The role of contraceptive attributes in women's contraceptive decision making.

PubMed

Madden, Tessa; Secura, Gina M; Nease, Robert F; Politi, Mary C; Peipert, Jeffrey F

2015-07-01

Contraceptive methods have differing attributes. Women's preferences for these attributes may influence contraceptive decision making. Our objective was to identify women's contraceptive preferences among women initiating a new contraceptive method. We conducted a cross-sectional, self-administered survey of women's contraceptive preferences at the time of enrollment into the Contraceptive CHOICE Project. Participants were asked to rank the importance of 15 contraceptive attributes on a 3-point scale (1 = not at all important, 2 = somewhat important, and 3 = very important) and then to rank the 3 attributes that were the most important when choosing a contraceptive method. The survey also contained questions about prior contraceptive experience and barriers to contraceptive use. Information about demographic and reproductive characteristics was collected through the CHOICE Project baseline survey. There were 2590 women who completed the survey. Our sample was racially and socioeconomically diverse. Method attributes with the highest importance score (mean score [SD]) were effectiveness (2.97 [0.18]), safety (2.96 [0.22]), affordability (2.61 [0.61]), whether the method is long lasting (2.58 [0.61]), and whether the method is "forgettable" (2.54 [0.66]). The attributes most likely to be ranked by respondents among the top 3 attributes included effectiveness (84.2%), safety (67.8%), and side effects of the method (44.6%). Multiple contraceptive attributes influence decision making and no single attribute drives most women's decisions. Tailoring communication and helping women make complex tradeoffs between attributes can better support their contraceptive decisions and may assist them in making value-consistent choices. This process could improve continuation and satisfaction. Copyright © 2015 Elsevier Inc. All rights reserved.

Value Focused Thinking in Developing Aerobatic Aircraft Selection Model for Turkish Air Force

DTIC Science & Technology

2012-03-22

many reasons . Most problems in decision- making involve multiple objectives and uncertainties. The number of alternatives can be significant and make ...and Republic of Turkey all around the world”. This is a clear and concise statement of the most basic reason for decision. After making interview...Hwang, C.-L. (1995). Multiple Attribute Decison Making : An Introduction. California: Sage Publications. 90 Vita First Lieutenant

MAGDM linear-programming models with distinct uncertain preference structures.

PubMed

Xu, Zeshui S; Chen, Jian

2008-10-01

Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.

Evaluation and selection of decision-making methods to assess landfill mining projects.

PubMed

Hermann, Robert; Baumgartner, Rupert J; Vorbach, Stefan; Ragossnig, Arne; Pomberger, Roland

2015-09-01

For the first time in Austria, fundamental technological and economic studies on recovering secondary raw materials from large landfills have been carried out, based on the 'LAMIS - Landfill Mining Austria' pilot project. A main focus of the research - and the subject of this article - was to develop an assessment or decision-making procedure that allows landfill owners to thoroughly examine the feasibility of a landfill mining project in advance. Currently there are no standard procedures that would sufficiently cover all the multiple-criteria requirements. The basic structure of the multiple attribute decision making process was used to narrow down on selection, conceptual design and assessment of suitable procedures. Along with a breakdown into preliminary and main assessment, the entire foundation required was created, such as definitions of requirements to an assessment method, selection and accurate description of the various assessment criteria and classification of the target system for the present 'landfill mining' vs. 'retaining the landfill in after-care' decision-making problem. Based on these studies, cost-utility analysis and the analytical-hierarchy process were selected from the range of multiple attribute decision-making procedures and examined in detail. Overall, both methods have their pros and cons with regard to their use for assessing landfill mining projects. Merging these methods or connecting them with single-criteria decision-making methods (like the net present value method) may turn out to be reasonable and constitute an appropriate assessment method. © The Author(s) 2015.

Parental Influences, Career Decision-Making Attributions, and Self-Efficacy: Differences for Men and Women?

ERIC Educational Resources Information Center

Lease, Suzanne H.; Dahlbeck, David T.

2009-01-01

This study investigated the relations of maternal and paternal attachment, parenting styles, and career locus of control to college students' career decision self-efficacy and explored whether these relations differed by student gender. Data analysis using hierarchical multiple regression revealed that attachment was relevant for females' career…

More Than Just Accuracy: A Novel Method to Incorporate Multiple Test Attributes in Evaluating Diagnostic Tests Including Point of Care Tests.

PubMed

Thompson, Matthew; Weigl, Bernhard; Fitzpatrick, Annette; Ide, Nicole

2016-01-01

Current frameworks for evaluating diagnostic tests are constrained by a focus on diagnostic accuracy, and assume that all aspects of the testing process and test attributes are discrete and equally important. Determining the balance between the benefits and harms associated with new or existing tests has been overlooked. Yet, this is critically important information for stakeholders involved in developing, testing, and implementing tests. This is particularly important for point of care tests (POCTs) where tradeoffs exist between numerous aspects of the testing process and test attributes. We developed a new model that multiple stakeholders (e.g., clinicians, patients, researchers, test developers, industry, regulators, and health care funders) can use to visualize the multiple attributes of tests, the interactions that occur between these attributes, and their impacts on health outcomes. We use multiple examples to illustrate interactions between test attributes (test availability, test experience, and test results) and outcomes, including several POCTs. The model could be used to prioritize research and development efforts, and inform regulatory submissions for new diagnostics. It could potentially provide a way to incorporate the relative weights that various subgroups or clinical settings might place on different test attributes. Our model provides a novel way that multiple stakeholders can use to visualize test attributes, their interactions, and impacts on individual and population outcomes. We anticipate that this will facilitate more informed decision making around diagnostic tests.

Intuitionistic uncertain linguistic partitioned Bonferroni means and their application to multiple attribute decision-making

NASA Astrophysics Data System (ADS)

Liu, Zhengmin; Liu, Peide

2017-04-01

The Bonferroni mean (BM) was originally introduced by Bonferroni and generalised by many other researchers due to its capacity to capture the interrelationship between input arguments. Nevertheless, in many situations, interrelationships do not always exist between all of the attributes. Attributes can be partitioned into several different categories and members of intra-partition are interrelated while no interrelationship exists between attributes of different partitions. In this paper, as complements to the existing generalisations of BM, we investigate the partitioned Bonferroni mean (PBM) under intuitionistic uncertain linguistic environments and develop two linguistic aggregation operators: intuitionistic uncertain linguistic partitioned Bonferroni mean (IULPBM) and its weighted form (WIULPBM). Then, motivated by the ideal of geometric mean and PBM, we further present the partitioned geometric Bonferroni mean (PGBM) and develop two linguistic geometric aggregation operators: intuitionistic uncertain linguistic partitioned geometric Bonferroni mean (IULPGBM) and its weighted form (WIULPGBM). Some properties and special cases of these proposed operators are also investigated and discussed in detail. Based on these operators, an approach for multiple attribute decision-making problems with intuitionistic uncertain linguistic information is developed. Finally, a practical example is presented to illustrate the developed approach and comparison analyses are conducted with other representative methods to verify the effectiveness and feasibility of the developed approach.

Do the right thing: the assumption of optimality in lay decision theory and causal judgment.

PubMed

Johnson, Samuel G B; Rips, Lance J

2015-03-01

Human decision-making is often characterized as irrational and suboptimal. Here we ask whether people nonetheless assume optimal choices from other decision-makers: Are people intuitive classical economists? In seven experiments, we show that an agent's perceived optimality in choice affects attributions of responsibility and causation for the outcomes of their actions. We use this paradigm to examine several issues in lay decision theory, including how responsibility judgments depend on the efficacy of the agent's actual and counterfactual choices (Experiments 1-3), individual differences in responsibility assignment strategies (Experiment 4), and how people conceptualize decisions involving trade-offs among multiple goals (Experiments 5-6). We also find similar results using everyday decision problems (Experiment 7). Taken together, these experiments show that attributions of responsibility depend not only on what decision-makers do, but also on the quality of the options they choose not to take. Copyright © 2015 Elsevier Inc. All rights reserved.

Research of Simple Multi-Attribute Rating Technique for Decision Support

NASA Astrophysics Data System (ADS)

Siregar, Dodi; Arisandi, Diki; Usman, Ari; Irwan, Dedy; Rahim, Robbi

2017-12-01

One of the roles of decision support system is that it can assist the decision maker in obtaining the appropriate alternative with the desired criteria, one of the methods that could apply for the decision maker is SMART method with multicriteria decision making. This multi-criteria decision-making theory has meaning where every alternative has criteria and has value and weight, and the author uses this approach to facilitate decision making with a compelling case. The problems discussed in this paper are classified into problems of a variety Multiobjective (multiple goals to be accomplished) and multicriteria (many of the decisive criteria in reaching such decisions).

Applications of fuzzy ranking methods to risk-management decisions

NASA Astrophysics Data System (ADS)

Mitchell, Harold A.; Carter, James C., III

1993-12-01

The Department of Energy is making significant improvements to its nuclear facilities as a result of more stringent regulation, internal audits, and recommendations from external review groups. A large backlog of upgrades has resulted. Currently, a prioritization method is being utilized which relies on a matrix of potential consequence and probability of occurrence. The attributes of the potential consequences considered include likelihood, exposure, public health and safety, environmental impact, site personnel safety, public relations, legal liability, and business loss. This paper describes an improved method which utilizes fuzzy multiple attribute decision methods to rank proposed improvement projects.

Value-Based Assessment of New Medical Technologies: Towards a Robust Methodological Framework for the Application of Multiple Criteria Decision Analysis in the Context of Health Technology Assessment.

PubMed

Angelis, Aris; Kanavos, Panos

2016-05-01

In recent years, multiple criteria decision analysis (MCDA) has emerged as a likely alternative to address shortcomings in health technology assessment (HTA) by offering a more holistic perspective to value assessment and acting as an alternative priority setting tool. In this paper, we argue that MCDA needs to subscribe to robust methodological processes related to the selection of objectives, criteria and attributes in order to be meaningful in the context of healthcare decision making and fulfil its role in value-based assessment (VBA). We propose a methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outline the stages involved in each phase and discuss their relevance in the HTA process. Importantly, criteria and attributes need to satisfy a set of desired properties, otherwise the outcome of the analysis can produce spurious results and misleading recommendations. Assuming the methodological process we propose is adhered to, the application of MCDA presents three very distinct advantages to decision makers in the context of HTA and VBA: first, it acts as an instrument for eliciting preferences on the performance of alternative options across a wider set of explicit criteria, leading to a more complete assessment of value; second, it allows the elicitation of preferences across the criteria themselves to reflect differences in their relative importance; and, third, the entire process of preference elicitation can be informed by direct stakeholder engagement, and can therefore reflect their own preferences. All features are fully transparent and facilitate decision making.

MADM-based smart parking guidance algorithm

PubMed Central

Li, Bo; Pei, Yijian; Wu, Hao; Huang, Dijiang

2017-01-01

In smart parking environments, how to choose suitable parking facilities with various attributes to satisfy certain criteria is an important decision issue. Based on the multiple attributes decision making (MADM) theory, this study proposed a smart parking guidance algorithm by considering three representative decision factors (i.e., walk duration, parking fee, and the number of vacant parking spaces) and various preferences of drivers. In this paper, the expected number of vacant parking spaces is regarded as an important attribute to reflect the difficulty degree of finding available parking spaces, and a queueing theory-based theoretical method was proposed to estimate this expected number for candidate parking facilities with different capacities, arrival rates, and service rates. The effectiveness of the MADM-based parking guidance algorithm was investigated and compared with a blind search-based approach in comprehensive scenarios with various distributions of parking facilities, traffic intensities, and user preferences. Experimental results show that the proposed MADM-based algorithm is effective to choose suitable parking resources to satisfy users’ preferences. Furthermore, it has also been observed that this newly proposed Markov Chain-based availability attribute is more effective to represent the availability of parking spaces than the arrival rate-based availability attribute proposed in existing research. PMID:29236698

A Generic Authentication LoA Derivation Model

NASA Astrophysics Data System (ADS)

Yao, Li; Zhang, Ning

One way of achieving a more fine-grained access control is to link an authentication level of assurance (LoA) derived from a requester’s authentication instance to the authorisation decision made to the requester. To realise this vision, there is a need for designing a LoA derivation model that supports the use and quantification of multiple LoA-effecting attributes, and analyse their composite effect on a given authentication instance. This paper reports the design of such a model, namely a generic LoA derivation model (GEA- LoADM). GEA-LoADM takes into account of multiple authentication attributes along with their relationships, abstracts the composite effect by the multiple attributes into a generic value, authentication LoA, and provides algorithms for the run-time derivation of LoA. The algorithms are tailored to reflect the relationships among the attributes involved in an authentication instance. The model has a number of valuable properties, including flexibility and extensibility; it can be applied to different application contexts and support easy addition of new attributes and removal of obsolete ones.

Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

NASA Astrophysics Data System (ADS)

Zaiwani, B. E.; Zarlis, M.; Efendi, S.

2018-03-01

In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems

USGS Publications Warehouse

Neckles, Hilary A.; Lyons, James E.; Guntenspergen, Glenn R.; Shriver, W. Gregory; Adamowicz, Susan C.

2015-01-01

Most salt marshes in the USA have been degraded by human activities, and coastal managers are faced with complex choices among possible actions to restore or enhance ecosystem integrity. We applied structured decision making (SDM) to guide selection of monitoring variables and management priorities for salt marshes within the National Wildlife Refuge System in the northeastern USA. In general, SDM is a systematic process for decomposing a decision into its essential elements. We first engaged stakeholders in clarifying regional salt marsh decision problems, defining objectives and attributes to evaluate whether objectives are achieved, and developing a pool of alternative management actions for achieving objectives. Through this process, we identified salt marsh attributes that were applicable to monitoring National Wildlife Refuges on a regional scale and that targeted management needs. We then analyzed management decisions within three salt marsh units at Prime Hook National Wildlife Refuge, coastal Delaware, as a case example of prioritizing management alternatives. Values for salt marsh attributes were estimated from 2 years of baseline monitoring data and expert opinion. We used linear value modeling to aggregate multiple attributes into a single performance score for each alternative, constrained optimization to identify alternatives that maximized total management benefits subject to refuge-wide cost constraints, and used graphical analysis to identify the optimal set of alternatives for the refuge. SDM offers an efficient, transparent approach for integrating monitoring into management practice and improving the quality of management decisions.

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

Screening and Evaluation Tool (SET) Users Guide

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

Pincock, Layne

This document is the users guide to using the Screening and Evaluation Tool (SET). SET is a tool for comparing multiple fuel cycle options against a common set of criteria and metrics. It does this using standard multi-attribute utility decision analysis methods.

Decision-making competence in younger and older adults: which cognitive abilities contribute to the application of decision rules?

PubMed

Rosi, Alessia; Bruine de Bruin, Wändi; Del Missier, Fabio; Cavallini, Elena; Russo, Riccardo

2017-12-28

Older adults perform worse than younger adults when applying decision rules to choose between options that vary along multiple attributes. Although previous studies have shown that general fluid cognitive abilities contribute to the accurate application of decision rules, relatively little is known about which specific cognitive abilities play the most important role. We examined the independent roles of working memory, verbal fluency, semantic knowledge, and components of executive functioning. We found that age-related decline in applying decision rules was statistically mediated by age-related decline in working memory and verbal fluency. Our results have implications for theories of aging and decision-making.

A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

NASA Astrophysics Data System (ADS)

Zhang, Wancheng; Xu, Yejun; Wang, Huimin

2016-01-01

The aim of this paper is to put forward a consensus reaching method for multi-attribute group decision-making (MAGDM) problems with linguistic information, in which the weight information of experts and attributes is unknown. First, some basic concepts and operational laws of 2-tuple linguistic label are introduced. Then, a grey relational analysis method and a maximising deviation method are proposed to calculate the incomplete weight information of experts and attributes respectively. To eliminate the conflict in the group, a weight-updating model is employed to derive the weights of experts based on their contribution to the consensus reaching process. After conflict elimination, the final group preference can be obtained which will give the ranking of the alternatives. The model can effectively avoid information distortion which is occurred regularly in the linguistic information processing. Finally, an illustrative example is given to illustrate the application of the proposed method and comparative analysis with the existing methods are offered to show the advantages of the proposed method.

Take-the-best and the influence of decision-inconsistent attributes on decision confidence and choices in memory-based decisions.

PubMed

Dummel, Sebastian; Rummel, Jan

2016-11-01

Take-the-best (TTB) is a decision strategy according to which attributes about choice options are sequentially processed in descending order of validity, and attribute processing is stopped once an attribute discriminates between options. Consequently, TTB-decisions rely on only one, the best discriminating, attribute, and lower-valid attributes need not be processed because they are TTB-irrelevant. Recent research suggests, however, that when attribute information is visually present during decision-making, TTB-irrelevant attributes are processed and integrated into decisions nonetheless. To examine whether TTB-irrelevant attributes are retrieved and integrated when decisions are made memory-based, we tested whether the consistency of a TTB-irrelevant attribute affects TTB-users' decision behaviour in a memory-based decision task. Participants first learned attribute configurations of several options. Afterwards, they made several decisions between two of the options, and we manipulated conflict between the second-best attribute and the TTB-decision. We assessed participants' decision confidence and the proportion of TTB-inconsistent choices. According to TTB, TTB-irrelevant attributes should not affect confidence and choices, because these attributes should not be retrieved. Results showed, however, that TTB-users were less confident and made more TTB-inconsistent choices when TTB-irrelevant information was in conflict with the TTB-decision than when it was not, suggesting that TTB-users retrieved and integrated TTB-irrelevant information.

Comparison of preferences of healthcare professionals and MS patients for attributes of disease-modifying drugs: A best-worst scaling.

PubMed

Kremer, Ingrid E H; Evers, Silvia M A A; Jongen, Peter J; Hiligsmann, Mickaël

2018-02-01

The choice between disease-modifying drugs (DMDs) for the treatment of multiple sclerosis (MS) becomes more often a shared decision between the patient and the neurologist and MS nurse. This study aimed to assess which DMD attributes are most important for the healthcare professionals in selecting a DMD for a patient. Subsequently, within this perspective, the neurologists' and nurses' perspectives were compared. Lastly, the healthcare professionals' perspective was compared with the patients' perspective to detect any differences that may need attention in the communication about DMDs. A best-worst scaling (BWS) was conducted among 27 neurologists and 33 MS nurses treating patients with MS to determine the importance of 27 DMD attributes. These attributes were identified through three focus groups with MS patients in a previous study (N=19). Relative importance scores (RISs) were estimated for each attribute. Multivariable linear regression analyses were used to compare the different perspectives. According to the neurologists and nurses, safety of the DMD was the most important DMD attribute in the treatment decision, closely followed by effect on disability progression, quality of life and relapse rate. Patients with MS agreed with the importance of the last three attributes, but valued safety significantly lower (b=-2.59, P<.001). This study suggests that, overall, neurologists and nurses regard the same DMD attributes as important as MS patients with the notable exception of safety. This study provides valuable information for the development of interventions to support shared decision making and highlights which attributes of DMDs may need additional attention. © 2017 The Authors Health Expectations Published by John Wiley & Sons Ltd.

A decision aid for intensity-modulated radiation-therapy plan selection in prostate cancer based on a prognostic Bayesian network and a Markov model.

PubMed

Smith, Wade P; Doctor, Jason; Meyer, Jürgen; Kalet, Ira J; Phillips, Mark H

2009-06-01

The prognosis of cancer patients treated with intensity-modulated radiation-therapy (IMRT) is inherently uncertain, depends on many decision variables, and requires that a physician balance competing objectives: maximum tumor control with minimal treatment complications. In order to better deal with the complex and multiple objective nature of the problem we have combined a prognostic probabilistic model with multi-attribute decision theory which incorporates patient preferences for outcomes. The response to IMRT for prostate cancer was modeled. A Bayesian network was used for prognosis for each treatment plan. Prognoses included predicting local tumor control, regional spread, distant metastases, and normal tissue complications resulting from treatment. A Markov model was constructed and used to calculate a quality-adjusted life-expectancy which aids in the multi-attribute decision process. Our method makes explicit the tradeoffs patients face between quality and quantity of life. This approach has advantages over current approaches because with our approach risks of health outcomes and patient preferences determine treatment decisions.

A qualitative evaluation of the crucial attributes of contextual information necessary in EHR design to support patient-centered medical home care.

PubMed

Weir, Charlene R; Staggers, Nancy; Gibson, Bryan; Doing-Harris, Kristina; Barrus, Robyn; Dunlea, Robert

2015-04-16

Effective implementation of a Primary Care Medical Home model of care (PCMH) requires integration of patients' contextual information (physical, mental, social and financial status) into an easily retrievable information source for the healthcare team and clinical decision-making. This project explored clinicians' perceptions about important attributes of contextual information for clinical decision-making, how contextual information is expressed in CPRS clinical documentation as well as how clinicians in a highly computerized environment manage information flow related to these areas. A qualitative design using Cognitive Task Analyses and a modified Critical Incident Technique were used. The study was conducted in a large VA with a fully implemented EHR located in the western United States. Seventeen providers working in a PCMH model of care in Primary Care, Home Based Care and Geriatrics reported on a recent difficult transition requiring contextual information for decision-making. The transcribed interviews were qualitatively analyzed for thematic development related to contextual information using an iterative process and multiple reviewers with ATLAS@ti software. Six overarching themes emerged as attributes of contextual information: Informativeness, goal language, temporality, source attribution, retrieval effort, and information quality. These results indicate that specific attributes are needed to in order for contextual information to fully support clinical decision-making in a Medical Home care delivery environment. Improved EHR designs are needed for ease of contextual information access, displaying linkages across time and settings, and explicit linkages to both clinician and patient goals. Implications relevant to providers' information needs, team functioning and EHR design are discussed.

Using a multidimensional unfolding approach to assess multiple sclerosis patient preferences for disease-modifying therapy: a pilot study

PubMed Central

Sempere, Angel Perez; Vera-Lopez, Vanesa; Gimenez-Martinez, Juana; Ruiz-Beato, Elena; Cuervo, Jesús; Maurino, Jorge

2017-01-01

Purpose Multidimensional unfolding is a multivariate method to assess preferences using a small sample size, a geometric model locating individuals and alternatives as points in a joint space. The objective was to evaluate relapsing–remitting multiple sclerosis (RRMS) patient preferences toward key disease-modifying therapy (DMT) attributes using multidimensional unfolding. Patients and methods A cross-sectional pilot study in RRMS patients was conducted. Drug attributes included relapse prevention, disease progression prevention, side-effect risk and route and schedule of administration. Assessment of preferences was performed through a five-card game. Patients were asked to value attributes from 1 (most preferred) to 5 (least preferred). Results A total of 37 patients were included; the mean age was 38.6 years, and 78.4% were female. Disease progression prevention was the most important factor (51.4%), followed by relapse prevention (40.5%). The frequency of administration had the lowest preference rating for 56.8% of patients. Finally, 19.6% valued the side-effect risk attribute as having low/very low importance. Conclusion Patients’ perspective for DMT attributes may provide valuable information to facilitate shared decision-making. Efficacy attributes were the most important drug characteristics for RRMS patients. Multidimensional unfolding seems to be a feasible approach to assess preferences in multiple sclerosis patients. Further elicitation studies using multidimensional unfolding with other stated choice methods are necessary to confirm these findings. PMID:28615928

A neuroimaging investigation of attribute framing and individual differences

PubMed Central

Murch, Kevin B.

2014-01-01

Functional magnetic resonance imaging was used to evaluate the neural basis of framing effects. We tested the reflexive and reflective systems model of social cognition as it relates to framing. We also examined the relationships among frame susceptibility, intelligence and personality measures. Participants evaluated whether personal attributes applied to themselves from multiple perspectives and in positive and negative frames. Participants rated whether each statement was descriptive or not and endorsed positive frames more than negative frames. Individual differences on frame decisions enabled us to form high and low frame susceptibility groups. Endorsement of frame-consistent attributes was associated with personality factors, cognitive reflection and intelligence. Reflexive brain regions were associated with positive frames while reflective areas were associated with negative frames. Region of Interest analyses showed that frame-inconsistent responses were associated with increased activation within reflective cognitive control regions including the left dorsolateral prefrontal cortex (PFC), dorsomedial PFC and left ventrolateral PFC. Frame-consistent responses were associated with increased activation in the right orbitofrontal cortex. These results demonstrate that individual differences in frame susceptibility influence personal attribute evaluations. Overall, this study clarifies the neural correlates of the reflective and reflexive systems of social cognition as applied to decisions about social attributions. PMID:23988759

A rough set approach for determining weights of decision makers in group decision making.

PubMed

Yang, Qiang; Du, Ping-An; Wang, Yong; Liang, Bin

2017-01-01

This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs' decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member' decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs' evaluations and selections.

Multiattribute selection of acute stroke imaging software platform for Extending the Time for Thrombolysis in Emergency Neurological Deficits (EXTEND) clinical trial.

PubMed

Churilov, Leonid; Liu, Daniel; Ma, Henry; Christensen, Soren; Nagakane, Yoshinari; Campbell, Bruce; Parsons, Mark W; Levi, Christopher R; Davis, Stephen M; Donnan, Geoffrey A

2013-04-01

The appropriateness of a software platform for rapid MRI assessment of the amount of salvageable brain tissue after stroke is critical for both the validity of the Extending the Time for Thrombolysis in Emergency Neurological Deficits (EXTEND) Clinical Trial of stroke thrombolysis beyond 4.5 hours and for stroke patient care outcomes. The objective of this research is to develop and implement a methodology for selecting the acute stroke imaging software platform most appropriate for the setting of a multi-centre clinical trial. A multi-disciplinary decision making panel formulated the set of preferentially independent evaluation attributes. Alternative Multi-Attribute Value Measurement methods were used to identify the best imaging software platform followed by sensitivity analysis to ensure the validity and robustness of the proposed solution. Four alternative imaging software platforms were identified. RApid processing of PerfusIon and Diffusion (RAPID) software was selected as the most appropriate for the needs of the EXTEND trial. A theoretically grounded generic multi-attribute selection methodology for imaging software was developed and implemented. The developed methodology assured both a high quality decision outcome and a rational and transparent decision process. This development contributes to stroke literature in the area of comprehensive evaluation of MRI clinical software. At the time of evaluation, RAPID software presented the most appropriate imaging software platform for use in the EXTEND clinical trial. The proposed multi-attribute imaging software evaluation methodology is based on sound theoretical foundations of multiple criteria decision analysis and can be successfully used for choosing the most appropriate imaging software while ensuring both robust decision process and outcomes. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.

Single-process versus multiple-strategy models of decision making: evidence from an information intrusion paradigm.

PubMed

Söllner, Anke; Bröder, Arndt; Glöckner, Andreas; Betsch, Tilmann

2014-02-01

When decision makers are confronted with different problems and situations, do they use a uniform mechanism as assumed by single-process models (SPMs) or do they choose adaptively from a set of available decision strategies as multiple-strategy models (MSMs) imply? Both frameworks of decision making have gathered a lot of support, but only rarely have they been contrasted with each other. Employing an information intrusion paradigm for multi-attribute decisions from givens, SPM and MSM predictions on information search, decision outcomes, attention, and confidence judgments were derived and tested against each other in two experiments. The results consistently support the SPM view: Participants seemingly using a "take-the-best" (TTB) strategy do not ignore TTB-irrelevant information as MSMs would predict, but adapt the amount of information searched, choose alternative choice options, and show varying confidence judgments contingent on the quality of the "irrelevant" information. The uniformity of these findings underlines the adequacy of the novel information intrusion paradigm and comprehensively promotes the notion of a uniform decision making mechanism as assumed by single-process models. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Multiple space-use strategies and their divergent consequences in a nonbreeding migratory bird (Parkesia noveboracensis)

Treesearch

Joseph A.M. Smith; Leonard R. Reitsma; Peter P. Marra

2011-01-01

We investigated the relationships among space-use patterns, home-range attributes, and individual characteristics to determine the consequences of different space-use strategies for the overwinter physical condition of Northern Waterthrushes (Parkesia noveboracensis). We have elsewhere demonstrated that heterogeneity in food availability drives the movement decisions...

Maclaurin symmetric mean operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decision-making

NASA Astrophysics Data System (ADS)

Liu, Peide; Qin, Xiyou

2017-11-01

Linguistic intuitionistic fuzzy number (LIFN) is a special intuitionistic fuzzy number which can more easily describe the vagueness existing in the real decision-making. Maclaurin symmetric mean (MSM) operator has the characteristic of considering the interrelationships among any number of input parameters. In this paper, we extended the MSM operator to the LIFNs and some extended MSM operators for LIFNs were proposed, some new decision-making methods were developed. Firstly, we introduced the definition, score function, properties and operational rules of the LIFNs. Then, we proposed some linguistic intuitionistic fuzzy MSM operators, such as linguistic intuitionistic fuzzy Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy Maclaurin symmetric mean (WLIFMSM) operator, linguistic intuitionistic fuzzy dual Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy dual Maclaurin symmetric mean (WLIFDMSM) operator. In the meantime, we studied some important properties of these operators, and developed some methods based on WLIFMSM operator and WLIFDMSM operator for multi-attribute decision-making. Finally, we use an example to demonstrate the effectiveness of the proposed methods.

Interpersonal reactivity and the attribution of emotional reactions.

PubMed

Haas, Brian W; Anderson, Ian W; Filkowski, Megan M

2015-06-01

The ability to identify the cause of another person's emotional reaction is an important component associated with improved success of social relationships and survival. Although many studies have investigated the mechanisms involved in emotion recognition, very little is currently known regarding the processes involved during emotion attribution decisions. Research on complementary "emotion understanding" mechanisms, including empathy and theory of mind, has demonstrated that emotion understanding decisions are often made through relatively emotion- or cognitive-based processing streams. The current study was designed to investigate the behavioral and brain mechanisms involved in emotion attribution decisions. We predicted that dual processes, emotional and cognitive, are engaged during emotion attribution decisions. Sixteen healthy adults completed the Interpersonal Reactivity Index to characterize individual differences in tendency to make emotion- versus cognitive-based interpersonal decisions. Participants then underwent functional MRI while making emotion attribution decisions. We found neuroimaging evidence that emotion attribution decisions engage a similar brain network as other forms of emotion understanding. Further, we found evidence in support of a dual processes model involved during emotion attribution decisions. Higher scores of personal distress were associated with quicker emotion attribution decisions and increased anterior insula activity. Conversely, higher scores in perspective taking were associated with delayed emotion attribution decisions and increased prefrontal cortex and premotor activity. These findings indicate that the making of emotion attribution decisions relies on dissociable emotional and cognitive processing streams within the brain. (c) 2015 APA, all rights reserved).

Response time modeling reveals multiple contextual cuing mechanisms.

PubMed

Sewell, David K; Colagiuri, Ben; Livesey, Evan J

2017-08-24

Contextual cuing refers to a response time (RT) benefit that occurs when observers search through displays that have been repeated over the course of an experiment. Although it is generally agreed that contextual cuing arises via an associative learning mechanism, there is uncertainty about the type(s) of process(es) that allow learning to influence RT. We contrast two leading accounts of the contextual cuing effect that differ in terms of the general process that is credited with producing the effect. The first, the expedited search account, attributes the cuing effect to an increase in the speed with which the target is acquired. The second, the decision threshold account, attributes the cuing effect to a reduction in the response threshold used by observers when making a subsequent decision about the target (e.g., judging its orientation). We use the diffusion model to contrast the quantitative predictions of these two accounts at the level of individual observers. Our use of the diffusion model allows us to also explore a novel decision-level locus of the cuing effect based on perceptual learning. This novel account attributes the RT benefit to a perceptual learning process that increases the quality of information used to drive the decision process. Our results reveal both individual differences in the process(es) involved in contextual cuing but also identify several striking regularities across observers. We find strong support for both the decision threshold account as well as the novel perceptual learning account. We find relatively weak support for the expedited search account.

Experimental analysis of multi-attribute decision-making based on Atanassov intuitionistic fuzzy sets: a discussion of anchor dependency and accuracy functions

NASA Astrophysics Data System (ADS)

Chen, Ting-Yu

2012-06-01

This article presents a useful method for relating anchor dependency and accuracy functions to multiple attribute decision-making (MADM) problems in the context of Atanassov intuitionistic fuzzy sets (A-IFSs). Considering anchored judgement with displaced ideals and solution precision with minimal hesitation, several auxiliary optimisation models have proposed to obtain the optimal weights of the attributes and to acquire the corresponding TOPSIS (the technique for order preference by similarity to the ideal solution) index for alternative rankings. Aside from the TOPSIS index, as a decision-maker's personal characteristics and own perception of self may also influence the direction in the axiom of choice, the evaluation of alternatives is conducted based on distances of each alternative from the positive and negative ideal alternatives, respectively. This article originates from Li's [Li, D.-F. (2005), 'Multiattribute Decision Making Models and Methods Using Intuitionistic Fuzzy Sets', Journal of Computer and System Sciences, 70, 73-85] work, which is a seminal study of intuitionistic fuzzy decision analysis using deduced auxiliary programming models, and deems it a benchmark method for comparative studies on anchor dependency and accuracy functions. The feasibility and effectiveness of the proposed methods are illustrated by a numerical example. Finally, a comparative analysis is illustrated with computational experiments on averaging accuracy functions, TOPSIS indices, separation measures from positive and negative ideal alternatives, consistency rates of ranking orders, contradiction rates of the top alternative and average Spearman correlation coefficients.

Pursuing the method of multiple working hypotheses to understand differences in process-based snow models

NASA Astrophysics Data System (ADS)

Clark, Martyn; Essery, Richard

2017-04-01

When faced with the complex and interdisciplinary challenge of building process-based land models, different modelers make different decisions at different points in the model development process. These modeling decisions are generally based on several considerations, including fidelity (e.g., what approaches faithfully simulate observed processes), complexity (e.g., which processes should be represented explicitly), practicality (e.g., what is the computational cost of the model simulations; are there sufficient resources to implement the desired modeling concepts), and data availability (e.g., is there sufficient data to force and evaluate models). Consequently the research community, comprising modelers of diverse background, experience, and modeling philosophy, has amassed a wide range of models, which differ in almost every aspect of their conceptualization and implementation. Model comparison studies have been undertaken to explore model differences, but have not been able to meaningfully attribute inter-model differences in predictive ability to individual model components because there are often too many structural and implementation differences among the different models considered. As a consequence, model comparison studies to date have provided limited insight into the causes of differences in model behavior, and model development has often relied on the inspiration and experience of individual modelers rather than on a systematic analysis of model shortcomings. This presentation will summarize the use of "multiple-hypothesis" modeling frameworks to understand differences in process-based snow models. Multiple-hypothesis frameworks define a master modeling template, and include a a wide variety of process parameterizations and spatial configurations that are used in existing models. Such frameworks provide the capability to decompose complex models into the individual decisions that are made as part of model development, and evaluate each decision in isolation. It is hence possible to attribute differences in system-scale model predictions to individual modeling decisions, providing scope to mimic the behavior of existing models, understand why models differ, characterize model uncertainty, and identify productive pathways to model improvement. Results will be presented applying multiple hypothesis frameworks to snow model comparison projects, including PILPS, SnowMIP, and the upcoming ESM-SnowMIP project.

A matter of tradeoffs: reintroduction as a multiple objective decision

USGS Publications Warehouse

Converse, Sarah J.; Moore, Clinton T.; Folk, Martin J.; Runge, Michael C.

2013-01-01

Decision making in guidance of reintroduction efforts is made challenging by the substantial scientific uncertainty typically involved. However, a less recognized challenge is that the management objectives are often numerous and complex. Decision makers managing reintroduction efforts are often concerned with more than just how to maximize the probability of reintroduction success from a population perspective. Decision makers are also weighing other concerns such as budget limitations, public support and/or opposition, impacts on the ecosystem, and the need to consider not just a single reintroduction effort, but conservation of the entire species. Multiple objective decision analysis is a powerful tool for formal analysis of such complex decisions. We demonstrate the use of multiple objective decision analysis in the case of the Florida non-migratory whooping crane reintroduction effort. In this case, the State of Florida was considering whether to resume releases of captive-reared crane chicks into the non-migratory whooping crane population in that state. Management objectives under consideration included maximizing the probability of successful population establishment, minimizing costs, maximizing public relations benefits, maximizing the number of birds available for alternative reintroduction efforts, and maximizing learning about the demographic patterns of reintroduced whooping cranes. The State of Florida engaged in a collaborative process with their management partners, first, to evaluate and characterize important uncertainties about system behavior, and next, to formally evaluate the tradeoffs between objectives using the Simple Multi-Attribute Rating Technique (SMART). The recommendation resulting from this process, to continue releases of cranes at a moderate intensity, was adopted by the State of Florida in late 2008. Although continued releases did not receive support from the International Whooping Crane Recovery Team, this approach does provide a template for the formal, transparent consideration of multiple, potentially competing, objectives in reintroduction decision making.

A neuroimaging investigation of attribute framing and individual differences.

PubMed

Murch, Kevin B; Krawczyk, Daniel C

2014-10-01

Functional magnetic resonance imaging was used to evaluate the neural basis of framing effects. We tested the reflexive and reflective systems model of social cognition as it relates to framing. We also examined the relationships among frame susceptibility, intelligence and personality measures. Participants evaluated whether personal attributes applied to themselves from multiple perspectives and in positive and negative frames. Participants rated whether each statement was descriptive or not and endorsed positive frames more than negative frames. Individual differences on frame decisions enabled us to form high and low frame susceptibility groups. Endorsement of frame-consistent attributes was associated with personality factors, cognitive reflection and intelligence. Reflexive brain regions were associated with positive frames while reflective areas were associated with negative frames. Region of Interest analyses showed that frame-inconsistent responses were associated with increased activation within reflective cognitive control regions including the left dorsolateral prefrontal cortex (PFC), dorsomedial PFC and left ventrolateral PFC. Frame-consistent responses were associated with increased activation in the right orbitofrontal cortex. These results demonstrate that individual differences in frame susceptibility influence personal attribute evaluations. Overall, this study clarifies the neural correlates of the reflective and reflexive systems of social cognition as applied to decisions about social attributions. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

"Your Credibility Could Be Shot": Preservice Teachers' Thinking about Nonfiction Graphic Novels, Curriculum Decision Making, and Professional Acceptance

ERIC Educational Resources Information Center

Clark, J. Spencer

2013-01-01

This article examined the value of using nonfiction graphic novels as historical narratives in the social studies curriculum. Preservice teachers evaluated several graphic novels and identified attributes of graphic novels that could contribute to students' development of historical thinking and understanding of multiple perspectives. Despite the…

Sowing seeds: transperineal implantation.

PubMed

Amerine, E; Nagle, G M; Bollinger, J R

2000-02-01

Prostate cancer, the second leading cause of male deaths in the United States, has increased by 126% since 1987 (Stephenson, 1998). Early diagnosis is attributed to public awareness and technologic advances. Multiple options for definitive treatment with equally positive outcomes dramatically influence the patient's decision-making process. One popular option for these patients is transperineal implantation of radioactive seeds into the prostate.

A rough set approach for determining weights of decision makers in group decision making

PubMed Central

Yang, Qiang; Du, Ping-an; Wang, Yong; Liang, Bin

2017-01-01

This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs’ decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member’ decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs’ evaluations and selections. PMID:28234974

Hierarchical competitions subserving multi-attribute choice

PubMed Central

Hunt, Laurence T; Dolan, Raymond J; Behrens, Timothy EJ

2015-01-01

Valuation is a key tenet of decision neuroscience, where it is generally assumed that different attributes of competing options are assimilated into unitary values. Such values are central to current neural models of choice. By contrast, psychological studies emphasize complex interactions between choice and valuation. Principles of neuronal selection also suggest competitive inhibition may occur in early valuation stages, before option selection. Here, we show behavior in multi-attribute choice is best explained by a model involving competition at multiple levels of representation. This hierarchical model also explains neural signals in human brain regions previously linked to valuation, including striatum, parietal and prefrontal cortex, where activity represents competition within-attribute, competition between attributes, and option selection. This multi-layered inhibition framework challenges the assumption that option values are computed before choice. Instead our results indicate a canonical competition mechanism throughout all stages of a processing hierarchy, not simply at a final choice stage. PMID:25306549

Putting people on the map through an approach that integrates social data in conservation planning.

PubMed

Stephanson, Sheri L; Mascia, Michael B

2014-10-01

Conservation planning is integral to strategic and effective operations of conservation organizations. Drawing upon biological sciences, conservation planning has historically made limited use of social data. We offer an approach for integrating data on social well-being into conservation planning that captures and places into context the spatial patterns and trends in human needs and capacities. This hierarchical approach provides a nested framework for characterizing and mapping data on social well-being in 5 domains: economic well-being, health, political empowerment, education, and culture. These 5 domains each have multiple attributes; each attribute may be characterized by one or more indicators. Through existing or novel data that display spatial and temporal heterogeneity in social well-being, conservation scientists, planners, and decision makers may measure, benchmark, map, and integrate these data within conservation planning processes. Selecting indicators and integrating these data into conservation planning is an iterative, participatory process tailored to the local context and planning goals. Social well-being data complement biophysical and threat-oriented social data within conservation planning processes to inform decisions regarding where and how to conserve biodiversity, provide a structure for exploring socioecological relationships, and to foster adaptive management. Building upon existing conservation planning methods and insights from multiple disciplines, this approach to putting people on the map can readily merge with current planning practices to facilitate more rigorous decision making. © 2014 Society for Conservation Biology.

The neural correlates of risky decision making across short and long runs

PubMed Central

Rao, Li-Lin; Dunn, John C.; Zhou, Yuan; Li, Shu

2015-01-01

People frequently change their preferences for options of gambles which they play once compared to those they play multiple times. In general, preferences for repeated play gambles are more consistent with the expected values of the options. According to the one-process view, the change in preference is due to a change in the structure of the gamble that is relevant to decision making. According to the two-process view, the change is attributable to a shift in the decision making strategy that is used. To adjudicate between these two theories, we asked participants to choose between gambles played once or 100 times, and to choose between them based on their expected value. Consistent with the two-process theory, we found a set of brain regions that were sensitive to the extent of behavioral change between single and aggregated play and also showed significant (de)activation in the expected value choice task. These results support the view that people change their decision making strategies for risky choice considered once or multiple times. PMID:26516095

Evidence-based Sensor Tasking for Space Domain Awareness

NASA Astrophysics Data System (ADS)

Jaunzemis, A.; Holzinger, M.; Jah, M.

2016-09-01

Space Domain Awareness (SDA) is the actionable knowledge required to predict, avoid, deter, operate through, recover from, and/or attribute cause to the loss and/or degradation of space capabilities and services. A main purpose for SDA is to provide decision-making processes with a quantifiable and timely body of evidence of behavior(s) attributable to specific space threats and/or hazards. To fulfill the promise of SDA, it is necessary for decision makers and analysts to pose specific hypotheses that may be supported or refuted by evidence, some of which may only be collected using sensor networks. While Bayesian inference may support some of these decision making needs, it does not adequately capture ambiguity in supporting evidence; i.e., it struggles to rigorously quantify 'known unknowns' for decision makers. Over the past 40 years, evidential reasoning approaches such as Dempster Shafer theory have been developed to address problems with ambiguous bodies of evidence. This paper applies mathematical theories of evidence using Dempster Shafer expert systems to address the following critical issues: 1) How decision makers can pose critical decision criteria as rigorous, testable hypotheses, 2) How to interrogate these hypotheses to reduce ambiguity, and 3) How to task a network of sensors to gather evidence for multiple competing hypotheses. This theory is tested using a simulated sensor tasking scenario balancing search versus track responsibilities.

Anthropology and decision making about chronic technological disasters: Mixed waste remediation on the Oak Ridge Reservation

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

Wolfe, A.K.; Schweitzer, M.

This paper discusses two related case studies of decision making about the remediation of mixed (hazardous and radioactive) wastes on the Oak Ridge Reservation in Tennessee. The three goals of the paper are to (1) place current decision-making efforts in the varied and evolving social, political, regulatory, economic, and technological contexts in which they occur; (2) present definitions and attributes of {open_quotes}successful{close_quotes} environmental decision making from the perspectives of key constituency groups that participate in decision making; and (3) discuss the role of anthropology in addressing environmental decision making. Environmental decision making about remediation is extraordinarily complex, involving human healthmore » and ecological risks; uncertainties about risks, technological ability to clean up, the financial costs of clean up; multiple and sometimes conflicting regulations; social equity and justice considerations; and decreasing budgets. Anthropological theories and methods can contribute to better understanding and, potentially, to better decision making.« less

Integrating evidence and individual preferences using a web-based multi-criteria decision analytic tool: an application to prostate cancer screening.

PubMed

Cunich, Michelle; Salkeld, Glenn; Dowie, Jack; Henderson, Joan; Bayram, Clare; Britt, Helena; Howard, Kirsten

2011-01-01

Annalisa© (AL) is a web-based decision-support template grounded in multi-criteria decision analysis (MCDA). It uses a simple expected value algorithm to calculate a score for each option by taking into account the individual's preferences for different criteria (as importance weights) and the evidence of the performance of each option on each criterion. Given the uncertainty surrounding the trade offs between benefits and harms for prostate cancer screening, this topic was chosen as the vehicle to introduce this new decision-support template. The aim of the study was to introduce a new decision-support template, AL, and to develop and pilot a decision-support tool for prostate cancer screening using it. A decision-support tool for prostate cancer screening (ALProst) was implemented in the AL template. ALProst incorporated evidence on both the benefits and the potential harms of prostate cancer screening (the 'attributes') from published randomized controlled trials (RCTs). Individual weights for each attribute were elicited during interviews. By combining the individual's preferences and the evidence, the best option for the user was identified on the basis of quantified scores. A convenience sample of computer-proficient primary-care physicians (general practitioners [GPs] in Australia) from the Sydney Metropolitan area (Australia) were invited to complete a face-to-face interview involving the decision-support tool. Preference for undergoing prostate-specific antigen testing for prostate cancer, both personally and for their patients, was sought prior to seeing the tool. After gaining hands-on experience with using the tool, GPs were asked to comment on the merits of the template and the tool. Preference for presenting the benefits of prostate cancer screening as the relative or absolute risk reduction in prostate cancer-specific mortality was also sought. Of 60 GPs approached, ten (six men and four women) completed an interview (16.7% response rate). Most GPs agreed/strongly agreed with positive statements about the ease with which they could use AL (seven GPs), and understand the information in, and format of, AL (nine and eight, respectively). Eight agreed/strongly agreed that ALProst would be a useful tool for discussing prostate cancer screening with their patients. GPs were also asked to nominate difficult clinical decisions that they, and their patients, have had to make; responses included cancer screening (including prostate cancer); treating patients with multiple illnesses/diseases; managing multiple cardiovascular disease risk factors; and managing patients who are receiving multiple medications. The common element was the need to consider multiple factors in making these complex decisions. AL is distinguishable from most other decision-support templates available today by its underlying conceptual framework, MCDA, and its power to combine individual preferences with evidence to derive the best option for the user quantitatively. It therefore becomes potentially useful for all decisions at all levels in the healthcare system. Moreover, it will provide a universal graphic 'language' that can overcome the burden to patients of encountering a plethora of widely varying decision aids for different conditions during their lifetime.

Qualitative Analysis of Surveyed Emergency Responders and the Identified Factors That Affect First Stage of Primary Triage Decision-Making of Mass Casualty Incidents

PubMed Central

Klein, Kelly R.; Burkle Jr., Frederick M.; Swienton, Raymond; King, Richard V.; Lehman, Thomas; North, Carol S.

2016-01-01

Introduction: After all large-scale disasters multiple papers are published describing the shortcomings of the triage methods utilized. This paper uses medical provider input to help describe attributes and patient characteristics that impact triage decisions. Methods: A survey distributed electronically to medical providers with and without disaster experience. Questions asked included what disaster experiences they had, and to rank six attributes in order of importance regarding triage. Results: 403 unique completed surveys were analyzed. 92% practiced a structural triage approach with the rest reporting they used “gestalt”.(gut feeling) Twelve per cent were identified as having placed patients in an expectant category during triage. Respiratory status, ability to speak, perfusion/pulse were all ranked in the top three. Gut feeling regardless of statistical analysis was fourth. Supplies were ranked in the top four when analyzed for those who had placed patients in the expectant category. Conclusion: Primary triage decisions in a mass casualty scenario are multifactorial and encompass patient mobility, life saving interventions, situational instincts, and logistics. PMID:27651979

Trusted Advisors, Decision Models and Other Keys to Communicating Science to Decision Makers

NASA Astrophysics Data System (ADS)

Webb, E.

2006-12-01

Water resource management decisions often involve multiple parties engaged in contentious negotiations that try to navigate through complex combinations of legal, social, hydrologic, financial, and engineering considerations. The standard approach for resolving these issues is some form of multi-party negotiation, a formal court decision, or a combination of the two. In all these cases, the role of the decision maker(s) is to choose and implement the best option that fits the needs and wants of the community. However, each path to a decision carries the risk of technical and/or financial infeasibility as well as the possibility of unintended consequences. To help reduce this risk, decision makers often rely on some type of predictive analysis from which they can evaluate the projected consequences of their decisions. Typically, decision makers are supported in the analysis process by trusted advisors who engage in the analysis as well as the day to day tasks associated with multi-party negotiations. In the case of water resource management, the analysis is frequently a numerical model or set of models that can simulate various management decisions across multiple systems and output results that illustrate the impact on areas of concern. Thus, in order to communicate scientific knowledge to the decision makers, the quality of the communication between the analysts, the trusted advisor, and the decision maker must be clear and direct. To illustrate this concept, a multi-attribute decision analysis matrix will be used to outline the value of computer model-based collaborative negotiation approaches to guide water resources decision making and communication with decision makers. In addition, the critical role of the trusted advisor and other secondary participants in the decision process will be discussed using examples from recent water negotiations.

Choosing spouses and houses: Impaired congruence between preference and choice following damage to the ventromedial prefrontal cortex.

PubMed

Bowren, Mark D; Croft, Katie E; Reber, Justin; Tranel, Daniel

2018-03-01

A well-documented effect of focal ventromedial prefrontal cortex (vmPFC) damage is a deficit in real-world decision making. An important aspect of this deficit may be a deficiency in "internal consistency" during social decision making-that is, impaired congruence between expressed preferences versus actual behavioral choices. An example of low internal consistency would be if one expressed the desire to marry someone with impeccable moral character, yet proceeded to marry someone convicted of multiple felonies. Here, we used a neuropsychological approach to investigate neural correlates of internal consistency in complex decision making. Sixteen individuals with focal vmPFC lesions, 16 brain damage comparison individuals, and 16 normal comparison individuals completed a 3-option forced-choice preference task in which choices were made using attribute sets. Participants also completed visual-analogue preference ratings to indicate how much they liked each option, and rated the influence of each attribute on their decision making. Options were either social (potential spouses) or nonsocial (potential houses). Internal consistency for a trial was defined as agreement between the choice and the most positively rated option. A mixed design analysis of variance revealed that internal consistency between choices and preferences derived from summed attribute ratings was significantly lower for the vmPFC group relative to comparison participants, but only in the social condition (pη2 = .09), 95% CI [.002, .163]. Internal consistency during social decisions may be deficient in patients with vmPFC damage, leading to a discrepancy between preferences and choices. The vmPFC may provide an important neural mechanism for aligning behavioral choices with expressed preferences. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Choosing Spouses and Houses: Impaired Congruence Between Preference and Choice Following Damage to the Ventromedial Prefrontal Cortex

PubMed Central

Bowren, Mark D.; Croft, Katie E.; Reber, Justin; Tranel, Daniel

2017-01-01

Objective A well-documented effect of focal ventromedial prefrontal cortex (vmPFC) damage is a deficit in real-world decision-making. An important aspect of this deficit may be a deficiency in “internal consistency” during social decision-making – that is, impaired congruence between expressed preferences versus actual behavioral choices. An example of low internal consistency would be if one expressed the desire to marry someone with impeccable moral character,” yet proceeded to marry someone convicted of multiple felonies. Here, we used a neuropsychological approach to investigate neural correlates of internal consistency in complex decision-making. Method Sixteen individuals with focal vmPFC lesions, 16 brain-damage comparison individuals, and 16 normal comparison individuals completed a three-option forced-choice preference task in which choices were made using attribute sets. Participants also completed visual-analogue preference ratings to indicate how much they liked each option, and rated the influence of each attribute on their decision-making. Options were either social (potential spouses) or non-social (potential houses). Internal consistency for a trial was defined as agreement between the choice and the most positively rated option. Results A mixed design ANOVA revealed that internal consistency between choices and preferences derived from summed attribute ratings was significantly lower for the vmPFC group relative to comparison participants, but only in the social condition (pη2 = .09), 95% CI [.002, .163]. Conclusions Internal consistency during social decisions may be deficient in patients with vmPFC damage, leading to a discrepancy between preferences and choices. The vmPFC may provide an important neural mechanism for aligning behavioral choices with expressed preferences. PMID:29620403

Necessary Contributions of Human Frontal Lobe Subregions to Reward Learning in a Dynamic, Multidimensional Environment.

PubMed

Vaidya, Avinash R; Fellows, Lesley K

2016-09-21

Real-world decisions are typically made between options that vary along multiple dimensions, requiring prioritization of the important dimensions to support optimal choice. Learning in this setting depends on attributing decision outcomes to the dimensions with predictive relevance rather than to dimensions that are irrelevant and nonpredictive. This attribution problem is computationally challenging, and likely requires an interplay between selective attention and reward learning. Both these processes have been separately linked to the prefrontal cortex, but little is known about how they combine to support learning the reward value of multidimensional stimuli. Here, we examined the necessary contributions of frontal lobe subregions in attributing feedback to relevant and irrelevant dimensions on a trial-by-trial basis in humans. Patients with focal frontal lobe damage completed a demanding reward learning task where options varied on three dimensions, only one of which predicted reward. Participants with left lateral frontal lobe damage attributed rewards to irrelevant dimensions, rather than the relevant dimension. Damage to the ventromedial frontal lobe also impaired learning about the relevant dimension, but did not increase reward attribution to irrelevant dimensions. The results argue for distinct roles for these two regions in learning the value of multidimensional decision options under dynamic conditions, with the lateral frontal lobe required for selecting the relevant dimension to associate with reward, and the ventromedial frontal lobe required to learn the reward association itself. The real world is complex and multidimensional; how do we attribute rewards to predictive features when surrounded by competing cues? Here, we tested the critical involvement of human frontal lobe subregions in a probabilistic, multidimensional learning environment, asking whether focal lesions affected trial-by-trial attribution of feedback to relevant and irrelevant dimensions. The left lateral frontal lobe was required for filtering option dimensions to allow appropriate feedback attribution, while the ventromedial frontal lobe was necessary for learning the value of features in the relevant dimension. These findings argue that selective attention and associative learning processes mediated by anatomically distinct frontal lobe subregions are both critical for adaptive choice in more complex, ecologically valid settings. Copyright © 2016 the authors 0270-6474/16/369843-16$15.00/0.

Blame attribution as a moderator of perceptions of sexual orientation-based hate crimes.

PubMed

Cramer, Robert J; Chandler, Joseph F; Wakeman, Emily E

2010-05-01

Blame attribution is a valuable mechanism explaining decision making. However, present literature mainly employs blame attribution as a dependent variable. The shortcoming of this fact is that blame attribution offers a potentially valuable explanatory mechanism for decision making. The authors designed two studies to investigate blame attribution as a moderator of sentencing decisions in sexual orientation-based hate crimes. Study 1 showed that mock jurors punished perpetrators of hate crimes more severely than a control condition. Also, degree of victim blame influenced punitive decision making. In Study 2, mock jurors extended findings that perpetrators of hate crimes are more harshly punished than those of other types of crimes. Victim and perpetrator blame failed to moderate decision making in this more complex scenario. Results are discussed in relation to hate crimes definitions and attribution theory.

Using Simpson's diversity index to examine multidimensional models of diversity in health professions education.

PubMed

McLaughlin, Jacqueline E; McLaughlin, Gerald W; McLaughlin, Josetta S; White, Carla Y

2016-01-03

This study explored new models of diversity for health professions education that incorporate multiple attributes and examined differences in diversity based on urbanicity, geographic region, and institutional structure. Simpson's Diversity Index was used to develop race, gender, and interprofessional diversity indices for health professions schools in the United States (N = 318). Sullivan's extension was used to develop a composite diversity index that incorporated multiple individual attributes for each school. Pearson's r was used to investigate correlations between continuous variables. ANOVA and independent t-tests were used to compare groups based on urbanicity, geographic region, and Basic Carnegie Classification. Mean (SD) for race, gender, and interprofessional diversity indices were 0.36(0.17), 0.45(0.07), and 0.22(0.27) respectively. All correlations between the three indices were weak. The composite diversity index for this sample was 0.34(0.13). Significant differences in diversity were found between institutions based on urbanicity, Basic Carnegie Classification, and geographic region. Multidimensional models provide support for expanding measures of diversity to include multiple characteristics and attributes. The approach demonstrated in this study enables institutions to complement and extend traditional measures of diversity as a means of providing evidence for decision-making and progress towards institutional initiatives.

Using Simpson’s diversity index to examine multidimensional models of diversity in health professions education

PubMed Central

McLaughlin, Gerald W.; McLaughlin, Josetta S.; White, Carla Y.

2016-01-01

Objectives This study explored new models of diversity for health professions education that incorporate multiple attributes and examined differences in diversity based on urbanicity, geographic region, and institutional structure. Methods Simpson’s Diversity Index was used to develop race, gender, and interprofessional diversity indices for health professions schools in the United States (N = 318). Sullivan’s extension was used to develop a composite diversity index that incorporated multiple individual attributes for each school. Pearson’s r was used to investigate correlations between continuous variables. ANOVA and independent t-tests were used to compare groups based on urbanicity, geographic region, and Basic Carnegie Classification. Results Mean (SD) for race, gender, and interprofessional  diversity indices were 0.36(0.17), 0.45(0.07), and 0.22(0.27) respectively. All correlations between the three indices were weak. The composite diversity index for this sample was 0.34(0.13). Significant differences in diversity were found between institutions based on urbanicity, Basic Carnegie Classification, and geographic region. Conclusions Multidimensional models provide support for expanding measures of diversity to include multiple characteristics and attributes. The approach demonstrated in this study enables institutions to complement and extend traditional measures of diversity as a means of providing evidence for decision-making and progress towards institutional initiatives. PMID:26724917

Multiple Criteria Decision Analysis (MCDA) for evaluating new medicines in Health Technology Assessment and beyond: The Advance Value Framework.

PubMed

Angelis, Aris; Kanavos, Panos

2017-09-01

Escalating drug prices have catalysed the generation of numerous "value frameworks" with the aim of informing payers, clinicians and patients on the assessment and appraisal process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions. In this paper, a Multiple Criteria Decision Analysis (MCDA) methodological process, based on Multi Attribute Value Theory (MAVT), is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down "value-focused thinking" approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers' concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory. The resulting value tree (Advance Value Tree) consists of three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative treatment options, assigning relative weights of importance to the criteria, and combining scores and weights. Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a structured and transparent way. Given its flexibility to meet diverse requirements and become readily adaptable across different settings, the Advance Value Framework could be offered as a decision-support tool for evaluators and payers to aid coverage and reimbursement of new medicines. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race.

