Decision Making In A High-Tech World: Automation Bias and Countermeasures

NASA Technical Reports Server (NTRS)

Mosier, Kathleen L.; Skitka, Linda J.; Burdick, Mark R.; Heers, Susan T.; Rosekind, Mark R. (Technical Monitor)

1996-01-01

Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.

42 CFR 412.278 - Administrator's review.

Code of Federal Regulations, 2014 CFR

2014-10-01

... or computational errors, or to correct the decision if the evidence that was considered in making the... discretion, may amend the decision to correct mathematical or computational errors, or to correct the...

42 CFR 412.278 - Administrator's review.

Code of Federal Regulations, 2011 CFR

2011-10-01

... or computational errors, or to correct the decision if the evidence that was considered in making the... discretion, may amend the decision to correct mathematical or computational errors, or to correct the...

42 CFR 412.278 - Administrator's review.

Code of Federal Regulations, 2012 CFR

2012-10-01

... or computational errors, or to correct the decision if the evidence that was considered in making the... discretion, may amend the decision to correct mathematical or computational errors, or to correct the...

42 CFR 412.278 - Administrator's review.

Code of Federal Regulations, 2013 CFR

2013-10-01

... or computational errors, or to correct the decision if the evidence that was considered in making the... discretion, may amend the decision to correct mathematical or computational errors, or to correct the...

The Dialectical Utility of Heuristic Processing in Outdoor Adventure Education

ERIC Educational Resources Information Center

Zajchowski, Chris A. B.; Brownlee, Matthew T. J.; Furman, Nate N.

2016-01-01

Heuristics--cognitive shortcuts used in decision-making events--have been paradoxically praised for their contribution to decision-making efficiency and prosecuted for their contribution to decision-making error (Gigerenzer & Gaissmaier, 2011; Gigerenzer, Todd, & ABC Research Group, 1999; Kahneman, 2011; Kahneman, Slovic, & Tversky,…

The development and validation of the clinicians' awareness towards cognitive errors (CATChES) in clinical decision making questionnaire tool.

PubMed

Chew, Keng Sheng; Kueh, Yee Cheng; Abdul Aziz, Adlihafizi

2017-03-21

Despite their importance on diagnostic accuracy, there is a paucity of literature on questionnaire tools to assess clinicians' awareness toward cognitive errors. A validation study was conducted to develop a questionnaire tool to evaluate the Clinician's Awareness Towards Cognitive Errors (CATChES) in clinical decision making. This questionnaire is divided into two parts. Part A is to evaluate the clinicians' awareness towards cognitive errors in clinical decision making while Part B is to evaluate their perception towards specific cognitive errors. Content validation for both parts was first determined followed by construct validation for Part A. Construct validation for Part B was not determined as the responses were set in a dichotomous format. For content validation, all items in both Part A and Part B were rated as "excellent" in terms of their relevance in clinical settings. For construct validation using exploratory factor analysis (EFA) for Part A, a two-factor model with total variance extraction of 60% was determined. Two items were deleted. Then, the EFA was repeated showing that all factor loadings are above the cut-off value of >0.5. The Cronbach's alpha for both factors are above 0.6. The CATChES questionnaire tool is a valid questionnaire tool aimed to evaluate the awareness among clinicians toward cognitive errors in clinical decision making.

Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework

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

Cappelli, M.; Gadomski, A. M.; Sepiellis, M.

In the field of nuclear power plant (NPP) safety modeling, the perception of the role of socio-cognitive engineering (SCE) is continuously increasing. Today, the focus is especially on the identification of human and organization decisional errors caused by operators and managers under high-risk conditions, as evident by analyzing reports on nuclear incidents occurred in the past. At present, the engineering and social safety requirements need to enlarge their domain of interest in such a way to include all possible losses generating events that could be the consequences of an abnormal state of a NPP. Socio-cognitive modeling of Integrated Nuclear Safetymore » Management (INSM) using the TOGA meta-theory has been discussed during the ICCAP 2011 Conference. In this paper, more detailed aspects of the cognitive decision-making and its possible human errors and organizational vulnerability are presented. The formal TOGA-based network model for cognitive decision-making enables to indicate and analyze nodes and arcs in which plant operators and managers errors may appear. The TOGA's multi-level IPK (Information, Preferences, Knowledge) model of abstract intelligent agents (AIAs) is applied. In the NPP context, super-safety approach is also discussed, by taking under consideration unexpected events and managing them from a systemic perspective. As the nature of human errors depends on the specific properties of the decision-maker and the decisional context of operation, a classification of decision-making using IPK is suggested. Several types of initial situations of decision-making useful for the diagnosis of NPP operators and managers errors are considered. The developed models can be used as a basis for applications to NPP educational or engineering simulators to be used for training the NPP executive staff. (authors)« less

Errors in statistical decision making Chapter 2 in Applied Statistics in Agricultural, Biological, and Environmental Sciences

USDA-ARS?s Scientific Manuscript database

Agronomic and Environmental research experiments result in data that are analyzed using statistical methods. These data are unavoidably accompanied by uncertainty. Decisions about hypotheses, based on statistical analyses of these data are therefore subject to error. This error is of three types,...

Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making

PubMed Central

Park, Hame; Lueckmann, Jan-Matthis; von Kriegstein, Katharina; Bitzer, Sebastian; Kiebel, Stefan J.

2016-01-01

Decisions in everyday life are prone to error. Standard models typically assume that errors during perceptual decisions are due to noise. However, it is unclear how noise in the sensory input affects the decision. Here we show that there are experimental tasks for which one can analyse the exact spatio-temporal details of a dynamic sensory noise and better understand variability in human perceptual decisions. Using a new experimental visual tracking task and a novel Bayesian decision making model, we found that the spatio-temporal noise fluctuations in the input of single trials explain a significant part of the observed responses. Our results show that modelling the precise internal representations of human participants helps predict when perceptual decisions go wrong. Furthermore, by modelling precisely the stimuli at the single-trial level, we were able to identify the underlying mechanism of perceptual decision making in more detail than standard models. PMID:26752272

A Grounded Theory Study of Aircraft Maintenance Technician Decision-Making

NASA Astrophysics Data System (ADS)

Norcross, Robert

Aircraft maintenance technician decision-making and actions have resulted in aircraft system errors causing aircraft incidents and accidents. Aircraft accident investigators and researchers examined the factors that influence aircraft maintenance technician errors and categorized the types of errors in an attempt to prevent similar occurrences. New aircraft technology introduced to improve aviation safety and efficiency incur failures that have no information contained in the aircraft maintenance manuals. According to the Federal Aviation Administration, aircraft maintenance technicians must use only approved aircraft maintenance documents to repair, modify, and service aircraft. This qualitative research used a grounded theory approach to explore the decision-making processes and actions taken by aircraft maintenance technicians when confronted with an aircraft problem not contained in the aircraft maintenance manuals. The target population for the research was Federal Aviation Administration licensed aircraft and power plant mechanics from across the United States. Nonprobability purposeful sampling was used to obtain aircraft maintenance technicians with the experience sought in the study problem. The sample population recruitment yielded 19 participants for eight focus group sessions to obtain opinions, perceptions, and experiences related to the study problem. All data collected was entered into the Atlas ti qualitative analysis software. The emergence of Aircraft Maintenance Technician decision-making themes regarding Aircraft Maintenance Manual content, Aircraft Maintenance Technician experience, and legal implications of not following Aircraft Maintenance Manuals surfaced. Conclusions from this study suggest Aircraft Maintenance Technician decision-making were influenced by experience, gaps in the Aircraft Maintenance Manuals, reliance on others, realizing the impact of decisions concerning aircraft airworthiness, management pressures, and legal concerns related to decision-making. Recommendations included an in-depth systematic review of the Aircraft Maintenance Manuals, development of a Federal Aviation Administration approved standardized Aircraft Maintenance Technician decision-making flow diagram, and implementation of risk based decision-making training. The benefit of this study is to save the airline industry revenue by preventing poor decision-making practices that result in inefficient maintenance actions and aircraft incidents and accidents.

The science of medical decision making: neurosurgery, errors, and personal cognitive strategies for improving quality of care.

PubMed

Fargen, Kyle M; Friedman, William A

2014-01-01

During the last 2 decades, there has been a shift in the U.S. health care system towards improving the quality of health care provided by enhancing patient safety and reducing medical errors. Unfortunately, surgical complications, patient harm events, and malpractice claims remain common in the field of neurosurgery. Many of these events are potentially avoidable. There are an increasing number of publications in the medical literature in which authors address cognitive errors in diagnosis and treatment and strategies for reducing such errors, but these are for the most part absent in the neurosurgical literature. The purpose of this article is to highlight the complexities of medical decision making to a neurosurgical audience, with the hope of providing insight into the biases that lead us towards error and strategies to overcome our innate cognitive deficiencies. To accomplish this goal, we review the current literature on medical errors and just culture, explain the dual process theory of cognition, identify common cognitive errors affecting neurosurgeons in practice, review cognitive debiasing strategies, and finally provide simple methods that can be easily assimilated into neurosurgical practice to improve clinical decision making. Copyright © 2014 Elsevier Inc. All rights reserved.

A priori discretization error metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar

2016-12-01

Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under candidate discretization schemes validate the strong correlation between the proposed discretization error metrics and hydrologic simulation responses. Discretization decision-making results show that the common and convenient approach of making uniform discretization decisions across the watershed performs worse than the proposed non-uniform discretization approach in terms of preserving spatial heterogeneity under the same computational cost.

Three-class ROC analysis--the equal error utility assumption and the optimality of three-class ROC surface using the ideal observer.

PubMed

He, Xin; Frey, Eric C

2006-08-01

Previously, we have developed a decision model for three-class receiver operating characteristic (ROC) analysis based on decision theory. The proposed decision model maximizes the expected decision utility under the assumption that incorrect decisions have equal utilities under the same hypothesis (equal error utility assumption). This assumption reduced the dimensionality of the "general" three-class ROC analysis and provided a practical figure-of-merit to evaluate the three-class task performance. However, it also limits the generality of the resulting model because the equal error utility assumption will not apply for all clinical three-class decision tasks. The goal of this study was to investigate the optimality of the proposed three-class decision model with respect to several other decision criteria. In particular, besides the maximum expected utility (MEU) criterion used in the previous study, we investigated the maximum-correctness (MC) (or minimum-error), maximum likelihood (ML), and Nyman-Pearson (N-P) criteria. We found that by making assumptions for both MEU and N-P criteria, all decision criteria lead to the previously-proposed three-class decision model. As a result, this model maximizes the expected utility under the equal error utility assumption, maximizes the probability of making correct decisions, satisfies the N-P criterion in the sense that it maximizes the sensitivity of one class given the sensitivities of the other two classes, and the resulting ROC surface contains the maximum likelihood decision operating point. While the proposed three-class ROC analysis model is not optimal in the general sense due to the use of the equal error utility assumption, the range of criteria for which it is optimal increases its applicability for evaluating and comparing a range of diagnostic systems.

Decision making in urological surgery.

PubMed

Abboudi, Hamid; Ahmed, Kamran; Normahani, Pasha; Abboudi, May; Kirby, Roger; Challacombe, Ben; Khan, Mohammed Shamim; Dasgupta, Prokar

2012-06-01

Non-technical skills are important behavioural aspects that a urologist must be fully competent at to minimise harm to patients. The majority of surgical errors are now known to be due to errors in judgment and decision making as opposed to the technical aspects of the craft. The authors reviewed the published literature regarding decision-making theory and in practice related to urology as well as the current tools available to assess decision-making skills. Limitations include limited number of studies, and the available studies are of low quality. Decision making is the psychological process of choosing between alternative courses of action. In the surgical environment, this can often be a complex balance of benefit and risk within a variable time frame and dynamic setting. In recent years, the emphasis of new surgical curriculums has shifted towards non-technical surgical skills; however, the assessment tools in place are far from objective, reliable and valid. Surgical simulators and video-assisted questionnaires are useful methods for appraisal of trainees. Well-designed, robust and validated tools need to be implemented in training and assessment of decision-making skills in urology. Patient safety can only be ensured when safe and effective decisions are made.

Using Covert Response Activation to Test Latent Assumptions of Formal Decision-Making Models in Humans.

PubMed

Servant, Mathieu; White, Corey; Montagnini, Anna; Burle, Borís

2015-07-15

Most decisions that we make build upon multiple streams of sensory evidence and control mechanisms are needed to filter out irrelevant information. Sequential sampling models of perceptual decision making have recently been enriched by attentional mechanisms that weight sensory evidence in a dynamic and goal-directed way. However, the framework retains the longstanding hypothesis that motor activity is engaged only once a decision threshold is reached. To probe latent assumptions of these models, neurophysiological indices are needed. Therefore, we collected behavioral and EMG data in the flanker task, a standard paradigm to investigate decisions about relevance. Although the models captured response time distributions and accuracy data, EMG analyses of response agonist muscles challenged the assumption of independence between decision and motor processes. Those analyses revealed covert incorrect EMG activity ("partial error") in a fraction of trials in which the correct response was finally given, providing intermediate states of evidence accumulation and response activation at the single-trial level. We extended the models by allowing motor activity to occur before a commitment to a choice and demonstrated that the proposed framework captured the rate, latency, and EMG surface of partial errors, along with the speed of the correction process. In return, EMG data provided strong constraints to discriminate between competing models that made similar behavioral predictions. Our study opens new theoretical and methodological avenues for understanding the links among decision making, cognitive control, and motor execution in humans. Sequential sampling models of perceptual decision making assume that sensory information is accumulated until a criterion quantity of evidence is obtained, from where the decision terminates in a choice and motor activity is engaged. The very existence of covert incorrect EMG activity ("partial error") during the evidence accumulation process challenges this longstanding assumption. In the present work, we use partial errors to better constrain sequential sampling models at the single-trial level. Copyright © 2015 the authors 0270-6474/15/3510371-15$15.00/0.

An Overview of Judgment and Decision Making Research Through the Lens of Fuzzy Trace Theory.

PubMed

Setton, Roni; Wilhelms, Evan; Weldon, Becky; Chick, Christina; Reyna, Valerie

2014-12-01

We present the basic tenets of fuzzy trace theory, a comprehensive theory of memory, judgment, and decision making that is grounded in research on how information is stored as knowledge, mentally represented, retrieved from storage, and processed. In doing so, we highlight how it is distinguished from traditional models of decision making in that gist reasoning plays a central role. The theory also distinguishes advanced intuition from primitive impulsivity. It predicts that different sorts of errors occur with respect to each component of judgment and decision making: background knowledge, representation, retrieval, and processing. Classic errors in the judgment and decision making literature, such as risky-choice framing and the conjunction fallacy, are accounted for by fuzzy trace theory and new results generated by the theory contradict traditional approaches. We also describe how developmental changes in brain and behavior offer crucial insight into adult cognitive processing. Research investigating brain and behavior in developing and special populations supports fuzzy trace theory's predictions about reliance on gist processing.

An Overview of Judgment and Decision Making Research Through the Lens of Fuzzy Trace Theory

PubMed Central

Setton, Roni; Wilhelms, Evan; Weldon, Becky; Chick, Christina; Reyna, Valerie

2017-01-01

We present the basic tenets of fuzzy trace theory, a comprehensive theory of memory, judgment, and decision making that is grounded in research on how information is stored as knowledge, mentally represented, retrieved from storage, and processed. In doing so, we highlight how it is distinguished from traditional models of decision making in that gist reasoning plays a central role. The theory also distinguishes advanced intuition from primitive impulsivity. It predicts that different sorts of errors occur with respect to each component of judgment and decision making: background knowledge, representation, retrieval, and processing. Classic errors in the judgment and decision making literature, such as risky-choice framing and the conjunction fallacy, are accounted for by fuzzy trace theory and new results generated by the theory contradict traditional approaches. We also describe how developmental changes in brain and behavior offer crucial insight into adult cognitive processing. Research investigating brain and behavior in developing and special populations supports fuzzy trace theory’s predictions about reliance on gist processing. PMID:28725239

Principal Candidates Create Decision-Making Simulations to Prepare for the JOB

ERIC Educational Resources Information Center

Staub, Nancy A.; Bravender, Marlena

2014-01-01

Online simulations offer opportunities for trial and error decision-making. What better tool for a principal than to make decisions when the consequences will not have real-world ramifications. In this study, two groups of graduate students in a principal preparation program taking the same course in the same semester use online simulations…

Feasibility of neuro-morphic computing to emulate error-conflict based decision making.

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

Branch, Darren W.

2009-09-01

A key aspect of decision making is determining when errors or conflicts exist in information and knowing whether to continue or terminate an action. Understanding the error-conflict processing is crucial in order to emulate higher brain functions in hardware and software systems. Specific brain regions, most notably the anterior cingulate cortex (ACC) are known to respond to the presence of conflicts in information by assigning a value to an action. Essentially, this conflict signal triggers strategic adjustments in cognitive control, which serve to prevent further conflict. The most probable mechanism is the ACC reports and discriminates different types of feedback,more » both positive and negative, that relate to different adaptations. Unique cells called spindle neurons that are primarily found in the ACC (layer Vb) are known to be responsible for cognitive dissonance (disambiguation between alternatives). Thus, the ACC through a specific set of cells likely plays a central role in the ability of humans to make difficult decisions and solve challenging problems in the midst of conflicting information. In addition to dealing with cognitive dissonance, decision making in high consequence scenarios also relies on the integration of multiple sets of information (sensory, reward, emotion, etc.). Thus, a second area of interest for this proposal lies in the corticostriatal networks that serve as an integration region for multiple cognitive inputs. In order to engineer neurological decision making processes in silicon devices, we will determine the key cells, inputs, and outputs of conflict/error detection in the ACC region. The second goal is understand in vitro models of corticostriatal networks and the impact of physical deficits on decision making, specifically in stressful scenarios with conflicting streams of data from multiple inputs. We will elucidate the mechanisms of cognitive data integration in order to implement a future corticostriatal-like network in silicon devices for improved decision processing.« less

Rational Choice and the Framing of Decisions.

DTIC Science & Technology

1986-05-29

decision under risk is the deriva- .- tion of the expected utility rule from simple principles of rational choice that make no . reference to long-run...corrective power of incentives depends on the nature of the particular error and cannot be taken for granted. The assumption of rationality of decision making ...easily eliminated by experience must be demonstrated. Finally, it is sometimes argued that failures of rationality in individual decision making are

Learning to Make More Effective Decisions: Changing Beliefs as a Prelude to Action

ERIC Educational Resources Information Center

Friedman, Sheldon

2004-01-01

Decision-makers in organizations often make what appear as being intuitively obviously and reasonable decisions, which often turn out to yield unintended outcomes. The cause of such ineffective decisions can be a combination of cognitive biases, poor mental models of complex systems, and errors in thinking provoked by anxiety, all of which tend to…

Different effects of dopaminergic medication on perceptual decision-making in Parkinson's disease as a function of task difficulty and speed-accuracy instructions.

PubMed

Huang, Yu-Ting; Georgiev, Dejan; Foltynie, Tom; Limousin, Patricia; Speekenbrink, Maarten; Jahanshahi, Marjan

2015-08-01

When choosing between two options, sufficient accumulation of information is required to favor one of the options over the other, before a decision is finally reached. To establish the effect of dopaminergic medication on the rate of accumulation of information, decision thresholds and speed-accuracy trade-offs, we tested 14 patients with Parkinson's disease (PD) on and off dopaminergic medication and 14 age-matched healthy controls on two versions of the moving-dots task. One version manipulated the level of task difficulty and hence effort required for decision-making and the other the urgency, requiring decision-making under speed vs. accuracy instructions. The drift diffusion model was fitted to the behavioral data. As expected, the reaction time data revealed an effect of task difficulty, such that the easier the perceptual decision-making task was, the faster the participants responded. PD patients not only made significantly more errors compared to healthy controls, but interestingly they also made significantly more errors ON than OFF medication. The drift diffusion model indicated that PD patients had lower drift rates when tested ON compared to OFF medication, indicating that dopamine levels influenced the quality of information derived from sensory information. On the speed-accuracy task, dopaminergic medication did not directly influence reaction times or error rates. PD patients OFF medication had slower RTs and made more errors with speed than accuracy instructions compared to the controls, whereas such differences were not observed ON medication. PD patients had lower drift rates and higher response thresholds than the healthy controls both with speed and accuracy instructions and ON and OFF medication. For the patients, only non-decision time was higher OFF than ON medication and higher with accuracy than speed instructions. The present results demonstrate that when task difficulty is manipulated, dopaminergic medication impairs perceptual decision-making and renders it more errorful in PD relative to when patients are tested OFF medication. In contrast, for the speed/accuracy task, being ON medication improved performance by eliminating the significantly higher errors and slower RTs observed for patients OFF medication compared to the HC group. There was no evidence of dopaminergic medication inducing impulsive decisions when patients were acting under speed pressure. For the speed-accuracy instructions, the sole effect of dopaminergic medication was on non-decision time, which suggests that medication primarily affected processes tightly coupled with the motor symptoms of PD. Interestingly, the current results suggest opposite effects of dopaminergic medication on the levels of difficulty and speed-accuracy versions of the moving dots task, possibly reflecting the differential effect of dopamine on modulating drift rate (levels of difficulty task) and non-decision time (speed-accuracy task) in the process of perceptual decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

"Decision sidestepping: How the motivation for closure prompts individuals to bypass decision making": Correction to Otto et al. (2016).

PubMed

2016-09-01

Reports an error in "Decision sidestepping: How the motivation for closure prompts individuals to bypass decision making" by Ashley S. Otto, Joshua J. Clarkson and Frank R. Kardes ( Journal of Personality and Social Psychology , 2016[Jul], Vol 111[1], 1-16). In the article, the main heading for Experiment 3 was missing due to a production error, and the first sentence of the first paragraph of Experiment 3 should begin as follows: Experiment 2 offered support for the hypothesis that those seeking closure engage in decision sidestepping to reduce the bothersome nature of decision making. (The following abstract of the original article appeared in record 2016-30159-001.) We all too often have to make decisions—from the mundane (e.g., what to eat for breakfast) to the complex (e.g., what to buy a loved one)—and yet there exists a multitude of strategies that allows us to make a decision. This work focuses on a subset of decision strategies that allows individuals to make decisions by bypassing the decision-making process—a phenomenon we term decision sidestepping. Critical to the present manuscript, however, we contend that decision sidestepping stems from the motivation to achieve closure. We link this proposition back to the fundamental nature of closure and how those seeking closure are highly bothered by decision making. As such, we argue that the motivation to achieve closure prompts a reliance on sidestepping strategies (e.g., default bias, choice delegation, status quo bias, inaction inertia, option fixation) to reduce the bothersome nature of decision making. In support of this framework, five experiments demonstrate that (a) those seeking closure are more likely to engage in decision sidestepping, (b) the effect of closure on sidestepping stems from the bothersome nature of decision making, and (c) the reliance on sidestepping results in downstream consequences for subsequent choice. Taken together, these findings offer unique insight into the cognitive motivations stimulating a reliance on decision sidestepping and thus a novel framework by which to understand how individuals make decisions while bypassing the decision-making process. PsycINFO Database Record (c) 2016 APA, all rights reserved

Judging Statistical Models of Individual Decision Making under Risk Using In- and Out-of-Sample Criteria

PubMed Central

Drichoutis, Andreas C.; Lusk, Jayson L.

2014-01-01

Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample. PMID:25029467

Judging statistical models of individual decision making under risk using in- and out-of-sample criteria.

PubMed

Drichoutis, Andreas C; Lusk, Jayson L

2014-01-01

Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample.

Offside Decisions by Expert Assistant Referees in Association Football: Perception and Recall of Spatial Positions in Complex Dynamic Events

ERIC Educational Resources Information Center

Gilis, Bart; Helsen, Werner; Catteeuw, Peter; Wagemans, Johan

2008-01-01

This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Federation Internationale de Football Association (FIFA; n = 29)…

Automation Bias: Decision Making and Performance in High-Tech Cockpits

NASA Technical Reports Server (NTRS)

Mosier, Kathleen L.; Skitka, Linda J.; Heers, Susan; Burdick, Mark; Rosekind, Mark R. (Technical Monitor)

1997-01-01

Automated aids and decision support tools are rapidly becoming indispensible tools in high-technology cockpits, and are assuming increasing control of "cognitive" flight tasks, such as calculating fuel-efficient routes, navigating, or detecting and diagnosing system malfunctions and abnormalities. This study was designed to investigate "automation bias," a recently documented factor in the use of automated aids and decision support systems. The term refers to omission and commission errors resulting from the use of automated cues as a heuristic replacement for vigilant information seeking and processing. Glass-cockpit pilots flew flight scenarios involving automation "events," or opportunities for automation-related omission and commission errors. Pilots who perceived themselves as "accountable" for their performance and strategies of interaction with the automation were more likely to double-check automated functioning against other cues, and less likely to commit errors. Pilots were also likely to erroneously "remember" the presence of expected cues when describing their decision-making processes.

Decision-making in schizophrenia: A predictive-coding perspective.

PubMed

Sterzer, Philipp; Voss, Martin; Schlagenhauf, Florian; Heinz, Andreas

2018-05-31

Dysfunctional decision-making has been implicated in the positive and negative symptoms of schizophrenia. Decision-making can be conceptualized within the framework of hierarchical predictive coding as the result of a Bayesian inference process that uses prior beliefs to infer states of the world. According to this idea, prior beliefs encoded at higher levels in the brain are fed back as predictive signals to lower levels. Whenever these predictions are violated by the incoming sensory data, a prediction error is generated and fed forward to update beliefs encoded at higher levels. Well-documented impairments in cognitive decision-making support the view that these neural inference mechanisms are altered in schizophrenia. There is also extensive evidence relating the symptoms of schizophrenia to aberrant signaling of prediction errors, especially in the domain of reward and value-based decision-making. Moreover, the idea of altered predictive coding is supported by evidence for impaired low-level sensory mechanisms and motor processes. We review behavioral and neural findings from these research areas and provide an integrated view suggesting that schizophrenia may be related to a pervasive alteration in predictive coding at multiple hierarchical levels, including cognitive and value-based decision-making processes as well as sensory and motor systems. We relate these findings to decision-making processes and propose that varying degrees of impairment in the implicated brain areas contribute to the variety of psychotic experiences. Copyright © 2018 Elsevier Inc. All rights reserved.

Reexamining our bias against heuristics.

PubMed

McLaughlin, Kevin; Eva, Kevin W; Norman, Geoff R

2014-08-01

Using heuristics offers several cognitive advantages, such as increased speed and reduced effort when making decisions, in addition to allowing us to make decision in situations where missing data do not allow for formal reasoning. But the traditional view of heuristics is that they trade accuracy for efficiency. Here the authors discuss sources of bias in the literature implicating the use of heuristics in diagnostic error and highlight the fact that there are also data suggesting that under certain circumstances using heuristics may lead to better decisions that formal analysis. They suggest that diagnostic error is frequently misattributed to the use of heuristics and propose an alternative view whereby content knowledge is the root cause of diagnostic performance and heuristics lie on the causal pathway between knowledge and diagnostic error or success.

Computation and measurement of cell decision making errors using single cell data

PubMed Central

Habibi, Iman; Cheong, Raymond; Levchenko, Andre; Emamian, Effat S.; Abdi, Ali

2017-01-01

In this study a new computational method is developed to quantify decision making errors in cells, caused by noise and signaling failures. Analysis of tumor necrosis factor (TNF) signaling pathway which regulates the transcription factor Nuclear Factor κB (NF-κB) using this method identifies two types of incorrect cell decisions called false alarm and miss. These two events represent, respectively, declaring a signal which is not present and missing a signal that does exist. Using single cell experimental data and the developed method, we compute false alarm and miss error probabilities in wild-type cells and provide a formulation which shows how these metrics depend on the signal transduction noise level. We also show that in the presence of abnormalities in a cell, decision making processes can be significantly affected, compared to a wild-type cell, and the method is able to model and measure such effects. In the TNF—NF-κB pathway, the method computes and reveals changes in false alarm and miss probabilities in A20-deficient cells, caused by cell’s inability to inhibit TNF-induced NF-κB response. In biological terms, a higher false alarm metric in this abnormal TNF signaling system indicates perceiving more cytokine signals which in fact do not exist at the system input, whereas a higher miss metric indicates that it is highly likely to miss signals that actually exist. Overall, this study demonstrates the ability of the developed method for modeling cell decision making errors under normal and abnormal conditions, and in the presence of transduction noise uncertainty. Compared to the previously reported pathway capacity metric, our results suggest that the introduced decision error metrics characterize signaling failures more accurately. This is mainly because while capacity is a useful metric to study information transmission in signaling pathways, it does not capture the overlap between TNF-induced noisy response curves. PMID:28379950

Computation and measurement of cell decision making errors using single cell data.

PubMed

Habibi, Iman; Cheong, Raymond; Lipniacki, Tomasz; Levchenko, Andre; Emamian, Effat S; Abdi, Ali

2017-04-01

In this study a new computational method is developed to quantify decision making errors in cells, caused by noise and signaling failures. Analysis of tumor necrosis factor (TNF) signaling pathway which regulates the transcription factor Nuclear Factor κB (NF-κB) using this method identifies two types of incorrect cell decisions called false alarm and miss. These two events represent, respectively, declaring a signal which is not present and missing a signal that does exist. Using single cell experimental data and the developed method, we compute false alarm and miss error probabilities in wild-type cells and provide a formulation which shows how these metrics depend on the signal transduction noise level. We also show that in the presence of abnormalities in a cell, decision making processes can be significantly affected, compared to a wild-type cell, and the method is able to model and measure such effects. In the TNF-NF-κB pathway, the method computes and reveals changes in false alarm and miss probabilities in A20-deficient cells, caused by cell's inability to inhibit TNF-induced NF-κB response. In biological terms, a higher false alarm metric in this abnormal TNF signaling system indicates perceiving more cytokine signals which in fact do not exist at the system input, whereas a higher miss metric indicates that it is highly likely to miss signals that actually exist. Overall, this study demonstrates the ability of the developed method for modeling cell decision making errors under normal and abnormal conditions, and in the presence of transduction noise uncertainty. Compared to the previously reported pathway capacity metric, our results suggest that the introduced decision error metrics characterize signaling failures more accurately. This is mainly because while capacity is a useful metric to study information transmission in signaling pathways, it does not capture the overlap between TNF-induced noisy response curves.

Agency and Error in Young Adults' Stories of Sexual Decision Making

ERIC Educational Resources Information Center

Allen, Katherine R.; Husser, Erica K.; Stone, Dana J.; Jordal, Christian E.

2008-01-01

We conducted a qualitative analysis of 148 college students' written comments about themselves as sexual decision makers. Most participants described experiences in which they were actively engaged in decision-making processes of "waiting it out" to "working it out." The four patterns were (a) I am in control, (b) I am experimenting and learning,…

29 CFR 18.103 - Rulings on evidence.

Code of Federal Regulations, 2010 CFR

2010-07-01

... is more probably true than not true that the error did not materially contribute to the decision or... if explicitly not relied upon by the judge in support of the decision or order. (b) Record of offer... making of an offer in question and answer form. (c) Plain error. Nothing in this rule precludes taking...

Meta-analysis in evidence-based healthcare: a paradigm shift away from random effects is overdue.

PubMed

Doi, Suhail A R; Furuya-Kanamori, Luis; Thalib, Lukman; Barendregt, Jan J

2017-12-01

Each year up to 20 000 systematic reviews and meta-analyses are published whose results influence healthcare decisions, thus making the robustness and reliability of meta-analytic methods one of the world's top clinical and public health priorities. The evidence synthesis makes use of either fixed-effect or random-effects statistical methods. The fixed-effect method has largely been replaced by the random-effects method as heterogeneity of study effects led to poor error estimation. However, despite the widespread use and acceptance of the random-effects method to correct this, it too remains unsatisfactory and continues to suffer from defective error estimation, posing a serious threat to decision-making in evidence-based clinical and public health practice. We discuss here the problem with the random-effects approach and demonstrate that there exist better estimators under the fixed-effect model framework that can achieve optimal error estimation. We argue for an urgent return to the earlier framework with updates that address these problems and conclude that doing so can markedly improve the reliability of meta-analytical findings and thus decision-making in healthcare.

