice, many practical clinical questions have arisen regarding its use. To address such questions, the International Society for Clinical Densitometry (ISCD) and International Osteoporosis Foundations (IOF) assigned task forces to review the best available medical evidence and make recommendations for optimal use of FRAX(®) in clinical practice. Questions were identified and divided into three general categories. A task force was assigned to investigating the medical evidence in each category and developing clinically useful recommendations. The BMD Task Force addressed issues that included the potential use of skeletal sites other than the femoral neck, the use of technologies other than DXA, and the deletion or addition of clinical data for FRAX(®) input. The evidence and recommendations were presented to a panel of experts at the ISCD-IOF FRAX(®) Position Development Conference, resulting in the development of ISCD-IOF Official Positions addressing FRAX(®)-related issues. Copyright © 2011 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

A Hybrid Approach to Composite Damage and Failure Analysis Combining Synergistic Damage Mechanics and Peridynamics

DTIC Science & Technology

2016-03-31

fiber distributions. Task 2.1 is concerned with damage evolution in a peridynamic model of poroelastic materials. Initial results for both tasks are...distributions. Task 2.1 is concerned with damage evolution in a peridynamic model of poroelastic materials. Initial results for both tasks are reported and...Task 2.1: Damage evolution in a peridynamic model of poroelastic materials. Background and Motivation In order to model the presence of pores and

Task inhibition, conflict, and the n-2 repetition cost: A combined computational and empirical approach.

PubMed

Sexton, Nicholas J; Cooper, Richard P

2017-05-01

Task inhibition (also known as backward inhibition) is an hypothesised form of cognitive inhibition evident in multi-task situations, with the role of facilitating switching between multiple, competing tasks. This article presents a novel cognitive computational model of a backward inhibition mechanism. By combining aspects of previous cognitive models in task switching and conflict monitoring, the model instantiates the theoretical proposal that backward inhibition is the direct result of conflict between multiple task representations. In a first simulation, we demonstrate that the model produces two effects widely observed in the empirical literature, specifically, reaction time costs for both (n-1) task switches and n-2 task repeats. Through a systematic search of parameter space, we demonstrate that these effects are a general property of the model's theoretical content, and not specific parameter settings. We further demonstrate that the model captures previously reported empirical effects of inter-trial interval on n-2 switch costs. A final simulation extends the paradigm of switching between tasks of asymmetric difficulty to three tasks, and generates novel predictions for n-2 repetition costs. Specifically, the model predicts that n-2 repetition costs associated with hard-easy-hard alternations are greater than for easy-hard-easy alternations. Finally, we report two behavioural experiments testing this hypothesis, with results consistent with the model predictions. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

PubMed

Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

2015-03-01

The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

Nurse task shifting for antiretroviral treatment services in Namibia: implementation research to move evidence into action.

PubMed

O'Malley, Gabrielle; Asrat, Lily; Sharma, Anjali; Hamunime, Ndapewa; Stephanus, Yvonne; Brandt, Laura; Ali, Deqa; Kaindjee-Tjituka, Francina; Natanael, Salomo; Gweshe, Justice; Feldacker, Caryl; Shihepo, Ella

2014-01-01

Evidence from several sub-Saharan countries support nurse-initiated antiretroviral treatment as a feasible alternative to doctor-led models characteristic of early responses to the HIV epidemic. However, service delivery models shown to be effective in one country may not be readily adopted in another. This study used an implementation research approach to assist policy makers and other stakeholders to assess the acceptability and feasibility of task shifting in the Namibian context. The Namibian Ministry of Health and Social Services implemented a Task Shifting Demonstration Project (TSDP) at 9 sites at different levels of the health system. Six months after implementation, a mixed methods evaluation was conducted. Seventy semi-structured interviews were conducted with patients, managers, doctors and nurses directly involved with the TSDP. Physician-evaluators observed and compared health service provision between doctors and nurses for 40 patients (80 observations), documenting performance in agreement with the national guidelines on 13 clinical care indicators. Doctors, nurses, and patients interviewed believed task shifting would improve access to and quality of HIV services. Doctors and nurses both reported an increase in nurses' skills as a result of the project. Observation data showed doctors and nurses were in considerable agreement (>80%) with each other on all dimensions of HIV care and ≥90% on eight dimensions. To ensure success of national scale-up of the task shifting model, challenges involving infrastructure, on-going mentoring, and nursing scope of practice should be anticipated and addressed. In combination with findings from other studies in the region, data from the TSDP provided critical and timely information to the Namibian Ministry of Health and Social Services, thus helping to move evidence into action. Small-scale implementation research projects enable stakeholders to learn by doing, and provide an opportunity to test and modify the intervention before expansion.

Nurse Task Shifting for Antiretroviral Treatment Services in Namibia: Implementation Research to Move Evidence into Action

PubMed Central

O’Malley, Gabrielle; Asrat, Lily; Sharma, Anjali; Hamunime, Ndapewa; Stephanus, Yvonne; Brandt, Laura; Ali, Deqa; Kaindjee-Tjituka, Francina; Natanael, Salomo; Gweshe, Justice; Feldacker, Caryl; Shihepo, Ella

2014-01-01

Background Evidence from several sub-Saharan countries support nurse-initiated antiretroviral treatment as a feasible alternative to doctor-led models characteristic of early responses to the HIV epidemic. However, service delivery models shown to be effective in one country may not be readily adopted in another. This study used an implementation research approach to assist policy makers and other stakeholders to assess the acceptability and feasibility of task shifting in the Namibian context. Methods The Namibian Ministry of Health and Social Services implemented a Task Shifting Demonstration Project (TSDP) at 9 sites at different levels of the health system. Six months after implementation, a mixed methods evaluation was conducted. Seventy semi-structured interviews were conducted with patients, managers, doctors and nurses directly involved with the TSDP. Physician-evaluators observed and compared health service provision between doctors and nurses for 40 patients (80 observations), documenting performance in agreement with the national guidelines on 13 clinical care indicators. Results Doctors, nurses, and patients interviewed believed task shifting would improve access to and quality of HIV services. Doctors and nurses both reported an increase in nurses’ skills as a result of the project. Observation data showed doctors and nurses were in considerable agreement (>80%) with each other on all dimensions of HIV care and ≥90% on eight dimensions. To ensure success of national scale-up of the task shifting model, challenges involving infrastructure, on-going mentoring, and nursing scope of practice should be anticipated and addressed. Conclusion In combination with findings from other studies in the region, data from the TSDP provided critical and timely information to the Namibian Ministry of Health and Social Services, thus helping to move evidence into action. Small-scale implementation research projects enable stakeholders to learn by doing, and provide an opportunity to test and modify the intervention before expansion. PMID:24642894

Benefits of task-shifting HIV care to nurses in terms of health-related quality of life in patients initiating antiretroviral therapy in rural district hospitals in Cameroon [Stratall Agence Nationale de Recherche sur le SIDA (ANRS) 12110/Ensemble pour une Solidarité Thérapeutique Hospitalière en Réseau (ESTHER) substudy].

PubMed

Suzan-Monti, M; Blanche, J; Boyer, S; Kouanfack, C; Delaporte, E; Bonono, R-C; Carrieri, P M; Protopopescu, C; Laurent, C; Spire, B

2015-05-01

The World Health Organization (WHO) recommends task-shifting HIV care to nurses in low-resource settings with limited numbers of physicians. However, the effect of such task-shifting on the health-related quality of life (HRQL) of people living with HIV (PLHIV) has seldom been evaluated. We aimed to investigate the effect of task-shifting HIV care to nurses on HRQL outcomes in PLHIV initiating antiretroviral therapy (ART) in rural district hospitals in Cameroon. Outcomes in PLHIV were longitudinally collected in the 2006-2010 Stratall trial. PLHIV were followed up for 24 months by nurses and/or physicians. Six HRQL dimensions were assessed during face-to-face interviews using the WHO Quality of Life (WHOQOL)-HIV BREF scale: physical health; psychological health; independence level; social relationships; environment; and spirituality/religion/personal beliefs. The degree of task-shifting was estimated using a consultant ratio (i.e. the ratio of nurse-led to physician-led visits). The effect of task-shifting and other potential correlates on HRQL dimensions was explored using a Heckman two-stage approach based on linear mixed models to adjust for the potential bias caused by missing data in the outcomes. Of 1424 visits in 440 PLHIV (70.5% female; median age 36 years; median CD4 count 188 cells/μL at enrolment), 423 (29.7%) were task-shifted to nurses. After multiple adjustment, task-shifting was associated with higher HRQL level for four dimensions: physical health [coefficient 0.7; 95% confidence interval (CI) 0.1-1.2; P = 0.01], psychological health (coefficient 0.5; 95% CI 0.0-1.0; P = 0.05), independence level (coefficient 0.6; 95% CI 0.1-1.1; P = 0.01) and environment (coefficient 0.6; 95% CI 0.1-1.0; P = 0.02). Task-shifting HIV care to nurses benefits the HRQL of PLHIV. Together with the previously demonstrated comparable clinical effectiveness of physician-based and nurse-based models of HIV care, our results support the WHO recommendation for task-shifting. © 2015 British HIV Association.

What Makes Patient Navigation Most Effective: Defining Useful Tasks and Networks.

PubMed

Gunn, Christine; Battaglia, Tracy A; Parker, Victoria A; Clark, Jack A; Paskett, Electra D; Calhoun, Elizabeth; Snyder, Frederick R; Bergling, Emily; Freund, Karen M

2017-01-01

Given the momentum in adopting patient navigation into cancer care, there is a need to understand the contribution of specific navigator activities to improved clinical outcomes. A mixed-methods study combined direct observations of patient navigators within the Patient Navigation Research Program and outcome data from the trial. We correlated the frequency of navigator tasks with the outcome of rate of diagnostic resolution within 365 days among patients who received the intervention relative to controls. A focused content analysis examined those tasks with the strongest correlations between navigator tasks and patient outcomes. Navigating directly with specific patients (r = 0.679), working with clinical providers to facilitate patient care (r = 0.643), and performing tasks not directly related to their diagnostic evaluation for patients were positively associated with more timely diagnosis (r = 0.714). Using medical records for non-navigation tasks had a negative association (r = -0.643). Content analysis revealed service provision directed at specific patients improved care while systems-focused activities did not.

Dimebon enhances hippocampus-dependent learning in both appetitive and inhibitory memory tasks in mice.

PubMed

Vignisse, Julie; Steinbusch, Harry W M; Bolkunov, Alexei; Nunes, Joao; Santos, Ana Isabel; Grandfils, Christian; Bachurin, Sergei; Strekalova, Tatyana

2011-03-30

Pre-clinical and clinical studies on dimebon (dimebolin or latrepirdine) have demonstrated its use as a cognitive enhancer. Here, we show that dimebon administered to 3-month-old C57BL6N mice 15 min prior to training in both appetitive and inhibitory learning tasks via repeated (0.1 mg/kg) and acute (0.5 mg/kg) i.p. injections, respectively, increases memory scores. Acute treatment with dimebon was found to enhance inhibitory learning, as also shown in the step-down avoidance paradigm in 7-month-old mice. Bolus administration of dimebon did not affect the animals' locomotion, exploration or anxiety-like behaviour, with the exception of exploratory behaviour in older mice in the novel cage test. In a model of appetitive learning, a spatial version of the Y-maze, dimebon increased the rate of correct choices and decreased the latency of accessing a water reward after water deprivation, and increased the duration of drinking behaviour during training/testing procedures. Repeated treatment with dimebon did not alter the behaviours in other tests or water consumption. Acute treatment of water-deprived and non-water-deprived mice with dimebon also did not affect their water intake. Our data suggest that dimebon enhances hippocampus-dependent learning in both appetitive and inhibitory tasks in mice. Copyright © 2011 Elsevier B.V. All rights reserved.

Determining if an older adult can make and execute decisions to live safely at home: a capacity assessment and intervention model

PubMed Central

Skelton, Felicia; Kunik, Mark E.; Regev, Tziona; Naik, Aanand D.