PubMed

Warnke, Tom; Reinhardt, Oliver; Klabunde, Anna; Willekens, Frans; Uhrmacher, Adelinde M

2017-10-01

Individuals' decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for Linked Lives (ML3) to describe the diverse decision processes of linked lives succinctly in continuous time. The context of individuals is modelled by networks the individual is part of, such as family ties and other social networks. Central concepts, such as behaviour conditional on agent attributes, age-dependent behaviour, and stochastic waiting times, are tightly integrated in the language. Thereby, alternative decisions are modelled by concurrent processes that compete by stochastic race. Using a migration model, we demonstrate how this allows for compact description of complex decisions, here based on the Theory of Planned Behaviour. We describe the challenges for the simulation algorithm posed by stochastic race between multiple concurrent complex decisions.

Rationality in collective decision-making by ant colonies.

PubMed

Edwards, Susan C; Pratt, Stephen C

2009-10-22

Economic models of animal behaviour assume that decision-makers are rational, meaning that they assess options according to intrinsic fitness value and not by comparison with available alternatives. This expectation is frequently violated, but the significance of irrational behaviour remains controversial. One possibility is that irrationality arises from cognitive constraints that necessitate short cuts like comparative evaluation. If so, the study of whether and when irrationality occurs can illuminate cognitive mechanisms. We applied this logic in a novel setting: the collective decisions of insect societies. We tested for irrationality in colonies of Temnothorax ants choosing between two nest sites that varied in multiple attributes, such that neither site was clearly superior. In similar situations, individual animals show irrational changes in preference when a third relatively unattractive option is introduced. In contrast, we found no such effect in colonies. We suggest that immunity to irrationality in this case may result from the ants' decentralized decision mechanism. A colony's choice does not depend on site comparison by individuals, but instead self-organizes from the interactions of multiple ants, most of which are aware of only a single site. This strategy may filter out comparative effects, preventing systematic errors that would otherwise arise from the cognitive limitations of individuals.

Thermal power systems small power systems applications project. Decision analysis for evaluating and ranking small solar thermal power system technologies. Volume 1: A brief introduction to multiattribute decision analysis. [explanation of multiattribute decision analysis methods used in evaluating alternatives for small powered systems

NASA Technical Reports Server (NTRS)

Feinberg, A.; Miles, R. F., Jr.

1978-01-01

The principal concepts of the Keeney and Raiffa approach to multiattribute decision analysis are described. Topics discussed include the concepts of decision alternatives, outcomes, objectives, attributes and their states, attribute utility functions, and the necessary independence properties for the attribute states to be aggregated into a numerical representation of the preferences of the decision maker for the outcomes and decision alternatives.

Attributions of responsibility and affective reactions to decision outcomes.

PubMed

Zeelenberg, M; van der Pligt, J; de Vries, N K

2000-06-01

Immediate affective reactions to outcomes are more intense following decisions to act than following decisions not to act. This finding holds for both positive and negative outcomes. We relate this "actor-effect" to attribution theory and argue that decision makers are seen as more responsible for outcomes when these are the result of a decision to act as compared to a decision not to act. Experiment 1 (N = 80) tests the main assumption underlying our reasoning and shows that affective reactions to decision outcomes are indeed more intense when the decision maker is seen as more responsible. Experiment 2 (N = 40) tests whether the actor effect can be predicted on the basis of differential attributions following action and inaction. Participants read vignettes in which active and passive actors obtained a positive or negative outcome. Action resulted in more intense affect than inaction, and positive outcomes resulted in more intense affect than negative outcomes. Experiment 2 further shows that responsibility attributions and affective reactions to outcomes are highly correlated; that is, more extreme affective reactions are associated with more internal attributions. We discuss the implications for research on post-decisional reactions.

Demands on attention and the role of response priming in visual discrimination of feature conjunctions.

PubMed

Fournier, Lisa R; Herbert, Rhonda J; Farris, Carrie

2004-10-01

This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less discriminable of these features alone was faster (conjunction benefits) when the task-relevant features differed in discriminability and were consistently mapped to responses. Conjunction benefits were attributed to asynchronous decision priming across attended, task-relevant dimensions. A failure to find conjunction benefits for disjunctive conjunctions was attributed to increased memory demands and variable feature-response mapping for 2- versus single-feature targets. Further, attentional demands were similar between single- and 2-feature targets when response mapping, memory demands, and discriminability of the task-relevant features were equated between targets. Implications of the findings for recent attention models are discussed. (c) 2004 APA, all rights reserved

Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews.

PubMed

Kuesten, Carla; Bi, Jian

2018-06-03

Conventional drivers of liking analysis was extended with a time dimension into temporal drivers of liking (TDOL) based on functional data analysis methodology and non-additive models for multiple-attribute time-intensity (MATI) data. The non-additive models, which consider both direct effects and interaction effects of attributes to consumer overall liking, include Choquet integral and fuzzy measure in the multi-criteria decision-making, and linear regression based on variance decomposition. Dynamics of TDOL, i.e., the derivatives of the relative importance functional curves were also explored. Well-established R packages 'fda', 'kappalab' and 'relaimpo' were used in the paper for developing TDOL. Applied use of these methods shows that the relative importance of MATI curves offers insights for understanding the temporal aspects of consumer liking for fruit chews.

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Rejecting a bad option feels like choosing a good one.

PubMed

Perfecto, Hannah; Galak, Jeff; Simmons, Joseph P; Nelson, Leif D

2017-11-01

Across 4,151 participants, the authors demonstrate a novel framing effect, attribute matching, whereby matching a salient attribute of a decision frame with that of a decision's options facilitates decision-making. This attribute matching is shown to increase decision confidence and, ultimately, consensus estimates by increasing feelings of metacognitive ease. In Study 1, participants choosing the more attractive of two faces or rejecting the less attractive face reported greater confidence in and perceived consensus around their decision. Using positive and negative words, Study 2 showed that the attribute's extremity moderates the size of the effect. Study 3 found decision ease mediates these changes in confidence and consensus estimates. Consistent with a misattribution account, when participants were warned about this external source of ease in Study 4, the effect disappeared. Study 5 extended attribute matching beyond valence to objective judgments. The authors conclude by discussing related psychological constructs as well as downstream consequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average.

PubMed

Gorsevski, Pece V; Donevska, Katerina R; Mitrovski, Cvetko D; Frizado, Joseph P

2012-02-01

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessing the Effects of Financial Literacy on Patient Engagement.

PubMed

Meyer, Melanie A; Hudak, Ronald P

2016-07-01

We investigated the relationship between financial literacy and patient engagement while considering the possible interaction effects due to patient financial responsibility and patient-physician shared decision making, and the impact of personal attributes. Participants consisted of an Internet-based sample of American adults (N = 160). Hierarchical multiple linear regression analysis was conducted to examine the relationship of the study variables on patient engagement. We found that patient financial responsibility (β = -.19, p < .05) and patient-physician shared decision-making (β = .17, p < .05) predicted patient engagement. However, there was no statistically significant relationship between patient financial literacy and patient engagement; moreover, the moderation effects of patient financial responsibility and shared decision making with financial literacy also were not statistically significant. Increasing patient financial responsibility and patient-physician shared decision making can impact patient engagement. Understanding the predictors of patient engagement and the factors that influence financial behaviors may allow for the development of interventions to enable patients to make better healthcare decisions, and ultimately, improve health outcomes.

Extracting multistage screening rules from online dating activity data.

PubMed

Bruch, Elizabeth; Feinberg, Fred; Lee, Kee Yeun

2016-09-20

This paper presents a statistical framework for harnessing online activity data to better understand how people make decisions. Building on insights from cognitive science and decision theory, we develop a discrete choice model that allows for exploratory behavior and multiple stages of decision making, with different rules enacted at each stage. Critically, the approach can identify if and when people invoke noncompensatory screeners that eliminate large swaths of alternatives from detailed consideration. The model is estimated using deidentified activity data on 1.1 million browsing and writing decisions observed on an online dating site. We find that mate seekers enact screeners ("deal breakers") that encode acceptability cutoffs. A nonparametric account of heterogeneity reveals that, even after controlling for a host of observable attributes, mate evaluation differs across decision stages as well as across identified groupings of men and women. Our statistical framework can be widely applied in analyzing large-scale data on multistage choices, which typify searches for "big ticket" items.

Extracting multistage screening rules from online dating activity data

PubMed Central

Bruch, Elizabeth; Feinberg, Fred; Lee, Kee Yeun

2016-01-01

This paper presents a statistical framework for harnessing online activity data to better understand how people make decisions. Building on insights from cognitive science and decision theory, we develop a discrete choice model that allows for exploratory behavior and multiple stages of decision making, with different rules enacted at each stage. Critically, the approach can identify if and when people invoke noncompensatory screeners that eliminate large swaths of alternatives from detailed consideration. The model is estimated using deidentified activity data on 1.1 million browsing and writing decisions observed on an online dating site. We find that mate seekers enact screeners (“deal breakers”) that encode acceptability cutoffs. A nonparametric account of heterogeneity reveals that, even after controlling for a host of observable attributes, mate evaluation differs across decision stages as well as across identified groupings of men and women. Our statistical framework can be widely applied in analyzing large-scale data on multistage choices, which typify searches for “big ticket” items. PMID:27578870

A Novel Hybrid MADM Based Competence Set Expansions of a SOC Design Service Firm

NASA Astrophysics Data System (ADS)

Huang, Chi-Yo; Tzeng, Gwo-Hshiung; Lue, Yeou-Feng; Chuang, Hsiu-Tyan

As the IC (integrated circuit) industry migrates to the System-on-Chip (SOC) era, a novel business model, the SOC design service (DS), is emerging. However, how to expand a firm’s innovation competences while satisfying multiple objectives including highest quality, lowest cost, and fastest time to market as well as most revenues for economics of scale are always problems for a design service firm. Therefore, attempts to expand the innovation competences, and thus the competitiveness, of latecomers in the SOC DS industry have already become the most critical issue facing the top managers of SOC design service firms. In this paper, a novel multiple attribute decision making (MADM) analytic framework based on the concept of competence set expansion, as well as MADM methods consisting with DEMATEL, ANP and multiple objective decision making (MODM) will be proposed in order to define a path for expanding a late-coming SOC DS firm’s innovation capabilities. An empirical study on expanding innovation competence sets, of a late-coming Taiwanese DS firm then will be presented.

Time to decision: the drivers of innovation adoption decisions

NASA Astrophysics Data System (ADS)

Ciganek, Andrew Paul; (Dave) Haseman, William; Ramamurthy, K.

2014-03-01

Organisations desire timeliness. Timeliness facilitates a better responsiveness to changes in an organisation's external environment to either attain or maintain competitiveness. Despite its importance, decision timeliness has not been explicitly examined. Decision timeliness is measured in this study as the time taken to commit to a decision. The research objective is to identify the drivers of decision timeliness in the context of adopting service-oriented architecture (SOA), an innovation for enterprise computing. A research model rooted in the technology-organisation-environment (TOE) framework is proposed and tested with data collected in a large-scale study. The research variables have been examined before in the context of adoption, but their applicability to the timeliness of innovation decision-making has not received much attention and their salience is unclear. The results support multiple hypothesised relationships, including the finding that a risk-oriented organisational culture as well as normative and coercive pressures accelerates decision timeliness. Top management support as well as the traditional innovation attributes (compatibility, relative advantage and complexity/ease-of-use) were not found to be significant when examining their influence on decision timeliness, which appears inconsistent with generally accepted knowledge and deserves further examination.

Attention and attribute overlap in preferential choice.

PubMed

Bhatia, Sudeep

2017-07-01

Attributes that are common, or overlapping, across alternatives in two-alternative forced preferential choice tasks are often non-diagnostic. In many settings, attending to and evaluating these attributes does not help the decision maker determine which of the available alternatives is the most desirable. For this reason, many existing behavioural theories propose that decision makers ignore common attributes while deliberating. Across six experiments, we find that decision makers do direct their attention selectively and ignore attributes that are not present in or associated with either of the available alternatives. However, they are as likely to attend to common attributes as they are to attend to attributes that are unique to a single alternative. These results suggest the need for novel theories of attention in preferential choice.

Informing vaccine decision-making: A strategic multi-attribute ranking tool for vaccines-SMART Vaccines 2.0.

PubMed

Knobler, Stacey; Bok, Karin; Gellin, Bruce

2017-01-20

SMART Vaccines 2.0 software is being developed to support decision-making among multiple stakeholders in the process of prioritizing investments to optimize the outcomes of vaccine development and deployment. Vaccines and associated vaccination programs are one of the most successful and effective public health interventions to prevent communicable diseases and vaccine researchers are continually working towards expanding targets for communicable and non-communicable diseases through preventive and therapeutic modes. A growing body of evidence on emerging vaccine technologies, trends in disease burden, costs associated with vaccine development and deployment, and benefits derived from disease prevention through vaccination and a range of other factors can inform decision-making and investment in new and improved vaccines and targeted utilization of already existing vaccines. Recognizing that an array of inputs influences these decisions, the strategic multi-attribute ranking method for vaccines (SMART Vaccines 2.0) is in development as a web-based tool-modified from a U.S. Institute of Medicine Committee effort (IOM, 2015)-to highlight data needs and create transparency to facilitate dialogue and information-sharing among decision-makers and to optimize the investment of resources leading to improved health outcomes. Current development efforts of the SMART Vaccines 2.0 framework seek to generate a weighted recommendation on vaccine development or vaccination priorities based on population, disease, economic, and vaccine-specific data in combination with individual preference and weights of user-selected attributes incorporating valuations of health, economics, demographics, public concern, scientific and business, programmatic, and political considerations. Further development of the design and utility of the tool is being carried out by the National Vaccine Program Office of the Department of Health and Human Services and the Fogarty International Center of the National Institutes of Health. We aim to demonstrate the utility of SMART Vaccines 2.0 through the engagement of a community of relevant stakeholders and to identify a limited number of pilot projects to determine explicitly defined attribute preferences and the related data and model requirements that are responsive to user needs and able to improve the use of evidence for vaccine-related decision-making and consequential priorities of vaccination options. Copyright © 2016 Elsevier Ltd. All rights reserved.

Attributes Affecting Computer-Aided Decision Making--A Literature Survey.

ERIC Educational Resources Information Center

Moldafsky, Neil I; Kwon, Ik-Whan

1994-01-01

Reviews current literature about personal, demographic, situational, and cognitive attributes that affect computer-aided decision making. The effectiveness of computer-aided decision making is explored in relation to decision quality, effectiveness, and confidence. Studies of the effects of age, anxiety, cognitive type, attitude, gender, and prior…

An interval-valued 2-tuple linguistic group decision-making model based on the Choquet integral operator

NASA Astrophysics Data System (ADS)

Liu, Bingsheng; Fu, Meiqing; Zhang, Shuibo; Xue, Bin; Zhou, Qi; Zhang, Shiruo

2018-01-01

The Choquet integral (IL) operator is an effective approach for handling interdependence among decision attributes in complex decision-making problems. However, the fuzzy measures of attributes and attribute sets required by IL are difficult to achieve directly, which limits the application of IL. This paper proposes a new method for determining fuzzy measures of attributes by extending Marichal's concept of entropy for fuzzy measure. To well represent the assessment information, interval-valued 2-tuple linguistic context is utilised to represent information. Then, we propose a Choquet integral operator in an interval-valued 2-tuple linguistic environment, which can effectively handle the correlation between attributes. In addition, we apply these methods to solve multi-attribute group decision-making problems. The feasibility and validity of the proposed operator is demonstrated by comparisons with other models in illustrative example part.

Blame Attribution as a Moderator of Perceptions of Sexual Orientation-Based Hate Crimes

ERIC Educational Resources Information Center

Cramer, Robert J.; Chandler, Joseph F.; Wakeman, Emily E.

2010-01-01

Blame attribution is a valuable mechanism explaining decision making. However, present literature mainly employs blame attribution as a dependent variable. The shortcoming of this fact is that blame attribution offers a potentially valuable explanatory mechanism for decision making. The authors designed two studies to investigate blame attribution…

Memory-based decision-making with heuristics: evidence for a controlled activation of memory representations.

PubMed

Khader, Patrick H; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rösler, Frank

2011-11-01

Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by activating long-term memory representations of only those attributes that are necessary for the decision. However, from behavioral studies alone, it is unclear whether using heuristics is indeed associated with limited memory search. The present study tested this assumption by monitoring the activation of specific long-term-memory representations with fMRI while participants made memory-based decisions using the "take-the-best" heuristic. For different decision trials, different numbers and types of information had to be retrieved and processed. The attributes consisted of visual information known to be represented in different parts of the posterior cortex. We found that the amount of information required for a decision was mirrored by a parametric activation of the dorsolateral PFC. Such a parametric pattern was also observed in all posterior areas, suggesting that activation was not limited to those attributes required for a decision. However, the posterior increases were systematically modulated by the relative importance of the information for making a decision. These findings suggest that memory-based decision-making is mediated by the dorsolateral PFC, which selectively controls posterior storage areas. In addition, the systematic modulations of the posterior activations indicate a selective boosting of activation of decision-relevant attributes.

Rationality in collective decision-making by ant colonies

PubMed Central

Edwards, Susan C.; Pratt, Stephen C.

2009-01-01

Economic models of animal behaviour assume that decision-makers are rational, meaning that they assess options according to intrinsic fitness value and not by comparison with available alternatives. This expectation is frequently violated, but the significance of irrational behaviour remains controversial. One possibility is that irrationality arises from cognitive constraints that necessitate short cuts like comparative evaluation. If so, the study of whether and when irrationality occurs can illuminate cognitive mechanisms. We applied this logic in a novel setting: the collective decisions of insect societies. We tested for irrationality in colonies of Temnothorax ants choosing between two nest sites that varied in multiple attributes, such that neither site was clearly superior. In similar situations, individual animals show irrational changes in preference when a third relatively unattractive option is introduced. In contrast, we found no such effect in colonies. We suggest that immunity to irrationality in this case may result from the ants’ decentralized decision mechanism. A colony's choice does not depend on site comparison by individuals, but instead self-organizes from the interactions of multiple ants, most of which are aware of only a single site. This strategy may filter out comparative effects, preventing systematic errors that would otherwise arise from the cognitive limitations of individuals. PMID:19625319

Patient autonomy in multiple sclerosis--possible goals and assessment strategies.

PubMed

Heesen, C; Köpke, S; Solari, A; Geiger, F; Kasper, J

2013-08-15

Patient autonomy has been increasingly acknowledged as prerequisite for successful medical decision making in Western countries. In medical decisions with a need to involve a health professional, patient autonomy becomes apparent in the extent of patients' participation in the communication as described in the concept of shared decision making. Patient autonomy can be derived from different perspectives or goals and the focus of evaluation approaches may vary accordingly. Multiple sclerosis (MS) is a paradigmatic disease to study patient autonomy mainly because MS patients are highly disease competent and due to ambiguous evidence on many aspects of disease-related medical decision making. This review gives an overview on measurement issues in studying decision making in MS, categorized according to prerequisites, process measures and outcomes of patient autonomy. As relevant prerequisites role preferences, risk attribution, risk tolerance, and risk knowledge are discussed. Regarding processes, we distinguish intra-psychic and interpersonal aspects. Intra-psychic processes are elucidated using the theory of planned behavior, which guided development of a 30-item scale to capture decisions about immunotherapy. Moreover, a theory of uncertainty management has been created resulting in the development of a corresponding measurement concept. Interpersonal processes evolving between physician and patient can be thoroughly analyzed from different perspectives by use of the newly developed comprehensive MAPPIN'SDM inventory. Concerning outcomes, besides health related outcomes, we discuss match of preferred roles during the decision encounters (preference match), decisional conflict as well as an application of the multidimensional measure of informed choice to decisions of MS patients. These approaches provide an overview on patient-inherent and interpersonal factors and processes modulating medical decision making and health behavior in MS and beyond. Copyright © 2013. Published by Elsevier B.V.

Segmenting a general practitioner market to improve recruitment outcomes.

PubMed

Hemphill, Elizabeth; Kulik, Carol T

2011-05-01

Recruitment is an ongoing challenge in the health industry with general practitioner (GP) shortages in many areas beyond rural and Indigenous communities. This paper suggests a marketing solution that identifies different segments of the GP market for recruitment strategy development. In February 2008, 96 GPs in Australia responded to a mail questionnaire (of which 85 questionnaires were useable). A total of 350 GPs were sent the questionnaire. Respondents considered small sets of attributes in the decision to accept a new job at a general practice and selected the most and least important attribute from each set. We identified latent class clusters (cohorts) of GPs from the most-least important data. Three cohorts were found in the GP market, distinguishing practitioners who emphasised job, family or practice attributes in their decision to join a practice. Few significant demographic differences exist between the cohorts. A segmented GP market suggests two alternative recruitment strategies. One option is for general practices to target members of a single cohort (family-, job-, or practice-focussed GPs). The other option is for general practices to diversify their recruitment strategies to target all three cohorts (family-, job- and practice-focussed GPs). A single brand (practice) can have multiple advertising strategies with each strategy involving advertising activities targeting a particular consumer segment.

PeerShield: determining control and resilience criticality of collaborative cyber assets in networks

NASA Astrophysics Data System (ADS)

Cam, Hasan

2012-06-01

As attackers get more coordinated and advanced in cyber attacks, cyber assets are required to have much more resilience, control effectiveness, and collaboration in networks. Such a requirement makes it essential to take a comprehensive and objective approach for measuring the individual and relative performances of cyber security assets in network nodes. To this end, this paper presents four techniques as to how the relative importance of cyber assets can be measured more comprehensively and objectively by considering together the main variables of risk assessment (e.g., threats, vulnerabilities), multiple attributes (e.g., resilience, control, and influence), network connectivity and controllability among collaborative cyber assets in networks. In the first technique, a Bayesian network is used to include the random variables for control, recovery, and resilience attributes of nodes, in addition to the random variables of threats, vulnerabilities, and risk. The second technique shows how graph matching and coloring can be utilized to form collaborative pairs of nodes to shield together against threats and vulnerabilities. The third technique ranks the security assets of nodes by incorporating multiple weights and thresholds of attributes into a decision-making algorithm. In the fourth technique, the hierarchically well-separated tree is enhanced to first identify critical nodes of a network with respect to their attributes and network connectivity, and then selecting some nodes as driver nodes for network controllability.

Comparative analysis of decision maker preferences for equity/efficiency attributes in reimbursement decisions in three European countries.

PubMed

Baji, Petra; García-Goñi, Manuel; Gulácsi, László; Mentzakis, Emmanouil; Paolucci, Francesco

2016-09-01

In addition to cost-effectiveness, national guidelines often include other factors in reimbursement decisions. However, weights attached to these are rarely quantified, thus decisions can depend strongly on decision-maker preferences. To explore the preferences of policymakers and healthcare professionals involved in the decision-making process for different efficiency and equity attributes of interventions and to analyse cross-country differences. Discrete choice experiments (DCEs) were carried out in Austria, Hungary, and Norway with policymakers and other professionals working in the health industry (N = 153 respondents). Interventions were described in terms of different efficiency and equity attributes (severity of disease, target age of the population and willingness to subsidise others, potential number of beneficiaries, individual health benefit, and cost-effectiveness). Parameter estimates from the DCE were used to calculate the probability of choosing a healthcare intervention with different characteristics, and to rank different equity and efficiency attributes according to their importance. In all three countries, cost-effectiveness, individual health benefit and severity of the disease were significant and equally important determinants of decisions. All countries show preferences for interventions targeting young and middle aged populations compared to those targeting populations over 60. However, decision-makers in Austria and Hungary show preferences more oriented to efficiency than equity, while those in Norway show equal preferences for equity and efficiency attributes. We find that factors other than cost-effectiveness seem to play an equally important role in decision-making. We also find evidence of cross-country differences in the weight of efficiency and equity attributes.

The influence of expert opinions on the selection of wastewater treatment alternatives: a group decision-making approach.

PubMed

Kalbar, Pradip P; Karmakar, Subhankar; Asolekar, Shyam R

2013-10-15

The application of multiple-attribute decision-making (MADM) to real life decision problems suggests that avoiding the loss of information through scenario-based approaches and including expert opinions in the decision-making process are two major challenges that require more research efforts. Recently, a wastewater treatment technology selection effort has been made with a 'scenario-based' method of MADM. This paper focuses on a novel approach to incorporate expert opinions into the scenario-based decision-making process, as expert opinions play a major role in the selection of treatment technologies. The sets of criteria and the indicators that are used consist of both qualitative and quantitative criteria. The group decision-making (GDM) approach that is implemented for aggregating expert opinions is based on an analytical hierarchy process (AHP), which is the most widely used MADM method. The pairwise comparison matrices (PCMs) for qualitative criteria are formed based on expert opinions, whereas, a novel approach is proposed for generating PCMs for quantitative criteria. It has been determined that the experts largely prefer natural treatment systems because they are more sustainable in any scenario. However, PCMs based on expert opinions suggest that advanced technologies such as the sequencing batch reactor (SBR) can also be appropriate for a given decision scenario. The proposed GDM approach is a rationalized process that will be more appropriate in realistic scenarios where multiple stakeholders with local and regional societal priorities are involved in the selection of treatment technology. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dual conception of risk in the Iowa Gambling Task: effects of sleep deprivation and test-retest gap.

PubMed

Singh, Varsha

2013-01-01

Risk in the Iowa Gambling Task (IGT) is often understood in terms of intertemporal choices, i.e., preference for immediate outcomes in favor of delayed outcomes is considered risky decision making. According to behavioral economics, healthy decision makers are expected to refrain from choosing the short-sighted immediate gain because, over time (10 trials of the IGT), the immediate gains result in a long term loss (net loss). Instead decision makers are expected to maximize their gains by choosing options that, over time (10 trials), result in delayed or long term gains (net gain). However, task choices are sometimes made on the basis of the frequency of reward and punishment such that frequent rewards/infrequent punishments are favored over infrequent rewards/frequent punishments. The presence of these two attributes (intertemporality and frequency of reward) in IGT decision making may correspond to the emotion-cognition dichotomy and reflect a dual conception of risk. Decision making on the basis of the two attributes was tested under two conditions: delay in retest and sleep deprivation. An interaction between sleep deprivation and time delay was expected to attenuate the difference between the two attributes. Participants were 40 male university students. Analysis of the effects of IGT attribute type (intertemporal vs. frequency of reinforcement), sleep deprivation (sleep deprivation vs. no sleep deprivation), and test-retest gap (short vs. long delay) showed a significant within-subjects effect of IGT attribute type thus confirming the difference between the two attributes. Sleep deprivation had no effect on the attributes, but test-retest gap and the three-way interaction between attribute type, test-retest gap, and sleep deprivation were significantly different. Post-hoc tests revealed that sleep deprivation and short test-retest gap attenuated the difference between the two attributes. Furthermore, the results showed an expected trend of increase in intertemporal decision making at retest suggesting that intertemporal decision making benefited from repeated task exposure. The present findings add to understanding of the emotion-cognition dichotomy. Further, they show an important time-dependent effect of a universally experienced constraint (sleep deprivation) on decision making. It is concluded that risky decision making in the IGT is contingent on the attribute under consideration and is affected by factors such as time elapsed and constraint experienced before the retest.

Multi-Attribute Tradespace Exploration in Space System Design

NASA Astrophysics Data System (ADS)

Ross, A. M.; Hastings, D. E.

2002-01-01

The complexity inherent in space systems necessarily requires intense expenditures of resources both human and monetary. The high level of ambiguity present in the early design phases of these systems causes long, highly iterative, and costly design cycles. This paper looks at incorporating decision theory methods into the early design processes to streamline communication of wants and needs among stakeholders and between levels of design. Communication channeled through formal utility interviews and analysis enables engineers to better understand the key drivers for the system and allows a more thorough exploration of the design tradespace. Multi-Attribute Tradespace Exploration (MATE), an evolving process incorporating decision theory into model and simulation- based design, has been applied to several space system case studies at MIT. Preliminary results indicate that this process can improve the quality of communication to more quickly resolve project ambiguity, and enable the engineer to discover better value designs for multiple stakeholders. MATE is also being integrated into a concurrent design environment to facilitate the transfer knowledge of important drivers into higher fidelity design phases. Formal utility theory provides a mechanism to bridge the language barrier between experts of different backgrounds and differing needs (e.g. scientists, engineers, managers, etc). MATE with concurrent design couples decision makers more closely to the design, and most importantly, maintains their presence between formal reviews.

I know why you voted for Trump: (Over)inferring motives based on choice.

PubMed

Barasz, Kate; Kim, Tami; Evangelidis, Ioannis

2018-05-10

People often speculate about why others make the choices they do. This paper investigates how such inferences are formed as a function of what is chosen. Specifically, when observers encounter someone else's choice (e.g., of political candidate), they use the chosen option's attribute values (e.g., a candidate's specific stance on a policy issue) to infer the importance of that attribute (e.g., the policy issue) to the decision-maker. Consequently, when a chosen option has an attribute whose value is extreme (e.g., an extreme policy stance), observers infer-sometimes incorrectly-that this attribute disproportionately motivated the decision-maker's choice. Seven studies demonstrate how observers use an attribute's value to infer its weight-the value-weight heuristic-and identify the role of perceived diagnosticity: more extreme attribute values give observers the subjective sense that they know more about a decision-maker's preferences, and in turn, increase the attribute's perceived importance. The paper explores how this heuristic can produce erroneous inferences and influence broader beliefs about decision-makers. Copyright © 2018 Elsevier B.V. All rights reserved.

A Decision Analysis Perspective on Multiple Response Robust Optimization

DTIC Science & Technology

2012-03-01

the utility function in question is monotonically increasing and is twice differentiable . If γ(y) = 0, the utility function is describing risk neutral...twice differentiable , the risk aversion function with respect to a single attribute, yi, i = 1, . . . , n, is given in Equation 2.9, γUyi = − U ′′yi U...UV (V (y1, y2)) and fol- lowing the chain rule of differentiation , Matheson and Abbas [31] show that the risk aversion with respect to a single

Group Decision Making Based on Heronian Aggregation Operators of Intuitionistic Fuzzy Numbers.

PubMed

Liu, Peide; Chen, Shyi-Ming

2017-09-01

Archimedean t -conorm and t -norm provide the general operational rules for intuitionistic fuzzy numbers (IFNs). The aggregation operators based on them can generalize most of the existing aggregation operators. At the same time, the Heronian mean (HM) has a significant advantage of considering interrelationships between the attributes. Therefore, it is very necessary to extend the HM based on IFNs and to construct intuitionistic fuzzy HM operators based on the Archimedean t -conorm and t -norm. In this paper, we first discuss intuitionistic fuzzy operational rules based on the Archimedean t -conorm and t -norm. Then, we propose the intuitionistic fuzzy Archimedean Heronian aggregation (IFAHA) operator and the intuitionistic fuzzy weight Archimedean Heronian aggregation (IFWAHA) operator. We also further discuss some properties and some special cases of these new operators. Moreover, we also propose a new multiple attribute group decision making (MAGDM) method based on the proposed IFAHA operator and the proposed IFWAHA operator. Finally, we use an illustrative example to show the MAGDM processes and to illustrate the effectiveness of the developed method.

Patient‐focussed decision‐making in early‐stage prostate cancer: insights from a cognitively based decision aid

PubMed Central

Feldman‐Stewart, Deb; Brundage, Michael D; Manen, Lori Van; Svenson, Ola

2004-01-01

Abstract Purpose  To study the cognitive processes of early‐stage prostate cancer patients as they determined which treatment they preferred, using our cognitively based decision aid. Method  The aid was a one‐to‐one interview that included the structured presentation of information, listing exercises in which the patient identified attributes important to his decision, and trade‐off exercises to help him weigh and integrate those attributes together. At various points of the interview, patients identified the attributes they felt were important to their decision, rated their treatment options and completed standardized assessments relating to their decision. In addition, patients participated in a follow‐up interview at the time they made their actual treatment decision and again 3 months later. Results  Sixty of 70 (86%) of the invited patients participated in the study. Participating patients identified a median of four important attributes (range 1–10); 36 different attributes were identified at some point in the interview by the group. During the interview, 78% of patients changed which attributes they considered important, and 72% changed their treatment ratings. Stability of treatment choice after the interview and lack of regret after the decision were each positively associated with increasing differentiation between treatment options over time. Conclusions  The decision process appears to be dynamic for the patients with great variability across patients in what is important to the decision. Increasing stability of choice and lack of regret appear to be related positively to increasing difference over time in how attractive the preferred option is over its closest competitor, rather than to the size of the difference at any one point in time. PMID:15117387

Waiving away the chance of freedom: exploring why prisoners decide against applying for parole.

PubMed

Best, Brianna L; Wodahl, Eric J; Holmes, Malcolm D

2014-03-01

Little is known about inmates' decisions regarding seeking release on parole, even though many choose to waive their parole hearings. Using semistructured, in-depth interviews with 25 adult male parole-eligible inmates who had waived a parole hearing, we seek to better understand the reasons inmates forgo the possibility of parole. We frame the study in rational choice theory, which suggests that inmates balance the perceived costs and benefits of remaining in prison versus returning to the community in reaching their decisions. A large majority of inmates attributed the decision to waive their hearings, in part, to concerns about the hearing process (e.g., parole denial likely, fear of negative experience), and most also listed various reasons that made remaining in prison a better outcome compared with release on parole (e.g., prison easier than parole, fear of revocation). The findings suggest that inmates' parole waiver decisions involve multiple factors that merit further examination.

The Relationship of Decision-Making Styles and Attributional Styles in Addicted and Non-addicted Men.

PubMed

Shaghaghy, Farhad; Saffarinia, Majid; Iranpoor, Mohadeseh; Soltanynejad, Ali

2011-01-01

One of social problems which has affected our society and resulted in problems for different groups of people is drug abuse. This issue indicates a serious psychological, physical and social problem in community. Social skills have positive and successful influences in prevention of substance abuse. This includes the ability to explain events correctly and then appropriate decision making. This study compares decision making styles and attributional styles between addicted and non addicted men to recognize their role in addiction. In this study, 200 addicted and non addicted men were randomly selected. Decision-making style and attributional style questionnaires were used. Data analysis was performed by independent Student's t and Pearson correlation tests. The study population included 81 addicted and 90 non-addicted men. Addicted and non addicted men were significantly different in rational decision-making style (P < 0.05). Negative relationship was found between rational decision making and optimistic attribution style (r = -0.305, P < 0.01) and direct relationship was found between rational decision making and learned helplessness (r = 0.309, P < 0.01). Our study showed that addicts are less rational in decision making and addicts that developed learned helplessness were less rational and did not have optimistic attribution style. These issues show that addiction institutions and therapists have to pay attention to cognitive factors for addiction prevention.

The effect of subjective awareness measures on performance in artificial grammar learning task.

PubMed

Ivanchei, Ivan I; Moroshkina, Nadezhda V

2018-01-01

Systematic research into implicit learning requires well-developed awareness-measurement techniques. Recently, trial-by-trial measures have been widely used. However, they can increase complexity of a study because they are an additional experimental variable. We tested the effects of these measures on performance in artificial grammar learning study. Four groups of participants were assigned to different awareness measures conditions: confidence ratings, post-decision wagering, decision strategy attribution or none. Decision-strategy-attribution participants demonstrated better grammar learning and longer response times compared to controls. They also exhibited a conservative bias. Grammaticality by itself was a stronger predictor of strings endorsement in decision-strategy-attribution group compared to other groups. Confidence ratings and post-decision wagering only affected the response times. These results were supported by an additional experiment that used a balanced chunk strength design. We conclude that a decision-strategy-attribution procedure may force participants to adopt an analytical decision-making strategy and rely mostly on conscious knowledge of artificial grammar. Copyright © 2017 Elsevier Inc. All rights reserved.

An explanatory analysis of driver injury severity in rear-end crashes using a decision table/Naïve Bayes (DTNB) hybrid classifier.

PubMed

Chen, Cong; Zhang, Guohui; Yang, Jinfu; Milton, John C; Alcántara, Adélamar Dely

2016-05-01

Rear-end crashes are a major type of traffic crashes in the U.S. Of practical necessity is a comprehensive examination of its mechanism that results in injuries and fatalities. Decision table (DT) and Naïve Bayes (NB) methods have both been used widely but separately for solving classification problems in multiple areas except for traffic safety research. Based on a two-year rear-end crash dataset, this paper applies a decision table/Naïve Bayes (DTNB) hybrid classifier to select the deterministic attributes and predict driver injury outcomes in rear-end crashes. The test results show that the hybrid classifier performs reasonably well, which was indicated by several performance evaluation measurements, such as accuracy, F-measure, ROC, and AUC. Fifteen significant attributes were found to be significant in predicting driver injury severities, including weather, lighting conditions, road geometry characteristics, driver behavior information, etc. The extracted decision rules demonstrate that heavy vehicle involvement, a comfortable traffic environment, inferior lighting conditions, two-lane rural roadways, vehicle disabled damage, and two-vehicle crashes would increase the likelihood of drivers sustaining fatal injuries. The research limitations on data size, data structure, and result presentation are also summarized. The applied methodology and estimation results provide insights for developing effective countermeasures to alleviate rear-end crash injury severities and improve traffic system safety performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Patient centered decision making: use of conjoint analysis to determine risk-benefit trade-offs for preference sensitive treatment choices.

PubMed

Wilson, Leslie; Loucks, Aimee; Bui, Christine; Gipson, Greg; Zhong, Lixian; Schwartzburg, Amy; Crabtree, Elizabeth; Goodin, Douglas; Waubant, Emmanuelle; McCulloch, Charles

2014-09-15

Understanding patient preferences facilitates shared decision-making and focuses on patient-centered outcomes. Little is known about relapsing-remitting multiple sclerosis (RRMS) patient preferences for disease modifying therapies (DMTs). We use choice based conjoint (CBC) analysis to calculate patient preferences for risk/benefit trade-offs for hypothetical DMTs. Patients with RRMS were surveyed between 2012 and 2013. Our CBC survey mimicked the decision-making process and trade-offs of patients choosing DMTs, based on all possible DMT attributes. Mixed-effects logistic regression analyzed preferences. We estimated maximum acceptable risk trade-offs for various DMT benefits. Severe side-effect risks had the biggest impact on patient preference with a 1% risk, decreasing patient preference five-fold compared to no risk. (OR=0.22, p<0.001). Symptom improvement was the most preferred benefit (OR=3.68, p<0.001), followed by prevention of progression of 10 years (OR=2.4, p<0.001). Daily oral administration had the third highest DMT preference rating (OR=2.08, p<0.001). Patients were willing to accept 0.08% severe risk for a year delayed relapse, and 0.22% for 4 vs 2 year prevented progression. We provided patient preferences and risk-benefit trade-offs for attributes of all available DMTs. Evaluation of patient preferences is a key step in shared decision making and may significantly impact early drug initiation and compliance. Copyright © 2014 Elsevier B.V. All rights reserved.

Critical care nurses' decision making: sedation assessment and management in intensive care.

PubMed

Aitken, Leanne M; Marshall, Andrea P; Elliott, Rosalind; McKinley, Sharon

2009-01-01

This study was designed to examine the decision making processes that nurses use when assessing and managing sedation for a critically ill patient, specifically the attributes and concepts used to determine sedation needs and the influence of a sedation guideline on the decision making processes. Sedation management forms an integral component of the care of critical care patients. Despite this, there is little understanding of how nurses make decisions regarding assessment and management of intensive care patients' sedation requirements. Appropriate nursing assessment and management of sedation therapy is essential to quality patient care. Observational study. Nurses providing sedation management for a critically ill patient were observed and asked to think aloud during two separate occasions for two hours of care. Follow-up interviews were conducted to collect data from five expert critical care nurses pre- and postimplementation of a sedation guideline. Data from all sources were integrated, with data analysis identifying the type and number of attributes and concepts used to form decisions. Attributes and concepts most frequently used related to sedation and sedatives, anxiety and agitation, pain and comfort and neurological status. On average each participant raised 48 attributes related to sedation assessment and management in the preintervention phase and 57 attributes postintervention. These attributes related to assessment (pre, 58%; post, 65%), physiology (pre, 10%; post, 9%) and treatment (pre, 31%; post, 26%) aspects of care. Decision making in this setting is highly complex, incorporating a wide range of attributes that concentrate primarily on assessment aspects of care. Clinical guidelines should provide support for strategies known to positively influence practice. Further, the education of nurses to use such guidelines optimally must take into account the highly complex iterative process and wide range of data sources used to make decisions.

Preferences of processing companies for attributes of Swiss milk: a conjoint analysis in a business-to-business market.

PubMed

Boesch, I

2013-04-01

This study aimed to determine key attributes of milk that drive a processor's supply decisions and possibilities for differentiation based on these product attributes. Feedback-driven exploration was applied to derive product attributes relevant to the buying decision. Conjoint analysis with hierarchical Bayes estimation methods was used to determine the relative importance of attributes. Results show that the technical aspects of milk, as well as the price and country of origin, dominate the buying decision. Potential for differentiation was found for environmental and societal attributes as well as freedom from genetically modified products. Product and supplier criteria also provide the potential to segment the market if the price premium is held within limits. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space

PubMed Central

McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon

2015-01-01

Introduction Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses—where outcomes are considered separately, with their joint relationship under uncertainty ignored—lead to incorrect inference regarding preferred strategies. Objective The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Methods Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Results Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Conclusion Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple effects under uncertainty across potential threshold values for effect, better informing net benefit assessment and related reimbursement and research decisions. PMID:25751629

Visualization-based decision support for value-driven system design

NASA Astrophysics Data System (ADS)

Tibor, Elliott

In the past 50 years, the military, communication, and transportation systems that permeate our world, have grown exponentially in size and complexity. The development and production of these systems has seen ballooning costs and increased risk. This is particularly critical for the aerospace industry. The inability to deal with growing system complexity is a crippling force in the advancement of engineered systems. Value-Driven Design represents a paradigm shift in the field of design engineering that has potential to help counteract this trend. The philosophy of Value-Driven Design places the desires of the stakeholder at the forefront of the design process to capture true preferences and reveal system alternatives that were never previously thought possible. Modern aerospace engineering design problems are large, complex, and involve multiple levels of decision-making. To find the best design, the decision-maker is often required to analyze hundreds or thousands of combinations of design variables and attributes. Visualization can be used to support these decisions, by communicating large amounts of data in a meaningful way. Understanding the design space, the subsystem relationships, and the design uncertainties is vital to the advancement of Value-Driven Design as an accepted process for the development of more effective, efficient, robust, and elegant aerospace systems. This research investigates the use of multi-dimensional data visualization tools to support decision-making under uncertainty during the Value-Driven Design process. A satellite design system comprising a satellite, ground station, and launch vehicle is used to demonstrate effectiveness of new visualization methods to aid in decision support during complex aerospace system design. These methods are used to facilitate the exploration of the feasible design space by representing the value impact of system attribute changes and comparing the results of multi-objective optimization formulations with a Value-Driven Design formulation. The visualization methods are also used to assist in the decomposition of a value function, by representing attribute sensitivities to aid with trade-off studies. Lastly, visualization is used to enable greater understanding of the subsystem relationships, by displaying derivative-based couplings, and the design uncertainties, through implementation of utility theory. The use of these visualization methods is shown to enhance the decision-making capabilities of the designer by granting them a more holistic view of the complex design space.

The Voice of the Patient Methodology: A Novel Mixed-Methods Approach to Identifying Treatment Goals for Men with Prostate Cancer.

PubMed

Saigal, Christopher S; Lambrechts, Sylvia I; Seenu Srinivasan, V; Dahan, Ely

2017-06-01

Many guidelines advocate the use of shared decision making for men with newly diagnosed prostate cancer. Decision aids can facilitate the process of shared decision making. Implicit in this approach is the idea that physicians understand which elements of treatment matter to patients. Little formal work exists to guide physicians or developers of decision aids in identifying these attributes. We use a mixed-methods technique adapted from marketing science, the 'Voice of the Patient', to describe and identify treatment elements of value for men with localized prostate cancer. We conducted semi-structured interviews with 30 men treated for prostate cancer in the urology clinic of the West Los Angeles Veteran Affairs Medical Center. We used a qualitative analysis to generate themes in patient narratives, and a quantitative approach, agglomerative hierarchical clustering, to identify attributes of treatment that were most relevant to patients making decisions about prostate cancer. We identified five 'traditional' prostate cancer treatment attributes: sexual dysfunction, bowel problems, urinary problems, lifespan, and others' opinions. We further identified two novel treatment attributes: a treatment's ability to validate a sense of proactivity and the need for an incision (separate from risks of surgery). Application of a successful marketing technique, the 'Voice of the Customer', in a clinical setting elicits non-obvious attributes that highlight unique patient decision-making concerns. Use of this method in the development of decision aids may result in more effective decision support.

Neural Signatures of Controlled and Automatic Retrieval Processes in Memory-based Decision-making.

PubMed

Khader, Patrick H; Pachur, Thorsten; Weber, Lilian A E; Jost, Kerstin

2016-01-01

Decision-making often requires retrieval from memory. Drawing on the neural ACT-R theory [Anderson, J. R., Fincham, J. M., Qin, Y., & Stocco, A. A central circuit of the mind. Trends in Cognitive Sciences, 12, 136-143, 2008] and other neural models of memory, we delineated the neural signatures of two fundamental retrieval aspects during decision-making: automatic and controlled activation of memory representations. To disentangle these processes, we combined a paradigm developed to examine neural correlates of selective and sequential memory retrieval in decision-making with a manipulation of associative fan (i.e., the decision options were associated with one, two, or three attributes). The results show that both the automatic activation of all attributes associated with a decision option and the controlled sequential retrieval of specific attributes can be traced in material-specific brain areas. Moreover, the two facets of memory retrieval were associated with distinct activation patterns within the frontoparietal network: The dorsolateral prefrontal cortex was found to reflect increasing retrieval effort during both automatic and controlled activation of attributes. In contrast, the superior parietal cortex only responded to controlled retrieval, arguably reflecting the sequential updating of attribute information in working memory. This dissociation in activation pattern is consistent with ACT-R and constitutes an important step toward a neural model of the retrieval dynamics involved in memory-based decision-making.

Survival or Mortality: Does Risk Attribute Framing Influence Decision-Making Behavior in a Discrete Choice Experiment?

PubMed

Veldwijk, Jorien; Essers, Brigitte A B; Lambooij, Mattijs S; Dirksen, Carmen D; Smit, Henriette A; de Wit, G Ardine

2016-01-01

To test how attribute framing in a discrete choice experiment (DCE) affects respondents' decision-making behavior and their preferences. Two versions of a DCE questionnaire containing nine choice tasks were distributed among a representative sample of the Dutch population aged 55 to 65 years. The DCE consisted of four attributes related to the decision regarding participation in genetic screening for colorectal cancer (CRC). The risk attribute included was framed positively as the probability of surviving CRC and negatively as the probability of dying from CRC. Panel mixed-logit models were used to estimate the relative importance of the attributes. The data of the positively and negatively framed DCE were compared on the basis of direct attribute ranking, dominant decision-making behavior, preferences, and importance scores. The majority (56%) of the respondents ranked survival as the most important attribute in the positively framed DCE, whereas only a minority (8%) of the respondents ranked mortality as the most important attribute in the negatively framed DCE. Respondents made dominant choices based on survival significantly more often than based on mortality. The framing of the risk attribute significantly influenced all attribute-level estimates and resulted in different preference structures among respondents in the positively and negatively framed data set. Risk framing affects how respondents value the presented risk. Positive risk framing led to increased dominant decision-making behavior, whereas negative risk framing led to risk-seeking behavior. Attribute framing should have a prominent part in the expert and focus group interviews, and different types of framing should be used in the pilot version of DCEs as well as in actual DCEs to estimate the magnitude of the effect of choosing different types of framing. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Attribute Development Using Continuous Stakeholder Engagement to Prioritize Treatment Decisions: A Framework for Patient-Centered Research.

PubMed

dosReis, Susan; Castillo, Wendy Camelo; Ross, Melissa; Fitz-Randolph, Marcy; Vaughn-Lee, Angela; Butler, Beverly

To develop a methodological approach for selecting, validating, and prioritizing attributes for health care decision making. Participants (n = 48) were recruited from community support groups if they had a child aged 26 years or younger diagnosed with a coexisting mental health condition and cognitive impairment. Six in-depth interviews eliciting care management experiences were transcribed and coded into themes following the principles of grounded theory and the constant comparative method. Six focus groups involving 42 participants assessed the relevance, priority, and meaning and inter-relationship among the themes. The positive predictive value and sensitivity assessed agreement on thematic meaning. A final list was selected from the top priorities with good agreement as candidate attributes. Attribute levels reflecting the range of experiences in care management decisions emerged from the verbatim passages within each coded theme. Participants were the child's mother (73%), white (77%), married (69%), and on average 48 years old. The children were on average 14 years old; 44% had an intellectual disability, 25% had autism, and more than half had anxiety or attention-deficit/hyperactivity disorder. All 14 attributes identified from the in-depth interviews were deemed relevant. The positive predictive value exceeded 90%, and the sensitivity ranged from 64% to 89%. The final set of attributes formed the framework for care management decisions consisting of six attributes (medication, behavior, services, social, treatment effects, and school) each with three levels. A systematic approach grounded in qualitative methods produced a framework of relevant, important, and actionable attributes representing competing alternatives in clinical decisions. Copyright © 2016. Published by Elsevier Inc.

Privacy Protection on Multiple Sensitive Attributes

NASA Astrophysics Data System (ADS)

Li, Zhen; Ye, Xiaojun

In recent years, a privacy model called k-anonymity has gained popularity in the microdata releasing. As the microdata may contain multiple sensitive attributes about an individual, the protection of multiple sensitive attributes has become an important problem. Different from the existing models of single sensitive attribute, extra associations among multiple sensitive attributes should be invested. Two kinds of disclosure scenarios may happen because of logical associations. The Q&S Diversity is checked to prevent the foregoing disclosure risks, with an α Requirement definition used to ensure the diversity requirement. At last, a two-step greedy generalization algorithm is used to carry out the multiple sensitive attributes processing which deal with quasi-identifiers and sensitive attributes respectively. We reduce the overall distortion by the measure of Masking SA.

GPA and Attribute Framing Effects: Are Better Students More Sensitive or More Susceptible?

ERIC Educational Resources Information Center

Dunegan, Ken

2010-01-01

Data from 2 studies show students differ in terms of how attribute framing alters perceptions and reactions in a decision-making episode. Using student GPA as a moderator, results from a role-play-decision-making exercise (Experiment 1) show perceptions and intended actions of higher GPA students were more strongly affected by attribute framing…

Medical decision-making and the patient: understanding preference patterns for growth hormone therapy using conjoint analysis.

PubMed

Singh, J; Cuttler, L; Shin, M; Silvers, J B; Neuhauser, D

1998-08-01

This study examines two questions that relate to patients' role in medical decision making: (1) Do patients utilize multiple attributes in evaluating different treatment options?, and (2) Do patient treatment preferences evidence heterogeneity and disparate patterns? Although research has examined these questions by using either individual- or aggregate-level approaches, the authors demonstrate an intermediate level approach (ie, relating to patient subgroups). The authors utilize growth augmentation therapy (GAT) as a context for analyzing these questions because GAT reflects a class of nonemergency treatments that (1) are based on genetic technology, (2) aim to improve the quality (rather than quantity) of life, and (3) offer useful insights for the patient's role in medical decision making. Using conjoint analysis, a methodology especially suited for the study of patient-consumer preferences but largely unexplored in the medical field, data were obtained from 154 parents for their decision to pursue GAT for their child. In all, six attributes were utilized to study GAT, including risk of long-term side effects (1:10,000 or 1:100,000), certainty of effect (50% or 100% of cases), amount of effect (1-2 inches or 4-5 inches in adult height), out-of-pocket cost ($100, $2,000, or $10,000/year) and child's attitude (likes or not likes therapy). An experimental design using conjoint analysis procedures revealed five preference patterns that reflect clear disparities in the importance that parents attach to the different attributes of growth therapy. These preference patterns are (1) child-focused (23%), (2) risk-conscious (36%), (3) balanced (23%), (4) cost-conscious (14%), and (5) ease-of-use (4%) oriented. Additional tests provided evidence for the validity of these preference patterns. Finally, this preference heterogeneity related systematically to parental characteristics (eg, demographic, psychologic). The study results offer additional insights into medical decision making with the consumer as the focal point and extend previous work that has tended to emphasize either an individual- or aggregate-based analysis. Implications for researchers and health care delivery in general and growth hormone management in particular are provided.

Lawyers' attitudes toward involuntary treatment.

PubMed

Luchins, Daniel J; Cooper, Amy E; Hanrahan, Patricia; Heyrman, Mark J

2006-01-01

This study examined whether lawyers' attributions of responsibility for mental illnesses affect their decisions about involuntary treatment. A survey that was mailed in 2003 to Illinois lawyers involved in involuntary commitment elicited recommendations for involuntary treatment for characters presented in vignettes. The survey also sought respondents' attributions of personal responsibility for the onset and recurrence of mental illnesses. A total of 89 lawyers responded to the survey, a response rate of 48 percent. Decisions to hospitalize persons with mental illness involuntarily increased significantly with the level of risk of harm and were significantly related to attributions of responsibility for the recurrence of mental illness. Decisions to recommend involuntary medication were not related to attributions of responsibility.

Research on Attribute Reduction in Hoisting Motor State Recognition of Quayside Container Crane

NASA Astrophysics Data System (ADS)

Li, F.; Tang, G.; Hu, X.

2017-07-01

In view of too many attributes in hoisting motor state recognition of quayside container crane. Attribute reduction method based on discernibility matrix is introduced to attribute reduction of lifting motor state information table. A method of attribute reduction based on the combination of rough set and genetic algorithm is proposed to deal with the hoisting motor state decision table. Under the condition that the information system's decision-making ability is unchanged, the redundant attribute is deleted. Which reduces the complexity and computation of the recognition process of the hoisting motor. It is possible to realize the fast state recognition.

Rigorously testing multialternative decision field theory against random utility models.

PubMed

Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg

2014-06-01

Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions. PsycINFO Database Record (c) 2014 APA, all rights reserved.

An intelligent, knowledge-based multiple criteria decision making advisor for systems design

NASA Astrophysics Data System (ADS)

Li, Yongchang

In systems engineering, design and operation of systems are two main problems which always attract researcher's attentions. The accomplishment of activities in these problems often requires proper decisions to be made so that the desired goal can be achieved, thus, decision making needs to be carefully fulfilled in the design and operation of systems. Design is a decision making process which permeates through out the design process, and is at the core of all design activities. In modern aircraft design, more and more attention is paid to the conceptual and preliminary design phases so as to increase the odds of choosing a design that will ultimately be successful at the completion of the design process, therefore, decisions made during these early design stages play a critical role in determining the success of a design. Since aerospace systems are complex systems with interacting disciplines and technologies, the Decision Makers (DMs) dealing with such design problems are involved in balancing the multiple, potentially conflicting attributes/criteria, transforming a large amount of customer supplied guidelines into a solidly defined set of requirement definitions. Thus, one could state with confidence that modern aerospace system design is a Multiple Criteria Decision Making (MCDM) process. A variety of existing decision making methods are available to deal with this type of decision problems. The selection of the most appropriate decision making method is of particular importance since inappropriate decision methods are likely causes of misleading engineering design decisions. With no sufficient knowledge about each of the methods, it is usually difficult for the DMs to find an appropriate analytical model capable of solving their problems. In addition, with the complexity of the decision problem and the demand for more capable methods increasing, new decision making methods are emerging with time. These various methods exacerbate the difficulty of the selection of an appropriate decision making method. Furthermore, some DMs may be exclusively using one or two specific methods which they are familiar with or trust and not realizing that they may be inappropriate to handle certain classes of the problems, thus yielding erroneous results. These issues reveal that in order to ensure a good decision a suitable decision method should be chosen before the decision making process proceeds. The first part of this dissertation proposes an MCDM process supported by an intelligent, knowledge-based advisor system referred to as Multi-Criteria Interactive Decision-Making Advisor and Synthesis process (MIDAS), which is able to facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. The second part of this dissertation presents an autonomous decision making advisor which is capable of dealing with ever-evolving real time information and making autonomous decisions under uncertain conditions. The advisor encompasses a Markov Decision Process (MDP) formulation which takes uncertainty into account when determines the best action for each system state. (Abstract shortened by UMI.)

Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting.

PubMed

Carpenter, Stephanie M; Yates, J Frank; Preston, Stephanie D; Chen, Lydia

2016-01-01

Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional "coherence shifting," the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed.

Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting

PubMed Central

Carpenter, Stephanie M.; Yates, J. Frank; Preston, Stephanie D.; Chen, Lydia

2016-01-01

Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional “coherence shifting,” the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed. PMID:26986752

Multi-criteria decision analysis in environmental sciences: ten years of applications and trends.

PubMed

Huang, Ivy B; Keisler, Jeffrey; Linkov, Igor

2011-09-01

Decision-making in environmental projects requires consideration of trade-offs between socio-political, environmental, and economic impacts and is often complicated by various stakeholder views. Multi-criteria decision analysis (MCDA) emerged as a formal methodology to face available technical information and stakeholder values to support decisions in many fields and can be especially valuable in environmental decision making. This study reviews environmental applications of MCDA. Over 300 papers published between 2000 and 2009 reporting MCDA applications in the environmental field were identified through a series of queries in the Web of Science database. The papers were classified by their environmental application area, decision or intervention type. In addition, the papers were also classified by the MCDA methods used in the analysis (analytic hierarchy process, multi-attribute utility theory, and outranking). The results suggest that there is a significant growth in environmental applications of MCDA over the last decade across all environmental application areas. Multiple MCDA tools have been successfully used for environmental applications. Even though the use of the specific methods and tools varies in different application areas and geographic regions, our review of a few papers where several methods were used in parallel with the same problem indicates that recommended course of action does not vary significantly with the method applied. Published by Elsevier B.V.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media.

PubMed

Sonter, Laura J; Watson, Keri B; Wood, Spencer A; Ricketts, Taylor H

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18-20.2 at 95% confidence) to Vermont's tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making.

Meeting the challenge of interacting threats in freshwater ecosystems: A call to scientists and managers

USGS Publications Warehouse

Craig, Laura S.; Olden, Julian D.; Arthington, Angela; Entrekin, Sally; Hawkins, Charles P.; Kelly, John J.; Kennedy, Theodore A.; Maitland, Bryan M.; Rosi, Emma J.; Roy, Allison; Strayer, David L.; Tank, Jennifer L.; West, Amie O.; Wooten, Matthew S.

2017-01-01

Human activities create threats that have consequences for freshwater ecosystems and, in most watersheds, observed ecological responses are the result of complex interactions among multiple threats and their associated ecological alterations. Here we discuss the value of considering multiple threats in research and management, offer suggestions for filling knowledge gaps, and provide guidance for addressing the urgent management challenges posed by multiple threats in freshwater ecosystems. There is a growing literature assessing responses to multiple alterations, and we build off this background to identify three areas that require greater attention: linking observed alterations to threats, understanding when and where threats overlap, and choosing metrics that best quantify the effects of multiple threats. Advancing science in these areas will help us understand existing ecosystem conditions and predict future risk from multiple threats. Because addressing the complex issues and novel ecosystems that arise from the interaction of multiple threats in freshwater ecosystems represents a significant management challenge, and the risks of management failure include loss of biodiversity, ecological goods, and ecosystem services, we also identify actions that could improve decision-making and management outcomes. These actions include drawing insights from management of individual threats, using threat attributes (e.g., causes and spatio-temporal dynamics) to identify suitable management approaches, testing management strategies that are likely to be successful despite uncertainties about the nature of interactions among threats, avoiding unintended consequences, and maximizing conservation benefits. We also acknowledge the broadly applicable challenges of decision-making within a socio-political and economic framework, and suggest that multidisciplinary teams will be needed to innovate solutions to meet the current and future challenge of interacting threats in freshwater ecosystems. 