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.

Decision-making when data and inferences are not conclusive: risk-benefit and acceptable regret approach.

PubMed

Hozo, Iztok; Schell, Michael J; Djulbegovic, Benjamin

2008-07-01

The absolute truth in research is unobtainable, as no evidence or research hypothesis is ever 100% conclusive. Therefore, all data and inferences can in principle be considered as "inconclusive." Scientific inference and decision-making need to take into account errors, which are unavoidable in the research enterprise. The errors can occur at the level of conclusions that aim to discern the truthfulness of research hypothesis based on the accuracy of research evidence and hypothesis, and decisions, the goal of which is to enable optimal decision-making under present and specific circumstances. To optimize the chance of both correct conclusions and correct decisions, the synthesis of all major statistical approaches to clinical research is needed. The integration of these approaches (frequentist, Bayesian, and decision-analytic) can be accomplished through formal risk:benefit (R:B) analysis. This chapter illustrates the rational choice of a research hypothesis using R:B analysis based on decision-theoretic expected utility theory framework and the concept of "acceptable regret" to calculate the threshold probability of the "truth" above which the benefit of accepting a research hypothesis outweighs its risks.

Regret and the rationality of choices.

PubMed

Bourgeois-Gironde, Sacha

2010-01-27

Regret helps to optimize decision behaviour. It can be defined as a rational emotion. Several recent neurobiological studies have confirmed the interface between emotion and cognition at which regret is located and documented its role in decision behaviour. These data give credibility to the incorporation of regret in decision theory that had been proposed by economists in the 1980s. However, finer distinctions are required in order to get a better grasp of how regret and behaviour influence each other. Regret can be defined as a predictive error signal but this signal does not necessarily transpose into a decision-weight influencing behaviour. Clinical studies on several types of patients show that the processing of an error signal and its influence on subsequent behaviour can be dissociated. We propose a general understanding of how regret and decision-making are connected in terms of regret being modulated by rational antecedents of choice. Regret and the modification of behaviour on its basis will depend on the criteria of rationality involved in decision-making. We indicate current and prospective lines of research in order to refine our views on how regret contributes to optimal decision-making.

Relationship between impulsivity and decision-making in cocaine dependence

PubMed Central

Kjome, Kimberly L.; Lane, Scott D.; Schmitz, Joy M.; Green, Charles; Ma, Liangsuo; Prasla, Irshad; Swann, Alan C.; Moeller, F. Gerard

2010-01-01

Impulsivity and decision-making are associated on a theoretical level in that impaired planning is a component of both. However, few studies have examined the relationship between measures of decision-making and impulsivity in clinical populations. The purpose of this study was to compare cocaine-dependent subjects to controls on a measure of decision-making (the Iowa Gambling Task or IGT), a questionnaire measure of impulsivity (the Barratt Impulsiveness Scale or BIS-11), and a measure of behavioral inhibition (the immediate memory task or IMT), and to examine the interrelationship among these measures. Results of the study showed that cocaine-dependent subjects made more disadvantageous choices on the IGT, had higher scores on the BIS, and more commission errors on the IMT. Cognitive model analysis showed that choice consistency factors on the IGT differed between cocaine-dependent subjects and controls. However, there was no significant correlation between IGT performance and the BIS total score or subscales or IMT commission errors. These results suggest that in cocaine dependent subjects there is little overlap between decision-making as measured by the IGT and impulsivity/behavioral inhibition as measured by the BIS and IMT. PMID:20478631

A Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.

PubMed

Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis

2015-01-01

Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.

Offside decisions by expert assistant referees in association football: Perception and recall of spatial positions in complex dynamic events.

PubMed

Gilis, Bart; Helsen, Werner; Catteeuw, Peter; Wagemans, Johan

2008-03-01

This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Fédération Internationale de Football Association (FIFA; n = 29) and Belgian elite (n = 28) assistant referees (ARs) assessed 64 computer-based offside situations. First, an expertise effect was found. The FIFA ARs assessed the trials more accurately than the Belgian ARs (76.4% vs. 67.5%). Second, regarding the type of error, all ARs clearly tended to raise their flag in doubtful situations. This observation could be explained by a perceptual bias associated with the flash-lag effect. Specifically, attackers were perceived ahead of their actual positions, and this tendency was stronger for the Belgian than for the FIFA ARs (11.0 vs. 8.4 pixels), in particular when the difficulty of the trials increased. Further experimentation is needed to examine whether video- and computer-based decision-making training is effective in improving the decision-making skills of ARs during the game. PsycINFO Database Record (c) 2008 APA, all rights reserved

Context Effects in Multi-Alternative Decision Making: Empirical Data and a Bayesian Model

ERIC Educational Resources Information Center

Hawkins, Guy; Brown, Scott D.; Steyvers, Mark; Wagenmakers, Eric-Jan

2012-01-01

For decisions between many alternatives, the benchmark result is Hick's Law: that response time increases log-linearly with the number of choice alternatives. Even when Hick's Law is observed for response times, divergent results have been observed for error rates--sometimes error rates increase with the number of choice alternatives, and…

Clinical decision-making: heuristics and cognitive biases for the ophthalmologist.

PubMed

Hussain, Ahsen; Oestreicher, James

Diagnostic errors have a significant impact on health care outcomes and patient care. The underlying causes and development of diagnostic error are complex with flaws in health care systems, as well as human error, playing a role. Cognitive biases and a failure of decision-making shortcuts (heuristics) are human factors that can compromise the diagnostic process. We describe these mechanisms, their role with the clinician, and provide clinical scenarios to highlight the various points at which biases may emerge. We discuss strategies to modify the development and influence of these processes and the vulnerability of heuristics to provide insight and improve clinical outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

Prediction Error Representation in Individuals with Generalized Anxiety Disorder During Passive Avoidance

PubMed Central

White, Stuart F.; Geraci, Marilla; Lewis, Elizabeth; Leshin, Joseph; Teng, Cindy; Averbeck, Bruno; Meffert, Harma; Ernst, Monique; Blair, James R.; Grillon, Christian; Blair, Karina S.

2017-01-01

Objective Deficits in reinforcement-based decision-making have been reported in Generalized Anxiety Disorder. However, the pathophysiology of these deficits is largely unknown, extant studies have mainly examined youth and the integrity of core functional processes underpinning decision-making remain undetermined. In particular, it is unclear whether the representation of reinforcement prediction error (PE: the difference between received and expected reinforcement) is disrupted in Generalized Anxiety Disorder. The current study addresses these issues in adults with the disorder. Methods Forty-six un-medicated individuals with Generalized Anxiety Disorder and 32 healthy controls group-matched on IQ, gender and age, completed a passive avoidance task while undergoing functional MRI. Results Behaviorally, individuals with Generalized Anxiety Disorder showed impaired reinforcement-based decision-making. Imaging results revealed that during feedback, individuals with Generalized Anxiety Disorder relative to healthy controls showed a reduced correlation between PE and activity within ventromedial prefrontal cortex, ventral striatum and other structures implicated in decision-making. In addition, individuals with Generalized Anxiety Disorder relative to healthy participants showed a reduced correlation between punishment, but not reward, PEs and activity within bilateral lentiform nucleus/putamen. Conclusions This is the first study to identify computational impairments during decision-making in Generalized Anxiety Disorder. PE signaling is significantly disrupted in individuals with the disorder and may underpin the decision-making deficits observed in patients with GAD. PMID:27631963

Affective forecasting: an unrecognized challenge in making serious health decisions.

PubMed

Halpern, Jodi; Arnold, Robert M

2008-10-01

Patients facing medical decisions that will impact quality of life make assumptions about how they will adjust emotionally to living with health declines and disability. Despite abundant research on decision-making, we have no direct research on how accurately patients envision their future well-being and how this influences their decisions. Outside medicine, psychological research on "affective forecasting" consistently shows that people poorly predict their future ability to adapt to adversity. This finding is important for medicine, since many serious health decisions hinge on quality-of-life judgments. We describe three specific mechanisms for affective forecasting errors that may influence health decisions: focalism, in which people focus more on what will change than on what will stay the same; immune neglect, in which they fail to envision how their own coping skills will lessen their unhappiness; and failure to predict adaptation, in which people fail to envision shifts in what they value. We discuss emotional and social factors that interact with these cognitive biases. We describe how caregivers can recognize these biases in the clinical setting and suggest interventions to help patients recognize and address affective forecasting errors.

Conflict between Place and Response Navigation Strategies: Effects on Vicarious Trial and Error (VTE) Behaviors

ERIC Educational Resources Information Center

Schmidt, Brandy; Papale, Andrew; Redish, A. David; Markus, Etan J.

2013-01-01

Navigation can be accomplished through multiple decision-making strategies, using different information-processing computations. A well-studied dichotomy in these decision-making strategies compares hippocampal-dependent "place" and dorsal-lateral striatal dependent "response" strategies. A place strategy depends on the ability to flexibly respond…

Decision-Making Accuracy of CBM Progress-Monitoring Data

ERIC Educational Resources Information Center

Hintze, John M.; Wells, Craig S.; Marcotte, Amanda M.; Solomon, Benjamin G.

2018-01-01

This study examined the diagnostic accuracy associated with decision making as is typically conducted with curriculum-based measurement (CBM) approaches to progress monitoring. Using previously published estimates of the standard errors of estimate associated with CBM, 20,000 progress-monitoring data sets were simulated to model student reading…

Collegiate Aviation Review. September 1994.

ERIC Educational Resources Information Center

Barker, Ballard M., Ed.

This document contains four papers on aviation education. The first paper, "Why Aren't We Teaching Aeronautical Decision Making?" (Richard J. Adams), reviews 15 years of aviation research into the causes of human performance errors in aviation and provides guidelines for designing the next generation of aeronautical decision-making materials.…

Selection Practices of Group Leaders: A National Survey.

ERIC Educational Resources Information Center

Riva, Maria T.; Lippert, Laurel; Tackett, M. Jan

2000-01-01

Study surveys the selection practices of group leaders. Explores methods of selection, variables used to make selection decisions, and the types of selection errors that leaders have experienced. Results suggest that group leaders use clinical judgment to make selection decisions and endorse using some specific variables in selection. (Contains 22…

Using the Situated Clinical Decision-Making framework to guide analysis of nurses' clinical decision-making.

PubMed

Gillespie, Mary

2010-11-01

Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.

Evaluating team decision-making as an emergent phenomenon.

PubMed

Kinnear, John; Wilson, Nick; O'Dwyer, Anthony

2018-04-01

The complexity of modern clinical practice has highlighted the fallibility of individual clinicians' decision-making, with effective teamwork emerging as a key to patient safety. Dual process theory is widely accepted as a framework for individual decision-making, with type 1 processes responsible for fast, intuitive and automatic decisions and type 2 processes for slow, analytical decisions. However, dual process theory does not explain cognition at the group level, when individuals act in teams. Team cognition resulting from dynamic interaction of individuals is said to be more resilient to decision-making error and greater than simply aggregated cognition. Clinicians were paired as teams and asked to solve a cognitive puzzle constructed as a drug calculation. The frequency at which the teams made incorrect decisions was compared with that of individual clinicians answering the same question. When clinicians acted in pairs, 63% answered the cognitive puzzle correctly, compared with 33% of clinicians as individuals, showing a statistically significant difference in performance (χ 2 (1, n=116)=24.329, P<0.001). Based on the predicted performance of teams made up of the random pairing of individuals who had the same propensity to answer as previously, there was no statistical difference in the actual and predicted teams' performance. Teams are less prone to making errors of decision-making than individuals. However, the improved performance is likely to be owing to the effect of aggregated cognition rather than any improved decision-making as a result of the interaction. There is no evidence of team cognition as an emergent and distinct entity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Stress-induced cortisol facilitates threat-related decision making among police officers.

PubMed

Akinola, Modupe; Mendes, Wendy Berry

2012-02-01

Previous research suggests that cortisol can affect cognitive functions such as memory, decision making, and attentiveness to threat-related cues. Here, we examine whether increases in cortisol, brought on by an acute social stressor, influence threat-related decision making. Eighty-one police officers completed a standardized laboratory stressor and then immediately completed a computer simulated decision-making task designed to examine decisions to accurately shoot or not shoot armed and unarmed Black and White targets. Results indicated that police officers who had larger cortisol increases to the social-stress task subsequently made fewer errors when deciding to shoot armed Black targets relative to armed White targets, suggesting that hypothalamic pituitary adrenal (HPA) activation may exacerbate vigilance for threat cues. We conclude with a discussion of the implications of threat-initiated decision making.

Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making.

PubMed

Schönberg, Tom; Daw, Nathaniel D; Joel, Daphna; O'Doherty, John P

2007-11-21

The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans.

Error Tendencies in Processing Student Feedback for Instructional Decision Making.

ERIC Educational Resources Information Center

Schermerhorn, John R., Jr.; And Others

1985-01-01

Seeks to assist instructors in recognizing two basic errors that can occur in processing student evaluation data on instructional development efforts; offers a research framework for future investigations of the error tendencies and related issues; and suggests ways in which instructors can confront and manage error tendencies in practice. (MBR)

Regret and the rationality of choices

PubMed Central

Bourgeois-Gironde, Sacha

2010-01-01

Regret helps to optimize decision behaviour. It can be defined as a rational emotion. Several recent neurobiological studies have confirmed the interface between emotion and cognition at which regret is located and documented its role in decision behaviour. These data give credibility to the incorporation of regret in decision theory that had been proposed by economists in the 1980s. However, finer distinctions are required in order to get a better grasp of how regret and behaviour influence each other. Regret can be defined as a predictive error signal but this signal does not necessarily transpose into a decision-weight influencing behaviour. Clinical studies on several types of patients show that the processing of an error signal and its influence on subsequent behaviour can be dissociated. We propose a general understanding of how regret and decision-making are connected in terms of regret being modulated by rational antecedents of choice. Regret and the modification of behaviour on its basis will depend on the criteria of rationality involved in decision-making. We indicate current and prospective lines of research in order to refine our views on how regret contributes to optimal decision-making. PMID:20026463

Rational decision-making in inhibitory control.

PubMed

Shenoy, Pradeep; Yu, Angela J

2011-01-01

An important aspect of cognitive flexibility is inhibitory control, the ability to dynamically modify or cancel planned actions in response to changes in the sensory environment or task demands. We formulate a probabilistic, rational decision-making framework for inhibitory control in the stop signal paradigm. Our model posits that subjects maintain a Bayes-optimal, continually updated representation of sensory inputs, and repeatedly assess the relative value of stopping and going on a fine temporal scale, in order to make an optimal decision on when and whether to go on each trial. We further posit that they implement this continual evaluation with respect to a global objective function capturing the various reward and penalties associated with different behavioral outcomes, such as speed and accuracy, or the relative costs of stop errors and go errors. We demonstrate that our rational decision-making model naturally gives rise to basic behavioral characteristics consistently observed for this paradigm, as well as more subtle effects due to contextual factors such as reward contingencies or motivational factors. Furthermore, we show that the classical race model can be seen as a computationally simpler, perhaps neurally plausible, approximation to optimal decision-making. This conceptual link allows us to predict how the parameters of the race model, such as the stopping latency, should change with task parameters and individual experiences/ability.

Rational Decision-Making in Inhibitory Control

PubMed Central

Shenoy, Pradeep; Yu, Angela J.

2011-01-01

An important aspect of cognitive flexibility is inhibitory control, the ability to dynamically modify or cancel planned actions in response to changes in the sensory environment or task demands. We formulate a probabilistic, rational decision-making framework for inhibitory control in the stop signal paradigm. Our model posits that subjects maintain a Bayes-optimal, continually updated representation of sensory inputs, and repeatedly assess the relative value of stopping and going on a fine temporal scale, in order to make an optimal decision on when and whether to go on each trial. We further posit that they implement this continual evaluation with respect to a global objective function capturing the various reward and penalties associated with different behavioral outcomes, such as speed and accuracy, or the relative costs of stop errors and go errors. We demonstrate that our rational decision-making model naturally gives rise to basic behavioral characteristics consistently observed for this paradigm, as well as more subtle effects due to contextual factors such as reward contingencies or motivational factors. Furthermore, we show that the classical race model can be seen as a computationally simpler, perhaps neurally plausible, approximation to optimal decision-making. This conceptual link allows us to predict how the parameters of the race model, such as the stopping latency, should change with task parameters and individual experiences/ability. PMID:21647306

A new computational account of cognitive control over reinforcement-based decision-making: Modeling of a probabilistic learning task.

PubMed

Zendehrouh, Sareh

2015-11-01

Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.

Research implications of science-informed, value-based decision making.

PubMed

Dowie, Jack

2004-01-01

In 'Hard' science, scientists correctly operate as the 'guardians of certainty', using hypothesis testing formulations and value judgements about error rates and time discounting that make classical inferential methods appropriate. But these methods can neither generate most of the inputs needed by decision makers in their time frame, nor generate them in a form that allows them to be integrated into the decision in an analytically coherent and transparent way. The need for transparent accountability in public decision making under uncertainty and value conflict means the analytical coherence provided by the stochastic Bayesian decision analytic approach, drawing on the outputs of Bayesian science, is needed. If scientific researchers are to play the role they should be playing in informing value-based decision making, they need to see themselves also as 'guardians of uncertainty', ensuring that the best possible current posterior distributions on relevant parameters are made available for decision making, irrespective of the state of the certainty-seeking research. The paper distinguishes the actors employing different technologies in terms of the focus of the technology (knowledge, values, choice); the 'home base' mode of their activity on the cognitive continuum of varying analysis-to-intuition ratios; and the underlying value judgements of the activity (especially error loss functions and time discount rates). Those who propose any principle of decision making other than the banal 'Best Principle', including the 'Precautionary Principle', are properly interpreted as advocates seeking to have their own value judgements and preferences regarding mode location apply. The task for accountable decision makers, and their supporting technologists, is to determine the best course of action under the universal conditions of uncertainty and value difference/conflict.

Safety evaluation of driver cognitive failures and driving errors on right-turn filtering movement at signalized road intersections based on Fuzzy Cellular Automata (FCA) model.

PubMed

Chai, Chen; Wong, Yiik Diew; Wang, Xuesong

2017-07-01

This paper proposes a simulation-based approach to estimate safety impact of driver cognitive failures and driving errors. Fuzzy Logic, which involves linguistic terms and uncertainty, is incorporated with Cellular Automata model to simulate decision-making process of right-turn filtering movement at signalized intersections. Simulation experiments are conducted to estimate the relationships between cognitive failures and driving errors with safety performance. Simulation results show Different types of cognitive failures are found to have varied relationship with driving errors and safety performance. For right-turn filtering movement, cognitive failures are more likely to result in driving errors with denser conflicting traffic stream. Moreover, different driving errors are found to have different safety impacts. The study serves to provide a novel approach to linguistically assess cognitions and replicate decision-making procedures of the individual driver. Compare to crash analysis, the proposed FCA model allows quantitative estimation of particular cognitive failures, and the impact of cognitions on driving errors and safety performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Humans Optimize Decision-Making by Delaying Decision Onset

PubMed Central

Teichert, Tobias; Ferrera, Vincent P.; Grinband, Jack

2014-01-01

Why do humans make errors on seemingly trivial perceptual decisions? It has been shown that such errors occur in part because the decision process (evidence accumulation) is initiated before selective attention has isolated the relevant sensory information from salient distractors. Nevertheless, it is typically assumed that subjects increase accuracy by prolonging the decision process rather than delaying decision onset. To date it has not been tested whether humans can strategically delay decision onset to increase response accuracy. To address this question we measured the time course of selective attention in a motion interference task using a novel variant of the response signal paradigm. Based on these measurements we estimated time-dependent drift rate and showed that subjects should in principle be able trade speed for accuracy very effectively by delaying decision onset. Using the time-dependent estimate of drift rate we show that subjects indeed delay decision onset in addition to raising response threshold when asked to stress accuracy over speed in a free reaction version of the same motion-interference task. These findings show that decision onset is a critical aspect of the decision process that can be adjusted to effectively improve decision accuracy. PMID:24599295

A taxonomy of decision problems on the flight deck

NASA Technical Reports Server (NTRS)

Orasanu, Judith M.; Fischer, Ute; Tarrel, Richard J.

1993-01-01

Examining cases of real crews making decisions in full-mission simulators or through Aviation Safety Reporting System (ASRS) reports shows that there are many different types of decisions that crews must make. Features of the situation determine the type of decision that must be made. The paper identifies six types of decisions that require different types of cognitive work and are also subject to different types of error or failure. These different requirements, along with descriptions of effective crew strategies, can serve as a basis for developing training practices and for evaluating crews.

[Medical expert systems and clinical needs].

PubMed

Buscher, H P

1991-10-18

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

Smart algorithms and adaptive methods in computational fluid dynamics

NASA Astrophysics Data System (ADS)

Tinsley Oden, J.

1989-05-01

A review is presented of the use of smart algorithms which employ adaptive methods in processing large amounts of data in computational fluid dynamics (CFD). Smart algorithms use a rationally based set of criteria for automatic decision making in an attempt to produce optimal simulations of complex fluid dynamics problems. The information needed to make these decisions is not known beforehand and evolves in structure and form during the numerical solution of flow problems. Once the code makes a decision based on the available data, the structure of the data may change, and criteria may be reapplied in order to direct the analysis toward an acceptable end. Intelligent decisions are made by processing vast amounts of data that evolve unpredictably during the calculation. The basic components of adaptive methods and their application to complex problems of fluid dynamics are reviewed. The basic components of adaptive methods are: (1) data structures, that is what approaches are available for modifying data structures of an approximation so as to reduce errors; (2) error estimation, that is what techniques exist for estimating error evolution in a CFD calculation; and (3) solvers, what algorithms are available which can function in changing meshes. Numerical examples which demonstrate the viability of these approaches are presented.

Automation bias: decision making and performance in high-tech cockpits.

PubMed

Mosier, K L; Skitka, L J; Heers, S; Burdick, M

1997-01-01

Automated aids and decision support tools are rapidly becoming indispensable tools in high-technology cockpits and are assuming increasing control of"cognitive" flight tasks, such as calculating fuel-efficient routes, navigating, or detecting and diagnosing system malfunctions and abnormalities. This study was designed to investigate automation bias, a recently documented factor in the use of automated aids and decision support systems. The term refers to omission and commission errors resulting from the use of automated cues as a heuristic replacement for vigilant information seeking and processing. Glass-cockpit pilots flew flight scenarios involving automation events or opportunities for automation-related omission and commission errors. Although experimentally manipulated accountability demands did not significantly impact performance, post hoc analyses revealed that those pilots who reported an internalized perception of "accountability" for their performance and strategies of interaction with the automation were significantly more likely to double-check automated functioning against other cues and less likely to commit errors than those who did not share this perception. Pilots were also lilkely to erroneously "remember" the presence of expected cues when describing their decision-making processes.

Greater decision-making competence is associated with greater expected-value sensitivity, but not overall risk taking: an examination of concurrent validity.

PubMed

Parker, Andrew M; Weller, Joshua A

2015-01-01

Decision-making competence reflects individual differences in the susceptibility to committing decision-making errors, measured using tasks common from behavioral decision research (e.g., framing effects, under/overconfidence, following decision rules). Prior research demonstrates that those with higher decision-making competence report lower incidence of health-risking and antisocial behaviors, but there has been less focus on intermediate processes that may impact real-world decisions, and, in particular, those implicated by normative models. Here we test the associations between measures of youth decision-making competence (Y-DMC) and one such process, the degree to which individuals make choices consistent with maximizing expected value (EV). Using a task involving hypothetical gambles, we find that greater EV sensitivity is associated with greater Y-DMC. Higher Y-DMC scores are associated with (a) choosing risky options when EV favors those options and (b) avoiding risky options when EV favors a certain option. This relationship is stronger for gambles that involved potential losses. The results suggest that Y-DMC captures decision processes consistent with standard normative evaluations of risky decisions.

Decision-making in nursing practice: An integrative literature review.

PubMed

Nibbelink, Christine W; Brewer, Barbara B

2018-03-01

To identify and summarise factors and processes related to registered nurses' patient care decision-making in medical-surgical environments. A secondary goal of this literature review was to determine whether medical-surgical decision-making literature included factors that appeared to be similar to concepts and factors in naturalistic decision making (NDM). Decision-making in acute care nursing requires an evaluation of many complex factors. While decision-making research in acute care nursing is prevalent, errors in decision-making continue to lead to poor patient outcomes. Naturalistic decision making may provide a framework for further exploring decision-making in acute care nursing practice. A better understanding of the literature is needed to guide future research to more effectively support acute care nurse decision-making. PubMed and CINAHL databases were searched, and research meeting criteria was included. Data were identified from all included articles, and themes were developed based on these data. Key findings in this review include nursing experience and associated factors; organisation and unit culture influences on decision-making; education; understanding patient status; situation awareness; and autonomy. Acute care nurses employ a variety of decision-making factors and processes and informally identify experienced nurses to be important resources for decision-making. Incorporation of evidence into acute care nursing practice continues to be a struggle for acute care nurses. This review indicates that naturalistic decision making may be applicable to decision-making nursing research. Experienced nurses bring a broad range of previous patient encounters to their practice influencing their intuitive, unconscious processes which facilitates decision-making. Using naturalistic decision making as a conceptual framework to guide research may help with understanding how to better support less experienced nurses' decision-making for enhanced patient outcomes. © 2017 John Wiley & Sons Ltd.

The pitfalls of premature closure: clinical decision-making in a case of aortic dissection

PubMed Central

Kumar, Bharat; Kanna, Balavenkatesh; Kumar, Suresh

2011-01-01

Premature closure is a type of cognitive error in which the physician fails to consider reasonable alternatives after an initial diagnosis is made. It is a common cause of delayed diagnosis and misdiagnosis borne out of a faulty clinical decision-making process. The authors present a case of aortic dissection in which premature closure was avoided by the aggressive pursuit of the appropriate differential diagnosis, and discuss the importance of disciplined clinical decision-making in the setting of chest pain. PMID:22679162

Data-driven Modelling for decision making under uncertainty

NASA Astrophysics Data System (ADS)

Angria S, Layla; Dwi Sari, Yunita; Zarlis, Muhammad; Tulus

2018-01-01

The rise of the issues with the uncertainty of decision making has become a very warm conversation in operation research. Many models have been presented, one of which is with data-driven modelling (DDM). The purpose of this paper is to extract and recognize patterns in data, and find the best model in decision-making problem under uncertainty by using data-driven modeling approach with linear programming, linear and nonlinear differential equation, bayesian approach. Model criteria tested to determine the smallest error, and it will be the best model that can be used.

Working memory capacity as controlled attention in tactical decision making.

PubMed

Furley, Philip A; Memmert, Daniel

2012-06-01

The controlled attention theory of working memory capacity (WMC, Engle 2002) suggests that WMC represents a domain free limitation in the ability to control attention and is predictive of an individual's capability of staying focused, avoiding distraction and impulsive errors. In the present paper we test the predictive power of WMC in computer-based sport decision-making tasks. Experiment 1 demonstrated that high-WMC athletes were better able at focusing their attention on tactical decision making while blocking out irrelevant auditory distraction. Experiment 2 showed that high-WMC athletes were more successful at adapting their tactical decision making according to the situation instead of relying on prepotent inappropriate decisions. The present results provide additional but also unique support for the controlled attention theory of WMC by demonstrating that WMC is predictive of controlling attention in complex settings among different modalities and highlight the importance of working memory in tactical decision making.

Expert Intraoperative Judgment and Decision-Making: Defining the Cognitive Competencies for Safe Laparoscopic Cholecystectomy.

PubMed

Madani, Amin; Watanabe, Yusuke; Feldman, Liane S; Vassiliou, Melina C; Barkun, Jeffrey S; Fried, Gerald M; Aggarwal, Rajesh

2015-11-01

Bile duct injuries from laparoscopic cholecystectomy remain a significant source of morbidity and are often the result of intraoperative errors in perception, judgment, and decision-making. This qualitative study aimed to define and characterize higher-order cognitive competencies required to safely perform a laparoscopic cholecystectomy. Hierarchical and cognitive task analyses for establishing a critical view of safety during laparoscopic cholecystectomy were performed using qualitative methods to map the thoughts and practices that characterize expert performance. Experts with more than 5 years of experience, and who have performed at least 100 laparoscopic cholecystectomies, participated in semi-structured interviews and field observations. Verbal data were transcribed verbatim, supplemented with content from published literature, coded, thematically analyzed using grounded-theory by 2 independent reviewers, and synthesized into a list of items. A conceptual framework was created based on 10 interviews with experts, 9 procedures, and 18 literary sources. Experts included 6 minimally invasive surgeons, 2 hepato-pancreatico-biliary surgeons, and 2 acute care general surgeons (median years in practice, 11 [range 8 to 14]). One hundred eight cognitive elements (35 [32%] related to situation awareness, 47 [44%] involving decision-making, and 26 [24%] action-oriented subtasks) and 75 potential errors were identified and categorized into 6 general themes and 14 procedural tasks. Of the 75 potential errors, root causes were mapped to errors in situation awareness (24 [32%]), decision-making (49 [65%]), or either one (61 [81%]). This study defines the competencies that are essential to establishing a critical view of safety and avoiding bile duct injuries during laparoscopic cholecystectomy. This framework may serve as the basis for instructional design, assessment tools, and quality-control metrics to prevent injuries and promote a culture of patient safety. Copyright © 2015 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

The information value of early career productivity in mathematics: a ROC analysis of prediction errors in bibliometricly informed decision making.

PubMed

Lindahl, Jonas; Danell, Rickard

The aim of this study was to provide a framework to evaluate bibliometric indicators as decision support tools from a decision making perspective and to examine the information value of early career publication rate as a predictor of future productivity. We used ROC analysis to evaluate a bibliometric indicator as a tool for binary decision making. The dataset consisted of 451 early career researchers in the mathematical sub-field of number theory. We investigated the effect of three different definitions of top performance groups-top 10, top 25, and top 50 %; the consequences of using different thresholds in the prediction models; and the added prediction value of information on early career research collaboration and publications in prestige journals. We conclude that early career performance productivity has an information value in all tested decision scenarios, but future performance is more predictable if the definition of a high performance group is more exclusive. Estimated optimal decision thresholds using the Youden index indicated that the top 10 % decision scenario should use 7 articles, the top 25 % scenario should use 7 articles, and the top 50 % should use 5 articles to minimize prediction errors. A comparative analysis between the decision thresholds provided by the Youden index which take consequences into consideration and a method commonly used in evaluative bibliometrics which do not take consequences into consideration when determining decision thresholds, indicated that differences are trivial for the top 25 and the 50 % groups. However, a statistically significant difference between the methods was found for the top 10 % group. Information on early career collaboration and publication strategies did not add any prediction value to the bibliometric indicator publication rate in any of the models. The key contributions of this research is the focus on consequences in terms of prediction errors and the notion of transforming uncertainty into risk when we are choosing decision thresholds in bibliometricly informed decision making. The significance of our results are discussed from the point of view of a science policy and management.

New paradigm for understanding in-flight decision making errors: a neurophysiological model leveraging human factors.