2009-01-01

Determining an older adult’s capacity to live safely and independently in the community presents a serious and complicated challenge to the health care system. Evaluating one’s ability to make and execute decisions regarding safe and independent living incorporates clinical assessments, bioethical considerations, and often legal declarations of capacity. Capacity assessments usually result in life changes for patients and their families, including a caregiver managing some everyday tasks, placement outside of the home, and even legal guardianship. The process of determining capacity and recommending intervention is often inefficient and highly variable in most cases. Physicians are rarely trained to conduct capacity assessments and assessment methods are heterogeneous. An interdisciplinary team of clinicians developed the capacity assessment and intervention (CAI) model at a community outpatient geriatrics clinic to address these critical gaps. This report follows one patient through the entire CAI model, describing processes for a typical case. It then examines two additional case reports that highlight common challenges in capacity assessment. The CAI model uses assessment methods common to geriatrics clinical practice and conducts assessments and interventions in a standardized fashion. Reliance on common, validated measures increases generalizability of the model across geriatrics practice settings and patient populations. PMID:19481271

The role of extra-foveal processing in 3D imaging

NASA Astrophysics Data System (ADS)

Eckstein, Miguel P.; Lago, Miguel A.; Abbey, Craig K.

2017-03-01

The field of medical image quality has relied on the assumption that metrics of image quality for simple visual detection tasks are a reliable proxy for the more clinically realistic visual search tasks. Rank order of signal detectability across conditions often generalizes from detection to search tasks. Here, we argue that search in 3D images represents a paradigm shift in medical imaging: radiologists typically cannot exhaustively scrutinize all regions of interest with the high acuity fovea requiring detection of signals with extra-foveal areas (visual periphery) of the human retina. We hypothesize that extra-foveal processing can alter the detectability of certain types of signals in medical images with important implications for search in 3D medical images. We compare visual search of two different types of signals in 2D vs. 3D images. We show that a small microcalcification-like signal is more highly detectable than a larger mass-like signal in 2D search, but its detectability largely decreases (relative to the larger signal) in the 3D search task. Utilizing measurements of observer detectability as a function retinal eccentricity and observer eye fixations we can predict the pattern of results in the 2D and 3D search studies. Our findings: 1) suggest that observer performance findings with 2D search might not always generalize to 3D search; 2) motivate the development of a new family of model observers that take into account the inhomogeneous visual processing across the retina (foveated model observers).

Higher mental workload is associated with poorer laparoscopic performance as measured by the NASA-TLX tool.

PubMed

Yurko, Yuliya Y; Scerbo, Mark W; Prabhu, Ajita S; Acker, Christina E; Stefanidis, Dimitrios

2010-10-01

Increased workload during task performance may increase fatigue and facilitate errors. The National Aeronautics and Space Administration-Task Load Index (NASA-TLX) is a previously validated tool for workload self-assessment. We assessed the relationship of workload and performance during simulator training on a complex laparoscopic task. NASA-TLX workload data from three separate trials were analyzed. All participants were novices (n = 28), followed the same curriculum on the fundamentals of laparoscopic surgery suturing model, and were tested in the animal operating room (OR) on a Nissen fundoplication model after training. Performance and workload scores were recorded at baseline, after proficiency achievement, and during the test. Performance, NASA-TLX scores, and inadvertent injuries during the test were analyzed and compared. Workload scores declined during training and mirrored performance changes. NASA-TLX scores correlated significantly with performance scores (r = -0.5, P < 0.001). Participants with higher workload scores caused more inadvertent injuries to adjacent structures in the OR (r = 0.38, P < 0.05). Increased mental and physical workload scores at baseline correlated with higher workload scores in the OR (r = 0.52-0.82; P < 0.05) and more inadvertent injuries (r = 0.52, P < 0.01). Increased workload is associated with inferior task performance and higher likelihood of errors. The NASA-TLX questionnaire accurately reflects workload changes during simulator training and may identify individuals more likely to experience high workload and more prone to errors during skill transfer to the clinical environment.

Understanding psychiatric disorder by capturing ecologically relevant features of learning and decision-making.

PubMed

Scholl, Jacqueline; Klein-Flügge, Miriam

2017-09-28

Recent research in cognitive neuroscience has begun to uncover the processes underlying increasingly complex voluntary behaviours, including learning and decision-making. Partly this success has been possible by progressing from simple experimental tasks to paradigms that incorporate more ecological features. More specifically, the premise is that to understand cognitions and brain functions relevant for real life, we need to introduce some of the ecological challenges that we have evolved to solve. This often entails an increase in task complexity, which can be managed by using computational models to help parse complex behaviours into specific component mechanisms. Here we propose that using computational models with tasks that capture ecologically relevant learning and decision-making processes may provide a critical advantage for capturing the mechanisms underlying symptoms of disorders in psychiatry. As a result, it may help develop mechanistic approaches towards diagnosis and treatment. We begin this review by mapping out the basic concepts and models of learning and decision-making. We then move on to consider specific challenges that emerge in realistic environments and describe how they can be captured by tasks. These include changes of context, uncertainty, reflexive/emotional biases, cost-benefit decision-making, and balancing exploration and exploitation. Where appropriate we highlight future or current links to psychiatry. We particularly draw examples from research on clinical depression, a disorder that greatly compromises motivated behaviours in real-life, but where simpler paradigms have yielded mixed results. Finally, we highlight several paradigms that could be used to help provide new insights into the mechanisms of psychiatric disorders. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Enhanced sequential reaction time task performance in a rat model of mesial temporal lobe epilepsy with classic hippocampal sclerosis.

PubMed

Will, Johanna L; Eckart, Moritz T; Rosenow, Felix; Bauer, Sebastian; Oertel, Wolfgang H; Schwarting, Rainer K W; Norwood, Braxton A

2013-06-15

The human serial reaction time task (SRTT) has widely been used to study the neural basis of implicit learning. It is well documented, in both human and animal studies, that striatal dopaminergic processes play a major role in this task. However, findings on the role of the hippocampus - which is mainly associated with declarative memory - in implicit learning and performance are less univocal. We used a SRTT to evaluate implicit learning and performance in rats with perforant pathway stimulation-induced hippocampal neuron loss; a clinically-relevant animal model of mesial temporal lobe epilepsy (MTLS-HS). As has been previously reported for the Sprague-Dawley strain, 8h of continuous stimulation in male Wistar rats reliably induced widespread neuron loss in areas CA3 and CA1 with a characteristic sparing of CA2 and the granule cells. Histological analysis revealed that hippocampal volume was reduced by an average of 44%. Despite this severe hippocampal injury, rats showed superior performance in our instrumental SRTT, namely shorter reaction times, and without a loss in accuracy, especially during the second half of our 16-days testing period. These results demonstrate that a hippocampal lesion can improve performance in a rat SRTT, which is probably due to enhanced instrumental performance. In line with our previous findings based on ibotenic-acid induced hippocampal lesion, these data support the hypothesis that loss or impairment of hippocampal function can enhance specific task performance, especially when it is dependent on procedural (striatum-dependent) mechanisms with minimal spatial requirements. As the animal model used here exhibits the defining characteristics of MTLE-HS, these findings may have implications for the study and management of patients with MTLE. Copyright © 2013 Elsevier B.V. All rights reserved.

Fusiform Gyrus Dysfunction is Associated with Perceptual Processing Efficiency to Emotional Faces in Adolescent Depression: A Model-Based Approach.

PubMed

Ho, Tiffany C; Zhang, Shunan; Sacchet, Matthew D; Weng, Helen; Connolly, Colm G; Henje Blom, Eva; Han, Laura K M; Mobayed, Nisreen O; Yang, Tony T

2016-01-01

While the extant literature has focused on major depressive disorder (MDD) as being characterized by abnormalities in processing affective stimuli (e.g., facial expressions), little is known regarding which specific aspects of cognition influence the evaluation of affective stimuli, and what are the underlying neural correlates. To investigate these issues, we assessed 26 adolescents diagnosed with MDD and 37 well-matched healthy controls (HCL) who completed an emotion identification task of dynamically morphing faces during functional magnetic resonance imaging (fMRI). We analyzed the behavioral data using a sequential sampling model of response time (RT) commonly used to elucidate aspects of cognition in binary perceptual decision making tasks: the Linear Ballistic Accumulator (LBA) model. Using a hierarchical Bayesian estimation method, we obtained group-level and individual-level estimates of LBA parameters on the facial emotion identification task. While the MDD and HCL groups did not differ in mean RT, accuracy, or group-level estimates of perceptual processing efficiency (i.e., drift rate parameter of the LBA), the MDD group showed significantly reduced responses in left fusiform gyrus compared to the HCL group during the facial emotion identification task. Furthermore, within the MDD group, fMRI signal in the left fusiform gyrus during affective face processing was significantly associated with greater individual-level estimates of perceptual processing efficiency. Our results therefore suggest that affective processing biases in adolescents with MDD are characterized by greater perceptual processing efficiency of affective visual information in sensory brain regions responsible for the early processing of visual information. The theoretical, methodological, and clinical implications of our results are discussed.

Fusiform Gyrus Dysfunction is Associated with Perceptual Processing Efficiency to Emotional Faces in Adolescent Depression: A Model-Based Approach

PubMed Central

Ho, Tiffany C.; Zhang, Shunan; Sacchet, Matthew D.; Weng, Helen; Connolly, Colm G.; Henje Blom, Eva; Han, Laura K. M.; Mobayed, Nisreen O.; Yang, Tony T.

2016-01-01

While the extant literature has focused on major depressive disorder (MDD) as being characterized by abnormalities in processing affective stimuli (e.g., facial expressions), little is known regarding which specific aspects of cognition influence the evaluation of affective stimuli, and what are the underlying neural correlates. To investigate these issues, we assessed 26 adolescents diagnosed with MDD and 37 well-matched healthy controls (HCL) who completed an emotion identification task of dynamically morphing faces during functional magnetic resonance imaging (fMRI). We analyzed the behavioral data using a sequential sampling model of response time (RT) commonly used to elucidate aspects of cognition in binary perceptual decision making tasks: the Linear Ballistic Accumulator (LBA) model. Using a hierarchical Bayesian estimation method, we obtained group-level and individual-level estimates of LBA parameters on the facial emotion identification task. While the MDD and HCL groups did not differ in mean RT, accuracy, or group-level estimates of perceptual processing efficiency (i.e., drift rate parameter of the LBA), the MDD group showed significantly reduced responses in left fusiform gyrus compared to the HCL group during the facial emotion identification task. Furthermore, within the MDD group, fMRI signal in the left fusiform gyrus during affective face processing was significantly associated with greater individual-level estimates of perceptual processing efficiency. Our results therefore suggest that affective processing biases in adolescents with MDD are characterized by greater perceptual processing efficiency of affective visual information in sensory brain regions responsible for the early processing of visual information. The theoretical, methodological, and clinical implications of our results are discussed. PMID:26869950

DESIGNING PHARMACEUTICAL TRIALS FOR SARCOPENIA IN FRAIL OLDER ADULTS: EU/US TASK FORCE RECOMMENDATIONS

PubMed Central

VELLAS, B.; PAHOR, M.; MANINI, T.; ROOKS, D.; GURALNIK, J.M.; MORLEY, J.; STUDENSKI, S.; EVANS, W.; ASBRAND, C.; FARIELLO, R.; PEREIRA, S.; ROLLAND, Y.; VAN KAN, G. ABELLAN; CESARI, M.; CHUMLEA, WM.C.; FIELDING, R.

2014-01-01

An international task force of academic and industry leaders in sarcopenia research met on December 5, 2012 in Orlando, Florida to develop guidelines for designing and executing randomized clinical trials of sarcopenia treatments. The Task Force reviewed results from previous trials in related disease areas to extract lessons relevant to future sarcopenia trials, including practical issues regarding the design and conduct of trials in elderly populations, the definition of appropriate target populations, and the selection of screening tools, outcome measures, and biomarkers. They discussed regulatory issues, the challenges posed by trials of different types of interventions, and the need for standardization and harmonization. The Task Force concluded with recommendations for advancing the field toward better clinical trials. PMID:23933872

A review of GPU-based medical image reconstruction.