A potential role of reward and punishment in the facilitation of the emotion-cognition dichotomy in the Iowa Gambling Task.

PubMed

Singh, Varsha

2013-01-01

The Iowa Gambling Task (IGT) is based on the assumption that a decision maker is equally motivated to seek reward and avoid punishment, and that decision making is governed solely by the intertemporal attribute (i.e., preference for an option that produces an immediate outcome instead of one that yields a delayed outcome is believed to reflect risky decision making and is considered a deficit). It was assumed in the present study that the emotion- and cognition-based processing dichotomy manifests in the IGT as reward and punishment frequency and the intertemporal attribute. It was further proposed that the delineation of emotion- and cognition-based processing is contingent upon reward and punishment as manifested in the frame of the task (variant type) and task motivation (instruction type). The effects of IGT variant type (reward vs. punishment) and instruction type (task motivation induced by instruction types: reward, punishment, reward and punishment, or no hint) on the intertemporal and frequency attributes of IGT decision-making were analyzed. Decision making in the reward variant was equally governed by both attributes, and significantly affected by instruction type, while decision making in the punishment variant was differentially affected by the two attributes and not significantly impacted by instruction type. These results suggest that reward and punishment manifested via task frame as well as the task motivation may facilitate the differentiation of emotion- and cognition-based processing in the IGT.

A potential role of reward and punishment in the facilitation of the emotion-cognition dichotomy in the Iowa Gambling Task

PubMed Central

Singh, Varsha

2013-01-01

The Iowa Gambling Task (IGT) is based on the assumption that a decision maker is equally motivated to seek reward and avoid punishment, and that decision making is governed solely by the intertemporal attribute (i.e., preference for an option that produces an immediate outcome instead of one that yields a delayed outcome is believed to reflect risky decision making and is considered a deficit). It was assumed in the present study that the emotion- and cognition-based processing dichotomy manifests in the IGT as reward and punishment frequency and the intertemporal attribute. It was further proposed that the delineation of emotion- and cognition-based processing is contingent upon reward and punishment as manifested in the frame of the task (variant type) and task motivation (instruction type). The effects of IGT variant type (reward vs. punishment) and instruction type (task motivation induced by instruction types: reward, punishment, reward and punishment, or no hint) on the intertemporal and frequency attributes of IGT decision-making were analyzed. Decision making in the reward variant was equally governed by both attributes, and significantly affected by instruction type, while decision making in the punishment variant was differentially affected by the two attributes and not significantly impacted by instruction type. These results suggest that reward and punishment manifested via task frame as well as the task motivation may facilitate the differentiation of emotion- and cognition-based processing in the IGT. PMID:24381567

Application of preprocessing filtering on Decision Tree C4.5 and rough set theory

NASA Astrophysics Data System (ADS)

Chan, Joseph C. C.; Lin, Tsau Y.

2001-03-01

This paper compares two artificial intelligence methods: the Decision Tree C4.5 and Rough Set Theory on the stock market data. The Decision Tree C4.5 is reviewed with the Rough Set Theory. An enhanced window application is developed to facilitate the pre-processing filtering by introducing the feature (attribute) transformations, which allows users to input formulas and create new attributes. Also, the application produces three varieties of data set with delaying, averaging, and summation. The results prove the improvement of pre-processing by applying feature (attribute) transformations on Decision Tree C4.5. Moreover, the comparison between Decision Tree C4.5 and Rough Set Theory is based on the clarity, automation, accuracy, dimensionality, raw data, and speed, which is supported by the rules sets generated by both algorithms on three different sets of data.

Comparing Analytic Hierarchy Process and Discrete-Choice Experiment to Elicit Patient Preferences for Treatment Characteristics in Age-Related Macular Degeneration.

PubMed

Danner, Marion; Vennedey, Vera; Hiligsmann, Mickaël; Fauser, Sascha; Gross, Christian; Stock, Stephanie

2017-09-01

In this study, we conducted an analytic hierarchy process (AHP) and a discrete choice experiment (DCE) to elicit the preferences of patients with age-related macular degeneration using identical attributes and levels. To compare preference-based weights for age-related macular degeneration treatment attributes and levels generated by two elicitation methods. The properties of both methods were assessed, including ease of instrument use. A DCE and an AHP experiment were designed on the basis of five attributes. Preference-based weights were generated using the matrix multiplication method for attributes and levels in AHP and a mixed multinomial logit model for levels in the DCE. Attribute importance was further compared using coefficient (DCE) and weight (AHP) level ranges. The questionnaire difficulty was rated on a qualitative scale. Patients were asked to think aloud while providing their judgments. AHP and DCE generated similar results regarding levels, stressing a preference for visual improvement, frequent monitoring, on-demand and less frequent injection schemes, approved drugs, and mild side effects. Attribute weights derived on the basis of level ranges led to a ranking that was opposite to the AHP directly calculated attribute weights. For example, visual function ranked first in the AHP and last on the basis of level ranges. The results across the methods were similar, with one exception: the directly measured AHP attribute weights were different from the level-based interpretation of attribute importance in both DCE and AHP. The dependence/independence of attribute importance on level ranges in DCE and AHP, respectively, should be taken into account when choosing a method to support decision making. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Multiattribute evaluation in formulary decision making as applied to calcium-channel blockers.

PubMed

Schumacher, G E

1991-02-01

The use of multiattribute utility theory (MAUT) to make a formulary decision involving calcium-channel blockers (CCBs) is described. The MAUT method is a procedure for identifying, characterizing, and comparing the many variables that may affect a decision. Although applications in pharmacy have been infrequent, MAUT should be particularly appealing to formulary committees. The steps of the MAUT method are (1) determine the viewpoint of the decision makers, (2) identify the decision alternatives, (3) identify the attributes to be evaluated, (4) identify the factors to be used in evaluating the attributes, (5) establish a utility scale for scoring each factor, (6) transform the values for each factor to its utility scale, (7) determine weights for each attribute and factor, (8) calculate the total utility score for each decision alternative, (9) determine which decision alternative has the greatest total score, and (10) perform a sensitivity analysis. The viewpoint of a formulary committee in a health maintenance organization was simulated to develop a model for using the MAUT method to compare CCBs for single-agent therapy of chronic stable angina in ambulatory patients for one year. The attributes chosen were effectiveness, safety, patient acceptance, and cost and weighted 36%, 29%, 21%, and 14%, respectively, as contributions to the evaluation. The rank order of the decision alternatives was (1) generic verapamil, (2) brand-name verapamil, (3) diltiazem, (4) nicardipine, and (5) nifedipine. The MAUT method provides a standardized yet flexible format for comparing and selecting among formulary alternatives.

Multiple-hypothesis multiple-model line tracking

NASA Astrophysics Data System (ADS)

Pace, Donald W.; Owen, Mark W.; Cox, Henry

2000-07-01

Passive sonar signal processing generally includes tracking of narrowband and/or broadband signature components observed on a Lofargram or on a Bearing-Time-Record (BTR) display. Fielded line tracking approaches to date have been recursive and single-hypthesis-oriented Kalman- or alpha-beta filters, with no mechanism for considering tracking alternatives beyond the most recent scan of measurements. While adaptivity is often built into the filter to handle changing track dynamics, these approaches are still extensions of single target tracking solutions to multiple target tracking environment. This paper describes an application of multiple-hypothesis, multiple target tracking technology to the sonar line tracking problem. A Multiple Hypothesis Line Tracker (MHLT) is developed which retains the recursive minimum-mean-square-error tracking behavior of a Kalman Filter in a maximum-a-posteriori delayed-decision multiple hypothesis context. Multiple line track filter states are developed and maintained using the interacting multiple model (IMM) state representation. Further, the data association and assignment problem is enhanced by considering line attribute information (line bandwidth and SNR) in addition to beam/bearing and frequency fit. MHLT results on real sonar data are presented to demonstrate the benefits of the multiple hypothesis approach. The utility of the system in cluttered environments and particularly in crossing line situations is shown.

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

PubMed

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

Marketing the University to Student-Athletes: Understanding University Selection Criteria

ERIC Educational Resources Information Center

Judson, Kimberly M.; James, Jeffrey D.; Aurand, Timothy W.

2004-01-01

As competition for top athletes intensifies, and as challenges associated with recruitment increase, universities must develop and employ recruiting strategies based upon attributes that student-athletes identify as important to their decision-making process. The study investigates college choice decision attributes of student-athletes, identifies…

Study on the Application of TOPSIS Method to the Introduction of Foreign Players in CBA Games

NASA Astrophysics Data System (ADS)

Zhongyou, Xing

The TOPSIS method is a multiple attribute decision-making method. This paper introduces the current situation of the introduction of foreign players in CBA games, presents the principles and calculation steps of TOPSIS method in detail, and applies it to the quantitative evaluation of the comprehensively competitive ability during the introduction of foreign players. Through the analysis of practical application, we found that the TOPSIS method has relatively high rationality and applicability when it is used to evaluate the comprehensively competitive ability during the introduction of foreign players.

Visual analytics techniques for large multi-attribute time series data

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.

2008-01-01

Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year's monthly sales with last year's sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need to detect the outliers early enough to act upon them. In this paper, two new visual analytic techniques are introduced: The color cell-based Visual Time Series Line Charts and Maps highlight significant changes over time in a long time series data and the new Visual Content Query facilitates finding the contents and histories of interesting patterns and anomalies, which leads to root cause identification. We have applied both methods to two real-world applications to mine enterprise data warehouse and customer credit card fraud data to illustrate the wide applicability and usefulness of these techniques.

A decision aid for men with early stage prostate cancer: theoretical basis and a test by surrogate patients

PubMed Central

Feldman‐Stewart, Deb; Brundage, Michael D.; Van Manen, Lori

2008-01-01

Background We developed a decision aid for patients with curable prostate cancer based on Svenson’s DiffCon Theory of Decision Making. This study was designed to determine if surrogate patients using the aid could understand the information presented, complete all tasks, show evidence of differentiation, and arrive at a preferred treatment choice. Methods Men, at least 50 years old and never diagnosed with prostate cancer, were recruited through local advertisements. Participants were asked to imagine that they were a case‐scenario patient. Then they completed the decision aid interview, which included three components: (i) information presentation, with comprehension questions, (ii) exercises to help identify attributes important to the decision, and (iii) value‐clarification exercises. Results Sixty‐nine men volunteered. They had a mean age of 61.2 (range 50–83) years, 37% had no formal education beyond high school, and 87% were living with a partner. All participants completed all aspects of the interview. They answered an average of 10 comprehension questions each, with a mean of 94.7% correct without a prompt. Each attribute in the information presented was identified by at least one participant as important to his decision. Participants identified a median of five attributes as important (ranges 1–14) at each of three points during the interview; 75% changed at least one important attribute during the interview. Forty‐nine per cent of participants also identified attributes as important that were not included in the presented information. Participants showed a wide range of values in each of seven trade‐off exercises. Eighty‐eight per cent of participants showed evidence of differentiation; 75% had a clear treatment preference by the end of the interview. Conclusions Our decision aid appears to meet its goals for surrogate patients and illustrates the strengths of the DiffCon theory. The ability of the aid to accommodate wide variability, both in information needs and in important attributes, is a particular strength of the decision aid. It now requires testing in patients with prostate cancer. PMID:11703496

Contextual Attributes of Indirect Bullying Situations that Influence Teachers' Decisions to Intervene

ERIC Educational Resources Information Center

Blain-Arcaro, Christine; Smith, J. David; Cunningham, Charles E.; Vaillancourt, Tracy; Rimas, Heather

2012-01-01

Indirect bullying occurs frequently yet receives little attention by teachers. Using conjoint analysis, we examined the influence of situational attributes on teachers' decisions to intervene in indirect bullying. Results revealed that teachers (N = 235) were most influenced by victimized children's distress. Additional analyses identified two…

Critical Thinking as a Leadership Attribute.

PubMed

Werner, Stacy H; Bleich, Michael R

2017-01-01

Leaders are tasked with making decisions that have substantial impact on an organization's well-being. Decision making requires critical thinking and requisite action taking. The nature of critical thinking and how professional development educators can strengthen this attribute are presented. J Contin Educ Nurs. 2017;48(1):9-11. Copyright 2017, SLACK Incorporated.

Predicting social and communicative ability in school-age children with autism spectrum disorder: A pilot study of the Social Attribution Task, Multiple Choice.

PubMed

Burger-Caplan, Rebecca; Saulnier, Celine; Jones, Warren; Klin, Ami

2016-11-01

The Social Attribution Task, Multiple Choice is introduced as a measure of implicit social cognitive ability in children, addressing a key challenge in quantification of social cognitive function in autism spectrum disorder, whereby individuals can often be successful in explicit social scenarios, despite marked social adaptive deficits. The 19-question Social Attribution Task, Multiple Choice, which presents ambiguous stimuli meant to elicit social attribution, was administered to children with autism spectrum disorder (N = 23) and to age-matched and verbal IQ-matched typically developing children (N = 57). The Social Attribution Task, Multiple Choice performance differed between autism spectrum disorder and typically developing groups, with typically developing children performing significantly better than children with autism spectrum disorder. The Social Attribution Task, Multiple Choice scores were positively correlated with age (r = 0.474) while being independent from verbal IQ (r = 0.236). The Social Attribution Task, Multiple Choice was strongly correlated with Vineland Adaptive Behavior Scales Communication (r = 0.464) and Socialization (r = 0.482) scores, but not with Daily Living Skills scores (r = 0.116), suggesting that the implicit social cognitive ability underlying performance on the Social Attribution Task, Multiple Choice is associated with real-life social adaptive function. © The Author(s) 2016.

Some induced intuitionistic fuzzy aggregation operators applied to multi-attribute group decision making

NASA Astrophysics Data System (ADS)

Su, Zhi-xin; Xia, Guo-ping; Chen, Ming-yuan

2011-11-01

In this paper, we define various induced intuitionistic fuzzy aggregation operators, including induced intuitionistic fuzzy ordered weighted averaging (OWA) operator, induced intuitionistic fuzzy hybrid averaging (I-IFHA) operator, induced interval-valued intuitionistic fuzzy OWA operator, and induced interval-valued intuitionistic fuzzy hybrid averaging (I-IIFHA) operator. We also establish various properties of these operators. And then, an approach based on I-IFHA operator and intuitionistic fuzzy weighted averaging (WA) operator is developed to solve multi-attribute group decision-making (MAGDM) problems. In such problems, attribute weights and the decision makers' (DMs') weights are real numbers and attribute values provided by the DMs are intuitionistic fuzzy numbers (IFNs), and an approach based on I-IIFHA operator and interval-valued intuitionistic fuzzy WA operator is developed to solve MAGDM problems where the attribute values provided by the DMs are interval-valued IFNs. Furthermore, induced intuitionistic fuzzy hybrid geometric operator and induced interval-valued intuitionistic fuzzy hybrid geometric operator are proposed. Finally, a numerical example is presented to illustrate the developed approaches.

Decision Making and Binge Drinking: A Longitudinal Study

PubMed Central

Goudriaan, Anna E.; Grekin, Emily R.; Sher, Kenneth J.

2009-01-01

Background: Behavioral decision making, as measured by the Iowa Gambling Task (IGT) is found to be diminished in individuals with substance dependence and other types of disinhibitory psychopathology. However, little is known regarding the relation between heavy alcohol use and decision-making skills in young adults. This study therefore investigated whether binge drinking is related to disadvantageous decision making, as measured by the IGT. We also examined the relation between decision making and impulsivity. Methods: Latent class growth analysis was used to classify college students into 4 groups (each group n = 50, 50% male), based on their binge drinking trajectories over a 2-year time period (precollege through second year of college). Participants were 200 college students, divided in 4 subgroups: (1) low binge drinkers, (2) stable moderate binge drinkers, (3) increasing binge drinkers, and (4) stable high binge drinkers. A measure of decision making, the IGT, impulsivity questionnaires, and multiple indicators of heavy alcohol use were included. Results: The stable high binge-drinking group made less advantageous choices on the IGT than the low binge-drinking group. Impulsivity was not related to decision-making performance. Decision-making performance did not differ by gender, but deck preferences and decision time patterns did differ; women preferred low frequency, high amount punishments to a greater extent than men. Conclusions: Although disadvantageous decision making is related to binge-drinking patterns in emerging adulthood, this relation is independent of impulsivity. Additionally, the association appears attributable to those who engage in heavy (binge) drinking at an early age, but not to age of onset of drinking in general. PMID:17403069

Improving the food waste composting facilities site selection for sustainable development using a hybrid modified MADM model.

PubMed

Liu, Kung-Ming; Lin, Sheng-Hau; Hsieh, Jing-Chzi; Tzeng, Gwo-Hshiung

2018-05-01

With the growth of population and the development of urbanization, waste management has always been a critical global issue. Recently, more and more countries have found that food waste constitutes the majority of municipal waste, if they are disposed of properly, will bring more benefits in sustainable development. Regarding the issue of selecting and improving the location to make the disposal facility towards achieving the aspiration level for sustainable development, since it involves multiple and complicated interaction factors about environment, society, and economy which have to be considered properly in the decision-making process of mutual influence relationship. It is basically a multiple attribute decision making (MADM) issue, a difficult problem which has been obsessing the governments of many countries is widely studied and discussed. This study uses the new hybrid modified MADM model, as follows, first to build an influential network relation map (INRM) via DEMATEL technique, next to confirm the influential weightings via DANP (DEMATEL-based ANP), and then to construct a decision-making model via a hybrid modified VIKOR method to improve and select the location for remaining the best disposal facilities. Finally, an empirical case study is illustrated to demonstrate that the proposed model can be effective and useful. In finding the process of decision making, environmental pollution is the main concern of many people in the area, but actually it is the resistance by the general public that has to be considered with first priority. Copyright © 2018. Published by Elsevier Ltd.

An attentional drift diffusion model over binary-attribute choice.

PubMed

Fisher, Geoffrey

2017-11-01

In order to make good decisions, individuals need to identify and properly integrate information about various attributes associated with a choice. Since choices are often complex and made rapidly, they are typically affected by contextual variables that are thought to influence how much attention is paid to different attributes. I propose a modification of the attentional drift-diffusion model, the binary-attribute attentional drift diffusion model (baDDM), which describes the choice process over simple binary-attribute choices and how it is affected by fluctuations in visual attention. Using an eye-tracking experiment, I find the baDDM makes accurate quantitative predictions about several key variables including choices, reaction times, and how these variables are correlated with attention to two attributes in an accept-reject decision. Furthermore, I estimate an attribute-based fixation bias that suggests attention to an attribute increases its subjective weight by 5%, while the unattended attribute's weight is decreased by 10%. Copyright © 2017 Elsevier B.V. All rights reserved.

Developing Decision-Making Skills for Socio-Scientific Issues

ERIC Educational Resources Information Center

Lee, Yeung Chung

2007-01-01

The ability to make informed decisions on science-related social issues is considered an important attribute of scientific literacy. Literature to inform science educators how to bridge the gap between rhetoric and practice--and to assist them in developing this attribute in their students--burgeons. In view of the great diversity of…

Women's and Men's Marriages: Marital Satisfaction, Perceived Control, and Attitudes toward Women.

ERIC Educational Resources Information Center

Madden, Margaret E.

Previous research on marriage indicates that perceptions of control are important to marital satisfaction. To investigate the relationship between attributions of personal control and other variables in marriage, e.g., measures of satisfaction, decision making, and task performance, and attributions of control over decisions and tasks, and to…

Decision by Sampling

ERIC Educational Resources Information Center

Stewart, Neil; Chater, Nick; Brown, Gordon D. A.

2006-01-01

We present a theory of decision by sampling (DbS) in which, in contrast with traditional models, there are no underlying psychoeconomic scales. Instead, we assume that an attribute's subjective value is constructed from a series of binary, ordinal comparisons to a sample of attribute values drawn from memory and is its rank within the sample. We…

Sex, Attribution, and Severity Influence Intervention Decisions of Informal Helpers in Domestic Violence

ERIC Educational Resources Information Center

Chabot, Heather Frasier; Tracy, Tracy L.; Manning, Christine A.; Poisson, Chelsea A.

2009-01-01

Most domestic violence (DV) researchers examine professional intervention (e.g., police and nurses), but informal helpers (e.g., friends and bystanders) are critical. The authors measure undergraduates' intervention likelihood, type of involvement (i.e., contact with abuser), and the influence of attribution decisions in DV situations where the…

Evaluation of Communication about Groups: The Hydra Phenomenon.

ERIC Educational Resources Information Center

Desmond, Roger Jon; Bezzini, John

A study investigated how the attribution of a problem solution to an individual or group affects the consumer's perception of the solution's quality. Based on the tendency to support group decision-making (Hydra phenomenon) it was predicted that decisions attributed to groups would be perceived as higher in quality than those made by individuals,…

Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach

PubMed Central

Singh, Kh. Manglem; Khelchandra, Thongam; Mehta, R. K.

2017-01-01

Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant installation site is an issue of relevance. Environmental impact assessment is often used as a legislative requirement in site selection for decades. The purpose of this current work is to develop a model for decision makers to rank or classify various power plant projects according to multiple criteria attributes such as air quality, water quality, cost of energy delivery, ecological impact, natural hazard, and project duration. The case study in the paper relates to the application of multilayer perceptron trained by genetic algorithm for ranking various power plant locations in India. PMID:28331490

Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach.

PubMed

Shimray, Benjamin A; Singh, Kh Manglem; Khelchandra, Thongam; Mehta, R K

2017-01-01

Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant installation site is an issue of relevance. Environmental impact assessment is often used as a legislative requirement in site selection for decades. The purpose of this current work is to develop a model for decision makers to rank or classify various power plant projects according to multiple criteria attributes such as air quality, water quality, cost of energy delivery, ecological impact, natural hazard, and project duration. The case study in the paper relates to the application of multilayer perceptron trained by genetic algorithm for ranking various power plant locations in India.

Perceived Mortality and Perceived Morality: Perceptions of Value-Orientation Are More Likely When a Decision Is Preceded by a Mortality Reminder

PubMed Central

Nordmo, Mads; Norman, Elisabeth

2016-01-01

The questions addressed in this paper are whether and how reported mortality reminders can function as an indication of sincerity when communicating ambiguously motivated decisions. In two experiments, participants were exposed to a fictitious CEO who announced a decision to implement new organizational measures that were both environmentally and financially beneficial. In the experimental condition, the CEO attributed her new ideas to a recent mortality reminder. In the active control condition, the CEO attributed her decision to a non-lethal dentistry health scare, and in the passive control condition the CEO did not give any account of events preceding her decision. When a CEO implemented new corporate initiatives after a mortality reminder, her motivation for doing so was perceived as somewhat more motivated by intrinsic values, and significantly less motivated by financial gains. This change in attribution patterns was demonstrated to be indirectly related to a positive evaluation of the CEO, as well as an increased willingness to pay for the organization’s services. The second experiment further demonstrated that the reduced attribution to financial motivation associated with mortality awareness persisted even when the CEO in question was known for placing a high personal priority on financial goal attainment. The findings underscore the importance of perceived value-oriented motivation when communicating climate change mitigating policies, and the role of mortality awareness as one of many ways to induce such attributions. PMID:26973555

Perceived Mortality and Perceived Morality: Perceptions of Value-Orientation Are More Likely When a Decision Is Preceded by a Mortality Reminder.

PubMed

Nordmo, Mads; Norman, Elisabeth

2016-01-01

The questions addressed in this paper are whether and how reported mortality reminders can function as an indication of sincerity when communicating ambiguously motivated decisions. In two experiments, participants were exposed to a fictitious CEO who announced a decision to implement new organizational measures that were both environmentally and financially beneficial. In the experimental condition, the CEO attributed her new ideas to a recent mortality reminder. In the active control condition, the CEO attributed her decision to a non-lethal dentistry health scare, and in the passive control condition the CEO did not give any account of events preceding her decision. When a CEO implemented new corporate initiatives after a mortality reminder, her motivation for doing so was perceived as somewhat more motivated by intrinsic values, and significantly less motivated by financial gains. This change in attribution patterns was demonstrated to be indirectly related to a positive evaluation of the CEO, as well as an increased willingness to pay for the organization's services. The second experiment further demonstrated that the reduced attribution to financial motivation associated with mortality awareness persisted even when the CEO in question was known for placing a high personal priority on financial goal attainment. The findings underscore the importance of perceived value-oriented motivation when communicating climate change mitigating policies, and the role of mortality awareness as one of many ways to induce such attributions.

Interval MULTIMOORA method with target values of attributes based on interval distance and preference degree: biomaterials selection

NASA Astrophysics Data System (ADS)

Hafezalkotob, Arian; Hafezalkotob, Ashkan

2017-06-01

A target-based MADM method covers beneficial and non-beneficial attributes besides target values for some attributes. Such techniques are considered as the comprehensive forms of MADM approaches. Target-based MADM methods can also be used in traditional decision-making problems in which beneficial and non-beneficial attributes only exist. In many practical selection problems, some attributes have given target values. The values of decision matrix and target-based attributes can be provided as intervals in some of such problems. Some target-based decision-making methods have recently been developed; however, a research gap exists in the area of MADM techniques with target-based attributes under uncertainty of information. We extend the MULTIMOORA method for solving practical material selection problems in which material properties and their target values are given as interval numbers. We employ various concepts of interval computations to reduce degeneration of uncertain data. In this regard, we use interval arithmetic and introduce innovative formula for interval distance of interval numbers to create interval target-based normalization technique. Furthermore, we use a pairwise preference matrix based on the concept of degree of preference of interval numbers to calculate the maximum, minimum, and ranking of these numbers. Two decision-making problems regarding biomaterials selection of hip and knee prostheses are discussed. Preference degree-based ranking lists for subordinate parts of the extended MULTIMOORA method are generated by calculating the relative degrees of preference for the arranged assessment values of the biomaterials. The resultant rankings for the problem are compared with the outcomes of other target-based models in the literature.

How decisions emerge: action dynamics in intertemporal decision making.

PubMed

Dshemuchadse, Maja; Scherbaum, Stefan; Goschke, Thomas

2013-02-01

In intertemporal decision making, individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to an extent that seems irrational from an economical perspective. This behavior has been attributed to a lack of self-control and reflection, the nonlinearity of human time perception, and several other sources. Although an increasing number of models propose different mathematical descriptions of temporal discounting, the dynamics of the decision process behind temporal discounting are much less clear. In this study, we obtained further insights into the mechanisms of intertemporal decisions by observing choice action dynamics via a novel combination of continuously recorded mouse movements and a multiple regression approach. Participants had to choose between two hypothetical options (sooner/smaller vs. later/larger) by moving the mouse cursor from the bottom of the screen either to the top left or to the top right. We observed less direct mouse movements when participants chose later/larger rewards, indicating that participants had to overcome the attraction of the sooner/smaller reward first. Additionally, our results suggest that framing time information differently changes the weighting of value. We conclude that using a continuous process-oriented approach could further advance the understanding of intertemporal choice beyond the identification of the best fitted mathematical description of the discounting function by uncovering the way intertemporal decisions are performed. 2013 APA, all rights reserved

Following your heart or your head: focusing on emotions versus information differentially influences the decisions of younger and older adults.

PubMed

Mikels, Joseph A; Löckenhoff, Corinna E; Maglio, Sam J; Goldstein, Mary K; Garber, Alan; Carstensen, Laura L

2010-03-01

Research on aging has indicated that whereas deliberative cognitive processes decline with age, emotional processes are relatively spared. To examine the implications of these divergent trajectories in the context of health care choices, we investigated whether instructional manipulations emphasizing a focus on feelings or details would have differential effects on decision quality among younger and older adults. We presented 60 younger and 60 older adults with health care choices that required them to hold in mind and consider multiple pieces of information. Instructional manipulations in the emotion-focus condition asked participants to focus on their emotional reactions to the options, report their feelings about the options, and then make a choice. In the information-focus condition, participants were instructed to focus on the specific attributes, report the details about the options, and then make a choice. In a control condition, no directives were given. Manipulation checks indicated that the instructions were successful in eliciting different modes of processing. Decision quality data indicate that younger adults performed better in the information-focus than in the control condition whereas older adults performed better in the emotion-focus and control conditions than in the information-focus condition. Findings support and extend extant theorizing on aging and decision making as well as suggest that interventions to improve decision-making quality should take the age of the decision maker into account.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media

PubMed Central

Watson, Keri B.; Wood, Spencer A.; Ricketts, Taylor H.

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18–20.2 at 95% confidence) to Vermont’s tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making. PMID:27611325

A Response-Time Approach to Comparing Generalized Rational and Take-the-Best Models of Decision Making

ERIC Educational Resources Information Center

Bergert, F. Bryan; Nosofsky, Robert M.

2007-01-01

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT)…

The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games

NASA Astrophysics Data System (ADS)

Lamb, Richard L.

Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity (for SEGs) has occurred at a time when school systems have increased the type, number, and presentations of student achievement tests for decision-making purposes. These tests often task the form of end of course (year) tests and periodic benchmark testing. As the use of these tests, has increased policymakers have suggested their use as a measure for teacher accountability. The change in testing resulted from a push by school districts and policy makers at various component levels for a data-driven decision-making (D3M) approach. With the data-driven decision making approaches by school districts, there has been an increased focus on the measurement and assessment of student content knowledge with little focus on the contributing factors and cognitive attributes within learning that cross multiple-content areas. One-way to increase the focus on these aspects of learning (factors and attributes) that are additional to content learning is through assessments based in cognitive diagnostics. Cognitive diagnostics are a family of methodological approaches in which tasks tie to specific cognitive attributes for analytical purposes. This study explores data derived from computer data logging (n=158,000) in an observational design, using traditional statistical techniques such as clustering (exploratory and confirmatory), item response theory and through data mining techniques such as artificial neural network analysis. From these analyses, a model of student learning emerges illustrating student thinking and learning while engaged in SEG Design. This study seeks to use cognitive diagnostic type approaches to measure student learning while designing science task based SEGs. In addition, the study suggests that it may be possible to use SEGs to provide a means to administer cognitive diagnostic based assessments in real time. Results of this study suggest the confirmation of four families (factors) of traits illustrating a simple factor loading structure. Item response theory (IRT) results illustrate a 2-parameter logistic model (2PLM) fit allowing for parameterization using the IRT-True Score Method (chi2=1.70, df=1, p=0.19). Finally, fit statistics for the artificial neural network suggest the developed model adequately fits the current data set and provides a means to explore cognitive attributes and their effect on task outcomes. This study has developed a justification for combining and developing two distinct areas of research related to student learning. The first is the use of cognitive diagnostic approaches to assess student learning as it relates to the cognitive attributes used during science processing. The second area is an examination and modeling of the relationship between attributes as propagated in an artificial neural network. Results of the study provide for an ANN model of student cognition while designing science based SEGs (r 2=0.73, RMSE= 0.21) at a convergence of 1000 training iterations. The literature presented in this dissertation work integrates work from multiple field areas. Fields represented in this work range from science education, educational psychology, measurement, and computational psychology.

Is it the time to rethink clinical decision-making strategies? From a single clinical outcome evaluation to a Clinical Multi-criteria Decision Assessment (CMDA).

PubMed

Migliore, Alberto; Integlia, Davide; Bizzi, Emanuele; Piaggio, Tomaso

2015-10-01

There are plenty of different clinical, organizational and economic parameters to consider in order having a complete assessment of the total impact of a pharmaceutical treatment. In the attempt to follow, a holistic approach aimed to provide an evaluation embracing all clinical parameters in order to choose the best treatments, it is necessary to compare and weight multiple criteria. Therefore, a change is required: we need to move from a decision-making context based on the assessment of one single criteria towards a transparent and systematic framework enabling decision makers to assess all relevant parameters simultaneously in order to choose the best treatment to use. In order to apply the MCDA methodology to clinical decision making the best pharmaceutical treatment (or medical devices) to use to treat a specific pathology, we suggest a specific application of the Multiple Criteria Decision Analysis for the purpose, like a Clinical Multi-criteria Decision Assessment CMDA. In CMDA, results from both meta-analysis and observational studies are used by a clinical consensus after attributing weights to specific domains and related parameters. The decision will result from a related comparison of all consequences (i.e., efficacy, safety, adherence, administration route) existing behind the choice to use a specific pharmacological treatment. The match will yield a score (in absolute value) that link each parameter with a specific intervention, and then a final score for each treatment. The higher is the final score; the most appropriate is the intervention to treat disease considering all criteria (domain an parameters). The results will allow the physician to evaluate the best clinical treatment for his patients considering at the same time all relevant criteria such as clinical effectiveness for all parameters and administration route. The use of CMDA model will yield a clear and complete indication of the best pharmaceutical treatment to use for patients, helping physicians to choose drugs with a complete set of information, imputed in the model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multicriteria decision analysis: Overview and implications for environmental decision making

USGS Publications Warehouse

Hermans, Caroline M.; Erickson, Jon D.; Erickson, Jon D.; Messner, Frank; Ring, Irene

2007-01-01

Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

Political ideology and labor arbitrators' decision making in work-family conflict cases.

PubMed

Biernat, Monica; Malin, Martin H

2008-07-01

Labor arbitrators were asked to render decisions about grievances brought by employees who had been fired because of problems created by work conflicts with family responsibilities. The study examined the effects of experimentally manipulated grievant attributes (gender, type of work-family conflict) as well as arbitrator attributes (gender, political ideology) on decision making. When employees were depicted as having had child care problems, liberal arbitrators tended to favor female over male grievants, and political conservatism predicted more favorable judgments rendered toward male grievants. Overall, the data suggest that child care responsibilities cue different patterns of gender bias among liberal and conservative decision makers.

The Multi-Attribute Group Decision-Making Method Based on Interval Grey Trapezoid Fuzzy Linguistic Variables.

PubMed

Yin, Kedong; Wang, Pengyu; Li, Xuemei

2017-12-13

With respect to multi-attribute group decision-making (MAGDM) problems, where attribute values take the form of interval grey trapezoid fuzzy linguistic variables (IGTFLVs) and the weights (including expert and attribute weight) are unknown, improved grey relational MAGDM methods are proposed. First, the concept of IGTFLV, the operational rules, the distance between IGTFLVs, and the projection formula between the two IGTFLV vectors are defined. Second, the expert weights are determined by using the maximum proximity method based on the projection values between the IGTFLV vectors. The attribute weights are determined by the maximum deviation method and the priorities of alternatives are determined by improved grey relational analysis. Finally, an example is given to prove the effectiveness of the proposed method and the flexibility of IGTFLV.

Protein attributes contribute to halo-stability, bioinformatics approach

PubMed Central

2011-01-01

Halophile proteins can tolerate high salt concentrations. Understanding halophilicity features is the first step toward engineering halostable crops. To this end, we examined protein features contributing to the halo-toleration of halophilic organisms. We compared more than 850 features for halophilic and non-halophilic proteins with various screening, clustering, decision tree, and generalized rule induction models to search for patterns that code for halo-toleration. Up to 251 protein attributes selected by various attribute weighting algorithms as important features contribute to halo-stability; from them 14 attributes selected by 90% of models and the count of hydrogen gained the highest value (1.0) in 70% of attribute weighting models, showing the importance of this attribute in feature selection modeling. The other attributes mostly were the frequencies of di-peptides. No changes were found in the numbers of groups when K-Means and TwoStep clustering modeling were performed on datasets with or without feature selection filtering. Although the depths of induced trees were not high, the accuracies of trees were higher than 94% and the frequency of hydrophobic residues pointed as the most important feature to build trees. The performance evaluation of decision tree models had the same values and the best correctness percentage recorded with the Exhaustive CHAID and CHAID models. We did not find any significant difference in the percent of correctness, performance evaluation, and mean correctness of various decision tree models with or without feature selection. For the first time, we analyzed the performance of different screening, clustering, and decision tree algorithms for discriminating halophilic and non-halophilic proteins and the results showed that amino acid composition can be used to discriminate between halo-tolerant and halo-sensitive proteins. PMID:21592393

Operation Exodus: The Massacre of 44 Philippine Police Commandos In Mamasapano Clash

DTIC Science & Technology

2016-09-01

strategic thinking, utilizing Game Theory and Multi-Attribute Decision Making; the combination of these two dynamic tools is used to evaluate their...thinking, utilizing Game Theory and Multi-Attribute Decision Making; the combination of these two dynamic tools is used to evaluate their potential...35 A. GAME THEORETIC APPROACH ......................................................36 B. APPLYING GAME THEORY TO OPLAN: EXODUS

Pharmacists’ Opinions of the Value of CAPE Outcomes in Hiring Decisions

PubMed Central

Marsh, Wallace A.; Castleberry, Ashley N.; Kelley, Katherine A.; Boyce, Eric G.

2017-01-01

Objective. The Hiring Intent Reasoning Examination (HIRE) was designed to explore the utility of the CAPE 2013 outcomes attributes from the perspective of practicing pharmacists, examine how each attribute influences hiring decisions, and identify which of the attributes are perceived as most and least valuable by practicing pharmacists. Methods. An electronic questionnaire was developed and distributed to licensed pharmacists in four states to collect their opinions about 15 CAPE subdomains plus five additional business related attributes. The attributes that respondents identified were: necessary to be a good pharmacist, would impact hiring decisions, most important to them, and in short supply in the applicant pool. Data were analyzed using statistical analysis software to determine the relative importance of each to practicing pharmacists and various subsets of pharmacists. Results. The CAPE subdomains were considered necessary for most jobs by 51% or more of the 3723 respondents (range, 51% to 99%). The necessity for business-related attributes ranged from 21% to 92%. The percentage who would not hire an applicant who did not possess the attribute ranged from 2% to 71.5%; the percentage who considered the attribute most valuable ranged from 0.3% to 35%; and the percentage who felt the attribute was in short supply ranged from 5% to 36%. Opinions varied depending upon gender, practice setting and whether the pharmacist was an employee or employer. Conclusion. The results of this study can be used by faculty and administrators to inform curricular design and emphasis on CAPE domains and business-related education in pharmacy programs. PMID:29367774

A response-time approach to comparing generalized rational and take-the-best models of decision making.

PubMed

Bergert, F Bryan; Nosofsky, Robert M

2007-01-01

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT) approach. TTB predicts that RT is determined solely by the expected time required to locate the 1st discriminating attribute, whereas RAT predicts that RT is determined by the difference in summed evidence between the 2 alternatives. Critical test pairs are used that partially decouple these 2 factors. Under conditions in which ideal observer TTB and RAT strategies yield equivalent decisions, both the RT results and the estimated attribute weights suggest that the vast majority of subjects adopted the generalized TTB strategy. The RT approach is also validated in an experimental condition in which use of a RAT strategy is essentially forced upon subjects. (c) 2007 APA, all rights reserved.

Estimating Classification Accuracy for Complex Decision Rules Based on Multiple Scores

ERIC Educational Resources Information Center

Douglas, Karen M.; Mislevy, Robert J.

2010-01-01

Important decisions about students are made by combining multiple measures using complex decision rules. Although methods for characterizing the accuracy of decisions based on a single measure have been suggested by numerous researchers, such methods are not useful for estimating the accuracy of decisions based on multiple measures. This study…

National Drug Formulary review of statin therapeutic group using the multiattribute scoring tool

PubMed Central

Ramli, Azuana; Aljunid, Syed Mohamed; Sulong, Saperi; Md Yusof, Faridah Aryani

2013-01-01

Purpose HMG-CoA reductase inhibitors (statins) are extensively used in treating hypercholesterolemia. The statins available in Malaysia include atorvastatin, lovastatin, pravastatin, rosuvastatin, simvastatin, and fluvastatin. Over the years, they have accumulated in the National Drug Formulary; hence, the need for review. Effective selection of the best drugs to remain in the formulary can become complex due to the multiple drug attributes involved, and is made worse by the limited time and resources available. The multiattribute scoring tool (MAST) systematizes the evaluation of the drug attributes to facilitate the drug selection process. In this study, a MAST framework was developed to rank the statins based on their utilities or benefits. Methods Published literature on multicriteria decision analysis (MCDA) were studied and five sessions of expert group discussions were conducted to build the MAST framework and to review the evidence. The attributes identified and selected for analysis were efficacy (clinical efficacy, clinical endpoints), safety (drug interactions, serious side effects and documentation), drug applicability (drug strength/formulation, indications, dose frequency, side effects, food–drug interactions, and dose adjustments), and cost. The average weights assigned by the members for efficacy, safety, drug applicability and cost were 32.6%, 26.2%, 24.1%, and 17.1%, respectively. The utility values of the attributes were scored based on the published evidence or/and agreements during the group discussions. The attribute scores were added up to provide the total utility score. Results Using the MAST, the six statins under review were successfully scored and ranked. Atorvastatin scored the highest total utility score (TUS) of 84.48, followed by simvastatin (83.11). Atorvastatin and simvastatin scored consistently high, even before drug costs were included. The low scores on the side effects for atorvastatin were compensated for by the higher scores on the clinical endpoints resulting in a higher TUS for atorvastatin. Fluvastatin recorded the lowest TUS. Conclusion The multiattribute scoring tool was successfully applied to organize decision variables in reviewing statins for the formulary. Based on the TUS, atorvastatin is recommended to remain in the formulary and be considered as first-line in the treatment of hypercholesterolemia. PMID:24353428

Using multi-criteria decision making for selection of the optimal strategy for municipal solid waste management.

PubMed

Jovanovic, Sasa; Savic, Slobodan; Jovicic, Nebojsa; Boskovic, Goran; Djordjevic, Zorica

2016-09-01

Multi-criteria decision making (MCDM) is a relatively new tool for decision makers who deal with numerous and often contradictory factors during their decision making process. This paper presents a procedure to choose the optimal municipal solid waste (MSW) management system for the area of the city of Kragujevac (Republic of Serbia) based on the MCDM method. Two methods of multiple attribute decision making, i.e. SAW (simple additive weighting method) and TOPSIS (technique for order preference by similarity to ideal solution), respectively, were used to compare the proposed waste management strategies (WMS). Each of the created strategies was simulated using the software package IWM2. Total values for eight chosen parameters were calculated for all the strategies. Contribution of each of the six waste treatment options was valorized. The SAW analysis was used to obtain the sum characteristics for all the waste management treatment strategies and they were ranked accordingly. The TOPSIS method was used to calculate the relative closeness factors to the ideal solution for all the alternatives. Then, the proposed strategies were ranked in form of tables and diagrams obtained based on both MCDM methods. As shown in this paper, the results were in good agreement, which additionally confirmed and facilitated the choice of the optimal MSW management strategy. © The Author(s) 2016.

Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods.

PubMed

Hall, Jim W; Lempert, Robert J; Keller, Klaus; Hackbarth, Andrew; Mijere, Christophe; McInerney, David J

2012-10-01

This study compares two widely used approaches for robustness analysis of decision problems: the info-gap method originally developed by Ben-Haim and the robust decision making (RDM) approach originally developed by Lempert, Popper, and Bankes. The study uses each approach to evaluate alternative paths for climate-altering greenhouse gas emissions given the potential for nonlinear threshold responses in the climate system, significant uncertainty about such a threshold response and a variety of other key parameters, as well as the ability to learn about any threshold responses over time. Info-gap and RDM share many similarities. Both represent uncertainty as sets of multiple plausible futures, and both seek to identify robust strategies whose performance is insensitive to uncertainties. Yet they also exhibit important differences, as they arrange their analyses in different orders, treat losses and gains in different ways, and take different approaches to imprecise probabilistic information. The study finds that the two approaches reach similar but not identical policy recommendations and that their differing attributes raise important questions about their appropriate roles in decision support applications. The comparison not only improves understanding of these specific methods, it also suggests some broader insights into robustness approaches and a framework for comparing them. © 2012 RAND Corporation.

New Methods for Crafting Locally Decision-Relevant Scenarios

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2015-12-01

Scenarios can play an important role in helping decision makers to imagine future worlds, both good and bad, different than the one with which we are familiar and to take concrete steps now to address the risks generated by climate change. At their best, scenarios can effectively represent deep uncertainty; integrate over multiple domains; and enable parties with different expectation and values to expand the range of futures they consider, to see the world from different points of view, and to grapple seriously with the potential implications of surprising or inconvenient futures. These attributes of scenario processes can prove crucial in helping craft effective responses to climate change. But traditional scenario methods can also fail to overcome difficulties related to choosing, communicating, and using scenarios to identify, evaluate, and reach consensus on appropriate policies. Such challenges can limit scenario's impact in broad public discourse. This talk will demonstrate how new decision support approaches can employ new quantitative tools that allow scenarios to emerge from a process of deliberation with analysis among stakeholders, rather than serve as inputs to it, thereby increasing the impacts of scenarios on decision making. This talk will demonstrate these methods in the design of a decision support tool to help residents of low lying coastal cities grapple with the long-term risks of sea level rise. In particular, this talk will show how information from the IPCC SSP's can be combined with local information to provide a rich set of locally decision-relevant information.

Visually Exploring Transportation Schedules.

PubMed

Palomo, Cesar; Guo, Zhan; Silva, Cláudio T; Freire, Juliana

2016-01-01

Public transportation schedules are designed by agencies to optimize service quality under multiple constraints. However, real service usually deviates from the plan. Therefore, transportation analysts need to identify, compare and explain both eventual and systemic performance issues that must be addressed so that better timetables can be created. The purely statistical tools commonly used by analysts pose many difficulties due to the large number of attributes at trip- and station-level for planned and real service. Also challenging is the need for models at multiple scales to search for patterns at different times and stations, since analysts do not know exactly where or when relevant patterns might emerge and need to compute statistical summaries for multiple attributes at different granularities. To aid in this analysis, we worked in close collaboration with a transportation expert to design TR-EX, a visual exploration tool developed to identify, inspect and compare spatio-temporal patterns for planned and real transportation service. TR-EX combines two new visual encodings inspired by Marey's Train Schedule: Trips Explorer for trip-level analysis of frequency, deviation and speed; and Stops Explorer for station-level study of delay, wait time, reliability and performance deficiencies such as bunching. To tackle overplotting and to provide a robust representation for a large numbers of trips and stops at multiple scales, the system supports variable kernel bandwidths to achieve the level of detail required by users for different tasks. We justify our design decisions based on specific analysis needs of transportation analysts. We provide anecdotal evidence of the efficacy of TR-EX through a series of case studies that explore NYC subway service, which illustrate how TR-EX can be used to confirm hypotheses and derive new insights through visual exploration.

Decision aids for people facing health treatment or screening decisions.

PubMed

Stacey, Dawn; Légaré, France; Col, Nananda F; Bennett, Carol L; Barry, Michael J; Eden, Karen B; Holmes-Rovner, Margaret; Llewellyn-Thomas, Hilary; Lyddiatt, Anne; Thomson, Richard; Trevena, Lyndal; Wu, Julie H C

2014-01-28

Decision aids are intended to help people participate in decisions that involve weighing the benefits and harms of treatment options often with scientific uncertainty. To assess the effects of decision aids for people facing treatment or screening decisions. For this update, we searched from 2009 to June 2012 in MEDLINE; CENTRAL; EMBASE; PsycINFO; and grey literature. Cumulatively, we have searched each database since its start date including CINAHL (to September 2008). We included published randomized controlled trials of decision aids, which are interventions designed to support patients' decision making by making explicit the decision, providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies of participants making hypothetical decisions. Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were:A) 'choice made' attributes;B) 'decision-making process' attributes.Secondary outcomes were behavioral, health, and health-system effects. We pooled results using mean differences (MD) and relative risks (RR), applying a random-effects model. This update includes 33 new studies for a total of 115 studies involving 34,444 participants. For risk of bias, selective outcome reporting and blinding of participants and personnel were mostly rated as unclear due to inadequate reporting. Based on 7 items, 8 of 115 studies had high risk of bias for 1 or 2 items each.Of 115 included studies, 88 (76.5%) used at least one of the IPDAS effectiveness criteria: A) 'choice made' attributes criteria: knowledge scores (76 studies); accurate risk perceptions (25 studies); and informed value-based choice (20 studies); and B) 'decision-making process' attributes criteria: feeling informed (34 studies) and feeling clear about values (29 studies).A) Criteria involving 'choice made' attributes:Compared to usual care, decision aids increased knowledge (MD 13.34 out of 100; 95% confidence interval (CI) 11.17 to 15.51; n = 42). When more detailed decision aids were compared to simple decision aids, the relative improvement in knowledge was significant (MD 5.52 out of 100; 95% CI 3.90 to 7.15; n = 19). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.82; 95% CI 1.52 to 2.16; n = 19). Exposure to a decision aid with explicit values clarification resulted in a higher proportion of patients choosing an option congruent with their values (RR 1.51; 95% CI 1.17 to 1.96; n = 13).B) Criteria involving 'decision-making process' attributes:Decision aids compared to usual care interventions resulted in:a) lower decisional conflict related to feeling uninformed (MD -7.26 of 100; 95% CI -9.73 to -4.78; n = 22) and feeling unclear about personal values (MD -6.09; 95% CI -8.50 to -3.67; n = 18);b) reduced proportions of people who were passive in decision making (RR 0.66; 95% CI 0.53 to 0.81; n = 14); andc) reduced proportions of people who remained undecided post-intervention (RR 0.59; 95% CI 0.47 to 0.72; n = 18).Decision aids appeared to have a positive effect on patient-practitioner communication in all nine studies that measured this outcome. For satisfaction with the decision (n = 20), decision-making process (n = 17), and/or preparation for decision making (n = 3), those exposed to a decision aid were either more satisfied, or there was no difference between the decision aid versus comparison interventions. No studies evaluated decision-making process attributes for helping patients to recognize that a decision needs to be made, or understanding that values affect the choice.C) Secondary outcomes Exposure to decision aids compared to usual care reduced the number of people of choosing major elective invasive surgery in favour of more conservative options (RR 0.79; 95% CI 0.68 to 0.93; n = 15). Exposure to decision aids compared to usual care reduced the number of people choosing to have prostate-specific antigen screening (RR 0.87; 95% CI 0.77 to 0.98; n = 9). When detailed compared to simple decision aids were used, fewer people chose menopausal hormone therapy (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable.The effect of decision aids on length of consultation varied from 8 minutes shorter to 23 minutes longer (median 2.55 minutes longer) with 2 studies indicating statistically-significantly longer, 1 study shorter, and 6 studies reporting no difference in consultation length. Groups of patients receiving decision aids do not appear to differ from comparison groups in terms of anxiety (n = 30), general health outcomes (n = 11), and condition-specific health outcomes (n = 11). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive. There is high-quality evidence that decision aids compared to usual care improve people's knowledge regarding options, and reduce their decisional conflict related to feeling uninformed and unclear about their personal values. There is moderate-quality evidence that decision aids compared to usual care stimulate people to take a more active role in decision making, and improve accurate risk perceptions when probabilities are included in decision aids, compared to not being included. There is low-quality evidence that decision aids improve congruence between the chosen option and the patient's values.New for this updated review is further evidence indicating more informed, values-based choices, and improved patient-practitioner communication. There is a variable effect of decision aids on length of consultation. Consistent with findings from the previous review, decision aids have a variable effect on choices. They reduce the number of people choosing discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, cost-effectiveness, use with lower literacy populations, and level of detail needed in decision aids need further evaluation. Little is known about the degree of detail that decision aids need in order to have a positive effect on attributes of the choice made, or the decision-making process.

The role of personal values in Chinese consumers' food consumption decisions. A case study of healthy drinks.

PubMed

Lee, Pui Yee; Lusk, Karen; Mirosa, Miranda; Oey, Indrawati

2014-02-01

Differences in culture, language, and behavior between Chinese and Western consumers make entering the Chinese market a challenge. Chinese consumers may desire similar product features (e.g. brand name, quality, and flavor) to Western consumers but the value that consumers attach to the same product may differ cross-nationally. Besides values, an understanding of desired product attributes and the consequences linking to these values is also important. To the authors' knowledge, there is no published scientific research that investigates how personal values influence Chinese consumers' food consumption decisions. The aim of this research was to identify the links among product attributes, consequences of these attributes, and personal values associated with healthy drink consumption decisions within the Chinese market. Specifically, this research employed means-end chain theory and used association pattern technique (APT) as the main data collection technique to identify these links. Focus groups (n=6) were held in Hangzhou, China to identify the important attributes and consequences involved in the consumption decisions of healthy drinks. These attributes and consequences along with Schwartz's 10 basic values were used to construct the matrices included in the APT survey. A total of 600 APT surveys were administered in six different companies in Hangzhou, with 570 returned. Construction of the hierarchical value map (HVM) identified four of Schwartz's personal values influencing Chinese consumers' healthy drink consumption decisions: security, hedonism, benevolence, and self-direction. Food safety was the foremost concern for Chinese consumers when choosing healthy drinks. Chinese consumers also sought a good tasting and nutritious drink that was good value for money. Results from this study provide food marketers with an in-depth understanding of Chinese consumers' healthy drink consumption decisions. Implications and recommendations are provided that will assist food marketers to effectively enact marketing strategies in China. Copyright © 2013 Elsevier Ltd. All rights reserved.

Fuzzy sets, rough sets, and modeling evidence: Theory and Application. A Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection

NASA Technical Reports Server (NTRS)

Dekorvin, Andre

1992-01-01

The Dempster-Shafer theory of evidence is applied to a multiattribute decision making problem whereby the decision maker (DM) must compromise with available alternatives, none of which exactly satisfies his ideal. The decision mechanism is constrained by the uncertainty inherent in the determination of the relative importance of each attribute element and the classification of existing alternatives. The classification of alternatives is addressed through expert evaluation of the degree to which each element is contained in each available alternative. The relative importance of each attribute element is determined through pairwise comparisons of the elements by the decision maker and implementation of a ratio scale quantification method. Then the 'belief' and 'plausibility' that an alternative will satisfy the decision maker's ideal are calculated and combined to rank order the available alternatives. Application to the problem of selecting computer software is given.

PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

NASA Astrophysics Data System (ADS)

Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

2018-03-01

Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

Factors related to the decision of men and women to continue taking science courses in college

NASA Astrophysics Data System (ADS)

Deboer, George E.

The purpose of this study was to determine the importance of the transition between a student's initial collegiate science experience and the decision to continue in science, and whether the reasons students give to explain their success or failure in their first course are related to that decision. Attribution theory provided the framework for investigating these factors. The results showed that for unsuccessful students, the plan to continue in science was unrelated to gender, mathematical aptitude, performance in the first science course, or attributions to luck, effort, ability, or task difficulty. For successful students, the plan to continue in science was directly related to attributions to ability, and inversely related to task difficulty. The results demonstrate the importance of a sense of competence for students who continue in science.

Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory.

PubMed

Korn, Christoph W; Rosenblau, Gabriela; Rodriguez Buritica, Julia M; Heekeren, Hauke R

2016-01-01

A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities) but negative feedback externally (e.g., to environmental factors). However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors' credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did--or did not--receive feedback on their veridical performance. Finally, participants re-rated the actors' credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors' credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or incorrect performance alone could not explain the observed positivity bias. Furthermore, participants' behavior in our task was linked to the most widely used measure of attribution style. In sum, our findings suggest that positive and negative performance feedback influences the evaluation of task-related stimuli, as predicted by attribution theory. Therefore, our study points to the relevance of attribution theory for feedback processing in decision-making and provides a novel outlook for decision-making biases.

Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory

PubMed Central

Rodriguez Buritica, Julia M.; Heekeren, Hauke R.

2016-01-01

A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities) but negative feedback externally (e.g., to environmental factors). However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors’ credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did—or did not—receive feedback on their veridical performance. Finally, participants re-rated the actors’ credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors’ credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or incorrect performance alone could not explain the observed positivity bias. Furthermore, participants’ behavior in our task was linked to the most widely used measure of attribution style. In sum, our findings suggest that positive and negative performance feedback influences the evaluation of task-related stimuli, as predicted by attribution theory. Therefore, our study points to the relevance of attribution theory for feedback processing in decision-making and provides a novel outlook for decision-making biases. PMID:26849646

HIV or HIV-Therapy? Causal attributions of symptoms and their impact on treatment decisions among women and men with HIV

PubMed Central

2009-01-01

Objectives Among people with HIV, we examined symptom attribution to HIV or HIV-therapy, awareness of potential side effects and discontinuation of treatment, as well as sex/gender differences. Methods HIV-patients (N = 168, 46% female) completed a comprehensive symptom checklist (attributing each endorsed symptom to HIV, HIV-therapy, or other causes), reported reasons for treatment discontinuations and potential ART-related laboratory abnormalities. Results Main symptom areas were fatigue/sleep/energy, depression/mood, lipodystrophy, and gastrointestinal, dermatological, and neurological problems. Top HIV-attributed symptoms were lack of stamina/energy in both genders, night sweats, depression, mood swings in women; and fatigue, lethargy, difficulties concentrating in men. Women attributed symptoms less frequently to HIV than men, particularly fa-tigue(p < .01). Top treatment-attributed symptoms were lipodystrophy and gastrointestinal problems in both genders. Symptom attribution to HIV-therapy did not differ between genders. Over the past six months, 22% switched/interrupted ART due to side effects. In women, side effect-related treatment decisions were more complex, involving more side effects and substances. Remarkably, women took predominantly protease inhibitor-sparing regimens (p = .05). Both genders reported only 15% of potential ART-related laboratory abnormalities but more than 50% had laboratory abnormalities. Notably, women had fewer elevated renal parameters (p < .01). Conclusions Men may attribute symptoms more often to HIV and maintain a treatment-regimen despite side effects, whereas women may be more prudent in avoiding treatment side effects. Lacking awareness of laboratory abnormalities in both genders potentially indicates gaps in physician-patient communication. Gender differences in causal attributions of symptoms/side effects may influence treatment decisions. PMID:19380286

Influences of packaging attributes on consumer purchase decisions for fresh produce.

PubMed

Koutsimanis, Georgios; Getter, Kristin; Behe, Bridget; Harte, Janice; Almenar, Eva

2012-10-01

Packaging attributes are considered to have an influence on consumer purchase decisions for food and, as a consequence, also on its consumption. To improve the current minimal understanding of these influences for fresh produce, a survey instrument in the form of an online questionnaire has been developed and launched in the US. The first part of the questionnaire covers consumers' preferences for packaging convenience features, characteristics, materials, disposal method, and others for fresh produces in general, and the second focuses on attributes like price, container size, produce shelf life for a specific fresh produce, sweet cherries, to allow us to supply specific values for these factors to the participants. Cluster and conjoint analyses of responses from 292 participants reveal that specific packaging and produce attributes affect consumer purchase decisions of fresh produce in general and of sweet cherries in particular (P ≤ 0.05) and that some are population segment dependent (P ≤ 0.05). For produce packaging in general, 'extend the "best by" date' was ranked as the top convenience feature, the type of packaging material was considered to affect the food product quality (92.7%) and containers made from bio-based materials were highly appealing (3.52 out of 5.00). The most important attributes that affect the purchasing decisions of consumers regarding a specific fresh produce like sweet cherries are price (25%), shelf life (19%) and container size (17.2%). Copyright © 2012 Elsevier Ltd. All rights reserved.

Efficient group decision making in workshop settings

Treesearch

Daniel L. Schmoldt; David L. Peterson

2001-01-01

Public land managers must treat multiple values coincidentally in time and space, which requires the participation of multiple resource specialists and consideration of diverse clientele interests in the decision process. This implies decision making that includes multiple participants, both internally and externally. Decades of social science research on decision...