PubMed

Souvestre, P A; Landrock, C K; Blaber, A P

2008-08-01

Human factors centered aviation accident analyses report that skill based errors are known to be cause of 80% of all accidents, decision making related errors 30% and perceptual errors 6%1. In-flight decision making error is a long time recognized major avenue leading to incidents and accidents. Through the past three decades, tremendous and costly efforts have been developed to attempt to clarify causation, roles and responsibility as well as to elaborate various preventative and curative countermeasures blending state of the art biomedical, technological advances and psychophysiological training strategies. In-flight related statistics have not been shown significantly changed and a significant number of issues remain not yet resolved. Fine Postural System and its corollary, Postural Deficiency Syndrome (PDS), both defined in the 1980's, are respectively neurophysiological and medical diagnostic models that reflect central neural sensory-motor and cognitive controls regulatory status. They are successfully used in complex neurotraumatology and related rehabilitation for over two decades. Analysis of clinical data taken over a ten-year period from acute and chronic post-traumatic PDS patients shows a strong correlation between symptoms commonly exhibited before, along side, or even after error, and sensory-motor or PDS related symptoms. Examples are given on how PDS related central sensory-motor control dysfunction can be correctly identified and monitored via a neurophysiological ocular-vestibular-postural monitoring system. The data presented provides strong evidence that a specific biomedical assessment methodology can lead to a better understanding of in-flight adaptive neurophysiological, cognitive and perceptual dysfunctional status that could induce in flight-errors. How relevant human factors can be identified and leveraged to maintain optimal performance will be addressed.

Making electronic prescribing alerts more effective: scenario-based experimental study in junior doctors

PubMed Central

Shah, Priya; Wyatt, Jeremy C; Makubate, Boikanyo; Cross, Frank W

2011-01-01

Objective Expert authorities recommend clinical decision support systems to reduce prescribing error rates, yet large numbers of insignificant on-screen alerts presented in modal dialog boxes persistently interrupt clinicians, limiting the effectiveness of these systems. This study compared the impact of modal and non-modal electronic (e-) prescribing alerts on prescribing error rates, to help inform the design of clinical decision support systems. Design A randomized study of 24 junior doctors each performing 30 simulated prescribing tasks in random order with a prototype e-prescribing system. Using a within-participant design, doctors were randomized to be shown one of three types of e-prescribing alert (modal, non-modal, no alert) during each prescribing task. Measurements The main outcome measure was prescribing error rate. Structured interviews were performed to elicit participants' preferences for the prescribing alerts and their views on clinical decision support systems. Results Participants exposed to modal alerts were 11.6 times less likely to make a prescribing error than those not shown an alert (OR 11.56, 95% CI 6.00 to 22.26). Those shown a non-modal alert were 3.2 times less likely to make a prescribing error (OR 3.18, 95% CI 1.91 to 5.30) than those not shown an alert. The error rate with non-modal alerts was 3.6 times higher than with modal alerts (95% CI 1.88 to 7.04). Conclusions Both kinds of e-prescribing alerts significantly reduced prescribing error rates, but modal alerts were over three times more effective than non-modal alerts. This study provides new evidence about the relative effects of modal and non-modal alerts on prescribing outcomes. PMID:21836158

Role of the medial prefrontal cortex in impaired decision making in juvenile attention-deficit/hyperactivity disorder.

PubMed

Hauser, Tobias U; Iannaccone, Reto; Ball, Juliane; Mathys, Christoph; Brandeis, Daniel; Walitza, Susanne; Brem, Silvia

2014-10-01

Attention-deficit/hyperactivity disorder (ADHD) has been associated with deficient decision making and learning. Models of ADHD have suggested that these deficits could be caused by impaired reward prediction errors (RPEs). Reward prediction errors are signals that indicate violations of expectations and are known to be encoded by the dopaminergic system. However, the precise learning and decision-making deficits and their neurobiological correlates in ADHD are not well known. To determine the impaired decision-making and learning mechanisms in juvenile ADHD using advanced computational models, as well as the related neural RPE processes using multimodal neuroimaging. Twenty adolescents with ADHD and 20 healthy adolescents serving as controls (aged 12-16 years) were examined using a probabilistic reversal learning task while simultaneous functional magnetic resonance imaging and electroencephalogram were recorded. Learning and decision making were investigated by contrasting a hierarchical Bayesian model with an advanced reinforcement learning model and by comparing the model parameters. The neural correlates of RPEs were studied in functional magnetic resonance imaging and electroencephalogram. Adolescents with ADHD showed more simplistic learning as reflected by the reinforcement learning model (exceedance probability, Px = .92) and had increased exploratory behavior compared with healthy controls (mean [SD] decision steepness parameter β: ADHD, 4.83 [2.97]; controls, 6.04 [2.53]; P = .02). The functional magnetic resonance imaging analysis revealed impaired RPE processing in the medial prefrontal cortex during cue as well as during outcome presentation (P < .05, family-wise error correction). The outcome-related impairment in the medial prefrontal cortex could be attributed to deficient processing at 200 to 400 milliseconds after feedback presentation as reflected by reduced feedback-related negativity (ADHD, 0.61 [3.90] μV; controls, -1.68 [2.52] μV; P = .04). The combination of computational modeling of behavior and multimodal neuroimaging revealed that impaired decision making and learning mechanisms in adolescents with ADHD are driven by impaired RPE processing in the medial prefrontal cortex. This novel, combined approach furthers the understanding of the pathomechanisms in ADHD and may advance treatment strategies.

Skin-deep diagnosis: affective bias and zebra retreat complicating the diagnosis of systemic sclerosis.

PubMed

Miller, Chad S

2013-01-01

Nearly half of medical errors can be attributed to an error of clinical reasoning or decision making. It is estimated that the correct diagnosis is missed or delayed in between 5% and 14% of acute hospital admissions. Through understanding why and how physicians make these errors, it is hoped that strategies can be developed to decrease the number of these errors. In the present case, a patient presented with dyspnea, gastrointestinal symptoms and weight loss; the diagnosis was initially missed when the treating physicians took mental short cuts and used heuristics as in this case. Heuristics have an inherent bias that can lead to faulty reasoning or conclusions, especially in complex or difficult cases. Affective bias, which is the overinvolvement of emotion in clinical decision making, limited the available information for diagnosis because of the hesitancy to acquire a full history and perform a complete physical examination in this patient. Zebra retreat, another type of bias, is when a rare diagnosis figures prominently on the differential diagnosis but the physician retreats for various reasons. Zebra retreat also factored in the delayed diagnosis. Through the description of these clinical reasoning errors in an actual case, it is hoped that future errors can be prevented or inspiration for additional research in this area will develop.

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Hammer, John M.; Wan, C. Yoon; Vasandani, Vijay

1987-01-01

The current research is focused on detection of human error and protection from its consequences. A program for monitoring pilot error by comparing pilot actions to a script was described. It dealt primarily with routine errors (slips) that occurred during checklist activity. The model to which operator actions were compared was a script. Current research is an extension along these two dimensions. The ORS fault detection aid uses a sophisticated device model rather than a script. The newer initiative, the model-based and constraint-based warning system, uses an even more sophisticated device model and is to prevent all types of error, not just slips or bad decision.

78 FR 43969 - Agency Information Collection (Regulation for Reconsideration of Denied Claims) Activity Under...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-22

... collection. Abstract: Veterans who disagree with the initial decision denying their healthcare benefits in... allows decision making to be more responsive to Veterans using the VA healthcare system. An agency may... date of the initial decision. The request must state why the decision is in error and include any new...

75 FR 25321 - Agency Information Collection (Regulation for Reconsideration of Denied Claims) Activity Under...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-07

... collection. Abstract: Veterans who disagree with the initial decision denying their healthcare benefits in... appeals and allows decision making to be more responsive to veterans using the VA healthcare system. An... year of the date of the initial decision. The request must state why the decision is in error and...

Conflict between place and response navigation strategies: effects on vicarious trial and error (VTE) behaviors.

PubMed

Schmidt, Brandy; Papale, Andrew; Redish, A David; Markus, Etan J

2013-02-15

Navigation can be accomplished through multiple decision-making strategies, using different information-processing computations. A well-studied dichotomy in these decision-making strategies compares hippocampal-dependent "place" and dorsal-lateral striatal-dependent "response" strategies. A place strategy depends on the ability to flexibly respond to environmental cues, while a response strategy depends on the ability to quickly recognize and react to situations with well-learned action-outcome relationships. When rats reach decision points, they sometimes pause and orient toward the potential routes of travel, a process termed vicarious trial and error (VTE). VTE co-occurs with neurophysiological information processing, including sweeps of representation ahead of the animal in the hippocampus and transient representations of reward in the ventral striatum and orbitofrontal cortex. To examine the relationship between VTE and the place/response strategy dichotomy, we analyzed data in which rats were cued to switch between place and response strategies on a plus maze. The configuration of the maze allowed for place and response strategies to work competitively or cooperatively. Animals showed increased VTE on trials entailing competition between navigational systems, linking VTE with deliberative decision-making. Even in a well-learned task, VTE was preferentially exhibited when a spatial selection was required, further linking VTE behavior with decision-making associated with hippocampal processing.

Prediction Error Representation in Individuals With Generalized Anxiety Disorder During Passive Avoidance.

PubMed

White, Stuart F; Geraci, Marilla; Lewis, Elizabeth; Leshin, Joseph; Teng, Cindy; Averbeck, Bruno; Meffert, Harma; Ernst, Monique; Blair, James R; Grillon, Christian; Blair, Karina S

2017-02-01

Deficits in reinforcement-based decision making have been reported in generalized anxiety disorder. However, the pathophysiology of these deficits is largely unknown; published studies have mainly examined adolescents, and the integrity of core functional processes underpinning decision making remains undetermined. In particular, it is unclear whether the representation of reinforcement prediction error (PE) (the difference between received and expected reinforcement) is disrupted in generalized anxiety disorder. This study addresses these issues in adults with the disorder. Forty-six unmedicated individuals with generalized anxiety disorder and 32 healthy comparison subjects group-matched on IQ, gender, and age performed a passive avoidance task while undergoing functional MRI. Data analyses were performed using a computational modeling approach. Behaviorally, individuals with generalized anxiety disorder showed impaired reinforcement-based decision making. Imaging results revealed that during feedback, individuals with generalized anxiety disorder relative to healthy subjects showed a reduced correlation between PE and activity within the ventromedial prefrontal cortex, ventral striatum, and other structures implicated in decision making. In addition, individuals with generalized anxiety disorder relative to healthy participants showed a reduced correlation between punishment PEs, but not reward PEs, and activity within the left and right lentiform nucleus/putamen. This is the first study to identify computational impairments during decision making in generalized anxiety disorder. PE signaling is significantly disrupted in individuals with the disorder and may lead to their decision-making deficits and excessive worry about everyday problems by disrupting the online updating ("reality check") of the current relationship between the expected values of current response options and the actual received rewards and punishments.

Swarm intelligence: when uncertainty meets conflict.

PubMed

Conradt, Larissa; List, Christian; Roper, Timothy J

2013-11-01

Good decision making is important for the survival and fitness of stakeholders, but decisions usually involve uncertainty and conflict. We know surprisingly little about profitable decision-making strategies in conflict situations. On the one hand, sharing decisions with others can pool information and decrease uncertainty (swarm intelligence). On the other hand, sharing decisions can hand influence to individuals whose goals conflict. Thus, when should an animal share decisions with others? Using a theoretical model, we show that, contrary to intuition, decision sharing by animals with conflicting goals often increases individual gains as well as decision accuracy. Thus, conflict-far from hampering effective decision making-can improve decision outcomes for all stakeholders, as long as they share large-scale goals. In contrast, decisions shared by animals without conflict were often surprisingly poor. The underlying mechanism is that animals with conflicting goals are less correlated in individual choice errors. These results provide a strong argument in the interest of all stakeholders for not excluding other (e.g., minority) factions from collective decisions. The observed benefits of including diverse factions among the decision makers could also be relevant to human collective decision making.

Complex contexts and relationships affect clinical decisions in group therapy.

PubMed

Tasca, Giorgio A; Mcquaid, Nancy; Balfour, Louise

2016-09-01

Clinical errors tend to be underreported even though examining them can provide important training and professional development opportunities. The group therapy context may be prone to clinician errors because of the added complexity within which therapists work and patients receive treatment. We discuss clinical errors that occurred within a group therapy in which a patient for whom group was not appropriate was admitted to the treatment and then was not removed by the clinicians. This was countertherapeutic for both patient and group. Two clinicians were involved: a clinical supervisor who initially assessed and admitted the patient to the group, and a group therapist. To complicate matters, the group therapy occurred within the context of a clinical research trial. The errors, possible solutions, and recommendations are discussed within Reason's Organizational Accident Model (Reason, 2000). In particular, we discuss clinician errors in the context of countertransference and clinician heuristics, group therapy as a local work condition that complicates clinical decision-making, and the impact of the research context as a latent organizational factor. We also present clinical vignettes from the pregroup preparation, group therapy, and supervision. Group therapists are more likely to avoid errors in clinical decisions if they engage in reflective practice about their internal experiences and about the impact of the context in which they work. Therapists must keep in mind the various levels of group functioning, especially related to the group-as-a-whole (i.e., group composition, cohesion, group climate, and safety) when making complex clinical decisions in order to optimize patient outcomes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Follow the heart or the head? The interactive influence model of emotion and cognition.

PubMed

Luo, Jiayi; Yu, Rongjun

2015-01-01

The experience of emotion has a powerful influence on daily-life decision making. Following Plato's description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in "the head") reins in our impulses (from "the heart") and overrides our snap judgments. However, from Darwin's evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. Here, drawing findings from behavioral economics and neuroeconomics, we provide a new model, labeled "The interactive influence model of emotion and cognition," to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making.

fMRI evidence for a dual process account of the speed-accuracy tradeoff in decision-making.

PubMed

Ivanoff, Jason; Branning, Philip; Marois, René

2008-07-09

The speed and accuracy of decision-making have a well-known trading relationship: hasty decisions are more prone to errors while careful, accurate judgments take more time. Despite the pervasiveness of this speed-accuracy trade-off (SAT) in decision-making, its neural basis is still unknown. Using functional magnetic resonance imaging (fMRI) we show that emphasizing the speed of a perceptual decision at the expense of its accuracy lowers the amount of evidence-related activity in lateral prefrontal cortex. Moreover, this speed-accuracy difference in lateral prefrontal cortex activity correlates with the speed-accuracy difference in the decision criterion metric of signal detection theory. We also show that the same instructions increase baseline activity in a dorso-medial cortical area involved in the internal generation of actions. These findings suggest that the SAT is neurally implemented by modulating not only the amount of externally-derived sensory evidence used to make a decision, but also the internal urge to make a response. We propose that these processes combine to control the temporal dynamics of the speed-accuracy trade-off in decision-making.

A Model of Supervisor Decision-Making in the Accommodation of Workers with Low Back Pain.

PubMed

Williams-Whitt, Kelly; Kristman, Vicki; Shaw, William S; Soklaridis, Sophie; Reguly, Paula

2016-09-01

Purpose To explore supervisors' perspectives and decision-making processes in the accommodation of back injured workers. Methods Twenty-three semi-structured, in-depth interviews were conducted with supervisors from eleven Canadian organizations about their role in providing job accommodations. Supervisors were identified through an on-line survey and interviews were recorded, transcribed and entered into NVivo software. The initial analyses identified common units of meaning, which were used to develop a coding guide. Interviews were coded, and a model of supervisor decision-making was developed based on the themes, categories and connecting ideas identified in the data. Results The decision-making model includes a process element that is described as iterative "trial and error" decision-making. Medical restrictions are compared to job demands, employee abilities and available alternatives. A feasible modification is identified through brainstorming and then implemented by the supervisor. Resources used for brainstorming include information, supervisor experience and autonomy, and organizational supports. The model also incorporates the experience of accommodation as a job demand that causes strain for the supervisor. Accommodation demands affect the supervisor's attitude, brainstorming and monitoring effort, and communication with returning employees. Resources and demands have a combined effect on accommodation decision complexity, which in turn affects the quality of the accommodation option selected. If the employee is unable to complete the tasks or is reinjured during the accommodation, the decision cycle repeats. More frequent iteration through the trial and error process reduces the likelihood of return to work success. Conclusion A series of propositions is developed to illustrate the relationships among categories in the model. The model and propositions show: (a) the iterative, problem solving nature of the RTW process; (b) decision resources necessary for accommodation planning, and (c) the impact accommodation demands may have on supervisors and RTW quality.

Training of perceptual-cognitive skills in offside decision making.

PubMed

Catteeuw, Peter; Gilis, Bart; Jaspers, Arne; Wagemans, Johan; Helsen, Werner

2010-12-01

This study investigates the effect of two off-field training formats to improve offside decision making. One group trained with video simulations and another with computer animations. Feedback after every offside situation allowed assistant referees to compensate for the consequences of the flash-lag effect and to improve their decision-making accuracy. First, response accuracy improved and flag errors decreased for both training groups implying that training interventions with feedback taught assistant referees to better deal with the flash-lag effect. Second, the results demonstrated no effect of format, although assistant referees rated video simulations higher for fidelity than computer animations. This implies that a cognitive correction to a perceptual effect can be learned also when the format does not correspond closely with the original perceptual situation. Off-field offside decision-making training should be considered as part of training because it is a considerable help to gain more experience and to improve overall decision-making performance.

[Clinical economics: a concept to optimize healthcare services].

PubMed

Porzsolt, F; Bauer, K; Henne-Bruns, D

2012-03-01

Clinical economics strives to support healthcare decisions by economic considerations. Making economic decisions does not mean saving costs but rather comparing the gained added value with the burden which has to be accepted. The necessary rules are offered in various disciplines, such as economy, epidemiology and ethics. Medical doctors have recognized these rules but are not applying them in daily clinical practice. This lacking orientation leads to preventable errors. Examples of these errors are shown for diagnosis, screening, prognosis and therapy. As these errors can be prevented by application of clinical economic principles the possible consequences for optimization of healthcare are discussed.

How we learn to make decisions: rapid propagation of reinforcement learning prediction errors in humans.

PubMed

Krigolson, Olav E; Hassall, Cameron D; Handy, Todd C

2014-03-01

Our ability to make decisions is predicated upon our knowledge of the outcomes of the actions available to us. Reinforcement learning theory posits that actions followed by a reward or punishment acquire value through the computation of prediction errors-discrepancies between the predicted and the actual reward. A multitude of neuroimaging studies have demonstrated that rewards and punishments evoke neural responses that appear to reflect reinforcement learning prediction errors [e.g., Krigolson, O. E., Pierce, L. J., Holroyd, C. B., & Tanaka, J. W. Learning to become an expert: Reinforcement learning and the acquisition of perceptual expertise. Journal of Cognitive Neuroscience, 21, 1833-1840, 2009; Bayer, H. M., & Glimcher, P. W. Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47, 129-141, 2005; O'Doherty, J. P. Reward representations and reward-related learning in the human brain: Insights from neuroimaging. Current Opinion in Neurobiology, 14, 769-776, 2004; Holroyd, C. B., & Coles, M. G. H. The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679-709, 2002]. Here, we used the brain ERP technique to demonstrate that not only do rewards elicit a neural response akin to a prediction error but also that this signal rapidly diminished and propagated to the time of choice presentation with learning. Specifically, in a simple, learnable gambling task, we show that novel rewards elicited a feedback error-related negativity that rapidly decreased in amplitude with learning. Furthermore, we demonstrate the existence of a reward positivity at choice presentation, a previously unreported ERP component that has a similar timing and topography as the feedback error-related negativity that increased in amplitude with learning. The pattern of results we observed mirrored the output of a computational model that we implemented to compute reward prediction errors and the changes in amplitude of these prediction errors at the time of choice presentation and reward delivery. Our results provide further support that the computations that underlie human learning and decision-making follow reinforcement learning principles.

[The Role and Function of Informatics Nurses in Information Technology Decision-Making].

PubMed

Lee, Tso-Ying

2017-08-01

The medical environment has changed greatly with the coming of the information age, and, increasingly, the operating procedures for medical services have been altered in keeping with the trend toward mobile, paperless services. Informatization has the potential to improve the working efficiency of medical personnel, enhance patient care safety, and give medical organizations a positive image. Informatics nurses play an important role in the decision-making processes that accompany informatization. As one of the decision-making links in the information technology lifecycle, this role affects the success of the development and operation of information systems. The present paper examines the functions and professional knowledge that informatics nurses must possess during the technology lifecycle, the four stages of which include: planning, analysis, design/development/revision, and implementation/assessment/support/maintenance. The present paper further examines the decision-making shortcomings and errors that an informatics nurses may make during the decision-making process. We hope that this paper will serve as an effective and useful reference for informatics nurses during the informatization decision-making process.

Noradrenergic modulation of vicarious trial-and-error behavior during a spatial decision-making task in rats.

PubMed

Amemiya, S; Noji, T; Kubota, N; Nishijima, T; Kita, I

2014-04-18

Deliberation between possible options before making a decision is crucial to responding with an optimal choice. However, the neural mechanisms regulating this deliberative decision-making process are still unclear. Recent studies have proposed that the locus coeruleus-noradrenaline (LC-NA) system plays a role in attention, behavioral flexibility, and exploration, which contribute to the search for an optimal choice under uncertain situations. In the present study, we examined whether the LC-NA system relates to the deliberative process in a T-maze spatial decision-making task in rats. To quantify deliberation in rats, we recorded vicarious trial-and-error behavior (VTE), which is considered to reflect a deliberative process exploring optimal choices. In experiment 1, we manipulated the difficulty of choice by varying the amount of reward pellets between the two maze arms (0 vs. 4, 1 vs. 3, 2 vs. 2). A difficulty-dependent increase in VTE was accompanied by a reduction of choice bias toward the high reward arm and an increase in time required to select one of the two arms in the more difficult manipulation. In addition, the increase of c-Fos-positive NA neurons in the LC depended on the task difficulty and the amount of c-Fos expression in LC-NA neurons positively correlated with the occurrence of VTE. In experiment 2, we inhibited LC-NA activity by injection of clonidine, an agonist of the alpha2 autoreceptor, during a decision-making task (1 vs. 3). The clonidine injection suppressed occurrence of VTE in the early phase of the task and subsequently impaired a valuable choice later in the task. These results suggest that the LC-NA system regulates the deliberative process during decision-making. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Pressing the Approach: A NASA Study of 19 Recent Accidents Yields a New Perspective on Pilot Error

NASA Technical Reports Server (NTRS)

Berman, Benjamin A.; Dismukes, R. Key

2007-01-01

This article begins with a review of two sample airplane accidents that were caused by pilot error. The analysis of these and 17 other accidents suggested that almost all experienced pilot operating in the same environment in which the accident crews were operating and knowing only what the accident crews knew at each moment of the flight, would be vulnerable to making a similar decision and similar errors. Whether a particular crew in a given situation makes errors depends on somewhat random interaction of factors. Two themes that seem to be prevalent in these cases are: Plan Continuation Bias, and Snowballing Workload.

Simulation and Modeling Efforts to Support Decision Making in Healthcare Supply Chain Management

PubMed Central

Lazarova-Molnar, Sanja

2014-01-01

Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges. PMID:24683333

Defining and Measuring Decision-Making for the Management of Trauma Patients.

PubMed

Madani, Amin; Gips, Amanda; Razek, Tarek; Deckelbaum, Dan L; Mulder, David S; Grushka, Jeremy R

Effective management of trauma patients is heavily dependent on sound judgment and decision-making. Yet, current methods for training and assessing these advanced cognitive skills are subjective, lack standardization, and are prone to error. This qualitative study aims to define and characterize the cognitive and interpersonal competencies required to optimally manage injured patients. Cognitive and hierarchical task analyses for managing unstable trauma patients were performed using qualitative methods to map the thoughts, behaviors, and practices that characterize expert performance. Trauma team leaders and board-certified trauma surgeons participated in semistructured interviews that were transcribed verbatim. Data were supplemented with content from published literature and prospectively collected field notes from observations of the trauma team during trauma activations. The data were coded and analyzed using grounded theory by 2 independent reviewers. A framework was created based on 14 interviews with experts (lasting 1-2 hours each), 35 field observations (20 [57%] blunt; 15 [43%] penetrating; median Injury Severity Score 20 [13-25]), and 15 literary sources. Experts included 11 trauma surgeons and 3 emergency physicians from 7 Level 1 academic institutions in North America (median years in practice: 12 [8-17]). Twenty-nine competencies were identified, including 17 (59%) related to situation awareness, 6 (21%) involving decision-making, and 6 (21%) requiring interpersonal skills. Of 40 potential errors that were identified, root causes were mapped to errors in situation awareness (20 [50%]), decision-making (10 [25%]), or interpersonal skills (10 [25%]). This study defines cognitive and interpersonal competencies that are essential for the management of trauma patients. This framework may serve as the basis for novel curricula to train and assess decision-making skills, and to develop quality-control metrics to improve team and individual performance. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Is More Screening Better? The Relationship between Frequent Screening, Accurate Decisions, and Reading Proficiency

ERIC Educational Resources Information Center

VanDerHeyden, Amanda M.; Burns, Matthew K.; Bonifay, Wesley

2018-01-01

Screening is necessary to detect risk and prevent reading failure. Yet the amount of screening that commonly occurs in U.S. schools may undermine its value, creating more error in decision making and lost instructional opportunity. This 2-year longitudinal study examined the decision accuracy associated with collecting concurrent reading screening…

Artificial Experience: Situation Awareness Training in Nursing

ERIC Educational Resources Information Center

Hinton, Janine E.

2011-01-01

The quasi-experimental research study developed and tested an education process to reduce and trap medication errors. The study was framed by Endsley's (1995a) model of situation awareness in dynamic decision making. Situation awareness improvement strategies were practiced during high-fidelity clinical simulations. Harmful medication errors occur…

ANFIS multi criteria decision making for overseas construction projects: a methodology

NASA Astrophysics Data System (ADS)

Utama, W. P.; Chan, A. P. C.; Zulherman; Zahoor, H.; Gao, R.; Jumas, D. Y.

2018-02-01

A critical part when a company targeting a foreign market is how to make a better decision in connection with potential project selection. Since different attributes of information are often incomplete, imprecise and ill-defined in overseas projects selection, the process of decision making by relying on the experiences and intuition is a risky attitude. This paper aims to demonstrate a decision support method in deciding overseas construction projects (OCPs). An Adaptive Neuro-Fuzzy Inference System (ANFIS), the amalgamation of Neural Network and Fuzzy Theory, was used as decision support tool to decide to go or not go on OCPs. Root mean square error (RMSE) and coefficient of correlation (R) were employed to identify the ANFIS system indicating an optimum and efficient result. The optimum result was obtained from ANFIS network with two input membership functions, Gaussian membership function (gaussmf) and hybrid optimization method. The result shows that ANFIS may help the decision-making process for go/not go decision in OCPs.

Impaired decision-making under risk is associated with gaming-specific inhibition deficits among college students with Internet gaming disorder.

PubMed

Yao, Yuan-Wei; Wang, Ling-Jiao; Yip, Sarah W; Chen, Pin-Ru; Li, Song; Xu, Jiansong; Zhang, Jin-Tao; Deng, Lin-Yuan; Liu, Qin-Xue; Fang, Xiao-Yi

2015-09-30

A growing body of evidence indicates that both inhibition and decision-making deficits play essential roles in the development and maintenance of Internet gaming disorder (IGD). Clarifying whether impaired decision-making among individuals with IGD is related to poor inhibition will advance our understanding of IGD and contribute to intervention development. However, the relationship between these two functions remains unclear. In this study, we sought to systemically examine inhibitory processes, decision-making and the relationship between the two among individuals with IGD. Thirty-four individuals with IGD and 32 matched healthy controls (HCs) were recruited. In comparison to HCs, IGD subjects demonstrated inhibition deficits during performance of the gaming-related Go/No-Go task and impaired decision-making under risk. In addition, errors on No-Go trials during the gaming-related Go/No-Go task were positively associated with decision-making impairments under risk but not under ambiguity among IGD subjects. These results suggest individuals with IGD are impaired in some aspects of inhibition and decision-making functions, and that decision-making deficits under risk are linked to poor inhibition specifically related to gaming cues, which has implications for the development of novel intervention. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Follow the heart or the head? The interactive influence model of emotion and cognition

PubMed Central

Luo, Jiayi; Yu, Rongjun

2015-01-01

The experience of emotion has a powerful influence on daily-life decision making. Following Plato’s description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in “the head”) reins in our impulses (from “the heart”) and overrides our snap judgments. However, from Darwin’s evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. Here, drawing findings from behavioral economics and neuroeconomics, we provide a new model, labeled “The interactive influence model of emotion and cognition,” to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making. PMID:25999889

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.

Aeronautical Decision Making for Student and Private Pilots.

DTIC Science & Technology

1987-05-01

you learn to gain voluntary control over your body to achieve the relaxation response. In autogenic training , you learn to shut down many bodily...Ahstruct "Aviation accident data indicate that the majority of aircraft mishaps are due to judgment error. This training manual is part of a project to...develop materials and techniques to help improve pilot decision making. Training programs using prototype versions of these materials have

An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning

PubMed Central

Balasubramani, Pragathi P.; Chakravarthy, V. Srinivasa; Ravindran, Balaraman; Moustafa, Ahmed A.

2014-01-01

Although empirical and neural studies show that serotonin (5HT) plays many functional roles in the brain, prior computational models mostly focus on its role in behavioral inhibition. In this study, we present a model of risk based decision making in a modified Reinforcement Learning (RL)-framework. The model depicts the roles of dopamine (DA) and serotonin (5HT) in Basal Ganglia (BG). In this model, the DA signal is represented by the temporal difference error (δ), while the 5HT signal is represented by a parameter (α) that controls risk prediction error. This formulation that accommodates both 5HT and DA reconciles some of the diverse roles of 5HT particularly in connection with the BG system. We apply the model to different experimental paradigms used to study the role of 5HT: (1) Risk-sensitive decision making, where 5HT controls risk assessment, (2) Temporal reward prediction, where 5HT controls time-scale of reward prediction, and (3) Reward/Punishment sensitivity, in which the punishment prediction error depends on 5HT levels. Thus the proposed integrated RL model reconciles several existing theories of 5HT and DA in the BG. PMID:24795614

Poor Decision Making is Associated with an Increased Risk of Mortality Among Community-Dwelling Older Persons without Dementia

PubMed Central

Boyle, Patricia A.; Wilson, Robert S.; Yu, Lei; Buchman, Aron S.; Bennett, David A.

2013-01-01

Background Decision making is thought to be an important determinant of health and well-being across the lifespan, but little is known about the association of decision making with mortality. Methods Participants were 675 older persons without dementia from the Rush Memory and Aging Project, a longitudinal cohort study of aging. Baseline assessments of decision making were used to predict the risk of mortality during up to 4 years of follow-up. Results The mean score on the decision making measure at baseline was 7.1 (SD=2.9, range: 0-12), with lower scores indicating poorer decision making. During up to 4 years of follow-up (mean=1.7 years), 40 (6% of 675) persons died. In a proportional hazards model adjusted for age, sex, and education, the risk of mortality increased by about 20% for each additional decision making error (HR=1.19, 95% CI 1.07, 1.32, p=0.002). Thus, a person who performed poorly on the measure of decision making (score=3, 10th percentile) was about four times more likely to die compared to a person who performed well (score=11, 90th percentile). Further, the association of decision making with mortality persisted after adjustment for the level of cognitive function. Conclusion Poor decision making is associated with an increased risk of mortality in old age even after accounting for cognitive function. PMID:23364306

Poor decision making is associated with an increased risk of mortality among community-dwelling older persons without dementia.

PubMed

Boyle, Patricia A; Wilson, Robert S; Yu, Lei; Buchman, Aron S; Bennett, David A

2013-01-01

Decision making is thought to be an important determinant of health and well-being across the lifespan, but little is known about the association of decision making with mortality. Participants were 675 older persons without dementia from the Rush Memory and Aging Project, a longitudinal cohort study of aging. Baseline assessments of decision making were used to predict the risk of mortality during up to 4 years of follow-up. The mean score on the decision making measure at baseline was 7.1 (SD = 2.9, range: 0-12), with lower scores indicating poorer decision making. During up to 4 years of follow-up (mean = 1.7 years), 40 (6% of 675) persons died. In a proportional hazards model adjusted for age, sex and education, the risk of mortality increased by about 20% for each additional decision making error (HR = 1.19, 95% CI = 1.07-1.32, p = 0.002). Thus, a person who performed poorly on the measure of decision making (score = 3, 10th percentile) was about 4 times more likely to die compared to a person who performed well (score = 11, 90th percentile). Further, the association of decision making with mortality persisted after adjustment for the level of cognitive function. Poor decision making is associated with an increased risk of mortality in old age even after accounting for cognitive function. Copyright © 2013 S. Karger AG, Basel.