PubMed

Després, Philippe; Jia, Xun

2017-10-01

Tomographic image reconstruction is a computationally demanding task, even more so when advanced models are used to describe a more complete and accurate picture of the image formation process. Such advanced modeling and reconstruction algorithms can lead to better images, often with less dose, but at the price of long calculation times that are hardly compatible with clinical workflows. Fortunately, reconstruction tasks can often be executed advantageously on Graphics Processing Units (GPUs), which are exploited as massively parallel computational engines. This review paper focuses on recent developments made in GPU-based medical image reconstruction, from a CT, PET, SPECT, MRI and US perspective. Strategies and approaches to get the most out of GPUs in image reconstruction are presented as well as innovative applications arising from an increased computing capacity. The future of GPU-based image reconstruction is also envisioned, based on current trends in high-performance computing. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Indexing sensory plasticity: Evidence for distinct Predictive Coding and Hebbian learning mechanisms in the cerebral cortex.

PubMed

Spriggs, M J; Sumner, R L; McMillan, R L; Moran, R J; Kirk, I J; Muthukumaraswamy, S D

2018-04-30

The Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aim of the current study was to compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain. Forty participants were presented with both paradigms during EEG recording. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. This therefore indicates that both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations. Copyright © 2018 Elsevier Inc. All rights reserved.

Identification of the Gene for Scleroderma in the Tsk/2 Mouse Strain: Implications for Human Scleroderma Pathogenesis and Subset Distinctions

DTIC Science & Technology

2012-07-01

Philadelphia, PA 19104 1 Jul 2011 - 30 Jun 2012Annual01-07-2012 This project is focused on an animal model of the human disease, systemic sclerosis ...earliest indicator of tight-skin in the tissue Animal model, systemic sclerosis , scleroderma, Tsk2/+, fibrosis, gene, genetics, TGFβ 35 eblanken...the  multiple  clinical parameters of fibrotic disease from birth  onward.   BODY  Milestones were assigned to this proposal, with tasks to be

Single Neurons in M1 and Premotor Cortex Directly Reflect Behavioral Interference

PubMed Central

Zach, Neta; Inbar, Dorrit; Grinvald, Yael; Vaadia, Eilon

2012-01-01

Some motor tasks, if learned together, interfere with each other's consolidation and subsequent retention, whereas other tasks do not. Interfering tasks are said to employ the same internal model whereas noninterfering tasks use different models. The division of function among internal models, as well as their possible neural substrates, are not well understood. To investigate these questions, we compared responses of single cells in the primary motor cortex and premotor cortex of primates to interfering and noninterfering tasks. The interfering tasks were visuomotor rotation followed by opposing visuomotor rotation. The noninterfering tasks were visuomotor rotation followed by an arbitrary association task. Learning two noninterfering tasks led to the simultaneous formation of neural activity typical of both tasks, at the level of single neurons. In contrast, and in accordance with behavioral results, after learning two interfering tasks, only the second task was successfully reflected in motor cortical single cell activity. These results support the hypothesis that the representational capacity of motor cortical cells is the basis of behavioral interference and division between internal models. PMID:22427923

Structural and functional alterations in the brain during working memory in medication-naïve patients at clinical high-risk for psychosis.

PubMed

Gisselgård, Jens; Lebedev, Alexander V; Dæhli Kurz, Kathinka; Joa, Inge; Johannessen, Jan Olav; Brønnick, Kolbjørn

2018-01-01

Several previous studies suggest that clinical high risk for psychosis (CHR) is associated with prefrontal functional abnormalities and more widespread reduced grey matter in prefrontal, temporal and parietal areas. We investigated neural correlates to CHR in medication-naïve patients. 41 CHR patients and 37 healthy controls were examined with 1.5 Tesla MRI, yielding functional scans while performing an N-back task and structural T1-weighted brain images. Functional and structural data underwent automated preprocessing steps in SPM and Freesurfer, correspondingly. The groups were compared employing mass-univariate strategy within the generalized linear modelling framework. CHR demonstrated reduced suppression of the medial temporal lobe (MTL) regions during n-back task. We also found that, consistent with previous findings, CHR subjects demonstrated thinning in prefrontal, cingulate, insular and inferior temporal areas, as well as reduced hippocampal volumes. The present findings add to the growing evidence of specific structural and functional abnormalities in the brain as potential neuroimaging markers of psychosis vulnerability.

A neural joint model for entity and relation extraction from biomedical text.

PubMed

Li, Fei; Zhang, Meishan; Fu, Guohong; Ji, Donghong

2017-03-31

Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above. Our model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction. The proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

A grid to facilitate physics staffing justification.

PubMed

Klein, Eric E

2009-12-03

Justification of clinical physics staffing levels is difficult due to the lack of direction as how to equate clinical needs with the staffing levels and competency required. When a physicist negotiates staffing requests to administration, she/he often refers to American College of Radiology staffing level suggestions, and resources such as the Abt studies. This approach is often met with questions as to how to fairly derive the time it takes to perform tasks. The result is often insufficient and/or inexperienced staff handling complex and cumbersome tasks. We undertook development of a staffing justification grid to equate the clinical needs to the quantity and quality of staffing required. The first step is using the Abt study, customized to the clinical setting, to derive time per task multiplied by the anticipated number of such tasks. Inclusion of vacation, meeting, and developmental time may be incorporated along with allocated time for education and administration. This is followed by mapping the tasks to the level of competency/experience needed. For example, in an academic setting the faculty appointment levels correlate with experience. Non-staff personnel, such as IMRT QA technicians or clerical staff, should also be part of the equation. By using the staffing justification grid, we derived strong documentation to justify a substantial budget increase. The grid also proved useful when our clinical demands changed. Justification for physics staffing can be significantly strengthened with a properly developed data-based time and work analysis. A staffing grid is presented, along with a development methodology that facilitated our justification. Though our grid is for a large academic facility, the methodology can be extended to a non-academic setting, and to a smaller scale. This grid method not only equates the clinical needs with the quantity of staffing, but can also help generate the personnel budget, based on the type of staff and personnel required. The grid is easily adaptable when changes to the clinical environment change, such as an increase in IMRT or IGRT applications.

Comparison of two simulation systems to support robotic-assisted surgical training: a pilot study (Swine model).

PubMed

Whitehurst, Sabrina V; Lockrow, Ernest G; Lendvay, Thomas S; Propst, Anthony M; Dunlow, Susan G; Rosemeyer, Christopher J; Gobern, Joseph M; White, Lee W; Skinner, Anna; Buller, Jerome L

2015-01-01

To compare the efficacy of simulation-based training between the Mimic dV- Trainer and traditional dry lab da Vinci robot training. A prospective randomized study analyzing the performance of 20 robotics-naive participants. Participants were enrolled in an online da Vinci Intuitive Surgical didactic training module, followed by training in use of the da Vinci standard surgical robot. Spatial ability tests were performed as well. Participants were randomly assigned to 1 of 2 training conditions: performance of 3 Fundamentals of Laparoscopic Surgery dry lab tasks using the da Vinci or performance of 4 dV-Trainer tasks. Participants in both groups performed all tasks to empirically establish proficiency criterion. Participants then performed the transfer task, a cystotomy closure using the daVinci robot on a live animal (swine) model. The performance of robotic tasks was blindly assessed by a panel of experienced surgeons using objective tracking data and using the validated Global Evaluative Assessment of Robotic Surgery (GEARS), a structured assessment tool. No statistically significant difference in surgeon performance was found between the 2 training conditions, dV-Trainer and da Vinci robot. Analysis of a 95% confidence interval for the difference in means (-0.803 to 0.543) indicated that the 2 methods are unlikely to differ to an extent that would be clinically meaningful. Based on the results of this study, a curriculum on the dV- Trainer was shown to be comparable to traditional da Vinci robot training. Therefore, we have identified that training on a virtual reality system may be an alternative to live animal training for future robotic surgeons. Published by Elsevier Inc.

Drawing Nomograms with R: applications to categorical outcome and survival data.

PubMed

Zhang, Zhongheng; Kattan, Michael W

2017-05-01

Outcome prediction is a major task in clinical medicine. The standard approach to this work is to collect a variety of predictors and build a model of appropriate type. The model is a mathematical equation that connects the outcome of interest with the predictors. A new patient with given clinical characteristics can be predicted for outcome with this model. However, the equation describing the relationship between predictors and outcome is often complex and the computation requires software for practical use. There is another method called nomogram which is a graphical calculating device allowing an approximate graphical computation of a mathematical function. In this article, we describe how to draw nomograms for various outcomes with nomogram() function. Binary outcome is fit by logistic regression model and the outcome of interest is the probability of the event of interest. Ordinal outcome variable is also discussed. Survival analysis can be fit with parametric model to fully describe the distributions of survival time. Statistics such as the median survival time, survival probability up to a specific time point are taken as the outcome of interest.

Elementary Students' Learning of Materials Science Practices Through Instruction Based on Engineering Design Tasks

NASA Astrophysics Data System (ADS)

Wendell, Kristen Bethke; Lee, Hee-Sun

2010-12-01

Materials science, which entails the practices of selecting, testing, and characterizing materials, is an important discipline within the study of matter. This paper examines how third grade students' materials science performance changes over the course of instruction based on an engineering design challenge. We conducted a case study of nine students who participated in engineering design-based science instruction with the goal of constructing a stable, quiet, thermally comfortable model house. The learning outcome of materials science practices was assessed by clinical interviews conducted before and after the instruction, and the learning process was assessed by students' workbooks completed during the instruction. The interviews included two materials selection tasks for designing a sturdy stepstool and an insulated pet habitat. Results indicate that: (1) students significantly improved on both materials selection tasks, (2) their gains were significantly positively associated with the degree of completion of their workbooks, and (3) students who were highly engaged with the workbook's reflective record-keeping tasks showed the greatest improvement on the interviews. These findings suggest the important role workbooks can play in facilitating elementary students' learning of science through authentic activity such as engineering design.

Executive function and attention are preserved in older surgically menopausal monkeys receiving estrogen or estrogen plus progesterone.

PubMed

Voytko, Mary Lou; Murray, Rhonda; Higgs, Casey J

2009-08-19

Animal models of menopause have been used to further define the cognitive processes that respond to hormone therapy and to investigate parameters that may influence the cognitive effects of estrogen. Many investigations in animals have focused on memory; however, the effects of hormone therapy on executive function and attention processes have not been well studied. Thus, the purpose of this set of investigations was to assess the effects of estrogen therapy alone or with progesterone on executive and attention processes in middle-aged ovariectomized monkeys. Monkeys were preoperatively trained on a modified version of the Wisconsin card sort task and on a visual cued reaction time task. Hormone therapy was initiated at the time of ovariectomy and cognitive function was reassessed at 2, 12, and 24 weeks postoperatively. Relative to monkeys receiving either of the estrogen therapies, monkeys receiving placebo were impaired in their ability to shift a cognitive set in the Wisconsin card sort task and were impaired in shifting visuospatial attention in the visual cued reaction time task. Our findings are consistent with clinical studies that indicate that hormone therapy can improve executive function and attention processes in postmenopausal women.

Revisiting the continuum hypothesis: toward an in-depth exploration of executive functions in korsakoff syndrome.

PubMed

Brion, Mélanie; Pitel, Anne-Lise; Beaunieux, Hélène; Maurage, Pierre

2014-01-01

Korsakoff syndrome (KS) is a neurological state mostly caused by alcohol-dependence and leading to disproportionate episodic memory deficits. KS patients present more severe anterograde amnesia than Alcohol-Dependent Subjects (ADS), which led to the continuum hypothesis postulating a progressive increase in brain and cognitive damages during the evolution from ADS to KS. This hypothesis has been extensively examined for memory but is still debated for other abilities, notably executive functions (EF). EF have up to now been explored by unspecific tasks in KS, and few studies explored their interactions with memory. Exploring EF in KS by specific tasks based on current EF models could thus renew the exploration of the continuum hypothesis. This paper will propose a research program aiming at: (1) clarifying the extent of executive dysfunctions in KS by tasks focusing on specific EF subcomponents; (2) determining the differential EF deficits in ADS and KS; (3) exploring EF-memory interactions in KS with innovative tasks. At the fundamental level, this exploration will test the continuum hypothesis beyond memory. At the clinical level, it will propose new rehabilitation tools focusing on the EF specifically impaired in KS.