Publically accessible decision support system of the spatially referenced regressions on watershed attributes (SPARROW) model and model enhancements in South Carolina

Treesearch

Celeste Journey; Anne B. Hoos; David E. Ladd; John W. brakebill; Richard A. Smith

2016-01-01

The U.S. Geological Survey (USGS) National Water Quality Assessment program has developed a web-based decision support system (DSS) to provide free public access to the steady-stateSPAtially Referenced Regressions On Watershed attributes (SPARROW) model simulation results on nutrient conditions in streams and rivers and to offer scenario testing capabilities for...

Decision-making in irrigation networks: Selecting appropriate canal structures using multi-attribute decision analysis.

PubMed

Hosseinzade, Zeinab; Pagsuyoin, Sheree A; Ponnambalam, Kumaraswamy; Monem, Mohammad J

2017-12-01

The stiff competition for water between agriculture and non-agricultural production sectors makes it necessary to have effective management of irrigation networks in farms. However, the process of selecting flow control structures in irrigation networks is highly complex and involves different levels of decision makers. In this paper, we apply multi-attribute decision making (MADM) methodology to develop a decision analysis (DA) framework for evaluating, ranking and selecting check and intake structures for irrigation canals. The DA framework consists of identifying relevant attributes for canal structures, developing a robust scoring system for alternatives, identifying a procedure for data quality control, and identifying a MADM model for the decision analysis. An application is illustrated through an analysis for automation purposes of the Qazvin irrigation network, one of the oldest and most complex irrigation networks in Iran. A survey questionnaire designed based on the decision framework was distributed to experts, managers, and operators of the Qazvin network and to experts from the Ministry of Power in Iran. Five check structures and four intake structures were evaluated. A decision matrix was generated from the average scores collected from the survey, and was subsequently solved using TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. To identify the most critical structure attributes for the selection process, optimal attribute weights were calculated using Entropy method. For check structures, results show that the duckbill weir is the preferred structure while the pivot weir is the least preferred. Use of the duckbill weir can potentially address the problem with existing Amil gates where manual intervention is required to regulate water levels during periods of flow extremes. For intake structures, the Neyrpic® gate and constant head orifice are the most and least preferred alternatives, respectively. Some advantages of the Neyrpic® gate are ease of operation and capacity to measure discharge flows. Overall, the application to the Qazvin irrigation network demonstrates the utility of the proposed DA framework in selecting appropriate structures for regulating water flows in irrigation canals. This framework systematically aids the decision process by capturing decisions made at various levels (individual farmers to high-level management). It can be applied to other cases where a new irrigation network is being designed, or where changes in irrigation structures need to be identified to improve flow control in existing networks. Copyright © 2017 Elsevier B.V. All rights reserved.

Diffusion theory of decision making in continuous report.

PubMed

Smith, Philip L

2016-07-01

I present a diffusion model for decision making in continuous report tasks, in which a continuous, circularly distributed, stimulus attribute in working memory is matched to a representation of the attribute in the stimulus display. Memory retrieval is modeled as a 2-dimensional diffusion process with vector-valued drift on a disk, whose bounding circle represents the decision criterion. The direction and magnitude of the drift vector describe the identity of the stimulus and the quality of its representation in memory, respectively. The point at which the diffusion exits the disk determines the reported value of the attribute and the time to exit the disk determines the decision time. Expressions for the joint distribution of decision times and report outcomes are obtained by means of the Girsanov change-of-measure theorem, which allows the properties of the nonzero-drift diffusion process to be characterized as a function of a Euclidian-distance Bessel process. Predicted report precision is equal to the product of the decision criterion and the drift magnitude and follows a von Mises distribution, in agreement with the treatment of precision in the working memory literature. Trial-to-trial variability in criterion and drift rate leads, respectively, to direct and inverse relationships between report accuracy and decision times, in agreement with, and generalizing, the standard diffusion model of 2-choice decisions. The 2-dimensional model provides a process account of working memory precision and its relationship with the diffusion model, and a new way to investigate the properties of working memory, via the distributions of decision times. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Using multicriteria decision analysis during drug development to predict reimbursement decisions.

PubMed

Williams, Paul; Mauskopf, Josephine; Lebiecki, Jake; Kilburg, Anne

2014-01-01

Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound. The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes. The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products 'just likely to be reimbursed'; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products. The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA. Prediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway.

Using multicriteria decision analysis during drug development to predict reimbursement decisions

PubMed Central

Williams, Paul; Mauskopf, Josephine; Lebiecki, Jake; Kilburg, Anne

2014-01-01

Background Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound. Objective The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes. Methods The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products ‘just likely to be reimbursed’; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products. Results The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA. Conclusions Prediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway.

Memory-Based Decision-Making with Heuristics: Evidence for a Controlled Activation of Memory Representations

ERIC Educational Resources Information Center

Khader, Patrick H.; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rosler, Frank

2011-01-01

Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by…

[Medical decision making in symptoms of type 2 diabetes mellitus in general practice].

PubMed

de Cruppé, W; von dem Knesebeck, O; Gerstenberger, E; Link, C; Marceau, L; Siegrist, J; Geraedts, M; McKinlay, J

2011-02-01

Patient and physician attributes influence medical decisions as non-medical factors. The current study examines the influence of patient age and gender and physicians' gender and years of clinical experience on medical decision making in patients with undiagnosed diabetes type 2. A factorial experiment was conducted to estimate the influence of patient and physician attributes. An identical physician patient encounter with a patient presenting with diabetes symptoms was videotaped with varying patient attributes. Professional actors played the "patients". A sample of 64 randomly chosen and stratified (gender and years of experience) primary care physicians was interviewed about the presented videos. Results show few significant differences in diagnostic decisions: Younger patients were asked more frequently about psychosocial problems while with older patients a cancer diagnosis was more often taken into consideration. Female physicians made an earlier second appointment date compared to male physicians. Physicians with more years of professional experience considered more often diabetes as the diagnosis than physicians with less experience. Medical decision making in patients with diabetes type 2 is only marginally influenced by patients' and physicians' characteristics under study. © Georg Thieme Verlag KG Stuttgart · New York.

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

Rowe, M.D.; Pierce, B.L.

This report presents results of tests of different final site selection methods used for siting large-scale facilities such as nuclear power plants. Test data are adapted from a nuclear power plant siting study conducted on Long Island, New York. The purpose of the tests is to determine whether or not different final site selection methods produce different results, and to obtain some understanding of the nature of any differences found. Decision rules and weighting methods are included. Decision rules tested are Weighting Summation, Power Law, Decision Analysis, Goal Programming, and Goal Attainment; weighting methods tested are Categorization, Ranking, Rating Ratiomore » Estimation, Metfessel Allocation, Indifferent Tradeoff, Decision Analysis lottery, and Global Evaluation. Results show that different methods can, indeed, produce different results, but that the probability that they will do so is controlled by the structure of differences among the sites being evaluated. Differences in weights and suitability scores attributable to methods have reduced significance if the alternatives include one or two sites that are superior to all others in many attributes. The more tradeoffs there are among good and bad levels of different attributes at different sites, the more important are the specifics of methods to the final decision. 5 refs., 14 figs., 19 tabs.« less

Four Common Simplifications of Multi-Criteria Decision Analysis do not hold for River Rehabilitation

PubMed Central

2016-01-01

River rehabilitation aims at alleviating negative effects of human impacts such as loss of biodiversity and reduction of ecosystem services. Such interventions entail difficult trade-offs between different ecological and often socio-economic objectives. Multi-Criteria Decision Analysis (MCDA) is a very suitable approach that helps assessing the current ecological state and prioritizing river rehabilitation measures in a standardized way, based on stakeholder or expert preferences. Applications of MCDA in river rehabilitation projects are often simplified, i.e. using a limited number of objectives and indicators, assuming linear value functions, aggregating individual indicator assessments additively, and/or assuming risk neutrality of experts. Here, we demonstrate an implementation of MCDA expert preference assessments to river rehabilitation and provide ample material for other applications. To test whether the above simplifications reflect common expert opinion, we carried out very detailed interviews with five river ecologists and a hydraulic engineer. We defined essential objectives and measurable quality indicators (attributes), elicited the experts´ preferences for objectives on a standardized scale (value functions) and their risk attitude, and identified suitable aggregation methods. The experts recommended an extensive objectives hierarchy including between 54 and 93 essential objectives and between 37 to 61 essential attributes. For 81% of these, they defined non-linear value functions and in 76% recommended multiplicative aggregation. The experts were risk averse or risk prone (but never risk neutral), depending on the current ecological state of the river, and the experts´ personal importance of objectives. We conclude that the four commonly applied simplifications clearly do not reflect the opinion of river rehabilitation experts. The optimal level of model complexity, however, remains highly case-study specific depending on data and resource availability, the context, and the complexity of the decision problem. PMID:26954353

Good-parent beliefs of parents of seriously ill children.

PubMed

Feudtner, Chris; Walter, Jennifer K; Faerber, Jennifer A; Hill, Douglas L; Carroll, Karen W; Mollen, Cynthia J; Miller, Victoria A; Morrison, Wynne E; Munson, David; Kang, Tammy I; Hinds, Pamela S

2015-01-01

Parents' beliefs about what they need to do to be a good parent when their children are seriously ill influence their medical decisions, and better understanding of these beliefs may improve decision support. To assess parents' perceptions regarding the relative importance of 12 good-parent attributes. A cross-sectional, discrete-choice experiment was conducted at a children's hospital. Participants included 200 parents of children with serious illness. Ratings of 12 good-parent attributes, with subsequent use of latent class analysis to identify groups of parents with similar ratings of attributes, and ascertainment of whether membership in a particular group was associated with demographic or clinical characteristics. The highest-ranked good-parent attribute was making sure that my child feels loved, followed by focusing on my child's health, making informed medical care decisions, and advocating for my child with medical staff. We identified 4 groups of parents with similar patterns of good-parent-attribute ratings, which we labeled as: child feels loved (n=68), child's health (n=56), advocacy and informed (n=55), and spiritual well-being (n=21). Compared with the other groups, the child's health group reported more financial difficulties, was less educated, and had a higher proportion of children with new complex, chronic conditions. Parents endorse a broad range of beliefs that represent what they perceive they should do to be a good parent for their seriously ill child. Common patterns of how parents prioritize these attributes exist, suggesting future research to better understand the origins and development of good-parent beliefs among these parents. More important, engaging parents individually regarding what they perceive to be the core duties they must fulfill to be a good parent may enable more customized and effective decision support.

The eyes have it: Using eye tracking to inform information processing strategies in multi-attributes choices.

PubMed

Ryan, Mandy; Krucien, Nicolas; Hermens, Frouke

2018-04-01

Although choice experiments (CEs) are widely applied in economics to study choice behaviour, understanding of how individuals process attribute information remains limited. We show how eye-tracking methods can provide insight into how decisions are made. Participants completed a CE, while their eye movements were recorded. Results show that although the information presented guided participants' decisions, there were also several processing biases at work. Evidence was found of (a) top-to-bottom, (b) left-to-right, and (c) first-to-last order biases. Experimental factors-whether attributes are defined as "best" or "worst," choice task complexity, and attribute ordering-also influence information processing. How individuals visually process attribute information was shown to be related to their choices. Implications for the design and analysis of CEs and future research are discussed. Copyright © 2017 John Wiley & Sons, Ltd.

Comparison of potential method in analytic hierarchy process for multi-attribute of catering service companies

NASA Astrophysics Data System (ADS)

Mamat, Siti Salwana; Ahmad, Tahir; Awang, Siti Rahmah

2017-08-01

Analytic Hierarchy Process (AHP) is a method used in structuring, measuring and synthesizing criteria, in particular ranking of multiple criteria in decision making problems. On the other hand, Potential Method is a ranking procedure in which utilizes preference graph ς (V, A). Two nodes are adjacent if they are compared in a pairwise comparison whereby the assigned arc is oriented towards the more preferred node. In this paper Potential Method is used to solve problem on a catering service selection. The comparison of result by using Potential method is made with Extent Analysis. The Potential Method is found to produce the same rank as Extent Analysis in AHP.

Using features of Arden Syntax with object-oriented medical data models for guideline modeling.

PubMed

Peleg, M; Ogunyemi, O; Tu, S; Boxwala, A A; Zeng, Q; Greenes, R A; Shortliffe, E H

2001-01-01

Computer-interpretable guidelines (CIGs) can deliver patient-specific decision support at the point of care. CIGs base their recommendations on eligibility and decision criteria that relate medical concepts to patient data. CIG models use expression languages for specifying these criteria, and define models for medical data to which the expressions can refer. In developing version 3 of the GuideLine Interchange Format (GLIF3), we used existing standards as the medical data model and expression language. We investigated the object-oriented HL7 Reference Information Model (RIM) as a default data model. We developed an expression language, called GEL, based on Arden Syntax's logic grammar. Together with other GLIF constructs, GEL reconciles incompatibilities between the data models of Arden Syntax and the HL7 RIM. These incompatibilities include Arden's lack of support for complex data types and time intervals, and the mismatch between Arden's single primary time and multiple time attributes of the HL7 RIM.

Measuring the influence of professional nursing practice on global hospital performance in an organizational context.

PubMed

Fasoli, Dijon R

2008-01-01

The purpose of this study was to measure the influence of professional nursing practice (PNP) on global hospital performance (GHP). Evidence links PNP and positive outcomes for patients and nurses, however, little is known about PNP influence on GHP measures used for patient decision-making and hospital management resource allocation decisions. A quantitative study using multiple regression analysis to predict a composite measure of GHP was conducted. Two survey instruments measuring perspectives of the PNP environment were completed by 1815 (31.3%) Registered Nurses (RN) and 28 (100%) Senior Nurse Executives (SNE) at 28 northeastern US hospitals. Secondary data provided organizational attributes. The degree of PNP was consistently reported by RNs and SNEs. When regressed with organizational factors, PNP was not a significant predictor of GHP. Better GHP was associated with lower lengths of stay, lower profitability, less admission growth, and non-health system affiliation. Further research is needed to define a nursing-sensitive GHP measure.

Representing causal knowledge in environmental policy interventions: Advantages and opportunities for qualitative influence diagram applications.

PubMed

Carriger, John F; Dyson, Brian E; Benson, William H

2018-01-15

This article develops and explores a methodology for using qualitative influence diagrams in environmental policy and management to support decision making efforts that minimize risk and increase resiliency. Influence diagrams are representations of the conditional aspects of a problem domain. Their graphical properties are useful for structuring causal knowledge relevant to policy interventions and can be used to enhance inference and inclusivity of multiple viewpoints. Qualitative components of influence diagrams are beneficial tools for identifying and examining the interactions among the critical variables in complex policy development and implementation. Policy interventions on social-environmental systems can be intuitively diagrammed for representing knowledge of critical relationships among economic, environmental, and social attributes. Examples relevant to coastal resiliency issues in the U.S. Gulf Coast region are developed to illustrate model structures for developing qualitative influence diagrams useful for clarifying important policy intervention issues and enhancing transparency in decision making. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Analytical group decision making in natural resources: methodology and application

Treesearch

Daniel L. Schmoldt; David L. Peterson

2000-01-01

Group decision making is becoming increasingly important in natural resource management and associated scientific applications, because multiple values are treated coincidentally in time and space, multiple resource specialists are needed, and multiple stakeholders must be included in the decision process. Decades of social science research on decision making in groups...

Integrating Multiple Criteria Evaluation and GIS in Ecotourism: a Review

NASA Astrophysics Data System (ADS)

Mohd, Z. H.; Ujang, U.

2016-09-01

The concept of 'Eco-tourism' is increasingly heard in recent decades. Ecotourism is one adventure that environmentally responsible intended to appreciate the nature experiences and cultures. Ecotourism should have low impact on environment and must contribute to the prosperity of local residents. This article reviews the use of Multiple Criteria Evaluation (MCE) and Geographic Information System (GIS) in ecotourism. Multiple criteria evaluation mostly used to land suitability analysis or fulfill specific objectives based on various attributes that exist in the selected area. To support the process of environmental decision making, the application of GIS is used to display and analysis the data through Analytic Hierarchy Process (AHP). Integration between MCE and GIS tool is important to determine the relative weight for the criteria used objectively. With the MCE method, it can resolve the conflict between recreation and conservation which is to minimize the environmental and human impact. Most studies evidences that the GIS-based AHP as a multi criteria evaluation is a strong and effective in tourism planning which can aid in the development of ecotourism industry effectively.

Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States

PubMed Central

Manson, Steven M.; Evans, Tom

2007-01-01

We combine mixed-methods research with integrated agent-based modeling to understand land change and economic decision making in the United States and Mexico. This work demonstrates how sustainability science benefits from combining integrated agent-based modeling (which blends methods from the social, ecological, and information sciences) and mixed-methods research (which interleaves multiple approaches ranging from qualitative field research to quantitative laboratory experiments and interpretation of remotely sensed imagery). We test assumptions of utility-maximizing behavior in household-level landscape management in south-central Indiana, linking parcel data, land cover derived from aerial photography, and findings from laboratory experiments. We examine the role of uncertainty and limited information, preferences, differential demographic attributes, and past experience and future time horizons. We also use evolutionary programming to represent bounded rationality in agriculturalist households in the southern Yucatán of Mexico. This approach captures realistic rule of thumb strategies while identifying social and environmental factors in a manner similar to econometric models. These case studies highlight the role of computational models of decision making in land-change contexts and advance our understanding of decision making in general. PMID:18093928

Information Foraging for Perceptual Decisions

PubMed Central

2016-01-01

We tested an information foraging framework to characterize the mechanisms that drive active (visual) sampling behavior in decision problems that involve multiple sources of information. Experiments 1 through 3 involved participants making an absolute judgment about the direction of motion of a single random dot motion pattern. In Experiment 4, participants made a relative comparison between 2 motion patterns that could only be sampled sequentially. Our results show that: (a) Information (about noisy motion information) grows to an asymptotic level that depends on the quality of the information source; (b) The limited growth is attributable to unequal weighting of the incoming sensory evidence, with early samples being weighted more heavily; (c) Little information is lost once a new source of information is being sampled; and (d) The point at which the observer switches from 1 source to another is governed by online monitoring of his or her degree of (un)certainty about the sampled source. These findings demonstrate that the sampling strategy in perceptual decision-making is under some direct control by ongoing cognitive processing. More specifically, participants are able to track a measure of (un)certainty and use this information to guide their sampling behavior. PMID:27819455

[A multi-measure analysis of the similarity, attraction, and compromise effects in multi-attribute decision making].

PubMed

Tsuzuki, Takashi; Matsui, Hiroshi; Kikuchi, Manabu

2012-12-01

In multi-attribute decision making, the similarity, attraction, and compromise effects warrant specific investigation as they cause violations of principles in rational choice. In order to investigate these three effects simultaneously, we assigned 145 undergraduates to three context effect conditions. We requested them to solve the same 20 hypothetical purchase problems, each of which had three alternatives described along two attributes. We measured their choices, confidence ratings, and response times. We found that manipulating the third alternative had significant context effects for choice proportions and confidence ratings in all three conditions. Furthermore, the attraction effect was the most prominent with regard to choice proportions. In the compromise effect condition, although the choice proportion of the third alternative was high, the confidence rating was low and the response time was long. These results indicate that the relationship between choice proportions and confidence ratings requires further theoretical investigation. They also suggest that a combination of experimental and modeling studies is imperative to reveal the mechanisms underlying the context effects in multi-attribute, multi-alternative decision making.

Mapping clinical outcomes expectations to treatment decisions: an application to vestibular schwannoma management.

PubMed

Cheung, Steven W; Aranda, Derick; Driscoll, Colin L W; Parsa, Andrew T

2010-02-01

Complex medical decision making obligates tradeoff assessments among treatment outcomes expectations, but an accessible tool to perform the necessary analysis is conspicuously absent. We aimed to demonstrate methodology and feasibility of adapting conjoint analysis for mapping clinical outcomes expectations to treatment decisions in vestibular schwannoma (VS) management. Prospective. Tertiary medical center and US-based otologists/neurotologists. Treatment preference profiles among VS stakeholders-61 younger and 74 older prospective patients, 61 observation patients, and 60 surgeons-were assessed for the synthetic VS case scenario of a 10-mm tumor in association with useful hearing and normal facial function. Treatment attribute utility. Conjoint analysis attribute levels were set in accordance to the results of a meta-analysis. Forty-five case series were disaggregated to formulate microsurgery facial nerve and hearing preservation outcomes expectations models. Attribute utilities were computed and mapped to the realistic treatment choices of translabyrinthine craniotomy, middle fossa craniotomy, and gamma knife radiosurgery. Among the treatment attributes of likelihoods of causing deafness, temporary facial weakness for 2 months, and incurable cancer within 20 years, and recovery time, permanent deafness was less important to tumor surgeons, and temporary facial weakness was more important to tumor surgeons and observation patients (Wilcoxon rank-sum, p < 0.001). Inverse mapping of preference profiles to realistic treatment choices showed all study cohorts were inclined to choose gamma knife radiosurgery. Mapping clinical outcomes expectations to treatment decisions for a synthetic clinical scenario revealed inhomogeneous drivers of choice selection among study cohorts. Medical decision engines that analyze personal preferences of outcomes expectations for VS and many other diseases may be developed to promote shared decision making among health care stakeholders and transparency in the informed consent process.

Misremembrance of options past: source monitoring and choice.

PubMed

Mather, M; Shafir, E; Johnson, M K

2000-03-01

This study reveals that when remembering past decisions, people engage in choice-supportive memory distortion. When asked to make memory attributions of options' features, participants made source-monitoring errors that supported their decisions. They tended to attribute, both correctly and incorrectly, more positive features to the option they had selected than to its competitor. In addition, they sometimes attributed, both correctly and incorrectly, more negative features to the nonselected option. This pattern of distortion may be beneficial to people's general well-being, reducing regret for options not taken. At the same time, it is problematic for memory accuracy, for accountability, and for learning from past experience.

Differential impact of affective and cognitive attributes on preference under deliberation and distraction

PubMed Central

Wang, Zuo-Jun; Chan, Kai-Qin; Chen, Jiao-Jiao; Chen, Ai; Wang, Fei

2015-01-01

Two experiments were designed to test the hypothesis that affective information looms relatively larger than cognitive information when individuals are distracted for a period of time compared to when they engage in deliberative thinking. In two studies, participants were presented with information about 4 decision alternatives: An affective alternative that scored high on affective attributes but low on cognitive attributes, a cognitive alternative with the opposite trade-off, and two fillers. They were then asked to indicate their attitudes toward each of four decision alternatives either immediately, after a period of deliberation, or after a period of distraction. The results of both experiments demonstrated that participants significantly preferred the affective alternative to the cognitive alternative after distraction, but not after deliberation. The implications for understanding when and how unconscious thought may lead to better decisions are being discussed. PMID:25983714

Decisions, Decisions, Decisions: Recreation Site Choice with Expected Congestion and Social Interaction

ERIC Educational Resources Information Center

Snipes, Katherine H.

2009-01-01

A set of computer-based recreation choice experiments were run to examine the effect of expected congestion and social interactions on the decision making process. MouseTrace is a process-tracing program that recorded individual subject's information acquisitions and provided the necessary information to determine if subjects used attribute-based…

Spatial variation in breeding habitat selection by Cerulean Warblers (Setophaga cerulea) throughout the Appalachian Mountains

USGS Publications Warehouse

Boves, Than J.; Buehler, David A.; Sheehan, James; Wood, Petra Bohall; Rodewald, Amanda D.; Larkin, Jeffrey L.; Keyser, Patrick D.; Newell, Felicity L.; Evans, Andrea; George, Gregory A.; Wigley, T.B.

2013-01-01

Studies of habitat selection are often of limited utility because they focus on small geographic areas, fail to examine behavior at multiple scales, or lack an assessment of the fitness consequences of habitat decisions. These limitations can hamper the identification of successful site-specific management strategies, which are urgently needed for severely declining species like Cerulean Warblers (Setophaga cerulea). We assessed how breeding habitat decisions made by Cerulean Warblers at multiple scales, and the subsequent effects of these decisions on nest survival, varied across the Appalachian Mountains. Selection for structural habitat features varied substantially among areas, particularly at the territory scale. Males within the least-forested landscapes selected microhabitat features that reflected more closed-canopy forest conditions, whereas males in highly forested landscapes favored features associated with canopy disturbance. Selection of nest-patch and nest-site attributes by females was more consistent across areas, with females selecting for increased tree size and understory cover and decreased basal area and midstory cover. Floristic preferences were similar across study areas: White Oak (Quercus alba), Cucumber-tree (Magnolia acuminata), and Sugar Maple (Acer saccharum) were preferred as nest trees, whereas red oak species (subgenus Erythrobalanus) and Red Maple (A. rubrum) were avoided. The habitat features that were related to nest survival also varied among study areas, and preferred features were negatively associated with nest survival at one area. Thus, our results indicate that large-scale spatial heterogeneity may influence local habitat-selection behavior and that it may be necessary to articulate site-specific management strategies for Cerulean Warblers.

Influence of Product and Supplier Attributes on Hardwood Lumber Purchase Decisions

Treesearch

Craig L. Forbes; Steven A. Sinclair; Robert J. Bush; Philip A. Araman

1994-01-01

This study determined the influence of product and supplier attributes on hardwood lumber purchases by wood furniture manufacturers and investigated differences across manufacturer type, geographic region, firm size, and kiln ownership. Professional lumber buyers rated the importance and difference across suppliers of various attributes. Purchase influence scores were...

Global Educators' Personal Attribution of a Global Perspective

ERIC Educational Resources Information Center

Carano, Kenneth Thomas

2013-01-01

This case study of self-identifying global educators investigated factors that they attributed to the development of their global perspective and how it influenced curricular decision-making. Analysis resulted in seven themes identified by the participants as having attributed to the development of a global perspective: (a) family, (b) exposure to…

Deciding how to decide: ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making.

PubMed

Fellows, Lesley K

2006-04-01

Ventromedial frontal lobe (VMF) damage is associated with impaired decision making. Recent efforts to understand the functions of this brain region have focused on its role in tracking reward, punishment and risk. However, decision making is complex, and frontal lobe damage might be expected to affect it at other levels. This study used process-tracing techniques to explore the effect of VMF damage on multi-attribute decision making under certainty. Thirteen subjects with focal VMF damage were compared with 11 subjects with frontal damage that spared the VMF and 21 demographically matched healthy control subjects. Participants chose rental apartments in a standard information board task drawn from the literature on normal decision making. VMF subjects performed the decision making task in a way that differed markedly from all other groups, favouring an 'alternative-based' information acquisition strategy (i.e. they organized their information search around individual apartments). In contrast, both healthy control subjects and subjects with damage predominantly involving dorsal and/or lateral prefrontal cortex pursued primarily 'attribute-based' search strategies (in which information was acquired about categories such as rent and noise level across several apartments). This difference in the pattern of information acquisition argues for systematic differences in the underlying decision heuristics and strategies employed by subjects with VMF damage, which in turn may affect the quality of their choices. These findings suggest that the processes supported by ventral and medial prefrontal cortex need to be conceptualized more broadly, to account for changes in decision making under conditions of certainty, as well as uncertainty, following damage to these areas.

Decision Making under Ambiguity and Objective Risk in Higher Age - A Review on Cognitive and Emotional Contributions.

PubMed

Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

2017-01-01

The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors - responsible for age-related differences in decision making - are additionally pointed out.

Decision Making under Ambiguity and Objective Risk in Higher Age – A Review on Cognitive and Emotional Contributions

PubMed Central

Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

2017-01-01

The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors – responsible for age-related differences in decision making – are additionally pointed out. PMID:29270145

Patients' ratings of genetic conditions validate a taxonomy to simplify decisions about preconception carrier screening via genome sequencing.

PubMed

Leo, Michael C; McMullen, Carmit; Wilfond, Benjamin S; Lynch, Frances L; Reiss, Jacob A; Gilmore, Marian J; Himes, Patricia; Kauffman, Tia L; Davis, James V; Jarvik, Gail P; Berg, Jonathan S; Harding, Cary; Kennedy, Kathleen A; Simpson, Dana Kostiner; Quigley, Denise I; Richards, C Sue; Rope, Alan F; Goddard, Katrina A B

2016-03-01

Advances in genome sequencing and gene discovery have created opportunities to efficiently assess more genetic conditions than ever before. Given the large number of conditions that can be screened, the implementation of expanded carrier screening using genome sequencing will require practical methods of simplifying decisions about the conditions for which patients want to be screened. One method to simplify decision making is to generate a taxonomy based on expert judgment. However, expert perceptions of condition attributes used to classify these conditions may differ from those used by patients. To understand whether expert and patient perceptions differ, we asked women who had received preconception genetic carrier screening in the last 3 years to fill out a survey to rate the attributes (predictability, controllability, visibility, and severity) of several autosomal recessive or X-linked genetic conditions. These conditions were classified into one of five taxonomy categories developed by subject experts (significantly shortened lifespan, serious medical problems, mild medical problems, unpredictable medical outcomes, and adult-onset conditions). A total of 193 women provided 739 usable ratings across 20 conditions. The mean ratings and correlations demonstrated that participants made distinctions across both attributes and categories. Aggregated mean attribute ratings across categories demonstrated logical consistency between the key features of each attribute and category, although participants perceived little difference between the mild and serious categories. This study provides empirical evidence for the validity of our proposed taxonomy, which will simplify patient decisions for results they would like to receive from preconception carrier screening via genome sequencing. © 2016 Wiley Periodicals, Inc.

Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features.

PubMed

Li, Hongyang; Panwar, Bharat; Omenn, Gilbert S; Guan, Yuanfang

2018-02-01

The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge. We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction. Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

Validation of a Cognitive Diagnostic Model across Multiple Forms of a Reading Comprehension Assessment

ERIC Educational Resources Information Center

Clark, Amy K.

2013-01-01

The present study sought to fit a cognitive diagnostic model (CDM) across multiple forms of a passage-based reading comprehension assessment using the attribute hierarchy method. Previous research on CDMs for reading comprehension assessments served as a basis for the attributes in the hierarchy. The two attribute hierarchies were fit to data from…

Model For Marketing Strategy Decision Based On Multicriteria Decicion Making: A Case Study In Batik Madura Industry

NASA Astrophysics Data System (ADS)

Anna, I. D.; Cahyadi, I.; Yakin, A.

2018-01-01

Selection of marketing strategy is a prominent competitive advantage for small and medium enterprises business development. The selection process is is a multiple criteria decision-making problem, which includes evaluation of various attributes or criteria in a process of strategy formulation. The objective of this paper is to develop a model for the selection of a marketing strategy in Batik Madura industry. The current study proposes an integrated approach based on analytic network process (ANP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine the best strategy for Batik Madura marketing problems. Based on the results of group decision-making technique, this study selected fourteen criteria, including consistency, cost, trend following, customer loyalty, business volume, uniqueness manpower, customer numbers, promotion, branding, bussiness network, outlet location, credibility and the inovation as Batik Madura marketing strategy evaluation criteria. A survey questionnaire developed from literature review was distributed to a sample frame of Batik Madura SMEs in Pamekasan. In the decision procedure step, expert evaluators were asked to establish the decision matrix by comparing the marketing strategy alternatives under each of the individual criteria. Then, considerations obtained from ANP and TOPSIS methods were applied to build the specific criteria constraints and range of the launch strategy in the model. The model in this study demonstrates that, under current business situation, Straight-focus marketing strategy is the best marketing strategy for Batik Madura SMEs in Pamekasan.

Factors associated with suicidal ideation: the role of context.

PubMed

Han, Sehee; Lee, Hee-Sun

2013-06-01

No previous study could be found that examined the longitudinal association between suicidal ideation and the factors associated with it and that considered both individual and contextual characteristics simultaneously. This study examined whether variation in suicidal ideation is attributable to the administrative-area level and examined suicidal ideation and the factors associated with it at multiple levels, especially focusing on social capital. Longitudinal data of 5222 individuals and 2741 households in 25 administrative areas from the Wave 1 and Wave 2 of the Seoul Welfare Panel Study were used. In the study, 2.7% of variation in suicidal ideation was attributable to the administrative area. The results also suggested that perceived helpfulness at individual level (odds ratio (OR) = 0.60; 95% confidence interval (CI) = 0.43, 0.83) and organizational participation at administrative-area level were associated with suicidal ideation (OR = 0.73; 95% CI = 0.53, 0.99). Policy makers should consider laying down policies aimed at preventing suicide at administrative-area level as suicidal ideation of individuals is different between administrative areas. However, it should also be recognized that directing attention solely at administrative-area level is not efficient, as only small variations in suicidal ideation are attributable to this level. Decision makers need to consider policies promoting social capital, as it may play a role in reducing suicide risk.

Undetected cognitive impairment and decision-making capacity in patients receiving hospice care.

PubMed

Burton, Cynthia Z; Twamley, Elizabeth W; Lee, Lana C; Palmer, Barton W; Jeste, Dilip V; Dunn, Laura B; Irwin, Scott A

2012-04-01

: Cognitive dysfunction is common in patients with advanced, life-threatening illness and can be attributed to a variety of factors (e.g., advanced age, opiate medication). Such dysfunction likely affects decisional capacity, which is a crucial consideration as the end-of-life approaches and patients face multiple choices regarding treatment, family, and estate planning. This study examined the prevalence of cognitive impairment and its impact on decision-making abilities among hospice patients with neither a chart diagnosis of a cognitive disorder nor clinically apparent cognitive impairment (e.g., delirium, unresponsiveness). : A total of 110 participants receiving hospice services completed a 1-hour neuropsychological battery, a measure of decisional capacity, and accompanying interviews. : In general, participants were mildly impaired on measures of verbal learning, verbal memory, and verbal fluency; 54% of the sample was classified as having significant, previously undetected cognitive impairment. These individuals performed significantly worse than the other participants on all neuropsychological and decisional capacity measures, with effect sizes ranging from medium to very large (0.43-2.70). A number of verbal abilities as well as global cognitive functioning significantly predicted decision-making capacity. : Despite an absence of documented or clinically obvious impairment, more than half of the sample had significant cognitive impairments. Assessment of cognition in hospice patients is warranted, including assessment of verbal abilities that may interfere with understanding or reasoning related to treatment decisions. Identification of patients at risk for impaired cognition and decision making may lead to effective interventions to improve decision making and honor the wishes of patients and families.

Employment Decisions Made by Mothers of Infants.

ERIC Educational Resources Information Center

Hock, Ellen; And Others

1985-01-01

Assessed how individual characteristics and perceptions of infant needs are associated with decisions about employment. Comparisons and findings about decisions to work or stay home are interpreted in light of maternal demographic and personality attributes and maternal perceptions of infant needs and characteristics. (Author/BL)

The inaction effect in the psychology of regret.

PubMed

Zeelenberg, Marcel; van de Bos, Kees; van Dijk, Eric; Pieters, Rik

2002-03-01

Previous research showed that decisions to act (i.e., actions) produce more regret than decisions not to act (i.e., inactions). This previous research focused on decisions made in isolation and ignored that decisions are often made in response to earlier outcomes. The authors show in 4 experiments that these prior outcomes may promote action and hence make inaction more abnormal. They manipulated information about a prior outcome. As hypothesized, when prior outcomes were positive or absent, people attributed more regret to action than to inaction. However, as predicted and counter to previous research, following negative prior outcomes, more regret was attributed to inaction, a finding that the authors label the inaction effect. Experiment 4, showing differential effects for regret and disappointment, demonstrates the need for emotion-specific predictions.

Coding Theory Information Theory and Radar

DTIC Science & Technology

2005-01-01

the design and synthesis of artificial multiagent systems and for the understanding of human decision-making processes. This... altruism that may exist in a complex society. SGT derives its ability to account simultaneously for both group and individual interests from the structure of ...satisficing decision theory as a model of human decision mak- ing. 2 Multi-Attribute Decision Making Many decision problems involve the consideration of

26 CFR 301.6231(e)-2 - Judicial decision not a bar to certain adjustments.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 18 2010-04-01 2010-04-01 false Judicial decision not a bar to certain....6231(e)-2 Judicial decision not a bar to certain adjustments. (a) In general. A court decision with respect to a partner's income tax liability attributable to nonpartnership items shall not be a bar to...

Decision-theoretic approach to data acquisition for transit operations planning

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

Ritchie, S.G.

The most costly element of transportation planning and modeling activities in the past has usually been that of data acquisition. This is even truer today when the unit costs of data collection are increasing rapidly and at the same time budgets are severely limited by continuing policies of fiscal austerity in the public sector. The overall objectives of this research were to improve the decisions and decision-making capabilities of transit operators or planners in short-range transit planning, and to improve the quality and cost-effectiveness of associated route or corridor-level data collection and service monitoring activities. A new approach was presentedmore » for sequentially updating the parameters of both simple and multiple linear regression models with stochastic regressors, and for determining the expected value of sample information and expected net gain of sampling for associated sample designs. A new approach was also presented for estimating and updating (both spatially and temporally) the parameters of multinomial logit discrete choice models, and for determining associated optimal sample designs for attribute-based and choice-based sampling methods. The approach provides an effective framework for addressing the issue of optimal sampling method and sample size, which to date have been largely unresolved. The application of these methodologies and the feasibility of the decision-theoretic approach was illustrated with a hypothetical case study example.« less

Physician Service Attribution Methods for Examining Provision of Low-Value Care

PubMed Central

Chang, Eva; Buist, Diana SM; Handley, Matthew; Pardee, Roy; Gundersen, Gabrielle; Reid, Robert J.

2016-01-01

Objectives: There has been significant research on provider attribution for quality and cost. Low-value care is an area of heightened focus, with little of the focus being on measurement; a key methodological decision is how to attribute delivered services and procedures. We illustrate the difference in relative and absolute physician- and panel-attributed services and procedures using overuse in cervical cancer screening. Study Design: A retrospective, cross-sectional study in an integrated health care system. Methods: We used 2013 physician-level data from Group Health Cooperative to calculate two utilization attributions: (1) panel attribution with the procedure assigned to the physician’s predetermined panel, regardless of who performed the procedure; and (2) physician attribution with the procedure assigned to the performing physician. We calculated the percentage of low-value cervical cancer screening tests and ranked physicians within the clinic using the two utilization attribution methods. Results: The percentage of low-value cervical cancer screening varied substantially between physician and panel attributions. Across the whole delivery system, median panel- and physician-attributed percentages were 15 percent and 10 percent, respectively. Among sampled clinics, panel-attributed percentages ranged between 10 percent and 17 percent, and physician-attributed percentages ranged between 9 percent and 13 percent. Within a clinic, median panel-attributed screening percentage was 17 percent (range 0 percent–27 percent) and physician-attributed percentage was 11 percent (range 0 percent–24 percent); physician rank varied by attribution method. Conclusions: The attribution method is an important methodological decision when developing low-value care measures since measures may ultimately have an impact on national benchmarking and quality scores. Cross-organizational dialogue and transparency in low-value care measurement will become increasingly important for all stakeholders. PMID:28203612

Physician Service Attribution Methods for Examining Provision of Low-Value Care.

PubMed

Chang, Eva; Buist, Diana Sm; Handley, Matthew; Pardee, Roy; Gundersen, Gabrielle; Reid, Robert J

2016-01-01

There has been significant research on provider attribution for quality and cost. Low-value care is an area of heightened focus, with little of the focus being on measurement; a key methodological decision is how to attribute delivered services and procedures. We illustrate the difference in relative and absolute physician- and panel-attributed services and procedures using overuse in cervical cancer screening. A retrospective, cross-sectional study in an integrated health care system. We used 2013 physician-level data from Group Health Cooperative to calculate two utilization attributions: (1) panel attribution with the procedure assigned to the physician's predetermined panel, regardless of who performed the procedure; and (2) physician attribution with the procedure assigned to the performing physician. We calculated the percentage of low-value cervical cancer screening tests and ranked physicians within the clinic using the two utilization attribution methods. The percentage of low-value cervical cancer screening varied substantially between physician and panel attributions. Across the whole delivery system, median panel- and physician-attributed percentages were 15 percent and 10 percent, respectively. Among sampled clinics, panel-attributed percentages ranged between 10 percent and 17 percent, and physician-attributed percentages ranged between 9 percent and 13 percent. Within a clinic, median panel-attributed screening percentage was 17 percent (range 0 percent-27 percent) and physician-attributed percentage was 11 percent (range 0 percent-24 percent); physician rank varied by attribution method. The attribution method is an important methodological decision when developing low-value care measures since measures may ultimately have an impact on national benchmarking and quality scores. Cross-organizational dialogue and transparency in low-value care measurement will become increasingly important for all stakeholders.

An Ethical (Descriptive) Framework for Judgment of Actions and Decisions in the Construction Industry and Engineering-Part I.

PubMed

Alkhatib, Omar J; Abdou, Alaa

2018-04-01

The construction industry is usually characterized as a fragmented system of multiple-organizational entities in which members from different technical backgrounds and moral values join together to develop a particular business or project. The greatest challenge in the construction process for the achievement of a successful practice is the development of an outstanding reputation, which is built on identifying and applying an ethical framework. This framework should reflect a common ethical ground for myriad people involved in this process to survive and compete ethically in today's turbulent construction market. This study establishes a framework for ethical judgment of behavior and actions conducted in the construction process. The framework was primarily developed based on the essential attributes of business management identified in the literature review and subsequently incorporates additional attributes identified to prevent breaches in the construction industry and common ethical values related to professional engineering. The proposed judgment framework is based primarily on the ethical dimension of professional responsibility. The Ethical Judgment Framework consists of descriptive approaches involving technical, professional, administrative, and miscellaneous terms. The framework provides the basis for judging actions as either ethical or unethical. Furthermore, the framework can be implemented as a form of preventive ethics, which would help avoid ethical dilemmas and moral allegations. The framework can be considered a decision-making model to guide actions and improve the ethical reasoning process that would help individuals think through possible implications and consequences of ethical dilemmas in the construction industry.

Identifying Thresholds for Ecosystem-Based Management

PubMed Central

Samhouri, Jameal F.; Levin, Phillip S.; Ainsworth, Cameron H.

2010-01-01

Background One of the greatest obstacles to moving ecosystem-based management (EBM) from concept to practice is the lack of a systematic approach to defining ecosystem-level decision criteria, or reference points that trigger management action. Methodology/Principal Findings To assist resource managers and policymakers in developing EBM decision criteria, we introduce a quantitative, transferable method for identifying utility thresholds. A utility threshold is the level of human-induced pressure (e.g., pollution) at which small changes produce substantial improvements toward the EBM goal of protecting an ecosystem's structural (e.g., diversity) and functional (e.g., resilience) attributes. The analytical approach is based on the detection of nonlinearities in relationships between ecosystem attributes and pressures. We illustrate the method with a hypothetical case study of (1) fishing and (2) nearshore habitat pressure using an empirically-validated marine ecosystem model for British Columbia, Canada, and derive numerical threshold values in terms of the density of two empirically-tractable indicator groups, sablefish and jellyfish. We also describe how to incorporate uncertainty into the estimation of utility thresholds and highlight their value in the context of understanding EBM trade-offs. Conclusions/Significance For any policy scenario, an understanding of utility thresholds provides insight into the amount and type of management intervention required to make significant progress toward improved ecosystem structure and function. The approach outlined in this paper can be applied in the context of single or multiple human-induced pressures, to any marine, freshwater, or terrestrial ecosystem, and should facilitate more effective management. PMID:20126647

Qualitatively Coherent Representation Makes Decision-Making Easier with Binary-Colored Multi-Attribute Tables: An Eye-Tracking Study

PubMed Central

Morii, Masahiro; Ideno, Takashi; Takemura, Kazuhisa; Okada, Mitsuhiro

2017-01-01

We aimed to identify the ways in which coloring cells affected decision-making in the context of binary-colored multi-attribute tables, using eye movement data. In our black-white attribute tables, the value of attributes was limited to two (with a certain threshold for each attribute) and each cell of the table was colored either black or white on the white background. We compared the two natural ways of systematic color assignment: “quantitatively coherent” ways and “qualitatively coherent” ways (namely, the ways in which the black-white distinction represented the quantitative amount distinction, and the ways in which the black-white distinction represented the quality distinction). The former consists of the following two types: (Type 1) “larger is black,” where the larger value-level was represented by black, and “smaller is white,” and (Type 2) “smaller is black.” The latter consisted of the following two types: (Type 3) “better is black,” and (Type 4) “worse is black.” We obtained the following two findings. [Result 1] The qualitatively coherent black-white tables (Types 3 and 4) made decision-making easier than the quantitatively coherent ones (Types 1 and 2). [Result 2] Among the two qualitatively coherent types, the “black is better” tables (Type 3) made decision making easier; in fact, the participants focused on the more important (black) cells in the case of “black is better” tables (Type 3) while they did not focus enough on the more important (white) ones in the case of the “white is better” tables (Type 4). We also examined some measures of eye movement patterns and showed that these measures supported our hypotheses. The data showed differences in the eye movement patterns between the first and second halves of each trial, which indicated the phased or combined decision strategies taken by the participants. PMID:28861020

Development of a decision aid for energy resource management for the Navajo Nation incorporating environmental cultural values

NASA Astrophysics Data System (ADS)

Necefer, Len Edward

Decision-making surrounding pathways of future energy resource management are complexity and requires balancing tradeoffs of multiple environmental, social, economic, and technical outcomes. Technical decision aid can provide a framework for informed decision making, allowing individuals to better understand the tradeoff between resources, technology, energy services, and prices. While technical decision aid have made significant advances in evaluating these quantitative aspects of energy planning and performance, they have not been designed to incorporate human factors, such as preferences and behavior that are informed by cultural values. Incorporating cultural values into decision tools can provide not only an improved decision framework for the Navajo Nation, but also generate new insights on how these perspective can improve decision making on energy resources. Ensuring these aids are a cultural fit for each context has the potential to increase trust and promote understanding of the tradeoffs involved in energy resource management. In this dissertation I present the development of a technical tool that explicitly addresses cultural and spiritual values and experimentally assesses their influence on the preferences and decision making of Navajo citizens. Chapter 2 describes the results of a public elicitation effort to gather information about stakeholder views and concerns related to energy development in the Navajo Nation in order to develop a larger sample survey and a decision-support tool that links techno-economic energy models with sociocultural attributes. Chapter 3 details the methods of developing the energy decision aid and its underlying assumptions for alternative energy projects and their impacts. This tool also provides an alternative to economic valuation of cultural impacts based upon an ordinal index tied to environmental impacts. Chapter 4 details the the influence of various cultural, environmental, and economic outcome information provided through the developed decision aid on beliefs and preferences related to the type and scale of energy development, trust of decision makers, and larger concern for environmental protection. Finally, chapter 5 presents concluding thoughts future research and on how technical-social decision tools can provide a means ensuring effective decision making on the Navajo Nation and other American Indian communities.

Prescription medicines: decision-making preferences of patients who receive different levels of public subsidy.

PubMed

Robertson, Jane; Doran, Evan; Henry, David A; Salkeld, Glenn

2014-02-01

To compare the relative importance of medicine attributes and decision-making preferences of patients with higher or lower levels of insurance coverage in a publicly funded health care system. Cross-sectional telephone survey of randomly selected regular medicine users aged ≥18 years in the Hunter Valley, NSW, Australia. Questions about 27 medicine attributes and active involvement in decisions to start a new medicine. After adjustment, there were few differences between the 408 concession card holders (high insurance) and 410 general beneficiaries (low insurance) in their assessment of the importance of medicine attributes. For both groups, the explanation of treatment options, establishing the need for the medicine, and medicine efficacy and safety were the most important considerations. Medicine costs, the treatment burden and medicine familiarity were less important; the views of family and friends ranked lowest. There was a statistically significantly greater influence of the regular doctor for the concession card holders than general beneficiaries (93.6 vs. 84%, adjusted OR 2.80, 95% CI 1.31, 5.99). Concession card holders were more likely to favour doctors having more say in the decision-making process (crude OR 1.69, 95% CI 1.28, 2.24), and more likely to report the most recent treatment decision being made by the doctor alone, compared with general beneficiaries (61.2 vs. 40.3%). Medicine need, efficacy and safety are viewed as paramount for most patients, irrespective of insurance status. While patients report the importance of participation in treatment decisions, delegation of decision making to the doctor was common in practice. © 2011 John Wiley & Sons Ltd.

A model for plant lighting system selection.

PubMed

Ciolkosz, D E; Albright, L D; Sager, J C; Langhans, R W

2002-01-01

A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.

Game Relativity: How Context Influences Strategic Decision Making

ERIC Educational Resources Information Center

Vlaev, Ivo; Chater, Nick

2006-01-01

Existing models of strategic decision making typically assume that only the attributes of the currently played game need be considered when reaching a decision. The results presented in this article demonstrate that the so-called "cooperativeness" of the previously played prisoner's dilemma games influence choices and predictions in the current…

How Decisions Emerge: Action Dynamics in Intertemporal Decision Making

ERIC Educational Resources Information Center

Dshemuchadse, Maja; Scherbaum, Stefan; Goschke, Thomas

2013-01-01

In intertemporal decision making, individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to an extent that seems irrational from an economical perspective. This behavior has been attributed to a lack of self-control and reflection, the nonlinearity of human time perception, and several other sources.…

Judgements about fellow professionals and the management of patients receiving palliative care in primary care: a qualitative study.

PubMed

Walshe, Catherine; Todd, Chris; Caress, Ann-Louise; Chew-Graham, Carolyn

2008-04-01

Policies emphasise the importance of collaborative working in community palliative care. Collaborations are generally formed through formal and informal referral processes, but little is known about what influences professionals' decisions to refer to such services. To explore the influences on referrals within general and specialist community palliative care services. Qualitative, multiple-case study. Three primary care trusts in the north-west of England. Multiple data collection methods were employed, including documentary analysis, observation of referral team meetings and interviews. This paper primarily reports data from interviews with 47 health professionals, including GPs, district nurses, and specialist palliative care professionals. Judgements -- positive and negative -- about aspects of fellow professionals' performances appeared to influence referral decisions and ongoing collaboration and care. Attributes upon which these judgements were based included professional responsiveness and communication, respect, working and workload management practices, perceived expertise, and notions of elite practice. The effects of such judgements on referral and healthcare practices were altered by professional "game playing" to achieve professionals' desired outcomes. Palliative care policies and protocols need to take account of these complex and subtle influences on referrals and collaboration. In particular, teamwork and partnership are encouraged within palliative care work, but critical judgements indicate that such partnerships may be difficult or fragile. It is likely that such judgemental attitudes and practices affect many aspects of primary care, not just palliative care.

Putting It All Together: A Unified Account of Word Recognition and Reaction-Time Distributions

ERIC Educational Resources Information Center

Norris, Dennis

2009-01-01

R. Ratcliff, P. Gomez, and G. McKoon (2004) suggested much of what goes on in lexical decision is attributable to decision processes and may not be particularly informative about word recognition. They proposed that lexical decision should be characterized by a decision process, taking the form of a drift-diffusion model (R. Ratcliff, 1978), that…

Identifying attributes of food literacy: a scoping review.

PubMed

Azevedo Perry, Elsie; Thomas, Heather; Samra, H Ruby; Edmonstone, Shannon; Davidson, Lyndsay; Faulkner, Amy; Petermann, Lisa; Manafò, Elizabeth; Kirkpatrick, Sharon I

2017-09-01

An absence of food literacy measurement tools makes it challenging for nutrition practitioners to assess the impact of food literacy on healthy diets and to evaluate the outcomes of food literacy interventions. The objective of the present scoping review was to identify the attributes of food literacy. A scoping review of peer-reviewed and grey literature was conducted and attributes of food literacy identified. Subjects included in the search were high-risk groups. Eligible articles were limited to research from Canada, USA, the UK, Australia and New Zealand. The search identified nineteen peer-reviewed and thirty grey literature sources. Fifteen identified food literacy attributes were organized into five categories. Food and Nutrition Knowledge informs decisions about intake and distinguishing between 'healthy' and 'unhealthy' foods. Food Skills focuses on techniques of food purchasing, preparation, handling and storage. Self-Efficacy and Confidence represent one's capacity to perform successfully in specific situations. Ecologic refers to beyond self and the interaction of macro- and microsystems with food decisions and behaviours. Food Decisions reflects the application of knowledge, information and skills to make food choices. These interdependent attributes are depicted in a proposed conceptual model. The lack of evaluated tools inhibits the ability to assess and monitor food literacy; tailor, target and evaluate programmes; identify gaps in programming; engage in advocacy; and allocate resources. The present scoping review provides the foundation for the development of a food literacy measurement tool to address these gaps.

A scheme of hidden-structure attribute-based encryption with multiple authorities

NASA Astrophysics Data System (ADS)

Ling, J.; Weng, A. X.

2018-05-01

In the most of the CP-ABE schemes with hidden access structure, both all the user attributes and the key generation are managed by only one authority. The key generation efficiency will decrease as the number of user increases, and the data will encounter security issues as the only authority is attacked. We proposed a scheme of hidden-structure attribute-based encryption with multiple authorities, which introduces multiple semi-trusted attribute authorities, avoiding the threat even though one or more authorities are attacked. We also realized user revocation by managing a revocation list. Based on DBDH assumption, we proved that our scheme is of IND-CMA security. The analysis shows that our scheme improves the key generation efficiency.

Gist memory in the unconscious-thought effect.

PubMed

Abadie, Marlène; Waroquier, Laurent; Terrier, Patrice

2013-07-01

The unconscious-thought effect (UTE) occurs when people are better able to make complex decisions after a period of distraction rather than immediately or after a period of conscious deliberation. This finding has often been interpreted as evidence of unconscious thinking. In two experiments, we provided the first evidence that the UTE is accompanied by enhanced memory for the gist of decision-relevant attributes and demonstrated that the cognitive demands of a distraction task moderate its effect on decision making and gist memory. It was only following a low-demand distraction task that participants chose the best alternative more often and displayed enhanced gist memory for decision-relevant attributes. These findings suggest that the UTE occurs only if cognitive resources are available and that it is accompanied by enhanced organization of information in memory, as shown by the increase in gist memory.

Engaging and supporting fathers to promote breast feeding: a concept analysis.

PubMed

Sherriff, Nigel; Hall, Valerie; Panton, Christina

2014-06-01

Empirical evidence demonstrates that fathers have a strong influence on a mother's decision to initiate and continue breast feeding. However, no clear delineation of what behaviours and attributes constitute father support or differentiate it from other kinds of support is provided in the current literature. The purpose of this study was to analyse the concept of 'father support' in relation to maternity services and broader health settings, thereby clarifying meaning to enable comprehension and application in practice, education, and research. A concept analysis combining the evolutionary model of concept development with the inter-related theoretical, fieldwork and analytical phases of the hybrid model of concept development. Children's Centres in East and West Sussex in Southern England. Repeated qualitative research over two phases with 16 parents of breast fed infants through seven focus groups and five telephone interviews. CINAHL, PsycINFO, AMED, MEDLINE, OVID and EMBASE databases were searched for articles published in English between 1999 and 2013 using the keywords breast feeding, father, and support. Seven same-sex focus groups and five individual interviews were also conducted over two research phases with the parents of breast fed infants to expand and exemplify, and then validate the analysis of the literature search. Five main attributes of father support in relation to breast feeding were identified: (1) knowledge about breast feeding; (2) positive attitude to breast feeding; (3) involvement in the decision-making process; (4) practical support; and (5) emotional support. Multiple antecedents and consequences to these attributes were also identified. This study has contributed to clarifying the meaning of father support in relation to breast feeding and provides an important starting point for the development of a theoretical and practical model of optimal breast feeding that takes into account father support. Identification of attributes, antecedents, and consequences of father support may assist practitioners to reflect on current working practices and service delivery models, and offer important educational opportunities for the training of student midwives and other health professionals. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Framing effects in medical situations: distinctions of attribute, goal and risky choice frames.

PubMed

Peng, Jiaxi; Jiang, Yuan; Miao, Danmin; Li, Rui; Xiao, Wei

2013-06-01

To verify whether three different framing effects (risky choice, attribute and goal) exist in simulated medical situations and to analyse any differences. Medical decision-making problems were established, relating to medical skill evaluation, patient compliance and a selection of treatment options. All problems were described in positive and negative frame conditions. Significantly more positive evaluations were made if the doctor's medical records were described as 'of 100 patients, 70 patients became better' compared with those described as 'of 100 patients, 30 patients didn't become better'. Doctor's advice described in a negative frame resulted in significantly more decisions to comply, compared with advice described in a positive frame. Treatment options described in terms of survival rates resulted in significantly more adventurous choices compared with options described in terms of mortality rates. Decision-making reversal appeared in the risky choice and attribute frames, but not the goal frame. Framing effects were shown to exist in simulated medical situations, but there were significant differences among the three kinds of such effects.

Enriching the national map database for multi-scale use: Introducing the visibilityfilter attribution

USGS Publications Warehouse

Stauffer, Andrew J.; Webinger, Seth; Roche, Brittany

2016-01-01

The US Geological Survey’s (USGS) National Geospatial Technical Operations Center is prototyping and evaluating the ability to filter data through a range of scales using 1:24,000-scale The National Map (TNM) datasets as the source. A “VisibilityFilter” attribute is under evaluation that can be added to all TNM vector data themes and will permit filtering of data to eight target scales between 1:24,000 and 1:5,000,000, thus defining each feature’s smallest applicable scale-of-use. For a prototype implementation, map specifications for 1:100,000- and 1:250,000-scale USGS Topographic Map Series are being utilized to define feature content appropriate at fixed mapping scales to guide generalization decisions that are documented in a ScaleMaster diagram. This paper defines the VisibilityFilter attribute, the generalization decisions made for each TNM data theme, and how these decisions are embedded into the data to support efficient data filtering.

A discrete-choice experiment to determine patient preferences for injectable multiple sclerosis treatments in Germany.

PubMed

Poulos, Christine; Kinter, Elizabeth; Yang, Jui-Chen; Bridges, John F P; Posner, Joshua; Gleißner, Erika; Mühlbacher, Axel; Kieseier, Bernd

2016-03-01

The aim of this study was to assess the relative importance of features of a hypothetical injectable disease-modifying treatment for patients with multiple sclerosis using a discrete-choice experiment. German residents at least 18 years of age with a self-reported physician diagnosis of multiple sclerosis completed a 25-30 minute online discrete-choice experiment. Patients were asked to choose one of two hypothetical injectable treatments for multiple sclerosis, defined by different levels of six attributes (disability progression, the number of relapses in the next 4 years, injection time, frequency of injections, presence of flu-like symptoms, and presence of injection-site reactions). The data were analyzed using a random-parameters logit model. Of 202 adults who completed the survey, results from 189 were used in the analysis. Approximately 50% of all patients reported a diagnosis of relapsing-remitting multiple sclerosis, and 31% reported secondary progressive multiple sclerosis. Approximately 71% of patients had current or prior experience with injectable multiple sclerosis medication. Approximately 53% had experienced flu-like symptoms caused by their medication, and 47% had experienced mild injection-site reactions. At least one significant difference was seen between levels in all attributes, except injection time. The greatest change in relative importance between levels of an attribute was years until symptoms get worse from 1 to 4 years. The magnitude of this difference was about twice that of relapses in the next 4 years, frequency of injections, and flu-like symptoms. Most attributes examined in this experiment had an influence on patient preference. Patients placed a significant value on improvements in the frequency of dosing and disability progression. Results suggest that changes in injection frequency can be as important as changes in efficacy and safety attributes. Understanding which attributes of injectable therapies influence patient preference could potentially improve outcomes and adherence in patients with multiple sclerosis.