Subsecond dopamine fluctuations in human striatum encode superposed error signals about actual and counterfactual reward

PubMed Central

Kishida, Kenneth T.; Saez, Ignacio; Lohrenz, Terry; Witcher, Mark R.; Laxton, Adrian W.; Tatter, Stephen B.; White, Jason P.; Ellis, Thomas L.; Phillips, Paul E. M.; Montague, P. Read

2016-01-01

In the mammalian brain, dopamine is a critical neuromodulator whose actions underlie learning, decision-making, and behavioral control. Degeneration of dopamine neurons causes Parkinson’s disease, whereas dysregulation of dopamine signaling is believed to contribute to psychiatric conditions such as schizophrenia, addiction, and depression. Experiments in animal models suggest the hypothesis that dopamine release in human striatum encodes reward prediction errors (RPEs) (the difference between actual and expected outcomes) during ongoing decision-making. Blood oxygen level-dependent (BOLD) imaging experiments in humans support the idea that RPEs are tracked in the striatum; however, BOLD measurements cannot be used to infer the action of any one specific neurotransmitter. We monitored dopamine levels with subsecond temporal resolution in humans (n = 17) with Parkinson’s disease while they executed a sequential decision-making task. Participants placed bets and experienced monetary gains or losses. Dopamine fluctuations in the striatum fail to encode RPEs, as anticipated by a large body of work in model organisms. Instead, subsecond dopamine fluctuations encode an integration of RPEs with counterfactual prediction errors, the latter defined by how much better or worse the experienced outcome could have been. How dopamine fluctuations combine the actual and counterfactual is unknown. One possibility is that this process is the normal behavior of reward processing dopamine neurons, which previously had not been tested by experiments in animal models. Alternatively, this superposition of error terms may result from an additional yet-to-be-identified subclass of dopamine neurons. PMID:26598677

Subsecond dopamine fluctuations in human striatum encode superposed error signals about actual and counterfactual reward.

PubMed

Kishida, Kenneth T; Saez, Ignacio; Lohrenz, Terry; Witcher, Mark R; Laxton, Adrian W; Tatter, Stephen B; White, Jason P; Ellis, Thomas L; Phillips, Paul E M; Montague, P Read

2016-01-05

In the mammalian brain, dopamine is a critical neuromodulator whose actions underlie learning, decision-making, and behavioral control. Degeneration of dopamine neurons causes Parkinson's disease, whereas dysregulation of dopamine signaling is believed to contribute to psychiatric conditions such as schizophrenia, addiction, and depression. Experiments in animal models suggest the hypothesis that dopamine release in human striatum encodes reward prediction errors (RPEs) (the difference between actual and expected outcomes) during ongoing decision-making. Blood oxygen level-dependent (BOLD) imaging experiments in humans support the idea that RPEs are tracked in the striatum; however, BOLD measurements cannot be used to infer the action of any one specific neurotransmitter. We monitored dopamine levels with subsecond temporal resolution in humans (n = 17) with Parkinson's disease while they executed a sequential decision-making task. Participants placed bets and experienced monetary gains or losses. Dopamine fluctuations in the striatum fail to encode RPEs, as anticipated by a large body of work in model organisms. Instead, subsecond dopamine fluctuations encode an integration of RPEs with counterfactual prediction errors, the latter defined by how much better or worse the experienced outcome could have been. How dopamine fluctuations combine the actual and counterfactual is unknown. One possibility is that this process is the normal behavior of reward processing dopamine neurons, which previously had not been tested by experiments in animal models. Alternatively, this superposition of error terms may result from an additional yet-to-be-identified subclass of dopamine neurons.

Form and Objective of the Decision Rule in Absolute Identification

NASA Technical Reports Server (NTRS)

Balakrishnan, J. D.

1997-01-01

In several conditions of a line length identification experiment, the subjects' decision making strategies were systematically biased against the responses on the edges of the stimulus range. When the range and number of the stimuli were small, the bias caused the percentage of correct responses to be highest in the center and lowest on the extremes of the range. Two general classes of decision rules that would explain these results are considered. The first class assumes that subjects intend to adopt an optimal decision rule, but systematically misrepresent one or more parameters of the decision making context. The second class assumes that subjects use a different measure of performance than the one assumed by the experimenter: instead of maximizing the chances of a correct response, the subject attempts to minimize the expected size of the response error (a "fidelity criterion"). In a second experiment, extended experience and feedback did not diminish the bias effect, but explicitly penalizing all response errors equally, regardless of their size, did reduce or eliminate it in some subjects. Both results favor the fidelity criterion over the optimal rule.

Development and preliminary user testing of the DCIDA (Dynamic computer interactive decision application) for 'nudging' patients towards high quality decisions.

PubMed

Bansback, Nick; Li, Linda C; Lynd, Larry; Bryan, Stirling

2014-08-01

Patient decision aids (PtDA) are developed to facilitate informed, value-based decisions about health. Research suggests that even when informed with necessary evidence and information, cognitive errors can prevent patients from choosing the option that is most congruent with their own values. We sought to utilize principles of behavioural economics to develop a computer application that presents information from conventional decision aids in a way that reduces these errors, subsequently promoting higher quality decisions. The Dynamic Computer Interactive Decision Application (DCIDA) was developed to target four common errors that can impede quality decision making with PtDAs: unstable values, order effects, overweighting of rare events, and information overload. Healthy volunteers were recruited to an interview to use three PtDAs converted to the DCIDA on a computer equipped with an eye tracker. Participants were first used a conventional PtDA, and then subsequently used the DCIDA version. User testing was assessed based on whether respondents found the software both usable: evaluated using a) eye-tracking, b) the system usability scale, and c) user verbal responses from a 'think aloud' protocol; and useful: evaluated using a) eye-tracking, b) whether preferences for options were changed, and c) and the decisional conflict scale. Of the 20 participants recruited to the study, 11 were male (55%), the mean age was 35, 18 had at least a high school education (90%), and 8 (40%) had a college or university degree. Eye-tracking results, alongside a mean system usability scale score of 73 (range 68-85), indicated a reasonable degree of usability for the DCIDA. The think aloud study suggested areas for further improvement. The DCIDA also appeared to be useful to participants wherein subjects focused more on the features of the decision that were most important to them (21% increase in time spent focusing on the most important feature). Seven subjects (25%) changed their preferred option when using DCIDA. Preliminary results suggest that DCIDA has potential to improve the quality of patient decision-making. Next steps include larger studies to test individual components of DCIDA and feasibility testing with patients making real decisions.

Does the cost function matter in Bayes decision rule?

PubMed

Schlü ter, Ralf; Nussbaum-Thom, Markus; Ney, Hermann

2012-02-01

In many tasks in pattern recognition, such as automatic speech recognition (ASR), optical character recognition (OCR), part-of-speech (POS) tagging, and other string recognition tasks, we are faced with a well-known inconsistency: The Bayes decision rule is usually used to minimize string (symbol sequence) error, whereas, in practice, we want to minimize symbol (word, character, tag, etc.) error. When comparing different recognition systems, we do indeed use symbol error rate as an evaluation measure. The topic of this work is to analyze the relation between string (i.e., 0-1) and symbol error (i.e., metric, integer valued) cost functions in the Bayes decision rule, for which fundamental analytic results are derived. Simple conditions are derived for which the Bayes decision rule with integer-valued metric cost function and with 0-1 cost gives the same decisions or leads to classes with limited cost. The corresponding conditions can be tested with complexity linear in the number of classes. The results obtained do not make any assumption w.r.t. the structure of the underlying distributions or the classification problem. Nevertheless, the general analytic results are analyzed via simulations of string recognition problems with Levenshtein (edit) distance cost function. The results support earlier findings that considerable improvements are to be expected when initial error rates are high.

The use of logistic regression to enhance risk assessment and decision making by mental health administrators.

PubMed

Menditto, Anthony A; Linhorst, Donald M; Coleman, James C; Beck, Niels C

2006-04-01

Development of policies and procedures to contend with the risks presented by elopement, aggression, and suicidal behaviors are long-standing challenges for mental health administrators. Guidance in making such judgments can be obtained through the use of a multivariate statistical technique known as logistic regression. This procedure can be used to develop a predictive equation that is mathematically formulated to use the best combination of predictors, rather than considering just one factor at a time. This paper presents an overview of logistic regression and its utility in mental health administrative decision making. A case example of its application is presented using data on elopements from Missouri's long-term state psychiatric hospitals. Ultimately, the use of statistical prediction analyses tempered with differential qualitative weighting of classification errors can augment decision-making processes in a manner that provides guidance and flexibility while wrestling with the complex problem of risk assessment and decision making.

Decision feedback loop for tracking a polyphase modulated carrier

NASA Technical Reports Server (NTRS)

Simon, M. K. (Inventor)

1974-01-01

A multiple phase modulated carrier tracking loop for use in a frequency shift keying system is described in which carrier tracking efficiency is improved by making use of the decision signals made on the data phase transmitted in each T-second interval. The decision signal is used to produce a pair of decision-feedback quadrature signals for enhancing the loop's performance in developing a loop phase error signal.

A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

NASA Astrophysics Data System (ADS)

Coyne, Kevin Anthony

The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional branching events and provide a better representation of the IDAC cognitive model. An operator decision-making engine capable of responding to dynamic changes in situational context was implemented. The IDAC human performance model was fully integrated with a detailed nuclear plant model in order to realistically simulate plant accident scenarios. Finally, the improved ADS-IDAC model was calibrated, validated, and updated using actual nuclear plant crew performance data. This research led to the following general conclusions: (1) A relatively small number of branching rules are capable of efficiently capturing a wide spectrum of crew-to-crew variabilities. (2) Compared to traditional static risk assessment methods, ADS-IDAC can provide a more realistic and integrated assessment of human error events by directly determining the effect of operator behaviors on plant thermal hydraulic parameters. (3) The ADS-IDAC approach provides an efficient framework for capturing actual operator performance data such as timing of operator actions, mental models, and decision-making activities.

Risk Aversion is Associated with Decision Making among Community-Based Older Persons

PubMed Central

Boyle, Patricia A.; Yu, Lei; Buchman, Aron S.; Bennett, David A.

2012-01-01

Background: Risk aversion is associated with many important decisions among younger and middle aged persons, but the association of risk aversion with decision making has not been well studied among older persons who face some of the most significant decisions of their lives. Method: Using data from 606 community-dwelling older persons without dementia from the Rush Memory and Aging Project, an ongoing longitudinal epidemiologic study of aging, we examined the association of risk aversion with decision making. Risk aversion was measured using standard behavioral economics questions in which participants were asked to choose between a certain monetary payment ($15) versus a gamble in which they could gain more than $15 or gain nothing; potential gamble gains ranged from $20 to $300 with the gain amounts varied randomly over questions. Decision making was measured using a 12 item version of the Decision Making Competence Assessment Tool. Findings: In a linear regression model adjusted for age, sex, education, and income, greater risk aversion was associated with poorer decision making [estimate = −1.03, standard error (SE) = 0.35, p = 0.003]. Subsequent analyses showed that the association of risk aversion with decision making persisted after adjustment for global cognitive function as well as executive and non-executive cognitive abilities. Conclusion: Similar to findings from studies of younger persons, risk aversion is associated with poorer decision making among older persons who face a myriad of complex and influential decisions. PMID:22754545

Risk Aversion is Associated with Decision Making among Community-Based Older Persons.

PubMed

Boyle, Patricia A; Yu, Lei; Buchman, Aron S; Bennett, David A

2012-01-01

Risk aversion is associated with many important decisions among younger and middle aged persons, but the association of risk aversion with decision making has not been well studied among older persons who face some of the most significant decisions of their lives. Using data from 606 community-dwelling older persons without dementia from the Rush Memory and Aging Project, an ongoing longitudinal epidemiologic study of aging, we examined the association of risk aversion with decision making. Risk aversion was measured using standard behavioral economics questions in which participants were asked to choose between a certain monetary payment ($15) versus a gamble in which they could gain more than $15 or gain nothing; potential gamble gains ranged from $20 to $300 with the gain amounts varied randomly over questions. Decision making was measured using a 12 item version of the Decision Making Competence Assessment Tool. In a linear regression model adjusted for age, sex, education, and income, greater risk aversion was associated with poorer decision making [estimate = -1.03, standard error (SE) = 0.35, p = 0.003]. Subsequent analyses showed that the association of risk aversion with decision making persisted after adjustment for global cognitive function as well as executive and non-executive cognitive abilities. Similar to findings from studies of younger persons, risk aversion is associated with poorer decision making among older persons who face a myriad of complex and influential decisions.

Understanding Decision Making in Critical Care

PubMed Central

Lighthall, Geoffrey K.; Vazquez-Guillamet, Cristina

2015-01-01

Background Human decision making involves the deliberate formulation of hypotheses and plans as well as the use of subconscious means of judging probability, likely outcome, and proper action. Rationale There is a growing recognition that intuitive strategies such as use of heuristics and pattern recognition described in other industries are applicable to high-acuity environments in medicine. Despite the applicability of theories of cognition to the intensive care unit, a discussion of decision-making strategies is currently absent in the critical care literature. Content This article provides an overview of known cognitive strategies, as well as a synthesis of their use in critical care. By understanding the ways by which humans formulate diagnoses and make critical decisions, we may be able to minimize errors in our own judgments as well as build training activities around known strengths and limitations of cognition. PMID:26387708

Judgment and decision making.

PubMed

Mellers, B A; Schwartz, A; Cooke, A D

1998-01-01

For many decades, research in judgment and decision making has examined behavioral violations of rational choice theory. In that framework, rationality is expressed as a single correct decision shared by experimenters and subjects that satisfies internal coherence within a set of preferences and beliefs. Outside of psychology, social scientists are now debating the need to modify rational choice theory with behavioral assumptions. Within psychology, researchers are debating assumptions about errors for many different definitions of rationality. Alternative frameworks are being proposed. These frameworks view decisions as more reasonable and adaptive that previously thought. For example, "rule following." Rule following, which occurs when a rule or norm is applied to a situation, often minimizes effort and provides satisfying solutions that are "good enough," though not necessarily the best. When rules are ambiguous, people look for reasons to guide their decisions. They may also let their emotions take charge. This chapter presents recent research on judgment and decision making from traditional and alternative frameworks.

Human Decision Making Based on Variations in Internal Noise: An EEG Study

PubMed Central

Amitay, Sygal; Guiraud, Jeanne; Sohoglu, Ediz; Zobay, Oliver; Edmonds, Barrie A.; Zhang, Yu-Xuan; Moore, David R.

2013-01-01

Perceptual decision making is prone to errors, especially near threshold. Physiological, behavioural and modeling studies suggest this is due to the intrinsic or ‘internal’ noise in neural systems, which derives from a mixture of bottom-up and top-down sources. We show here that internal noise can form the basis of perceptual decision making when the external signal lacks the required information for the decision. We recorded electroencephalographic (EEG) activity in listeners attempting to discriminate between identical tones. Since the acoustic signal was constant, bottom-up and top-down influences were under experimental control. We found that early cortical responses to the identical stimuli varied in global field power and topography according to the perceptual decision made, and activity preceding stimulus presentation could predict both later activity and behavioural decision. Our results suggest that activity variations induced by internal noise of both sensory and cognitive origin are sufficient to drive discrimination judgments. PMID:23840904

Avoiding and identifying errors in health technology assessment models: qualitative study and methodological review.

PubMed

Chilcott, J; Tappenden, P; Rawdin, A; Johnson, M; Kaltenthaler, E; Paisley, S; Papaioannou, D; Shippam, A

2010-05-01

Health policy decisions must be relevant, evidence-based and transparent. Decision-analytic modelling supports this process but its role is reliant on its credibility. Errors in mathematical decision models or simulation exercises are unavoidable but little attention has been paid to processes in model development. Numerous error avoidance/identification strategies could be adopted but it is difficult to evaluate the merits of strategies for improving the credibility of models without first developing an understanding of error types and causes. The study aims to describe the current comprehension of errors in the HTA modelling community and generate a taxonomy of model errors. Four primary objectives are to: (1) describe the current understanding of errors in HTA modelling; (2) understand current processes applied by the technology assessment community for avoiding errors in development, debugging and critically appraising models for errors; (3) use HTA modellers' perceptions of model errors with the wider non-HTA literature to develop a taxonomy of model errors; and (4) explore potential methods and procedures to reduce the occurrence of errors in models. It also describes the model development process as perceived by practitioners working within the HTA community. A methodological review was undertaken using an iterative search methodology. Exploratory searches informed the scope of interviews; later searches focused on issues arising from the interviews. Searches were undertaken in February 2008 and January 2009. In-depth qualitative interviews were performed with 12 HTA modellers from academic and commercial modelling sectors. All qualitative data were analysed using the Framework approach. Descriptive and explanatory accounts were used to interrogate the data within and across themes and subthemes: organisation, roles and communication; the model development process; definition of error; types of model error; strategies for avoiding errors; strategies for identifying errors; and barriers and facilitators. There was no common language in the discussion of modelling errors and there was inconsistency in the perceived boundaries of what constitutes an error. Asked about the definition of model error, there was a tendency for interviewees to exclude matters of judgement from being errors and focus on 'slips' and 'lapses', but discussion of slips and lapses comprised less than 20% of the discussion on types of errors. Interviewees devoted 70% of the discussion to softer elements of the process of defining the decision question and conceptual modelling, mostly the realms of judgement, skills, experience and training. The original focus concerned model errors, but it may be more useful to refer to modelling risks. Several interviewees discussed concepts of validation and verification, with notable consistency in interpretation: verification meaning the process of ensuring that the computer model correctly implemented the intended model, whereas validation means the process of ensuring that a model is fit for purpose. Methodological literature on verification and validation of models makes reference to the Hermeneutic philosophical position, highlighting that the concept of model validation should not be externalized from the decision-makers and the decision-making process. Interviewees demonstrated examples of all major error types identified in the literature: errors in the description of the decision problem, in model structure, in use of evidence, in implementation of the model, in operation of the model, and in presentation and understanding of results. The HTA error classifications were compared against existing classifications of model errors in the literature. A range of techniques and processes are currently used to avoid errors in HTA models: engaging with clinical experts, clients and decision-makers to ensure mutual understanding, producing written documentation of the proposed model, explicit conceptual modelling, stepping through skeleton models with experts, ensuring transparency in reporting, adopting standard housekeeping techniques, and ensuring that those parties involved in the model development process have sufficient and relevant training. Clarity and mutual understanding were identified as key issues. However, their current implementation is not framed within an overall strategy for structuring complex problems. Some of the questioning may have biased interviewees responses but as all interviewees were represented in the analysis no rebalancing of the report was deemed necessary. A potential weakness of the literature review was its focus on spreadsheet and program development rather than specifically on model development. It should also be noted that the identified literature concerning programming errors was very narrow despite broad searches being undertaken. Published definitions of overall model validity comprising conceptual model validation, verification of the computer model, and operational validity of the use of the model in addressing the real-world problem are consistent with the views expressed by the HTA community and are therefore recommended as the basis for further discussions of model credibility. Such discussions should focus on risks, including errors of implementation, errors in matters of judgement and violations. Discussions of modelling risks should reflect the potentially complex network of cognitive breakdowns that lead to errors in models and existing research on the cognitive basis of human error should be included in an examination of modelling errors. There is a need to develop a better understanding of the skills requirements for the development, operation and use of HTA models. Interaction between modeller and client in developing mutual understanding of a model establishes that model's significance and its warranty. This highlights that model credibility is the central concern of decision-makers using models so it is crucial that the concept of model validation should not be externalized from the decision-makers and the decision-making process. Recommendations for future research would be studies of verification and validation; the model development process; and identification of modifications to the modelling process with the aim of preventing the occurrence of errors and improving the identification of errors in models.

Multi-criteria decision making approaches for quality control of genome-wide association studies.

PubMed

Malovini, Alberto; Rognoni, Carla; Puca, Annibale; Bellazzi, Riccardo

2009-03-01

Experimental errors in the genotyping phases of a Genome-Wide Association Study (GWAS) can lead to false positive findings and to spurious associations. An appropriate quality control phase could minimize the effects of this kind of errors. Several filtering criteria can be used to perform quality control. Currently, no formal methods have been proposed for taking into account at the same time these criteria and the experimenter's preferences. In this paper we propose two strategies for setting appropriate genotyping rate thresholds for GWAS quality control. These two approaches are based on the Multi-Criteria Decision Making theory. We have applied our method on a real dataset composed by 734 individuals affected by Arterial Hypertension (AH) and 486 nonagenarians without history of AH. The proposed strategies appear to deal with GWAS quality control in a sound way, as they lead to rationalize and make explicit the experimenter's choices thus providing more reproducible results.

Case-based clinical reasoning in feline medicine: 2: Managing cognitive error.

PubMed

Canfield, Paul J; Whitehead, Martin L; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-03-01

This is Article 2 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. Article 1, published in the January 2016 issue of JFMS, discussed the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). This second article examines ways of managing cognitive error, particularly the negative impact of bias, when making a diagnosis. Article 3, to appear in the May 2016 issue, explores the use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Analyzing Decision Logs to Understand Decision Making in Serious Crime Investigations.

PubMed

Dando, Coral J; Ormerod, Thomas C

2017-12-01

Objective To study decision making by detectives when investigating serious crime through the examination of decision logs to explore hypothesis generation and evidence selection. Background Decision logs are used to record and justify decisions made during serious crime investigations. The complexity of investigative decision making is well documented, as are the errors associated with miscarriages of justice and inquests. The use of decision logs has not been the subject of an empirical investigation, yet they offer an important window into the nature of investigative decision making in dynamic, time-critical environments. Method A sample of decision logs from British police forces was analyzed qualitatively and quantitatively to explore hypothesis generation and evidence selection by police detectives. Results Analyses revealed diversity in documentation of decisions that did not correlate with case type and identified significant limitations of the decision log approach to supporting investigative decision making. Differences emerged between experienced and less experienced officers' decision log records in exploration of alternative hypotheses, generation of hypotheses, and sources of evidential inquiry opened over phase of investigation. Conclusion The practical use of decision logs is highly constrained by their format and context of use. Despite this, decision log records suggest that experienced detectives display strategic decision making to avoid confirmation and satisficing, which affect less experienced detectives. Application Potential applications of this research include both training in case documentation and the development of new decision log media that encourage detectives, irrespective of experience, to generate multiple hypotheses and optimize the timely selection of evidence to test them.

Error Ratio Analysis: Alternate Mathematics Assessment for General and Special Educators.

ERIC Educational Resources Information Center

Miller, James H.; Carr, Sonya C.

1997-01-01

Eighty-seven elementary students in grades four, five, and six, were administered a 30-item multiplication instrument to assess performance in computation across grade levels. An interpretation of student performance using error ratio analysis is provided and the use of this method with groups of students for instructional decision making is…

Effects of Crew Resource Management Training on Medical Errors in a Simulated Prehospital Setting

ERIC Educational Resources Information Center

Carhart, Elliot D.

2012-01-01

This applied dissertation investigated the effect of crew resource management (CRM) training on medical errors in a simulated prehospital setting. Specific areas addressed by this program included situational awareness, decision making, task management, teamwork, and communication. This study is believed to be the first investigation of CRM…

76 FR 20438 - Proposed Model Performance Measures for State Traffic Records Systems

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-12

... what data elements are critical. States should take advantage of these decision-making opportunities to... single database. Error means the recorded value for some data element of interest is incorrect. Error... into the database) and the number of missing (blank) data elements in the records that are in a...

Mitigating Errors of Representation: A Practical Case Study of the University Experience Survey

ERIC Educational Resources Information Center

Whiteley, Sonia

2014-01-01

The Total Survey Error (TSE) paradigm provides a framework that supports the effective planning of research, guides decision making about data collection and contextualises the interpretation and dissemination of findings. TSE also allows researchers to systematically evaluate and improve the design and execution of ongoing survey programs and…

Confidence Intervals for Weighted Composite Scores under the Compound Binomial Error Model

ERIC Educational Resources Information Center

Kim, Kyung Yong; Lee, Won-Chan

2018-01-01

Reporting confidence intervals with test scores helps test users make important decisions about examinees by providing information about the precision of test scores. Although a variety of estimation procedures based on the binomial error model are available for computing intervals for test scores, these procedures assume that items are randomly…

Cognitive reflection vs. calculation in decision making

PubMed Central

Sinayev, Aleksandr; Peters, Ellen

2015-01-01

Scores on the three-item Cognitive Reflection Test (CRT) have been linked with dual-system theory and normative decision making (Frederick, 2005). In particular, the CRT is thought to measure monitoring of System 1 intuitions such that, if cognitive reflection is high enough, intuitive errors will be detected and the problem will be solved. However, CRT items also require numeric ability to be answered correctly and it is unclear how much numeric ability vs. cognitive reflection contributes to better decision making. In two studies, CRT responses were used to calculate Cognitive Reflection and numeric ability; a numeracy scale was also administered. Numeric ability, measured on the CRT or the numeracy scale, accounted for the CRT's ability to predict more normative decisions (a subscale of decision-making competence, incentivized measures of impatient and risk-averse choice, and self-reported financial outcomes); Cognitive Reflection contributed no independent predictive power. Results were similar whether the two abilities were modeled (Study 1) or calculated using proportions (Studies 1 and 2). These findings demonstrate numeric ability as a robust predictor of superior decision making across multiple tasks and outcomes. They also indicate that correlations of decision performance with the CRT are insufficient evidence to implicate overriding intuitions in the decision-making biases and outcomes we examined. Numeric ability appears to be the key mechanism instead. PMID:25999877

Cognitive reflection vs. calculation in decision making.

PubMed

Sinayev, Aleksandr; Peters, Ellen

2015-01-01

Scores on the three-item Cognitive Reflection Test (CRT) have been linked with dual-system theory and normative decision making (Frederick, 2005). In particular, the CRT is thought to measure monitoring of System 1 intuitions such that, if cognitive reflection is high enough, intuitive errors will be detected and the problem will be solved. However, CRT items also require numeric ability to be answered correctly and it is unclear how much numeric ability vs. cognitive reflection contributes to better decision making. In two studies, CRT responses were used to calculate Cognitive Reflection and numeric ability; a numeracy scale was also administered. Numeric ability, measured on the CRT or the numeracy scale, accounted for the CRT's ability to predict more normative decisions (a subscale of decision-making competence, incentivized measures of impatient and risk-averse choice, and self-reported financial outcomes); Cognitive Reflection contributed no independent predictive power. Results were similar whether the two abilities were modeled (Study 1) or calculated using proportions (Studies 1 and 2). These findings demonstrate numeric ability as a robust predictor of superior decision making across multiple tasks and outcomes. They also indicate that correlations of decision performance with the CRT are insufficient evidence to implicate overriding intuitions in the decision-making biases and outcomes we examined. Numeric ability appears to be the key mechanism instead.

Executive function and decision-making in women with fibromyalgia.

PubMed

Verdejo-García, Antonio; López-Torrecillas, Francisca; Calandre, Elena Pita; Delgado-Rodríguez, Antonia; Bechara, Antoine

2009-02-01

Patients with fibromyalgia (FM) typically report cognitive problems, and they state that these deficits are disturbing in everyday life. Despite these substantial subjective complaints by FM patients, very few studies have addressed objectively the effect of such aversive states on neuropsychological performance. In this study we aimed to examine possible impairment of executive function and decision-making in a sample of 36 women diagnosed with FM and 36 healthy women matched in age, education, and socio-economic status. We contrasted performance of both groups on two measures of executive functioning: the Wisconsin Card Sorting Test (WCST), which assesses cognitive flexibility skills, and the Iowa Gambling Tasks (IGT; original and variant versions), which assess emotion-based decision-making. We also examined the relationship between executive function performance and pain experience, and between executive function and personality traits of novelty-seeking, harm avoidance, reward dependence, and persistence (measured by the Temperament and Character Inventory-Revised). Results showed that on the WCST, FM women showed poorer performance than healthy comparison women on the number of categories and non-perseverative errors, but not on perseverative errors. FM patients also showed altered learning curve in the original IGT (where reward is immediate and punishment is delayed), suggesting compromised emotion-based decision-making; but not in the variant IGT (where punishment is immediate but reward is delayed), suggesting hypersensitivity to reward. Personality variables were very mildly associated with cognitive performance in FM women.

Genetic Factors of Individual Differences in Decision Making in Economic Behavior: A Japanese Twin Study using the Allais Problem.

PubMed

Shikishima, Chizuru; Hiraishi, Kai; Yamagata, Shinji; Ando, Juko; Okada, Mitsuhiro

2015-01-01

Why does decision making differ among individuals? People sometimes make seemingly inconsistent decisions with lower expected (monetary) utility even when objective information of probabilities and reward are provided. It is noteworthy, however, that a certain proportion of people do not provide anomalous responses, choosing the alternatives with higher expected utility, thus appearing to be more "rational." We investigated the genetic and environmental influences on these types of individual differences in decision making using a classical Allais problem task. Participants were 1,199 Japanese adult twins aged 20-47. Univariate genetic analysis revealed that approximately a third of the Allais problem response variance was explained by genetic factors and the rest by environmental factors unique to individuals and measurement error. The environmental factor shared between families did not contribute to the variance. Subsequent multivariate genetic analysis clarified that decision making using the expected utility theory was associated with general intelligence and that the association was largely mediated by the same genetic factor. We approach the mechanism underlying two types of "rational" decision making from the perspective of genetic correlations with cognitive abilities.

Effects of different feedback types on information integration in repeated monetary gambles

PubMed Central

Haffke, Peter; Hübner, Ronald

2015-01-01

Most models of risky decision making assume that all relevant information is taken into account (e.g., von Neumann and Morgenstern, 1944; Kahneman and Tversky, 1979). However, there are also some models supposing that only part of the information is considered (e.g., Brandstätter et al., 2006; Gigerenzer and Gaissmaier, 2011). To further investigate the amount of information that is usually used for decision making, and how the use depends on feedback, we conducted a series of three experiments in which participants choose between two lotteries and where no feedback, outcome feedback, and error feedback was provided, respectively. The results show that without feedback participants mostly chose the lottery with the higher winning probability, and largely ignored the potential gains. The same results occurred when the outcome of each decision was fed back. Only after presenting error feedback (i.e., signaling whether a choice was optimal or not), participants considered probabilities as well as gains, resulting in more optimal choices. We propose that outcome feedback was ineffective, because of its probabilistic and ambiguous nature. Participants improve information integration only if provided with a consistent and deterministic signal such as error feedback. PMID:25667576

Effects of different feedback types on information integration in repeated monetary gambles.

PubMed

Haffke, Peter; Hübner, Ronald

2014-01-01

Most models of risky decision making assume that all relevant information is taken into account (e.g., von Neumann and Morgenstern, 1944; Kahneman and Tversky, 1979). However, there are also some models supposing that only part of the information is considered (e.g., Brandstätter et al., 2006; Gigerenzer and Gaissmaier, 2011). To further investigate the amount of information that is usually used for decision making, and how the use depends on feedback, we conducted a series of three experiments in which participants choose between two lotteries and where no feedback, outcome feedback, and error feedback was provided, respectively. The results show that without feedback participants mostly chose the lottery with the higher winning probability, and largely ignored the potential gains. The same results occurred when the outcome of each decision was fed back. Only after presenting error feedback (i.e., signaling whether a choice was optimal or not), participants considered probabilities as well as gains, resulting in more optimal choices. We propose that outcome feedback was ineffective, because of its probabilistic and ambiguous nature. Participants improve information integration only if provided with a consistent and deterministic signal such as error feedback.

Automated Decision-Making and Big Data: Concerns for People With Mental Illness.