Revisiting the Continuum Hypothesis: Toward an In-Depth Exploration of Executive Functions in Korsakoff Syndrome

PubMed Central

Brion, Mélanie; Pitel, Anne-Lise; Beaunieux, Hélène; Maurage, Pierre

2014-01-01

Korsakoff syndrome (KS) is a neurological state mostly caused by alcohol-dependence and leading to disproportionate episodic memory deficits. KS patients present more severe anterograde amnesia than Alcohol-Dependent Subjects (ADS), which led to the continuum hypothesis postulating a progressive increase in brain and cognitive damages during the evolution from ADS to KS. This hypothesis has been extensively examined for memory but is still debated for other abilities, notably executive functions (EF). EF have up to now been explored by unspecific tasks in KS, and few studies explored their interactions with memory. Exploring EF in KS by specific tasks based on current EF models could thus renew the exploration of the continuum hypothesis. This paper will propose a research program aiming at: (1) clarifying the extent of executive dysfunctions in KS by tasks focusing on specific EF subcomponents; (2) determining the differential EF deficits in ADS and KS; (3) exploring EF-memory interactions in KS with innovative tasks. At the fundamental level, this exploration will test the continuum hypothesis beyond memory. At the clinical level, it will propose new rehabilitation tools focusing on the EF specifically impaired in KS. PMID:25071526

Prediction of pilot reserve attention capacity during air-to-air target tracking

NASA Technical Reports Server (NTRS)

Onstott, E. D.; Faulkner, W. H.

1977-01-01

Reserve attention capacity of a pilot was calculated using a pilot model that allocates exclusive model attention according to the ranking of task urgency functions whose variables are tracking error and error rate. The modeled task consisted of tracking a maneuvering target aircraft both vertically and horizontally, and when possible, performing a diverting side task which was simulated by the precise positioning of an electrical stylus and modeled as a task of constant urgency in the attention allocation algorithm. The urgency of the single loop vertical task is simply the magnitude of the vertical tracking error, while the multiloop horizontal task requires a nonlinear urgency measure of error and error rate terms. Comparison of model results with flight simulation data verified the computed model statistics of tracking error of both axes, lateral and longitudinal stick amplitude and rate, and side task episodes. Full data for the simulation tracking statistics as well as the explicit equations and structure of the urgency function multiaxis pilot model are presented.

Integrating Cognitive Task Analysis into Instructional Systems Development.

ERIC Educational Resources Information Center

Ryder, Joan M.; Redding, Richard E.

1993-01-01

Discussion of instructional systems development (ISD) focuses on recent developments in cognitive task analysis and describes the Integrated Task Analysis Model, a framework for integrating cognitive and behavioral task analysis methods within the ISD model. Three components of expertise are analyzed: skills, knowledge, and mental models. (96…

Perceptual learning: toward a comprehensive theory.

PubMed

Watanabe, Takeo; Sasaki, Yuka

2015-01-03

Visual perceptual learning (VPL) is long-term performance increase resulting from visual perceptual experience. Task-relevant VPL of a feature results from training of a task on the feature relevant to the task. Task-irrelevant VPL arises as a result of exposure to the feature irrelevant to the trained task. At least two serious problems exist. First, there is the controversy over which stage of information processing is changed in association with task-relevant VPL. Second, no model has ever explained both task-relevant and task-irrelevant VPL. Here we propose a dual plasticity model in which feature-based plasticity is a change in a representation of the learned feature, and task-based plasticity is a change in processing of the trained task. Although the two types of plasticity underlie task-relevant VPL, only feature-based plasticity underlies task-irrelevant VPL. This model provides a new comprehensive framework in which apparently contradictory results could be explained.

A matrix for the qualitative evaluation of nursing tasks.

PubMed

Durosaiye, Isaiah O; Hadjri, Karim; Liyanage, Champika L; Bennett, Kina

2018-04-01

To formulate a model for patient-nurse interaction; to compile a comprehensive list of nursing tasks on hospital wards; and to construct a nursing tasks demand matrix. The physical demands associated with nursing profession are of growing interest among researchers. Yet, it is the complexity of nursing tasks that defines the demands of ward nurses' role. This study explores nursing tasks, based on patient-nurse interaction on hospital wards. Extant literature was reviewed to formulate a patient-nurse interaction model. Twenty ward nurses were interviewed to compile a list of nursing tasks. These nursing tasks were mapped against the patient-nurse interaction model. A patient-nurse interaction model was created, consisting of: (1) patient care, (2) patient surveillance and (3) patient support. Twenty-three nursing tasks were identified. The nursing tasks demand matrix was constructed. Ward managers may use a nursing tasks demand matrix to determine the demands of nursing tasks on ward nurses. While many studies have explored either the physical or the psychosocial aspects of nursing tasks separately, this study suggests that the physicality of nursing tasks must be evaluated in tandem with their complexity. Ward managers may take a holistic approach to nursing tasks evaluation by using a nursing tasks demand matrix. © 2017 John Wiley & Sons Ltd.

Enhancing clinical concept extraction with distributional semantics

PubMed Central

Cohen, Trevor; Wu, Stephen; Gonzalez, Graciela

2011-01-01

Extracting concepts (such as drugs, symptoms, and diagnoses) from clinical narratives constitutes a basic enabling technology to unlock the knowledge within and support more advanced reasoning applications such as diagnosis explanation, disease progression modeling, and intelligent analysis of the effectiveness of treatment. The recent release of annotated training sets of de-identified clinical narratives has contributed to the development and refinement of concept extraction methods. However, as the annotation process is labor-intensive, training data are necessarily limited in the concepts and concept patterns covered, which impacts the performance of supervised machine learning applications trained with these data. This paper proposes an approach to minimize this limitation by combining supervised machine learning with empirical learning of semantic relatedness from the distribution of the relevant words in additional unannotated text. The approach uses a sequential discriminative classifier (Conditional Random Fields) to extract the mentions of medical problems, treatments and tests from clinical narratives. It takes advantage of all Medline abstracts indexed as being of the publication type “clinical trials” to estimate the relatedness between words in the i2b2/VA training and testing corpora. In addition to the traditional features such as dictionary matching, pattern matching and part-of-speech tags, we also used as a feature words that appear in similar contexts to the word in question (that is, words that have a similar vector representation measured with the commonly used cosine metric, where vector representations are derived using methods of distributional semantics). To the best of our knowledge, this is the first effort exploring the use of distributional semantics, the semantics derived empirically from unannotated text often using vector space models, for a sequence classification task such as concept extraction. Therefore, we first experimented with different sliding window models and found the model with parameters that led to best performance in a preliminary sequence labeling task. The evaluation of this approach, performed against the i2b2/VA concept extraction corpus, showed that incorporating features based on the distribution of words across a large unannotated corpus significantly aids concept extraction. Compared to a supervised-only approach as a baseline, the micro-averaged f-measure for exact match increased from 80.3% to 82.3% and the micro-averaged f-measure based on inexact match increased from 89.7% to 91.3%. These improvements are highly significant according to the bootstrap resampling method and also considering the performance of other systems. Thus, distributional semantic features significantly improve the performance of concept extraction from clinical narratives by taking advantage of word distribution information obtained from unannotated data. PMID:22085698

Task sharing of a psychological intervention for maternal depression in Khayelitsha, South Africa: study protocol for a randomized controlled trial.

PubMed

Lund, Crick; Schneider, Marguerite; Davies, Thandi; Nyatsanza, Memory; Honikman, Simone; Bhana, Arvin; Bass, Judith; Bolton, Paul; Dewey, Michael; Joska, John; Kagee, Ashraf; Myer, Landon; Petersen, Inge; Prince, Martin; Stein, Dan J; Thornicroft, Graham; Tomlinson, Mark; Alem, Atalay; Susser, Ezra

2014-11-21

Maternal depression carries a major public health burden for mothers and their infants, yet there is a substantial treatment gap for this condition in low-resourced regions such as sub-Saharan Africa. To address this treatment gap, the strategy of "task sharing" has been proposed, involving the delivery of interventions by non-specialist health workers trained and supervised by specialists in routine healthcare delivery systems. Several psychological interventions have shown benefit in treating maternal depression, but few have been rigorously evaluated using a task sharing approach. The proposed trial will be the first randomised controlled trial (RCT) evaluating a task sharing model of delivering care for women with maternal depression in sub-Saharan Africa. The objective of this RCT is to determine the effectiveness and cost-effectiveness of a task sharing counseling intervention for maternal depression in South Africa. The study is an individual-level two-arm RCT. A total of 420 depressed pregnant women will be recruited from two ante-natal clinics in a low-income township area of Cape Town, using the Edinburgh Postnatal Depression Scale to screen for depression; 210 women will be randomly allocated to each of the intervention and control arms. The intervention group will be given six sessions of basic counseling over a period of 3 to 4 months, provided by trained community health workers (CHW)s. The control group will receive three monthly phone calls from a CHW trained to conduct phone calls but not basic counseling. The primary outcome measure is the 17-Item Hamilton Depression Rating Scale (HDRS-17). The outcome measures will be applied at the baseline assessment, and at three follow-up points: 1 month before delivery, and 3 and 12 months after delivery. The primary analysis will be by intention-to-treat and secondary analyses will be on a per protocol population. The primary outcome measure will be analyzed using linear regression adjusting for baseline symptom severity measured using the HDRS-17. The findings of this trial can provide policy makers with evidence regarding the effectiveness and cost-effectiveness of structured psychological interventions for maternal depression delivered by appropriately trained and supervised non-specialist CHWs in sub-Saharan Africa. Clinical Trials (ClinicalTrials.gov): NCT01977326, registered on 24/10/2013; Pan African Clinical Trials Registry (http://www.pactr.org): PACTR201403000676264, registered on 11/10/2013.

Hidden Markov model analysis of force/torque information in telemanipulation

NASA Technical Reports Server (NTRS)

Hannaford, Blake; Lee, Paul

1991-01-01

A model for the prediction and analysis of sensor information recorded during robotic performance of telemanipulation tasks is presented. The model uses the hidden Markov model to describe the task structure, the operator's or intelligent controller's goal structure, and the sensor signals. A methodology for constructing the model parameters based on engineering knowledge of the task is described. It is concluded that the model and its optimal state estimation algorithm, the Viterbi algorithm, are very succesful at the task of segmenting the data record into phases corresponding to subgoals of the task. The model provides a rich modeling structure within a statistical framework, which enables it to represent complex systems and be robust to real-world sensory signals.

Altered intrinsic and extrinsic connectivity in schizophrenia.

PubMed

Zhou, Yuan; Zeidman, Peter; Wu, Shihao; Razi, Adeel; Chen, Cheng; Yang, Liuqing; Zou, Jilin; Wang, Gaohua; Wang, Huiling; Friston, Karl J

2018-01-01

Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia.

Ultrasound image filtering using the mutiplicative model

NASA Astrophysics Data System (ADS)

Navarrete, Hugo; Frery, Alejandro C.; Sanchez, Fermin; Anto, Joan

2002-04-01

Ultrasound images, as a special case of coherent images, are normally corrupted with multiplicative noise i.e. speckle noise. Speckle noise reduction is a difficult task due to its multiplicative nature, but good statistical models of speckle formation are useful to design adaptive speckle reduction filters. In this article a new statistical model, emerging from the Multiplicative Model framework, is presented and compared to previous models (Rayleigh, Rice and K laws). It is shown that the proposed model gives the best performance when modeling the statistics of ultrasound images. Finally, the parameters of the model can be used to quantify the extent of speckle formation; this quantification is applied to adaptive speckle reduction filter design. The effectiveness of the filter is demonstrated on typical in-vivo log-compressed B-scan images obtained by a clinical ultrasound system.

Computer-generated reminders and quality of pediatric HIV care in a resource-limited setting.