A Decision Support System for Mitigating Stream Temperature Impacts in the Sacramento River

NASA Astrophysics Data System (ADS)

Caldwell, R. J.; Zagona, E. A.; Rajagopalan, B.

2014-12-01

Increasing demands on the limited and variable water supply across the West can result in insufficient streamflow to sustain healthy fish habitat. We develop an integrated decision support system (DSS) for modeling and mitigating stream temperature impacts and demonstrate it on the Sacramento River system in California. Water management in the Sacramento River is a complex task with a diverse set of demands ranging from municipal supply to mitigation of fisheries impacts due to high water temperatures. Current operations utilize the temperature control device (TCD) structure at Shasta Dam to mitigate these high water temperatures downstream at designated compliance points. The TCD structure at Shasta Dam offers a rather unique opportunity to mitigate water temperature violations through adjustments to both release volume and temperature. In this study, we develop and evaluate a model-based DSS with four broad components that are coupled to produce the decision tool for stream temperature mitigation: (i) a suite of statistical models for modeling stream temperature attributes using hydrology and climate variables of critical importance to fish habitat; (ii) a reservoir thermal model for modeling the thermal structure and, consequently, the water release temperature, (iii) a stochastic weather generator to simulate weather sequences consistent with seasonal outlooks; and, (iv) a set of decision rules (i.e., 'rubric') for reservoir water releases in response to outputs from the above components. Multiple options for modifying releases at Shasta Dam were considered in the DSS, including mixing water from multiple elevations through the TCD and using different acceptable levels of risk. The DSS also incorporates forecast uncertainties and reservoir operating options to help mitigate stream temperature impacts for fish habitat, while efficiently using the reservoir water supply and cold pool storage. The use of these coupled tools in simulating impacts of future climate on stream temperature variability is also demonstrated. Results indicate that the DSS could substantially reduce the number of violations of thermal criteria, while ensuring maintenance of the cold pool storage throughout the summer.

Effective visualization of integrated knowledge and data to enable informed decisions in drug development and translational medicine

PubMed Central

2013-01-01

Integrative understanding of preclinical and clinical data is imperative to enable informed decisions and reduce the attrition rate during drug development. The volume and variety of data generated during drug development have increased tremendously. A new information model and visualization tool was developed to effectively utilize all available data and current knowledge. The Knowledge Plot integrates preclinical, clinical, efficacy and safety data by adding two concepts: knowledge from the different disciplines and protein binding. Internal and public available data were gathered and processed to allow flexible and interactive visualizations. The exposure was expressed as the unbound concentration of the compound and the treatment effect was normalized and scaled by including expert opinion on what a biologically meaningful treatment effect would be. The Knowledge Plot has been applied both retrospectively and prospectively in project teams in a number of different therapeutic areas, resulting in closer collaboration between multiple disciplines discussing both preclinical and clinical data. The Plot allows head to head comparisons of compounds and was used to support Candidate Drug selections and differentiation from comparators and competitors, back translation of clinical data, understanding the predictability of preclinical models and assays, reviewing drift in primary endpoints over the years, and evaluate or benchmark compounds in due diligence comparing multiple attributes. The Knowledge Plot concept allows flexible integration and visualization of relevant data for interpretation in order to enable scientific and informed decision-making in various stages of drug development. The concept can be used for communication, decision-making, knowledge management, and as a forward and back translational tool, that will result in an improved understanding of the competitive edge for a particular project or disease area portfolio. In addition, it also builds up a knowledge and translational continuum, which in turn will reduce the attrition rate and costs of clinical development by identifying poor candidates early. PMID:24098919

Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B.

PubMed

Chen, Xiao Yu; Ma, Li Zhuang; Chu, Na; Zhou, Min; Hu, Yiyang

2013-01-01

Chronic hepatitis B (CHB) is a serious public health problem, and Traditional Chinese Medicine (TCM) plays an important role in the control and treatment for CHB. In the treatment of TCM, zheng discrimination is the most important step. In this paper, an approach based on CFS-GA (Correlation based Feature Selection and Genetic Algorithm) and C5.0 boost decision tree is used for zheng classification and progression in the TCM treatment of CHB. The CFS-GA performs better than the typical method of CFS. By CFS-GA, the acquired attribute subset is classified by C5.0 boost decision tree for TCM zheng classification of CHB, and C5.0 decision tree outperforms two typical decision trees of NBTree and REPTree on CFS-GA, CFS, and nonselection in comparison. Based on the critical indicators from C5.0 decision tree, important lab indicators in zheng progression are obtained by the method of stepwise discriminant analysis for expressing TCM zhengs in CHB, and alterations of the important indicators are also analyzed in zheng progression. In conclusion, all the three decision trees perform better on CFS-GA than on CFS and nonselection, and C5.0 decision tree outperforms the two typical decision trees both on attribute selection and nonselection.

Comparison of two multi-criteria decision techniques for eliciting treatment preferences in people with neurological disorders.

PubMed

Ijzerman, Maarten J; van Til, Janine A; Snoek, Govert J

2008-12-01

To present and compare two multi-criteria decision techniques (analytic hierarchy process [AHP] and conjoint analysis [CA]) for eliciting preferences in patients with cervical spinal cord injury (SCI) who are eligible for surgical augmentation of hand function, either with or without implantation of a neuroprosthesis. The methods were compared in respect to attribute weights, overall preference, and practical experiences. Two previously designed and administered multi-criteria decision surveys in patients with SCI were compared and further analysed. Attributes and their weights in the AHP experiment were determined by an expert panel, followed by determination of the weights in the patient group. Attributes for the CA were selected and validated using an expert panel, piloted in six patients with SCI and subsequently administered to the same group of patients as participated in the AHP experiment. Both experiments showed the importance of non-outcome-related factors such as inpatient stay and number of surgical procedures. In particular, patients were less concerned with clinical outcomes in actual decision making. Overall preference in both the AHP and CA was in favor of tendon reconstruction (0.6 vs 0.4 for neuroprosthetic implantation). Both methods were easy to apply, but AHP was less easily explained and understood. Both the AHP and CA methods produced similar outcomes, which may have been caused by the obvious preferences of patients. CA may be preferred because of the holistic approach of considering all treatment attributes simultaneously and, hence, its power in simulating real market decisions. On the other hand, the AHP method is preferred as a hands-on, easy-to-implement task with immediate feedback to the respondent. This flexibility allows AHP to be used in shared decision making. However, the way the technique is composed results in many inconsistencies. Patients preferred CA but complained about the number of choice tasks.

Developing an Environmental Currency Relevant to People

EPA Science Inventory

EPA (and others worldwide) wanted to more fully include environmental attributes in decision making but there was no systematic approach that defined and organized the environment to identify and potentially quantify those environmental attributes that humans required, valued, or...

Decision making and preferences for acoustic signals in choice situations by female crickets.

PubMed

Gabel, Eileen; Kuntze, Janine; Hennig, R Matthias

2015-08-01

Multiple attributes usually have to be assessed when choosing a mate. Efficient choice of the best mate is complicated if the available cues are not positively correlated, as is often the case during acoustic communication. Because of varying distances of signalers, a female may be confronted with signals of diverse quality at different intensities. Here, we examined how available cues are weighted for a decision by female crickets. Two songs with different temporal patterns and/or sound intensities were presented in a choice paradigm and compared with female responses from a no-choice test. When both patterns were presented at equal intensity, preference functions became wider in choice situations compared with a no-choice paradigm. When the stimuli in two-choice tests were presented at different intensities, this effect was counteracted as preference functions became narrower compared with choice tests using stimuli of equal intensity. The weighting of intensity differences depended on pattern quality and was therefore non-linear. A simple computational model based on pattern and intensity cues reliably predicted female decisions. A comparison of processing schemes suggested that the computations for pattern recognition and directionality are performed in a network with parallel topology. However, the computational flow of information corresponded to serial processing. © 2015. Published by The Company of Biologists Ltd.

Humanizing Outgroups Through Multiple Categorization

PubMed Central

Prati, Francesca; Crisp, Richard J.; Meleady, Rose; Rubini, Monica

2016-01-01

In three studies, we examined the impact of multiple categorization on intergroup dehumanization. Study 1 showed that perceiving members of a rival university along multiple versus simple categorical dimensions enhanced the tendency to attribute human traits to this group. Study 2 showed that multiple versus simple categorization of immigrants increased the attribution of uniquely human emotions to them. This effect was explained by the sequential mediation of increased individuation of the outgroup and reduced outgroup threat. Study 3 replicated this sequential mediation model and introduced a novel way of measuring humanization in which participants generated attributes corresponding to the outgroup in a free response format. Participants generated more uniquely human traits in the multiple versus simple categorization conditions. We discuss the theoretical implications of these findings and consider their role in informing and improving efforts to ameliorate contemporary forms of intergroup discrimination. PMID:26984016

Counterfactual Thinking and Ethical Decision Making: A New Approach to an Old Problem for Marketing Education

ERIC Educational Resources Information Center

Celuch, Kevin; Saxby, Carl

2013-01-01

The present study extends understanding of the self-regulatory aspects of ethical decision making by integrating and exploring relationships among counterfactual thinking, attribution, anticipatory emotions, and ethical decision-making constructs and processes. Specifically, we examine the effects of a manipulation designed to stimulate a…

Development of Moral Emotions and Decision-Making from Childhood to Young Adulthood

ERIC Educational Resources Information Center

Hasegawa, Mari

2016-01-01

This study investigated the development of moral decision-making and moral emotion attributions in antisocial behavior and peer relationship dilemma scenarios. Participants were 540 school- and college-aged students, who were asked to explain their moral decision-making, subsequent emotions, and reasoning in regard to the scenarios. We combined…

Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making. Copyright © 2016. Published by Elsevier Inc.

The North American Regional Climate Change Assessment Program (NARCCAP): Status and results

NASA Astrophysics Data System (ADS)

Arritt, R.

2009-04-01

NARCCAP is an international program that is generating projections of climate change for the U.S., Canada, and northern Mexico at decision-relevant regional scales. NARCCAP uses multiple limited-area regional climate models (RCMs) nested within multiple atmosphere-ocean general circulation models (AOGCMs). The use of multiple regional and global models allows us to investigate the uncertainty in model responses to future emissions (here, the A2 SRES scenario). The project also includes global time-slice experiments at the same discretization (50 km) using the GFDL atmospheric model (AM2.1) and the NCAR atmospheric model (CAM3). Phase I of the experiment uses the regional models nested within reanalysis in order to establish uncertainty attributable to the RCMs themselves. Phase II of the project then nests the RCMs within results from the current and future runs of the AOGCMs to explore the cascade of uncertainty from the global to the regional models. Phase I has been completed and the results to be shown include findings that spectral nudging is beneficial in some regions but not in others. Phase II is nearing completion and some preliminary results will be shown.

Decision fatigue: A conceptual analysis.

PubMed

Pignatiello, Grant A; Martin, Richard J; Hickman, Ronald L

2018-03-01

Decision fatigue is an applicable concept to healthcare psychology. Due to a lack of conceptual clarity, we present a concept analysis of decision fatigue. A search of the term "decision fatigue" was conducted across seven research databases, which yielded 17 relevant articles. The authors identified three antecedent themes (decisional, self-regulatory, and situational) and three attributional themes (behavioral, cognitive, and physiological) of decision fatigue. However, the extant literature failed to adequately describe consequences of decision fatigue. This concept analysis provides needed conceptual clarity for decision fatigue, a concept possessing relevance to nursing and allied health sciences.

The Elasticity of Preferences.

PubMed

Simon, Dan; Spiller, Stephen A

2016-12-01

We explore how preferences for attributes are constructed when people choose between multiattribute options. As found in prior research, we observed that while people make decisions, their preferences for the attributes in question shift to support the emerging choice, thus enabling confident decisions. The novelty of the studies reported here is that participants repeated the same task 6 to 8 weeks later. We found that between tasks, preferences returned to near their original levels, only to shift again to support the second choice, regardless of which choice participants made. Similar patterns were observed in a free-choice task (Study 1) and when the favorableness of options was manipulated (Study 2). It follows that preferences behave in an elastic manner: In the absence of situational pressures, they rest at baseline levels, but during the process of reaching a decision, they morph to support the chosen options. This elasticity appears to facilitate confident decision making in the face of decisional conflict.

Contribution of the Multi Attribute Value Theory to conflict resolution in groundwater management. Application to the Mancha Oriental groundwater system, Spain

NASA Astrophysics Data System (ADS)

Apperl, B.; Andreu, J.; Karjalainen, T. P.; Pulido-Velazquez, M.

2014-09-01

The implementation of the EU Water Framework Directive demands participatory water resource management approaches. Decision making in groundwater quantity and quality management is complex because of the existence of many independent actors, heterogeneous stakeholder interests, multiple objectives, different potential policies, and uncertain outcomes. Conflicting stakeholder interests have been often identified as an impediment to the realization and success of water regulations and policies. The management of complex groundwater systems requires clarifying stakeholders' positions (identifying stakeholders preferences and values), improving transparency with respect to outcomes of alternatives, and moving the discussion from the selection of alternatives towards definition of fundamental objectives (value-thinking approach), what facilitates negotiation. The aims of the study are to analyse the potential of the multi attribute value theory for conflict resolution in groundwater management and to evaluate the benefit of stakeholder incorporation in the different stages of the planning process to find an overall satisfying solution for groundwater management. The research was conducted in the Mancha Oriental groundwater system (Spain), subject to an intensive use of groundwater for irrigation. A complex set of objectives and attributes were defined, and the management alternatives were created by a combination of different fundamental actions, considering different implementation stages and future changes in water resources availability. Interviews were conducted with representative stakeholder groups using an interactive platform, showing simultaneously the consequences of changes of preferences to the alternative ranking. Results show that the acceptation of alternatives depends strongly on the combination of measures and the implementation stages. Uncertainties of the results were notable but did not influence heavily on the alternative ranking. The expected reduction of future groundwater resources by climate change increases the conflict potential. The implementation of the method to a very complex case study, with many conflicting objectives and alternatives and uncertain outcomes, including future scenarios under water limiting conditions, illustrate the potential of the method for supporting management decisions.

Contribution of the multi-attribute value theory to conflict resolution in groundwater management - application to the Mancha Oriental groundwater system, Spain

NASA Astrophysics Data System (ADS)

Apperl, B.; Pulido-Velazquez, M.; Andreu, J.; Karjalainen, T. P.

2015-03-01

The implementation of the EU Water Framework Directive demands participatory water resource management approaches. Decision making in groundwater quantity and quality management is complex because of the existence of many independent actors, heterogeneous stakeholder interests, multiple objectives, different potential policies, and uncertain outcomes. Conflicting stakeholder interests have often been identified as an impediment to the realisation and success of water regulations and policies. The management of complex groundwater systems requires the clarification of stakeholders' positions (identifying stakeholder preferences and values), improving transparency with respect to outcomes of alternatives, and moving the discussion from the selection of alternatives towards the definition of fundamental objectives (value-thinking approach), which facilitates negotiation. The aims of the study are to analyse the potential of the multi-attribute value theory for conflict resolution in groundwater management and to evaluate the benefit of stakeholder incorporation into the different stages of the planning process, to find an overall satisfying solution for groundwater management. The research was conducted in the Mancha Oriental groundwater system (Spain), subject to intensive use of groundwater for irrigation. A complex set of objectives and attributes was defined, and the management alternatives were created by a combination of different fundamental actions, considering different implementation stages and future changes in water resource availability. Interviews were conducted with representative stakeholder groups using an interactive platform, showing simultaneously the consequences of changes in preferences to the alternative ranking. Results show that the approval of alternatives depends strongly on the combination of measures and the implementation stages. Uncertainties in the results were notable, but did not influence the alternative ranking heavily. The expected reduction in future groundwater resources by climate change increases the conflict potential. The implementation of the method in a very complex case study, with many conflicting objectives and alternatives and uncertain outcomes, including future scenarios under water limiting conditions, illustrates the potential of the method for supporting management decisions.

General Matthew B. Ridgway: Attributes of Battle Command and Decision-Making

DTIC Science & Technology

1998-02-13

information dominance require the attributes of future battle commanders be different than those of the past? This paper focuses on the intellectual and personality traits of General Matthew B. Ridgway as they apply to operational command and decision-making. These traits are considered essential for analysis and serve as a framework in which to examine their applicability to future command. The essential qualities of an operational commander are divided into two categories: intellect and personality. Each category is further divided into elemental traits. The application

The antecedents and consequences of a beyond-choice view of decision situations: A construal level theory perspective.

PubMed

Halamish, Vered; Borovoi, Leah; Liberman, Nira

2017-02-01

Evaluating alternatives and comparing them to each other are integral to decision-making. In addition, however, decision makers may adopt a view that goes beyond choice and make inferences about the entire set of alternatives, about the dimensions that are relevant in similar decisions, and about the range of values on a specific dimension. We examined some antecedents and consequences of adopting a beyond-choice view of decision situations. Based on Construal Level Theory we suggest that a beyond-choice view entails high (vs. low) level of construal of the decision situation and hence is more likely to occur for decisions that are more psychologically distant. We further suggest that a consequence of a beyond-choice view might be a later difficulty to remember which attribute belongs to which alternative. To examine these predictions we conducted an experiment in which participants evaluated decision scenarios that were described as being relevant for the distant (vs. the near) future. One day later they answered a decision-related source recognition test in which they were asked to remember which attribute belongs to which alternative. As predicted, people had more source-memory errors in the distant than in the near future condition. These results suggest that a beyond-choice view of decision situations is an important consequence of psychological distance (vs. proximity). Copyright © 2016 Elsevier B.V. All rights reserved.

Semantic layers for illustrative volume rendering.

PubMed

Rautek, Peter; Bruckner, Stefan; Gröller, Eduard

2007-01-01

Direct volume rendering techniques map volumetric attributes (e.g., density, gradient magnitude, etc.) to visual styles. Commonly this mapping is specified by a transfer function. The specification of transfer functions is a complex task and requires expert knowledge about the underlying rendering technique. In the case of multiple volumetric attributes and multiple visual styles the specification of the multi-dimensional transfer function becomes more challenging and non-intuitive. We present a novel methodology for the specification of a mapping from several volumetric attributes to multiple illustrative visual styles. We introduce semantic layers that allow a domain expert to specify the mapping in the natural language of the domain. A semantic layer defines the mapping of volumetric attributes to one visual style. Volumetric attributes and visual styles are represented as fuzzy sets. The mapping is specified by rules that are evaluated with fuzzy logic arithmetics. The user specifies the fuzzy sets and the rules without special knowledge about the underlying rendering technique. Semantic layers allow for a linguistic specification of the mapping from attributes to visual styles replacing the traditional transfer function specification.

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

PubMed

Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

2017-08-10

Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

Patient Preferences for Attributes of Multiple Sclerosis Disease-Modifying Therapies

PubMed Central

Loucks, Aimee; Gipson, Gregory; Zhong, Lixian; Bui, Christine; Miller, Elizabeth; Owen, Mary; Pelletier, Daniel; Goodin, Douglas; Waubant, Emmanuelle; McCulloch, Charles E.

2015-01-01

Background: Timely individualized treatment is essential to improving relapsing-remitting multiple sclerosis (RRMS) patient health outcomes, yet little is known about how patients make treatment decisions. We sought to evaluate RRMS patient preferences for risks and benefits of treatment. Methods: Fifty patients with RRMS completed conjoint analysis surveys with 16 hypothetical disease-modifying therapy (DMT) medication profiles developed using a fractional factorial design. Medication profiles were assigned preference ratings from 0 (not acceptable) to 10 (most favorable). Medication attributes included a range of benefits, adverse effects, administration routes, and market durations. Analytical models used linear mixed-effects regression. Results: Participants showed the highest preference for medication profiles that would improve their symptoms (β = 0.81–1.03, P < .001), not a proven DMT outcome. Preventing relapses, the main clinical trial outcome, was not associated with significant preferences (P = .35). Each year of preventing magnetic resonance imaging changes and disease symptom progression showed DMT preferences of 0.17 point (β = 0.17, P = .002) and 0.12 point (β = 0.12, P < .001), respectively. Daily oral administration was preferred over all parenteral routes (P < .001). A 1% increase in death or severe disability decreased relative DMT preference by 1.15 points (P < .001). Conclusions: Patient preference focused on symptoms and prevention of progression but not on relapse prevention, the proven drug outcome. Patients were willing to accept some level of serious risk for certain types and amounts of benefits, and they strongly preferred daily oral administration over all other options. PMID:25892977

Developing and piloting the multiple mini-interview in pre-registration student midwife selection in a UK setting.

PubMed

Callwood, Alison; Cooke, Debbie; Allan, Helen

2014-12-01

Published research has demonstrated that the multiple mini-interview (MMI) is a reliable assessment instrument in medical and nursing student selection. There is a dearth of evidence specifically relating to the advancement and subsequent evaluation of MMIs in the context of student midwife selection. To develop, pilot and examine the reliability of MMIs in pre-registration student midwife selection in a UK setting. DeVellis' framework for questionnaire development underpinned the generation of MMI scenarios. BSc (Hons) Midwifery Studies students at a Higher Education Institution in the UK volunteered to participate in 'mock' MMI circuits during the first week of their programme. An eight station model was piloted. Communication skills were rated at each station as a generic attribute. Station specific attributes assessed included: compassion and empathy; respect for difference and diversity; honesty and integrity; intellectual curiosity and reflective nature; advocacy; respect for privacy and dignity; team working and initiative; the role of the midwife and motivation to become a midwife. Participants' responses to scenario questions were rated on a 7 point scale. Cronbach's alpha scores measuring internal consistency ranged from 0.91 to 0.97 CONCLUSION: The systematic development of the MMI model and scenarios resulted in 'excellent' reliability across all stations. These findings endorse the MMI technique as a reliable alternative to the personal interview in informing final decisions in pre-registration student midwife selection. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review.

PubMed

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh; Sadiq, Rehan

2015-01-01

Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, and finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Suboptimal choice in rats: incentive salience attribution promotes maladaptive decision-making

PubMed Central

Chow, Jonathan J; Smith, Aaron P; Wilson, A George; Zentall, Thomas R; Beckmann, Joshua S

2016-01-01

Stimuli that are more predictive of subsequent reward also function as better conditioned reinforcers. Moreover, stimuli attributed with incentive salience function as more robust conditioned reinforcers. Some theories have suggested that conditioned reinforcement plays an important role in promoting suboptimal choice behavior, like gambling. The present experiments examined how different stimuli, those attributed with incentive salience versus those without, can function in tandem with stimulus-reward predictive utility to promote maladaptive decision-making in rats. One group of rats had lights associated with goal-tracking as the reward-predictive stimuli and another had levers associated with sign-tracking as the reward-predictive stimuli. All rats were first trained on a choice procedure in which the expected value across both alternatives was equivalent but differed in their stimulus-reward predictive utility. Next, the expected value across both alternatives was systematically changed so that the alternative with greater stimulus-reward predictive utility was suboptimal in regard to primary reinforcement. The results demonstrate that in order to obtain suboptimal choice behavior, incentive salience alongside strong stimulus-reward predictive utility may be necessary; thus, maladaptive decision-making can be driven more by the value attributed to stimuli imbued with incentive salience that reliably predict a reward rather than the reward itself. PMID:27993692

Suboptimal choice in rats: Incentive salience attribution promotes maladaptive decision-making.

PubMed

Chow, Jonathan J; Smith, Aaron P; Wilson, A George; Zentall, Thomas R; Beckmann, Joshua S

2017-03-01

Stimuli that are more predictive of subsequent reward also function as better conditioned reinforcers. Moreover, stimuli attributed with incentive salience function as more robust conditioned reinforcers. Some theories have suggested that conditioned reinforcement plays an important role in promoting suboptimal choice behavior, like gambling. The present experiments examined how different stimuli, those attributed with incentive salience versus those without, can function in tandem with stimulus-reward predictive utility to promote maladaptive decision-making in rats. One group of rats had lights associated with goal-tracking as the reward-predictive stimuli and another had levers associated with sign-tracking as the reward-predictive stimuli. All rats were first trained on a choice procedure in which the expected value across both alternatives was equivalent but differed in their stimulus-reward predictive utility. Next, the expected value across both alternatives was systematically changed so that the alternative with greater stimulus-reward predictive utility was suboptimal in regard to primary reinforcement. The results demonstrate that in order to obtain suboptimal choice behavior, incentive salience alongside strong stimulus-reward predictive utility may be necessary; thus, maladaptive decision-making can be driven more by the value attributed to stimuli imbued with incentive salience that reliably predict a reward rather than the reward itself. Copyright © 2016 Elsevier B.V. All rights reserved.

The coherence effect: Blending cold and hot cognitions.

PubMed

Simon, Dan; Stenstrom, Douglas M; Read, Stephen J

2015-09-01

Previous research has shown that making complex judgments and decisions entails a mental reconstruction of the task in a way that increases the state of coherence between the emerging conclusion and its underlying attributes: The attributes that support the conclusion grow stronger, whereas the attributes that support the losing option weaken. This coherence effect is understood to occur bidirectionally, in that conclusions follow from the decision-maker's evaluation of the attributes, while the evaluations of the attributes shift to cohere with the emerging conclusion. The current studies were designed to extend the coherence effect to encompass cognitions that could be considered "hot," such as valence evaluations, motivation toward outcomes of events, liking and disliking of actors, and emotions toward actors. Study 1 found that evaluations of a complex social relationship were accompanied not only by supportive interpretations of the ambiguous facts, but also by concordant hot cognitions. Studies 2 through 4 included manipulations to demonstrate the spreading of coherence from cold to hot cognitions and in the opposite direction. We observed these effects following a manipulation of the facts (Study 2), a manipulation of participants' emotions toward the actor (Study 3), and a manipulation of participants' motivation toward the outcome of the case (Study 4). These results support the proposition that complex judgments and decisions are performed by coherence-based reasoning: a holistic, connectionist process that maximizes coherence among and between the myriad of factors involved in the tasks and the hot cognitive reactions to them. (c) 2015 APA, all rights reserved).

The effect of parental intellectual disability status on child protection service worker decision making.

PubMed

Proctor, S N; Azar, S T

2013-12-01

There is evidence to suggest that parents with an intellectual disability (ID) constitute a higher proportion of child-protective services (CPS) cases than would be expected based on the prevalence of ID in the general population. Researchers have suggested that the stereotypic assumptions and expectations that CPS workers have about parents with an ID might influence decisions and responses made to such parents. This study examined whether parental ID (having an ID vs. not) had an effect on CPS workers' emotional reactions, attributions and decisions about risk to the child, whether to remove the child and workers' general willingness to help the parent. Two hundred and twelve CPS workers read vignettes describing parents who were labelled as either having or not having an ID. Workers responded to the vignettes by making ratings of their emotional reactions, attributions and decisions regarding risk, removal and helping. CPS workers made significantly higher ratings of pity, willingness to help and risk for parents with an ID than for parents without an ID. Lower ratings of anger and disgust were found for parents with an ID than for parents without an ID. Parents' intellectual status did not have a direct effect on workers' attributions or removal decisions. The results show evidence for the influence of stereotypes regarding parental ID due to its differential effect on CPS workers' emotional reactions and decisions about child risk and their willingness to help. © 2012 The Authors. Journal of Intellectual Disability Research © 2012 John Wiley & Sons Ltd, MENCAP & IASSID.

Agency Modulates the Lateral and Medial Prefrontal Cortex Responses in Belief-Based Decision Making

PubMed Central

Xue, Gui; He, Qinghua; Lu, Zhong-Lin; Levin, Irwin P.; Dong, Qi; Bechara, Antoine

2013-01-01

Many real-life decisions in complex and changing environments are guided by the decision maker’s beliefs, such as her perceived control over decision outcomes (i.e., agency), leading to phenomena like the “illusion of control”. However, the neural mechanisms underlying the “agency” effect on belief-based decisions are not well understood. Using functional imaging and a card guessing game, we revealed that the agency manipulation (i.e., either asking the subjects (SG) or the computer (CG) to guess the location of the winning card) not only affected the size of subjects’ bets, but also their “world model” regarding the outcome dependency. Functional imaging results revealed that the decision-related activation in the lateral and medial prefrontal cortex (PFC) was significantly modulated by agency and previous outcome. Specifically, these PFC regions showed stronger activation when subjects made decisions after losses than after wins under the CG condition, but the pattern was reversed under the SG condition. Furthermore, subjects with high external attribution of negative events were more affected by agency at the behavioral and neural levels. These results suggest that the prefrontal decision-making system can be modulated by abstract beliefs, and are thus vulnerable to factors such as false agency and attribution. PMID:23762332

Can promoting patient decision making be exclusionary? Moral expectations and cultural difference in the narratives of UK maternity clinicians.

PubMed

Davies, Myfanwy; Elwyn, Glyn; Papadopoulos, Irena; Fleming, Lon; Williams, Gareth

2009-01-01

Patient autonomy in health care decision making is increasingly advocated as a means of promoting patients' 'responsibilities' for treatments and costs. However, little is known with regard to clinicians' understanding of patients' potential responsibilities in decision making. We explore how clinicians may view decision making as a 'moral' obligation and examine how moral virtue is discursively constructed in this context and in the face of ethnic and social difference. Data reported are derived from an interview study that examined perceptions of maternity decision making among Arab Muslim women and clinicians. Results reported here are from the clinician sample which includes obstetricians, general practitioners (GPs) and midwives. Clinicians perceived that a key element of their role involved imparting relevant information to their clients and, increasingly, involving them in making autonomous decisions about their care. However, by analysing and assessing the attribution of specific cultural differences in clinicians' discussion of decision making processes with minority group women, we demonstrate how some clinicians justified their failure to promote autonomy through shared decision making with women from these groups. We will demonstrate these attributes to be those of passivity and non-rationality which entail some negative moral judgements and which have a complex relationship to gender and power

Distinct Roles of Dopamine and Subthalamic Nucleus in Learning and Probabilistic Decision Making

ERIC Educational Resources Information Center

Coulthard, Elizabeth J.; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K.; Murphy, Gillian; Keeley, Sophie; Whone, Alan L.

2012-01-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making…

A unifying Bayesian account of contextual effects in value-based choice

PubMed Central

Friston, Karl J.; Dolan, Raymond J.

2017-01-01

Empirical evidence suggests the incentive value of an option is affected by other options available during choice and by options presented in the past. These contextual effects are hard to reconcile with classical theories and have inspired accounts where contextual influences play a crucial role. However, each account only addresses one or the other of the empirical findings and a unifying perspective has been elusive. Here, we offer a unifying theory of context effects on incentive value attribution and choice based on normative Bayesian principles. This formulation assumes that incentive value corresponds to a precision-weighted prediction error, where predictions are based upon expectations about reward. We show that this scheme explains a wide range of contextual effects, such as those elicited by other options available during choice (or within-choice context effects). These include both conditions in which choice requires an integration of multiple attributes and conditions where a multi-attribute integration is not necessary. Moreover, the same scheme explains context effects elicited by options presented in the past or between-choice context effects. Our formulation encompasses a wide range of contextual influences (comprising both within- and between-choice effects) by calling on Bayesian principles, without invoking ad-hoc assumptions. This helps clarify the contextual nature of incentive value and choice behaviour and may offer insights into psychopathologies characterized by dysfunctional decision-making, such as addiction and pathological gambling. PMID:28981514

Bringing Meaning to Numbers: The Impact of Evaluative Categories on Decisions

ERIC Educational Resources Information Center

Peters, Ellen; Dieckmann, Nathan F.; Vastfjall, Daniel; Mertz, C. K.; Slovic, Paul; Hibbard, Judith H.

2009-01-01

Decision makers are often quite poor at using numeric information in decisions. The results of 4 experiments demonstrate that a manipulation of evaluative meaning (i.e., the extent to which an attribute can be mapped onto a good/bad scale; this manipulation is accomplished through the addition of visual boundary lines and evaluative labels to a…

Application of Grey Relational Analysis to Decision-Making during Product Development

ERIC Educational Resources Information Center

Hsiao, Shih-Wen; Lin, Hsin-Hung; Ko, Ya-Chuan

2017-01-01

A multi-attribute decision-making (MADM) approach was proposed in this study as a prediction method that differs from the conventional production and design methods for a product. When a client has different dimensional requirements, this approach can quickly provide a company with design decisions for each product. The production factors of a…

Uncertainty in sample estimates and the implicit loss function for soil information.

NASA Astrophysics Data System (ADS)

Lark, Murray

2015-04-01

One significant challenge in the communication of uncertain information is how to enable the sponsors of sampling exercises to make a rational choice of sample size. One way to do this is to compute the value of additional information given the loss function for errors. The loss function expresses the costs that result from decisions made using erroneous information. In certain circumstances, such as remediation of contaminated land prior to development, loss functions can be computed and used to guide rational decision making on the amount of resource to spend on sampling to collect soil information. In many circumstances the loss function cannot be obtained prior to decision making. This may be the case when multiple decisions may be based on the soil information and the costs of errors are hard to predict. The implicit loss function is proposed as a tool to aid decision making in these circumstances. Conditional on a logistical model which expresses costs of soil sampling as a function of effort, and statistical information from which the error of estimates can be modelled as a function of effort, the implicit loss function is the loss function which makes a particular decision on effort rational. In this presentation the loss function is defined and computed for a number of arbitrary decisions on sampling effort for a hypothetical soil monitoring problem. This is based on a logistical model of sampling cost parameterized from a recent geochemical survey of soil in Donegal, Ireland and on statistical parameters estimated with the aid of a process model for change in soil organic carbon. It is shown how the implicit loss function might provide a basis for reflection on a particular choice of sample size by comparing it with the values attributed to soil properties and functions. Scope for further research to develop and apply the implicit loss function to help decision making by policy makers and regulators is then discussed.

Nurse-led immunotreatment DEcision Coaching In people with Multiple Sclerosis (DECIMS) - Feasibility testing, pilot randomised controlled trial and mixed methods process evaluation.

PubMed

Rahn, A C; Köpke, S; Backhus, I; Kasper, J; Anger, K; Untiedt, B; Alegiani, A; Kleiter, I; Mühlhauser, I; Heesen, C

2018-02-01

Treatment decision-making is complex for people with multiple sclerosis. Profound information on available options is virtually not possible in regular neurologist encounters. The "nurse decision coach model" was developed to redistribute health professionals' tasks in supporting immunotreatment decision-making following the principles of informed shared decision-making. To test the feasibility of a decision coaching programme and recruitment strategies to inform the main trial. Feasibility testing and parallel pilot randomised controlled trial, accompanied by a mixed methods process evaluation. Two German multiple sclerosis university centres. People with suspected or relapsing-remitting multiple sclerosis facing immunotreatment decisions on first line drugs were recruited. Randomisation to the intervention (n = 38) or control group (n = 35) was performed on a daily basis. Quantitative and qualitative process data were collected from people with multiple sclerosis, nurses and physicians. We report on the development and piloting of the decision coaching programme. It comprises a training course for multiple sclerosis nurses and the coaching intervention. The intervention consists of up to three structured nurse-led decision coaching sessions, access to an evidence-based online information platform (DECIMS-Wiki) and a final physician consultation. After feasibility testing, a pilot randomised controlled trial was performed. People with multiple sclerosis were randomised to the intervention or control group. The latter had also access to the DECIMS-Wiki, but received otherwise care as usual. Nurses were not blinded to group assignment, while people with multiple sclerosis and physicians were. The primary outcome was 'informed choice' after six months including the sub-dimensions' risk knowledge (after 14 days), attitude concerning immunotreatment (after physician consultation), and treatment uptake (after six months). Quantitative process evaluation data were collected via questionnaires. Qualitative interviews were performed with all nurses and a convenience sample of nine people with multiple sclerosis. 116 people with multiple sclerosis fulfilled the inclusion criteria and 73 (63%) were included. Groups were comparable at baseline. Data of 51 people with multiple sclerosis (70%) were available for the primary endpoint. In the intervention group 15 of 31 (48%) people with multiple sclerosis achieved an informed choice after six months and 6 of 20 (30%) in the control group. Process evaluation data illustrated a positive response towards the coaching programme as well as good acceptance. The pilot-phase showed promising results concerning acceptability and feasibility of the intervention, which was well perceived by people with multiple sclerosis, most nurses and physicians. Delegating parts of the immunotreatment decision-making process to trained nurses has the potential to increase informed choice and participation as well as effectiveness of patient-physician consultations. Copyright © 2017 Elsevier Ltd. All rights reserved.

What They Think: Attributions Made by Youth Workers about Youth Circumstances and the Implications for Service-Delivery in Out-of-School Time Programs

ERIC Educational Resources Information Center

Travis, Raphael

2010-01-01

The current study explored attributions made by youth work professionals ("workers") in out-of-school time (OST) programs about the social circumstances of and perceived need of program youth. It followed prior research examining impacts of worker-level attributions on decision-making in service delivery. Two types of OST programs were…

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

PubMed

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

Policy impacts of ecosystem services knowledge

PubMed Central

Posner, Stephen M.; McKenzie, Emily; Ricketts, Taylor H.

2016-01-01

Research about ecosystem services (ES) often aims to generate knowledge that influences policies and institutions for conservation and human development. However, we have limited understanding of how decision-makers use ES knowledge or what factors facilitate use. Here we address this gap and report on, to our knowledge, the first quantitative analysis of the factors and conditions that explain the policy impact of ES knowledge. We analyze a global sample of cases where similar ES knowledge was generated and applied to decision-making. We first test whether attributes of ES knowledge themselves predict different measures of impact on decisions. We find that legitimacy of knowledge is more often associated with impact than either the credibility or salience of the knowledge. We also examine whether predictor variables related to the science-to-policy process and the contextual conditions of a case are significant in predicting impact. Our findings indicate that, although many factors are important, attributes of the knowledge and aspects of the science-to-policy process that enhance legitimacy best explain the impact of ES science on decision-making. Our results are consistent with both theory and previous qualitative assessments in suggesting that the attributes and perceptions of scientific knowledge and process within which knowledge is coproduced are important determinants of whether that knowledge leads to action. PMID:26831101

Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project.

PubMed

Alghamdi, Manal; Al-Mallah, Mouaz; Keteyian, Steven; Brawner, Clinton; Ehrman, Jonathan; Sakr, Sherif

2017-01-01

Machine learning is becoming a popular and important approach in the field of medical research. In this study, we investigate the relative performance of various machine learning methods such as Decision Tree, Naïve Bayes, Logistic Regression, Logistic Model Tree and Random Forests for predicting incident diabetes using medical records of cardiorespiratory fitness. In addition, we apply different techniques to uncover potential predictors of diabetes. This FIT project study used data of 32,555 patients who are free of any known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems between 1991 and 2009 and had a complete 5-year follow-up. At the completion of the fifth year, 5,099 of those patients have developed diabetes. The dataset contained 62 attributes classified into four categories: demographic characteristics, disease history, medication use history, and stress test vital signs. We developed an Ensembling-based predictive model using 13 attributes that were selected based on their clinical importance, Multiple Linear Regression, and Information Gain Ranking methods. The negative effect of the imbalance class of the constructed model was handled by Synthetic Minority Oversampling Technique (SMOTE). The overall performance of the predictive model classifier was improved by the Ensemble machine learning approach using the Vote method with three Decision Trees (Naïve Bayes Tree, Random Forest, and Logistic Model Tree) and achieved high accuracy of prediction (AUC = 0.92). The study shows the potential of ensembling and SMOTE approaches for predicting incident diabetes using cardiorespiratory fitness data.

The clinical utility index as a practical multiattribute approach to drug development decisions.

PubMed

Poland, B; Hodge, F L; Khan, A; Clemen, R T; Wagner, J A; Dykstra, K; Krishna, R

2009-07-01

We identify some innovative approaches to predicting overall patient benefit from investigational drugs to support development decisions. We then illustrate calculation of a probabilistic clinical utility index (CUI), an implementation of multiattribute utility that focuses on clinical attributes. We recommend use of the CUI for the support of early drug development decisions because of its practicality, reasonable accuracy, and transparency to decision makers, at stages in which financial factors that may dominate later-phase decisions are less critical.

Robotic intelligence kernel

DOEpatents

Bruemmer, David J [Idaho Falls, ID

2009-11-17

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

A Literature Review and Compilation of Nuclear Waste Management System Attributes for Use in Multi-Objective System Evaluations.

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

Kalinina, Elena Arkadievna; Samsa, Michael

The purpose of this work was to compile a comprehensive initial set of potential nuclear waste management system attributes. This initial set of attributes is intended to serve as a starting point for additional consideration by system analysts and planners to facilitate the development of a waste management system multi-objective evaluation framework based on the principles and methodology of multi-attribute utility analysis. The compilation is primarily based on a review of reports issued by the Canadian Nuclear Waste Management Organization (NWMO) and the Blue Ribbon Commission on America's Nuclear Future (BRC), but also an extensive review of the available literaturemore » for similar and past efforts as well. Numerous system attributes found in different sources were combined into a single objectives-oriented hierarchical structure. This study provides a discussion of the data sources and the descriptions of the hierarchical structure. A particular focus of this study was on collecting and compiling inputs from past studies that involved the participation of various external stakeholders. However, while the important role of stakeholder input in a country's waste management decision process is recognized in the referenced sources, there are only a limited number of in-depth studies of the stakeholders' differing perspectives. Compiling a comprehensive hierarchical listing of attributes is a complex task since stakeholders have multiple and often conflicting interests. The BRC worked for two years (January 2010 to January 2012) to "ensure it has heard from as many points of view as possible." The Canadian NWMO study took four years and ample resources, involving national and regional stakeholders' dialogs, internet-based dialogs, information and discussion sessions, open houses, workshops, round tables, public attitude research, website, and topic reports. The current compilation effort benefited from the distillation of these many varied inputs conducted by the previous studies.« less

Systematic Review of Patients' and Parents' Preferences for ADHD Treatment Options and Processes of Care.

PubMed

Schatz, Nicole K; Fabiano, Gregory A; Cunningham, Charles E; dosReis, Susan; Waschbusch, Daniel A; Jerome, Stephanie; Lupas, Kellina; Morris, Karen L

2015-12-01

Patient preferences are an important topic of study with respect to attention-deficit hyperactivity disorder (ADHD) interventions, as there are multiple treatment choices available, multiple developmental levels to consider, and multiple potential individuals involved in treatment (children, parents, and adults with ADHD). Stated preference methods such as discrete choice experiment (DCE), best-worst scaling (BWS), and other utility value methods such as standard gamble interview (SGI) and time trade-off (TTO) are becoming more common in research addressing preferences for ADHD treatments. A synthesis of this research may facilitate improved patient-centered and family-centered treatment for ADHD. The purpose of this review was to synthesize reports across existing DCE, BWS, TTO, and SGI studies to assess which aspects of ADHD treatment are most studied as well as most preferred and influential in treatment decisions. MEDLINE, PsycINFO. A total of 41 studies referring to preferences for ADHD treatment were identified through the initial search and contact with researchers. Of these, 13 reported ADHD treatment preference data from a study using DCE, BWS, or SGI methods. No TTO studies were identified that met inclusion criteria. Methods and designs varied considerably across studies. Relatively few studies focused on preferences among children, adolescents, and adults compared with those that focused on the preferences of parents of children with ADHD. The majority of studies focused primarily on medication treatments, with many fewer focused on psychosocial treatments. Some studies indicated that parents of children with ADHD prefer to avoid stimulant medications in favor of behavioral or psychosocial interventions. Others report that parents see medication as a preferred treatment. Treatment outcome is a particularly salient attribute for treatment decisions for many informants. Potential outcomes of various treatments play a proximal role in patients' and families' decisions for ADHD treatment. Because the majority of studies focus on medication treatments for children with ADHD, more research is necessary to understand preferences related to behavioral and other psychosocial treatments both as stand-alone interventions and used in combination with medication. Additional research is also needed to assess the treatment preferences of adults with ADHD. In general, DCE, BWS, and SGI methods allow measurement of patient preferences in a manner that approximates the uncertainty and trade-offs inherent in real-world treatment decision making and provides valuable information to inform patient-centered and family-centered treatment.

Hidden Item Variance in Multiple Mini-Interview Scores

ERIC Educational Resources Information Center

Zaidi, Nikki L.; Swoboda, Christopher M.; Kelcey, Benjamin M.; Manuel, R. Stephen

2017-01-01

The extant literature has largely ignored a potentially significant source of variance in multiple mini-interview (MMI) scores by "hiding" the variance attributable to the sample of attributes used on an evaluation form. This potential source of hidden variance can be defined as rating items, which typically comprise an MMI evaluation…

Issues in Distance Education: A Primer for Higher Education Decision Makers

ERIC Educational Resources Information Center

Beaudoin, Michael

2016-01-01

This chapter presents an overview of current issues related to distance learning in higher education. It identifies central questions, issues, challenges, and opportunities that must be addressed by decision makers, as well as key attributes of effective leaders.

Measurements of Rationality: Individual Differences in Information Processing, the Transitivity of Preferences and Decision Strategies

PubMed Central

Sleboda, Patrycja; Sokolowska, Joanna

2017-01-01

The first goal of this study was to validate the Rational-Experiential Inventory (REI) and the Cognitive Reflection Test (CRT) through checking their relation to the transitivity axiom. The second goal was to test the relation between decision strategies and cognitive style as well as the relation between decision strategies and the transitivity of preferences. The following characteristics of strategies were investigated: requirements for trade-offs, maximization vs. satisficing and option-wise vs. attribute-wise information processing. Respondents were given choices between two multi-attribute options. The options were designed so that the choice indicated which strategy was applied. Both the REI-R and the CRT were found to be good predictors of the transitivity of preferences. Respondents who applied compensatory strategies and the maximization criterion scored highly on the REI-R and in the CRT, whereas those who applied the satisficing rule scored highly on the REI-R but not in the CRT. Attribute-wise information processing was related to low scores in both measurements. Option-wise information processing led to a high transitivity of preferences. PMID:29093695

Preference Reversals in Decision Making Under Risk are Accompanied by Changes in Attention to Different Attributes.

PubMed

Kim, Betty E; Seligman, Darryl; Kable, Joseph W

2012-01-01

Recent work has shown that visual fixations reflect and influence trial-to-trial variability in people's preferences between goods. Here we extend this principle to attribute weights during decision making under risk. We measured eye movements while people chose between two risky gambles or bid on a single gamble. Consistent with previous work, we found that people exhibited systematic preference reversals between choices and bids. For two gambles matched in expected value, people systematically chose the higher probability option but provided a higher bid for the option that offered the greater amount to win. This effect was accompanied by a shift in fixations of the two attributes, with people fixating on probabilities more during choices and on amounts more during bids. Our results suggest that the construction of value during decision making under risk depends on task context partly because the task differentially directs attention at probabilities vs. amounts. Since recent work demonstrates that neural correlates of value vary with visual fixations, our results also suggest testable hypotheses regarding how task context modulates the neural computation of value to generate preference reversals.

Measurements of Rationality: Individual Differences in Information Processing, the Transitivity of Preferences and Decision Strategies.

PubMed

Sleboda, Patrycja; Sokolowska, Joanna

2017-01-01

The first goal of this study was to validate the Rational-Experiential Inventory ( REI ) and the Cognitive Reflection Test ( CRT ) through checking their relation to the transitivity axiom. The second goal was to test the relation between decision strategies and cognitive style as well as the relation between decision strategies and the transitivity of preferences. The following characteristics of strategies were investigated: requirements for trade-offs, maximization vs. satisficing and option-wise vs. attribute-wise information processing. Respondents were given choices between two multi-attribute options. The options were designed so that the choice indicated which strategy was applied. Both the REI-R and the CRT were found to be good predictors of the transitivity of preferences. Respondents who applied compensatory strategies and the maximization criterion scored highly on the REI-R and in the CRT , whereas those who applied the satisficing rule scored highly on the REI-R but not in the CRT . Attribute-wise information processing was related to low scores in both measurements. Option-wise information processing led to a high transitivity of preferences.

Three Human Attributes

ERIC Educational Resources Information Center

Eaves, Ronald C.; Williams, Thomas O., Jr.

2004-01-01

This study represents a beginning step in research that may ultimately show that the multitudes of human behavior that educators currently encounter may be reduced to three broad human attributes: arousal, affect, and cognition. The resulting simplicity should lead to improved understanding and better decision making by practitioners. Four…

Team Attributes, Processes, and Values: A Pedagogical Framework

ERIC Educational Resources Information Center

Keyton, Joann; Beck, Stephenson J.

2008-01-01

This article proposes a pedagogical framework to help students analyze their group and team interactions. Intersecting five fundamental group attributes (group size, group goal, group member interdependence, group structure, and group identity) with three overarching group processes (leadership, decision making, and conflict management) creates an…

The double-edged sword of genetic accounts of criminality: causal attributions from genetic ascriptions affect legal decision making.

PubMed

Cheung, Benjamin Y; Heine, Steven J

2015-12-01

Much debate exists surrounding the applicability of genetic information in the courtroom, making the psychological processes underlying how people consider this information important to explore. This article addresses how people think about different kinds of causal explanations in legal decision-making contexts. Three studies involving a total of 600 Mechanical Turk and university participants found that genetic, versus environmental, explanations of criminal behavior lead people to view the applicability of various defense claims differently, perceive the perpetrator's mental state differently, and draw different causal attributions. Moreover, mediation and path analyses highlight the double-edged nature of genetic attributions-they simultaneously reduce people's perception of the perpetrator's sense of control while increasing people's tendencies to attribute the cause to internal factors and to expect the perpetrator to reoffend. These countervailing relations, in turn, predict sentencing in opposite directions, although no overall differences in sentencing or ultimate verdicts were found. © 2015 by the Society for Personality and Social Psychology, Inc.

Knowledge Style Profiling: An Exploration of Cognitive, Temperament, Demographic and Organizational Characteristics among Decision Makers Using Advanced Analytical Technologies

ERIC Educational Resources Information Center

Polito, Vincent A., Jr.

2010-01-01

The objective of this research was to explore the possibilities of identifying knowledge style factors that could be used as central elements of a professional business analyst's (PBA) performance attributes at work for those decision makers that use advanced analytical technologies on decision making tasks. Indicators of knowledge style were…

Using Consumer Behavior and Decision Models to Aid Students in Choosing a Major.

ERIC Educational Resources Information Center

Kaynama, Shohreh A.; Smith, Louise W.

1996-01-01

A study found that using consumer behavior and decision models to guide students to a major can be useful and enjoyable for students. Students consider many of the basic parameters through multi-attribute and decision-analysis models, so time with professors, who were found to be the most influential group, can be used for more individual and…

Judgements about fellow professionals and the management of patients receiving palliative care in primary care: a qualitative study

PubMed Central

Walshe, Catherine; Todd, Chris; Caress, Ann-Louise; Chew-Graham, Carolyn

2008-01-01

Background Policies emphasise the importance of collaborative working in community palliative care. Collaborations are generally formed through formal and informal referral processes, but little is known about what influences professionals' decisions to refer to such services. Aim To explore the influences on referrals within general and specialist community palliative care services. Design of study Qualitative, multiple-case study. Setting Three primary care trusts in the north-west of England. Method Multiple data collection methods were employed, including documentary analysis, observation of referral team meetings and interviews. This paper primarily reports data from interviews with 47 health professionals, including GPs, district nurses, and specialist palliative care professionals. Results Judgements — positive and negative — about aspects of fellow professionals' performances appeared to influence referral decisions and ongoing collaboration and care. Attributes upon which these judgements were based included professional responsiveness and communication, respect, working and workload management practices, perceived expertise, and notions of elite practice. The effects of such judgements on referral and healthcare practices were altered by professional ‘game playing’ to achieve professionals' desired outcomes. Conclusion Palliative care policies and protocols need to take account of these complex and subtle influences on referrals and collaboration. In particular, teamwork and partnership are encouraged within palliative care work, but critical judgements indicate that such partnerships may be difficult or fragile. It is likely that such judgemental attitudes and practices affect many aspects of primary care, not just palliative care. PMID:18494176

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review

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

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh

2015-01-15

Highlights: • We review Municipal Solid Waste Management studies with focus on multiple stakeholders. • We focus on studies with multi-criteria decision analysis methods and discover their trends. • Most studies do not offer solutions for situations where stakeholders compete for more benefits or have unequal voting powers. • Governments and experts are the most participated stakeholders and AHP is the most dominant method. - Abstract: Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, andmore » finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies.« less

Technology to control variation in meat quality

USDA-ARS?s Scientific Manuscript database

Consumers have certain expectations regarding the quality of the meat they purchase. Lean color is the primary quality attribute used by consumers to make purchase decisions. Similarly, repeat purchase decisions are generally a result of eating satisfaction, which is determined by the perceived va...

Focus Groups in Elderly Ophthalmologic Patients: Setting the Stage for Quantitative Preference Elicitation.

PubMed

Danner, Marion; Vennedey, Vera; Hiligsmann, Mickaël; Fauser, Sascha; Stock, Stephanie

2016-02-01

Patients suffering from age-related macular degeneration (AMD) are rarely actively involved in decision-making, despite facing preference-sensitive treatment decisions. This paper presents a qualitative study to prepare quantitative preference elicitation in AMD patients. The aims of this study were (1) to gain familiarity with and learn about the special requirements of the AMD patient population for quantitative data collection; and (2) to select/refine patient-relevant treatment attributes and levels, and gain insights into preference structures. Semi-structured focus group interviews were performed. An interview guide including preselected categories in the form of seven potentially patient-relevant treatment attributes was followed. To identify the most patient-relevant treatment attributes, a ranking exercise was performed. Deductive content analyses were done by two independent reviewers for each attribute to derive subcategories (potential levels of attributes) and depict preference trends. The focus group interviews included 21 patients. The interviews revealed that quantitative preference surveys in this population will have to be interviewer assisted to make the survey feasible for patients. The five most patient-relevant attributes were the effect on visual function [ranking score (RS): 139], injection frequency (RS: 101), approval status (RS: 83), side effects (RS: 79), and monitoring frequency (RS: 76). Attribute and level refinement was based on patients' statements. Preference trends and dependencies between attributes informed the quantitative instrument design. This study suggests that qualitative research is a very helpful step to prepare the design and administration of quantitative preference elicitation instruments. It especially facilitated familiarization with the target population and its preferences, and it supported attribute/level refinement.

Conjoint Analysis: A Study of the Effects of Using Person Variables.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…

Theory of the decision/problem state

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

A theory of the decision-problem state was introduced and elaborated. Starting with the basic model of a decision-problem condition, an attempt was made to explain how a major decision-problem may consist of subsets of decision-problem conditions composing different condition sequences. In addition, the basic classical decision-tree model was modified to allow for the introduction of a series of characteristics that may be encountered in an analysis of a decision-problem state. The resulting hierarchical model reflects the unique attributes of the decision-problem state. The basic model of a decision-problem condition was used as a base to evolve a more complex model that is more representative of the decision-problem state and may be used to initiate research on decision-problem states.

The Protected Areas Visitor Impact Management (PAVIM) framework: A simplified process for making management decisions

USGS Publications Warehouse

Farrell, T.A.; Marion, J.L.

2002-01-01

Ecotourism and protected area visitation in Central and South America have resulted in ecological impacts, which some protected areas managers have addressed by employing visitor impact management frameworks. In this paper, we propose the Protected Area Visitor Impact Management (PAVIM) framework as an alternative to carrying capacity and other frameworks such as Limits of Acceptable Change. We use a set of evaluation criteria to compare the relative positive and negative attributes of carrying capacity, other decision-making frameworks and the new framework, within the context of their actual and potential use in Central and South America. Positive attributes of PAVIM include simplicity, flexibility, cost effectiveness, timeliness, and incorporating input from stakeholders and local residents. Negative attributes include diminished objectivity and cultural sensitivity issues. Further research and application of PAVIM are recommended.

Modeling organizational justice improvements in a pediatric health service : a discrete-choice conjoint experiment.

PubMed

Cunningham, Charles E; Kostrzewa, Linda; Rimas, Heather; Chen, Yvonne; Deal, Ken; Blatz, Susan; Bowman, Alida; Buchanan, Don H; Calvert, Randy; Jennings, Barbara

2013-01-01

Patients value health service teams that function effectively. Organizational justice is linked to the performance, health, and emotional adjustment of the members of these teams. We used a discrete-choice conjoint experiment to study the organizational justice improvement preferences of pediatric health service providers. Using themes from a focus group with 22 staff, we composed 14 four-level organizational justice improvement attributes. A sample of 652 staff (76 % return) completed 30 choice tasks, each presenting three hospitals defined by experimentally varying the attribute levels. Latent class analysis yielded three segments. Procedural justice attributes were more important to the Decision Sensitive segment, 50.6 % of the sample. They preferred to contribute to and understand how all decisions were made and expected management to act promptly on more staff suggestions. Interactional justice attributes were more important to the Conduct Sensitive segment (38.5 %). A universal code of respectful conduct, consequences encouraging respectful interaction, and management's response when staff disagreed with them were more important to this segment. Distributive justice attributes were more important to the Benefit Sensitive segment, 10.9 % of the sample. Simulations predicted that, while Decision Sensitive (74.9 %) participants preferred procedural justice improvements, Conduct (74.6 %) and Benefit Sensitive (50.3 %) participants preferred interactional justice improvements. Overall, 97.4 % of participants would prefer an approach combining procedural and interactional justice improvements. Efforts to create the health service environments that patients value need to be comprehensive enough to address the preferences of segments of staff who are sensitive to different dimensions of organizational justice.

Challenges and strategies in applying performance measurement to federal public health programs.

PubMed

DeGroff, Amy; Schooley, Michael; Chapel, Thomas; Poister, Theodore H

2010-11-01

Performance measurement is widely accepted in public health as an important management tool supporting program improvement and accountability. However, several challenges impede developing and implementing performance measurement systems at the federal level, including the complexity of public health problems that reflect multiple determinants and involve outcomes that may take years to achieve, the decentralized and networked nature of public health program implementation, and the lack of reliable and consistent data sources and other issues related to measurement. All three of these challenges hinder the ability to attribute program results to specific public health program efforts. The purpose of this paper is to explore these issues in detail and offer potential solutions that support the development of robust and practical performance measures to meet the needs for program improvement and accountability. Adapting performance measurement to public health programs is both an evolving science and art. Through the strategies presented here, appropriate systems can be developed and monitored to support the production of meaningful data that will inform effective decision making at multiple levels. Published by Elsevier Ltd.

Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

NASA Astrophysics Data System (ADS)

Ohdaira, Tetsushi

2014-07-01

Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision.

Ventromedial Frontal Lobe Damage Alters how Specific Attributes are Weighed in Subjective Valuation.

PubMed

Vaidya, Avinash R; Sefranek, Marcus; Fellows, Lesley K

2017-10-23

The concept of subjective value is central to current neurobiological views of economic decision-making. Much of this work has focused on signals in the ventromedial frontal lobe (VMF) that correlate with the subjective value of a variety of stimuli (e.g., food, monetary gambles), and are thought to support decision-making. However, the neural processes involved in assessing and integrating value information from the attributes of such complex options remain to be defined. Here, we tested the necessary role of VMF in weighting attributes of naturalistic stimuli during value judgments. We asked how distinct attributes of visual artworks influenced the subjective value ratings of subjects with VMF damage, compared to healthy participants and a frontal lobe damaged control group. Subjects with VMF damage were less influenced by the energy (emotion, complexity) and color radiance (warmth, saturation) of the artwork, while they were similar to control groups in considering saliency, balance and concreteness. These dissociations argue that VMF is critical for allowing certain affective content to influence subjective value, while sparing the influence of perceptual or representational information. These distinctions are important for better defining the often-underspecified concept of subjective value and developing more detailed models of the brain mechanisms underlying decision behavior. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Attribute Framing and Goal Framing Effects in Health Decisions.