PubMed

Monteith, Scott; Glenn, Tasha

2016-12-01

Automated decision-making by computer algorithms based on data from our behaviors is fundamental to the digital economy. Automated decisions impact everyone, occurring routinely in education, employment, health care, credit, and government services. Technologies that generate tracking data, including smartphones, credit cards, websites, social media, and sensors, offer unprecedented benefits. However, people are vulnerable to errors and biases in the underlying data and algorithms, especially those with mental illness. Algorithms based on big data from seemingly unrelated sources may create obstacles to community integration. Voluntary online self-disclosure and constant tracking blur traditional concepts of public versus private data, medical versus non-medical data, and human versus automated decision-making. In contrast to sharing sensitive information with a physician in a confidential relationship, there may be numerous readers of information revealed online; data may be sold repeatedly; used in proprietary algorithms; and are effectively permanent. Technological changes challenge traditional norms affecting privacy and decision-making, and continued discussions on new approaches to provide privacy protections are needed.

Neural evidence for description dependent reward processing in the framing effect.

PubMed

Yu, Rongjun; Zhang, Ping

2014-01-01

Human decision making can be influenced by emotionally valenced contexts, known as the framing effect. We used event-related brain potentials to investigate how framing influences the encoding of reward. We found that the feedback related negativity (FRN), which indexes the "worse than expected" negative prediction error in the anterior cingulate cortex (ACC), was more negative for the negative frame than for the positive frame in the win domain. Consistent with previous findings that the FRN is not sensitive to "better than expected" positive prediction error, the FRN did not differentiate the positive and negative frame in the loss domain. Our results provide neural evidence that the description invariance principle which states that reward representation and decision making are not influenced by how options are presented is violated in the framing effect.

Improving patient care. The cognitive psychology of missed diagnoses.

PubMed

Redelmeier, Donald A

2005-01-18

Cognitive psychology is the science that examines how people reason, formulate judgments, and make decisions. This case involves a patient given a diagnosis of pharyngitis, whose ultimate diagnosis of osteomyelitis was missed through a series of cognitive shortcuts. These errors include the availability heuristic (in which people judge likelihood by how easily examples spring to mind), the anchoring heuristic (in which people stick with initial impressions), framing effects (in which people make different decisions depending on how information is presented), blind obedience (in which people stop thinking when confronted with authority), and premature closure (in which several alternatives are not pursued). Rather than trying to completely eliminate cognitive shortcuts (which often serve clinicians well), becoming aware of common errors might lead to sustained improvement in patient care.

Sequential Probability Ratio Testing with Power Projective Base Method Improves Decision-Making for BCI

PubMed Central

Liu, Rong

2017-01-01

Obtaining a fast and reliable decision is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this study, the EEG signals were firstly analyzed with a power projective base method. Then we were applied a decision-making model, the sequential probability ratio testing (SPRT), for single-trial classification of motor imagery movement events. The unique strength of this proposed classification method lies in its accumulative process, which increases the discriminative power as more and more evidence is observed over time. The properties of the method were illustrated on thirteen subjects' recordings from three datasets. Results showed that our proposed power projective method outperformed two benchmark methods for every subject. Moreover, with sequential classifier, the accuracies across subjects were significantly higher than that with nonsequential ones. The average maximum accuracy of the SPRT method was 84.1%, as compared with 82.3% accuracy for the sequential Bayesian (SB) method. The proposed SPRT method provides an explicit relationship between stopping time, thresholds, and error, which is important for balancing the time-accuracy trade-off. These results suggest SPRT would be useful in speeding up decision-making while trading off errors in BCI. PMID:29348781

Diagnosing Crime and Diagnosing Disease: Bias Reduction Strategies in the Forensic and Clinical Sciences.

PubMed

Lockhart, Joseph J; Satya-Murti, Saty

2017-11-01

Cognitive effort is an essential part of both forensic and clinical decision-making. Errors occur in both fields because the cognitive process is complex and prone to bias. We performed a selective review of full-text English language literature on cognitive bias leading to diagnostic and forensic errors. Earlier work (1970-2000) concentrated on classifying and raising bias awareness. Recently (2000-2016), the emphasis has shifted toward strategies for "debiasing." While the forensic sciences have focused on the control of misleading contextual cues, clinical debiasing efforts have relied on checklists and hypothetical scenarios. No single generally applicable and effective bias reduction strategy has emerged so far. Generalized attempts at bias elimination have not been particularly successful. It is time to shift focus to the study of errors within specific domains, and how to best communicate uncertainty in order to improve decision making on the part of both the expert and the trier-of-fact. © 2017 American Academy of Forensic Sciences.

Determination of the anaerobic threshold in the pre-operative assessment clinic: inter-observer measurement error.

PubMed

Sinclair, R C F; Danjoux, G R; Goodridge, V; Batterham, A M

2009-11-01

The variability between observers in the interpretation of cardiopulmonary exercise tests may impact upon clinical decision making and affect the risk stratification and peri-operative management of a patient. The purpose of this study was to quantify the inter-reader variability in the determination of the anaerobic threshold (V-slope method). A series of 21 cardiopulmonary exercise tests from patients attending a surgical pre-operative assessment clinic were read independently by nine experienced clinicians regularly involved in clinical decision making. The grand mean for the anaerobic threshold was 10.5 ml O(2).kg body mass(-1).min(-1). The technical error of measurement was 8.1% (circa 0.9 ml.kg(-1).min(-1); 90% confidence interval, 7.4-8.9%). The mean absolute difference between readers was 4.5% with a typical random error of 6.5% (6.0-7.2%). We conclude that the inter-observer variability for experienced clinicians determining the anaerobic threshold from cardiopulmonary exercise tests is acceptable.

EEG Classification with a Sequential Decision-Making Method in Motor Imagery BCI.

PubMed

Liu, Rong; Wang, Yongxuan; Newman, Geoffrey I; Thakor, Nitish V; Ying, Sarah

2017-12-01

To develop subject-specific classifier to recognize mental states fast and reliably is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this paper, a sequential decision-making strategy is explored in conjunction with an optimal wavelet analysis for EEG classification. The subject-specific wavelet parameters based on a grid-search method were first developed to determine evidence accumulative curve for the sequential classifier. Then we proposed a new method to set the two constrained thresholds in the sequential probability ratio test (SPRT) based on the cumulative curve and a desired expected stopping time. As a result, it balanced the decision time of each class, and we term it balanced threshold SPRT (BTSPRT). The properties of the method were illustrated on 14 subjects' recordings from offline and online tests. Results showed the average maximum accuracy of the proposed method to be 83.4% and the average decision time of 2.77[Formula: see text]s, when compared with 79.2% accuracy and a decision time of 3.01[Formula: see text]s for the sequential Bayesian (SB) method. The BTSPRT method not only improves the classification accuracy and decision speed comparing with the other nonsequential or SB methods, but also provides an explicit relationship between stopping time, thresholds and error, which is important for balancing the speed-accuracy tradeoff. These results suggest that BTSPRT would be useful in explicitly adjusting the tradeoff between rapid decision-making and error-free device control.

Pediatric residents' decision-making around disclosing and reporting adverse events: the importance of social context.

PubMed

Coffey, Maitreya; Thomson, Kelly; Tallett, Susan; Matlow, Anne

2010-10-01

Although experts advise disclosing medical errors to patients, individual physicians' different levels of knowledge and comfort suggest a gap between recommendations and practice. This study explored pediatric residents' knowledge and attitudes about disclosure. In 2006, the authors of this single-center, mixed-methods study surveyed 64 pediatric residents at the University of Toronto and then held three focus groups with a total of 24 of those residents. Thirty-seven (58%) residents completed questionnaires. Most agreed that medical errors are one of the most serious problems in health care, that errors should be disclosed, and that disclosure would be difficult. When shown a scenario involving a medical error, over 90% correctly identified the error, but only 40% would definitely disclose it. Most would apologize, but far fewer would acknowledge harm if it occurred or use the word "mistake." Most had witnessed or performed a disclosure, but only 40% reported receiving teaching on disclosure. Most reported experiencing negative effects of errors, including anxiety and reduced confidence. Data from the focus groups emphasized the extent to which residents consider contextual information when making decisions around disclosure. Themes included their or their team's degree of responsibility for the error versus others, quality of team relationships, training level, existence of social boundaries, and their position within a hierarchy. These findings add to the understanding of facilitators and inhibitors of error disclosure and reporting. The influence of social context warrants further study and should be considered in medical curriculum design and hospital guideline implementation.

Nicotine and varenicline ameliorate changes in reward-based choice strategy and altered decision-making in methamphetamine-treated rats.

PubMed

Mizoguchi, Hiroyuki; Wang, Tian; Kusaba, Mizuki; Fukumoto, Kazuya; Yamada, Kiyofumi

2018-06-20

Patients suffering from neuropsychiatric disorders such as substance use and addiction disorders show impaired decision-making, which may be associated with their psychiatric disorders. Previously, using a gambling test for rodents, we demonstrated that methamphetamine-dependent rats showed alterations in their decision-making strategy. In this study, we investigated the effect of nicotine on impaired decision-making strategy in rats which have been treated repeatedly with methamphetamine. Nicotine has previously been shown to have therapeutic effects on attentional and cognitive abnormalities in psychosis. Rats were administered methamphetamine subcutaneously (sc) at 4 mg/kg once a day, for 30 days, and their decision-making was then assessed with a rodent gambling task. We found that methamphetamine-treated rats preferred the high-risk/high-return actions, which is consistent with our previous findings. Methamphetamine-induced impairment of decision-making was reversed by daily nicotine treatment (0.3 mg/kg, sc). This effect was associated with the reduction of lose-shift behavior after negative reward prediction error. Repeated treatment with nicotine had no effects on arm-choice behavior in naïve rats. Varenicline, an α4β2-nicotinic acetylcholine receptor partial agonist, also ameliorated the altered decision-making in methamphetamine-treated rats. Our findings suggest that nicotine treatment is useful for ameliorating the altered decision-making caused by methamphetamine treatment, and that the α4β2-nicotinic acetylcholine receptor is a therapeutic target for poor decision-making. Copyright © 2018. Published by Elsevier B.V.

Development and preliminary user testing of the DCIDA (Dynamic computer interactive decision application) for ‘nudging’ patients towards high quality decisions

PubMed Central

2014-01-01

Background Patient decision aids (PtDA) are developed to facilitate informed, value-based decisions about health. Research suggests that even when informed with necessary evidence and information, cognitive errors can prevent patients from choosing the option that is most congruent with their own values. We sought to utilize principles of behavioural economics to develop a computer application that presents information from conventional decision aids in a way that reduces these errors, subsequently promoting higher quality decisions. Method The Dynamic Computer Interactive Decision Application (DCIDA) was developed to target four common errors that can impede quality decision making with PtDAs: unstable values, order effects, overweighting of rare events, and information overload. Healthy volunteers were recruited to an interview to use three PtDAs converted to the DCIDA on a computer equipped with an eye tracker. Participants were first used a conventional PtDA, and then subsequently used the DCIDA version. User testing was assessed based on whether respondents found the software both usable: evaluated using a) eye-tracking, b) the system usability scale, and c) user verbal responses from a ‘think aloud’ protocol; and useful: evaluated using a) eye-tracking, b) whether preferences for options were changed, and c) and the decisional conflict scale. Results Of the 20 participants recruited to the study, 11 were male (55%), the mean age was 35, 18 had at least a high school education (90%), and 8 (40%) had a college or university degree. Eye-tracking results, alongside a mean system usability scale score of 73 (range 68–85), indicated a reasonable degree of usability for the DCIDA. The think aloud study suggested areas for further improvement. The DCIDA also appeared to be useful to participants wherein subjects focused more on the features of the decision that were most important to them (21% increase in time spent focusing on the most important feature). Seven subjects (25%) changed their preferred option when using DCIDA. Conclusion Preliminary results suggest that DCIDA has potential to improve the quality of patient decision-making. Next steps include larger studies to test individual components of DCIDA and feasibility testing with patients making real decisions. PMID:25084808

The impact of human-technology cooperation and distributed cognition in forensic science: biasing effects of AFIS contextual information on human experts.

PubMed

Dror, Itiel E; Wertheim, Kasey; Fraser-Mackenzie, Peter; Walajtys, Jeff

2012-03-01

Experts play a critical role in forensic decision making, even when cognition is offloaded and distributed between human and machine. In this paper, we investigated the impact of using Automated Fingerprint Identification Systems (AFIS) on human decision makers. We provided 3680 AFIS lists (a total of 55,200 comparisons) to 23 latent fingerprint examiners as part of their normal casework. We manipulated the position of the matching print in the AFIS list. The data showed that latent fingerprint examiners were affected by the position of the matching print in terms of false exclusions and false inconclusives. Furthermore, the data showed that false identification errors were more likely at the top of the list and that such errors occurred even when the correct match was present further down the list. These effects need to be studied and considered carefully, so as to optimize human decision making when using technologies such as AFIS. © 2011 American Academy of Forensic Sciences.

Measuring coverage in MNCH: total survey error and the interpretation of intervention coverage estimates from household surveys.

PubMed

Eisele, Thomas P; Rhoda, Dale A; Cutts, Felicity T; Keating, Joseph; Ren, Ruilin; Barros, Aluisio J D; Arnold, Fred

2013-01-01

Nationally representative household surveys are increasingly relied upon to measure maternal, newborn, and child health (MNCH) intervention coverage at the population level in low- and middle-income countries. Surveys are the best tool we have for this purpose and are central to national and global decision making. However, all survey point estimates have a certain level of error (total survey error) comprising sampling and non-sampling error, both of which must be considered when interpreting survey results for decision making. In this review, we discuss the importance of considering these errors when interpreting MNCH intervention coverage estimates derived from household surveys, using relevant examples from national surveys to provide context. Sampling error is usually thought of as the precision of a point estimate and is represented by 95% confidence intervals, which are measurable. Confidence intervals can inform judgments about whether estimated parameters are likely to be different from the real value of a parameter. We recommend, therefore, that confidence intervals for key coverage indicators should always be provided in survey reports. By contrast, the direction and magnitude of non-sampling error is almost always unmeasurable, and therefore unknown. Information error and bias are the most common sources of non-sampling error in household survey estimates and we recommend that they should always be carefully considered when interpreting MNCH intervention coverage based on survey data. Overall, we recommend that future research on measuring MNCH intervention coverage should focus on refining and improving survey-based coverage estimates to develop a better understanding of how results should be interpreted and used.

Measuring Coverage in MNCH: Total Survey Error and the Interpretation of Intervention Coverage Estimates from Household Surveys

PubMed Central

Eisele, Thomas P.; Rhoda, Dale A.; Cutts, Felicity T.; Keating, Joseph; Ren, Ruilin; Barros, Aluisio J. D.; Arnold, Fred

2013-01-01

Nationally representative household surveys are increasingly relied upon to measure maternal, newborn, and child health (MNCH) intervention coverage at the population level in low- and middle-income countries. Surveys are the best tool we have for this purpose and are central to national and global decision making. However, all survey point estimates have a certain level of error (total survey error) comprising sampling and non-sampling error, both of which must be considered when interpreting survey results for decision making. In this review, we discuss the importance of considering these errors when interpreting MNCH intervention coverage estimates derived from household surveys, using relevant examples from national surveys to provide context. Sampling error is usually thought of as the precision of a point estimate and is represented by 95% confidence intervals, which are measurable. Confidence intervals can inform judgments about whether estimated parameters are likely to be different from the real value of a parameter. We recommend, therefore, that confidence intervals for key coverage indicators should always be provided in survey reports. By contrast, the direction and magnitude of non-sampling error is almost always unmeasurable, and therefore unknown. Information error and bias are the most common sources of non-sampling error in household survey estimates and we recommend that they should always be carefully considered when interpreting MNCH intervention coverage based on survey data. Overall, we recommend that future research on measuring MNCH intervention coverage should focus on refining and improving survey-based coverage estimates to develop a better understanding of how results should be interpreted and used. PMID:23667331

First-degree relatives of suicide completers may have impaired decision-making but functional cognitive control.

PubMed

Hoehne, A; Richard-Devantoy, S; Ding, Y; Turecki, G; Jollant, F

2015-09-01

The heritability of suicide is well established. Transmission of risk appears to follow traits more than disorders like depression. In the present project, we aimed at investigating the potential for transmission of cognitive deficits previously observed in suicide attempters, specifically impaired decision-making and cognitive control. Seventeen healthy first-degree relatives of suicide completers with no personal history of suicidal act were compared to 18 first-degree relatives of individuals with major depressive disorder but no family history of suicidal act, and 19 healthy controls. Decision-making was assessed with the Iowa Gambling Task, and cognitive control with the Stroop Task, the Hayling Sentence Completion Test, and the Trail-Making Test. Both suicide and depressed relatives showed lower gambling task net scores than healthy controls. However, there were trends toward lower learning abilities in suicide than depressed relatives (interaction: p = 0.07), with more risky choices at the end of the test. Suicide relatives also showed a higher number of self-corrected errors relative to the total number of errors in the Stroop colour test compared to both control groups, with no difference in interference scores. There was no group-difference for any other cognitive tests. Our findings suggest that decision-making impairment may be found in healthy relatives of suicides and represent a cognitive endophenotype of suicidal behaviour. Normal cognitive control (or self-corrected deficits) may protect relatives against suicidal acts. Impairments in value-based and control processes may, therefore, be part of the suicide vulnerability and represent potential targets of preventative interventions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Trial Maneuver Generation and Selection in the Paladin Tactical Decision Generation System

NASA Technical Reports Server (NTRS)

Chappell, Alan R.; McManus, John W.; Goodrich, Kenneth H.

1992-01-01

To date, increased levels of maneuverability and controllability in aircraft have been postulated as tactically advantageous, but little research has studied maneuvers or tactics that make use of these capabilities. In order to help fill this void, a real time tactical decision generation system for air combat engagements, Paladin, has been developed. Paladin models an air combat engagement as a series of discrete decisions. A detailed description of Paladin's decision making process is presented. This includes the sources of data used, methods of generating reasonable maneuvers for the Paladin aircraft, and selection criteria for choosing the "best" maneuver. Simulation results are presented that show Paladin to be relatively insensitive to errors introduced into the decision process by estimation of future positional and geometric data.

Trial maneuver generation and selection in the Paladin tactical decision generation system

NASA Technical Reports Server (NTRS)

Chappell, Alan R.; Mcmanus, John W.; Goodrich, Kenneth H.

1993-01-01

To date, increased levels of maneuverability and controllability in aircraft have been postulated as tactically advantageous, but little research has studied maneuvers or tactics that make use of these capabilities. In order to help fill this void, a real-time tactical decision generation system for air combat engagements, Paladin, has been developed. Paladin models an air combat engagement as a series of discrete decisions. A detailed description of Paladin's decision making process is presented. This includes the sources of data used, methods of generating reasonable maneuvers for the Paladin aircraft, and selection criteria for choosing the 'best' maneuver. Simulation results are presented that show Paladin to be relatively insensitive to errors introduced into the decision process by estimation of future positional and geometric data.

Informed use of patients' records on trusted health care services.

PubMed

Sahama, Tony; Miller, Evonne

2011-01-01

Health care is an information-intensive business. Sharing information in health care processes is a smart use of data enabling informed decision-making whilst ensuring. the privacy and security of patient information. To achieve this, we propose data encryption techniques embedded Information Accountability Framework (IAF) that establishes transitions of the technological concept, thus enabling understanding of shared responsibility, accessibility, and efficient cost effective informed decisions between health care professionals and patients. The IAF results reveal possibilities of efficient informed medical decision making and minimisation of medical errors. Of achieving this will require significant cultural changes and research synergies to ensure the sustainability, acceptability and durability of the IAF.

Neural evidence for description dependent reward processing in the framing effect

PubMed Central

Yu, Rongjun; Zhang, Ping

2014-01-01

Human decision making can be influenced by emotionally valenced contexts, known as the framing effect. We used event-related brain potentials to investigate how framing influences the encoding of reward. We found that the feedback related negativity (FRN), which indexes the “worse than expected” negative prediction error in the anterior cingulate cortex (ACC), was more negative for the negative frame than for the positive frame in the win domain. Consistent with previous findings that the FRN is not sensitive to “better than expected” positive prediction error, the FRN did not differentiate the positive and negative frame in the loss domain. Our results provide neural evidence that the description invariance principle which states that reward representation and decision making are not influenced by how options are presented is violated in the framing effect. PMID:24733998

Visual anticipation biases conscious decision making but not bottom-up visual processing.

PubMed

Mathews, Zenon; Cetnarski, Ryszard; Verschure, Paul F M J

2014-01-01

Prediction plays a key role in control of attention but it is not clear which aspects of prediction are most prominent in conscious experience. An evolving view on the brain is that it can be seen as a prediction machine that optimizes its ability to predict states of the world and the self through the top-down propagation of predictions and the bottom-up presentation of prediction errors. There are competing views though on whether prediction or prediction errors dominate the formation of conscious experience. Yet, the dynamic effects of prediction on perception, decision making and consciousness have been difficult to assess and to model. We propose a novel mathematical framework and a psychophysical paradigm that allows us to assess both the hierarchical structuring of perceptual consciousness, its content and the impact of predictions and/or errors on conscious experience, attention and decision-making. Using a displacement detection task combined with reverse correlation, we reveal signatures of the usage of prediction at three different levels of perceptual processing: bottom-up fast saccades, top-down driven slow saccades and consciousnes decisions. Our results suggest that the brain employs multiple parallel mechanism at different levels of perceptual processing in order to shape effective sensory consciousness within a predicted perceptual scene. We further observe that bottom-up sensory and top-down predictive processes can be dissociated through cognitive load. We propose a probabilistic data association model from dynamical systems theory to model the predictive multi-scale bias in perceptual processing that we observe and its role in the formation of conscious experience. We propose that these results support the hypothesis that consciousness provides a time-delayed description of a task that is used to prospectively optimize real time control structures, rather than being engaged in the real-time control of behavior itself.

Multi-Criteria Decision Making Approaches for Quality Control of Genome-Wide Association Studies

PubMed Central

Malovini, Alberto; Rognoni, Carla; Puca, Annibale; Bellazzi, Riccardo

2009-01-01

Experimental errors in the genotyping phases of a Genome-Wide Association Study (GWAS) can lead to false positive findings and to spurious associations. An appropriate quality control phase could minimize the effects of this kind of errors. Several filtering criteria can be used to perform quality control. Currently, no formal methods have been proposed for taking into account at the same time these criteria and the experimenter’s preferences. In this paper we propose two strategies for setting appropriate genotyping rate thresholds for GWAS quality control. These two approaches are based on the Multi-Criteria Decision Making theory. We have applied our method on a real dataset composed by 734 individuals affected by Arterial Hypertension (AH) and 486 nonagenarians without history of AH. The proposed strategies appear to deal with GWAS quality control in a sound way, as they lead to rationalize and make explicit the experimenter’s choices thus providing more reproducible results. PMID:21347174

A regret-induced status-quo bias

PubMed Central

Nicolle, A.; Fleming, S.M.; Bach, D.R.; Driver, J.; Dolan, R. J.

2011-01-01

A suboptimal bias towards accepting the ‘status-quo’ option in decision-making is well established behaviorally, but the underlying neural mechanisms are less clear. Behavioral evidence suggests the emotion of regret is higher when errors arise from rejection rather than acceptance of a status-quo option. Such asymmetry in the genesis of regret might drive the status-quo bias on subsequent decisions, if indeed erroneous status-quo rejections have a greater neuronal impact than erroneous status-quo acceptances. To test this, we acquired human fMRI data during a difficult perceptual decision task that incorporated a trial-to-trial intrinsic status-quo option, with explicit signaling of outcomes (error or correct). Behaviorally, experienced regret was higher after an erroneous status-quo rejection compared to acceptance. Anterior insula and medial prefrontal cortex showed increased BOLD signal after such status-quo rejection errors. In line with our hypothesis, a similar pattern of signal change predicted acceptance of the status-quo on a subsequent trial. Thus, our data link a regret-induced status-quo bias to error-related activity on the preceding trial. PMID:21368043

Masked Visual Analysis: Minimizing Type I Error in Visually Guided Single-Case Design for Communication Disorders

PubMed Central

Hitchcock, Elaine R.; Ferron, John

2017-01-01

Purpose Single-case experimental designs are widely used to study interventions for communication disorders. Traditionally, single-case experiments follow a response-guided approach, where design decisions during the study are based on participants' observed patterns of behavior. However, this approach has been criticized for its high rate of Type I error. In masked visual analysis (MVA), response-guided decisions are made by a researcher who is blinded to participants' identities and treatment assignments. MVA also makes it possible to conduct a hypothesis test assessing the significance of treatment effects. Method This tutorial describes the principles of MVA, including both how experiments can be set up and how results can be used for hypothesis testing. We then report a case study showing how MVA was deployed in a multiple-baseline across-subjects study investigating treatment for residual errors affecting rhotics. Strengths and weaknesses of MVA are discussed. Conclusions Given their important role in the evidence base that informs clinical decision making, it is critical for single-case experimental studies to be conducted in a way that allows researchers to draw valid inferences. As a method that can increase the rigor of single-case studies while preserving the benefits of a response-guided approach, MVA warrants expanded attention from researchers in communication disorders. PMID:28595354

Masked Visual Analysis: Minimizing Type I Error in Visually Guided Single-Case Design for Communication Disorders.

PubMed

Byun, Tara McAllister; Hitchcock, Elaine R; Ferron, John

2017-06-10

Single-case experimental designs are widely used to study interventions for communication disorders. Traditionally, single-case experiments follow a response-guided approach, where design decisions during the study are based on participants' observed patterns of behavior. However, this approach has been criticized for its high rate of Type I error. In masked visual analysis (MVA), response-guided decisions are made by a researcher who is blinded to participants' identities and treatment assignments. MVA also makes it possible to conduct a hypothesis test assessing the significance of treatment effects. This tutorial describes the principles of MVA, including both how experiments can be set up and how results can be used for hypothesis testing. We then report a case study showing how MVA was deployed in a multiple-baseline across-subjects study investigating treatment for residual errors affecting rhotics. Strengths and weaknesses of MVA are discussed. Given their important role in the evidence base that informs clinical decision making, it is critical for single-case experimental studies to be conducted in a way that allows researchers to draw valid inferences. As a method that can increase the rigor of single-case studies while preserving the benefits of a response-guided approach, MVA warrants expanded attention from researchers in communication disorders.

Reduction in chemotherapy order errors with computerised physician order entry and clinical decision support systems.

PubMed

Aziz, Muhammad Tahir; Ur-Rehman, Tofeeq; Qureshi, Sadia; Bukhari, Nadeem Irfan

Medication errors in chemotherapy are frequent and lead to patient morbidity and mortality, as well as increased rates of re-admission and length of stay, and considerable extra costs. Objective: This study investigated the proposition that computerised chemotherapy ordering reduces the incidence and severity of chemotherapy protocol errors. A computerised physician order entry of chemotherapy order (C-CO) with clinical decision support system was developed in-house, including standardised chemotherapy protocol definitions, automation of pharmacy distribution, clinical checks, labeling and invoicing. A prospective study was then conducted in a C-CO versus paper based chemotherapy order (P-CO) in a 30-bed chemotherapy bay of a tertiary hospital. Both C-CO and P-CO orders, including pharmacoeconomic analysis and the severity of medication errors, were checked and validated by a clinical pharmacist. A group analysis and field trial were also conducted to assess clarity, feasibility and decision making. The C-CO was very usable in terms of its clarity and feasibility. The incidence of medication errors was significantly lower in the C-CO compared with the P-CO (10/3765 [0.26%] versus 134/5514 [2.4%]). There was also a reduction in dispensing time of chemotherapy protocols in the C-CO. The chemotherapy computerisation with clinical decision support system resulted in a significant decrease in the occurrence and severity of medication errors, improvements in chemotherapy dispensing and administration times, and reduction of chemotherapy cost.

Clinical cognition and diagnostic error: applications of a dual process model of reasoning.

PubMed

Croskerry, Pat

2009-09-01

Both systemic and individual factors contribute to missed or delayed diagnoses. Among the multiple factors that impact clinical performance of the individual, the caliber of cognition is perhaps the most relevant and deserves our attention and understanding. In the last few decades, cognitive psychologists have gained substantial insights into the processes that underlie cognition, and a new, universal model of reasoning and decision making has emerged, Dual Process Theory. The theory has immediate application to medical decision making and provides an overall schema for understanding the variety of theoretical approaches that have been taken in the past. The model has important practical applications for decision making across the multiple domains of healthcare, and may be used as a template for teaching decision theory, as well as a platform for future research. Importantly, specific operating characteristics of the model explain how diagnostic failure occurs.

Ethics in the Pediatric Emergency Department: When Mistakes Happen: An Approach to the Process, Evaluation, and Response to Medical Errors.

PubMed

Dreisinger, Naomi; Zapolsky, Nathan

2017-02-01

The emergency department (ED) is an environment that is conducive to medical errors. The ED is a time-pressured environment where physicians aim to rapidly evaluate and treat patients. Quick thinking and problem-based solutions are often used to assist in evaluation and diagnosis. Error analysis leads to an understanding of the cause of a medical error and is important to prevent future errors. Research suggests mechanisms to prevent medical errors in the pediatric ED, but prevention is not always possible. Transparency about errors is necessary to assure a trusting doctor-patient relationship. Patients want to be informed about all errors, and apologies are hard. Apologizing for a significant medical error that may have caused a complication is even harder. Having a systematic way to go about apologizing makes the process easier, and helps assure that the right information is relayed to the patient and his or her family. This creates an environment of autonomy and shared decision making that is ultimately beneficial to all aspects of patient care.

Is the relationship between pattern recall and decision-making influenced by anticipatory recall?

PubMed

Gorman, Adam D; Abernethy, Bruce; Farrow, Damian

2013-01-01

The present study compared traditional measures of pattern recall to measures of anticipatory recall and decision-making to examine the underlying mechanisms of expert pattern perception and to address methodological limitations in previous studies where anticipatory recall has generally been overlooked. Recall performance in expert and novice basketball players was measured by examining the spatial error in recalling player positions both for a target image (traditional recall) and at 40-ms increments following the target image (anticipatory recall). Decision-making performance was measured by comparing the participant's response to those identified by a panel of expert coaches. Anticipatory recall was observed in the recall task and was significantly more pronounced for the experts, suggesting that traditional methods of spatial recall analysis may not have provided a completely accurate determination of the full magnitude of the experts' superiority. Accounting for anticipatory recall also increased the relative contribution of recall skill to decision-making accuracy although the gains in explained variance were modest and of debatable functional significance.

Artificial neural networks in mammography interpretation and diagnostic decision making.

PubMed

Ayer, Turgay; Chen, Qiushi; Burnside, Elizabeth S

2013-01-01

Screening mammography is the most effective means for early detection of breast cancer. Although general rules for discriminating malignant and benign lesions exist, radiologists are unable to perfectly detect and classify all lesions as malignant and benign, for many reasons which include, but are not limited to, overlap of features that distinguish malignancy, difficulty in estimating disease risk, and variability in recommended management. When predictive variables are numerous and interact, ad hoc decision making strategies based on experience and memory may lead to systematic errors and variability in practice. The integration of computer models to help radiologists increase the accuracy of mammography examinations in diagnostic decision making has gained increasing attention in the last two decades. In this study, we provide an overview of one of the most commonly used models, artificial neural networks (ANNs), in mammography interpretation and diagnostic decision making and discuss important features in mammography interpretation. We conclude by discussing several common limitations of existing research on ANN-based detection and diagnostic models and provide possible future research directions.

Personnel reliability impact on petrochemical facilities monitoring system's failure skipping probability

NASA Astrophysics Data System (ADS)

Kostyukov, V. N.; Naumenko, A. P.