PubMed

Were, Martin C; Nyandiko, Winstone M; Huang, Kristin T L; Slaven, James E; Shen, Changyu; Tierney, William M; Vreeman, Rachel C

2013-03-01

To evaluate the impact of clinician-targeted computer-generated reminders on compliance with HIV care guidelines in a resource-limited setting. We conducted this randomized, controlled trial in an HIV referral clinic in Kenya caring for HIV-infected and HIV-exposed children (<14 years of age). For children randomly assigned to the intervention group, printed patient summaries containing computer-generated patient-specific reminders for overdue care recommendations were provided to the clinician at the time of the child's clinic visit. For children in the control group, clinicians received the summaries, but no computer-generated reminders. We compared differences between the intervention and control groups in completion of overdue tasks, including HIV testing, laboratory monitoring, initiating antiretroviral therapy, and making referrals. During the 5-month study period, 1611 patients (49% female, 70% HIV-infected) were eligible to receive at least 1 computer-generated reminder (ie, had an overdue clinical task). We observed a fourfold increase in the completion of overdue clinical tasks when reminders were availed to providers over the course of the study (68% intervention vs 18% control, P < .001). Orders also occurred earlier for the intervention group (77 days, SD 2.4 days) compared with the control group (104 days, SD 1.2 days) (P < .001). Response rates to reminders varied significantly by type of reminder and between clinicians. Clinician-targeted, computer-generated clinical reminders are associated with a significant increase in completion of overdue clinical tasks for HIV-infected and exposed children in a resource-limited setting.

Motivation and Performance within a Collaborative Computer-Based Modeling Task: Relations between Students' Achievement Goal Orientation, Self-Efficacy, Cognitive Processing, and Achievement

ERIC Educational Resources Information Center

Sins, Patrick H. M.; van Joolingen, Wouter R.; Savelsbergh, Elwin R.; van Hout-Wolters, Bernadette

2008-01-01

Purpose of the present study was to test a conceptual model of relations among achievement goal orientation, self-efficacy, cognitive processing, and achievement of students working within a particular collaborative task context. The task involved a collaborative computer-based modeling task. In order to test the model, group measures of…

Evaluation of Ground Vibrations Induced by Military Noise Sources

DTIC Science & Technology

2006-08-01

1 Task 2—Determine the acoustic -to-seismic coupling coefficients C1 and C2 ...................... 1 Task 3—Computational modeling ...Determine the acoustic -to-seismic coupling coefficients C1 and C2 ....................45 Task 3—Computational modeling of acoustically induced ground...ground conditions. Task 3—Computational modeling of acoustically induced ground motion The simple model of blast sound interaction with the

Unexpected Dual Task Benefits on Cycling in Parkinson Disease and Healthy Adults: A Neuro-Behavioral Model

PubMed Central

Altmann, Lori J. P.; Stegemöller, Elizabeth; Hazamy, Audrey A.; Wilson, Jonathan P.; Okun, Michael S.; McFarland, Nikolaus R.; Shukla, Aparna Wagle; Hass, Chris J.

2015-01-01

Background When performing two tasks at once, a dual task, performance on one or both tasks typically suffers. People with Parkinson’s disease (PD) usually experience larger dual task decrements on motor tasks than healthy older adults (HOA). Our objective was to investigate the decrements in cycling caused by performing cognitive tasks with a range of difficulty in people with PD and HOAs. Methods Twenty-eight participants with Parkinson’s disease and 20 healthy older adults completed a baseline cycling task with no secondary tasks and then completed dual task cycling while performing 12 tasks from six cognitive domains representing a wide range of difficulty. Results Cycling was faster during dual task conditions than at baseline, and was significantly faster for six tasks (all p<.02) across both groups. Cycling speed improved the most during the easiest cognitive tasks, and cognitive performance was largely unaffected. Cycling improvement was predicted by task difficulty (p<.001). People with Parkinson’s disease cycled slower (p<.03) and showed reduced dual task benefits (p<.01) than healthy older adults. Conclusions Unexpectedly, participants’ motor performance improved during cognitive dual tasks, which cannot be explained in current models of dual task performance. To account for these findings, we propose a model integrating dual task and acute exercise approaches which posits that cognitive arousal during dual tasks increases resources to facilitate motor and cognitive performance, which is subsequently modulated by motor and cognitive task difficulty. This model can explain both the improvement observed on dual tasks in the current study and more typical dual task findings in other studies. PMID:25970607

Claretian Medical Center Task Analysis. Worker Education Program.

ERIC Educational Resources Information Center

Union of Needletrades, Industrial and Textile Employees.

This task analysis for positions at the Claretian Medical Center in southeast Chicago was developed to improve communication and customer service in the workplace. The task analysis was prepared through clinic tours, employee interviews, and supervisor questionnaires. It is used for the purpose of curriculum development for onsite instruction in…

Wayfinding and Glaucoma: A Virtual Reality Experiment.

PubMed

Daga, Fábio B; Macagno, Eduardo; Stevenson, Cory; Elhosseiny, Ahmed; Diniz-Filho, Alberto; Boer, Erwin R; Schulze, Jürgen; Medeiros, Felipe A

2017-07-01

Wayfinding, the process of determining and following a route between an origin and a destination, is an integral part of everyday tasks. The purpose of this study was to investigate the impact of glaucomatous visual field loss on wayfinding behavior using an immersive virtual reality (VR) environment. This cross-sectional study included 31 glaucomatous patients and 20 healthy subjects without evidence of overall cognitive impairment. Wayfinding experiments were modeled after the Morris water maze navigation task and conducted in an immersive VR environment. Two rooms were built varying only in the complexity of the visual scene in order to promote allocentric-based (room A, with multiple visual cues) versus egocentric-based (room B, with single visual cue) spatial representations of the environment. Wayfinding tasks in each room consisted of revisiting previously visible targets that subsequently became invisible. For room A, glaucoma patients spent on average 35.0 seconds to perform the wayfinding task, whereas healthy subjects spent an average of 24.4 seconds (P = 0.001). For room B, no statistically significant difference was seen on average time to complete the task (26.2 seconds versus 23.4 seconds, respectively; P = 0.514). For room A, each 1-dB worse binocular mean sensitivity was associated with 3.4% (P = 0.001) increase in time to complete the task. Glaucoma patients performed significantly worse on allocentric-based wayfinding tasks conducted in a VR environment, suggesting visual field loss may affect the construction of spatial cognitive maps relevant to successful wayfinding. VR environments may represent a useful approach for assessing functional vision endpoints for clinical trials of emerging therapies in ophthalmology.

Detailed analysis of the supermarket task included on the Japanese version of the Rapid Dementia Screening Test.

PubMed

Moriyama, Yasushi; Yoshino, Aihide; Muramatsu, Taro; Mimura, Masaru

2017-05-01

The supermarket task, which is included in the Japanese version of the Rapid Dementia Screening Test, requires the quick (1 min) generation of words for things that can be bought in a supermarket. Cluster size and switches are investigated during this task. We investigated how the severity of dementia related to cluster size and switches on the supermarket task in patients with Alzheimer's disease. We administered the Japanese version of the Rapid Dementia Screening Test to 250 patients with very mild to severe Alzheimer's disease and to 49 healthy volunteers. Patients had Mini-Mental State Examination scores from 12 to 26 and Clinical Dementia Rating scale scores from 0.5 to 3. Patients were divided into four groups based on their Clinical Dementia Rating score (0.5, 1, 2, 3). We performed statistical analyses between the four groups and control subjects based on cluster size and switch scores on the supermarket task. The score for cluster size and switches deteriorated according to the severity of dementia. Moreover, for subjects with a Clinical Dementia Rating score of 0.5, cluster size was impaired, but switches were intact. Our findings indicate that the scores for cluster size and switches on the supermarket task may be useful for detecting the severity of symptoms of dementia in patients with Alzheimer's disease. © 2016 The Authors. Psychogeriatrics © 2016 Japanese Psychogeriatric Society.

Task uncertainty and communication during nursing shift handovers.

PubMed

Mayor, Eric; Bangerter, Adrian; Aribot, Myriam

2012-09-01

We explore variations in handover duration and communication in nursing units. We hypothesize that duration per patient is higher in units facing high task uncertainty. We expect both topics and functions of communication to vary depending on task uncertainty. Handovers are changing in modern healthcare organizations, where standardized procedures are increasingly advocated for efficiency and reliability reasons. However, redesign of handover should take environmental contingencies of different clinical unit types into account. An important contingency in institutions is task uncertainty, which may affect how communicative routines like handover are accomplished. Nurse unit managers of 80 care units in 18 hospitals were interviewed in 2008 about topics and functions of handover communication and duration in their unit. Interviews were content-analysed. Clinical units were classified into a theory-based typology (unit type) that gradually increases on task uncertainty. Quantitative analyses were performed. Unit type affected resource allocation. Unit types facing higher uncertainty had higher handover duration per patient. As expected, unit type also affected communication content. Clinical units facing higher uncertainty discussed fewer topics, discussing treatment and care and organization of work less frequently. Finally, unit type affected functions of handover: sharing emotions was less often mentioned in unit types facing higher uncertainty. Task uncertainty and its relationship with functions and topics of handover should be taken into account during the design of handover procedures. © 2011 Blackwell Publishing Ltd.

The Association between Dual-Task Gait after Concussion and Prolonged Symptom Duration.

PubMed

Howell, David R; Brilliant, Anna; Berkstresser, Brant; Wang, Francis; Fraser, Joana; Meehan, William P

2017-12-01

Quantitative gait measurements can identify persistent postconcussion impairments. However, their prognostic utility after injury to identify the likelihood of prolonged concussion symptoms remains unknown. Our objective was to examine if dual-task gait performance measures are independently associated with persistent (> 28 days) concussion symptoms among a sample of athletes. Sixty individuals diagnosed with a sport-related concussion were assessed within 10 days of their injury. Each participant completed a postconcussion symptom scale, an injury history questionnaire, and a single/dual-task gait examination. They were followed until they no longer reported symptoms, and the duration of time required for symptom resolution was calculated. A binary multivariable logistic regression model determined the independent association between dual-task gait and symptom duration (≤ 28 days vs. >28 days) while controlling for the effect of gender, age, symptom severity, injury-to-examination time, and history of concussion. Seventeen (28%) participants reported a symptom duration >28 days. The dual-task cost for average gait speed (-25.9 ± 9.5% vs. -19.8 ± 8.9%; p = 0.027) and cadence (-18.0 ± 2.9% vs. -12.0 ± 7.7%; p = 0.029) was significantly greater among participants who experienced symptoms for >28 days. After adjusting for potential confounding variables, greater dual-task average gait speed costs were independently associated with prolonged symptom duration (aOR = 0.908; 95% CI = 0.835-0.987). Examinations of dual-task gait may provide useful information during multifaceted concussion examinations. Quantitative assessments that simultaneously test multiple domains, such as dual tasks, may be clinically valuable after a concussion to identify those more likely to experience symptoms for >28 days after injury.

A Novel Multisensory Integration Task Reveals Robust Deficits in Rodent Models of Schizophrenia: Converging Evidence for Remediation via Nicotinic Receptor Stimulation of Inhibitory Transmission in the Prefrontal Cortex.