PubMed

Krishnamurthy, Parthasarathy; Carter, Patrick; Blair, Edward

2001-07-01

Levin, Schneider, and Gaeth (LSG, 1998) have distinguished among three types of framing-risky choice, attribute, and goal framing-to reconcile conflicting findings in the literature. In the research reported here, we focus on attribute and goal framing. LSG propose that positive frames should be more effective than negative frames in the context of attribute framing, and negative frames should be more effective than positive frames in the context of goal framing. We test this framework by manipulating frame valence (positive vs negative) and frame type (attribute vs goal) in a unified context with common procedures. We also argue that the nature of effects in a goal-framing context may depend on the extent to which the research topic has "intrinsic self-relevance" to the population. In the context of medical decision making, we operationalize low intrinsic self-relevance by using student subjects and high intrinsic self-relevance by using patients. As expected, we find complete support for the LSG framework under low intrinsic self-relevance and modified support for the LSG framework under high intrinsic self-relevance. Overall, our research appears to confirm and extend the LSG framework. Copyright 2001 Academic Press.

Multi-Attribute Consensus Building Tool

ERIC Educational Resources Information Center

Shyyan, Vitaliy; Christensen, Laurene; Thurlow, Martha; Lazarus, Sheryl

2013-01-01

The Multi-Attribute Consensus Building (MACB) method is a quantitative approach for determining a group's opinion about the importance of each item (strategy, decision, recommendation, policy, priority, etc.) on a list (Vanderwood, & Erickson, 1994). This process enables a small or large group of participants to generate and discuss a set…

Preferences for Training Options: A Conjoint Analysis

ERIC Educational Resources Information Center

Gan, Chui Goh; Lee, Julie Anne; Soutar, Geoffrey N.

2009-01-01

Singapore is a growing educational hub for the Asia Pacific region. However, no prior research has examined how Singaporean managers trade off attributes of training programs when making executive training decisions. The current study used conjoint analysis to identify the most important attributes of training programs as word of mouth, trainers'…

Estimated Costs of Sporadic Gastrointestinal Illness Associated with Surface Water Recreation: A Combined Analysis of Data from NEEAR and CHEERS Studies

EPA Science Inventory

BACKGROUND: The ·burden of illness can be described by addressing both incidence and illness severity attributable to water recreation. Monetized as cost. attributable disease burden estimates can be useful for environmental management decisions. OBJECTIVES: We characterize the ...

Texas Urban Triangle : pilot study to implement a spatial decision support system (SDSS) for sustainable mobility.

DOT National Transportation Integrated Search

2011-03-01

This project addressed sustainable transportation in the Texas Urban Triangle (TUT) by conducting a pilot : project at the county scale. The project tested and developed the multi-attribute Spatial Decision Support : System (SDSS) developed in 2009 u...

Applicant Appearance and Selection Decision Making: Revitalizing Employment Interview Education.

ERIC Educational Resources Information Center

Ilkka, Richard J.

1995-01-01

Presents five instructional propositions based on employment interview research on the relationship between applicant appearance and interviewer selection decisions. Argues that educators should examine the process of appearance attribution, explore appearance and position expectations, invite dialog of alleged effects, and assess related…

Temporary site selection and decision-making methods: a case study of Tehran, Iran.

PubMed

Omidvar, Babak; Baradaran-Shoraka, Mohammad; Nojavan, Mehdi

2013-07-01

Decisions on selecting an appropriate site for temporary shelter used to be taken in a limited amount of time after a disaster. The need for a systematic method in this area inspired the MADM (multi-attribute decision making) for complex disaster management decisions. This research proposes a model for appropriate and systematic site selection for temporary shelters, before an earthquake, using a geographical information system and MADM based on an earthquake damage assessment. After the effective criteria for site selection of temporary shelters are determined, the geographical layers of these criteria are prepared for Municipal District No.1 of Greater Tehran, the capital of Iran. Given these attributes and the required shelter area (415-610 hectares), 14 zones are proposed initially. Various MADM methods are used for the final selection. The mean of the aggregated ranking results are determined, and 10 of the 14 initial zones are ranked. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.

The prefabricated building risk decision research of DM technology on the basis of Rough Set

NASA Astrophysics Data System (ADS)

Guo, Z. L.; Zhang, W. B.; Ma, L. H.

2017-08-01

With the resources crises and more serious pollution, the green building has been strongly advocated by most countries and become a new building style in the construction field. Compared with traditional building, the prefabricated building has its own irreplaceable advantages but is influenced by many uncertainties. So far, a majority of scholars have been studying based on qualitative researches from all of the word. This paper profoundly expounds its significance about the prefabricated building. On the premise of the existing research methods, combined with rough set theory, this paper redefines the factors which affect the prefabricated building risk. Moreover, it quantifies risk factors and establish an expert knowledge base through assessing. And then reduced risk factors about the redundant attributes and attribute values, finally form the simplest decision rule. This simplest decision rule, which is based on the DM technology of rough set theory, provides prefabricated building with a controllable new decision-making method.

Exploring regional stakeholder needs and requirements in terms of Extreme Weather Event Attribution

NASA Astrophysics Data System (ADS)

Schwab, M.; Meinke, I.; Vanderlinden, J. P.; Touili, N.; Von Storch, H.

2015-12-01

Extreme event attribution has increasingly received attention in the scientific community. It may also serve decision-making at the regional level where much of the climate change impact mitigation takes place. Nevertheless, there is, to date, little known about the requirements of regional actors in terms of extreme event attribution. We have therefore analysed these at the example of regional decision-makers for climate change-related activities and/or concerned with storm surge risks at the German Baltic Sea and heat wave risks in the Greater Paris area. In order to explore if stakeholders find scientific knowledge from extreme event attribution useful and how this information might be relevant to their decision-making, we consulted a diverse set of actors engaged in the assessment, mitigation and communication of storm surge, heat wave, and climate change-related risks. Extreme event attribution knowledge was perceived to be most useful to public and political awareness-raising, but was of little or no relevance for the consulted stakeholders themselves. It was not acknowledged that it would support adaptation planning as sometimes argued in the literature. The consulted coastal protection, health, and urban adaptation planners rather needed reliable statements about possible future changes in extreme events than causal statements about past events. To enhance salience, a suitable product of event attribution should be linked to regional problems, vulnerabilities, and impacts of climate change. Given that the tolerance of uncertainty is rather low, most of the stakeholders also claimed that a suitable product of event attribution is to be received from a trusted "honest broker" and published rather later, but with smaller uncertainties than vice versa. Institutional mechanisms, like regional climate services, which enable and foster communication, translation and mediation across the boundaries between knowledge and action can help fulfill such requirements. This is of particular importance for extreme event attribution which is often understood as science producing complex and abstract information attached to large uncertainties. They can serve as an interface for creating the necessary mutual understanding by being in a continuous dialogue with both science and stakeholders.

Will Anything Useful Come Out of Virtual Reality? Examination of a Naval Application

DTIC Science & Technology

1993-05-01

The term virtual reality can encompass varying meanings, but some generally accepted attributes of a virtual environment are that it is immersive...technology, but at present there are few practical applications which are utilizing the broad range of virtual reality technology. This paper will discuss an...Operability, operator functions, Virtual reality , Man-machine interface, Decision aids/decision making, Decision support. ASW.

Redefining roles of science in planning and management: ecology as a planning and management tool

Treesearch

Greg Mason; Stephen Murphy

2002-01-01

Science as a way of knowing has great value to decision-making but there is need to consider all its attributes and assess how science ought to be informing decision-making. Consideration of the critiques of science can make science stronger and more useful to decision-making in an environmental and ecological context. Scientists, planners, and managers need to...

Fall attributions among middle-aged and older adults with multiple sclerosis.

PubMed

Peterson, Elizabeth W; Ben Ari, Eynat; Asano, Miho; Finlayson, Marcia L

2013-05-01

To (1) explore the falls attributions of middle-aged and older adults with multiple sclerosis (MS); and (2) examine the personal, health, and MS-related factors associated with the 3 most common attributions. A cross-sectional, descriptive study using data collected through a telephone interview. Falls attributions were obtained through an open-ended question to elicit participants' stories about their most recent fall. Recruitment was done through a national volunteer MS registry. Community. People (N=354) who were ≥55 years of age were interviewed; 313 provided a falls story. Respondents were primarily married, community-dwelling women who had been living with MS for 21 years, on average. Not applicable. The 3 most common fall attributions were used as dependent variables to address the second research objective. A total of 14 falls attributions were identified. The most common were balance (41.5%), lower extremity malfunction (31%), and assistive technology (AT; 29.7%). Falls control was significantly associated with the balance attribution (odds ratio [OR]=.51; 95% confidence interval [CI], .29-.88), no variables were associated with lower extremity malfunction attribution, and use of multiple mobility devices was significantly associated with the AT attribution (OR=3.78; 95% CI, 2.09-6.85). Findings highlight the complex nature of falls among middle-aged and older adults with MS and point to the need for comprehensive fall prevention interventions for this population. Further investigation of the role that perceived control over falls plays in this population is warranted. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

PubMed Central

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541

Combining the Generic Entity-Attribute-Value Model and Terminological Models into a Common Ontology to Enable Data Integration and Decision Support.

PubMed

Bouaud, Jacques; Guézennec, Gilles; Séroussi, Brigitte

2018-01-01

The integration of clinical information models and termino-ontological models into a unique ontological framework is highly desirable for it facilitates data integration and management using the same formal mechanisms for both data concepts and information model components. This is particularly true for knowledge-based decision support tools that aim to take advantage of all facets of semantic web technologies in merging ontological reasoning, concept classification, and rule-based inferences. We present an ontology template that combines generic data model components with (parts of) existing termino-ontological resources. The approach is developed for the guideline-based decision support module on breast cancer management within the DESIREE European project. The approach is based on the entity attribute value model and could be extended to other domains.

A decision support system for delivering optimal quality peach and tomato

NASA Technical Reports Server (NTRS)

Thai, C. N.; Pease, J. N.; Shewfelt, R. L.

1990-01-01

Several studies have indicated that color and firmness are the two quality attributes most important to consumers in making purchasing decisions of fresh peaches and tomatoes. However, at present, retail produce managers do not have the proper information for handling fresh produce so it has the most appealing color and firmness when it reaches the consumer. This information should help them predict the consumer color and firmness perception and preference for produce from various storage conditions. Since 1987, for 'Redglobe' peach and 'Sunny' tomato, we have been generating information about their physical quality attributes (firmness and color) and their corresponding consumer sensory scores. This article reports on our current progress toward the goal of integrating such information into a model-based decision support system for retail level managers in handling fresh peaches and tomatoes.

Lateral orbitofrontal cortex links social impressions to political choices.

PubMed

Xia, Chenjie; Stolle, Dietlind; Gidengil, Elisabeth; Fellows, Lesley K

2015-06-03

Recent studies of political behavior suggest that voting decisions can be influenced substantially by "first-impression" social attributions based on physical appearance. Separate lines of research have implicated the orbitofrontal cortex (OFC) in the judgment of social traits on the one hand and economic decision-making on the other, making this region a plausible candidate for linking social attributions to voting decisions. Here, we asked whether OFC lesions in humans disrupted the ability to judge traits of political candidates or affected how these judgments influenced voting decisions. Seven patients with lateral OFC damage, 18 patients with frontal damage sparing the lateral OFC, and 53 matched healthy participants took part in a simulated election paradigm, in which they voted for real-life (but unknown) candidates based only on photographs of their faces. Consistent with previous work, attributions of "competence" and "attractiveness" based on candidate appearance predicted voting behavior in the healthy control group. Frontal damage did not affect substantially the ability to make competence or attractiveness judgments, but patients with damage to the lateral OFC differed from other groups in how they applied this information when voting. Only attractiveness ratings had any predictive power for voting choices after lateral OFC damage, whereas other frontal patients and healthy controls relied on information about both competence and attractiveness in making their choice. An intact lateral OFC may not be necessary for judgment of social traits based on physical appearance, but it seems to be crucial in applying this information in political decision-making. Copyright © 2015 the authors 0270-6474/15/358507-08$15.00/0.

Impact of Decision Criteria on Federal Aviation Administration Certification of Military Commercial Derivative Aircraft

DTIC Science & Technology

2012-03-01

Capt Low was a member of the Sigma Iota Epsilon professional management fraternity. He has performed as an on-equipment and off-equipment...FAA Certification, Military Commercial Derivative Aircraft, Multi-Attribute Decision Making 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

Adaptation of a Counseling Intervention to Address Multiple Cancer Risk Factors Among Overweight/Obese Latino Smokers

PubMed Central

Castro, Yessenia; Fernández, Maria E.; Strong, Larkin L.; Stewart, Diana W.; Krasny, Sarah; Robles, Eden Hernandez; Heredia, Natalia; Spears, Claire A.; Correa-Fernández, Virmarie; Eakin, Elizabeth; Resnicow, Ken; Basen-Engquist, Karen; Wetter, David W.

2015-01-01

More than 60% of cancer-related deaths in the United States are attributable to tobacco use, poor nutrition, and physical inactivity, and these risk factors tend to cluster together. Thus, strategies for cancer risk reduction would benefit from addressing multiple health risk behaviors. We adapted an evidence-based intervention grounded in social cognitive theory and principles of motivational interviewing originally developed for smoking cessation to also address physical activity and fruit/vegetable consumption among Latinos exhibiting multiple health risk behaviors. Literature reviews, focus groups, expert consultation, pretesting, and pilot testing were used to inform adaptation decisions. We identified common mechanisms underlying change in smoking, physical activity, and diet used as treatment targets; identified practical models of patient-centered cross-cultural service provision; and identified that family preferences and support as particularly strong concerns among the priority population. Adaptations made to the original intervention are described. The current study is a practical example of how an intervention can be adapted to maximize relevance and acceptability and also maintain the core elements of the original evidence-based intervention. The intervention has significant potential to influence cancer prevention efforts among Latinos in the United States and is being evaluated in a sample of 400 Latino overweight/obese smokers. PMID:25527143

Causal mediation analysis with multiple mediators in the presence of treatment noncompliance.

PubMed

Park, Soojin; Kürüm, Esra

2018-05-20

Randomized experiments are often complicated because of treatment noncompliance. This challenge prevents researchers from identifying the mediated portion of the intention-to-treated (ITT) effect, which is the effect of the assigned treatment that is attributed to a mediator. One solution suggests identifying the mediated ITT effect on the basis of the average causal mediation effect among compliers when there is a single mediator. However, considering the complex nature of the mediating mechanisms, it is natural to assume that there are multiple variables that mediate through the causal path. Motivated by an empirical analysis of a data set collected in a randomized interventional study, we develop a method to estimate the mediated portion of the ITT effect when both multiple dependent mediators and treatment noncompliance exist. This enables researchers to make an informed decision on how to strengthen the intervention effect by identifying relevant mediators despite treatment noncompliance. We propose a nonparametric estimation procedure and provide a sensitivity analysis for key assumptions. We conduct a Monte Carlo simulation study to assess the finite sample performance of the proposed approach. The proposed method is illustrated by an empirical analysis of JOBS II data, in which a job training intervention was used to prevent mental health deterioration among unemployed individuals. Copyright © 2018 John Wiley & Sons, Ltd.

Estimating the lifetime risk of cancer associated with multiple CT scans.

PubMed

Ivanov, V K; Kashcheev, V V; Chekin, S Yu; Menyaylo, A N; Pryakhin, E A; Tsyb, A F; Mettler, F A

2014-12-01

Multiple CT scans are often done on the same patient resulting in an increased risk of cancer. Prior publications have estimated risks on a population basis and often using an effective dose. Simply adding up the risks from single scans does not correctly account for the survival function. A methodology for estimating personal radiation risks attributed to multiple CT imaging using organ doses is presented in this article. The estimated magnitude of the attributable risk fraction for the possible development of radiation-induced cancer indicates the necessity for strong clinical justification when ordering multiple CT scans.

At Least I Tried: The Relationship between Regulatory Focus and Regret Following Action vs. Inaction

PubMed Central

Itzkin, Adi; Van Dijk, Dina; Azar, Ofer H.

2016-01-01

Regret is an unpleasant feeling that may arise following decisions that ended poorly, and may affect the decision-maker's well-being and future decision making. Some studies show that a decision to act leads to greater regret than a decision not to act when both resulted in failure, because the latter is usually the norm. In some cases, when the norm is to act, this pattern is reversed. We suggest that the decision maker's regulatory focus, affects regret after action or inaction. Specifically, promotion-focused individuals, who tend to be more proactive, view action as more normal than prevention-focused individuals, and therefore experience regulatory fit when an action decision is made. Hence, we hypothesized that promotion-focused individuals will feel less regret than prevention-focused individuals when a decision to act ended poorly. In addition, we hypothesized that a trigger for change implied in the situation, decreases the level of regret following action. We tested our hypotheses on a sample of 330 participants enrolled in an online survey. The participants received six decision scenarios, in which they were asked to evaluate the level of regret following action and inaction. Individual regulatory focus was measured by two different scales. Promotion-focused individuals attributed less regret than prevention-focused individuals to action decisions. Regret following inaction was not affected by regulatory focus. In addition, a trigger for change decreases regret following action. Orthodox people tend to attribute more regret than non-orthodox to a person who made an action decision. The results contribute to the literature by showing that not only the situation but also the decision maker's orientation affects the regret after action vs. inaction. PMID:27833581

Patient preferences for attributes of multiple sclerosis disease-modifying therapies: development and results of a ratings-based conjoint analysis.

PubMed

Wilson, Leslie S; Loucks, Aimee; Gipson, Gregory; Zhong, Lixian; Bui, Christine; Miller, Elizabeth; Owen, Mary; Pelletier, Daniel; Goodin, Douglas; Waubant, Emmanuelle; McCulloch, Charles E

2015-01-01

Timely individualized treatment is essential to improving relapsing-remitting multiple sclerosis (RRMS) patient health outcomes, yet little is known about how patients make treatment decisions. We sought to evaluate RRMS patient preferences for risks and benefits of treatment. Fifty patients with RRMS completed conjoint analysis surveys with 16 hypothetical disease-modifying therapy (DMT) medication profiles developed using a fractional factorial design. Medication profiles were assigned preference ratings from 0 (not acceptable) to 10 (most favorable). Medication attributes included a range of benefits, adverse effects, administration routes, and market durations. Analytical models used linear mixed-effects regression. Participants showed the highest preference for medication profiles that would improve their symptoms (β = 0.81-1.03, P < .001), not a proven DMT outcome. Preventing relapses, the main clinical trial outcome, was not associated with significant preferences (P = .35). Each year of preventing magnetic resonance imaging changes and disease symptom progression showed DMT preferences of 0.17 point (β = 0.17, P = .002) and 0.12 point (β = 0.12, P < .001), respectively. Daily oral administration was preferred over all parenteral routes (P < .001). A 1% increase in death or severe disability decreased relative DMT preference by 1.15 points (P < .001). Patient preference focused on symptoms and prevention of progression but not on relapse prevention, the proven drug outcome. Patients were willing to accept some level of serious risk for certain types and amounts of benefits, and they strongly preferred daily oral administration over all other options.

Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Marsh, Kevin; IJzerman, Maarten; Thokala, Praveen; Baltussen, Rob; Boysen, Meindert; Kaló, Zoltán; Lönngren, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Devlin, Nancy

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Difficult Decisions: A Qualitative Exploration of the Statistical Decision Making Process from the Perspectives of Psychology Students and Academics

PubMed Central

Allen, Peter J.; Dorozenko, Kate P.; Roberts, Lynne D.

2016-01-01

Quantitative research methods are essential to the development of professional competence in psychology. They are also an area of weakness for many students. In particular, students are known to struggle with the skill of selecting quantitative analytical strategies appropriate for common research questions, hypotheses and data types. To begin understanding this apparent deficit, we presented nine psychology undergraduates (who had all completed at least one quantitative methods course) with brief research vignettes, and asked them to explicate the process they would follow to identify an appropriate statistical technique for each. Thematic analysis revealed that all participants found this task challenging, and even those who had completed several research methods courses struggled to articulate how they would approach the vignettes on more than a very superficial and intuitive level. While some students recognized that there is a systematic decision making process that can be followed, none could describe it clearly or completely. We then presented the same vignettes to 10 psychology academics with particular expertise in conducting research and/or research methods instruction. Predictably, these “experts” were able to describe a far more systematic, comprehensive, flexible, and nuanced approach to statistical decision making, which begins early in the research process, and pays consideration to multiple contextual factors. They were sensitive to the challenges that students experience when making statistical decisions, which they attributed partially to how research methods and statistics are commonly taught. This sensitivity was reflected in their pedagogic practices. When asked to consider the format and features of an aid that could facilitate the statistical decision making process, both groups expressed a preference for an accessible, comprehensive and reputable resource that follows a basic decision tree logic. For the academics in particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an “answer.” Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities. PMID:26909064

Difficult Decisions: A Qualitative Exploration of the Statistical Decision Making Process from the Perspectives of Psychology Students and Academics.

PubMed

Allen, Peter J; Dorozenko, Kate P; Roberts, Lynne D

2016-01-01

Quantitative research methods are essential to the development of professional competence in psychology. They are also an area of weakness for many students. In particular, students are known to struggle with the skill of selecting quantitative analytical strategies appropriate for common research questions, hypotheses and data types. To begin understanding this apparent deficit, we presented nine psychology undergraduates (who had all completed at least one quantitative methods course) with brief research vignettes, and asked them to explicate the process they would follow to identify an appropriate statistical technique for each. Thematic analysis revealed that all participants found this task challenging, and even those who had completed several research methods courses struggled to articulate how they would approach the vignettes on more than a very superficial and intuitive level. While some students recognized that there is a systematic decision making process that can be followed, none could describe it clearly or completely. We then presented the same vignettes to 10 psychology academics with particular expertise in conducting research and/or research methods instruction. Predictably, these "experts" were able to describe a far more systematic, comprehensive, flexible, and nuanced approach to statistical decision making, which begins early in the research process, and pays consideration to multiple contextual factors. They were sensitive to the challenges that students experience when making statistical decisions, which they attributed partially to how research methods and statistics are commonly taught. This sensitivity was reflected in their pedagogic practices. When asked to consider the format and features of an aid that could facilitate the statistical decision making process, both groups expressed a preference for an accessible, comprehensive and reputable resource that follows a basic decision tree logic. For the academics in particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an "answer." Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities.

Attribute-based Decision Graphs: A framework for multiclass data classification.

PubMed

Bertini, João Roberto; Nicoletti, Maria do Carmo; Zhao, Liang

2017-01-01

Graph-based algorithms have been successfully applied in machine learning and data mining tasks. A simple but, widely used, approach to build graphs from vector-based data is to consider each data instance as a vertex and connecting pairs of it using a similarity measure. Although this abstraction presents some advantages, such as arbitrary shape representation of the original data, it is still tied to some drawbacks, for example, it is dependent on the choice of a pre-defined distance metric and is biased by the local information among data instances. Aiming at exploring alternative ways to build graphs from data, this paper proposes an algorithm for constructing a new type of graph, called Attribute-based Decision Graph-AbDG. Given a vector-based data set, an AbDG is built by partitioning each data attribute range into disjoint intervals and representing each interval as a vertex. The edges are then established between vertices from different attributes according to a pre-defined pattern. Classification is performed through a matching process among the attribute values of the new instance and AbDG. Moreover, AbDG provides an inner mechanism to handle missing attribute values, which contributes for expanding its applicability. Results of classification tasks have shown that AbDG is a competitive approach when compared to well-known multiclass algorithms. The main contribution of the proposed framework is the combination of the advantages of attribute-based and graph-based techniques to perform robust pattern matching data classification, while permitting the analysis the input data considering only a subset of its attributes. Copyright © 2016 Elsevier Ltd. All rights reserved.

A formulation of multidimensional growth models for the assessment and forecast of technology attributes

NASA Astrophysics Data System (ADS)

Danner, Travis W.

Developing technology systems requires all manner of investment---engineering talent, prototypes, test facilities, and more. Even for simple design problems the investment can be substantial; for complex technology systems, the development costs can be staggering. The profitability of a corporation in a technology-driven industry is crucially dependent on maximizing the effectiveness of research and development investment. Decision-makers charged with allocation of this investment are forced to choose between the further evolution of existing technologies and the pursuit of revolutionary technologies. At risk on the one hand is excessive investment in an evolutionary technology which has only limited availability for further improvement. On the other hand, the pursuit of a revolutionary technology may mean abandoning momentum and the potential for substantial evolutionary improvement resulting from the years of accumulated knowledge. The informed answer to this question, evolutionary or revolutionary, requires knowledge of the expected rate of improvement and the potential a technology offers for further improvement. This research is dedicated to formulating the assessment and forecasting tools necessary to acquire this knowledge. The same physical laws and principles that enable the development and improvement of specific technologies also limit the ultimate capability of those technologies. Researchers have long used this concept as the foundation for modeling technological advancement through extrapolation by analogy to biological growth models. These models are employed to depict technology development as it asymptotically approaches limits established by the fundamental principles on which the technological approach is based. This has proven an effective and accurate approach to modeling and forecasting simple single-attribute technologies. With increased system complexity and the introduction of multiple system objectives, however, the usefulness of this modeling technique begins to diminish. With the introduction of multiple objectives, researchers often abandon technology growth models for scoring models and technology frontiers. While both approaches possess advantages over current growth models for the assessment of multi-objective technologies, each lacks a necessary dimension for comprehensive technology assessment. By collapsing multiple system metrics into a single, non-intuitive technology measure, scoring models provide a succinct framework for multi-objective technology assessment and forecasting. Yet, with no consideration of physical limits, scoring models provide no insight as to the feasibility of a particular combination of system capabilities. They only indicate that a given combination of system capabilities yields a particular score. Conversely, technology frontiers are constructed with the distinct objective of providing insight into the feasibility of system capability combinations. Yet again, upper limits to overall system performance are ignored. Furthermore, the data required to forecast subsequent technology frontiers is often inhibitive. In an attempt to reincorporate the fundamental nature of technology advancement as bound by physical principles, researchers have sought to normalize multi-objective systems whereby the variability of a single system objective is eliminated as a result of changes in the remaining objectives. This drastically limits the applicability of the resulting technology model because it is only applicable for a single setting of all other system attributes. Attempts to maintain the interaction between the growth curves of each technical objective of a complex system have thus far been limited to qualitative and subjective consideration. This research proposes the formulation of multidimensional growth models as an approach to simulating the advancement of multi-objective technologies towards their upper limits. Multidimensional growth models were formulated by noticing and exploiting the correlation between technology growth models and technology frontiers. Both are frontiers in actuality. The technology growth curve is a frontier between capability levels of a single attribute and time, while a technology frontier is a frontier between the capability levels of two or more attributes. Multidimensional growth models are formulated by exploiting the mathematical significance of this correlation. The result is a model that can capture both the interaction between multiple system attributes and their expected rates of improvement over time. The fundamental nature of technology development is maintained, and interdependent growth curves are generated for each system metric with minimal data requirements. Being founded on the basic nature of technology advancement, relative to physical limits, the availability for further improvement can be determined for a single metric relative to other system measures of merit. A by-product of this modeling approach is a single n-dimensional technology frontier linking all n system attributes with time. This provides an environment capable of forecasting future system capability in the form of advancing technology frontiers. The ability of a multidimensional growth model to capture the expected improvement of a specific technological approach is dependent on accurately identifying the physical limitations to each pertinent attribute. This research investigates two potential approaches to identifying those physical limits, a physics-based approach and a regression-based approach. The regression-based approach has found limited acceptance among forecasters, although it does show potential for estimating upper limits with a specified degree of uncertainty. Forecasters have long favored physics-based approaches for establishing the upper limit to unidimensional growth models. The task of accurately identifying upper limits has become increasingly difficult with the extension of growth models into multiple dimensions. A lone researcher may be able to identify the physical limitation to a single attribute of a simple system; however, as system complexity and the number of attributes increases, the attention of researchers from multiple fields of study is required. Thus, limit identification is itself an area of research and development requiring some level of investment. Whether estimated by physics or regression-based approaches, predicted limits will always have some degree of uncertainty. This research takes the approach of quantifying the impact of that uncertainty on model forecasts rather than heavily endorsing a single technique to limit identification. In addition to formulating the multidimensional growth model, this research provides a systematic procedure for applying that model to specific technology architectures. Researchers and decision-makers are able to investigate the potential for additional improvement within that technology architecture and to estimate the expected cost of each incremental improvement relative to the cost of past improvements. In this manner, multidimensional growth models provide the necessary information to set reasonable program goals for the further evolution of a particular technological approach or to establish the need for revolutionary approaches in light of the constraining limits of conventional approaches.

A Systematic Design Method for Two-Variable Numeric Function Generators Using Multiple-Valued Decision Diagrams

DTIC Science & Technology

2010-08-01

R.K. Brayton , and A.L. Sangiovanni-Vincentelli, “Multi-valued decision diagrams: Theory and applications,” Multiple-Valued Logic: An International...S.N. Yanushkevich, D.M. Miller, V.P. Shmerko, and R.S. Stankovic, Decision Diagram Techniques for Micro- and Nanoelectronic De- sign, CRC Press, Taylor

Analysis of strength-of-preference measures in dichotomous choice models

Treesearch

Donald F. Dennis; Peter Newman; Robert Manning

2008-01-01

Choice models are becoming increasingly useful for soliciting and analyzing multiple objective decisions faced by recreation managers and others interested in decisions involving natural resources. Choice models are used to estimate relative values for multiple aspects of natural resource management, not individually but within the context of other relevant decision...

Elucidating the underlying components of food valuation in the human orbitofrontal cortex.

PubMed

Suzuki, Shinsuke; Cross, Logan; O'Doherty, John P

2017-12-01

The valuation of food is a fundamental component of our decision-making. Yet little is known about how value signals for food and other rewards are constructed by the brain. Using a food-based decision task in human participants, we found that subjective values can be predicted from beliefs about constituent nutritive attributes of food: protein, fat, carbohydrates and vitamin content. Multivariate analyses of functional MRI data demonstrated that, while food value is represented in patterns of neural activity in both medial and lateral parts of the orbitofrontal cortex (OFC), only the lateral OFC represents the elemental nutritive attributes. Effective connectivity analyses further indicate that information about the nutritive attributes represented in the lateral OFC is integrated within the medial OFC to compute an overall value. These findings provide a mechanistic account for the construction of food value from its constituent nutrients.

Determinant Product and Supplier Attributes in Domestic Markets for Hardwood Lumber

Treesearch

Robert J. Bush; Steven A. Sinclair; Philip A. Araman

1991-01-01

Product and supplier attributes that are critical in hardwood lumber purchase decisions (i.e., determinant) were investigated in four segments of the domestic market for hardwood lumber: millwork producers (Standard Industrial Classification (SIC) 2431), hardwood dimension and flooring producers (SIC 2426), wood household furniture producers (SIC 2511), and wood...

Attributes affecting campsite selection at two types of campgrounds in the Adirondack Park

Treesearch

Kye-Young Choi; Chad P. Dawson

2003-01-01

This study compared the important attributes affecting campers' decisions in selecting their preferred campsites at two different types of New York State Department of Environmental Conservation (NYSDEC) campgrounds in the Adirondack Park. Mail surveys were sent to campers using six NYSDEC campgrounds (three less-developed campgrounds and three more-developed...

A Structured Decision Approach for Integrating and Analyzing Community Perspectives in Re-Use Planning of Vacant Properties in Cleveland, Ohio

EPA Science Inventory

An integrated GIS-based, multi-attribute decision model deployed in a web-based platform is presented enabling an iterative, spatially explicit and collaborative analysis of relevant and available information for repurposing vacant land. The process incorporated traditional and ...

Counseling Students' Decision Making Regarding Teaching Effectiveness: A Conjoint Analysis

ERIC Educational Resources Information Center

Pietrzak, Dale; Duncan, Kelly; Korcuska, James S.

2008-01-01

The authors examined the relative importance of 4 attributes of decision making for student evaluation of teaching effectiveness: perceived knowledge base of the professor, professor's delivery style, course organization, and course workload. Participants were 234 counseling graduate students from 6 midwestern universities in the United States.…

Did College Choice Change during the Seventies?

ERIC Educational Resources Information Center

Jackson, Gregory A.

1988-01-01

Despite steady enrollment growth and external shocks to U.S. higher education system, high school graduates' college-going decisions in 1980, as much as in 1972, depended on their social, academic, and financial attributes. Analyses of two national longitudinal surveys underlie this finding, implying traditional students' college decisions are…

The Role of Epistemic Motivation in Individuals' Response to Decision Complexity

ERIC Educational Resources Information Center

Amit, Adi; Sagiv, Lilach

2013-01-01

Integrating findings on the effects of more alternatives with findings on the effects of more attributes, we offer a motivational decision-making model, suggesting that epistemic motivation moderates individuals' responses to complex information. Study 1 empirically investigated the shared essence of four conceptualizations of epistemic…

When does reading dirty words impede picture processing? Taboo interference with verbal and manual responses.

PubMed

Mädebach, Andreas; Markuske, Anna-Maria; Jescheniak, Jörg D

2018-05-22

Picture naming takes longer in the presence of socially inappropriate (taboo) distractor words compared with neutral distractor words. Previous studies have attributed this taboo interference effect to increased attentional capture by taboo words or verbal self-monitoring-that is, control processes scrutinizing verbal responses before articulation. In this study, we investigated the cause and locus of the taboo interference effect by contrasting three tasks that used the same target pictures, but systematically differed with respect to the processing stages involved: picture naming (requiring conceptual processing, lexical processing, and articulation), phoneme decision (requiring conceptual and lexical processing), and natural size decision (requiring conceptual processing only). We observed taboo interference in picture naming and phoneme decision. In size decision, taboo interference was not reliably observed under the same task conditions in which the effect arose in picture naming and phoneme decision, but it emerged when the difficulty of the size decision task was increased by visually degrading the target pictures. Overall, these results suggest that taboo interference cannot be exclusively attributed to verbal self-monitoring operating over articulatory responses. Instead, taboo interference appears to arise already prior to articulatory preparation, during lexical processing and-at least with sufficiently high task difficulty-during prelexical processing stages.

Representing causal knowledge in environmental policy interventions: Advantages and opportunities for qualitative influence diagram applications.

PubMed

Carriger, John F; Dyson, Brian E; Benson, William H

2018-05-01

This article develops and explores a methodology for using qualitative influence diagrams in environmental policy and management to support decision-making efforts that minimize risk and increase resiliency. Influence diagrams are representations of the conditional aspects of a problem domain. Their graphical properties are useful for structuring causal knowledge relevant to policy interventions and can be used to enhance inference and inclusivity of multiple viewpoints. Qualitative components of influence diagrams are beneficial tools for identifying and examining the interactions among the critical variables in complex policy development and implementation. Policy interventions on social-environmental systems can be intuitively diagrammed for representing knowledge of critical relationships among economic, environmental, and social attributes. Examples relevant to coastal resiliency issues in the US Gulf Coast region are developed to illustrate model structures for developing qualitative influence diagrams useful for clarifying important policy intervention issues and enhancing transparency in decision making. Integr Environ Assess Manag 2018;14:381-394. Published 2018. This article is a US Government work and is in the public domain in the USA. Published 2018. This article is a US Government work and is in the public domain in the USA.

Age-related differences in reliance behavior attributable to costs within a human-decision aid system.

PubMed

Ezer, Neta; Fisk, Arthur D; Rogers, Wendy A

2008-12-01

An empirical investigation was done to determine if there are age-related differences attributable to costs in reliance on a decision aid. Costs of reliance on a decision aid may affect reliance on the aid. Older and younger adults may not perceive and respond to a dynamic cost structure equally or objectively. Sixteen older adults (65-74 years) and 16 younger adults (18-28 years) performed a counting task with an imperfect decision aid. Two types of costs were manipulated: (a) cost of error (CoE) and (b) cost of verification (CoV). The percentage of trials in which participants agreed with the decision aid and did not perform the task manually was recorded as reliance. Participants decreased their reliance as the CoE increased and increased their reliance with a lower CoV; however, they tended to underrely on the decision aid. Younger adults tended to change their reliance behavior more than older adults did with the changing cost structure. Older and younger adults appear to interpret costs differently, with older adults being less responsive to changes in costs. Older adults may have been less able to monitor the changing costs and hence not adapt to them as well as younger adults. Designers of decision aids should consider explicitly stating costs associated with reliance on the aid, as individuals may differ in how they interpret and respond to changing costs.

Silence That Can Be Dangerous: A Vignette Study to Assess Healthcare Professionals’ Likelihood of Speaking up about Safety Concerns

PubMed Central

Schwappach, David L. B.; Gehring, Katrin

2014-01-01

Purpose To investigate the likelihood of speaking up about patient safety in oncology and to clarify the effect of clinical and situational context factors on the likelihood of voicing concerns. Patients and Methods 1013 nurses and doctors in oncology rated four clinical vignettes describing coworkers’ errors and rule violations in a self-administered factorial survey (65% response rate). Multiple regression analysis was used to model the likelihood of speaking up as outcome of vignette attributes, responder’s evaluations of the situation and personal characteristics. Results Respondents reported a high likelihood of speaking up about patient safety but the variation between and within types of errors and rule violations was substantial. Staff without managerial function provided significantly higher levels of decision difficulty and discomfort to speak up. Based on the information presented in the vignettes, 74%−96% would speak up towards a supervisor failing to check a prescription, 45%−81% would point a coworker to a missed hand disinfection, 82%−94% would speak up towards nurses who violate a safety rule in medication preparation, and 59%−92% would question a doctor violating a safety rule in lumbar puncture. Several vignette attributes predicted the likelihood of speaking up. Perceived potential harm, anticipated discomfort, and decision difficulty were significant predictors of the likelihood of speaking up. Conclusions Clinicians’ willingness to speak up about patient safety is considerably affected by contextual factors. Physicians and nurses without managerial function report substantial discomfort with speaking up. Oncology departments should provide staff with clear guidance and trainings on when and how to voice safety concerns. PMID:25116338

Marine spatial planning in practice

NASA Astrophysics Data System (ADS)

Collie, Jeremy S.; (Vic) Adamowicz, W. L.; Beck, Michael W.; Craig, Bethany; Essington, Timothy E.; Fluharty, David; Rice, Jake; Sanchirico, James N.

2013-01-01

Multiple competing uses of continental-shelf environments have led to a proliferation of marine spatial planning initiatives, together with expert guidance on marine spatial planning. This study provides an empirical review of marine spatial plans, their attributes, and the extent to which the expert guidance is actually being followed. We performed a structured review of 16 existing marine spatial plans and created an idealized marine spatial plan from the steps included in recent expert papers. A cluster analysis of the yes/no answers to 28 questions was used to ordinate the 16 marine spatial plans and to compare them with the idealized plan. All the plans that have been implemented have a high-level government mandate and the authority to implement spatial planning vested in existing institutions. Almost all the plans used data with clear criteria for data inclusion. Stakeholders were included in almost all the plans; they did not participate in all stages of the planning process but their roles were generally clearly defined. Decision-support tools were applied inconsistently across plans and were seldom used dynamically over time. Most spatial planning processes did not select specific outcomes, such as preferred use scenarios. Success is defined inconsistently across plans; in half the cases there are no metrics of success with reference benchmarks. Although monitoring is included in the majority of plans, only in some cases do monitoring results feed back into management decisions. The process of marine spatial planning had advanced in that some of the more recent plans were developed more quickly and contain more desirable attributes than earlier plans. Even so, existing marine spatial plans are heterogeneous—there are essential ingredients, but no single recipe for success.

Informed decision-making in elective major vascular surgery: analysis of 145 surgeon-patient consultations.

PubMed

Etchells, Edward; Ferrari, Michel; Kiss, Alex; Martyn, Nikki; Zinman, Deborah; Levinson, Wendy

2011-06-01

Prior studies show significant gaps in the informed decision-making process, a central goal of surgical care. These studies have been limited by their focus on low-risk decisions, single visits rather than entire consultations, or both. Our objectives were, first, to rate informed decision-making for major elective vascular surgery based on audiotapes of actual physician-patient conversations and, second, to compare ratings of informed decision-making for first visits to ratings for multiple visits by the same patient over time. We prospectively enrolled patients for whom vascular surgical treatment was a potential option at a tertiary care outpatient vascular surgery clinic. We audio-taped all surgeon-patient conversations, including multiple visits when necessary, until a decision was made. Using an existing method, we evaluated the transcripts for elements of decision-making, including basic elements (e.g., an explanation of the clinical condition), intermediate elements (e.g., risks and benefits) and complex elements (e.g., uncertainty around the decision). We analyzed 145 surgeon-patient consultations. Overall, 45% of consultations contained complex elements, whereas 23% did not contain the basic elements of decision-making. For the 67 consultations that involved multiple visits, ratings were significantly higher when evaluating all visits (50% complex elements) compared with evaluating only the first visit (33% complex elements, p < 0.001.) We found that 45% of consultations contained complex elements, which is higher than prior studies with similar methods. Analyzing decision-making over multiple visits yielded different results than analyzing decision-making for single visits.

26 CFR 1.1248-8 - Earnings and profits attributable to stock following certain non-recognition transactions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... of this section. (5) Reduction in earnings and profits attributable to stock to prevent multiple... reduce the CFC3 earnings and profits attributable to its CFC2 stock by $9. These reductions occur without... 26 Internal Revenue 11 2011-04-01 2011-04-01 false Earnings and profits attributable to stock...

Innovation Attributes and Adoption Decisions: Perspectives from Leaders of a National Sample of Addiction Treatment Organizations

PubMed Central

Knudsen, Hannah K.; Roman, Paul M

2014-01-01

Drawing on diffusion theory to further knowledge about evidence-based practices (EBPs) in the treatment of substance use disorders (SUDs), this study describes the perceived importance of innovation attributes in adoption decisions within a national sample of SUD treatment organizations. Face-to-face interviews were conducted with leaders of 307 organizations. A typology differentiated organizations reporting: (1) adoption of a treatment innovation in the past year (“recent adoption”), (2) plans to adopt an innovation in the upcoming year (“planned adoption”), or (3) no actual or planned adoption (“non-adoption”). About 30.7% of organizations reported recent adoption, 20.5% indicated planned adoption, and 48.8% were non-adopters. Leaders of organizations reporting recent adoption (n = 93) or planned adoption (n = 62) rated the importance of innovation attributes, including relative advantage, compatibility, complexity, and observability, on these adoption decisions using a Likert scale that ranged from 0 to 5. Innovation attributes most strongly endorsed were consistency with the program's treatment philosophy (mean = 4.47, SD = 1.03), improvement in the program's reputation with referral sources (mean = 4.00, SD = 1.33), reputational improvement with clients and their families (mean = 3.98, SD = 1.31), and reductions in treatment dropout (mean = 3.75, SD = 1.54). Innovation characteristics reflecting organizational growth and implementation costs were less strongly endorsed. Adopters and planners were generally similar in their importance ratings. There were modest differences in importance ratings when pharmacological innovations were compared to psychosocial interventions. These findings are consistent with diffusion theory and suggest that efforts to link EBPs with client satisfaction and potential reputational benefits may enhance the diffusion of EBPs. Attention to these attributes when developing and evaluating SUD treatment interventions may enhance efforts to increase subsequent adoption. PMID:25218918

Innovation attributes and adoption decisions: perspectives from leaders of a national sample of addiction treatment organizations.

PubMed

Knudsen, Hannah K; Roman, Paul M

2015-02-01

Drawing on diffusion theory to further knowledge about evidence-based practices (EBPs) in the treatment of substance use disorders (SUDs), this study describes the perceived importance of innovation attributes in adoption decisions within a national sample of SUD treatment organizations. Face-to-face interviews were conducted with leaders of 307 organizations. A typology differentiated organizations reporting: (1) adoption of a treatment innovation in the past year ("recent adoption"), (2) plans to adopt an innovation in the upcoming year ("planned adoption"), or (3) no actual or planned adoption ("non-adoption"). About 30.7% of organizations reported recent adoption, 20.5% indicated planned adoption, and 48.8% were non-adopters. Leaders of organizations reporting recent adoption (n=93) or planned adoption (n=62) rated the importance of innovation attributes, including relative advantage, compatibility, complexity, and observability, on these adoption decisions using a Likert scale that ranged from 0 to 5. Innovation attributes most strongly endorsed were consistency with the program's treatment philosophy (mean=4.47, SD=1.03), improvement in the program's reputation with referral sources (mean=4.00, SD=1.33), reputational improvement with clients and their families (mean=3.98, SD=1.31), and reductions in treatment dropout (mean=3.75, SD=1.54). Innovation characteristics reflecting organizational growth and implementation costs were less strongly endorsed. Adopters and planners were generally similar in their importance ratings. There were modest differences in importance ratings when pharmacological innovations were compared to psychosocial interventions. These findings are consistent with diffusion theory and suggest that efforts to link EBPs with client satisfaction and potential reputational benefits may enhance the diffusion of EBPs. Attention to these attributes when developing and evaluating SUD treatment interventions may enhance efforts to increase subsequent adoption. Copyright © 2015 Elsevier Inc. All rights reserved.

A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke.

PubMed

De Brún, Aoife; Flynn, Darren; Ternent, Laura; Price, Christopher I; Rodgers, Helen; Ford, Gary A; Rudd, Matthew; Lancsar, Emily; Simpson, Stephen; Teah, John; Thomson, Richard G

2018-06-22

A discrete choice experiment (DCE) is a method used to elicit participants' preferences and the relative importance of different attributes and levels within a decision-making process. DCEs have become popular in healthcare; however, approaches to identify the attributes/levels influencing a decision of interest and to selection methods for their inclusion in a DCE are under-reported. Our objectives were: to explore the development process used to select/present attributes/levels from the identified range that may be influential; to describe a systematic and rigorous development process for design of a DCE in the context of thrombolytic therapy for acute stroke; and, to discuss the advantages of our five-stage approach to enhance current guidance for developing DCEs. A five-stage DCE development process was undertaken. Methods employed included literature review, qualitative analysis of interview and ethnographic data, expert panel discussions, a quantitative structured prioritisation (ranking) exercise and pilot testing of the DCE using a 'think aloud' approach. The five-stage process reported helped to reduce the list of 22 initial patient-related factors to a final set of nine variable factors and six fixed factors for inclusion in a testable DCE using a vignette model of presentation. In order for the data and conclusions generated by DCEs to be deemed valid, it is crucial that the methods of design and development are documented and reported. This paper has detailed a rigorous and systematic approach to DCE development which may be useful to researchers seeking to establish methods for reducing and prioritising attributes for inclusion in future DCEs.

Predicting Social and Communicative Ability in School-Age Children with Autism Spectrum Disorder: A Pilot Study of the Social Attribution Task, Multiple Choice

ERIC Educational Resources Information Center

Burger-Caplan, Rebecca; Saulnier, Celine; Jones, Warren; Klin, Ami

2016-01-01

The Social Attribution Task, Multiple Choice is introduced as a measure of implicit social cognitive ability in children, addressing a key challenge in quantification of social cognitive function in autism spectrum disorder, whereby individuals can often be successful in explicit social scenarios, despite marked social adaptive deficits. The…

Stochastic nature of Landsat MSS data

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J.

1987-01-01

A multiple series generalization of the ARIMA models is used to model Landsat MSS scan lines as sequences of vectors, each vector having four elements (bands). The purpose of this work is to investigate if Landsat scan lines can be described by a general multiple series linear stochastic model and if the coefficients of such a model vary as a function of satellite system and target attributes. To accomplish this objective, an exploratory experimental design was set up incorporating six factors, four representing target attributes - location, cloud cover, row (within location), and column (within location) - and two factors representing system attributes - satellite number and detector bank. Each factor was included in the design at two levels and, with two replicates per treatment, 128 scan lines were analyzed. The results of the analysis suggests that a multiple AR(4) model is an adequate representation across all scan lines. Furthermore, the coefficients of the AR(4) model vary with location, particularly changes in physiography (slope regimes), and with percent cloud cover, but are insensitive to changes in system attributes.

Decision-making Strategies and Performance among Seniors1

PubMed Central

Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

2011-01-01

Using paper and pencil experiments administered in senior centers, we examine decision-making performance in multi-attribute decision problems. We differentiate the effects of declining cognitive performance and changing cognitive process on decision-making performance of seniors as they age. We find a significant decline in performance with age due to reduced reliance on common heuristics and increased decision-making randomness among our oldest subjects. However, we find that increasing the number of options in a decision problem increases the number of heuristics brought to the task. This challenges the choice overload view that people give up when confronted with too much choice. PMID:22408282

Perceptual grouping does not affect multi-attribute decision making if no processing costs are involved.

PubMed

Ettlin, Florence; Bröder, Arndt

2015-05-01

Adaptive strategy selection implies that a decision strategy is chosen based on its fit to the task and situation. However, other aspects, such as the way information is presented, can determine information search behavior; especially when the application of certain strategies over others is facilitated. But are such display effects on multi-attribute decisions also at work when the manipulation does not entail differential costs for different decision strategies? Three Mouselab experiments with hidden information and one eye tracking experiment with an open information board revealed that decision behavior is unaffected by purely perceptual manipulations of the display based on Gestalt principles; that is, based on manipulations that induce no noteworthy processing costs for different information search patterns. We discuss our results in the context of previous findings on display effects; specifically, how the combination of these findings and our results reveal the crucial role of differential processing costs for different strategies for the emergence of display effects. This finding describes a boundary condition of the commonly acknowledged influence of information displays and is in line with the ideas of adaptive strategy selection and cost-benefit tradeoffs. Copyright © 2015. Published by Elsevier B.V.

History matching through dynamic decision-making

PubMed Central

Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson

2017-01-01

History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413

Dissociation of emotional decision-making from cognitive decision-making in chronic schizophrenia.

PubMed

Lee, Yanghyun; Kim, Yang-Tae; Seo, Eugene; Park, Oaktae; Jeong, Sung-Hun; Kim, Sang Heon; Lee, Seung-Jae

2007-08-30

Recent studies have examined the decision-making ability of schizophrenic patients using the Iowa Gambling Task (IGT). These studies, however, were restricted to the assessment of emotional decision-making. Decision-making depends on cognitive functions as well as on emotion. The purpose of this study was to examine the performance of schizophrenic patients on the IGT and the Game of Dice Task (GDT), a decision-making task with explicit rules for gains and losses. In addition, it was intended to test whether poor performance on IGT is attributable to impairments in reversal learning within the schizophrenia group using the Simple Reversal Learning Task (SRLT), which is sensitive to measure the deficit of reversal learning following ventromedial prefrontal cortex damage. A group of 23 stable schizophrenic patients and 28 control subjects performed computerized versions of the IGT, GDT, SRLT and Wisconsin Card Sorting Test (WCST). While schizophrenic patients performed poorly on the IGT relative to normal controls, there was no significant difference between the two groups on GDT performance. The performance of the schizophrenia group on the SRLT was poorer than that of controls, but was not related to IGT performance. These data suggest that schizophrenic patients have impaired emotional decision-making but intact cognitive decision-making, suggesting that these two processes of decision-making are different. Furthermore, the impairments in reversal learning did not contribute to poor performance on the IGT in schizophrenia. Therefore, schizophrenic patients have difficulty in making decisions under ambiguous and uncertain situations whereas they make choices easily in clear and unequivocal ones. The emotional decision-making deficits in schizophrenia might be attributable more to another mechanism such as a somatic marker hypothesis than to an impairment in reversal learning.

A common perceptual temporal limit of binding synchronous inputs across different sensory attributes and modalities.

PubMed

Fujisaki, Waka; Nishida, Shin'ya

2010-08-07

The human brain processes different aspects of the surrounding environment through multiple sensory modalities, and each modality can be subdivided into multiple attribute-specific channels. When the brain rebinds sensory content information ('what') across different channels, temporal coincidence ('when') along with spatial coincidence ('where') provides a critical clue. It however remains unknown whether neural mechanisms for binding synchronous attributes are specific to each attribute combination, or universal and central. In human psychophysical experiments, we examined how combinations of visual, auditory and tactile attributes affect the temporal frequency limit of synchrony-based binding. The results indicated that the upper limits of cross-attribute binding were lower than those of within-attribute binding, and surprisingly similar for any combination of visual, auditory and tactile attributes (2-3 Hz). They are unlikely to be the limits for judging synchrony, since the temporal limit of a cross-attribute synchrony judgement was higher and varied with the modality combination (4-9 Hz). These findings suggest that cross-attribute temporal binding is mediated by a slow central process that combines separately processed 'what' and 'when' properties of a single event. While the synchrony performance reflects temporal bottlenecks existing in 'when' processing, the binding performance reflects the central temporal limit of integrating 'when' and 'what' properties.

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education

PubMed Central

PHELPS, CHARLES; RAPPUOLI, RINO; LEVIN, SCOTT; SHORTLIFFE, EDWARD; COLWELL, RITA

2016-01-01

Policy Points: Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning.Public health agencies’ current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost‐effectiveness.As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost‐effectiveness analyses widely recommended and used for public health planning.Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Context Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost‐effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Methods Our work employed a multicriteria systems analysis approach—specifically, multiattribute utility theory—to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost‐effectiveness analysis approach. Findings (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost‐effectiveness analysis. (2) More sophisticated systems‐level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. Conclusions The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost‐effectiveness analysis. The Strategic Multi‐Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. PMID:26994711

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education.

PubMed

Phelps, Charles; Madhavan, Guruprasad; Rappuoli, Rino; Levin, Scott; Shortliffe, Edward; Colwell, Rita

2016-03-01

Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost-effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Our work employed a multicriteria systems analysis approach--specifically, multiattribute utility theory--to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost-effectiveness analysis approach. (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost-effectiveness analysis. (2) More sophisticated systems-level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost-effectiveness analysis. The Strategic Multi-Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. © 2016 Milbank Memorial Fund.

Tailoring Software for Multiple Processor Systems

DTIC Science & Technology

1982-10-01

resource management decisions . Despite the lack of programming support, the use of multiple processor systems has grown sub- -stantially. Software has...making resource management decisions . Specifically, program- 1 mers need not allocate specific hardware resources to individual program components...Instead, such allocation decisions are automatically made based on high-level resource directives stated by ap- plication programmers, where each directive

Probabilistic confidence for decisions based on uncertain reliability estimates

NASA Astrophysics Data System (ADS)

Reid, Stuart G.

2013-05-01

Reliability assessments are commonly carried out to provide a rational basis for risk-informed decisions concerning the design or maintenance of engineering systems and structures. However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities. For uncertain probabilities of failure, a measure of 'probabilistic confidence' has been proposed to reflect the concern that uncertainty about the true probability of failure could result in a system or structure that is unsafe and could subsequently fail. The paper describes how the concept of probabilistic confidence can be applied to evaluate and appropriately limit the probabilities of failure attributable to particular uncertainties such as design errors that may critically affect the dependability of risk-acceptance decisions. This approach is illustrated with regard to the dependability of structural design processes based on prototype testing with uncertainties attributable to sampling variability.

Application of the fuzzy topsis multi-attribute decision making method to determine scholarship recipients

NASA Astrophysics Data System (ADS)

Irvanizam, I.

2018-03-01

Some scholarships have been routinely offered by Ministry of Research, Technology and Higher Education of the Republic of Indonesia for students at Syiah Kuala University. In reality, the scholarship selection process is becoming subjective and highly complex problem. Multi-Attribute Decision Making (MADM) techniques can be a solution in order to solve scholarship selection problem. In this study, we demonstrated the application of a fuzzy TOPSIS as an MADM technique by using a numerical example in order to calculate a triangular fuzzy number for the fuzzy data onto a normalized weight. We then use this normalized value to construct the normalized fuzzy decision matrix. We finally use the fuzzy TOPSIS to rank alternatives in descending order based on the relative closeness to the ideal solution. The result in terms of final ranking shows slightly different from the previous work.

How consumers are affected by product descriptions in online shopping: Event-related potentials evidence of the attribute framing effect.

PubMed

Jin, Jia; Zhang, Wuke; Chen, Mingliang

2017-12-01

Due to the limitations of the human ability to process information, e-consumers' decisions are likely to be influenced by various cognitive biases, such as the attribute framing effect. This effect has been well studied by numerous scholars; however, the associated underlying neural mechanisms with a critical temporal resolution have not been revealed. Thus, this study applies the measurement of event-related potentials (ERPs) to directly examine the role of attribute framing in information processing and decision-making in online shopping. The behavioral results showed that participants demonstrated a higher purchase intention with a shorter reaction time under a positive framing condition compared to participants under a negative framing condition. Compared with positive framing messages, the results of ERPs indicated that negative framing messages attracted more attention resources at the early stage of rapid automatic processing (larger P2 amplitude) and resulted in greater cognitive conflict and decision difficulty (larger P2-N2 complex). Moreover, compared with negative messages, positive framing messages allowed consumers to perceive a better future performance of products and classify these products as a categorization of higher evaluation (larger LPP amplitude) at the late cognitive processing stage of evaluation. Based on these results, we provide evidence for a better understanding of how different attribute framing messages are processed and ultimately lead to the framing effect. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

A Decision Support System for Solving Multiple Criteria Optimization Problems

ERIC Educational Resources Information Center

Filatovas, Ernestas; Kurasova, Olga

2011-01-01

In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria…

The multiple resource inventory decision-making process

Treesearch

Victor A. Rudis

1993-01-01

A model of the multiple resource inventory decision-making process is presented that identifies steps in conducting inventories, describes the infrastructure, and points out knowledge gaps that are common to many interdisciplinary studies.Successful efforts to date suggest the need to bridge the gaps by sharing elements, maintain dialogue among stakeholders in multiple...

Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning

NASA Technical Reports Server (NTRS)

Fayyad, U.; Irani, K.

1993-01-01

Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuous-valued attribute into multiple intervals.

A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes

NASA Astrophysics Data System (ADS)

Lu, Hongwei; Ren, Lixia; Chen, Yizhong; Tian, Peipei; Liu, Jia

2017-12-01

Due to the uncertainty (i.e., fuzziness, stochasticity and imprecision) existed simultaneously during the process for groundwater remediation, the accuracy of ranking results obtained by the traditional methods has been limited. This paper proposes a cloud model based multi-attribute decision making framework (CM-MADM) with Monte Carlo for the contaminated-groundwater remediation strategies selection. The cloud model is used to handle imprecise numerical quantities, which can describe the fuzziness and stochasticity of the information fully and precisely. In the proposed approach, the contaminated concentrations are aggregated via the backward cloud generator and the weights of attributes are calculated by employing the weight cloud module. A case study on the remedial alternative selection for a contaminated site suffering from a 1,1,1-trichloroethylene leakage problem in Shanghai, China is conducted to illustrate the efficiency and applicability of the developed approach. Totally, an attribute system which consists of ten attributes were used for evaluating each alternative through the developed method under uncertainty, including daily total pumping rate, total cost and cloud model based health risk. Results indicated that A14 was evaluated to be the most preferred alternative for the 5-year, A5 for the 10-year, A4 for the 15-year and A6 for the 20-year remediation.

Collaborative Response and Recovery from a Foot-and-Mouth Disease Animal Health Emergency: Supporting Decision Making in a Complex Environment with Multiple Stakeholders

DTIC Science & Technology

2013-12-01

RESPONSE AND RECOVERY FROM A FOOT-AND- MOUTH DISEASE ANIMAL HEALTH EMERGENCY: SUPPORTING DECISION MAKING IN A COMPLEX ENVIRONMENT WITH MULTIPLE...Thesis 4. TITLE AND SUBTITLE COLLABORATIVE RESPONSE AND RECOVERY FROM A FOOT-AND- MOUTH DISEASE ANIMAL HEALTH EMERGENCY: SUPPORTING DECISION MAKING...200 words ) This thesis recommends ways to support decision makers who must operate within the multi-stakeholder complex situation of response and

Parental Health Attributions of Childhood Health and Illness: Development of the Pediatric Cultural Health Attributions Questionnaire (Pedi-CHAQ).