2017-08-01

The paper dwells upon urgent issues of evaluating impact of actions conducted by complex technological systems operators on their safe operation considering application of condition monitoring systems for elements and sub-systems of petrochemical production facilities. The main task for the research is to distinguish factors and criteria of monitoring system properties description, which would allow to evaluate impact of errors made by personnel on operation of real-time condition monitoring and diagnostic systems for machinery of petrochemical facilities, and find and objective criteria for monitoring system class, considering a human factor. On the basis of real-time condition monitoring concepts of sudden failure skipping risk, static and dynamic error, monitoring systems, one may solve a task of evaluation of impact that personnel's qualification has on monitoring system operation in terms of error in personnel or operators' actions while receiving information from monitoring systems and operating a technological system. Operator is considered as a part of the technological system. Although, personnel's behavior is usually a combination of the following parameters: input signal - information perceiving, reaction - decision making, response - decision implementing. Based on several researches on behavior of nuclear powers station operators in USA, Italy and other countries, as well as on researches conducted by Russian scientists, required data on operator's reliability were selected for analysis of operator's behavior at technological facilities diagnostics and monitoring systems. The calculations revealed that for the monitoring system selected as an example, the failure skipping risk for the set values of static (less than 0.01) and dynamic (less than 0.001) errors considering all related factors of data on reliability of information perception, decision-making, and reaction fulfilled is 0.037, in case when all the facilities and error probability are under control - not more than 0.027. In case when only pump and compressor units are under control, the failure skipping risk is not more than 0.022, when the probability of error in operator's action is not more than 0.011. The work output shows that on the basis of the researches results an assessment of operators' reliability can be made in terms of almost any kind of production, but considering only technological capabilities, since operators' psychological and general training considerable vary in different production industries. Using latest technologies of engineering psychology and design of data support systems, situation assessment systems, decision-making and responding system, as well as achievement in condition monitoring in various production industries one can evaluate hazardous condition skipping risk probability considering static, dynamic errors and human factor.

The neural substrates of deliberative decision making: contrasting effects of hippocampus lesions on performance and vicarious trial-and-error behavior in a spatial memory task and a visual discrimination task

PubMed Central

Bett, David; Allison, Elizabeth; Murdoch, Lauren H.; Kaefer, Karola; Wood, Emma R.; Dudchenko, Paul A.

2012-01-01

Vicarious trial-and-errors (VTEs) are back-and-forth movements of the head exhibited by rodents and other animals when faced with a decision. These behaviors have recently been associated with prospective sweeps of hippocampal place cell firing, and thus may reflect a rodent model of deliberative decision-making. The aim of the current study was to test whether the hippocampus is essential for VTEs in a spatial memory task and in a simple visual discrimination (VD) task. We found that lesions of the hippocampus with ibotenic acid produced a significant impairment in the accuracy of choices in a serial spatial reversal (SR) task. In terms of VTEs, whereas sham-lesioned animals engaged in more VTE behavior prior to identifying the location of the reward as opposed to repeated trials after it had been located, the lesioned animals failed to show this difference. In contrast, damage to the hippocampus had no effect on acquisition of a VD or on the VTEs seen in this task. For both lesion and sham-lesion animals, adding an additional choice to the VD increased the number of VTEs and decreased the accuracy of choices. Together, these results suggest that the hippocampus may be specifically involved in VTE behavior during spatial decision making. PMID:23115549

Dopaminergic Modulation of Decision Making and Subjective Well-Being.

PubMed

Rutledge, Robb B; Skandali, Nikolina; Dayan, Peter; Dolan, Raymond J

2015-07-08

The neuromodulator dopamine has a well established role in reporting appetitive prediction errors that are widely considered in terms of learning. However, across a wide variety of contexts, both phasic and tonic aspects of dopamine are likely to exert more immediate effects that have been less well characterized. Of particular interest is dopamine's influence on economic risk taking and on subjective well-being, a quantity known to be substantially affected by prediction errors resulting from the outcomes of risky choices. By boosting dopamine levels using levodopa (l-DOPA) as human subjects made economic decisions and repeatedly reported their momentary happiness, we show here an effect on both choices and happiness. Boosting dopamine levels increased the number of risky options chosen in trials involving potential gains but not trials involving potential losses. This effect could be better captured as increased Pavlovian approach in an approach-avoidance decision model than as a change in risk preferences within an established prospect theory model. Boosting dopamine also increased happiness resulting from some rewards. Our findings thus identify specific novel influences of dopamine on decision making and emotion that are distinct from its established role in learning. Copyright © 2015 Rutledge et al.

Dopaminergic Modulation of Decision Making and Subjective Well-Being

PubMed Central

Skandali, Nikolina; Dayan, Peter; Dolan, Raymond J.

2015-01-01

The neuromodulator dopamine has a well established role in reporting appetitive prediction errors that are widely considered in terms of learning. However, across a wide variety of contexts, both phasic and tonic aspects of dopamine are likely to exert more immediate effects that have been less well characterized. Of particular interest is dopamine's influence on economic risk taking and on subjective well-being, a quantity known to be substantially affected by prediction errors resulting from the outcomes of risky choices. By boosting dopamine levels using levodopa (l-DOPA) as human subjects made economic decisions and repeatedly reported their momentary happiness, we show here an effect on both choices and happiness. Boosting dopamine levels increased the number of risky options chosen in trials involving potential gains but not trials involving potential losses. This effect could be better captured as increased Pavlovian approach in an approach–avoidance decision model than as a change in risk preferences within an established prospect theory model. Boosting dopamine also increased happiness resulting from some rewards. Our findings thus identify specific novel influences of dopamine on decision making and emotion that are distinct from its established role in learning. PMID:26156984

Goal-Directed Decision Making with Spiking Neurons.

PubMed

Friedrich, Johannes; Lengyel, Máté

2016-02-03

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. Copyright © 2016 the authors 0270-6474/16/361529-18$15.00/0.

Goal-Directed Decision Making with Spiking Neurons

PubMed Central

Lengyel, Máté

2016-01-01

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. SIGNIFICANCE STATEMENT Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. PMID:26843636

Error assessment for emerging traffic data collection devices.

DOT National Transportation Integrated Search

2014-06-01

Because access to travel time information can significantly influence the decision making of both agencies : and travelers, accurate and reliable travel time information is increasingly needed. One important step in : providing that information is to...

Confidence and Information Access in Clinical Decision-Making: An Examination of the Cognitive Processes that affect the Information-seeking Behavior of Physicians.

PubMed

Uy, Raymonde Charles; Sarmiento, Raymond Francis; Gavino, Alex; Fontelo, Paul

2014-01-01

Clinical decision-making involves the interplay between cognitive processes and physicians' perceptions of confidence in the context of their information-seeking behavior. The objectives of the study are: to examine how these concepts interact, to determine whether physician confidence, defined in relation to information need, affects clinical decision-making, and if information access improves decision accuracy. We analyzed previously collected data about resident physicians' perceptions of information need from a study comparing abstracts and full-text articles in clinical decision accuracy. We found that there is a significant relation between confidence and accuracy (φ=0.164, p<0.01). We also found various differences in the alignment of confidence and accuracy, demonstrating the concepts of underconfidence and overconfidence across years of clinical experience. Access to online literature also has a significant effect on accuracy (p<0.001). These results highlight possible CDSS strategies to reduce medical errors.

How Prediction Errors Shape Perception, Attention, and Motivation

PubMed Central

den Ouden, Hanneke E. M.; Kok, Peter; de Lange, Floris P.

2012-01-01

Prediction errors (PE) are a central notion in theoretical models of reinforcement learning, perceptual inference, decision-making and cognition, and prediction error signals have been reported across a wide range of brain regions and experimental paradigms. Here, we will make an attempt to see the forest for the trees and consider the commonalities and differences of reported PE signals in light of recent suggestions that the computation of PE forms a fundamental mode of brain function. We discuss where different types of PE are encoded, how they are generated, and the different functional roles they fulfill. We suggest that while encoding of PE is a common computation across brain regions, the content and function of these error signals can be very different and are determined by the afferent and efferent connections within the neural circuitry in which they arise. PMID:23248610

An integrated experiment for identification of best decision styles and teamworks with respect to HSE and ergonomics program: The case of a large oil refinery.

PubMed

Azadeh, A; Mokhtari, Z; Sharahi, Z Jiryaei; Zarrin, M

2015-12-01

Decision making failure is a predominant human error in emergency situations. To demonstrate the subject model, operators of an oil refinery were asked to answer a health, safety and environment HSE-decision styles (DS) questionnaire. In order to achieve this purpose, qualitative indicators in HSE and ergonomics domain have been collected. Decision styles, related to the questions, have been selected based on Driver taxonomy of human decision making approach. Teamwork efficiency has been assessed based on different decision style combinations. The efficiency has been ranked based on HSE performance. Results revealed that efficient decision styles resulted from data envelopment analysis (DEA) optimization model is consistent with the plant's dominant styles. Therefore, improvement in system performance could be achieved using the best operator for critical posts or in team arrangements. This is the first study that identifies the best decision styles with respect to HSE and ergonomics factors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Decision-Making under Risk of Loss in Children

PubMed Central

Steelandt, Sophie; Broihanne, Marie-Hélène; Romain, Amélie; Thierry, Bernard; Dufour, Valérie

2013-01-01

In human adults, judgment errors are known to often lead to irrational decision-making in risky contexts. While these errors can affect the accuracy of profit evaluation, they may have once enhanced survival in dangerous contexts following a “better be safe than sorry” rule of thumb. Such a rule can be critical for children, and it could develop early on. Here, we investigated the rationality of choices and the possible occurrence of judgment errors in children aged 3 to 9 years when exposed to a risky trade. Children were allocated with a piece of cookie that they could either keep or risk in exchange of the content of one cup among 6, visible in front of them. In the cups, cookies could be of larger, equal or smaller sizes than the initial allocation. Chances of losing or winning were manipulated by presenting different combinations of cookie sizes in the cups (for example 3 large, 2 equal and 1 small cookie). We investigated the rationality of children's response using the theoretical models of Expected Utility Theory (EUT) and Cumulative Prospect Theory. Children aged 3 to 4 years old were unable to discriminate the profitability of exchanging in the different combinations. From 5 years, children were better at maximizing their benefit in each combination, their decisions were negatively induced by the probability of losing, and they exhibited a framing effect, a judgment error found in adults. Confronting data to the EUT indicated that children aged over 5 were risk-seekers but also revealed inconsistencies in their choices. According to a complementary model, the Cumulative Prospect Theory (CPT), they exhibited loss aversion, a pattern also found in adults. These findings confirm that adult-like judgment errors occur in children, which suggests that they possess a survival value. PMID:23349682

Decision-making under risk of loss in children.

PubMed

Steelandt, Sophie; Broihanne, Marie-Hélène; Romain, Amélie; Thierry, Bernard; Dufour, Valérie

2013-01-01

In human adults, judgment errors are known to often lead to irrational decision-making in risky contexts. While these errors can affect the accuracy of profit evaluation, they may have once enhanced survival in dangerous contexts following a "better be safe than sorry" rule of thumb. Such a rule can be critical for children, and it could develop early on. Here, we investigated the rationality of choices and the possible occurrence of judgment errors in children aged 3 to 9 years when exposed to a risky trade. Children were allocated with a piece of cookie that they could either keep or risk in exchange of the content of one cup among 6, visible in front of them. In the cups, cookies could be of larger, equal or smaller sizes than the initial allocation. Chances of losing or winning were manipulated by presenting different combinations of cookie sizes in the cups (for example 3 large, 2 equal and 1 small cookie). We investigated the rationality of children's response using the theoretical models of Expected Utility Theory (EUT) and Cumulative Prospect Theory. Children aged 3 to 4 years old were unable to discriminate the profitability of exchanging in the different combinations. From 5 years, children were better at maximizing their benefit in each combination, their decisions were negatively induced by the probability of losing, and they exhibited a framing effect, a judgment error found in adults. Confronting data to the EUT indicated that children aged over 5 were risk-seekers but also revealed inconsistencies in their choices. According to a complementary model, the Cumulative Prospect Theory (CPT), they exhibited loss aversion, a pattern also found in adults. These findings confirm that adult-like judgment errors occur in children, which suggests that they possess a survival value.

Twenty-First Annual Conference on Manual Control

NASA Technical Reports Server (NTRS)

Miller, R. A. (Compiler); Jagacinski, R. J. (Compiler)

1986-01-01

The proceedings of the entitled conference are presented. Twenty-nine manuscripts and eight abstracts pertaining to workload, attention and errors, controller evaluation, movement skills, coordination and decision making, display evaluation and human operator modeling and manual control.

Benefit-risk Evaluation for Diagnostics: A Framework (BED-FRAME).

PubMed

Evans, Scott R; Pennello, Gene; Pantoja-Galicia, Norberto; Jiang, Hongyu; Hujer, Andrea M; Hujer, Kristine M; Manca, Claudia; Hill, Carol; Jacobs, Michael R; Chen, Liang; Patel, Robin; Kreiswirth, Barry N; Bonomo, Robert A

2016-09-15

The medical community needs systematic and pragmatic approaches for evaluating the benefit-risk trade-offs of diagnostics that assist in medical decision making. Benefit-Risk Evaluation of Diagnostics: A Framework (BED-FRAME) is a strategy for pragmatic evaluation of diagnostics designed to supplement traditional approaches. BED-FRAME evaluates diagnostic yield and addresses 2 key issues: (1) that diagnostic yield depends on prevalence, and (2) that different diagnostic errors carry different clinical consequences. As such, evaluating and comparing diagnostics depends on prevalence and the relative importance of potential errors. BED-FRAME provides a tool for communicating the expected clinical impact of diagnostic application and the expected trade-offs of diagnostic alternatives. BED-FRAME is a useful fundamental supplement to the standard analysis of diagnostic studies that will aid in clinical decision making. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Research on AHP decision algorithms based on BP algorithm

NASA Astrophysics Data System (ADS)

Ma, Ning; Guan, Jianhe

2017-10-01

Decision making is the thinking activity that people choose or judge, and scientific decision-making has always been a hot issue in the field of research. Analytic Hierarchy Process (AHP) is a simple and practical multi-criteria and multi-objective decision-making method that combines quantitative and qualitative and can show and calculate the subjective judgment in digital form. In the process of decision analysis using AHP method, the rationality of the two-dimensional judgment matrix has a great influence on the decision result. However, in dealing with the real problem, the judgment matrix produced by the two-dimensional comparison is often inconsistent, that is, it does not meet the consistency requirements. BP neural network algorithm is an adaptive nonlinear dynamic system. It has powerful collective computing ability and learning ability. It can perfect the data by constantly modifying the weights and thresholds of the network to achieve the goal of minimizing the mean square error. In this paper, the BP algorithm is used to deal with the consistency of the two-dimensional judgment matrix of the AHP.

Higher incentives can impair performance: neural evidence on reinforcement and rationality

PubMed Central

Achtziger, Anja; Hügelschäfer, Sabine; Steinhauser, Marco

2015-01-01

Standard economic thinking postulates that increased monetary incentives should increase performance. Human decision makers, however, frequently focus on past performance, a form of reinforcement learning occasionally at odds with rational decision making. We used an incentivized belief-updating task from economics to investigate this conflict through measurements of neural correlates of reward processing. We found that higher incentives fail to improve performance when immediate feedback on decision outcomes is provided. Subsequent analysis of the feedback-related negativity, an early event-related potential following feedback, revealed the mechanism behind this paradoxical effect. As incentives increase, the win/lose feedback becomes more prominent, leading to an increased reliance on reinforcement and more errors. This mechanism is relevant for economic decision making and the debate on performance-based payment. PMID:25816816

Market mechanisms protect the vulnerable brain.

PubMed

Ramchandran, Kanchna; Nayakankuppam, Dhananjay; Berg, Joyce; Tranel, Daniel; Denburg, Natalie L

2011-07-01

Markets are mechanisms of social exchange, intended to facilitate trading. However, the question remains as to whether markets would help or hurt individuals with decision-makings deficits, as is frequently encountered in the case of cognitive aging. Essential for predicting future gains and losses in monetary and social domains, the striatal nuclei in the brain undergo structural, neurochemical, and functional decline with age. We correlated the efficacy of market mechanisms with dorsal striatal decline in an aging population, by using market based trading in the context of the 2008 U.S. Presidential Elections (primary cycle). Impaired decision-makers displayed higher prediction error (difference between their prediction and actual outcome). Lower in vivo caudate volume was also associated with higher prediction error. Importantly, market-based trading protected older adults with lower caudate volume to a greater extent from their own poorly calibrated predictions. Counterintuitive to the traditional public perception of the market as a fickle, risky proposition where vulnerable traders are most surely to be burned, we suggest that market-based mechanisms protect individuals with brain-based decision-making vulnerabilities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Market mechanisms protect the vulnerable brain

PubMed Central

Ramchandran, Kanchna; Nayakankuppam, Dhananjay; Berg, Joyce; Tranel, Daniel

2011-01-01

Markets are mechanisms of social exchange, intended to facilitate trading. However, the question remains as to whether markets would help or hurt individuals with decision-makings deficits, as is frequently encountered in the case of cognitive aging. Essential for predicting future gains and losses in monetary and social domains, the striatal nuclei in the brain undergo structural, neurochemical, and functional decline with age. We correlated the efficacy of market mechanisms with dorsal striatal decline in an aging population, by using market based trading in the context of the 2008 U.S Presidential Elections (primary cycle). Impaired decision-makers displayed higher prediction error (difference between their prediction and actual outcome). Lower in vivo caudate volume was also associated with higher prediction error. Importantly, market-based trading protected older adults with lower caudate volume to a greater extent from their own poorly calibrated predictions. Counterintuitive to the traditional public perception of the market as a fickle, risky proposition where vulnerable traders are most surely to be burned, we suggest that market-based mechanisms protect individuals with brain-based decision-making vulnerabilities. PMID:21600226

Successful choice behavior is associated with distinct and coherent network states in anterior cingulate cortex

PubMed Central

Lapish, Christopher C.; Durstewitz, Daniel; Chandler, L. Judson; Seamans, Jeremy K.

2008-01-01

Successful decision making requires an ability to monitor contexts, actions, and outcomes. The anterior cingulate cortex (ACC) is thought to be critical for these functions, monitoring and guiding decisions especially in challenging situations involving conflict and errors. A number of different single-unit correlates have been observed in the ACC that reflect the diverse cognitive components involved. Yet how ACC neurons function as an integrated network is poorly understood. Here we show, using advanced population analysis of multiple single-unit recordings from the rat ACC during performance of an ecologically valid decision-making task, that ensembles of neurons move through different coherent and dissociable states as the cognitive requirements of the task change. This organization into distinct network patterns with respect to both firing-rate changes and correlations among units broke down during trials with numerous behavioral errors, especially at choice points of the task. These results point to an underlying functional organization into cell assemblies in the ACC that may monitor choices, outcomes, and task contexts, thus tracking the animal's progression through “task space.” PMID:18708525

Introduction to cognitive processes of expert pilots.

PubMed

Adams, R J; Ericsson, A E

2000-10-01

This report addresses the historical problem that a very high percentage of accidents have been classified as involving "pilot error." Through extensive research since 1977, the Federal Aviation Administration determined that the predominant underlying cause of these types of accidents involved decisional problems or cognitive information processing. To attack these problems, Aeronautical Decision Making (ADM) training materials were developed and tested for ten years. Since the publication of the ADM training manuals in 1987, significant reductions in human performance error (HPE) accidents have been documented both in the U.S. and world wide. However, shortcomings have been observed in the use of these materials for recurrency training and in their relevance to more experienced pilots. The following discussion defines the differences between expert and novice decision makers from a cognitive information processing perspective, correlates the development of expert pilot cognitive processes with training and experience, and reviews accident scenarios which exemplify those processes. This introductory material is a necessary prerequisite to an understanding of how to formulate expert pilot decision making training innovations; and, to continue the record of improved safety through ADM training.

Energy efficiency in cognitive radio network: Study of cooperative sensing using different channel sensing methods

NASA Astrophysics Data System (ADS)

Cui, Chenxuan

When cognitive radio (CR) operates, it starts by sensing spectrum and looking for idle bandwidth. There are several methods for CR to make a decision on either the channel is occupied or idle, for example, energy detection scheme, cyclostationary detection scheme and matching filtering detection scheme [1]. Among them, the most common method is energy detection scheme because of its algorithm and implementation simplicities [2]. There are two major methods for sensing, the first one is to sense single channel slot with varying bandwidth, whereas the second one is to sense multiple channels and each with same bandwidth. After sensing periods, samples are compared with a preset detection threshold and a decision is made on either the primary user (PU) is transmitting or not. Sometimes the sensing and decision results can be erroneous, for example, false alarm error and misdetection error may occur. In order to better control error probabilities and improve CR network performance (i.e. energy efficiency), we introduce cooperative sensing; in which several CR within a certain range detect and make decisions on channel availability together. The decisions are transmitted to and analyzed by a data fusion center (DFC) to make a final decision on channel availability. After the final decision is been made, DFC sends back the decision to the CRs in order to tell them to stay idle or start to transmit data to secondary receiver (SR) within a preset transmission time. After the transmission, a new cycle starts again with sensing. This thesis report is organized as followed: Chapter II review some of the papers on optimizing CR energy efficiency. In Chapter III, we study how to achieve maximal energy efficiency when CR senses single channel with changing bandwidth and with constrain on misdetection threshold in order to protect PU; furthermore, a case study is given and we calculate the energy efficiency. In Chapter IV, we study how to achieve maximal energy efficiency when CR senses multiple channels and each channel with same bandwidth, also, we preset a misdetection threshold and calculate the energy efficiency. A comparison will be shown between two sensing methods at the end of the chapter. Finally, Chapter V concludes this thesis.

Decisions without Direction: Career Guidance and Decision-Making among American Youth.

ERIC Educational Resources Information Center

Hurley, Dan, Ed.; Thorp, Jim, Ed.

The attitudes and career plans of high school juniors and seniors were examined in a telephone survey of 809 U.S. high school juniors and seniors (sampling error, +/-3.5%). The respondents ranged in age from 14 to 20 years and were evenly divided between males and females. The key conclusions were as follows: (1) students perceive a lack of career…

Criteria for assessing problem solving and decision making in complex environments

NASA Technical Reports Server (NTRS)

Orasanu, Judith

1993-01-01

Training crews to cope with unanticipated problems in high-risk, high-stress environments requires models of effective problem solving and decision making. Existing decision theories use the criteria of logical consistency and mathematical optimality to evaluate decision quality. While these approaches are useful under some circumstances, the assumptions underlying these models frequently are not met in dynamic time-pressured operational environments. Also, applying formal decision models is both labor and time intensive, a luxury often lacking in operational environments. Alternate approaches and criteria are needed. Given that operational problem solving and decision making are embedded in ongoing tasks, evaluation criteria must address the relation between those activities and satisfaction of broader task goals. Effectiveness and efficiency become relevant for judging reasoning performance in operational environments. New questions must be addressed: What is the relation between the quality of decisions and overall performance by crews engaged in critical high risk tasks? Are different strategies most effective for different types of decisions? How can various decision types be characterized? A preliminary model of decision types found in air transport environments will be described along with a preliminary performance model based on an analysis of 30 flight crews. The performance analysis examined behaviors that distinguish more and less effective crews (based on performance errors). Implications for training and system design will be discussed.

Pilot error in air carrier mishaps: longitudinal trends among 558 reports, 1983-2002.

PubMed

Baker, Susan P; Qiang, Yandong; Rebok, George W; Li, Guohua

2008-01-01

Many interventions have been implemented in recent decades to reduce pilot error in flight operations. This study aims to identify longitudinal trends in the prevalence and patterns of pilot error and other factors in U.S. air carrier mishaps. National Transportation Safety Board investigation reports were examined for 558 air carrier mishaps during 1983-2002. Pilot errors and circumstances of mishaps were described and categorized. Rates were calculated per 10 million flights. The overall mishap rate remained fairly stable, but the proportion of mishaps involving pilot error decreased from 42% in 1983-87 to 25% in 1998-2002, a 40% reduction. The rate of mishaps related to poor decisions declined from 6.2 to 1.8 per 10 million flights, a 71% reduction; much of this decrease was due to a 76% reduction in poor decisions related to weather. Mishandling wind or runway conditions declined by 78%. The rate of mishaps involving poor crew interaction declined by 68%. Mishaps during takeoff declined by 70%, from 5.3 to 1.6 per 10 million flights. The latter reduction was offset by an increase in mishaps while the aircraft was standing, from 2.5 to 6.0 per 10 million flights, and during pushback, which increased from 0 to 3.1 per 10 million flights. Reductions in pilot errors involving decision making and crew coordination are important trends that may reflect improvements in training and technological advances that facilitate good decisions. Mishaps while aircraft are standing and during pushback have increased and deserve special attention.

Pilot Error in Air Carrier Mishaps: Longitudinal Trends Among 558 Reports, 1983–2002

PubMed Central

Baker, Susan P.; Qiang, Yandong; Rebok, George W.; Li, Guohua

2009-01-01

Background Many interventions have been implemented in recent decades to reduce pilot error in flight operations. This study aims to identify longitudinal trends in the prevalence and patterns of pilot error and other factors in U.S. air carrier mishaps. Method National Transportation Safety Board investigation reports were examined for 558 air carrier mishaps during 1983–2002. Pilot errors and circumstances of mishaps were described and categorized. Rates were calculated per 10 million flights. Results The overall mishap rate remained fairly stable, but the proportion of mishaps involving pilot error decreased from 42% in 1983–87 to 25% in 1998–2002, a 40% reduction. The rate of mishaps related to poor decisions declined from 6.2 to 1.8 per 10 million flights, a 71% reduction; much of this decrease was due to a 76% reduction in poor decisions related to weather. Mishandling wind or runway conditions declined by 78%. The rate of mishaps involving poor crew interaction declined by 68%. Mishaps during takeoff declined by 70%, from 5.3 to 1.6 per 10 million flights. The latter reduction was offset by an increase in mishaps while the aircraft was standing, from 2.5 to 6.0 per 10 million flights, and during pushback, which increased from 0 to 3.1 per 10 million flights. Conclusions Reductions in pilot errors involving decision making and crew coordination are important trends that may reflect improvements in training and technological advances that facilitate good decisions. Mishaps while aircraft are standing and during push-back have increased and deserve special attention. PMID:18225771

Automation, decision support, and expert systems in nephrology.

PubMed

Soman, Sandeep; Zasuwa, Gerard; Yee, Jerry

2008-01-01

Increasing data suggest that errors in medicine occur frequently and result in substantial harm to the patient. The Institute of Medicine report described the magnitude of the problem, and public interest in this issue, which was already large, has grown. The traditional approach in medicine has been to identify the persons making the errors and recommend corrective strategies. However, it has become increasingly clear that it is more productive to focus on the systems and processes through which care is provided. If these systems are set up in ways that would both make errors less likely and identify those that do occur and, at the same time, improve efficiency, then safety and productivity would be substantially improved. Clinical decision support systems (CDSSs) are active knowledge systems that use 2 or more items of patient data to generate case specific recommendations. CDSSs are typically designed to integrate a medical knowledge base, patient data, and an inference engine to generate case specific advice. This article describes how automation, templating, and CDSS improve efficiency, patient care, and safety by reducing the frequency and consequences of medical errors in nephrology. We discuss practical applications of these in 3 settings: a computerized anemia-management program (CAMP, Henry Ford Health System, Detroit, MI), vascular access surveillance systems, and monthly capitation notes in the hemodialysis unit.

Potential barge transportation for inbound corn and grain

DOT National Transportation Integrated Search

1997-12-31

This research develops a model for estimating future barge and rail rates for decision making. The Box-Jenkins and the Regression Analysis with ARIMA errors forecasting methods were used to develop appropriate models for determining future rates. A s...

Jumping to the wrong conclusions? An investigation of the mechanisms of reasoning errors in delusions

PubMed Central

Jolley, Suzanne; Thompson, Claire; Hurley, James; Medin, Evelina; Butler, Lucy; Bebbington, Paul; Dunn, Graham; Freeman, Daniel; Fowler, David; Kuipers, Elizabeth; Garety, Philippa

2014-01-01

Understanding how people with delusions arrive at false conclusions is central to the refinement of cognitive behavioural interventions. Making hasty decisions based on limited data (‘jumping to conclusions’, JTC) is one potential causal mechanism, but reasoning errors may also result from other processes. In this study, we investigated the correlates of reasoning errors under differing task conditions in 204 participants with schizophrenia spectrum psychosis who completed three probabilistic reasoning tasks. Psychotic symptoms, affect, and IQ were also evaluated. We found that hasty decision makers were more likely to draw false conclusions, but only 37% of their reasoning errors were consistent with the limited data they had gathered. The remainder directly contradicted all the presented evidence. Reasoning errors showed task-dependent associations with IQ, affect, and psychotic symptoms. We conclude that limited data-gathering contributes to false conclusions but is not the only mechanism involved. Delusions may also be maintained by a tendency to disregard evidence. Low IQ and emotional biases may contribute to reasoning errors in more complex situations. Cognitive strategies to reduce reasoning errors should therefore extend beyond encouragement to gather more data, and incorporate interventions focused directly on these difficulties. PMID:24958065

Vaccine administration decision making: the case of yellow fever vaccine.

PubMed

Lown, Beth A; Chen, Lin H; Wilson, Mary E; Sisson, Emily; Gershman, Mark; Yanni, Emad; Jentes, Emily S; Hochberg, Natasha S; Hamer, Davidson H; Barnett, Elizabeth D

2012-09-01

Providers must counsel travelers to yellow fever (YF)-endemic areas, although risk estimates of disease and vaccine serious adverse events (SAEs) may be imprecise. The impact of risk information and patients' requests for participation in vaccine decisions on providers' recommendations is unknown. Vaccine providers were surveyed regarding decisions for 4 patient scenarios before and after being presented information about risk of YF disease vs vaccine SAEs. Participants' theoretical attitudes were compared with actual responses to scenarios in which patients wanted to share vaccine decisions. Analyses were done by using χ(2) tests with significance level of .05. Forty-six percent of respondents made appropriate initial YF vaccine administration decisions for a pregnant woman, 73% for an immunosuppressed man, and 49% for an 8-month-old infant. After receiving scenario-specific information, 20%, 54%, and 23% of respondents respectively who initially responded incorrectly changed to a more appropriate decision. Thirty-one percent of participants made consistently appropriate decisions. Among participants who made ≥1 incorrect decision, 35.7% made no decision changes after receiving information. In the scenario in which either a decision to withhold or to administer vaccine was acceptable, 19% of respondents refused a patient's request for vaccine. Targeted information is necessary but insufficient to change the process of vaccine administration decision making. Providers need additional education to enable them to apply evidence, overcome cognitive decision-making errors, and involve patients in vaccine decisions.

Neural signatures of experience-based improvements in deterministic decision-making.

PubMed

Tremel, Joshua J; Laurent, Patryk A; Wolk, David A; Wheeler, Mark E; Fiez, Julie A

2016-12-15

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatial attention during saccade decisions.

PubMed

Jonikaitis, Donatas; Klapetek, Anna; Deubel, Heiner

2017-07-01

Behavioral measures of decision making are usually limited to observations of decision outcomes. In the present study, we made use of the fact that oculomotor and sensory selection are closely linked to track oculomotor decision making before oculomotor responses are made. We asked participants to make a saccadic eye movement to one of two memorized target locations and observed that visual sensitivity increased at both the chosen and the nonchosen saccade target locations, with a clear bias toward the chosen target. The time course of changes in visual sensitivity was related to saccadic latency, with the competition between the chosen and nonchosen targets resolved faster before short-latency saccades. On error trials, we observed an increased competition between the chosen and nonchosen targets. Moreover, oculomotor selection and visual sensitivity were influenced by top-down and bottom-up factors as well as by selection history and predicted the direction of saccades. Our findings demonstrate that saccade decisions have direct visual consequences and show that decision making can be traced in the human oculomotor system well before choices are made. Our results also indicate a strong association between decision making, saccade target selection, and visual sensitivity. NEW & NOTEWORTHY We show that saccadic decisions can be tracked by measuring spatial attention. Spatial attention is allocated in parallel to the two competing saccade targets, and the time course of spatial attention differs for fast-slow and for correct-erroneous decisions. Saccade decisions take the form of a competition between potential saccade goals, which is associated with spatial attention allocation to those locations. Copyright © 2017 the American Physiological Society.