PubMed

Cloke, Jacob M; Nguyen, Robin; Chung, Beryl Y T; Wasserman, David I; De Lisio, Stephanie; Kim, Jun Chul; Bailey, Craig D C; Winters, Boyer D

2016-12-14

Atypical multisensory integration is an understudied cognitive symptom in schizophrenia. Procedures to evaluate multisensory integration in rodent models are lacking. We developed a novel multisensory object oddity (MSO) task to assess multisensory integration in ketamine-treated rats, a well established model of schizophrenia. Ketamine-treated rats displayed a selective MSO task impairment with tactile-visual and olfactory-visual sensory combinations, whereas basic unisensory perception was unaffected. Orbitofrontal cortex (OFC) administration of nicotine or ABT-418, an α 4 β 2 nicotinic acetylcholine receptor (nAChR) agonist, normalized MSO task performance in ketamine-treated rats and this effect was blocked by GABA A receptor antagonism. GABAergic currents were also decreased in OFC of ketamine-treated rats and were normalized by activation of α 4 β 2 nAChRs. Furthermore, parvalbumin (PV) immunoreactivity was decreased in the OFC of ketamine-treated rats. Accordingly, silencing of PV interneurons in OFC of PV-Cre mice using DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) selectively impaired MSO task performance and this was reversed by ABT-418. Likewise, clozapine-N-oxide-induced inhibition of PV interneurons in brain slices was reversed by activation of α 4 β 2 nAChRs. These findings strongly imply a role for prefrontal GABAergic transmission in the integration of multisensory object features, a cognitive process with relevance to schizophrenia. Accordingly, nAChR agonism, which improves various facets of cognition in schizophrenia, reversed the severe MSO task impairment in this study and appears to do so via a GABAergic mechanism. Interactions between GABAergic and nAChR receptor systems warrant further investigation for potential therapeutic applications. The novel behavioral procedure introduced in the current study is acutely sensitive to schizophrenia-relevant cognitive impairment and should prove highly valuable for such research. Adaptive behaviors are driven by integration of information from different sensory modalities. Multisensory integration is disrupted in patients with schizophrenia, but little is known about the neural basis of this cognitive symptom. Development and validation of multisensory integration tasks for animal models is essential given the strong link between functional outcome and cognitive impairment in schizophrenia. We present a novel multisensory object oddity procedure that detects selective multisensory integration deficits in a rat model of schizophrenia using various combinations of sensory modalities. Moreover, converging data are consistent with a nicotinic-GABAergic mechanism of multisensory integration in the prefrontal cortex, results with strong clinical relevance to the study of cognitive impairment and treatment in schizophrenia. Copyright © 2016 the authors 0270-6474/16/3612571-16$15.00/0.

Upper-Extremity Dual-Task Function: An Innovative Method to Assess Cognitive Impairment in Older Adults.

PubMed

Toosizadeh, Nima; Najafi, Bijan; Reiman, Eric M; Mager, Reine M; Veldhuizen, Jaimeson K; O'Connor, Kathy; Zamrini, Edward; Mohler, Jane

2016-01-01

Difficulties in orchestrating simultaneous tasks (i.e., dual-tasking) have been associated with cognitive impairments in older adults. Gait tests have been commonly used as the motor task component for dual-task assessments; however, many older adults have mobility impairments or there is a lack of space in busy clinical settings. We assessed an upper-extremity function (UEF) test as an alternative motor task to study the dual-task motor performance in older adults. Older adults (≥65 years) were recruited, and cognitive ability was measured using the Montreal cognitive assessment (MoCA). Participants performed repetitive elbow flexion with their maximum pace, once single-task, and once while counting backward by one (dual-task). Single- and dual-task gait tests were also performed with normal speed. Three-dimensional kinematics was measured both from upper-extremity and lower-extremity using wearable sensors to determine UEF and gait parameters. Parameters were compared between the cognitively impaired and healthy groups using analysis of variance tests, while controlling for age, gender, and body mass index (BMI). Correlations between UEF and gait parameters for dual-task and dual-task cost were assessed using linear regression models. Sixty-seven older adults were recruited (age = 83 ± 10 years). Based on MoCA, 10 (15%) were cognitively impaired. While no significant differences were observed in the single-task condition, within the dual-task condition, the cognitively impaired group showed significantly less arm flexion speed (62%, d = 1.51, p = 0.02) and range of motion (27%, d = 0.93, p = 0.04), and higher speed variability (88%, d = 1.82, p < 0.0001) compared to the cognitively intact group, when adjusted with age, gender, and BMI. Significant correlations were observed between UEF speed parameters and gait stride velocity for dual-task condition (r = 0.55, p < 0.0001) and dual-task cost (r = 0.28, p = 0.03). We introduced a novel test for assessing dual-task performance in older adults that lasts 20 s and is based on upper-extremity function. Our results confirm significant associations between upper-extremity speed, range of motion, and speed variability with both the MoCA score and the gait performance within the dual-task condition.

Upper-Extremity Dual-Task Function: An Innovative Method to Assess Cognitive Impairment in Older Adults

PubMed Central

Toosizadeh, Nima; Najafi, Bijan; Reiman, Eric M.; Mager, Reine M.; Veldhuizen, Jaimeson K.; O’Connor, Kathy; Zamrini, Edward; Mohler, Jane

2016-01-01

Background: Difficulties in orchestrating simultaneous tasks (i.e., dual-tasking) have been associated with cognitive impairments in older adults. Gait tests have been commonly used as the motor task component for dual-task assessments; however, many older adults have mobility impairments or there is a lack of space in busy clinical settings. We assessed an upper-extremity function (UEF) test as an alternative motor task to study the dual-task motor performance in older adults. Methods: Older adults (≥65 years) were recruited, and cognitive ability was measured using the Montreal cognitive assessment (MoCA). Participants performed repetitive elbow flexion with their maximum pace, once single-task, and once while counting backward by one (dual-task). Single- and dual-task gait tests were also performed with normal speed. Three-dimensional kinematics was measured both from upper-extremity and lower-extremity using wearable sensors to determine UEF and gait parameters. Parameters were compared between the cognitively impaired and healthy groups using analysis of variance tests, while controlling for age, gender, and body mass index (BMI). Correlations between UEF and gait parameters for dual-task and dual-task cost were assessed using linear regression models. Results: Sixty-seven older adults were recruited (age = 83 ± 10 years). Based on MoCA, 10 (15%) were cognitively impaired. While no significant differences were observed in the single-task condition, within the dual-task condition, the cognitively impaired group showed significantly less arm flexion speed (62%, d = 1.51, p = 0.02) and range of motion (27%, d = 0.93, p = 0.04), and higher speed variability (88%, d = 1.82, p < 0.0001) compared to the cognitively intact group, when adjusted with age, gender, and BMI. Significant correlations were observed between UEF speed parameters and gait stride velocity for dual-task condition (r = 0.55, p < 0.0001) and dual-task cost (r = 0.28, p = 0.03). Conclusion: We introduced a novel test for assessing dual-task performance in older adults that lasts 20 s and is based on upper-extremity function. Our results confirm significant associations between upper-extremity speed, range of motion, and speed variability with both the MoCA score and the gait performance within the dual-task condition. PMID:27458374

Cognitive task analysis: harmonizing tasks to human capacities.

PubMed

Neerincx, M A; Griffioen, E

1996-04-01

This paper presents the development of a cognitive task analysis that assesses the task load of jobs and provides indicators for the redesign of jobs. General principles of human task performance were selected and, subsequently, integrated into current task modelling techniques. The resulting cognitive task analysis centres around four aspects of task load: the number of actions in a period, the ratio between knowledge- and rule-based actions, lengthy uninterrupted actions, and momentary overloading. The method consists of three stages: (1) construction of a hierarchical task model, (2) a time-line analysis and task load assessment, and (3), if necessary, adjustment of the task model. An application of the cognitive task analysis in railway traffic control showed its benefits over the 'old' task load analysis of the Netherlands Railways. It provided a provisional standard for traffic control jobs, conveyed two load risks -- momentary overloading and underloading -- and resulted in proposals to satisfy the standard and to diminish the two load risk.

Performance-based workload assessment: Allocation strategy and added task sensitivity

NASA Technical Reports Server (NTRS)

Vidulich, Michael A.

1990-01-01

The preliminary results of a research program investigating the use of added tasks to evaluate mental workload are reviewed. The focus of the first studies was a reappraisal of the traditional secondary task logic that encouraged the use of low-priority instructions for the added task. It was believed that such low-priority tasks would encourage subjects to split their available resources among the two tasks. The primary task would be assigned all the resources it needed, and any remaining reserve capacity would be assigned to the secondary task. If the model were correct, this approach was expected to combine sensitivity to primary task difficulty with unintrusiveness to primary task performance. The first studies of the current project demonstrated that a high-priority added task, although intrusive, could be more sensitive than the traditional low-priority secondary task. These results suggested that a more appropriate model of the attentional effects associated with added task performance might be based on capacity switching, rather than the traditional optimal allocation model.

Teaching Veterinary Anesthesia: A Survey-Based Evaluation of Two High-Fidelity Models and Live-Animal Experience for Undergraduate Veterinary Students.

PubMed

Musk, Gabrielle C; Collins, Teresa; Hosgood, Giselle

In veterinary medical education, reduction, replacement, and refinement (the three Rs) must be considered. Three clinical skills in anesthesia were identified as challenging to students: endotracheal intubation, intravenous catheterization, and drug dose calculations. The aims of this project were to evaluate students' perception of their level of confidence in performing these three clinical skills in veterinary anesthesia, to document the extent of students' previous experience in performing these three tasks, and to describe students' emotional states during this training. Veterinary students completed a series of four surveys over the period of their pre-clinical training to evaluate the usefulness of high-fidelity models for skill acquisition in endotracheal intubation and intravenous catheterization. In addition, practice and ongoing assessment in drug dose calculations were performed. The curriculum during this period of training progressed from lectures and non-animal training, to anesthesia of pigs undergoing surgery from which they did not recover, and finally to anesthesia of dogs and cats in a neutering clinic. The level of confidence for each of the three clinical skills increased over the study period. For each skill, the number of students with no confidence decreased to zero and the proportion of students with higher levels of confidence increased. The high-fidelity models for endotracheal intubation and intravenous catheterization used to complement the live-animal teaching were considered a useful adjunct to the teaching of clinical skills in veterinary anesthesia. With practice, students became more confident performing drug dose calculations.

Predicting clinical symptoms of attention deficit hyperactivity disorder based on temporal patterns between and within intrinsic connectivity networks.

PubMed

Wang, Xun-Heng; Jiao, Yun; Li, Lihua

2017-10-24

Attention deficit hyperactivity disorder (ADHD) is a common brain disorder with high prevalence in school-age children. Previously developed machine learning-based methods have discriminated patients with ADHD from normal controls by providing label information of the disease for individuals. Inattention and impulsivity are the two most significant clinical symptoms of ADHD. However, predicting clinical symptoms (i.e., inattention and impulsivity) is a challenging task based on neuroimaging data. The goal of this study is twofold: to build predictive models for clinical symptoms of ADHD based on resting-state fMRI and to mine brain networks for predictive patterns of inattention and impulsivity. To achieve this goal, a cohort of 74 boys with ADHD and a cohort of 69 age-matched normal controls were recruited from the ADHD-200 Consortium. Both structural and resting-state fMRI images were obtained for each participant. Temporal patterns between and within intrinsic connectivity networks (ICNs) were applied as raw features in the predictive models. Specifically, sample entropy was taken asan intra-ICN feature, and phase synchronization (PS) was used asan inter-ICN feature. The predictive models were based on the least absolute shrinkage and selectionator operator (LASSO) algorithm. The performance of the predictive model for inattention is r=0.79 (p<10 -8 ), and the performance of the predictive model for impulsivity is r=0.48 (p<10 -8 ). The ICN-related predictive patterns may provide valuable information for investigating the brain network mechanisms of ADHD. In summary, the predictive models for clinical symptoms could be beneficial for personalizing ADHD medications. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

FRAX® International Task Force of the 2010 Joint International Society for Clinical Densitometry & International Osteoporosis Foundation Position Development Conference.