PubMed

Vaughn, Lisa M; McLinden, Daniel J; Shellmer, Diana; Baker, Raymond C

2011-01-01

The causes attributed to childhood health and illness across cultures (cultural health attributions) are key factors that are now more frequently identified as affecting the health outcomes of children. Research suggests that the causes attributed to an event such as illness are thought to affect subsequent motivation, emotional response, decision making, and behavior. To date, there is no measure of health attributions appropriate for use with parents of pediatric patients. Using the Many-Facets approach to Rasch analysis, this study assesses the psychometrics of a newly developed instrument, the Pediatric Health Attributions Questionnaire (Pedi-CHAQ), a measure designed to assess the cultural health attributions of parents in diverse communities. Results suggest acceptable Rasch model statistics of fit and reliability for the Pedi-CHAQ. A shortened version of the questionnaire was developed as a result of this study and next steps are discussed.

Fear of cancer recurrence and psychological well-being in women with breast cancer: The role of causal cancer attributions and optimism.

PubMed

Dumalaon-Canaria, J A; Prichard, I; Hutchinson, A D; Wilson, C

2018-01-01

This study aims to examine the association between cancer causal attributions, fear of cancer recurrence (FCR) and psychological well-being and the possible moderating effect of optimism among women with a previous diagnosis of breast cancer. Participants (N = 314) completed an online self-report assessment of causal attributions for their own breast cancer, FCR, psychological well-being and optimism. Simultaneous multiple regression analyses were conducted to explore the overall contribution of causal attributions to FCR and psychological well-being separately. Hierarchical multiple regression analyses were also utilised to examine the potential moderating influence of dispositional optimism on the relationship between causal attributions and FCR and psychological well-being. Causal attributions of environmental exposures, family history and stress were significantly associated with higher FCR. The attribution of stress was also significantly associated with lower psychological well-being. Optimism did not moderate the relationship between causal attributions and FCR or well-being. The observed relationships between causal attributions for breast cancer and FCR and psychological well-being suggest that the inclusion of causal attributions in screening for FCR is potentially important. Health professionals may need to provide greater psychological support to women who attribute their cancer to non-modifiable causes and consequently continue to experience distress. © 2016 John Wiley & Sons Ltd.

MULTIPLE SCALES FOR SUSTAINABLE RESULTS

EPA Science Inventory

This session will highlight recent research that incorporates the use of multiple scales and innovative environmental accounting to better inform decisions that affect sustainability, resilience, and vulnerability at all scales. Effective decision-making involves assessment at mu...

Dietary self-control is related to the speed with which health and taste attributes are processed

PubMed Central

Sullivan, Nicolette; Hutcherson, Cendri; Harris, Alison; Rangel, Antonio

2015-01-01

We propose that self-control failures, and variation across individuals in self-control abilities, are partly due to differences in the speed with which the decision-making circuitry processes basic attributes like taste, versus more abstract attributes such as health. We test these hypotheses by combining a dietary choice task with a novel form of mouse tracking that allows us to pinpoint when different attributes are being integrated into the choice process with millisecond temporal resolution. We find that, on average, taste attributes are processed about 195 ms earlier than health attributes during the choice process. We also find that 13 - 39% of observed individual differences in self-control ability can be explained by differences in the relative speed with which taste and health attributes are processed. PMID:25515527

What vaccine product attributes do immunization program stakeholders value? Results from interviews in six low- and middle-income countries.

PubMed

Kristensen, Debra D; Bartholomew, Kate; Villadiego, Shirley; Lorenson, Kristina

2016-12-07

This study attempts to capture the opinions of stakeholders working in immunization programs in low- and middle-income countries to understand how vaccine products could be improved to better meet their needs and to obtain feedback on specific vaccine product attributes including the number of doses per container and ease of preparing a dose for administration. We also reviewed how procurement decisions are made within immunization programs. Semi-structured interviews were undertaken with 158 immunization stakeholders in Brazil, China, India, Peru, the Philippines, and Tanzania. Interviewees included national decision-makers and advisors involved in vaccine-purchasing decisions (n=30), national Expanded Programme on Immunization managers (n=6), and health and logistics personnel at national, subnational, and health-facility levels (n=122). Immunization stakeholders at all levels of the supply chain valued vaccine product attributes that prevent heat damage, decrease vaccine wastage, and simplify delivery. Minimizing the time required to prepare a dose is especially valued by those closest to the work of actually administering vaccines. Respondents appreciated the benefits of lower-multidose presentations on reducing wastage but seemed to prefer single-dose vials even more. They also expressed concern about the need for training and the potential for confusion and vial contamination if opened vials of liquid preservative-free vaccines are not handled properly. Procurement decision-making processes varied widely between countries, though most relied heavily on international agencies and vaccine manufacturers for information. Copyright © 2016. Published by Elsevier Ltd.

A Fuzzy Rule Based Decision Support System for Identifying Location of Water Harvesting Technologies in Rainfed Agricultural Regions

NASA Astrophysics Data System (ADS)

Chaubey, I.; Vema, V. K.; Sudheer, K.

2016-12-01

Site suitability evaluation of water conservation structures in water scarce rainfed agricultural areas consist of assessment of various landscape characteristics and various criterion. Many of these landscape characteristic attributes are conveyed through linguistic terms rather than precise numeric values. Fuzzy rule based system are capable of incorporating uncertainty and vagueness, when various decision making criteria expressed in linguistic terms are expressed as fuzzy rules. In this study a fuzzy rule based decision support system is developed, for optimal site selection of water harvesting technologies. Water conservation technologies like farm ponds, Check dams, Rock filled dams and percolation ponds aid in conserving water for irrigation and recharging aquifers and development of such a system will aid in improving the efficiency of the structures. Attributes and criteria involved in decision making are classified into different groups to estimate the suitability of the particular technology. The developed model is applied and tested on an Indian watershed. The input attributes are prepared in raster format in ArcGIS software and suitability of each raster cell is calculated and output is generated in the form of a thematic map showing the suitability of the cells pertaining to different technologies. The output of the developed model is compared against the already existing structures and results are satisfactory. This developed model will aid in improving the sustainability and efficiency of the watershed management programs aimed at enhancing in situ moisture content.

A Probabilistic, Dynamic, and Attribute-wise Model of Intertemporal Choice

PubMed Central

Dai, Junyi; Busemeyer, Jerome R.

2014-01-01

Most theoretical and empirical research on intertemporal choice assumes a deterministic and static perspective, leading to the widely adopted delay discounting models. As a form of preferential choice, however, intertemporal choice may be generated by a stochastic process that requires some deliberation time to reach a decision. We conducted three experiments to investigate how choice and decision time varied as a function of manipulations designed to examine the delay duration effect, the common difference effect, and the magnitude effect in intertemporal choice. The results, especially those associated with the delay duration effect, challenged the traditional deterministic and static view and called for alternative approaches. Consequently, various static or dynamic stochastic choice models were explored and fit to the choice data, including alternative-wise models derived from the traditional exponential or hyperbolic discount function and attribute-wise models built upon comparisons of direct or relative differences in money and delay. Furthermore, for the first time, dynamic diffusion models, such as those based on decision field theory, were also fit to the choice and response time data simultaneously. The results revealed that the attribute-wise diffusion model with direct differences, power transformations of objective value and time, and varied diffusion parameter performed the best and could account for all three intertemporal effects. In addition, the empirical relationship between choice proportions and response times was consistent with the prediction of diffusion models and thus favored a stochastic choice process for intertemporal choice that requires some deliberation time to make a decision. PMID:24635188

Model for multi-stand management based on structural attributes of individual stands

Treesearch

G.W. Miller; J. Sullivan

1997-01-01

A growing interest in managing forest ecosystems calls for decision models that take into account attribute goals for large forest areas while continuing to recognize the individual stand as a basic unit of forest management. A dynamic, nonlinear forest management model is described that schedules silvicultural treatments for individual stands that are linked by multi-...

Service Oriented Architecture Security Risks and their Mitigation

DTIC Science & Technology

2012-10-01

this section can be mitigated by making use of suitable authentication , confidentiality, integrity, and authorisation standards such as Security...for authorisation . Machines/non-human users should be clearly identified and authenticated by the identity provision and authentication services... authentication , any security related attributes for the subject, and the authorisation decisions given based on the security and privilege attributes

How consumers choose health insurance.

PubMed

Chakraborty, G; Ettenson, R; Gaeth, G

1994-01-01

The authors used choice-based conjoint analysis to model consumers' decision processes when evaluating and selecting health insurance in a multiplan environment. Results indicate that consumer choice is affected by as many as 19 attributes, some of which have received little attention in previous studies. Moreover, the importance of the attributes varies across different demographic segments, giving marketers several targeting opportunities.

Design of decision support interventions for medication prescribing.

PubMed

Horsky, Jan; Phansalkar, Shobha; Desai, Amrita; Bell, Douglas; Middleton, Blackford

2013-06-01

Describe optimal design attributes of clinical decision support (CDS) interventions for medication prescribing, emphasizing perceptual, cognitive and functional characteristics that improve human-computer interaction (HCI) and patient safety. Findings from published reports on success, failures and lessons learned during implementation of CDS systems were reviewed and interpreted with regard to HCI and software usability principles. We then formulated design recommendations for CDS alerts that would reduce unnecessary workflow interruptions and allow clinicians to make informed decisions quickly, accurately and without extraneous cognitive and interactive effort. Excessive alerting that tends to distract clinicians rather than provide effective CDS can be reduced by designing only high severity alerts as interruptive dialog boxes and less severe warnings without explicit response requirement, by curating system knowledge bases to suppress warnings with low clinical utility and by integrating contextual patient data into the decision logic. Recommended design principles include parsimonious and consistent use of color and language, minimalist approach to the layout of information and controls, the use of font attributes to convey hierarchy and visual prominence of important data over supporting information, the inclusion of relevant patient data in the context of the alert and allowing clinicians to respond with one or two clicks. Although HCI and usability principles are well established and robust, CDS and EHR system interfaces rarely conform to the best known design conventions and are seldom conceived and designed well enough to be truly versatile and dependable tools. These relatively novel interventions still require careful monitoring, research and analysis of its track record to mature. Clarity and specificity of alert content and optimal perceptual and cognitive attributes, for example, are essential for providing effective decision support to clinicians. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Incorporating patient-preference evidence into regulatory decision making.

PubMed

Ho, Martin P; Gonzalez, Juan Marcos; Lerner, Herbert P; Neuland, Carolyn Y; Whang, Joyce M; McMurry-Heath, Michelle; Hauber, A Brett; Irony, Telba

2015-10-01

Patients have a unique role in deciding what treatments should be available for them and regulatory agencies should take their preferences into account when making treatment approval decisions. This is the first study designed to obtain quantitative patient-preference evidence to inform regulatory approval decisions by the Food and Drug Administration Center for Devices and Radiological Health. Five-hundred and forty United States adults with body mass index (BMI) ≥ 30 kg/m(2) evaluated tradeoffs among effectiveness, safety, and other attributes of weight-loss devices in a scientific survey. Discrete-choice experiments were used to quantify the importance of safety, effectiveness, and other attributes of weight-loss devices to obese respondents. A tool based on these measures is being used to inform benefit-risk assessments for premarket approval of medical devices. Respondent choices yielded preference scores indicating their relative value for attributes of weight-loss devices in this study. We developed a tool to estimate the minimum weight loss acceptable by a patient to receive a device with a given risk profile and the maximum mortality risk tolerable in exchange for a given weight loss. For example, to accept a device with 0.01 % mortality risk, a risk tolerant patient will require about 10 % total body weight loss lasting 5 years. Patient preference evidence was used make regulatory decision making more patient-centered. In addition, we captured the heterogeneity of patient preferences allowing market approval of effective devices for risk tolerant patients. CDRH is using the study tool to define minimum clinical effectiveness to evaluate new weight-loss devices. The methods presented can be applied to a wide variety of medical products. This study supports the ongoing development of a guidance document on incorporating patient preferences into medical-device premarket approval decisions.

Essays on Industrial Organization and Political Economy

ERIC Educational Resources Information Center

Camara, Odilon Roberto VG de a

2009-01-01

This thesis presents three essays on industrial organization and political economy. In the first essay, I show how the attributes of a managerial workforce affect firms' placement decisions and wage offers, and managers' quit decisions. My OLG model features two division managers and a CEO, where each executive may be at a different point in his…

Decision Making for Pap Testing among Pacific Islander Women

ERIC Educational Resources Information Center

Weiss, Jie W.; Mouttapa, Michele; Sablan-Santos, Lola; DeGuzman Lacsamana, Jasmine; Quitugua, Lourdes; Park Tanjasiri, Sora

2016-01-01

This study employed a Multi-Attribute Utility (MAU) model to examine the Pap test decision-making process among Pacific Islanders (PI) residing in Southern California. A total of 585 PI women were recruited through social networks from Samoan and Tongan churches, and Chamorro family clans. A questionnaire assessed Pap test knowledge, beliefs and…

Who Dares, Who Errs? Disentangling Cognitive and Motivational Roots of Age Differences in Decisions Under Risk.

PubMed

Pachur, Thorsten; Mata, Rui; Hertwig, Ralph

2017-04-01

We separate for the first time the roles of cognitive and motivational factors in shaping age differences in decision making under risk. Younger and older adults completed gain, loss, and mixed-domain choice problems as well as measures of cognitive functioning and affect. The older adults' decision quality was lower than the younger adults' in the loss domain, and this age difference was attributable to the older adults' lower cognitive abilities. In addition, the older adults chose the more risky option more often than the younger adults in the gain and mixed domains; this difference in risk aversion was attributable to less pronounced negative affect among the older adults. Computational modeling with a hierarchical Bayesian implementation of cumulative prospect theory revealed that the older adults had higher response noise and more optimistic decision weights for gains than did the younger adults. Moreover, the older adults showed no loss aversion, a finding that supports a positivity-focus (rather than a loss-prevention) view of motivational reorientation in older age.

Attributional (Explanatory) Thinking about Failure in New Achievement Settings

ERIC Educational Resources Information Center

Perry, Raymond P.; Stupnisky, Robert H.; Daniels, Lia M.; Haynes, Tara L.

2008-01-01

Attributional (explanatory) thinking involves the appraisal of factors that contribute to performance and is instrumental to motivation and goal striving. Little is understood, however, concerning attributional thinking when multiple causes are involved in the transition to new achievement settings. Our study examined such complex attributional…

Drug benefit decisions among older adults: a policy-capturing analysis.

PubMed

Cline, Richard R; Gupta, Kiran

2006-01-01

Under the Medicare Prescription Drug Improvement and Modernization Act, beneficiaries remaining in the traditional fee-for-service plan will face a variety of drug benefit options provided by private stand-alone prescription drug plans. Although these plans likely will differ with regard to a number of important attributes, little is known about older adults' judgment processes in this context. The objectives of this study were to 1) better understand the manner in which drug insurance attributes are weighted in older adults' judgments of drug benefit suitability, 2) explore variability in judgment strategies among seniors, and 3) assess seniors' insight into their judgment policies. Three focus groups were conducted with 19 older adults to elicit important drug plan attributes. A policy-capturing study with 32 seniors, none of whom had participated in the focus groups, then was employed to quantify the impacts of these attributes on judgments of plan suitability. Focus group participants reported that copayment, monthly premium, deductible, formulary use, and mail-order pharmacy use were important drug insurance attributes. The policy-capturing study showed that deductibles and premiums were weighted most heavily in judgment formation. However, significant variability in judgment policies was apparent, with 3 distinct groups emerging from cluster analysis. The first emphasized deductibles and copayments, the second premiums and deductibles, and the third use of a mail-order pharmacy and deductibles. Study volunteers exhibited insight into the role of some plan attributes in their judgments, but not others. Cost-sharing provisions appear to be most important in older adults' evaluations of drug benefit plans. However, significant heterogeneity in attribute preferences also was apparent in this study. Older adults may not be cognizant of the manner in which some plan attributes affect their evaluations, suggesting a role for decision aids in this process.

Relative importance of attributes of drug benefit plans: Thai civil servants' perspective.

PubMed

Ngorsuraches, Surachat; Wanishayakorn, Tanatape; Tanvejsilp, Pimwara; Udomaksorn, Siripa

2013-01-01

The drug benefit plan of Thailand's Civil Servant Medical Benefit Scheme (CSMBS) must be amended to control increasing costs; to that end, it is important to gather the views of beneficiaries before making changes to the benefit plan. To examine the relative importance of attributes of drug benefit plans from the perspective of CSMBS beneficiaries. Attributes and levels adopted from focus group discussions and a preliminary survey were used to develop a questionnaire concerning hypothetical drug benefit plans. A convenience sample of 650 CSMBS beneficiaries in Songkhla province was asked to rate the drug benefit plans. To determine the beneficiaries' decision models, judgment analysis was used. Policy-capturing analysis was used to examine the beneficiaries' preferences, and cluster analysis was conducted to explore the variability among judgment plans. Judgment policy insight was also examined. The results of the study showed that the beneficiaries weighed on cost-sharing as their most important attribute. The results remained unchanged, although only data from the beneficiaries who used the compensatory model were analyzed. The results of the cluster analysis showed that the largest cluster of beneficiaries weighed mostly on the cost-sharing attribute. The judgment policy insight results not only supported the finding that most beneficiaries focused on the cost-sharing attribute but also revealed that they might have the least understanding of how the formulary attribute affected beneficiaries' decision making. Cost-sharing was the most important attribute for the CSMBS beneficiaries. This study indicated that a possible preferred drug benefit plan should have no cost-sharing, permit access only to drugs listed in a closed formulary, allow beneficiaries to obtain 3 months of drugs, and allow them to obtain drugs from either a community pharmacy or a government hospital. Copyright © 2013 Elsevier Inc. All rights reserved.

Multiple Forensic Interviews during Investigations of Child Sexual Abuse: A Cost-Effectiveness Analysis

ERIC Educational Resources Information Center

Block, Stephanie D.; Foster, E. Michael; Pierce, Matthew W.; Berkoff, Molly C.; Runyan, Desmond K.

2013-01-01

In suspected child sexual abuse some professionals recommend multiple child interviews to increase the likelihood of disclosure or more details to improve decision-making and increase convictions. We modeled the yield of a policy of routinely conducting multiple child interviews and increased convictions. Our decision tree reflected the path of a…

Quantitative perceptual differences among over-the-counter vaginal products using a standardized methodology: implications for microbicide development☆

PubMed Central

Mahan, Ellen D.; Morrow, Kathleen M.; Hayes, John E.

2015-01-01

Background Increasing prevalence of HIV infection among women worldwide has motivated the development of female-initiated prevention methods, including gel-based microbicides. User acceptability is vital for microbicide success; however, varying cultural vaginal practices indicate multiple formulations must be developed to appeal to different populations. Perceptual attributes of microbicides have been identified as primary drivers of acceptability; however, previous studies do not allow for direct comparison of these qualities between multiple formulations. Study Design Six vaginal products were analyzed ex vivo using descriptive analysis. Perceptual attributes of samples were identified by trained participants (n=10) and rated quantitatively using scales based on a panel-developed lexicon. Data were analyzed using two-way ANOVAs for each attribute; product differences were assessed via Tukey’s honestly significant difference test. Results Significant differences were found between products for multiple attributes. Patterns were also seen for attributes across intended product usage (i.e., contraceptive, moisturizer or lubricant). For example, Options© Gynol II® (Caldwell Consumer Health, LLC) was significantly stickier and grainier than other products. Conclusions Descriptive analysis, a quantitative approach that is based on consensus lexicon usage among participants, successfully quantified perceptual differences among vaginal products. Since perceptual attributes of products can be directly compared quantitatively, this study represents a novel approach that could be used to inform rational design of microbicides. PMID:21757061

Quantitative perceptual differences among over-the-counter vaginal products using a standardized methodology: implications for microbicide development.

PubMed

Mahan, Ellen D; Morrow, Kathleen M; Hayes, John E

2011-08-01

Increasing prevalence of HIV infection among women worldwide has motivated the development of female-initiated prevention methods, including gel-based microbicides. User acceptability is vital for microbicide success; however, varying cultural vaginal practices indicate multiple formulations must be developed to appeal to different populations. Perceptual attributes of microbicides have been identified as primary drivers of acceptability; however, previous studies do not allow for direct comparison of these qualities between multiple formulations. Six vaginal products were analyzed ex vivo using descriptive analysis. Perceptual attributes of samples were identified by trained participants (n=10) and rated quantitatively using scales based on a panel-developed lexicon. Data were analyzed using two-way ANOVAs for each attribute; product differences were assessed via Tukey's honestly significant difference test. Significant differences were found between products for multiple attributes. Patterns were also seen for attributes across intended product usage (i.e., contraceptive, moisturizer or lubricant). For example, Options© Gynol II® (Caldwell Consumer Health, LLC) was significantly stickier and grainier than other products. Descriptive analysis, a quantitative approach that is based on consensus lexicon usage among participants, successfully quantified perceptual differences among vaginal products. Since perceptual attributes of products can be directly compared quantitatively, this study represents a novel approach that could be used to inform rational design of microbicides. Copyright © 2011 Elsevier Inc. All rights reserved.

Multiplicative mixing of object identity and image attributes in single inferior temporal neurons.

PubMed

Ratan Murty, N Apurva; Arun, S P

2018-04-03

Object recognition is challenging because the same object can produce vastly different images, mixing signals related to its identity with signals due to its image attributes, such as size, position, rotation, etc. Previous studies have shown that both signals are present in high-level visual areas, but precisely how they are combined has remained unclear. One possibility is that neurons might encode identity and attribute signals multiplicatively so that each can be efficiently decoded without interference from the other. Here, we show that, in high-level visual cortex, responses of single neurons can be explained better as a product rather than a sum of tuning for object identity and tuning for image attributes. This subtle effect in single neurons produced substantially better population decoding of object identity and image attributes in the neural population as a whole. This property was absent both in low-level vision models and in deep neural networks. It was also unique to invariances: when tested with two-part objects, neural responses were explained better as a sum than as a product of part tuning. Taken together, our results indicate that signals requiring separate decoding, such as object identity and image attributes, are combined multiplicatively in IT neurons, whereas signals that require integration (such as parts in an object) are combined additively. Copyright © 2018 the Author(s). Published by PNAS.

The best marketing strategy in aesthetic plastic surgery: evaluating patients' preferences by conjoint analysis.

PubMed

Marsidi, Nick; van den Bergh, Maurice W H M; Luijendijk, Roland W

2014-01-01

To provide the best marketing strategy for a private clinic, knowledge of patients' preferences is essential. In marketing, conjoint analysis has been frequently used to calculate which attributes of a product are most valuable to consumers. This study investigates the relative importance of attributes that influence the selection and decision-making process when choosing an aesthetic private clinic, using conjoint analysis. The following attributes were chosen by the senior author (R.W.L.) and a marketing and communications director after a preselection of 25 randomly selected people: relative cost of the procedure, travel time, experience of the plastic surgeon, size of the clinic, method of referral, and online presentation. The attributes were then divided into levels. Using a random factor conducted by SPSS, 18 different scenarios were created and rated online by 150 potential patients before their potential visit or consultation. The patients could rate these scenarios on a scale from 1 to 7 with respect to the likeliness of visiting the clinic. The most important attribute was experience of the surgeon (35.6 percent), followed by method of referral (21.5 percent), travel time (14.2 percent), cost of procedure (12.9 percent), online presentation (9.7 percent), and size of the clinic (6.1 percent). Six of 16 levels gave a negative influence on the decision making. The authors' study shows that the two most important attributes are the experience of the surgeon and the method of referral and that conjoint analysis is effective in determining patients' preferences. It also shows which levels positively or negatively contribute per attribute.

Applying voting theory in natural resource management: a case of multiple-criteria group decision support.

PubMed

Laukkanen, Sanna; Kangas, Annika; Kangas, Jyrki

2002-02-01

Voting theory has a lot in common with utility theory, and especially with group decision-making. An expected-utility-maximising strategy exists in voting situations, as well as in decision-making situations. Therefore, it is natural to utilise the achievements of voting theory also in group decision-making. Most voting systems are based on a single criterion or holistic preference information on decision alternatives. However, a voting scheme called multicriteria approval is specially developed for decision-making situations with multiple criteria. This study considers the voting theory from the group decision support point of view and compares it with some other methods applied to similar purposes in natural resource management. A case study is presented, where the approval voting approach is introduced to natural resources planning and tested in a forestry group decision-making process. Applying multicriteria approval method was found to be a potential approach for handling some challenges typical for forestry group decision support. These challenges include (i) utilising ordinal information in the evaluation of decision alternatives, (ii) being readily understandable for and treating equally all the stakeholders in possession of different levels of knowledge on the subject considered, (iii) fast and cheap acquisition of preference information from several stakeholders, and (iv) dealing with multiple criteria.

Multimorbidity and Decision-Making Preferences Among Older Adults.

PubMed

Chi, Winnie C; Wolff, Jennifer; Greer, Raquel; Dy, Sydney

2017-11-01

Understanding individuals' preferences for participating in health care decisions is foundational to delivering person-centered care. We aimed to (1) explore preferences for health care decision making among older adults, and (2) identify multimorbidity profiles associated with preferring less active, ie, passive, participation among older US adults. Ours was a cross-sectional, nationally representative study of 2,017 National Health and Aging Trends Study respondents. Passive decision-making preference was defined as preferring to leave decisions to physicians. Multimorbidity profiles, based on 13 prevalent chronic conditions, were examined as (1) presence of 2 or more conditions, (2) a simple conditions count, and (3) a condition clusters count. Multiple logistic regression was used with adjustment for age, sex, education, English proficiency, and mobility limitation. Most older adults preferred to participate actively in making health care decisions. Older adults with 4 or more conditions, however, and those with multiple condition clusters are relatively less likely to prefer active decision making. Primary care physicians should initiate a shared decision-making process with older adults with 4 or more conditions or multiple condition clusters. Physicians should anticipate variation in decision-making preferences among older adults and adapt a decision-making process that suits individuals' preferences for participation to ensure person-centered care delivery. © 2017 Annals of Family Medicine, Inc.

If there’s a penis, it’s most likely a man: Investigating the social construction of gender using eye tracking

PubMed Central

Briken, Peer; Dekker, Arne

2018-01-01

In their foundational work on the social construction of gender, Kessler and McKenna (1978) investigated the relationship between gender attribution and genital attribution. We used digital reproductions of the original stimuli to replicate their findings in the current social context. To further investigate the underlying decision processes we applied eye tracking. The stimuli shown varied in the composition of gender cues: from those more commonly associated with maleness to associated with femaleness. Applying the ethnomethodological approach originally used, participants were asked to decide for each stimulus whether they saw a man or a woman and to indicate subjective confidence with the decision. In line with the original results we found that the genital attribution contributed immensely to the gender attribution. Also, male gender was ascribed more often when the penis was present than was female gender when the vulva was shown. Eye tracking revealed that overall most dwell time as a proxy for important information was dedicated to the head, chest and genital areas of all the stimuli. Total dwell time depended on whether the gender attribution was made in line with the depicted genital, if the genital was a penis. Attributing female gender when a penis was present was associated with longer total dwell time, unlike attributing male gender with a vulva shown. This is indicative of higher cognitive effort and more difficulty ignoring the penis as opposed to the vulva. We interpret this finding in context of the persistent male dominance as well as to the socio-cultural understanding of the vulva as a concealed and therefore seemingly absent organ. In summary, we were able to show that the gender attribution is still closely linked to genital attribution when having a binary forced choice task and that the penis is a special cue in this attribution process. PMID:29494689

Effect of denoising on supervised lung parenchymal clusters

NASA Astrophysics Data System (ADS)

Jayamani, Padmapriya; Raghunath, Sushravya; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Bartholmai, Brian J.; Robb, Richard A.

2012-03-01

Denoising is a critical preconditioning step for quantitative analysis of medical images. Despite promises for more consistent diagnosis, denoising techniques are seldom explored in clinical settings. While this may be attributed to the esoteric nature of the parameter sensitve algorithms, lack of quantitative measures on their ecacy to enhance the clinical decision making is a primary cause of physician apathy. This paper addresses this issue by exploring the eect of denoising on the integrity of supervised lung parenchymal clusters. Multiple Volumes of Interests (VOIs) were selected across multiple high resolution CT scans to represent samples of dierent patterns (normal, emphysema, ground glass, honey combing and reticular). The VOIs were labeled through consensus of four radiologists. The original datasets were ltered by multiple denoising techniques (median ltering, anisotropic diusion, bilateral ltering and non-local means) and the corresponding ltered VOIs were extracted. Plurality of cluster indices based on multiple histogram-based pair-wise similarity measures were used to assess the quality of supervised clusters in the original and ltered space. The resultant rank orders were analyzed using the Borda criteria to nd the denoising-similarity measure combination that has the best cluster quality. Our exhaustive analyis reveals (a) for a number of similarity measures, the cluster quality is inferior in the ltered space; and (b) for measures that benet from denoising, a simple median ltering outperforms non-local means and bilateral ltering. Our study suggests the need to judiciously choose, if required, a denoising technique that does not deteriorate the integrity of supervised clusters.

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

NASA Astrophysics Data System (ADS)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

Creating ensembles of decision trees through sampling

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick

2005-08-30

A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

Perceived Competence and Depressive Symptoms among Adolescents: The Moderating Role of Attributional Style

ERIC Educational Resources Information Center

Kim-Spoon, Jungmeen; Ollendick, Thomas H.; Seligman, Laura D.

2012-01-01

This longitudinal study examined the interactive effects of depressive attributional style and multiple domains of perceived competence on depressive symptoms among 431 adolescents. Our structural equation modeling with latent factor interactions indicated that (1) for girls with a higher depressive attributional style, lower perceived competence…

Attributional Style and Depression in Multiple Sclerosis

PubMed Central

Arnett, Peter A.

2013-01-01

Several etiologic theories have been proposed to explain depression in the general population. Studying these models and modifying them for use in the multiple sclerosis (MS) population may allow us to better understand depression in MS. According to the reformulated learned helplessness (LH) theory, individuals who attribute negative events to internal, stable, and global causes are more vulnerable to depression. This study differentiated attributional style that was or was not related to MS in 52 patients with MS to test the LH theory in this population and to determine possible differences between illness-related and non-illness-related attributions. Patients were administered measures of attributional style, daily stressors, disability, and depressive symptoms. Participants were more likely to list non-MS-related than MS-related causes of negative events on the Attributional Style Questionnaire (ASQ), and more-disabled participants listed significantly more MS-related causes than did less-disabled individuals. Non-MS-related attributional style correlated with stress and depressive symptoms, but MS-related attributional style did not correlate with disability or depressive symptoms. Stress mediated the effect of non-MS-related attributional style on depressive symptoms. These results suggest that, although attributional style appears to be an important construct in MS, it does not seem to be related directly to depressive symptoms; rather, it is related to more perceived stress, which in turn is related to increased depressive symptoms. PMID:24453767

Attributional style and depression in multiple sclerosis: the learned helplessness model.

PubMed

Vargas, Gray A; Arnett, Peter A

2013-01-01

Several etiologic theories have been proposed to explain depression in the general population. Studying these models and modifying them for use in the multiple sclerosis (MS) population may allow us to better understand depression in MS. According to the reformulated learned helplessness (LH) theory, individuals who attribute negative events to internal, stable, and global causes are more vulnerable to depression. This study differentiated attributional style that was or was not related to MS in 52 patients with MS to test the LH theory in this population and to determine possible differences between illness-related and non-illness-related attributions. Patients were administered measures of attributional style, daily stressors, disability, and depressive symptoms. Participants were more likely to list non-MS-related than MS-related causes of negative events on the Attributional Style Questionnaire (ASQ), and more-disabled participants listed significantly more MS-related causes than did less-disabled individuals. Non-MS-related attributional style correlated with stress and depressive symptoms, but MS-related attributional style did not correlate with disability or depressive symptoms. Stress mediated the effect of non-MS-related attributional style on depressive symptoms. These results suggest that, although attributional style appears to be an important construct in MS, it does not seem to be related directly to depressive symptoms; rather, it is related to more perceived stress, which in turn is related to increased depressive symptoms.

A common perceptual temporal limit of binding synchronous inputs across different sensory attributes and modalities

PubMed Central

Fujisaki, Waka; Nishida, Shin'ya

2010-01-01

The human brain processes different aspects of the surrounding environment through multiple sensory modalities, and each modality can be subdivided into multiple attribute-specific channels. When the brain rebinds sensory content information (‘what’) across different channels, temporal coincidence (‘when’) along with spatial coincidence (‘where’) provides a critical clue. It however remains unknown whether neural mechanisms for binding synchronous attributes are specific to each attribute combination, or universal and central. In human psychophysical experiments, we examined how combinations of visual, auditory and tactile attributes affect the temporal frequency limit of synchrony-based binding. The results indicated that the upper limits of cross-attribute binding were lower than those of within-attribute binding, and surprisingly similar for any combination of visual, auditory and tactile attributes (2–3 Hz). They are unlikely to be the limits for judging synchrony, since the temporal limit of a cross-attribute synchrony judgement was higher and varied with the modality combination (4–9 Hz). These findings suggest that cross-attribute temporal binding is mediated by a slow central process that combines separately processed ‘what’ and ‘when’ properties of a single event. While the synchrony performance reflects temporal bottlenecks existing in ‘when’ processing, the binding performance reflects the central temporal limit of integrating ‘when’ and ‘what’ properties. PMID:20335212

Ethnic differences in informed decision-making about prenatal screening for Down's syndrome.

PubMed

Fransen, Mirjam P; Essink-Bot, Marie-Louise; Vogel, Ineke; Mackenbach, Johan P; Steegers, Eric A P; Wildschut, Hajo I J

2010-03-01

The aim of this study was to assess ethnic variations in informed decision-making about prenatal screening for Down's syndrome and to examine the contribution of background and decision-making variables. Pregnant women of Dutch, Turkish and Surinamese origin were recruited between 2006 and 2008 from community midwifery or obstetrical practices in The Netherlands. Each woman was personally interviewed 3 weeks (mean) after booking for prenatal care. Knowledge, attitude and participation in prenatal screening were assessed following the 'Multidimensional Measure of Informed Choice' that has been developed and applied in the UK. In total, 71% of the Dutch women were classified as informed decision-makers, compared with 5% of the Turkish and 26% of the Surinamese women. Differences between Surinamese and Dutch women could largely be attributed to differences in educational level and age. Differences between Dutch and Turkish women could mainly be attributed to differences in language skills and gender emancipation. Women from ethnic minority groups less often made an informed decision whether or not to participate in prenatal screening. Interventions to decrease these ethnic differences should first of all be aimed at overcoming language barriers and increasing comprehension among women with a low education level. To further develop diversity-sensitive strategies for counselling, it should be investigated how women from different ethnic backgrounds value informed decision-making in prenatal screening, what decision-relevant knowledge they need and what they take into account when considering participation in prenatal screening.

An Isometric Mapping Based Co-Location Decision Tree Algorithm

NASA Astrophysics Data System (ADS)

Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.

2018-05-01

Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

Empirical Evaluation of a Decision-Analytic Aid.

DTIC Science & Technology

1980-05-01

scenarios may be attributable to the use of the Baye- sian revision model by the latter group . In the A scenarios, as well as in the NA scenarios, aided...inten- tions and to make a decision by recommending one of four prespecified courses of action. The use of the aiding package significantly increased...courses of action. The use of the aiding package significantly in- I creased the number of correct decisions under the attack version of the scenarios

Decision precision or holistic heuristic?: Insights on on-site selection of student nurses and midwives.

PubMed

Macduff, Colin; Stephen, Audrey; Taylor, Ruth

2016-01-01

Concerns about quality of care delivery in the UK have led to more scrutiny of criteria and methods for the selection of student nurses. However few substantive research studies of on-site selection processes exist. This study elicited and interpreted perspectives on interviewing processes and related decision making involved in on-site selection of student nurses and midwives. Individual and focus group interviews were undertaken with 36 lecturers, 5 clinical staff and 72 students from seven Scottish universities. Enquiry focused primarily on interviewing of candidates on-site. Qualitative content analysis was used as a primary strategy, followed by in-depth thematic analysis. Students had very mixed experiences of interview processes. Staff typically took into account a range of candidate attributes that they valued in order to achieve holistic assessments. These included: interpersonal skills, team working, confidence, problem-solving, aptitude for caring, motivations, and commitment. Staff had mixed views of the validity and reliability of interview processes. A holistic heuristic for overall decision making predominated over belief in the precision of, and evidence base for, particular attribute measurement processes. While the development of measurement tools for particular attributes continues apace, tension between holism and precision is likely to persist within on-site selection procedures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Eliciting preferences for medical devices in South Korea: A discrete choice experiment.

PubMed

Lee, Hye-Jae; Bae, Eun-Young

2017-03-01

This study aims to identify the attributes that contribute to the value of medical devices and quantify the relative importance of them using a discrete choice experiment. Based on a literature review and expert consultation, seven attributes and their levels were identified-severity of disease (2), availability of substitutes (2), improvement in procedure (3), improvement in clinical outcomes (2), increase in survival (2), improvement in quality of life (3), and cost (4). Among 576 hypothetical profiles, optimal choice sets with 20 choices were developed and experts experienced in health technology assessment and reimbursement decision making in South Korea were surveyed. A total of 102 respondents participated in the survey. The results of the random-effect probit model showed that among the seven attributes, six, except for improvement in procedure, had a significant impact on respondents' choices on medical devices. Respondents were willing to pay the highest amount for devices that provided substantial improvements in quality of life, followed by increased survival, improved clinical outcome, treatment without substitutes, and technology for treating severe diseases. The findings of this experiment will inform decision-makers of the relative importance of the criteria and help them in reimbursement decision making of medical devices. Copyright © 2017 Elsevier B.V. All rights reserved.

Distinct roles of dopamine and subthalamic nucleus in learning and probabilistic decision making.

PubMed

Coulthard, Elizabeth J; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K; Murphy, Gillian; Keeley, Sophie; Whone, Alan L

2012-12-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making predict that learning individual stimulus-response associations and rapid combination of information from multiple stimuli are dependent on different components of basal ganglia circuitry. In particular, learning and retention of memory, required for optimal response choice, are significantly reliant on dopamine, whereas integrating information probabilistically is critically dependent upon functioning of the glutamatergic subthalamic nucleus (computing the 'normalization term' in Bayes' theorem). Here, we test these theories by investigating 22 patients with Parkinson's disease either treated with deep brain stimulation to the subthalamic nucleus and dopaminergic therapy or managed with dopaminergic therapy alone. We use computerized tasks that probe three cognitive functions-information acquisition (learning), memory over a delay and information integration when multiple pieces of sequentially presented information have to be combined. Patients performed the tasks ON or OFF deep brain stimulation and/or ON or OFF dopaminergic therapy. Consistent with the computational theories, we show that stopping dopaminergic therapy impairs memory for probabilistic information over a delay, whereas deep brain stimulation to the region of the subthalamic nucleus disrupts decision making when multiple pieces of acquired information must be combined. Furthermore, we found that when participants needed to update their decision on the basis of the last piece of information presented in the decision-making task, patients with deep brain stimulation of the subthalamic nucleus region did not slow down appropriately to revise their plan, a pattern of behaviour that mirrors the impulsivity described clinically in some patients with subthalamic nucleus deep brain stimulation. Thus, we demonstrate distinct mechanisms for two important facets of human decision making: first, a role for dopamine in memory consolidation, and second, the critical importance of the subthalamic nucleus in successful decision making when multiple pieces of information must be combined.

Tehran Air Pollutants Prediction Based on Random Forest Feature Selection Method

NASA Astrophysics Data System (ADS)

Shamsoddini, A.; Aboodi, M. R.; Karami, J.

2017-09-01

Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

Dual-processing accounts of reasoning, judgment, and social cognition.

PubMed

Evans, Jonathan St B T

2008-01-01

This article reviews a diverse set of proposals for dual processing in higher cognition within largely disconnected literatures in cognitive and social psychology. All these theories have in common the distinction between cognitive processes that are fast, automatic, and unconscious and those that are slow, deliberative, and conscious. A number of authors have recently suggested that there may be two architecturally (and evolutionarily) distinct cognitive systems underlying these dual-process accounts. However, it emerges that (a) there are multiple kinds of implicit processes described by different theorists and (b) not all of the proposed attributes of the two kinds of processing can be sensibly mapped on to two systems as currently conceived. It is suggested that while some dual-process theories are concerned with parallel competing processes involving explicit and implicit knowledge systems, others are concerned with the influence of preconscious processes that contextualize and shape deliberative reasoning and decision-making.

The scent of inbreeding: a male sex pheromone betrays inbred males

PubMed Central

van Bergen, Erik; Brakefield, Paul M.; Heuskin, Stéphanie; Zwaan, Bas J.; Nieberding, Caroline M.

2013-01-01

Inbreeding depression results from mating among genetically related individuals and impairs reproductive success. The decrease in male mating success is usually attributed to an impact on multiple fitness-related traits that reduce the general condition of inbred males. Here, we find that the production of the male sex pheromone is reduced significantly by inbreeding in the butterfly Bicyclus anynana. Other traits indicative of the general condition, including flight performance, are also negatively affected in male butterflies by inbreeding. Yet, we unambiguously show that only the production of male pheromones affects mating success. Thus, this pheromone signal informs females about the inbreeding status of their mating partners. We also identify the specific chemical component (hexadecanal) probably responsible for the decrease in male mating success. Our results advocate giving increased attention to olfactory communication as a major causal factor of mate-choice decisions and sexual selection. PMID:23466986

Disentangling the impact of multiple innovations to reduce delayed hospital discharges.

PubMed

Manzano-Santaella, Ana

2010-01-01

Delayed hospital discharges are often blamed for interrupting the smooth operation of hospitals. In England, the Community Care Act in 2003 introduced fines to social services departments to resolve this issue. Evaluations of this policy reported success in the reduction of delays. However, this policy was an amalgam of several innovations, not just the introduction of fines. This simultaneity makes attribution of impact of fines a difficult task because of the potential impact of those other measures. All the other designed organizational changes contain as much mechanisms of change as the more advertised fines. The exploration of how all these elements are connected unravels the inner workings of the programme as a whole, and by default, of the fines. This theoretical analysis also demonstrates how the reduction of some delays is based on the re-definition of key concepts for delayed discharges such as 'safe to transfer', team decision-making and causes for delays.

Mother natural: Motivations and associations for consuming natural foods.

PubMed

Moscato, Emily M; Machin, Jane E

2018-02-01

Natural is perceived as innately positive and is a widely sought-after attribute in food products. The natural food industry continues to grow in response to rising consumer demand. This qualitative study explored mothers' motivations for purchasing and consuming natural food products for themselves and their families. Mothers are an important population because of their disproportionate influence on household food consumption. We employed participant photography and a series of three weekly focus groups to derive a rich understanding of the activities surrounding and motivations behind seeking natural in everyday buying decisions. Five major themes were identified. First, natural nurtures well-being: physical, psychological, social, and emotional health. Second, natural behaves "supernaturally," allowing positive attributes to be transmitted from the source to the recipient. Third, natural is associated with authenticity, providing a sense of trust, transparency, and control. Fourth, consuming natural reinforces the socially constructed idea of a good mother. Lastly, the preference for natural does not always translate into purchase; mothers face compromises because of conflicting priorities and resources. Understanding mothers' multiple motivations provides deeper insight into the attraction for natural products. The findings have application in positioning interventions for more nutritional eating and revising regulations on the food label natural. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling innovation performance of European regions using multi-output neural networks

PubMed Central

Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes. PMID:28968449

Modelling innovation performance of European regions using multi-output neural networks.

PubMed

Hajek, Petr; Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

Service-Oriented Architecture Approach to MAGTF Logistics Support Systems

DTIC Science & Technology

2013-09-01

Support System-Marine Corps IT Information Technology KPI Key Performance Indicators LCE Logistics Command Element ITV In-transit Visibility LCM...building blocks, options, KPI (key performance indicators), design decisions and the corresponding; the physical attributes which is the second attribute... KPI ) that they impact. h. Layer 8 (Information Architecture) The business intelligence layer and information architecture safeguards the inclusion

The market for U. S. hardwoods in the United Kingdom: market needs and satisfaction with U. S. Products

Treesearch

Robert J. Bush; Philip A. Araman

1993-01-01

Importers of hardwood lumber in the United Kingdom were studied to determine the product and supplier attributes that most influenced their purchase decisions. Importers of North American hardwoods were least satisfied with Lumber Straightness. Straightness, Absence of Stain and the Absence of Surface Checks were the most important lumber attributes. On Time Shipment...

Learning multiple relative attributes with humans in the loop.

PubMed

Qian, Buyue; Wang, Xiang; Cao, Nan; Jiang, Yu-Gang; Davidson, Ian

2014-12-01

Semantic attributes have been recognized as a more spontaneous manner to describe and annotate image content. It is widely accepted that image annotation using semantic attributes is a significant improvement to the traditional binary or multiclass annotation due to its naturally continuous and relative properties. Though useful, existing approaches rely on an abundant supervision and high-quality training data, which limit their applicability. Two standard methods to overcome small amounts of guidance and low-quality training data are transfer and active learning. In the context of relative attributes, this would entail learning multiple relative attributes simultaneously and actively querying a human for additional information. This paper addresses the two main limitations in existing work: 1) it actively adds humans to the learning loop so that minimal additional guidance can be given and 2) it learns multiple relative attributes simultaneously and thereby leverages dependence amongst them. In this paper, we formulate a joint active learning to rank framework with pairwise supervision to achieve these two aims, which also has other benefits such as the ability to be kernelized. The proposed framework optimizes over a set of ranking functions (measuring the strength of the presence of attributes) simultaneously and dependently on each other. The proposed pairwise queries take the form of which one of these two pictures is more natural? These queries can be easily answered by humans. Extensive empirical study on real image data sets shows that our proposed method, compared with several state-of-the-art methods, achieves superior retrieval performance while requires significantly less human inputs.

Using decision mapping to inform the development of a stated choice survey to elicit youth preferences for sexual and reproductive health and HIV services in rural Malawi.

PubMed

Michaels-Igbokwe, Christine; Lagarde, Mylene; Cairns, John; Terris-Prestholt, Fern

2014-03-01

The process of designing and developing discrete choice experiments (DCEs) is often under reported. The need to adequately report the results of qualitative work used to identify attributes and levels used in a DCE is recognised. However, one area that has received relatively little attention is the exploration of the choice question of interest. This paper provides a case study of the process used to design a stated preference survey to assess youth preferences for integrated sexual and reproductive health (SRH) and HIV outreach services in Malawi. Development and design consisted of six distinct but overlapping and iterative stages. Stage one was a review of the literature. Stage two involved developing a decision map to conceptualise the choice processes involved. Stage three included twelve focus group discussions with young people aged 15-24 (n = 113) and three key informant interviews (n = 3) conducted in Ntcheu District, Malawi. Stage four involved analysis of qualitative data and identification of potential attributes and levels. The choice format and experimental design were selected in stages five and six. The results of the literature review were used to develop a decision map outlining the choices that young people accessing SRH services may face. For youth that would like to use services two key choices were identified: the choice between providers and the choice of service delivery attributes within a provider type. Youth preferences for provider type are best explored using a DCE with a labelled design, while preferences for service delivery attributes associated with a particular provider are better understood using an unlabelled design. Consequently, two DCEs were adopted to jointly assess preferences in this context. Used in combination, the results of the literature review, the decision mapping process and the qualitative work provided robust approach to designing the DCEs individually and as complementary pieces of work. Copyright © 2014 Elsevier Ltd. All rights reserved.

Decision Making Methods in Space Economics and Systems Engineering

NASA Technical Reports Server (NTRS)

Shishko, Robert

2006-01-01

This viewgraph presentation reviews various methods of decision making and the impact that they have on space economics and systems engineering. Some of the methods discussed are: Present Value and Internal Rate of Return (IRR); Cost-Benefit Analysis; Real Options; Cost-Effectiveness Analysis; Cost-Utility Analysis; Multi-Attribute Utility Theory (MAUT); and Analytic Hierarchy Process (AHP).

The Effects of Applicant Attractiveness, Managerial Attributes and Gender on Executive Employment Decisions.

ERIC Educational Resources Information Center

Best, Bethia J.; Spector, Paul E.

Although it has been shown that physical attractiveness is an advantage to male applicants for managerial positions, it is not clear whether attractiveness is an advantage or disadvantage to female applicants for these jobs. Male (N=25) and female (N=22) business administration students were asked to simulate selection decisions for a high level…

Postoptimality analysis in the selection of technology portfolios

NASA Technical Reports Server (NTRS)

Adumitroaie, Virgil; Shelton, Kacie; Elfes, Alberto; Weisbin, Charles R.

2006-01-01

This paper describes an approach for qualifying optimal technology portfolios obtained with a multi-attribute decision support system. The goal is twofold: to gauge the degree of confidence in the optimal solution and to provide the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy non-technical constraints.

Comprehensive decision tree models in bioinformatics.

PubMed

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics.

Comprehensive Decision Tree Models in Bioinformatics

PubMed Central

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Purpose Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. Methods This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. Results The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. Conclusions The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics. PMID:22479449

Online, Interactive Option Grid Patient Decision Aids and their Effect on User Preferences.

PubMed

Scalia, Peter; Durand, Marie-Anne; Kremer, Jan; Faber, Marjan; Elwyn, Glyn

2018-01-01

Randomized trials have shown that patient decision aids can modify users' preferred healthcare options, but research has yet to identify the attributes embedded in these tools that cause preferences to shift. The aim of this study was to investigate people's preferences as they used decision aids for 5 health decisions and, for each of the following: 1) determine if using the interactive Option Grid led to a pre-post shift in preferences; 2) determine which frequently asked questions (FAQs) led to preference shifts; 3) determine the FAQs that were rated as the most important as users compared options. Interactive Option Grid decision aids enable users to view attributes of available treatment or screening options, rate their importance, and specify their preferred options before and after decision aid use. The McNemar-Bowker paired test was used to compare stated pre-post preferences. Multinomial logistic regressions were conducted to investigate possible associations between covariates and preference shifts. Overall, 626 users completed the 5 most-used tools: 1) Amniocentesis test: yes or no? ( n = 73); 2) Angina: treatment options ( n = 88); 3) Breast cancer: surgical options ( n = 265); 4) Prostate Specific Antigen (PSA) test: yes or no? ( n = 82); 5) Statins for heart disease risk: yes or no? ( n = 118). The breast cancer, PSA, and statins Option Grid decision aids generated significant preference shifts. Generally, users shifted their preference when presented with the description of the available treatment options, and the risk associated with each option. The use of decision aids for some, but not all health decisions, was accompanied by a shift in user preferences. Users typically valued information associated with risks, and chose more risk averse options after completing the interactive tool.

Ambiguity Within Nursing Practice: An Evolutionary Concept Analysis.

PubMed

McMahon, Michelle A; Dluhy, Nancy M

2017-02-01

To analyze the concept of ambiguity in a nursing context. Ambiguity is inherent within nursing practice. As health care becomes increasingly complex, nurses must continue to successfully deal with greater amounts of clinical ambiguity. Although ambiguity is discussed in nursing, minimal concept refinement exists to capture the contextual intricacies from a nursing lens. Nurse perception of an ambiguous clinical event, in combination with nurse tolerance level for ambiguity, can impact nurse response. Yet, little is known about what constitutes ambiguity within nursing practice (AWNP). Rodgers evolutionary method was used to explore AWNP, with emphasis on nurse thinking during ambiguous clinical situations. Literature searches across multiple databases yielded 38 articles for analysis. Attributes of AWNP include (a) variations in cues/available information, (b) multiple interpretations, (c) novel/nonroutine presentations, and (d) unpredictable. Antecedents include (a) a context-specific, clinical situation with ambiguous features needing evaluation and (b) an individual to sense a knowledge gap or perceive ambiguity. Consequences include ranges of (a) emotional, (b) behavioral, and (c) cognitive clinician responses. Preliminary findings support AWNP as a distinct concept in which ambiguity perceived by the nurse likely affects judgment, decision making, and clinical interventions. AWNP is a clinically relevant concept requiring continued development.

A model of human decision making in multiple process monitoring situations

NASA Technical Reports Server (NTRS)

Greenstein, J. S.; Rouse, W. B.

1982-01-01

Human decision making in multiple process monitoring situations is considered. It is proposed that human decision making in many multiple process monitoring situations can be modeled in terms of the human's detection of process related events and his allocation of attention among processes once he feels event have occurred. A mathematical model of human event detection and attention allocation performance in multiple process monitoring situations is developed. An assumption made in developing the model is that, in attempting to detect events, the human generates estimates of the probabilities that events have occurred. An elementary pattern recognition technique, discriminant analysis, is used to model the human's generation of these probability estimates. The performance of the model is compared to that of four subjects in a multiple process monitoring situation requiring allocation of attention among processes.

Attributions and self-efficacy for physical activity in multiple sclerosis.

PubMed

Nickel, D; Spink, K; Andersen, M; Knox, K

2014-01-01

Self-efficacy is an important predictor of health-related physical activity in multiple sclerosis (MS). While past experiences are believed to influence efficacy beliefs, the explanations individuals provide for these experiences also may be critical. Our objective was to test the hypothesis that perceived success or failure to accumulate 150 min of physical activity in the previous week would moderate the relationship between the attributional dimension of stability and self-efficacy to exercise in the future. Forty-two adults with MS participated in this cross-sectional descriptive study. Participants completed questions assessing physical activity, perceived outcome for meeting the recommended level of endurance activity, attributions for the outcome, and exercise self-efficacy. Results from hierarchical multiple regression revealed a significant main effect for perceived outcome predicting self-efficacy that was qualified by a significant interaction. The final model, which included perceived outcome, stability, and the interaction term, predicted 37% of the variance in exercise self-efficacy, F (3, 38) = 7.27, p = .001. Our findings suggest that the best prediction of self-efficacy in the MS population may include the interaction of specific attributional dimensions with success/failure at meeting the recommended physical activity dose. Attributions may be another target for interventions aimed at increasing the physical activity in MS.

Visual Attention Allocation Between Robotic Arm and Environmental Process Control: Validating the STOM Task Switching Model

NASA Technical Reports Server (NTRS)

Wickens, Christopher; Vieanne, Alex; Clegg, Benjamin; Sebok, Angelia; Janes, Jessica

2015-01-01

Fifty six participants time shared a spacecraft environmental control system task with a realistic space robotic arm control task in either a manual or highly automated version. The former could suffer minor failures, whose diagnosis and repair were supported by a decision aid. At the end of the experiment this decision aid unexpectedly failed. We measured visual attention allocation and switching between the two tasks, in each of the eight conditions formed by manual-automated arm X expected-unexpected failure X monitoring- failure management. We also used our multi-attribute task switching model, based on task attributes of priority interest, difficulty and salience that were self-rated by participants, to predict allocation. An un-weighted model based on attributes of difficulty, interest and salience accounted for 96 percent of the task allocation variance across the 8 different conditions. Task difficulty served as an attractor, with more difficult tasks increasing the tendency to stay on task.

Ranking the strategies for Indian medical tourism sector through the integration of SWOT analysis and TOPSIS method.

PubMed

Ajmera, Puneeta

2017-10-09

Purpose Organizations have to evaluate their internal and external environments in this highly competitive world. Strengths, weaknesses, opportunities and threats (SWOT) analysis is a very useful technique which analyzes the strengths, weaknesses, opportunities and threats of an organization for taking strategic decisions and it also provides a foundation for the formulation of strategies. But the drawback of SWOT analysis is that it does not quantify the importance of individual factors affecting the organization and the individual factors are described in brief without weighing them. Because of this reason, SWOT analysis can be integrated with any multiple attribute decision-making (MADM) technique like the technique for order preference by similarity to ideal solution (TOPSIS), analytical hierarchy process, etc., to evaluate the best alternative among the available strategic alternatives. The paper aims to discuss these issues. Design/methodology/approach In this study, SWOT analysis is integrated with a multicriteria decision-making technique called TOPSIS to rank different strategies for Indian medical tourism in order of priority. Findings SO strategy (providing best facilitation and care to the medical tourists at par to developed countries) is the best strategy which matches with the four elements of S, W, O and T of SWOT matrix and 35 strategic indicators. Practical implications This paper proposes a solution based on a combined SWOT analysis and TOPSIS approach to help the organizations to evaluate and select strategies. Originality/value Creating a new technology or administering a new strategy always has some degree of resistance by employees. To minimize resistance, the author has used TOPSIS as it involves group thinking, requiring every manager of the organization to analyze and evaluate different alternatives and average measure of each parameter in final decision matrix.

Application of Visual Attention in Seismic Attribute Analysis

NASA Astrophysics Data System (ADS)

He, M.; Gu, H.; Wang, F.

2016-12-01

It has been proved that seismic attributes can be used to predict reservoir. The joint of multi-attribute and geological statistics, data mining, artificial intelligence, further promote the development of the seismic attribute analysis. However, the existing methods tend to have multiple solutions and insufficient generalization ability, which is mainly due to the complex relationship between seismic data and geological information, and undoubtedly own partly to the methods applied. Visual attention is a mechanism model of the human visual system which can concentrate on a few significant visual objects rapidly, even in a mixed scene. Actually, the model qualify good ability of target detection and recognition. In our study, the targets to be predicted are treated as visual objects, and an object representation based on well data is made in the attribute dimensions. Then in the same attribute space, the representation is served as a criterion to search the potential targets outside the wells. This method need not predict properties by building up a complicated relation between attributes and reservoir properties, but with reference to the standard determined before. So it has pretty good generalization ability, and the problem of multiple solutions can be weakened by defining the threshold of similarity.

VOMS/VOMRS utilization patterns and convergence plan

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

Ceccanti, A.; /INFN, CNAF; Ciaschini, V.

2010-01-01

The Grid community uses two well-established registration services, which allow users to be authenticated under the auspices of Virtual Organizations (VOs). The Virtual Organization Membership Service (VOMS), developed in the context of the Enabling Grid for E-sciencE (EGEE) project, is an Attribute Authority service that issues attributes expressing membership information of a subject within a VO. VOMS allows to partition users in groups, assign them roles and free-form attributes which are then used to drive authorization decisions. The VOMS administrative application, VOMS-Admin, manages and populates the VOMS database with membership information. The Virtual Organization Management Registration Service (VOMRS), developed atmore » Fermilab, extends the basic registration and management functionalities present in VOMS-Admin. It implements a registration workflow that requires VO usage policy acceptance and membership approval by administrators. VOMRS supports management of multiple grid certificates, and handling users' request for group and role assignments, and membership status. VOMRS is capable of interfacing to local systems with personnel information (e.g. the CERN Human Resource Database) and of pulling relevant member information from them. VOMRS synchronizes the relevant subset of information with VOMS. The recent development of new features in VOMS-Admin raises the possibility of rationalizing the support and converging on a single solution by continuing and extending existing collaborations between EGEE and OSG. Such strategy is supported by WLCG, OSG, US CMS, US Atlas, and other stakeholders worldwide. In this paper, we will analyze features in use by major experiments and the use cases for registration addressed by the mature single solution.« less

VOMS/VOMRS utilization patterns and convergence plan

NASA Astrophysics Data System (ADS)

Ceccanti, A.; Ciaschini, V.; Dimou, M.; Garzoglio, G.; Levshina, T.; Traylen, S.; Venturi, V.