Neural signatures of experience-based improvements in deterministic decision-making

PubMed Central

Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

2016-01-01

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644

The PoET (Prevention of Error-Based Transfers) Project.

PubMed

Oliver, Jill; Chidwick, Paula

2017-01-01

The PoET (Prevention of Error-based Transfers) Project is one of the Ethics Quality Improvement Projects (EQIPs) taking place at William Osler Health System. This specific project is designed to reduce transfers from long-term care to hospital that are caused by legal and ethical errors related to consent, capacity and substitute decision-making. The project is currently operating in eight long-term care homes in the Central West Local Health Integration Network and has seen a 56% reduction in multiple transfers before death in hospital.

Suicide behavior and neuropsychological assessment of type I bipolar patients.

PubMed

Malloy-Diniz, Leandro F; Neves, Fernando Silva; Abrantes, Suzana Silva Costa; Fuentes, Daniel; Corrêa, Humberto

2009-01-01

Neuropsychological deficits are often described in patients with bipolar disorder (BD). Some symptoms and/or associated characteristics of BD can be more closely associated to those cognitive impairments. We aimed to explore cognitive neuropsychological characteristics of type I bipolar patients (BPI) in terms of lifetime suicide attempt history. We studied 39 BPI outpatients compared with 53 healthy controls (HC) matched by age, educational and intellectual level. All subjects were submitted to a neuropsychological assessment of executive functions, decision-making and declarative episodic memory. When comparing BDI patients, regardless of suicide attempt history or HC, we observed that bipolar patients performed worse than controls on measures of memory, attention, executive functions and decision-making. Patients with a history of suicide attempt performed worse than non-attempters on measures of decision-making and there were a significant negative correlation between the number of suicide attempts and decision-making results (block 3 and net score). We also found significant positive correlation between the number of suicide attempts and amount of errors in Stroop Color Word Test (part 3). The sample studied can be considered small and a potentially confounding variable - medication status - were not controlled. Our results show the presence of neuropsychological deficits in memory, executive functions, attention and decision-making in BPI patients. Suicide attempts BPI scored worse than non-suicide attempt BPI on measures of decision-making. More suicide attempts were associated with a worse decision-making process. Future research should explore the relationship between the association between this specific cognitive deficits in BPIs, serotonergic function and suicide behavior in bipolar patients as well other diagnostic groups.

Testing decision rules for categorizing species' extinction risk to help develop quantitative listing criteria for the U.S. Endangered Species Act.

PubMed

Regan, Tracey J; Taylor, Barbara L; Thompson, Grant G; Cochrane, Jean Fitts; Ralls, Katherine; Runge, Michael C; Merrick, Richard

2013-08-01

Lack of guidance for interpreting the definitions of endangered and threatened in the U.S. Endangered Species Act (ESA) has resulted in case-by-case decision making leaving the process vulnerable to being considered arbitrary or capricious. Adopting quantitative decision rules would remedy this but requires the agency to specify the relative urgency concerning extinction events over time, cutoff risk values corresponding to different levels of protection, and the importance given to different types of listing errors. We tested the performance of 3 sets of decision rules that use alternative functions for weighting the relative urgency of future extinction events: a threshold rule set, which uses a decision rule of x% probability of extinction over y years; a concave rule set, where the relative importance of future extinction events declines exponentially over time; and a shoulder rule set that uses a sigmoid shape function, where relative importance declines slowly at first and then more rapidly. We obtained decision cutoffs by interviewing several biologists and then emulated the listing process with simulations that covered a range of extinction risks typical of ESA listing decisions. We evaluated performance of the decision rules under different data quantities and qualities on the basis of the relative importance of misclassification errors. Although there was little difference between the performance of alternative decision rules for correct listings, the distribution of misclassifications differed depending on the function used. Misclassifications for the threshold and concave listing criteria resulted in more overprotection errors, particularly as uncertainty increased, whereas errors for the shoulder listing criteria were more symmetrical. We developed and tested the framework for quantitative decision rules for listing species under the U.S. ESA. If policy values can be agreed on, use of this framework would improve the implementation of the ESA by increasing transparency and consistency. Conservation Biology © 2013 Society for Conservation Biology No claim to original US government works.

Erratum To: Indigenous Frameworks for Observing and Responding to Climate Change in Alaska

NASA Technical Reports Server (NTRS)

Cochran, Patricia; Huntington, Orville H.; Pungowiyi, Caleb; Tom, Stanley; Chapin, F. Stuart, III; Huntington, Henry P.; Maynard, Nancy G.; Trainor, Sarah F.

2014-01-01

In section 5, item 1 of this article it is stated that: A recent shift in decision-making authority from the politically appointed Board of Game to the Subsistence Division of the Alaska Department of Fish and Game should make these decisions about hunting regulations more responsive to local observations and needs. We now recognize that this shift in regulatory authority to ADF&G never occurred. We hereby correct this error so that wildlife users in Alaska do not come to ADF&G with expectations that this agency has authority to adjust hunting regulations to accommodate climate change.

Perceptions of disease risk: from social construction of subjective judgments to rational decision making.

PubMed

McRoberts, N; Hall, C; Madden, L V; Hughes, G

2011-06-01

Many factors influence how people form risk perceptions. Farmers' perceptions of risk and levels of risk aversion impact on decision-making about such things as technology adoption and disease management practices. Irrespective of the underlying factors that affect risk perceptions, those perceptions can be summarized by variables capturing impact and uncertainty components of risk. We discuss a new framework that has the subjective probability of disease and the cost of decision errors as its central features, which might allow a better integration of social science and epidemiology, to the benefit of plant disease management. By focusing on the probability and cost (or impact) dimensions of risk, the framework integrates research from the social sciences, economics, decision theory, and epidemiology. In particular, we review some useful properties of expected regret and skill value, two measures of expected cost that are particularly useful in the evaluation of decision tools. We highlight decision-theoretic constraints on the usefulness of decision tools that may partly explain cases of failure of adoption. We extend this analysis by considering information-theoretic criteria that link model complexity and relative performance and which might explain why users reject forecasters that impose even moderate increases in the complexity of decision making despite improvements in performance or accept very simple decision tools that have relatively poor performance.

Frequent methodological errors in clinical research.

PubMed

Silva Aycaguer, L C

2018-03-07

Several errors that are frequently present in clinical research are listed, discussed and illustrated. A distinction is made between what can be considered an "error" arising from ignorance or neglect, from what stems from a lack of integrity of researchers, although it is recognized and documented that it is not easy to establish when we are in a case and when in another. The work does not intend to make an exhaustive inventory of such problems, but focuses on those that, while frequent, are usually less evident or less marked in the various lists that have been published with this type of problems. It has been a decision to develop in detail the examples that illustrate the problems identified, instead of making a list of errors accompanied by an epidermal description of their characteristics. Copyright © 2018 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

Reasoning in psychosis: risky but not necessarily hasty.

PubMed

Moritz, Steffen; Scheu, Florian; Andreou, Christina; Pfueller, Ute; Weisbrod, Matthias; Roesch-Ely, Daniela

2016-01-01

A liberal acceptance (LA) threshold for hypotheses has been put forward to explain the well-replicated "jumping to conclusions" (JTC) bias in psychosis, particularly in patients with paranoid symptoms. According to this account, schizophrenia patients rest their decisions on lower subjective probability estimates. The initial formulation of the LA account also predicts an absence of the JTC bias under high task ambiguity (i.e., if more than one response option surpasses the subjective acceptance threshold). Schizophrenia patients (n = 62) with current or former delusions and healthy controls (n = 30) were compared on six scenarios of a variant of the beads task paradigm. Decision-making was assessed under low and high task ambiguity. Along with decision judgments (optional), participants were required to provide probability estimates for each option in order to determine decision thresholds (i.e., the probability the individual deems sufficient for a decision). In line with the LA account, schizophrenia patients showed a lowered decision threshold compared to controls (82% vs. 93%) which predicted both more errors and less draws to decisions. Group differences on thresholds were comparable across conditions. At the same time, patients did not show hasty decision-making, reflecting overall lowered probability estimates in patients. Results confirm core predictions derived from the LA account. Our results may (partly) explain why hasty decision-making is sometimes aggravated and sometimes abolished in psychosis. The proneness to make risky decisions may contribute to the pathogenesis of psychosis. A revised LA account is put forward.

Seasonality in communication and collective decision-making in ants.

PubMed

Stroeymeyt, N; Jordan, C; Mayer, G; Hovsepian, S; Giurfa, M; Franks, N R

2014-04-07

The ability of animals to adjust their behaviour according to seasonal changes in their ecology is crucial for their fitness. Eusocial insects display strong collective behavioural seasonality, yet the mechanisms underlying such changes are poorly understood. We show that nest preference by emigrating Temnothorax albipennis ant colonies is influenced by a season-specific modulatory pheromone that may help tune decision-making according to seasonal constraints. The modulatory pheromone triggers aversion towards low-quality nests and enhances colony cohesion in summer and autumn, but not after overwintering-in agreement with reports that field colonies split in spring and reunite in summer. Interestingly, we show that the pheromone acts by downgrading the perceived value of marked nests by informed and naive individuals. This contrasts with theories of collective intelligence, stating that accurate collective decision-making requires independent evaluation of options by individuals. The violation of independence highlighted here was accordingly shown to increase error rate during emigrations. However, this is counterbalanced by enhanced cohesion and the transmission of valuable information through the colony. Our results support recent claims that optimal decisions are not necessarily those that maximize accuracy. Other criteria-such as cohesion or reward rate-may be more relevant in animal decision-making.

Evaluating physician performance at individualizing care: a pilot study tracking contextual errors in medical decision making.

PubMed

Weiner, Saul J; Schwartz, Alan; Yudkowsky, Rachel; Schiff, Gordon D; Weaver, Frances M; Goldberg, Julie; Weiss, Kevin B

2007-01-01

Clinical decision making requires 2 distinct cognitive skills: the ability to classify patients' conditions into diagnostic and management categories that permit the application of research evidence and the ability to individualize or-more specifically-to contextualize care for patients whose circumstances and needs require variation from the standard approach to care. The purpose of this study was to develop and test a methodology for measuring physicians' performance at contextualizing care and compare it to their performance at planning biomedically appropriate care. First, the authors drafted 3 cases, each with 4 variations, 3 of which are embedded with biomedical and/or contextual information that is essential to planning care. Once the cases were validated as instruments for assessing physician performance, 54 internal medicine residents were then presented with opportunities to make these preidentified biomedical or contextual errors, and data were collected on information elicitation and error making. The case validation process was successful in that, in the final iteration, the physicians who received the contextual variant of cases proposed an alternate plan of care to those who received the baseline variant 100% of the time. The subsequent piloting of these validated cases unmasked previously unmeasured differences in physician performance at contextualizing care. The findings, which reflect the performance characteristics of the study population, are presented. This pilot study demonstrates a methodology for measuring physician performance at contextualizing care and illustrates the contribution of such information to an overall assessment of physician practice.

Abstraction of an Affective-Cognitive Decision Making Model Based on Simulated Behaviour and Perception Chains

NASA Astrophysics Data System (ADS)

Sharpanskykh, Alexei; Treur, Jan

Employing rich internal agent models of actors in large-scale socio-technical systems often results in scalability issues. The problem addressed in this paper is how to improve computational properties of a complex internal agent model, while preserving its behavioral properties. The problem is addressed for the case of an existing affective-cognitive decision making model instantiated for an emergency scenario. For this internal decision model an abstracted behavioral agent model is obtained, which ensures a substantial increase of the computational efficiency at the cost of approximately 1% behavioural error. The abstraction technique used can be applied to a wide range of internal agent models with loops, for example, involving mutual affective-cognitive interactions.

Different profiles of decision making and physiology under varying levels of stress in trained military personnel.

PubMed

Gamble, Katherine R; Vettel, Jean M; Patton, Debra J; Eddy, Marianna D; Caroline Davis, F; Garcia, Javier O; Spangler, Derek P; Thayer, Julian F; Brooks, Justin R

2018-03-23

Decision making is one of the most vital processes we use every day, ranging from mundane decisions about what to eat to life-threatening choices such as how to avoid a car collision. Thus, the context in which our decisions are made is critical, and our physiology enables adaptive responses that account for how environmental stress influences our performance. The relationship between stress and decision making can additionally be affected by one's expertise in making decisions in high-threat environments, where experts can develop an adaptive response that mitigates the negative impacts of stress. In the present study, 26 male military personnel made friend/foe discriminations in an environment where we manipulated the level of stress. In the high-stress condition, participants received a shock when they incorrectly shot a friend or missed shooting a foe; in the low-stress condition, participants received a vibration for an incorrect decision. We characterized performance using signal detection theory to investigate whether a participant changed their decision criterion to avoid making an error. Results showed that under high-stress, participants made more false alarms, mistaking friends as foes, and this co-occurred with increased high frequency heart rate variability. Finally, we examined the relationship between decision making and physiology, and found that participants exhibited adaptive behavioral and physiological profiles under different stress levels. We interpret this adaptive profile as a marker of an expert's ingrained training that does not require top down control, suggesting a way that expert training in high-stress environments helps to buffer negative impacts of stress on performance. Published by Elsevier B.V.

Trial-to-trial adjustments of speed-accuracy trade-offs in premotor and primary motor cortex

PubMed Central

Guberman, Guido; Cisek, Paul

2016-01-01

Recent studies have shown that activity in sensorimotor structures varies depending on the speed-accuracy trade-off (SAT) context in which a decision is made. Here we tested the hypothesis that the same areas also reflect a more local adjustment of SAT established between individual trials, based on the outcome of the previous decision. Two monkeys performed a reaching decision task in which sensory evidence continuously evolves during the time course of a trial. In two SAT contexts, we compared neural activity in trials following a correct choice vs. those following an error. In dorsal premotor cortex (PMd), we found that 23% of cells exhibited significantly weaker baseline activity after error trials, and for ∼30% of these this effect persisted into the deliberation epoch. These cells also contributed to the process of combining sensory evidence with the growing urgency to commit to a choice. We also found that the activity of 22% of PMd cells was increased after error trials. These neurons appeared to carry less information about sensory evidence and time-dependent urgency. For most of these modulated cells, the effect was independent of whether the previous error was expected or unexpected. We found similar phenomena in primary motor cortex (M1), with 25% of cells decreasing and 34% increasing activity after error trials, but unlike PMd, these neurons showed less clear differences in their response properties. These findings suggest that PMd and M1 belong to a network of brain areas involved in SAT adjustments established using the recent history of reinforcement. NEW & NOTEWORTHY Setting the speed-accuracy trade-off (SAT) is crucial for efficient decision making. Previous studies have reported that subjects adjust their SAT after individual decisions, usually choosing more conservatively after errors, but the neural correlates of this phenomenon are only partially known. Here, we show that neurons in PMd and M1 of monkeys performing a reach decision task support this mechanism by adequately modulating their firing rate as a function of the outcome of the previous decision. PMID:27852735

Decision Making for Borderline Cases in Pass/Fail Clinical Anatomy Courses: The Practical Value of the Standard Error of Measurement and Likelihood Ratio in a Diagnostic Test

ERIC Educational Resources Information Center

Severo, Milton; Silva-Pereira, Fernanda; Ferreira, Maria Amelia

2013-01-01

Several studies have shown that the standard error of measurement (SEM) can be used as an additional “safety net” to reduce the frequency of false-positive or false-negative student grading classifications. Practical examinations in clinical anatomy are often used as diagnostic tests to admit students to course final examinations. The aim of this…

Cognitive Task Analysis of Business Jet Pilots' Weather Flying Behaviors: Preliminary Results

NASA Technical Reports Server (NTRS)

Latorella, Kara; Pliske, Rebecca; Hutton, Robert; Chrenka, Jason

2001-01-01

This report presents preliminary findings from a cognitive task analysis (CTA) of business aviation piloting. Results describe challenging weather-related aviation decisions and the information and cues used to support these decisions. Further, these results demonstrate the role of expertise in business aviation decision-making in weather flying, and how weather information is acquired and assessed for reliability. The challenging weather scenarios and novice errors identified in the results provide the basis for experimental scenarios and dependent measures to be used in future flight simulation evaluations of candidate aviation weather information systems. Finally, we analyzed these preliminary results to recommend design and training interventions to improve business aviation decision-making with weather information. The primary objective of this report is to present these preliminary findings and to document the extended CTA methodology used to elicit and represent expert business aviator decision-making with weather information. These preliminary findings will be augmented with results from additional subjects using this methodology. A summary of the complete results, absent the detailed treatment of methodology provided in this report, will be documented in a separate publication.

The Reduction of Ventrolateral Prefrontal Cortex Gray Matter Volume Correlates with Loss of Economic Rationality in Aging.

PubMed

Chung, Hui-Kuan; Tymula, Agnieszka; Glimcher, Paul

2017-12-06

The population of people above 65 years old continues to grow, and there is mounting evidence that as humans age they are more likely to make errors. However, the specific effect of neuroanatomical aging on the efficiency of economic decision-making is poorly understood. We used whole-brain voxel-based morphometry analysis to determine where reduction of gray matter volume in healthy female and male adults over the age of 65 years correlates with a classic measure of economic irrationality: violations of the Generalized Axiom of Revealed Preference. All participants were functionally normal with Mini-Mental State Examination scores ranging between 26 and 30. While our elders showed the previously reported decline in rationality compared with younger subjects, chronological age per se did not correlate with rationality measures within our population of elders. Instead, reduction of gray matter density in ventrolateral prefrontal cortex correlates tightly with irrational behavior. Interestingly, using a large fMRI sample and meta-analytic tool with Neurosynth, we found that this brain area shows strong coactivation patterns with nearly all of the value-associated regions identified in previous studies. These findings point toward a neuroanatomic locus for economic rationality in the aging brain and highlight the importance of understanding both anatomy and function in the study of aging, cognition, and decision-making. SIGNIFICANCE STATEMENT Age is a crucial factor in decision-making, with older individuals making more errors in choices. Using whole-brain voxel-based morphometry analysis, we found that reduction of gray matter density in ventrolateral prefrontal cortex correlates with economic irrationality: reduced gray matter volume in this area correlates with the frequency and severity of violations of the Generalized Axiom of Revealed Preference. Furthermore, this brain area strongly coactivates with other reward-associated regions identified with Neurosynth. These findings point toward a role for neuroscientific discoveries in shaping long-standing economic views of decision-making. Copyright © 2017 the authors 0270-6474/17/3712068-10$15.00/0.

The Reduction of Ventrolateral Prefrontal Cortex Gray Matter Volume Correlates with Loss of Economic Rationality in Aging

PubMed Central

Tymula, Agnieszka

2017-01-01

The population of people above 65 years old continues to grow, and there is mounting evidence that as humans age they are more likely to make errors. However, the specific effect of neuroanatomical aging on the efficiency of economic decision-making is poorly understood. We used whole-brain voxel-based morphometry analysis to determine where reduction of gray matter volume in healthy female and male adults over the age of 65 years correlates with a classic measure of economic irrationality: violations of the Generalized Axiom of Revealed Preference. All participants were functionally normal with Mini-Mental State Examination scores ranging between 26 and 30. While our elders showed the previously reported decline in rationality compared with younger subjects, chronological age per se did not correlate with rationality measures within our population of elders. Instead, reduction of gray matter density in ventrolateral prefrontal cortex correlates tightly with irrational behavior. Interestingly, using a large fMRI sample and meta-analytic tool with Neurosynth, we found that this brain area shows strong coactivation patterns with nearly all of the value-associated regions identified in previous studies. These findings point toward a neuroanatomic locus for economic rationality in the aging brain and highlight the importance of understanding both anatomy and function in the study of aging, cognition, and decision-making. SIGNIFICANCE STATEMENT Age is a crucial factor in decision-making, with older individuals making more errors in choices. Using whole-brain voxel-based morphometry analysis, we found that reduction of gray matter density in ventrolateral prefrontal cortex correlates with economic irrationality: reduced gray matter volume in this area correlates with the frequency and severity of violations of the Generalized Axiom of Revealed Preference. Furthermore, this brain area strongly coactivates with other reward-associated regions identified with Neurosynth. These findings point toward a role for neuroscientific discoveries in shaping long-standing economic views of decision-making. PMID:28982708

Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease.

PubMed

Vassena, Eliana; Deraeve, James; Alexander, William H

2017-10-01

Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO model based on hierarchical error prediction, developed to explain MPFC-DLPFC interactions. We derive behavioral predictions that describe how effort and reward information is coded in PFC and how changing the configuration of such environmental information might affect decision-making and task performance involving motivation.

Context is everything or how could I have been that stupid?

PubMed

Croskerry, Pat

2009-01-01

Dual Process Theory provides a useful working model of decision-making. It broadly divides decision-making into intuitive (System 1) and analytical (System 2) processes. System 1 is especially dependent on contextual cues. There appears to be a universal human tendency to contextualize information, mostly in an effort to imbue meaning but also, perhaps, to conserve cognitive energy. Most decision errors occur in System 1, and this has two major implications. The first is that insufficient account may have been taken out of context when the original decision was made. Secondly, in trying to learn from decision failures, we need the highest fidelity of context reconstruction as possible. It should be appreciated that learning from past events is inevitably an imperfect process. Retrospective investigations, such as root-cause analysis, critical incident review, morbidity and mortality rounds and legal investigations, all suffer the limitation that they cannot faithfully reconstruct the context in which decisions were made and from which actions followed.

Impaired Expected Value Computations Coupled With Overreliance on Stimulus-Response Learning in Schizophrenia.

PubMed

Hernaus, Dennis; Gold, James M; Waltz, James A; Frank, Michael J

2018-04-03

While many have emphasized impaired reward prediction error signaling in schizophrenia, multiple studies suggest that some decision-making deficits may arise from overreliance on stimulus-response systems together with a compromised ability to represent expected value. Guided by computational frameworks, we formulated and tested two scenarios in which maladaptive representations of expected value should be most evident, thereby delineating conditions that may evoke decision-making impairments in schizophrenia. In a modified reinforcement learning paradigm, 42 medicated people with schizophrenia and 36 healthy volunteers learned to select the most frequently rewarded option in a 75-25 pair: once when presented with a more deterministic (90-10) pair and once when presented with a more probabilistic (60-40) pair. Novel and old combinations of choice options were presented in a subsequent transfer phase. Computational modeling was employed to elucidate contributions from stimulus-response systems (actor-critic) and expected value (Q-learning). People with schizophrenia showed robust performance impairments with increasing value difference between two competing options, which strongly correlated with decreased contributions from expected value-based learning (Q-learning). Moreover, a subtle yet consistent contextual choice bias for the probabilistic 75 option was present in people with schizophrenia, which could be accounted for by a context-dependent reward prediction error in the actor-critic. We provide evidence that decision-making impairments in schizophrenia increase monotonically with demands placed on expected value computations. A contextual choice bias is consistent with overreliance on stimulus-response learning, which may signify a deficit secondary to the maladaptive representation of expected value. These results shed new light on conditions under which decision-making impairments may arise. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Credit assignment in movement-dependent reinforcement learning

PubMed Central

Boggess, Matthew J.; Crossley, Matthew J.; Parvin, Darius; Ivry, Richard B.; Taylor, Jordan A.

2016-01-01

When a person fails to obtain an expected reward from an object in the environment, they face a credit assignment problem: Did the absence of reward reflect an extrinsic property of the environment or an intrinsic error in motor execution? To explore this problem, we modified a popular decision-making task used in studies of reinforcement learning, the two-armed bandit task. We compared a version in which choices were indicated by key presses, the standard response in such tasks, to a version in which the choices were indicated by reaching movements, which affords execution failures. In the key press condition, participants exhibited a strong risk aversion bias; strikingly, this bias reversed in the reaching condition. This result can be explained by a reinforcement model wherein movement errors influence decision-making, either by gating reward prediction errors or by modifying an implicit representation of motor competence. Two further experiments support the gating hypothesis. First, we used a condition in which we provided visual cues indicative of movement errors but informed the participants that trial outcomes were independent of their actual movements. The main result was replicated, indicating that the gating process is independent of participants’ explicit sense of control. Second, individuals with cerebellar degeneration failed to modulate their behavior between the key press and reach conditions, providing converging evidence of an implicit influence of movement error signals on reinforcement learning. These results provide a mechanistically tractable solution to the credit assignment problem. PMID:27247404

Credit assignment in movement-dependent reinforcement learning.

PubMed

McDougle, Samuel D; Boggess, Matthew J; Crossley, Matthew J; Parvin, Darius; Ivry, Richard B; Taylor, Jordan A

2016-06-14

When a person fails to obtain an expected reward from an object in the environment, they face a credit assignment problem: Did the absence of reward reflect an extrinsic property of the environment or an intrinsic error in motor execution? To explore this problem, we modified a popular decision-making task used in studies of reinforcement learning, the two-armed bandit task. We compared a version in which choices were indicated by key presses, the standard response in such tasks, to a version in which the choices were indicated by reaching movements, which affords execution failures. In the key press condition, participants exhibited a strong risk aversion bias; strikingly, this bias reversed in the reaching condition. This result can be explained by a reinforcement model wherein movement errors influence decision-making, either by gating reward prediction errors or by modifying an implicit representation of motor competence. Two further experiments support the gating hypothesis. First, we used a condition in which we provided visual cues indicative of movement errors but informed the participants that trial outcomes were independent of their actual movements. The main result was replicated, indicating that the gating process is independent of participants' explicit sense of control. Second, individuals with cerebellar degeneration failed to modulate their behavior between the key press and reach conditions, providing converging evidence of an implicit influence of movement error signals on reinforcement learning. These results provide a mechanistically tractable solution to the credit assignment problem.

Visual anticipation biases conscious decision making but not bottom-up visual processing

PubMed Central

Mathews, Zenon; Cetnarski, Ryszard; Verschure, Paul F. M. J.

2015-01-01

Prediction plays a key role in control of attention but it is not clear which aspects of prediction are most prominent in conscious experience. An evolving view on the brain is that it can be seen as a prediction machine that optimizes its ability to predict states of the world and the self through the top-down propagation of predictions and the bottom-up presentation of prediction errors. There are competing views though on whether prediction or prediction errors dominate the formation of conscious experience. Yet, the dynamic effects of prediction on perception, decision making and consciousness have been difficult to assess and to model. We propose a novel mathematical framework and a psychophysical paradigm that allows us to assess both the hierarchical structuring of perceptual consciousness, its content and the impact of predictions and/or errors on conscious experience, attention and decision-making. Using a displacement detection task combined with reverse correlation, we reveal signatures of the usage of prediction at three different levels of perceptual processing: bottom-up fast saccades, top-down driven slow saccades and consciousnes decisions. Our results suggest that the brain employs multiple parallel mechanism at different levels of perceptual processing in order to shape effective sensory consciousness within a predicted perceptual scene. We further observe that bottom-up sensory and top-down predictive processes can be dissociated through cognitive load. We propose a probabilistic data association model from dynamical systems theory to model the predictive multi-scale bias in perceptual processing that we observe and its role in the formation of conscious experience. We propose that these results support the hypothesis that consciousness provides a time-delayed description of a task that is used to prospectively optimize real time control structures, rather than being engaged in the real-time control of behavior itself. PMID:25741290

Observing Reasonable Consumers.

ERIC Educational Resources Information Center

Silber, Norman I.

1991-01-01

Although courts and legislators usually set legal standards that correspond to empirical knowledge of human behavior, recent developments in behavioral psychology have led courts to appreciate the limits and errors in consumer decision making. "Reasonable consumer" standards that are congruent with cognitive reality should be developed.…

Married women's decision making power on family planning use and associated factors in Mizan-Aman, South Ethiopia: a cross sectional study.

PubMed

Belay, Abeba Daniel; Mengesha, Zelalem Birhanu; Woldegebriel, Manay Kifle; Gelaw, Yalemzewod Assefa

2016-03-08

Women's use of family planning service is influenced by many factors, especially by their decision making power. A woman's decision-making power, be it individual or decision made in collaboration with a partner, is the most important factor in the use of family planning in a household. The purpose of this study was to assess the impact of women's decision making power on family planning use and its associated factors. A community-based cross-sectional study was conducted on married women in the child bearing age. The women who were living in Mizan city were selected using the simple random sampling method. Trained nurses collected the data by interview, using a structured and pre-tested questioner. Bivariable and multivariable binary logistic regression analysis was used to identify the associated factors, and the odds ratio with a 95% CI was computed to assess the strength of the association. Collinearity was also assessed by looking at standard errors in the final fitted model. Overall, more than two-thirds [67.2%: 95% CI (63-71%)] of the married women were found to be more autonomous to decide family planning use. Secondary education [AOR: 9.04, 95% CI: (4.50, 18.16)], government employment [AOR: 4.84, 95% CI: (2.03, 11.52)], being wives of government employed spouses [AOR 2.71, 95% CI: (1.24, 7.97)], having husbands with college or university education [AOR: 11.29, 95% CI: (4.66, 27.35)], and being in the younger age [AOR: 0.27, 95% CI :(0.09, 0.75)] were significantly associated with women's decision-making power on family planning. In this study, women had a high decision making power in family planning use. Age category (34-44-years), formal education, and occupational status had effects on women's decision making power. Promoting parental adult education and engaging women in out of house employment is essential to improve their decision making power in using family planning.

Lee as Critical Thinker: The Example of the Gettysburg Campaign

DTIC Science & Technology

2012-05-04

well as what should have been done if the critical thinking process had been conducted appropriately. Conclusion: Several human and military...of reasoning that make up the cognitive decision making process .6 The critical thinking elements of the model (Clarify Concern, Point of View...Finally, there are three remaining biases, traps, and errors that can negatively affect the critical thinking process . A confirmation trap describes

Model-based influences on humans’ choices and striatal prediction errors

PubMed Central

Daw, Nathaniel D.; Gershman, Samuel J.; Seymour, Ben; Dayan, Peter; Dolan, Raymond J.

2011-01-01

Summary The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. PMID:21435563

The role of the insula in intuitive expert bug detection in computer code: an fMRI study.

PubMed

Castelhano, Joao; Duarte, Isabel C; Ferreira, Carlos; Duraes, Joao; Madeira, Henrique; Castelo-Branco, Miguel

2018-05-09

Software programming is a complex and relatively recent human activity, involving the integration of mathematical, recursive thinking and language processing. The neural correlates of this recent human activity are still poorly understood. Error monitoring during this type of task, requiring the integration of language, logical symbol manipulation and other mathematical skills, is particularly challenging. We therefore aimed to investigate the neural correlates of decision-making during source code understanding and mental manipulation in professional participants with high expertise. The present fMRI study directly addressed error monitoring during source code comprehension, expert bug detection and decision-making. We used C code, which triggers the same sort of processing irrespective of the native language of the programmer. We discovered a distinct role for the insula in bug monitoring and detection and a novel connectivity pattern that goes beyond the expected activation pattern evoked by source code understanding in semantic language and mathematical processing regions. Importantly, insula activity levels were critically related to the quality of error detection, involving intuition, as signalled by reported initial bug suspicion, prior to final decision and bug detection. Activity in this salience network (SN) region evoked by bug suspicion was predictive of bug detection precision, suggesting that it encodes the quality of the behavioral evidence. Connectivity analysis provided evidence for top-down circuit "reutilization" stemming from anterior cingulate cortex (BA32), a core region in the SN that evolved for complex error monitoring such as required for this type of recent human activity. Cingulate (BA32) and anterolateral (BA10) frontal regions causally modulated decision processes in the insula, which in turn was related to activity of math processing regions in early parietal cortex. In other words, earlier brain regions used during evolution for other functions seem to be reutilized in a top-down manner for a new complex function, in an analogous manner as described for other cultural creations such as reading and literacy.

Detection of digital FSK using a phase-locked loop

NASA Technical Reports Server (NTRS)

Lindsey, W. C.; Simon, M. K.