PubMed

Cauley, Jane A; El-Hajj Fuleihan, Ghada; Luckey, Marjorie M

2011-01-01

Osteoporosis is a serious worldwide epidemic. FRAX® is a web-based tool developed by the Sheffield WHO Collaborating Center team, that integrates clinical risk factors and femoral neck BMD and calculates the 10 year fracture probability in order to help health care professionals identify patients who need treatment. However, only 31 countries have a FRAX® calculator. In the absence of a FRAX® model for a particular country, it has been suggested to use a surrogate country for which the epidemiology of osteoporosis most closely approximates the index country. More specific recommendations for clinicians in these countries are not available. In North America, concerns have also been raised regarding the assumptions used to construct the US ethnic specific FRAX® calculators with respect to the correction factors applied to derive fracture probabilities in Blacks, Asians and Hispanics in comparison to Whites. In addition, questions were raised about calculating fracture risk in other ethnic groups e.g., Native Americans and First Canadians. The International Society for Clinical Densitometry (ISCD) in conjunction with the International Osteoporosis Foundation (IOF) assembled an international panel of experts that ultimately developed joint Official Positions of the ISCD and IOF advising clinicians regarding FRAX® usage. As part of the process, the charge of the FRAX® International Task Force was to review and synthesize data regarding geographic and race/ethnic variability in hip fractures, non-hip osteoporotic fractures, and make recommendations about the use of FRAX® in ethnic groups and countries without a FRAX® calculator. This synthesis was presented to the expert panel and constitutes the data on which the subsequent Official Positions are predicated. A summary of the International Task Force composition and charge is presented here. Copyright © 2011 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Official Positions for FRAX® clinical regarding international differences from Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

PubMed

Cauley, Jane A; El-Hajj Fuleihan, Ghada; Arabi, Asma; Fujiwara, Saeko; Ragi-Eis, Sergio; Calderon, Andrew; Chionh, Siok Bee; Chen, Zhao; Curtis, Jeffrey R; Danielson, Michelle E; Hanley, David A; Kroger, Heikki; Kung, Annie W C; Lesnyak, Olga; Nieves, Jeri; Pluskiewicz, Wojciech; El Rassi, Rola; Silverman, Stuart; Schott, Anne-Marie; Rizzoli, Rene; Luckey, Marjorie

2011-01-01

Osteoporosis is a serious worldwide epidemic. Increased risk of fractures is the hallmark of the disease and is associated with increased morbidity, mortality and economic burden. FRAX® is a web-based tool developed by the Sheffield WHO Collaborating Center team, that integrates clinical risk factors, femoral neck BMD, country specific mortality and fracture data and calculates the 10 year fracture probability in order to help health care professionals identify patients who need treatment. However, only 31 countries have a FRAX® calculator at the time paper was accepted for publication. In the absence of a FRAX® model for a particular country, it has been suggested to use a surrogate country for which the epidemiology of osteoporosis most closely approximates the index country. More specific recommendations for clinicians in these countries are not available. In North America, concerns have also been raised regarding the assumptions used to construct the US ethnic specific FRAX® calculators with respect to the correction factors applied to derive fracture probabilities in Blacks, Asians and Hispanics in comparison to Whites. In addition, questions were raised about calculating fracture risk in other ethnic groups e.g., Native Americans and First Canadians. In order to provide additional guidance to clinicians, a FRAX® International Task Force was formed to address specific questions raised by physicians in countries without FRAX® calculators and seeking to integrate FRAX® into their clinical practice. The main questions that the task force tried to answer were the following: The Task Force members conducted appropriate literature reviews and developed preliminary statements that were discussed and graded by a panel of experts at the ISCD-IOF joint conference. The statements approved by the panel of experts are discussed in the current paper. Copyright © 2011. Published by Elsevier Inc.

Evaluating the effect of distractions in the operating room on clinical decision-making and patient safety.

PubMed

Murji, Ally; Luketic, Lea; Sobel, Mara L; Kulasegaram, Kulamakan Mahan; Leyland, Nicholas; Posner, Glenn

2016-10-01

Answering telephone calls and pagers is common distraction in the operating room. We sought to evaluate the impact of distractions on patient care by (1) assessing the accuracy and safety of responses to clinical questions posed to a surgeon while operating and (2) determining whether pager distractions affect simulation-based surgical performance. We conducted a randomized crossover study of obstetrics and gynecology residents. After studying a patient sign-out list, subjects performed a virtual salpingectomy. They were randomized to a distraction phase followed by quiet phase or vice versa. In the distraction phase, a pager beeped and subjects were asked questions based on the sign-out list. Accuracy of responses and the number of unsafe responses were recorded. In the quiet phase, trainees performed the task uninterrupted. Measures of surgical performance were successful task completion, time to task completion and operative blood loss. The mean score for correct responses to clinical questions during the distracted phase was 80 % (SD ±14 %). Nineteen residents (63 %) made at least 1 unsafe clinical decision while operating on the simulator (range 0-3). Subjects were more likely to successfully complete the surgical task in the allotted time under the quiet compared to distraction condition (OR 11.3, p = 0.03). There was no difference between the conditions in paired analysis for mean time (seconds) to task completion [426 (SD 133) vs. 440 (SD 186), p = 0.61] and mean operative blood loss (mL) [73.14 (SD 106) vs. 112.70 (SD 358), p = 0.47]. Distractions in the operating room may have a profound impact on patient safety on the wards. While multitasking in a simulated setting, the majority of residents made at least one unsafe clinical decision. Pager distractions also hindered surgical residents' ability to complete a simulated laparoscopic task in the allotted time without affecting other variables of surgical performance.

Validation of time to task performance assessment method in simulation: A comparative design study.

PubMed

Shinnick, Mary Ann; Woo, Mary A

2018-05-01

There is a lack of objective and valid measures for assessing nursing clinical competence which could adversely impact patient safety. Therefore, we evaluated an objective assessment of clinical competence, Time to Task (ability to perform specific, critical nursing care activities within 5 min), and compared it to two subjective measures, (Lasater Clinical Judgement Rubric [LCJR] and common "pass/fail" assessment). Using a prospective, "Known Groups" (Expert vs. Novice nurses) comparative design, Expert nurses (ICU nurses with >5 years of ICU experience) and Novice nurses (senior prelicensure nursing students) participated individually in a simulation of a patient in decompensated heart failure. Fourteen nursing instructors or preceptors, blinded to group assignment, reviewed 28 simulation videos (15 Expert and 13 Novice) and scored them using the LCJR and pass/fail assessments. Time to Task assessment was scored based on time thresholds for specific nursing actions prospectively set by an expert clinical panel. Statistical analysis consisted of Medians Test and sensitivity and specificity analyses. The LCJR total score was significantly different between Experts and Novices (p < 0.01) and revealed adequate sensitivity (ability to correctly identify "Expert" nurses; 0.72) but had a low specificity (ability to correctly identify "Novice" nurses; 0.40). For the subjective measure 'pass/fail', sensitivity was high (0.90) but specificity was low (0.47). The Time to Task measure had statistical significance between Expert and Novice groups (p < 0.01) and sensitivity (0.80) and specificity (0.85) were good. Commonly used subjective measures of clinical nursing competence have difficulties with achieving acceptable specificity. However, an objective measure, Time to Task, had good sensitivity and specificity in differentiating between groups. While more than one assessment instrument should be used to determine nurse competency, an objective measure, such as Time to Task, warrants further study. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization of medical imaging display systems: using the channelized Hotelling observer for detecting lung nodules: experimental study

NASA Astrophysics Data System (ADS)

Platisa, Ljiljana; Vansteenkiste, Ewout; Goossens, Bart; Marchessoux, Cédric; Kimpe, Tom; Philips, Wilfried

2009-02-01

Medical-imaging systems are designed to aid medical specialists in a specific task. Therefore, the physical parameters of a system need to optimize the task performance of a human observer. This requires measurements of human performance in a given task during the system optimization. Typically, psychophysical studies are conducted for this purpose. Numerical observer models have been successfully used to predict human performance in several detection tasks. Especially, the task of signal detection using a channelized Hotelling observer (CHO) in simulated images has been widely explored. However, there are few studies done for clinically acquired images that also contain anatomic noise. In this paper, we investigate the performance of a CHO in the task of detecting lung nodules in real radiographic images of the chest. To evaluate variability introduced by the limited available data, we employ a commonly used study of a multi-reader multi-case (MRMC) scenario. It accounts for both case and reader variability. Finally, we use the "oneshot" methods to estimate the MRMC variance of the area under the ROC curve (AUC). The obtained AUC compares well to those reported for human observer study on a similar data set. Furthermore, the "one-shot" analysis implies a fairly consistent performance of the CHO with the variance of AUC below 0.002. This indicates promising potential for numerical observers in optimization of medical imaging displays and encourages further investigation on the subject.

Large sex difference in adolescents on a timed line judgment task: attentional contributors and task relationship to mathematics.

PubMed

Collaer, Marcia L; Hill, Erica M

2006-01-01

Visuospatial performance, assessed with the new, group-administered Judgment of Line Angle and Position test (JLAP-13), varied with sex and mathematical competence in a group of adolescents. The JLAP-13, a low-level perceptual task, was modeled after a neuropsychological task dependent upon functioning of the posterior region of the right hemisphere [Benton et al, 1994 Contributions to Neuropsychological Assessment: A Clinical Manual (New York: Oxford University Press)]. High-school boys (N = 52) performed better than girls (N = 62), with a large effect for sex (d = 1.11). Performance increased with mathematical competence, but the sex difference did not vary significantly across different levels of mathematics coursework. On the basis of earlier work, it was predicted that male, but not female, performance in line judgment would decline with disruptions to task geometry (page frame), and that the sex difference would disappear with disruptions to geometry. These predictions were supported by a number of univariate and sex-specific analyses, although an omnibus repeated-measures analysis did not detect the predicted interaction, most likely owing to limitations in power. Thus, there is partial support for the notion that attentional predispositions or strategies may contribute to visuospatial sex differences, with males more likely than females to attend to, and rely upon, internal or external representations of task geometry. Additional support for this hypothesis may require development of new measures or experimental manipulations with more powerful geometrical disruptions.

Multimodality Tumor Delineation and Predictive Modelling via Fuzzy-Fusion Deformable Models and Biological Potential Functions

NASA Astrophysics Data System (ADS)

Wasserman, Richard Marc

The radiation therapy treatment planning (RTTP) process may be subdivided into three planning stages: gross tumor delineation, clinical target delineation, and modality dependent target definition. The research presented will focus on the first two planning tasks. A gross tumor target delineation methodology is proposed which focuses on the integration of MRI, CT, and PET imaging data towards the generation of a mathematically optimal tumor boundary. The solution to this problem is formulated within a framework integrating concepts from the fields of deformable modelling, region growing, fuzzy logic, and data fusion. The resulting fuzzy fusion algorithm can integrate both edge and region information from multiple medical modalities to delineate optimal regions of pathological tissue content. The subclinical boundaries of an infiltrating neoplasm cannot be determined explicitly via traditional imaging methods and are often defined to extend a fixed distance from the gross tumor boundary. In order to improve the clinical target definition process an estimation technique is proposed via which tumor growth may be modelled and subclinical growth predicted. An in vivo, macroscopic primary brain tumor growth model is presented, which may be fit to each patient undergoing treatment, allowing for the prediction of future growth and consequently the ability to estimate subclinical local invasion. Additionally, the patient specific in vivo tumor model will be of significant utility in multiple diagnostic clinical applications.

A three-talk model for shared decision making: multistage consultation process.

PubMed

Elwyn, Glyn; Durand, Marie Anne; Song, Julia; Aarts, Johanna; Barr, Paul J; Berger, Zackary; Cochran, Nan; Frosch, Dominick; Galasiński, Dariusz; Gulbrandsen, Pål; Han, Paul K J; Härter, Martin; Kinnersley, Paul; Lloyd, Amy; Mishra, Manish; Perestelo-Perez, Lilisbeth; Scholl, Isabelle; Tomori, Kounosuke; Trevena, Lyndal; Witteman, Holly O; Van der Weijden, Trudy

2017-11-06

Objectives  To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement. Design  Multistage consultation process. Setting  Key informant group, communities of interest, and survey of clinical specialties. Participants  19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties. Results  After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on "team talk," "option talk," and "decision talk," to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals. Conclusions  The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Leveraging workflow control patterns in the domain of clinical practice guidelines.