2010-04-01

The Grid community uses two well-established registration services, which allow users to be authenticated under the auspices of Virtual Organizations (VOs). The Virtual Organization Membership Service (VOMS), developed in the context of the Enabling Grid for E-sciencE (EGEE) project, is an Attribute Authority service that issues attributes expressing membership information of a subject within a VO. VOMS allows to partition users in groups, assign them roles and free-form attributes which are then used to drive authorization decisions. The VOMS administrative application, VOMS-Admin, manages and populates the VOMS database with membership information. The Virtual Organization Management Registration Service (VOMRS), developed at Fermilab, extends the basic registration and management functionalities present in VOMS-Admin. It implements a registration workflow that requires VO usage policy acceptance and membership approval by administrators. VOMRS supports management of multiple grid certificates, and handling users' request for group and role assignments, and membership status. VOMRS is capable of interfacing to local systems with personnel information (e.g. the CERN Human Resource Database) and of pulling relevant member information from them. VOMRS synchronizes the relevant subset of information with VOMS. The recent development of new features in VOMS-Admin raises the possibility of rationalizing the support and converging on a single solution by continuing and extending existing collaborations between EGEE and OSG. Such strategy is supported by WLCG, OSG, US CMS, US Atlas, and other stakeholders worldwide. In this paper, we will analyze features in use by major experiments and the use cases for registration addressed by the mature single solution.

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

NASA Astrophysics Data System (ADS)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

Ensemble modelling and structured decision-making to support Emergency Disease Management.

PubMed

Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

A framework for multi-stakeholder decision-making and conflict resolution

EPA Science Inventory

We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimiz...

The Neurobiology of Decision-Making and Responsibility: Reconciling Mechanism and Mindedness

PubMed Central

Shadlen, Michael N.; Roskies, Adina L.

2012-01-01

This essay reviews recent developments in neurobiology which are beginning to expose the mechanisms that underlie some elements of decision-making that bear on attributions of responsibility. These “elements” have been mainly studied in simple perceptual decision tasks, which are performed similarly by humans and non-human primates. Here we consider the role of neural noise, and suggest that thinking about the role of noise can shift the focus of discussions of randomness in decision-making away from its role in enabling alternate possibilities and toward a potential grounding role for responsibility. PMID:22536171

The application of natural science data to land management decision-making

NASA Technical Reports Server (NTRS)

Williams, D. L.; Sharpe, C. P.; Rowe, P. G.

1974-01-01

A natural environmental analysis process which allows the decision maker to know the probable consequences of a decision prior to the act is developed. Emphasis is placed on the fit between the natural environment and the social, economic, and functional attributes of man's communities and the transition from nature in its present state to various forms and intensities of development. Applications of the analysis are examined. It is concluded that the analysis is a workable system for land use management.

Presenting evidence and summary measures to best inform societal decisions when comparing multiple strategies.

PubMed

Eckermann, Simon; Willan, Andrew R

2011-07-01

Multiple strategy comparisons in health technology assessment (HTA) are becoming increasingly important, with multiple alternative therapeutic actions, combinations of therapies and diagnostic and genetic testing alternatives. Comparison under uncertainty of incremental cost, effects and cost effectiveness across more than two strategies is conceptually and practically very different from that for two strategies, where all evidence can be summarized in a single bivariate distribution on the incremental cost-effectiveness plane. Alternative methods for comparing multiple strategies in HTA have been developed in (i) presenting cost and effects on the cost-disutility plane and (ii) summarizing evidence with multiple strategy cost-effectiveness acceptability (CEA) and expected net loss (ENL) curves and frontiers. However, critical questions remain for the analyst and decision maker of how these techniques can be best employed across multiple strategies to (i) inform clinical and cost inference in presenting evidence, and (ii) summarize evidence of cost effectiveness to inform societal reimbursement decisions where preferences may be risk neutral or somewhat risk averse under the Arrow-Lind theorem. We critically consider how evidence across multiple strategies can be best presented and summarized to inform inference and societal reimbursement decisions, given currently available methods. In the process, we make a number of important original findings. First, in presenting evidence for multiple strategies, the joint distribution of costs and effects on the cost-disutility plane with associated flexible comparators varying across replicates for cost and effect axes ensure full cost and effect inference. Such inference is usually confounded on the cost-effectiveness plane with comparison relative to a fixed origin and axes. Second, in summarizing evidence for risk-neutral societal decision making, ENL curves and frontiers are shown to have advantages over the CEA frontier in directly presenting differences in expected net benefit (ENB). The CEA frontier, while identifying strategies that maximize ENB, only presents their probability of maximizing net benefit (NB) and, hence, fails to explain why strategies maximize ENB at any given threshold value. Third, in summarizing evidence for somewhat risk-averse societal decision making, trade-offs between the strategy maximizing ENB and other potentially optimal strategies with higher probability of maximizing NB should be presented over discrete threshold values where they arise. However, the probabilities informing these trade-offs and associated discrete threshold value regions should be derived from bilateral CEA curves to prevent confounding by other strategies inherent in multiple strategy CEA curves. Based on these findings, a series of recommendations are made for best presenting and summarizing cost-effectiveness evidence for reimbursement decisions when comparing multiple strategies, which are contrasted with advice for comparing two strategies. Implications for joint research and reimbursement decisions are also discussed.

The influence of a bystander agent's beliefs on children's and adults' decision-making process.

PubMed

Buttelmann, Frances; Buttelmann, David

2017-01-01

The ability to attribute and represent others' mental states (e.g., beliefs; so-called "theory of mind") is essential for participation in human social interaction. Despite a considerable body of research using tasks in which protagonists in the participants' attentional focus held false or true beliefs, the question of automatic belief attribution to bystander agents has received little attention. In the current study, we presented adults and 6-year-olds (N=92) with an implicit computer-based avoidance false-belief task in which participants were asked to place an object into one of three boxes. While doing so, we manipulated the beliefs of an irrelevant human-like or non-human-like bystander agent who was visible on the screen. Importantly, the bystander agent's beliefs were irrelevant for solving the task. Still, children's decision making was significantly influenced by the bystander agent's beliefs even if this was a non-human-like self-propelled object. Such an influence did not become obvious in adults' deliberate decisions but occurred only in their reaction times, which suggests that they also processed the bystander agent's beliefs but were able to suppress the influence of such beliefs on their behavior regulation. The results of a control study (N=53) ruled out low-level explanations and confirmed that self-propelledness of agents is a necessary factor for belief attribution to occur. Thus, not only do humans spontaneously ascribe beliefs to self-propelled bystander agents, but those beliefs even influence meaningful decisions in children. Copyright © 2016 Elsevier Inc. All rights reserved.

The association between job strain and emotional exhaustion in a cohort of 1,028 Finnish teachers.

PubMed

Santavirta, Nina; Solovieva, Svetlana; Theorell, Töres

2007-03-01

Teachers' work overload has been the subject of intense research, and the results of these studies show that a substantial proportion of teachers perceive their job as very stressful. To investigate how different formulations of high demands and low decision latitude was related to teachers' burnout, and to estimate the possible interaction between these factors. The sample consisted of 1,028 school teachers. Multivariate covariant analyses (MANCOVA) was used to evaluate the relationship between a high-strain job defined by 3 different cut-off points and burnout. Logistical regression analysis was used to estimate the separate and joint effects of demand and decision authority on emotional exhaustion. Interaction between high demands and low decision authority was analysed using relative excess risk due to interaction (RERI). An attributable proportion (AP) was calculated in order to estimate the proportion of emotionally exhausted teachers among those exposed to both risk factors that was attributable to their synergistic interaction. The group of teachers who perceived their job as a low-strain job was used as the reference group in the analysis. The effect of job strain on burnout was proved to be consistent and robust across alternative formulations. The main effect of high demands exceeded that of low decision authority in relation to emotional exhaustion. Furthermore, the 2 factors acted synergistically to increase the risk of burnout. In the case of burnout, teachers who perceived their job as highly demanding and low in control, 69% of the effect could be attributed to the synergism of these 2 factors.

The Role of Social Constructions and Biophysical Attributes of the Environment in Decision-Making in the Context of Biofuels and Rubber Production Partnership Regimes in Upland Philippines

NASA Astrophysics Data System (ADS)

Montefrio, M. F.

2012-12-01

Burgeoning attention in biofuels and natural rubber has spurred interest among governments and private companies in integrating marginalized communities into global commodity markets. Upland farmers from diverse cultural backgrounds and biophysical settings today are deciding whether to agree with partnership proposals from governments and private firms to grow biofuels and natural rubber. In this paper, I examine whether upland farmers' socio-environmental constructions (evaluative beliefs, place satisfaction, and ecological worldviews) and the actual biophysical attributes (land cover and soil types) of upland environments, respectively, function as significant predictors of the intent and decisions of indigenous and non-indigenous farmers to cooperate with government and private actors to establish certain biofuel crops and natural rubber production systems in Palawan, Philippines. Drawing from ethnography and statistical analysis of household surveys, I propose that social constructions and the biophysical attributes of the environment are closely related with each other and in turn both influence individual decision-making behavior in resource-based production partnership regimes. This has significant implications on the resilience of socio-ecological systems, particularly agro-ecosystems, as certain upland farmers prefer to engage in intensive, monocrop production of biofuels and natural rubber on relatively more biodiverse areas, such as secondary forests and traditional shifting cultivation lands. The study aims to advance new institutional theories of resource management, particularly Ostrom's Institutional Analysis and Development and Socio-Ecological Systems frameworks, and scholarship on environmental decision-making in the context of collective action.

Evolutionary and Neural Computing Based Decision Support System for Disease Diagnosis from Clinical Data Sets in Medical Practice.

PubMed

Sudha, M

2017-09-27

As a recent trend, various computational intelligence and machine learning approaches have been used for mining inferences hidden in the large clinical databases to assist the clinician in strategic decision making. In any target data the irrelevant information may be detrimental, causing confusion for the mining algorithm and degrades the prediction outcome. To address this issue, this study attempts to identify an intelligent approach to assist disease diagnostic procedure using an optimal set of attributes instead of all attributes present in the clinical data set. In this proposed Application Specific Intelligent Computing (ASIC) decision support system, a rough set based genetic algorithm is employed in pre-processing phase and a back propagation neural network is applied in training and testing phase. ASIC has two phases, the first phase handles outliers, noisy data, and missing values to obtain a qualitative target data to generate appropriate attribute reduct sets from the input data using rough computing based genetic algorithm centred on a relative fitness function measure. The succeeding phase of this system involves both training and testing of back propagation neural network classifier on the selected reducts. The model performance is evaluated with widely adopted existing classifiers. The proposed ASIC system for clinical decision support has been tested with breast cancer, fertility diagnosis and heart disease data set from the University of California at Irvine (UCI) machine learning repository. The proposed system outperformed the existing approaches attaining the accuracy rate of 95.33%, 97.61%, and 93.04% for breast cancer, fertility issue and heart disease diagnosis.

What counts as a decision? Predictors of perceived decision making.

PubMed

Chapman, G B; Niedermayer, L Y

2001-09-01

We examined lay perceptions of what counts as a decision. Eighty-six subjects read 10 scenarios that described clear decisions (e.g., choosing a graduate school), clear "nondecisions" (e.g., an accidental wrong turn), or ambiguous actions (e.g., eating a donut when on a diet or allowing someone else to make the decision). The subjects rated each scenario as to whether the actor had made a decision and also rated six other attributes. The scenarios were rated as clearly illustrating a decision if the actor engaged in a lot of thought and did not act reflexively. Consideration of consequences and having alternatives were moderately related to decision ratings, whereas having self-control problems and the influence of physiological drives showed little relationship with decision ratings. Thus, lay concepts of decision making differ from decision theory in that thoughtful, intentional behavior is more important in defining a decision than are decision theoretic components, such as alternatives and consequences.

Methodology to Estimate the Longitudinal Average Attributable Fraction of Guideline-recommended Medications for Death in Older Adults With Multiple Chronic Conditions

PubMed Central

Zhan, Yilei; Cohen, Andrew B.; Tinetti, Mary E.; Trentalange, Mark; McAvay, Gail

2016-01-01

Background: Persons with multiple chronic conditions receive multiple guideline-recommended medications to improve outcomes such as mortality. Our objective was to estimate the longitudinal average attributable fraction for 3-year survival of medications for cardiovascular conditions in persons with multiple chronic conditions and to determine whether heterogeneity occurred by age. Methods: Medicare Current Beneficiary Survey participants (N = 8,578) with two or more chronic conditions, enrolled from 2005 to 2009 with follow-up through 2011, were analyzed. We calculated the longitudinal extension of the average attributable fraction for oral medications (beta blockers, renin–angiotensin system blockers, and thiazide diuretics) indicated for cardiovascular conditions (atrial fibrillation, coronary artery disease, heart failure, and hypertension), on survival adjusted for 18 participant characteristics. Models stratified by age (≤80 and >80 years) were analyzed to determine heterogeneity of both cardiovascular conditions and medications. Results: Heart failure had the greatest average attributable fraction (39%) for mortality. The fractional contributions of beta blockers, renin–angiotensin system blockers, and thiazides to improve survival were 10.4%, 9.3%, and 7.2% respectively. In age-stratified models, of these medications thiazides had a significant contribution to survival only for those aged 80 years or younger. The effects of the remaining medications were similar in both age strata. Conclusions: Most cardiovascular medications were attributed independently to survival. The two cardiovascular conditions contributing independently to death were heart failure and atrial fibrillation. The medication effects were similar by age except for thiazides that had a significant contribution to survival in persons younger than 80 years. PMID:26748093

Valuating Privacy with Option Pricing Theory

NASA Astrophysics Data System (ADS)

Berthold, Stefan; Böhme, Rainer

One of the key challenges in the information society is responsible handling of personal data. An often-cited reason why people fail to make rational decisions regarding their own informational privacy is the high uncertainty about future consequences of information disclosures today. This chapter builds an analogy to financial options and draws on principles of option pricing to account for this uncertainty in the valuation of privacy. For this purpose, the development of a data subject's personal attributes over time and the development of the attribute distribution in the population are modeled as two stochastic processes, which fit into the Binomial Option Pricing Model (BOPM). Possible applications of such valuation methods to guide decision support in future privacy-enhancing technologies (PETs) are sketched.

Decision making on organ donation: the dilemmas of relatives of potential brain dead donors.

PubMed

de Groot, Jack; van Hoek, Maria; Hoedemaekers, Cornelia; Hoitsma, Andries; Smeets, Wim; Vernooij-Dassen, Myrra; van Leeuwen, Evert

2015-09-17

This article is part of a study to gain insight into the decision-making process by looking at the views of the relatives of potential brain dead donors. Alongside a literature review, focus interviews were held with healthcare professionals about their role in the request and decision-making process when post-mortal donation is at stake. This article describes the perspectives of the relatives. A content-analysis of 22 semi-structured in-depth interviews with relatives involved in an organ donation decision. Three themes were identified: 'conditions', 'ethical considerations' and 'look back'. Conditions were: 'sense of urgency', 'incompetence to decide' and 'agreement between relatives'. Ethical considerations result in a dilemma for non-donor families: aiding people or protecting the deceased's body, especially when they do not know his/her preference. Donor families respect the deceased's last will, generally confirmed in the National Donor Register. Looking back, the majority of non-donor families resolved their dilemma by justifying their decision with external arguments (lack of time, information etc.). Some non-donor families would like to be supported during decision-making. The discrepancy between general willingness to donate and the actual refusal of a donation request can be explained by multiple factors, with a cumulative effect. Firstly, half of the participants (most non-donor families) stated that they felt that they were not competent to decide in such a crisis and they seem to struggle with utilitarian considerations against their wish to protect the body. Secondly, non-donor families refused telling that they did not know the deceased's wishes or contesting posthumous autonomy of the eligible. Thirdly, the findings emphasise the importance of Donor Registration, because it seems to prevent dilemmas in decision-making, at least for donor families. Discrepancies between willingness to consent to donate and refusal at the bedside can be attributed to an unresolved dilemma: aiding people or protect the body of the deceased. Non-donor families felt incompetent to decide. They refused consent for donation, since their deceased had not given any directive. When ethical considerations do not lead to an unambiguous answer, situational factors were pivotal. Relatives of unregistered eligible donors are more prone to unstable decisions. To overcome ambivalence, coaching during decision-making is worth investigation.

Post-Marketing Regulation of Medicines Withdrawn from the Market Because of Drug-Attributed Deaths: An Analysis of Justification.

PubMed

Onakpoya, Igho J; Heneghan, Carl J; Aronson, Jeffrey K

2017-05-01

Several medicinal products have been withdrawn from the market because of drug-attributed deaths. However, there has been no investigation of whether such withdrawals were justified, and the extent to which confirmatory studies are used to investigate drug-adverse event relationships when deaths are reported is uncertain. We documented medicinal products withdrawn from the market because of drug-attributed deaths, identified confirmatory studies investigating the drug-adverse event relationships, examined whether withdrawals of medicinal products because of drug-attributed deaths after marketing were justified based on a mechanistic analysis, and examined the trends over time. We searched electronic and non-electronic sources to identify medicinal products that were withdrawn because of drug-attributed deaths. We used a previously published algorithm to examine whether the withdrawals of products were justified. We then searched PubMed and Google Scholar to identify studies investigating the drug-adverse event relationships, used the Oxford Centre for Evidence-Based Medicine criteria to document the levels of evidence, and assessed whether the evidence of an association was confirmed. We included 83 medicinal products. The reasons for withdrawal appeared to have been justified in 80 cases (96%). The median interval between the first reported adverse reaction that was related to the cause of death and the first reported death was 1 year (interquartile range = 1-3); products were withdrawn sooner when the interval between the first reported relevant adverse reaction and the first death was shorter. Confirmatory studies were conducted in 57 instances (69%), and there was evidence of an association in 52 cases (63%). Four products (5%) were re-introduced after initial withdrawal. Regulatory authorities have been justified in making withdrawal decisions when deaths have been attributed to medicinal products, using the precautionary principle when alternative decisions could have been made. Medicinal products are likely to be quickly withdrawn from the market when there is a short interval to the first reported deaths. The use of an algorithm such as we have used in this study could help to expedite the process of decision making.

A Fine-Grained API Link Prediction Approach Supporting CMDA Mashup Recommendation

NASA Astrophysics Data System (ADS)

Zhang, J.; Bao, Q.; Lee, T. J.; Ramachandran, R.; Lee, S.; Pan, L.; Gatlin, P. N.; Maskey, M.

2017-12-01

Service (API) discovery and recommendation is key to the wide spread of service oriented architecture and service oriented software engineering. Service recommendation typically relies on service linkage prediction calculated by the semantic distances (or similarities) among services based on their collection of inherent attributes. Given a specific context (mashup goal), however, different attributes may contribute differently to a service linkage. In this work, instead of training a model for all attributes as a whole, a novel approach is presented to simultaneously train separate models for individual attributes. Our contributions are summarized in three-fold. First is that we have developed a scalable attribute-level data model, featuring scalability and extensibility. We have extended Multiplicative Attribute Graph (MAG) model to represent node profiles featuring rich categorical attributes, while relaxing its constraint of requiring a priori knowledge of predefined attributes. LDA is leveraged to dynamically identify attributes based on attribute modeling, and multiple Gaussian fit is applied to find global optimal values. The second contribution is that we have seamlessly integrated the latent relationships between API attributes as well as observed network structure based on historical API usage data. Such a layered information model enables us to predict the probability of a link between two APIs based on their attribute link affinities carrying a variety of information including meta data, semantic data, historical usage data, as well as crowdsourcing user comments and annotations. The third contribution is that we have developed a finegrained context-aware mashup-API recommendation technique. On top of individual models trained for separate attributes, a dedicated layer is trained to represent the latent attribute distribution regarding mashup purpose, i.e., sensitivity of attributes to context. Thus, given the description of an intended mashup, the attributes sensitive to the goal will be identified, and corresponding attribute models will be exploited to compute the possibility of API linkages under the context. Such a layered model increases search accuracy.

The Influence of Lived Experience with Addiction and Recovery on Practice-Related Decisions among Professionals Working in Addiction Agencies Serving Women

ERIC Educational Resources Information Center

Novotna, Gabriela; Dobbins, Maureen; Jack, Susan M.; Sword, Wendy; Niccols, Alison; Brooks, Sandy; Henderson, Joanna

2013-01-01

Aims: The study objectives were to: (1) understand the value attributed to the lived experience of addiction and recovery among professionals working in addiction agencies serving women in Canada and (2) describe how lived experience influence practice-related decision-making. Methods: A descriptive qualitative study was conducted with a…

Bad Luck or Bad Decisions: College Students' Perceptions of the Reasons for and Consequences of Their Alcohol Overdose

ERIC Educational Resources Information Center

Reis, Janet

2007-01-01

Reasons for and immediate consequences of an alcohol overdose were explored for 217 undergraduate students requiring a medical emergency transport because of excessive alcohol consumption. The sample was categorized into 26 students attributing their overdose solely to bad luck and 191 students citing bad decision making as an explanation. A…

Satisficing Decision-Making in Supervisory Control. Part 2.

DTIC Science & Technology

1986-07-31

purpose of the United States Government. C-P Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge, Massachusetts 02139...of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA 02139 Satisficing Decision-Making in Supervisory Control Leonid Charny...example, that there are two attributes, speed and accuracy, and one is selecting a robot manipulator based -4n these two parameters. A set of alternatives

Understanding Decision-Making in Specialized Domestic Violence Courts: Can Contemporary Theoretical Frameworks Help Guide These Decisions?

PubMed

Pinchevsky, Gillian M

2016-05-22

This study fills a gap in the literature by exploring the utility of contemporary courtroom theoretical frameworks-uncertainty avoidance, causal attribution, and focal concerns-for explaining decision-making in specialized domestic violence courts. Using data from two specialized domestic violence courts, this study explores the predictors of prosecutorial and judicial decision-making and the extent to which these factors are congruent with theoretical frameworks often used in studies of court processing. Findings suggest that these theoretical frameworks only partially help explain decision-making in the courts under study. A discussion of the findings and implications for future research is provided. © The Author(s) 2016.

Identifying Important Attributes for Prognostic Prediction in Traumatic Brain Injury Patients. A Hybrid Method of Decision Tree and Neural Network.

PubMed

Pourahmad, Saeedeh; Hafizi-Rastani, Iman; Khalili, Hosseinali; Paydar, Shahram

2016-10-17

Generally, traumatic brain injury (TBI) patients do not have a stable condition, particularly after the first week of TBI. Hence, indicating the attributes in prognosis through a prediction model is of utmost importance since it helps caregivers with treatment-decision options, or prepares the relatives for the most-likely outcome. This study attempted to determine and order the attributes in prognostic prediction in TBI patients, based on early clinical findings. A hybrid method was employed, which combines a decision tree (DT) and an artificial neural network (ANN) in order to improve the modeling process. The DT approach was applied as the initial analysis of the network architecture to increase accuracy in prediction. Afterwards, the ANN structure was mapped from the initial DT based on a part of the data. Subsequently, the designed network was trained and validated by the remaining data. 5-fold cross-validation method was applied to train the network. The area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and accuracy rate were utilized as performance measures. The important attributes were then determined from the trained network using two methods: change of mean squared error (MSE), and sensitivity analysis (SA). The hybrid method offered better results compared to the DT method. The accuracy rate of 86.3 % vs. 82.2 %, sensitivity value of 55.1 % vs. 47.6 %, specificity value of 93.6 % vs. 91.1 %, and the area under the ROC curve of 0.705 vs. 0.695 were achieved for the hybrid method and DT, respectively. However, the attributes' order by DT method was more consistent with the clinical literature. The combination of different modeling methods can enhance their performance. However, it may create some complexities in computations and interpretations. The outcome of the present study could deliver some useful hints in prognostic prediction on the basis of early clinical findings for TBI patients.

Patient and Oncology Nurse Preferences for the Treatment Options in Advanced Melanoma: A Discrete Choice Experiment.

PubMed

Liu, Frank Xiaoqing; Witt, Edward A; Ebbinghaus, Scot; DiBonaventura Beyer, Grace; Basurto, Enrique; Joseph, Richard W

2017-10-25

Understanding the perceptions of patients and oncology nurses about the relative importance of benefits and risks associated with newer treatments of advanced melanoma can help to inform clinical decision-making. The aims of this study were to quantify and compare the views of patients and oncology nurses regarding the importance of attributes of treatments of advanced melanoma. A discrete choice experiment (DCE) was conducted in US-based oncology nurses and patients diagnosed with advanced melanoma. Patients and nurses were enlisted through online panels. In a series of scenarios, respondents had to choose between 2 hypothetical treatments, each with 7 attributes: mode of administration (MoA), dosing schedule (DS), median duration of therapy (DoT), objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and grade 3 or 4 adverse events (AEs). Hierarchical Bayesian logistic regression models were used to estimate preference weights. A total of 200 patients with advanced melanoma and 150 oncology nurses participated. The relative importance estimates of attributes by patients and nurses, respectively, were as follows: OS, 33% and 28%; AEs, 29% and 26%; ORR, 25% and 27%; PFS, 12% and 15%; DS, 2% and 3%; DoT, 0% and 0%; and MoA, 0% and 0%. Both patients and oncology nurses valued OS, ORR, and AEs as the most important treatment attributes for advanced melanoma, followed by PFS, whereas DS, DoT, and MoA were given less value in their treatment decisions. Oncology nurses and patients have similar views on important treatment considerations for advanced melanoma, which can help build trust in shared decision-making.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Eye Movements in Risky Choice

PubMed Central

Hermens, Frouke; Matthews, William J.

2015-01-01

Abstract We asked participants to make simple risky choices while we recorded their eye movements. We built a complete statistical model of the eye movements and found very little systematic variation in eye movements over the time course of a choice or across the different choices. The only exceptions were finding more (of the same) eye movements when choice options were similar, and an emerging gaze bias in which people looked more at the gamble they ultimately chose. These findings are inconsistent with prospect theory, the priority heuristic, or decision field theory. However, the eye movements made during a choice have a large relationship with the final choice, and this is mostly independent from the contribution of the actual attribute values in the choice options. That is, eye movements tell us not just about the processing of attribute values but also are independently associated with choice. The pattern is simple—people choose the gamble they look at more often, independently of the actual numbers they see—and this pattern is simpler than predicted by decision field theory, decision by sampling, and the parallel constraint satisfaction model. © 2015 The Authors. Journal of Behavioral Decision Making published by John Wiley & Sons Ltd. PMID:27522985

Application fuzzy multi-attribute decision analysis method to prioritize project success criteria

NASA Astrophysics Data System (ADS)

Phong, Nguyen Thanh; Quyen, Nguyen Le Hoang Thuy To

2017-11-01

Project success is a foundation for project owner to manage and control not only for the current project but also for future potential projects in construction companies. However, identifying the key success criteria for evaluating a particular project in real practice is a challenging task. Normally, it depends on a lot of factors, such as the expectation of the project owner and stakeholders, triple constraints of the project (cost, time, quality), and company's mission, vision, and objectives. Traditional decision-making methods for measuring the project success are usually based on subjective opinions of panel experts, resulting in irrational and inappropriate decisions. Therefore, this paper introduces a multi-attribute decision analysis method (MADAM) for weighting project success criteria by using fuzzy Analytical Hierarchy Process approach. It is found that this method is useful when dealing with imprecise and uncertain human judgments in evaluating project success criteria. Moreover, this research also suggests that although cost, time, and quality are three project success criteria projects, the satisfaction of project owner and acceptance of project stakeholders with the completed project criteria is the most important criteria for project success evaluation in Vietnam.

Adaptive management in the U.S. National Wildlife Refuge System: Science-management partnerships for conservation delivery

USGS Publications Warehouse

Moore, C.T.; Lonsdorf, E.V.; Knutson, M.G.; Laskowski, H.P.; Lor, S.K.

2011-01-01

Adaptive management is an approach to recurrent decision making in which uncertainty about the decision is reduced over time through comparison of outcomes predicted by competing models against observed values of those outcomes. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service is a large land management program charged with making natural resource management decisions, which often are made under considerable uncertainty, severe operational constraints, and conditions that limit ability to precisely carry out actions as intended. The NWRS presents outstanding opportunities for the application of adaptive management, but also difficult challenges. We describe two cooperative programs between the Fish and Wildlife Service and the U.S. Geological Survey to implement adaptive management at scales ranging from small, single refuge applications to large, multi-refuge, multi-region projects. Our experience to date suggests three important attributes common to successful implementation: a vigorous multi-partner collaboration, practical and informative decision framework components, and a sustained commitment to the process. Administrators in both agencies should consider these attributes when developing programs to promote the use and acceptance of adaptive management in the NWRS. ?? 2010 .

Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data

Treesearch

Andrew T. Hudak; Nicholas L. Crookston; Jeffrey S. Evans; David E. Hall; Michael J. Falkowski

2008-01-01

Meaningful relationships between forest structure attributes measured in representative field plots on the ground and remotely sensed data measured comprehensively across the same forested landscape facilitate the production of maps of forest attributes such as basal area (BA) and tree density (TD). Because imputation methods can efficiently predict multiple response...

Objective consensus from decision trees.

PubMed

Putora, Paul Martin; Panje, Cedric M; Papachristofilou, Alexandros; Dal Pra, Alan; Hundsberger, Thomas; Plasswilm, Ludwig

2014-12-05

Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources. Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus. Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters. Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

DOE PAGES

Azim, Riyasat; Li, Fangxing; Xue, Yaosuo; ...

2017-07-14

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

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

Azim, Riyasat; Li, Fangxing; Xue, Yaosuo

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less

Fuzzy logic system able to detect interesting areas of a video sequence

NASA Astrophysics Data System (ADS)

De Vleeschouwer, Christophe; Marichal, Xavier; Delmot, Thierry; Macq, Benoit M. M.

1997-06-01

This paper introduces an automatic tool able to analyze the picture according to the semantic interest an observer attributes to its content. Its aim is to give a 'level of interest' to the distinct areas of the picture extracted by any segmentation tool. For the purpose of dealing with semantic interpretation of images, a single criterion is clearly insufficient because the human brain, due to its a priori knowledge and its huge memory of real-world concrete scenes, combines different subjective criteria in order to assess its final decision. The developed method permits such combination through a model using assumptions to express some general subjective criteria. Fuzzy logic enables the user to encode knowledge in a form that is very close the way experts think about the decision process. This fuzzy modeling is also well suited to represent multiple collaborating or even conflicting experts opinions. Actually, the assumptions are verified through a non-hierarchical strategy that considers them in a random order, each partial result contributing to the final one. Presented results prove that the tool is effective for a wide range of natural pictures. It is versatile and flexible in that it can be used stand-alone or can take into account any a priori knowledge about the scene.

Rapid humanitarian assessments and rationality: a value-of-information study from Iraq, 2003-04.

PubMed

Benini, Aldo; Conley, Charles

2007-03-01

Rapid assessments are one of the standard informational tools in humanitarian response and are supposed to contribute to rational decision-making.(1) The extent to which the assessment organisation itself behaves rationally, however, is an open question. This can be evaluated against multiple criteria, such as the cost and value of the information it collects and its ability to adapt flexibly design or samples when the survey environment changes unforeseeably. An unusual data constellation from two concurrent recent (2003-04) rapid assessments in northern Iraq permits us to model part of the actual assessment behaviour in terms of geographical, community and prior substantive information attributes. The model correctly predicts the decisions, in 79 per cent of the 2,425 local communities in focus, that data collector teams in the Emergency Mine Action Survey made to visit or not to visit. The analysis demonstrates variably rational behaviour under conditions of insecurity, repeated regrouping and incomplete sampling frames. A pronounced bias towards very small rural settlements is irrational for the overall results, but may be a rational strategy of individual survey workers seeking to prolong their employment. Implications for future assessments are sketched in the areas of tools for urban surveys, greater adaptability, including early feedback from users, and sensibility to value-of-information concepts.

Stimulus Value Signals in Ventromedial PFC Reflect the Integration of Attribute Value Signals Computed in Fusiform Gyrus and Posterior Superior Temporal Gyrus

PubMed Central

Lim, Seung-Lark; O'Doherty, John P.

2013-01-01

We often have to make choices among multiattribute stimuli (e.g., a food that differs on its taste and health). Behavioral data suggest that choices are made by computing the value of the different attributes and then integrating them into an overall stimulus value signal. However, it is not known whether this theory describes the way the brain computes the stimulus value signals, or how the underlying computations might be implemented. We investigated these questions using a human fMRI task in which individuals had to evaluate T-shirts that varied in their visual esthetic (e.g., color) and semantic (e.g., meaning of logo printed in T-shirt) components. We found that activity in the fusiform gyrus, an area associated with the processing of visual features, correlated with the value of the visual esthetic attributes, but not with the value of the semantic attributes. In contrast, activity in posterior superior temporal gyrus, an area associated with the processing of semantic meaning, exhibited the opposite pattern. Furthermore, both areas exhibited functional connectivity with an area of ventromedial prefrontal cortex that reflects the computation of overall stimulus values at the time of decision. The results provide supporting evidence for the hypothesis that some attribute values are computed in cortical areas specialized in the processing of such features, and that those attribute-specific values are then passed to the vmPFC to be integrated into an overall stimulus value signal to guide the decision. PMID:23678116

Stimulus value signals in ventromedial PFC reflect the integration of attribute value signals computed in fusiform gyrus and posterior superior temporal gyrus.

PubMed

Lim, Seung-Lark; O'Doherty, John P; Rangel, Antonio

2013-05-15

We often have to make choices among multiattribute stimuli (e.g., a food that differs on its taste and health). Behavioral data suggest that choices are made by computing the value of the different attributes and then integrating them into an overall stimulus value signal. However, it is not known whether this theory describes the way the brain computes the stimulus value signals, or how the underlying computations might be implemented. We investigated these questions using a human fMRI task in which individuals had to evaluate T-shirts that varied in their visual esthetic (e.g., color) and semantic (e.g., meaning of logo printed in T-shirt) components. We found that activity in the fusiform gyrus, an area associated with the processing of visual features, correlated with the value of the visual esthetic attributes, but not with the value of the semantic attributes. In contrast, activity in posterior superior temporal gyrus, an area associated with the processing of semantic meaning, exhibited the opposite pattern. Furthermore, both areas exhibited functional connectivity with an area of ventromedial prefrontal cortex that reflects the computation of overall stimulus values at the time of decision. The results provide supporting evidence for the hypothesis that some attribute values are computed in cortical areas specialized in the processing of such features, and that those attribute-specific values are then passed to the vmPFC to be integrated into an overall stimulus value signal to guide the decision.

Computer Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2013-03-01

the decisions made by each individual modality. Fusion of features is the simple concatenation of feature vectors from multiple modalities to be...of Features BayesNet MDL 330 LibSVM PCA 80 J48 Wrapper Evaluator 11 3.5.3 Ensemble Based Decision Level Fusion. In ensemble learning multiple ...The high fusion percentages validate our hypothesis that by combining features from multiple modalities, classification accuracy can be improved. As

Urban Health Indicator Tools of the Physical Environment: a Systematic Review.

PubMed

Pineo, Helen; Glonti, Ketevan; Rutter, Harry; Zimmermann, Nici; Wilkinson, Paul; Davies, Michael

2018-04-16

Urban health indicator (UHI) tools provide evidence about the health impacts of the physical urban environment which can be used in built environment policy and decision-making. Where UHI tools provide data at the neighborhood (and lower) scale they can provide valuable information about health inequalities and environmental deprivation. This review performs a census of UHI tools and explores their nature and characteristics (including how they represent, simplify or address complex systems) to increase understanding of their potential use by municipal built environment policy and decision-makers. We searched seven bibliographic databases, four key journals and six practitioner websites and conducted Google searches between January 27, 2016 and February 24, 2016 for UHI tools. We extracted data from primary studies and online indicator systems. We included 198 documents which identified 145 UHI tools comprising 8006 indicators, from which we developed a taxonomy. Our taxonomy classifies the significant diversity of UHI tools with respect to topic, spatial scale, format, scope and purpose. The proportions of UHI tools which measure data at the neighborhood and lower scale, and present data via interactive maps, have both increased over time. This is particularly relevant to built environment policy and decision-makers, reflects growing analytical capability and offers the potential for improved understanding of the complexity of influences on urban health (an aspect noted as a particular challenge by some indicator producers). The relation between urban health indicators and health impacts attributable to modifiable environmental characteristics is often indirect. Furthermore, the use of UHI tools in policy and decision-making appears to be limited, thus raising questions about the continued development of such tools by multiple organisations duplicating scarce resources. Further research is needed to understand the requirements of built environment policy and decision-makers, public health professionals and local communities regarding the form and presentation of indicators which support their varied objectives.

Selecting essential information for biosurveillance--a multi-criteria decision analysis.

PubMed

Generous, Nicholas; Margevicius, Kristen J; Taylor-McCabe, Kirsten J; Brown, Mac; Daniel, W Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.

The Decision Path Not Taken

PubMed Central

Connor, Charles E.; Stuphorn, Veit

2017-01-01

Real-life decisions often involve multiple intermediate choices among competing, interdependent options. Lorteije et al. (2015) introduce a new paradigm for dissecting the neural strategies underlying such decisions. PMID:26402598

Science in Service to Society - A Review of Applied Science & Decision Support Development Serving Multiple Economic Sectors

NASA Astrophysics Data System (ADS)

Mahoney, W. P., III

2015-12-01

For more than 30 years, the Research Applications Laboratory (RAL) of the National Center for Atmospheric Research (NCAR) has conducted fundamental and applied research focused on developing decision support tools spanning multiple end-user groups representing a variety of economic sectors. Technology transfer is a primary mission of the laboratory where innovation is a key attribute and multidisciplinary research and development are the norm. Application areas include, aviation, surface transportation, wind and solar energy prediction, climate, weather and health, numerical weather prediction, biological and chemical plume dispersion for homeland security, flood prediction and water resource management, soil condition and crop maturity prediction among other application areas. The majority of the developed capabilities have been operationalized by the public, private, and academic sectors. Several commercial companies have been successfully formed around the technologies (e.g., Weather Information Technologies, Inc., Peak Weather Resources, Inc., and Global Weather Corporation) and many existing companies have improved their products by utilizing the RAL-developed weather system advancements (The Weather Channel, WSI, Schneider Electric, Xcel Energy, United Airlines, Vaisala, Panasonic, Idaho Power, etc.). The economic benefit estimates of implementing these technologies have ranged from billions of dollars in avoided commercial aircraft accidents over the last 30 years to 10s of millions of dollars of annual savings by state departments of transportation via more efficient ice and snow maintenance operations. Research and development at RAL is connected to the Broader Impacts Criterion of NSF and its focus on research that results in significant economic or societal impact. This talk will describe our research-to-operations process and discuss several technology transfer examples that have led to commercial opportunities.

Using histograms to introduce randomization in the generation of ensembles of decision trees

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick; Littau, David

2005-02-22

A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.

Intersections of discrimination due to unemployment and mental health problems: the role of double stigma for job- and help-seeking behaviors.

PubMed

Staiger, Tobias; Waldmann, Tamara; Oexle, Nathalie; Wigand, Moritz; Rüsch, Nicolas

2018-05-21

The everyday lives of unemployed people with mental health problems can be affected by multiple discrimination, but studies about double stigma-an overlap of identities and experiences of discrimination-in this group are lacking. We therefore studied multiple discrimination among unemployed people with mental health problems and its consequences for job- and help-seeking behaviors. Everyday discrimination and attributions of discrimination to unemployment and/or to mental health problems were examined among 301 unemployed individuals with mental health problems. Job search self-efficacy, barriers to care, and perceived need for treatment were compared among four subgroups, depending on attributions of experienced discrimination to unemployment and to mental health problems (group i); neither to unemployment nor to mental health problems (group ii); mainly to unemployment (group iii); or mainly to mental health problems (group iv). In multiple regressions among all participants, higher levels of discrimination predicted reduced job search self-efficacy and higher barriers to care; and attributions of discrimination to unemployment were associated with increased barriers to care. In ANOVAs for subgroup comparisons, group i participants, who attributed discrimination to both unemployment and mental health problems, reported lower job search self-efficacy, more perceived stigma-related barriers to care and more need for treatment than group iii participants, as well as more stigma-related barriers to care than group iv. Multiple discrimination may affect job search and help-seeking among unemployed individuals with mental health problems. Interventions to reduce public stigma and to improve coping with multiple discrimination for this group should be developed.

Decision Making in Adults with ADHD

ERIC Educational Resources Information Center

Montyla, Timo; Still, Johanna; Gullberg, Stina; Del Missier, Fabio

2012-01-01

Objectives: This study examined decision-making competence in ADHD by using multiple decision tasks with varying demands on analytic versus affective processes. Methods: Adults with ADHD and healthy controls completed two tasks of analytic decision making, as measured by the Adult Decision-Making Competence (A-DMC) battery, and two affective…

Estimation of effective dose and lifetime attributable risk from multiple head CT scans in ventriculoperitoneal shunted children.

PubMed

Aw-Zoretic, J; Seth, D; Katzman, G; Sammet, S

2014-10-01

The purpose of this review is to determine the averaged effective dose and lifetime attributable risk factor from multiple head computed tomography (CT) dose data on children with ventriculoperitoneal shunts (VPS). A total of 422 paediatric head CT exams were found between October 2008 and January 2011 and retrospectively reviewed. The CT dose data was weighted with the latest IRCP 103 conversion factor to obtain the effective dose per study and the averaged effective dose was calculated. Estimates of the lifetime attributable risk were also calculated from the averaged effective dose using a conversion factor from the latest BEIR VII report. Our study found the highest effective doses in neonates and the lowest effective doses were observed in the 10-18 years age group. We estimated a 0.007% potential increase risk in neonates and 0.001% potential increased risk in teenagers over the base risk. Multiple head CTs in children equates to a slight potential increase risk in lifetime attributable risk over the baseline risk for cancer, slightly higher in neonates relative to teenagers. The potential risks versus clinical benefit must be assessed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Shared Decision Making and Autonomy Among US Participants with Multiple Sclerosis in the NARCOMS Registry

PubMed Central

Thomas, Nina; Tyry, Tuula; Fox, Robert J.; Salter, Amber

2017-01-01

Background: Treatment decisions in multiple sclerosis (MS) are affected by many factors and are made by the patient, doctor, or both. With new disease-modifying therapies (DMTs) emerging, the complexity surrounding treatment decisions is increasing, further emphasizing the importance of understanding decision-making preferences. Methods: North American Research Committee on Multiple Sclerosis (NARCOMS) Registry participants completed the Fall 2014 Update survey, which included the Control Preferences Scale (CPS). The CPS consists of five images showing different patient/doctor roles in treatment decision making. The images were collapsed to three categories: patient-centered, shared, and physician-centered decision-making preferences. Associations between decision-making preferences and demographic and clinical factors were evaluated using multivariable logistic regression. Results: Of 7009 participants, 79.3% were women and 93.5% were white (mean [SD] age, 57.6 [10.3] years); 56.7% reported a history of relapses. Patient-centered decision making was most commonly preferred by participants (47.9%), followed by shared decision making (SDM; 42.8%). SDM preference was higher for women and those taking DMTs and increased with age and disease duration (all P < .05). Patient-centered decisions were most common for respondents not taking a DMT at the time of the survey and were preferred by those who had no DMT history compared with those who had previously taken a DMT (P < .0001). There was no difference in SDM preference by current MS disease course after adjusting for other disease-related factors. Conclusions: Responders reported most commonly considering their doctor's opinion before making a treatment decision and making decisions jointly with their doctor. DMT use, gender, and age were associated with decision-making preference. PMID:29270088

What Do Patients Want from Otolaryngologists? A Discrete Choice Experiment.

PubMed

Naunheim, Matthew R; Rathi, Vinay K; Naunheim, Margaret L; Alkire, Blake C; Lam, Allen C; Song, Phillip C; Shrime, Mark G

2017-10-01

Objectives Patient preferences are crucial for the delivery of patient-centered care. Discrete choice experiments (DCEs) are an emerging quantitative methodology used for understanding these preferences. In this study, we employed DCE techniques to understand the preferences of patients presenting for an ear, nose, and throat clinic visit. Study Design DCE. Setting Decision science laboratory. Methods A DCE survey of 5 attributes-wait time, physician experience, physician personality, utilization of visit time, and cost/copayment-was constructed with structured qualitative interviews with patients. The DCE was administered to participants from the general population, who chose among hypothetical scenarios that varied across these attributes. A conditional logit model was used to determine relative attribute importance, with a separate logit model for determining subject effects. Results A total of 161 participants were included. Cost/copayment had the greatest impact on decision making (importance, 32.2%), followed by wait time and physician experience (26.5% and 24.7%, respectively). Physician personality mattered least (4.7%), although all attributes were significantly correlated to decision making. Participants preferred doctors who spent more time performing physical examination than listening or explaining. Participants were willing to pay $52 extra to avoid a 4-week delay in appointment time; $87 extra for a physician with 10 years of experience (vs 0 years); and $9 extra for a caring, friendly, and compassionate doctor (vs formal, efficient, and business-like). Conclusion DCEs allow for powerful economic analyses that may help physicians understand patient preferences. Our model showed that cost is an important factor to patients and that patients are willing to pay extra for timely appointments, experience, and thorough physical examination.

Determining rules for closing customer service centers: A public utility company's fuzzy decision

NASA Technical Reports Server (NTRS)

Dekorvin, Andre; Shipley, Margaret F.

1992-01-01

In the present work, we consider the general problem of knowledge acquisition under uncertainty. A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision was made. Unique to this work is the fuzzy set representation of the conditions or attributes upon which the decision make may base his fuzzy set decision. From our examples, we infer certain and possible rules containing fuzzy terms. It should be stressed that the procedure determines how closely the expert follows the conditions under consideration in making his decision. We offer two examples pertaining to the possible decision to close a customer service center of a public utility company. In the first example, the decision maker does not follow too closely the conditions. In the second example, the conditions are much more relevant to the decision of the expert.

Clinical decision regret among critical care nurses: a qualitative analysis.

PubMed

Arslanian-Engoren, Cynthia; Scott, Linda D

2014-01-01

Decision regret is a negative cognitive emotion associated with experiences of guilt and situations of interpersonal harm. These negative affective responses may contribute to emotional exhaustion in critical care nurses (CCNs), increased staff turnover rates and high medication error rates. Yet, little is known about clinical decision regret among CCNs or the conditions or situations (e.g., feeling sleepy) that may precipitate its occurrence. To examine decision regret among CCNs, with an emphasis on clinical decisions made when nurses were most sleepy. A content analytic approach was used to examine the narrative descriptions of clinical decisions by CCNs when sleepy. Six decision regret themes emerged that represented deviations in practice or performance behaviors that were attributed to fatigued CCNs. While 157 CCNs disclosed a clinical decision they made at work while sleepy, the prevalence may be underestimated and warrants further investigation. Copyright © 2014 Elsevier Inc. All rights reserved.

Comparing Selections of Environmental Variables for Ecological Studies: A Focus on Terrain Attributes.

PubMed

Lecours, Vincent; Brown, Craig J; Devillers, Rodolphe; Lucieer, Vanessa L; Edinger, Evan N

2016-01-01

Selecting appropriate environmental variables is a key step in ecology. Terrain attributes (e.g. slope, rugosity) are routinely used as abiotic surrogates of species distribution and to produce habitat maps that can be used in decision-making for conservation or management. Selecting appropriate terrain attributes for ecological studies may be a challenging process that can lead users to select a subjective, potentially sub-optimal combination of attributes for their applications. The objective of this paper is to assess the impacts of subjectively selecting terrain attributes for ecological applications by comparing the performance of different combinations of terrain attributes in the production of habitat maps and species distribution models. Seven different selections of terrain attributes, alone or in combination with other environmental variables, were used to map benthic habitats of German Bank (off Nova Scotia, Canada). 29 maps of potential habitats based on unsupervised classifications of biophysical characteristics of German Bank were produced, and 29 species distribution models of sea scallops were generated using MaxEnt. The performances of the 58 maps were quantified and compared to evaluate the effectiveness of the various combinations of environmental variables. One of the combinations of terrain attributes-recommended in a related study and that includes a measure of relative position, slope, two measures of orientation, topographic mean and a measure of rugosity-yielded better results than the other selections for both methodologies, confirming that they together best describe terrain properties. Important differences in performance (up to 47% in accuracy measurement) and spatial outputs (up to 58% in spatial distribution of habitats) highlighted the importance of carefully selecting variables for ecological applications. This paper demonstrates that making a subjective choice of variables may reduce map accuracy and produce maps that do not adequately represent habitats and species distributions, thus having important implications when these maps are used for decision-making.

Structuring and Judgment in Decision Technology.

DTIC Science & Technology

1981-01-01

partly because it avoids weighting questions in which only remotely related attributes need to be compared. But there are several potential problems...weighting questions in which only remotely related attributes need to be compared. But there are also problems; * C- for example, respondents may add to an...favoring the nuclear option assigned weights which were similar to those preferring coal. All groups gave the highest weight to the health/safety

Using Technical Performance Measures

NASA Technical Reports Server (NTRS)

Garrett, Christopher J.; Levack, Daniel J. H.; Rhodes, Russel E.

2011-01-01

All programs have requirements. For these requirements to be met, there must be a means of measurement. A Technical Performance Measure (TPM) is defined to produce a measured quantity that can be compared to the requirement. In practice, the TPM is often expressed as a maximum or minimum and a goal. Example TPMs for a rocket program are: vacuum or sea level specific impulse (lsp), weight, reliability (often expressed as a failure rate), schedule, operability (turn-around time), design and development cost, production cost, and operating cost. Program status is evaluated by comparing the TPMs against specified values of the requirements. During the program many design decisions are made and most of them affect some or all of the TPMs. Often, the same design decision changes some TPMs favorably while affecting other TPMs unfavorably. The problem then becomes how to compare the effects of a design decision on different TPMs. How much failure rate is one second of specific impulse worth? How many days of schedule is one pound of weight worth? In other words, how to compare dissimilar quantities in order to trade and manage the TPMs to meet all requirements. One method that has been used successfully and has a mathematical basis is Utility Analysis. Utility Analysis enables quantitative comparison among dissimilar attributes. It uses a mathematical model that maps decision maker preferences over the tradeable range of each attribute. It is capable of modeling both independent and dependent attributes. Utility Analysis is well supported in the literature on Decision Theory. It has been used at Pratt & Whitney Rocketdyne for internal programs and for contracted work such as the J-2X rocket engine program. This paper describes the construction of TPMs and describes Utility Analysis. It then discusses the use of TPMs in design trades and to manage margin during a program using Utility Analysis.

"Only you can play with me!" Children's inclusive decision making, reasoning, and emotions based on peers' gender and behavior problems.

PubMed

Peplak, Joanna; Song, Ju-Hyun; Colasante, Tyler; Malti, Tina

2017-10-01

This study examined the development of children's decisions, reasoning, and emotions in contexts of peer inclusion/exclusion. We asked an ethnically diverse sample of 117 children aged 4years (n=59; 60% girls) and 8years (n=58; 49% girls) to choose between including hypothetical peers of the same or opposite gender and with or without attention deficit/hyperactivity problems and aggressive behavior. Children also provided justifications for, and emotions associated with, their inclusion decisions. Both 4- and 8-year-olds predominantly chose to include the in-group peer (i.e., the same-gender peer and peers without behavior problems), thereby demonstrating a normative in-group inclusive bias. Nevertheless, children included the out-group peer more in the gender context than in the behavior problem contexts. The majority of children reported group functioning-related, group identity-related, and stereotype-related reasoning after their in-group inclusion decisions, and they associated happy feelings with such decisions. Although most children attributed sadness to the excluded out-group peer, they attributed more anger to the excluded out-group peer in the aggression context compared with other contexts. We discuss the implications of our findings for current theorizing about children's social-cognitive and emotional development in contexts of peer inclusion and exclusion. Copyright © 2017 Elsevier Inc. All rights reserved.

New Splitting Criteria for Decision Trees in Stationary Data Streams.

PubMed

Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Rutkowski, Leszek; Duda, Piotr; Jaworski, Maciej

2018-06-01

The most popular tools for stream data mining are based on decision trees. In previous 15 years, all designed methods, headed by the very fast decision tree algorithm, relayed on Hoeffding's inequality and hundreds of researchers followed this scheme. Recently, we have demonstrated that although the Hoeffding decision trees are an effective tool for dealing with stream data, they are a purely heuristic procedure; for example, classical decision trees such as ID3 or CART cannot be adopted to data stream mining using Hoeffding's inequality. Therefore, there is an urgent need to develop new algorithms, which are both mathematically justified and characterized by good performance. In this paper, we address this problem by developing a family of new splitting criteria for classification in stationary data streams and investigating their probabilistic properties. The new criteria, derived using appropriate statistical tools, are based on the misclassification error and the Gini index impurity measures. The general division of splitting criteria into two types is proposed. Attributes chosen based on type- splitting criteria guarantee, with high probability, the highest expected value of split measure. Type- criteria ensure that the chosen attribute is the same, with high probability, as it would be chosen based on the whole infinite data stream. Moreover, in this paper, two hybrid splitting criteria are proposed, which are the combinations of single criteria based on the misclassification error and Gini index.

Recent progress in the development of ISO 19751

NASA Astrophysics Data System (ADS)

Farnand, Susan P.; Dalal, Edul N.; Ng, Yee S.

2006-01-01

A small number of general visual attributes have been recognized as essential in describing image quality. These include micro-uniformity, macro-uniformity, colour rendition, text and line quality, gloss, sharpness, and spatial adjacency or temporal adjacency attributes. The multiple-part International Standard discussed here was initiated by the INCITS W1 committee on the standardization of office equipment to address the need for unambiguously documented procedures and methods, which are widely applicable over the multiple printing technologies employed in office applications, for the appearance-based evaluation of these visually significant image quality attributes of printed image quality. 1,2 The resulting proposed International Standard, for which ISO/IEC WD 19751-1 3 presents an overview and an outline of the overall procedure and common methods, is based on a proposal that was predicated on the idea that image quality could be described by a small set of broad-based attributes. 4 Five ad hoc teams were established (now six since a sharpness team is in the process of being formed) to generate standards for one or more of these image quality attributes. Updates on the colour rendition, text and line quality, and gloss attributes are provided.

A Longitudinal Examination of the Hopelessness Theory of Depression in People Who Have Multiple Sclerosis

PubMed Central

Kneebone, I. I.; Guerrier, S.; Dunmore, E.; Jones, E.; Fife-Schaw, C.

2015-01-01

Purpose. Hopelessness theory predicts that negative attributional style will interact with negative life events over time to predict depression. The intention of this study was to test this in a population who are at greater risk of negative life events, people with Multiple Sclerosis (MS). Method. Data, including measures of attributional style, negative life events, and depressive symptoms, were collected via postal survey in 3 phases, each one a year apart. Results. Responses were received from over 380 participants at each study phase. Negative attributional style was consistently able to predict future depressive symptoms at low to moderate levels of association; however, this ability was not sustained when depressive symptoms at Phase 1 were controlled for. No substantial evidence to support the hypothesised interaction of negative attributional style and negative life events was found. Conclusions. Findings were not supportive of the causal interaction proposed by the hopelessness theory of depression. Further work considering other time frames, using methods to prime attributional style before assessment and specifically assessing the hopelessness subtype of depression, may prove to be more fruitful. Intervention directly to address attributional style should also be considered. PMID:26290622

The Valuation of Scientific and Technical Experiments

NASA Technical Reports Server (NTRS)

Williams, F. E.

1972-01-01

Rational selection of scientific and technical experiments for space missions is studied. Particular emphasis is placed on the assessment of value or worth of an experiment. A specification procedure is outlined and discussed for the case of one decision maker. Experiments are viewed as multi-attributed entities, and a relevant set of attributes is proposed. Alternative methods of describing levels of the attributes are proposed and discussed. The reasonableness of certain simplifying assumptions such as preferential and utility independence is explored, and it is tentatively concluded that preferential independence applies and utility independence appears to be appropriate.

Multiple scattering and the density distribution of a Cs MOT.

PubMed

Overstreet, K; Zabawa, P; Tallant, J; Schwettmann, A; Shaffer, J

2005-11-28

Multiple scattering is studied in a Cs magneto-optical trap (MOT). We use two Abel inversion algorithms to recover density distributions of the MOT from fluorescence images. Deviations of the density distribution from a Gaussian are attributed to multiple scattering.

Reliability and Validity Study of the Mobile Learning Adoption Scale Developed Based on the Diffusion of Innovations Theory

ERIC Educational Resources Information Center

Celik, Ismail; Sahin, Ismail; Aydin, Mustafa

2014-01-01

In this study, a mobile learning adoption scale (MLAS) was developed on the basis of Rogers' (2003) Diffusion of Innovations Theory. The scale that was developed consists of four sections. These sections are as follows: Stages in the innovation-decision process, Types of m-learning decision, Innovativeness level and attributes of m-learning. There…

Reliability and Validity Study of the Mobile Learning Adoption Scale Developed Based on the Diffusion of Innovations Theory

ERIC Educational Resources Information Center

Celik, Ismail; Sahin, Ismail; Aydin, Mustafa

2014-01-01

In this study, a mobile learning adoption scale (MLAS) was developed on the basis of Rogers' (2003) Diffusion of Innovations Theory. The scale that was developed consists of four sections. These sections are as follows: Stages in the innovation-decision process, Types of m-learning decision, Innovativeness level and attributes of m-learning.…

A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging.

PubMed

Nair, Shalini Rajandran; Tan, Li Kuo; Mohd Ramli, Norlisah; Lim, Shen Yang; Rahmat, Kartini; Mohd Nor, Hazman

2013-06-01

To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD). 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3. Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified. Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.

The value of superpower-submitted INDCs in cooperative and non-cooperative action scenarios: economic impact, dynamic risk, and temperature rise

NASA Astrophysics Data System (ADS)

Augustin, C. M.

2015-12-01

As the 2015 Paris climate talks near, policy discussions are focused on "intended nationally determined contributions" (INDCs) submitted in advance of the discussions. As the major global emitters - specifically the United States and China - have already submitted their INDCs, we have a point of comparison for evaluating the relative potential impacts of the proposed targets. By applying integrated assessment models to robust, publicly available data sets,we aim to evaluate the interplay between climate change and economic development, comment on emissions reduction scenarios in cooperative and non-cooperative situations, and assess the dynamic risks of multiple regional emissions scenarios. We use both the RICE model and the C-ROADS model to examine alternative regional outcomes for emissions, climate change, and damages,under different reduction scenarios, including a scenario where geo-engineering plays a prominent role. These simulators allow us to vary emissions, population, and economic levels in China and the United States specifically to comment on the international climate risk impact of actors working jointly - or not - toward a global climate goal. In a complementary piece of analysis we seek to understand the value judgments, trade-offs, and regional policies that would lead to favorable climate finance flows. To reach an international sample of industry decision-makers, we propose a novel application of a standard discrete-choice survey methodology. A conjoint analysis requires a participant to chose between combinations of attributes and identify trade-offs while allowing the researcher to determine the relative importance of each individual attribute by mathematically assessing the impact each attribute could have on total item utility. As climate policy negotiations will consist of allocation of scarce resources and rejection of certain attributes, a conjoint analysis is an ideal tool for evaluating policy outcomes. This research program seeks to provide a commentary useful to policy makers on the most desirable outcomes of the negotiations and other international cooperation.