PubMed

Kaiser, Katharina; Marcos, Mar

2016-02-10

Clinical practice guidelines (CPGs) include recommendations describing appropriate care for the management of patients with a specific clinical condition. A number of representation languages have been developed to support executable CPGs, with associated authoring/editing tools. Even with tool assistance, authoring of CPG models is a labor-intensive task. We aim at facilitating the early stages of CPG modeling task. In this context, we propose to support the authoring of CPG models based on a set of suitable procedural patterns described in an implementation-independent notation that can be then semi-automatically transformed into one of the alternative executable CPG languages. We have started with the workflow control patterns which have been identified in the fields of workflow systems and business process management. We have analyzed the suitability of these patterns by means of a qualitative analysis of CPG texts. Following our analysis we have implemented a selection of workflow patterns in the Asbru and PROforma CPG languages. As implementation-independent notation for the description of patterns we have chosen BPMN 2.0. Finally, we have developed XSLT transformations to convert the BPMN 2.0 version of the patterns into the Asbru and PROforma languages. We showed that although a significant number of workflow control patterns are suitable to describe CPG procedural knowledge, not all of them are applicable in the context of CPGs due to their focus on single-patient care. Moreover, CPGs may require additional patterns not included in the set of workflow control patterns. We also showed that nearly all the CPG-suitable patterns can be conveniently implemented in the Asbru and PROforma languages. Finally, we demonstrated that individual patterns can be semi-automatically transformed from a process specification in BPMN 2.0 to executable implementations in these languages. We propose a pattern and transformation-based approach for the development of CPG models. Such an approach can form the basis of a valid framework for the authoring of CPG models. The identification of adequate patterns and the implementation of transformations to convert patterns from a process specification into different executable implementations are the first necessary steps for our approach.

A model for the pilot's use of motion cues in roll-axis tracking tasks

NASA Technical Reports Server (NTRS)

Levison, W. H.; Junker, A. M.

1977-01-01

Simulated target-following and disturbance-regulation tasks were explored with subjects using visual-only and combined visual and motion cues. The effects of motion cues on task performance and pilot response behavior were appreciably different for the two task configurations and were consistent with data reported in earlier studies for similar task configurations. The optimal-control model for pilot/vehicle systems provided a task-independent framework for accounting for the pilot's use of motion cues. Specifically, the availability of motion cues was modeled by augmenting the set of perceptual variables to include position, rate, acceleration, and accleration-rate of the motion simulator, and results were consistent with the hypothesis of attention-sharing between visual and motion variables. This straightforward informational model allowed accurate model predictions of the effects of motion cues on a variety of response measures for both the target-following and disturbance-regulation tasks.

New Uses for Sensitivity Analysis: How Different Movement Tasks Effect Limb Model Parameter Sensitivity

NASA Technical Reports Server (NTRS)

Winters, J. M.; Stark, L.

1984-01-01

Original results for a newly developed eight-order nonlinear limb antagonistic muscle model of elbow flexion and extension are presented. A wider variety of sensitivity analysis techniques are used and a systematic protocol is established that shows how the different methods can be used efficiently to complement one another for maximum insight into model sensitivity. It is explicitly shown how the sensitivity of output behaviors to model parameters is a function of the controller input sequence, i.e., of the movement task. When the task is changed (for instance, from an input sequence that results in the usual fast movement task to a slower movement that may also involve external loading, etc.) the set of parameters with high sensitivity will in general also change. Such task-specific use of sensitivity analysis techniques identifies the set of parameters most important for a given task, and even suggests task-specific model reduction possibilities.

RACE/A: an architectural account of the interactions between learning, task control, and retrieval dynamics.

PubMed

van Maanen, Leendert; van Rijn, Hedderik; Taatgen, Niels

2012-01-01

This article discusses how sequential sampling models can be integrated in a cognitive architecture. The new theory Retrieval by Accumulating Evidence in an Architecture (RACE/A) combines the level of detail typically provided by sequential sampling models with the level of task complexity typically provided by cognitive architectures. We will use RACE/A to model data from two variants of a picture-word interference task in a psychological refractory period design. These models will demonstrate how RACE/A enables interactions between sequential sampling and long-term declarative learning, and between sequential sampling and task control. In a traditional sequential sampling model, the onset of the process within the task is unclear, as is the number of sampling processes. RACE/A provides a theoretical basis for estimating the onset of sequential sampling processes during task execution and allows for easy modeling of multiple sequential sampling processes within a task. Copyright © 2011 Cognitive Science Society, Inc.

Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.

PubMed

Sihong Chen; Jing Qin; Xing Ji; Baiying Lei; Tianfu Wang; Dong Ni; Jie-Zhi Cheng

2017-03-01

The gap between the computational and semantic features is the one of major factors that bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge this gap, we exploit three multi-task learning (MTL) schemes to leverage heterogeneous computational features derived from deep learning models of stacked denoising autoencoder (SDAE) and convolutional neural network (CNN), as well as hand-crafted Haar-like and HoG features, for the description of 9 semantic features for lung nodules in CT images. We regard that there may exist relations among the semantic features of "spiculation", "texture", "margin", etc., that can be explored with the MTL. The Lung Image Database Consortium (LIDC) data is adopted in this study for the rich annotation resources. The LIDC nodules were quantitatively scored w.r.t. 9 semantic features from 12 radiologists of several institutes in U.S.A. By treating each semantic feature as an individual task, the MTL schemes select and map the heterogeneous computational features toward the radiologists' ratings with cross validation evaluation schemes on the randomly selected 2400 nodules from the LIDC dataset. The experimental results suggest that the predicted semantic scores from the three MTL schemes are closer to the radiologists' ratings than the scores from single-task LASSO and elastic net regression methods. The proposed semantic attribute scoring scheme may provide richer quantitative assessments of nodules for better support of diagnostic decision and management. Meanwhile, the capability of the automatic association of medical image contents with the clinical semantic terms by our method may also assist the development of medical search engine.

Task Shifting in Dermatology: A Call to Action.

PubMed

Brown, Danielle N; Langan, Sinéad M; Freeman, Esther E

2017-11-01

Can task shifting be used to improve the delivery of dermatologic care in resource-poor settings worldwide? Task shifting is a means of redistributing available resources, whereby highly trained individuals train an available workforce to provide necessary care in low-resource settings. Limited evidence exists for task shifting in dermatology; however, studies from psychiatry demonstrate its efficacy. In the field of dermatology there is a need for high-quality evidence including randomized clinical trials to validate the implementation of task shifting in low-resource settings globally.

Task allocation model for minimization of completion time in distributed computer systems

NASA Astrophysics Data System (ADS)

Wang, Jai-Ping; Steidley, Carl W.

1993-08-01

A task in a distributed computing system consists of a set of related modules. Each of the modules will execute on one of the processors of the system and communicate with some other modules. In addition, precedence relationships may exist among the modules. Task allocation is an essential activity in distributed-software design. This activity is of importance to all phases of the development of a distributed system. This paper establishes task completion-time models and task allocation models for minimizing task completion time. Current work in this area is either at the experimental level or without the consideration of precedence relationships among modules. The development of mathematical models for the computation of task completion time and task allocation will benefit many real-time computer applications such as radar systems, navigation systems, industrial process control systems, image processing systems, and artificial intelligence oriented systems.

Protocol for a randomised controlled implementation trial of point-of-care viral load testing and task shifting: the Simplifying HIV TREAtment and Monitoring (STREAM) study

PubMed Central

Garrett, Nigel; Quame-Amaglo, Justice; Samsunder, Natasha; Ngobese, Hope; Ngomane, Noluthando; Moodley, Pravikrishnen; Mlisana, Koleka; Schaafsma, Torin; Donnell, Deborah; Barnabas, Ruanne; Naidoo, Kogieleum; Abdool Karim, Salim; Celum, Connie; Drain, Paul K

2017-01-01

Introduction Achieving the Joint United Nations Programme on HIV and AIDS 90-90-90 targets requires models of HIV care that expand antiretroviral therapy (ART) coverage without overburdening health systems. Point-of-care (POC) viral load (VL) testing has the potential to efficiently monitor ART treatment, while enrolled nurses may be able to provide safe and cost-effective chronic care for stable patients with HIV. This study aims to demonstrate whether POC VL testing combined with task shifting to enrolled nurses is non-inferior and cost-effective compared with laboratory-based VL monitoring and standard HIV care. Methods and analysis The STREAM (Simplifying HIV TREAtment and Monitoring) study is an open-label, non-inferiority, randomised controlled implementation trial. HIV-positive adults, clinically stable at 6 months after ART initiation, will be recruited in a large urban clinic in South Africa. Approximately 396 participants will be randomised 1:1 to receive POC HIV VL monitoring and potential task shifting to enrolled nurses, versus laboratory VL monitoring and standard South African HIV care. Initial clinic follow-up will be 2-monthly in both arms, with VL testing at enrolment, 6 months and 12 months. At 6 months (1 year after ART initiation), stable participants in both arms will qualify for a differentiated care model involving decentralised ART pickup at community-based pharmacies. The primary outcome is retention in care and virological suppression at 12 months from enrolment. Secondary outcomes include time to appropriate entry into the decentralised ART delivery programme, costs per virologically suppressed patient and cost-effectiveness of the intervention compared with standard care. Findings will inform the scale up of VL testing and differentiated care in HIV-endemic resource-limited settings. Ethics and dissemination Ethical approval has been granted by the University of KwaZulu-Natal Biomedical Research Ethics Committee (BFC296/16) and University of Washington Institutional Review Board (STUDY00001466). Results will be presented at international conferences and published in academic peer-reviewed journals. Trial registration NCT03066128; Pre-results. PMID:28963304

Using task performance to inform treatment planning for youth with ADHD: A systematic review.

PubMed

Molitor, Stephen J; Langberg, Joshua M

2017-12-01

The role that neuropsychological task performance plays in the assessment of Attention-Deficit/Hyperactivity Disorder (ADHD) is currently ambiguous, and findings are mixed regarding whether tasks have validity for diagnosing the disorder. Irrespective of their validity for diagnosing ADHD, neuropsychological tasks could provide valuable information to mental health professionals if they can inform recommendations for treatment targets and modalities. Therefore, this review sought to synthesize the available evidence related to the use of neuropsychological task performance as a tool for informing treatment planning for youth with ADHD. Reviewed studies focused on examinations of associations between task performance and academic, social, and health outcomes, as well as response to treatment. Twenty-five relevant studies using samples of youth diagnosed with ADHD in clinical, community, and school settings were identified. Review of the evidence suggests that task performance may be useful in identifying individuals with ADHD at risk for academic impairment. However, the evidence is less compelling for identifying youth at risk for impaired social functioning or poor health outcomes. The review also found that task performance is likely useful for predicting response to treatment with methylphenidate. Across studies, evidence indicated that interpreting task performance in an integrated manner, such as a factor score or mean score, was more consistently useful for predicting outcomes of interest than interpreting performance from a single task. Implications for the use of tasks in ADHD assessments are discussed, and future directions are outlined for further examining the clinical utility of task performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clinician search behaviors may be influenced by search engine design.

PubMed

Lau, Annie Y S; Coiera, Enrico; Zrimec, Tatjana; Compton, Paul

2010-06-30

Searching the Web for documents using information retrieval systems plays an important part in clinicians' practice of evidence-based medicine. While much research focuses on the design of methods to retrieve documents, there has been little examination of the way different search engine capabilities influence clinician search behaviors. Previous studies have shown that use of task-based search engines allows for faster searches with no loss of decision accuracy compared with resource-based engines. We hypothesized that changes in search behaviors may explain these differences. In all, 75 clinicians (44 doctors and 31 clinical nurse consultants) were randomized to use either a resource-based or a task-based version of a clinical information retrieval system to answer questions about 8 clinical scenarios in a controlled setting in a university computer laboratory. Clinicians using the resource-based system could select 1 of 6 resources, such as PubMed; clinicians using the task-based system could select 1 of 6 clinical tasks, such as diagnosis. Clinicians in both systems could reformulate search queries. System logs unobtrusively capturing clinicians' interactions with the systems were coded and analyzed for clinicians' search actions and query reformulation strategies. The most frequent search action of clinicians using the resource-based system was to explore a new resource with the same query, that is, these clinicians exhibited a "breadth-first" search behaviour. Of 1398 search actions, clinicians using the resource-based system conducted 401 (28.7%, 95% confidence interval [CI] 26.37-31.11) in this way. In contrast, the majority of clinicians using the task-based system exhibited a "depth-first" search behavior in which they reformulated query keywords while keeping to the same task profiles. Of 585 search actions conducted by clinicians using the task-based system, 379 (64.8%, 95% CI 60.83-68.55) were conducted in this way. This study provides evidence that different search engine designs are associated with different user search behaviors.