1975-01-01

A theory is presented for the design of a digital FSK receiver which employs a phase-locked loop to set up the desired matched filter as the arriving signal frequency switches. The developed mathematical model makes it possible to establish the error probability performance of systems which employ a class of digital FM modulations. The noise mechanism which accounts for decision errors is modeled on the basis of the Meyr distribution and renewal Markov process theory.

Abnormal decision-making in generalized anxiety disorder: Aversion of risk or stimulus-reinforcement impairment?

PubMed

Teng, Cindy; Otero, Marcela; Geraci, Marilla; Blair, R J R; Pine, Daniel S; Grillon, Christian; Blair, Karina S

2016-03-30

There is preliminary data indicating that patients with generalized anxiety disorder (GAD) show impairment on decision-making tasks requiring the appropriate representation of reinforcement value. The current study aimed to extend this literature using the passive avoidance (PA) learning task, where the participant has to learn to respond to stimuli that engender reward and avoid responding to stimuli that engender punishment. Six stimuli engendering reward and six engendering punishment are presented once per block for 10 blocks of trials. Thirty-nine medication-free patients with GAD and 29 age-, IQ and gender matched healthy comparison individuals performed the task. In addition, indexes of social functioning as assessed by the Global Assessment of Functioning (GAF) scale were obtained to allow for correlational analyzes of potential relations between cognitive and social impairments. The results revealed a Group-by-Error Type-by-Block interaction; patients with GAD committed significantly more commission (passive avoidance) errors than comparison individuals in the later blocks (blocks 7,8, and 9). In addition, the extent of impairment on these blocks was associated with their functional impairment as measured by the GAF scale. These results link GAD with anomalous decision-making and indicate that a potential problem in reinforcement representation may contribute to the severity of expression of their disorder. Copyright © 2016. Published by Elsevier Ireland Ltd.

"An integrative formal model of motivation and decision making: The MGPM*": Correction to Ballard et al. (2016).

PubMed

2017-02-01

Reports an error in "An integrative formal model of motivation and decision making: The MGPM*" by Timothy Ballard, Gillian Yeo, Shayne Loft, Jeffrey B. Vancouver and Andrew Neal ( Journal of Applied Psychology , 2016[Sep], Vol 101[9], 1240-1265). Equation A3 contained an error. This correct equation is provided in the erratum. (The following abstract of the original article appeared in record 2016-28692-001.) We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Jumping to the wrong conclusions? An investigation of the mechanisms of reasoning errors in delusions.

PubMed

Jolley, Suzanne; Thompson, Claire; Hurley, James; Medin, Evelina; Butler, Lucy; Bebbington, Paul; Dunn, Graham; Freeman, Daniel; Fowler, David; Kuipers, Elizabeth; Garety, Philippa

2014-10-30

Understanding how people with delusions arrive at false conclusions is central to the refinement of cognitive behavioural interventions. Making hasty decisions based on limited data ('jumping to conclusions', JTC) is one potential causal mechanism, but reasoning errors may also result from other processes. In this study, we investigated the correlates of reasoning errors under differing task conditions in 204 participants with schizophrenia spectrum psychosis who completed three probabilistic reasoning tasks. Psychotic symptoms, affect, and IQ were also evaluated. We found that hasty decision makers were more likely to draw false conclusions, but only 37% of their reasoning errors were consistent with the limited data they had gathered. The remainder directly contradicted all the presented evidence. Reasoning errors showed task-dependent associations with IQ, affect, and psychotic symptoms. We conclude that limited data-gathering contributes to false conclusions but is not the only mechanism involved. Delusions may also be maintained by a tendency to disregard evidence. Low IQ and emotional biases may contribute to reasoning errors in more complex situations. Cognitive strategies to reduce reasoning errors should therefore extend beyond encouragement to gather more data, and incorporate interventions focused directly on these difficulties. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Conflict Resolution as Near-Threshold Decision-Making: A Spiking Neural Circuit Model with Two-Stage Competition for Antisaccadic Task

PubMed Central

Wang, Xiao-Jing

2016-01-01

Automatic responses enable us to react quickly and effortlessly, but they often need to be inhibited so that an alternative, voluntary action can take place. To investigate the brain mechanism of controlled behavior, we investigated a biologically-based network model of spiking neurons for inhibitory control. In contrast to a simple race between pro- versus anti-response, our model incorporates a sensorimotor remapping module, and an action-selection module endowed with a “Stop” process through tonic inhibition. Both are under the modulation of rule-dependent control. We tested the model by applying it to the well known antisaccade task in which one must suppress the urge to look toward a visual target that suddenly appears, and shift the gaze diametrically away from the target instead. We found that the two-stage competition is crucial for reproducing the complex behavior and neuronal activity observed in the antisaccade task across multiple brain regions. Notably, our model demonstrates two types of errors: fast and slow. Fast errors result from failing to inhibit the quick automatic responses and therefore exhibit very short response times. Slow errors, in contrast, are due to incorrect decisions in the remapping process and exhibit long response times comparable to those of correct antisaccade responses. The model thus reveals a circuit mechanism for the empirically observed slow errors and broad distributions of erroneous response times in antisaccade. Our work suggests that selecting between competing automatic and voluntary actions in behavioral control can be understood in terms of near-threshold decision-making, sharing a common recurrent (attractor) neural circuit mechanism with discrimination in perception. PMID:27551824

Conflict Resolution as Near-Threshold Decision-Making: A Spiking Neural Circuit Model with Two-Stage Competition for Antisaccadic Task.

PubMed

Lo, Chung-Chuan; Wang, Xiao-Jing

2016-08-01

Automatic responses enable us to react quickly and effortlessly, but they often need to be inhibited so that an alternative, voluntary action can take place. To investigate the brain mechanism of controlled behavior, we investigated a biologically-based network model of spiking neurons for inhibitory control. In contrast to a simple race between pro- versus anti-response, our model incorporates a sensorimotor remapping module, and an action-selection module endowed with a "Stop" process through tonic inhibition. Both are under the modulation of rule-dependent control. We tested the model by applying it to the well known antisaccade task in which one must suppress the urge to look toward a visual target that suddenly appears, and shift the gaze diametrically away from the target instead. We found that the two-stage competition is crucial for reproducing the complex behavior and neuronal activity observed in the antisaccade task across multiple brain regions. Notably, our model demonstrates two types of errors: fast and slow. Fast errors result from failing to inhibit the quick automatic responses and therefore exhibit very short response times. Slow errors, in contrast, are due to incorrect decisions in the remapping process and exhibit long response times comparable to those of correct antisaccade responses. The model thus reveals a circuit mechanism for the empirically observed slow errors and broad distributions of erroneous response times in antisaccade. Our work suggests that selecting between competing automatic and voluntary actions in behavioral control can be understood in terms of near-threshold decision-making, sharing a common recurrent (attractor) neural circuit mechanism with discrimination in perception.

Double dissociation of value computations in orbitofrontal and anterior cingulate neurons

PubMed Central

Kennerley, Steven W.; Behrens, Timothy E. J.; Wallis, Jonathan D.

2011-01-01

Damage to prefrontal cortex (PFC) impairs decision-making, but the underlying value computations that might cause such impairments remain unclear. Here we report that value computations are doubly dissociable within PFC neurons. While many PFC neurons encoded chosen value, they used opponent encoding schemes such that averaging the neuronal population eliminated value coding. However, a special population of neurons in anterior cingulate cortex (ACC) - but not orbitofrontal cortex (OFC) - multiplex chosen value across decision parameters using a unified encoding scheme, and encoded reward prediction errors. In contrast, neurons in OFC - but not ACC - encoded chosen value relative to the recent history of choice values. Together, these results suggest complementary valuation processes across PFC areas: OFC neurons dynamically evaluate current choices relative to recent choice values, while ACC neurons encode choice predictions and prediction errors using a common valuation currency reflecting the integration of multiple decision parameters. PMID:22037498

Human Factors Effecting Forensic Decision Making: Workplace Stress and Well-being.

PubMed

Jeanguenat, Amy M; Dror, Itiel E

2018-01-01

Over the past decade, there has been a growing openness about the importance of human factors in forensic work. However, most of it focused on cognitive bias, and neglected issues of workplace wellness and stress. Forensic scientists work in a dynamic environment that includes common workplace pressures such as workload volume, tight deadlines, lack of advancement, number of working hours, low salary, technology distractions, and fluctuating priorities. However, in addition, forensic scientists also encounter a number of industry-specific pressures, such as technique criticism, repeated exposure to crime scenes or horrific case details, access to funding, working in an adversarial legal system, and zero tolerance for "errors". Thus, stress is an important human factor to mitigate for overall error management, productivity and decision quality (not to mention the well-being of the examiners themselves). Techniques such as mindfulness can become powerful tools to enhance work and decision quality. © 2017 American Academy of Forensic Sciences.

Higher incentives can impair performance: neural evidence on reinforcement and rationality.

PubMed

Achtziger, Anja; Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Steinhauser, Marco

2015-11-01

Standard economic thinking postulates that increased monetary incentives should increase performance. Human decision makers, however, frequently focus on past performance, a form of reinforcement learning occasionally at odds with rational decision making. We used an incentivized belief-updating task from economics to investigate this conflict through measurements of neural correlates of reward processing. We found that higher incentives fail to improve performance when immediate feedback on decision outcomes is provided. Subsequent analysis of the feedback-related negativity, an early event-related potential following feedback, revealed the mechanism behind this paradoxical effect. As incentives increase, the win/lose feedback becomes more prominent, leading to an increased reliance on reinforcement and more errors. This mechanism is relevant for economic decision making and the debate on performance-based payment. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Systematic Review of Medical Informatics-Supported Medication Decision Making.

PubMed

Melton, Brittany L

2017-01-01

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Most studies examined decision support systems as a means of reducing errors or risk, particularly associated with medication prescribing, whereas a few studies evaluated the impact medical informatics-based decision support systems have on workflow or operations efficiency. Most studies identified benefits associated with decision support systems, but some indicate there is room for improvement.

Developing a Corrective Action Simulator to Support Decision Making Research and Training

DTIC Science & Technology

2008-05-01

positions, and any time-based simulation injects (e.g., JSTARS reporting tracks, the Engineer reporting a new aircraft bingo time, a threat being active...future instantiations would benefit from migrating to the IMPRINT Pro version. During the course of this development effort the Army Research...initiating corrective action when a subordinate is observed to make an error (of omission or commission) 58 • Benefits of a Corrective

Reduced activation in ventral striatum and ventral tegmental area during probabilistic decision-making in schizophrenia.

PubMed

Rausch, Franziska; Mier, Daniela; Eifler, Sarah; Esslinger, Christine; Schilling, Claudia; Schirmbeck, Frederike; Englisch, Susanne; Meyer-Lindenberg, Andreas; Kirsch, Peter; Zink, Mathias

2014-07-01

Patients with schizophrenia suffer from deficits in monitoring and controlling their own thoughts. Within these so-called metacognitive impairments, alterations in probabilistic reasoning might be one cognitive phenomenon disposing to delusions. However, so far little is known about alterations in associated brain functionality. A previously established task for functional magnetic resonance imaging (fMRI), which requires a probabilistic decision after a variable amount of stimuli, was applied to 23 schizophrenia patients and 28 healthy controls matched for age, gender and educational levels. We compared activation patterns during decision-making under conditions of certainty versus uncertainty and evaluated the process of final decision-making in ventral striatum (VS) and ventral tegmental area (VTA). We replicated a pre-described extended cortical activation pattern during probabilistic reasoning. During final decision-making, activations in several fronto- and parietocortical areas, as well as in VS and VTA became apparent. In both of these regions schizophrenia patients showed a significantly reduced activation. These results further define the network underlying probabilistic decision-making. The observed hypo-activation in regions commonly associated with dopaminergic neurotransmission fits into current concepts of disrupted prediction error signaling in schizophrenia and suggests functional links to reward anticipation. Forthcoming studies with patients at risk for psychosis and drug-naive first episode patients are necessary to elucidate the development of these findings over time and the interplay with associated clinical symptoms. Copyright © 2014 Elsevier B.V. All rights reserved.

Impaired Flexible Reward-Based Decision-Making in Binge Eating Disorder: Evidence from Computational Modeling and Functional Neuroimaging.

PubMed

Reiter, Andrea M F; Heinze, Hans-Jochen; Schlagenhauf, Florian; Deserno, Lorenz

2017-02-01

Despite its clinical relevance and the recent recognition as a diagnostic category in the DSM-5, binge eating disorder (BED) has rarely been investigated from a cognitive neuroscientific perspective targeting a more precise neurocognitive profiling of the disorder. BED patients suffer from a lack of behavioral control during recurrent binge eating episodes and thus fail to adapt their behavior in the face of negative consequences, eg, high risk for obesity. To examine impairments in flexible reward-based decision-making, we exposed BED patients (n=22) and matched healthy individuals (n=22) to a reward-guided decision-making task during functional resonance imaging (fMRI). Performing fMRI analysis informed via computational modeling of choice behavior, we were able to identify specific signatures of altered decision-making in BED. On the behavioral level, we observed impaired behavioral adaptation in BED, which was due to enhanced switching behavior, a putative deficit in striking a balance between exploration and exploitation appropriately. This was accompanied by diminished activation related to exploratory decisions in the anterior insula/ventro-lateral prefrontal cortex. Moreover, although so-called model-free reward prediction errors remained intact, representation of ventro-medial prefrontal learning signatures, incorporating inference on unchosen options, was reduced in BED, which was associated with successful decision-making in the task. On the basis of a computational psychiatry account, the presented findings contribute to defining a neurocognitive phenotype of BED.

Impaired Flexible Reward-Based Decision-Making in Binge Eating Disorder: Evidence from Computational Modeling and Functional Neuroimaging

PubMed Central

Reiter, Andrea M F; Heinze, Hans-Jochen; Schlagenhauf, Florian; Deserno, Lorenz

2017-01-01

Despite its clinical relevance and the recent recognition as a diagnostic category in the DSM-5, binge eating disorder (BED) has rarely been investigated from a cognitive neuroscientific perspective targeting a more precise neurocognitive profiling of the disorder. BED patients suffer from a lack of behavioral control during recurrent binge eating episodes and thus fail to adapt their behavior in the face of negative consequences, eg, high risk for obesity. To examine impairments in flexible reward-based decision-making, we exposed BED patients (n=22) and matched healthy individuals (n=22) to a reward-guided decision-making task during functional resonance imaging (fMRI). Performing fMRI analysis informed via computational modeling of choice behavior, we were able to identify specific signatures of altered decision-making in BED. On the behavioral level, we observed impaired behavioral adaptation in BED, which was due to enhanced switching behavior, a putative deficit in striking a balance between exploration and exploitation appropriately. This was accompanied by diminished activation related to exploratory decisions in the anterior insula/ventro-lateral prefrontal cortex. Moreover, although so-called model-free reward prediction errors remained intact, representation of ventro–medial prefrontal learning signatures, incorporating inference on unchosen options, was reduced in BED, which was associated with successful decision-making in the task. On the basis of a computational psychiatry account, the presented findings contribute to defining a neurocognitive phenotype of BED. PMID:27301429

Efficient decision-making by volume-conserving physical object

NASA Astrophysics Data System (ADS)

Kim, Song-Ju; Aono, Masashi; Nameda, Etsushi

2015-08-01

Decision-making is one of the most important intellectual abilities of not only humans but also other biological organisms, helping their survival. This ability, however, may not be limited to biological systems and may be exhibited by physical systems. Here we demonstrate that any physical object, as long as its volume is conserved when coupled with suitable operations, provides a sophisticated decision-making capability. We consider the multi-armed bandit problem (MBP), the problem of finding, as accurately and quickly as possible, the most profitable option from a set of options that gives stochastic rewards. Efficient MBP solvers are useful for many practical applications, because MBP abstracts a variety of decision-making problems in real-world situations in which an efficient trial-and-error is required. These decisions are made as dictated by a physical object, which is moved in a manner similar to the fluctuations of a rigid body in a tug-of-war (TOW) game. This method, called ‘TOW dynamics’, exhibits higher efficiency than conventional reinforcement learning algorithms. We show analytical calculations that validate statistical reasons for TOW dynamics to produce the high performance despite its simplicity. These results imply that various physical systems in which some conservation law holds can be used to implement an efficient ‘decision-making object’. The proposed scheme will provide a new perspective to open up a physics-based analog computing paradigm and to understanding the biological information-processing principles that exploit their underlying physics.

Misfortune may be a blessing in disguise: Fairness perception and emotion modulate decision making.

PubMed

Liu, Hong-Hsiang; Hwang, Yin-Dir; Hsieh, Ming H; Hsu, Yung-Fong; Lai, Wen-Sung

2017-08-01

Fairness perception and equality during social interactions frequently elicit affective arousal and affect decision making. By integrating the dictator game and a probabilistic gambling task, this study aimed to investigate the effects of a negative experience induced by perceived unfairness on decision making using behavioral, model fitting, and electrophysiological approaches. Participants were randomly assigned to the neutral, harsh, or kind groups, which consisted of various asset allocation scenarios to induce different levels of perceived unfairness. The monetary gain was subsequently considered the initial asset in a negatively rewarded, probabilistic gambling task in which the participants were instructed to maintain as much asset as possible. Our behavioral results indicated that the participants in the harsh group exhibited increased levels of negative emotions but retained greater total game scores than the participants in the other two groups. Parameter estimation of a reinforcement learning model using a Bayesian approach indicated that these participants were more loss aversive and consistent in decision making. Data from simultaneous ERP recordings further demonstrated that these participants exhibited larger feedback-related negativity to unexpected outcomes in the gambling task, which suggests enhanced reward sensitivity and signaling of reward prediction error. Collectively, our study suggests that a negative experience may be an advantage in the modulation of reward-based decision making. © 2017 Society for Psychophysiological Research.

Interfacing to the brain’s motor decisions

PubMed Central

2017-01-01

It has been long known that neural activity, recorded with electrophysiological methods, contains rich information about a subject’s motor intentions, sensory experiences, allocation of attention, action planning, and even abstract thoughts. All these functions have been the subject of neurophysiological investigations, with the goal of understanding how neuronal activity represents behavioral parameters, sensory inputs, and cognitive functions. The field of brain-machine interfaces (BMIs) strives for a somewhat different goal: it endeavors to extract information from neural modulations to create a communication link between the brain and external devices. Although many remarkable successes have been already achieved in the BMI field, questions remain regarding the possibility of decoding high-order neural representations, such as decision making. Could BMIs be employed to decode the neural representations of decisions underlying goal-directed actions? In this review we lay out a framework that describes the computations underlying goal-directed actions as a multistep process performed by multiple cortical and subcortical areas. We then discuss how BMIs could connect to different decision-making steps and decode the neural processing ongoing before movements are initiated. Such decision-making BMIs could operate as a system with prediction that offers many advantages, such as shorter reaction time, better error processing, and improved unsupervised learning. To present the current state of the art, we review several recent BMIs incorporating decision-making components. PMID:28003406

Neuroeconomic measures of social decision-making across the lifespan.

PubMed

Zhu, Lusha; Walsh, Daniel; Hsu, Ming

2012-01-01

Social and decision-making deficits are often the first symptoms of a striking number of neurodegenerative disorders associated with aging. These includes not only disorders that directly impact dopamine and basal ganglia, such as Parkinson's disorder, but also degeneration in which multiple neural pathways are affected over the course of normal aging. The impact of such deficits can be dramatic, as in cases of financial fraud, which disproportionately affect the elderly. Unlike memory and motor impairments, however, which are readily recognized as symptoms of more serious underlying neurological conditions, social and decision-making deficits often do not elicit comparable concern in the elderly. Furthermore, few behavioral measures exist to quantify these deficits, due in part to our limited knowledge of the core cognitive components or their neurobiological substrates. Here we probe age-related differences in decision-making using a game theory paradigm previously shown to dissociate contributions of basal ganglia and prefrontal regions to behavior. Combined with computational modeling, we provide evidence that age-related changes in elderly participants are driven primarily by an over-reliance in trial-and-error reinforcement learning that does not take into account the strategic context, which may underlie cognitive deficits that contribute to social vulnerability in elderly individuals.

Physical mechanism of mind changes and tradeoffs among speed, accuracy, and energy cost in brain decision making: Landscape, flux, and path perspectives

NASA Astrophysics Data System (ADS)

Han, Yan; Kun, Zhang; Jin, Wang

2016-07-01

Cognitive behaviors are determined by underlying neural networks. Many brain functions, such as learning and memory, have been successfully described by attractor dynamics. For decision making in the brain, a quantitative description of global attractor landscapes has not yet been completely given. Here, we developed a theoretical framework to quantify the landscape associated with the steady state probability distributions and associated steady state curl flux, measuring the degree of non-equilibrium through the degree of detailed balance breaking for decision making. We quantified the decision-making processes with optimal paths from the undecided attractor states to the decided attractor states, which are identified as basins of attractions, on the landscape. Both landscape and flux determine the kinetic paths and speed. The kinetics and global stability of decision making are explored by quantifying the landscape topography through the barrier heights and the mean first passage time. Our theoretical predictions are in agreement with experimental observations: more errors occur under time pressure. We quantitatively explored two mechanisms of the speed-accuracy tradeoff with speed emphasis and further uncovered the tradeoffs among speed, accuracy, and energy cost. Our results imply that there is an optimal balance among speed, accuracy, and the energy cost in decision making. We uncovered the possible mechanisms of changes of mind and how mind changes improve performance in decision processes. Our landscape approach can help facilitate an understanding of the underlying physical mechanisms of cognitive processes and identify the key factors in the corresponding neural networks. Project supported by the National Natural Science Foundation of China (Grant Nos. 21190040, 91430217, and 11305176).

Assessing the role of evidence in patients' evaluation of complementary therapies: a quality study.

PubMed

Verhoef, Marja J; Mulkins, Andrea; Carlson, Linda E; Hilsden, Robert J; Kania, Anna

2007-12-01

Making the decision to use complementary and alternative medicine (CAM) for cancer treatment is difficult in light of the limited available evidence for these treatments. It is unclear how patients use evidence to make these decisions. (1) Describe the type of information about CAM that cancer patients use in their decision making; (2) understand why certain types of information about CAM are accepted as evidence by cancer patients; and (3) explore the role of scientific evidence in treatment decision making. A qualitative study design using in-depth semistructured interviews with cancer patients attending 4 conventional and integrative health care institutions in Alberta and British Columbia, Canada, was used. Twenty-seven patients were interviewed. Patients sought CAM information from a range of sources, including the Internet, health care providers, friends, relatives, and newspapers. Many expressed frustration about the overwhelming amount of available information and found it difficult to identify reliable information. Information was described as reliable if it supported them in arriving at a decision about CAM. Types of information participants identified included anecdotes, expert opinion, gut feeling, popular literature, scientific evidence, testimonials, advertising and trial and error. Profound differences were found between new CAM users, experienced CAM users, and users with late-stage cancer in type of information sought, the role of scientific evidence in decision making, and overall information needs. Although this was a relatively small qualitative study, the results suggest that (1) many patients do not value scientific evidence as highly as conventional providers and (2) it is important for clinicians and other information providers to be aware of the different types of information that patients seek out and access when making choices and decisions regarding CAM treatments and why they seek out these sources.

Blocking serotonin but not dopamine reuptake alters neural processing during perceptual decision making.

PubMed

Costa, Vincent D; Kakalios, Laura C; Averbeck, Bruno B

2016-10-01

Dopamine and serotonin have opponent interactions on aspects of impulsivity. Therefore we wanted to test the hypothesis that dopamine and serotonin would have opposing effects on speed-accuracy trade offs in a perceptual decision making task. Unlike other behavioral measures of impulsivity, perceptual decision making allows us to determine whether decreasing premature responses, often interpreted as decreased impulsivity, corresponds to increased behavioral performance. We administered GBR-12909 (a dopamine transporter blocker), escitalopram (a serotonin transporter blocker), or saline in separate sessions to 3 rhesus macaques. We found that animals had slower reaction times (RTs) on escitalopram than on GBR-12909 or saline. However, they were also least accurate on escitalopram. Animals were faster, although nonsignificantly, on GBR than saline and had equivalent accuracy. Administration of GBR-12909 did cause animals to be faster in error trials than correct trials. Therefore, from the point of view of RTs the animals were less impulsive on escitalopram. However, the decreased accuracy of the monkeys shows that they were not able to make use of their slower response times to make more accurate decisions. Therefore, impulsivity was reduced on escitalopram, but at the expense of a slower information-processing rate in the perceptual inference task. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Identification of factors associated with diagnostic error in primary care.

PubMed

Minué, Sergio; Bermúdez-Tamayo, Clara; Fernández, Alberto; Martín-Martín, José Jesús; Benítez, Vivian; Melguizo, Miguel; Caro, Araceli; Orgaz, María José; Prados, Miguel Angel; Díaz, José Enrique; Montoro, Rafael

2014-05-12

Missed, delayed or incorrect diagnoses are considered to be diagnostic errors. The aim of this paper is to describe the methodology of a study to analyse cognitive aspects of the process by which primary care (PC) physicians diagnose dyspnoea. It examines the possible links between the use of heuristics, suboptimal cognitive acts and diagnostic errors, using Reason's taxonomy of human error (slips, lapses, mistakes and violations). The influence of situational factors (professional experience, perceived overwork and fatigue) is also analysed. Cohort study of new episodes of dyspnoea in patients receiving care from family physicians and residents at PC centres in Granada (Spain). With an initial expected diagnostic error rate of 20%, and a sampling error of 3%, 384 episodes of dyspnoea are calculated to be required. In addition to filling out the electronic medical record of the patients attended, each physician fills out 2 specially designed questionnaires about the diagnostic process performed in each case of dyspnoea. The first questionnaire includes questions on the physician's initial diagnostic impression, the 3 most likely diagnoses (in order of likelihood), and the diagnosis reached after the initial medical history and physical examination. It also includes items on the physicians' perceived overwork and fatigue during patient care. The second questionnaire records the confirmed diagnosis once it is reached. The complete diagnostic process is peer-reviewed to identify and classify the diagnostic errors. The possible use of heuristics of representativeness, availability, and anchoring and adjustment in each diagnostic process is also analysed. Each audit is reviewed with the physician responsible for the diagnostic process. Finally, logistic regression models are used to determine if there are differences in the diagnostic error variables based on the heuristics identified. This work sets out a new approach to studying the diagnostic decision-making process in PC, taking advantage of new technologies which allow immediate recording of the decision-making process.

Identification of factors associated with diagnostic error in primary care

PubMed Central

2014-01-01

Background Missed, delayed or incorrect diagnoses are considered to be diagnostic errors. The aim of this paper is to describe the methodology of a study to analyse cognitive aspects of the process by which primary care (PC) physicians diagnose dyspnoea. It examines the possible links between the use of heuristics, suboptimal cognitive acts and diagnostic errors, using Reason’s taxonomy of human error (slips, lapses, mistakes and violations). The influence of situational factors (professional experience, perceived overwork and fatigue) is also analysed. Methods Cohort study of new episodes of dyspnoea in patients receiving care from family physicians and residents at PC centres in Granada (Spain). With an initial expected diagnostic error rate of 20%, and a sampling error of 3%, 384 episodes of dyspnoea are calculated to be required. In addition to filling out the electronic medical record of the patients attended, each physician fills out 2 specially designed questionnaires about the diagnostic process performed in each case of dyspnoea. The first questionnaire includes questions on the physician’s initial diagnostic impression, the 3 most likely diagnoses (in order of likelihood), and the diagnosis reached after the initial medical history and physical examination. It also includes items on the physicians’ perceived overwork and fatigue during patient care. The second questionnaire records the confirmed diagnosis once it is reached. The complete diagnostic process is peer-reviewed to identify and classify the diagnostic errors. The possible use of heuristics of representativeness, availability, and anchoring and adjustment in each diagnostic process is also analysed. Each audit is reviewed with the physician responsible for the diagnostic process. Finally, logistic regression models are used to determine if there are differences in the diagnostic error variables based on the heuristics identified. Discussion This work sets out a new approach to studying the diagnostic decision-making process in PC, taking advantage of new technologies which allow immediate recording of the decision-making process. PMID:24884984

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

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

2017-03-01

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

Conflict Monitoring in Dual Process Theories of Thinking

ERIC Educational Resources Information Center

De Neys, Wim; Glumicic, Tamara

2008-01-01

Popular dual process theories have characterized human thinking as an interplay between an intuitive-heuristic and demanding-analytic reasoning process. Although monitoring the output of the two systems for conflict is crucial to avoid decision making errors there are some widely different views on the efficiency of the process. Kahneman…

Two Philosophical Errors Concerning School Choice.

ERIC Educational Resources Information Center

Brighouse, Harry

1997-01-01

Argues, in contrast to David Hargreaves, that libertarianism implies a mild presumption against school choice, and that notions of common good are significant to educational decision making only when deciding between sets of institutions that perform equally well at delivering their obligations. Links these issues to questions about school choice.…

Exploring cognitive bias in destination therapy left ventricular assist device decision making: A retrospective qualitative framework analysis.

PubMed

Magid, Molly; McIlvennan, Colleen K; Jones, Jaqueline; Nowels, Carolyn T; Allen, Larry A; Thompson, Jocelyn S; Matlock, Dan

2016-10-01

Cognitive biases are psychological influences, which cause humans to make decisions, which do not seemingly maximize utility. For people with heart failure, the left ventricular assist device (LVAD) is a surgically implantable device with complex tradeoffs. As such, it represents an excellent model within which to explore cognitive bias in a real-world decision. We conducted a framework analysis to examine for evidence of cognitive bias among people deciding whether or not to get an LVAD. The aim of this study was to explore the influence of cognitive bias on the LVAD decision-making process. We analyzed previously conducted interviews of patients who had either accepted or declined an LVAD using a deductive, predetermined framework of cognitive biases. We coded and analyzed the interviews using an inductive-deductive framework approach, which also allowed for other themes to emerge. We interviewed a total of 22 heart failure patients who had gone through destination therapy LVAD decision making (15 who had accepted the LVAD and 7 who had declined). All patients appeared influenced by state dependence, where both groups described high current state of suffering, but the groups differed in whether they believed LVAD would relieve suffering or not. We found evidence of cognitive bias that appeared to influence decision making in both patient groups, but groups differed in terms of which cognitive biases were present. Among accepters, we found evidence of anchoring bias, availability bias, optimism bias, and affective forecasting. Among decliners, we found evidence of errors in affective forecasting. Medical decision making is often a complicated and multifaceted process that includes cognitive bias as well as other influences. It is important for clinicians to recognize that patients can be affected by cognitive bias, so they can better understand and improve the decision-making process to ensure that patients are fully informed. Published by Elsevier Inc.

Inertia and Decision Making.

PubMed

Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Li, Jiahui

2016-01-01

Decision inertia is the tendency to repeat previous choices independently of the outcome, which can give rise to perseveration in suboptimal choices. We investigate this tendency in probability-updating tasks. Study 1 shows that, whenever decision inertia conflicts with normatively optimal behavior (Bayesian updating), error rates are larger and decisions are slower. This is consistent with a dual-process view of decision inertia as an automatic process conflicting with a more rational, controlled one. We find evidence of decision inertia in both required and autonomous decisions, but the effect of inertia is more clear in the latter. Study 2 considers more complex decision situations where further conflict arises due to reinforcement processes. We find the same effects of decision inertia when reinforcement is aligned with Bayesian updating, but if the two latter processes conflict, the effects are limited to autonomous choices. Additionally, both studies show that the tendency to rely on decision inertia is positively associated with preference for consistency.

Inertia and Decision Making

PubMed Central

Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Li, Jiahui

2016-01-01

Decision inertia is the tendency to repeat previous choices independently of the outcome, which can give rise to perseveration in suboptimal choices. We investigate this tendency in probability-updating tasks. Study 1 shows that, whenever decision inertia conflicts with normatively optimal behavior (Bayesian updating), error rates are larger and decisions are slower. This is consistent with a dual-process view of decision inertia as an automatic process conflicting with a more rational, controlled one. We find evidence of decision inertia in both required and autonomous decisions, but the effect of inertia is more clear in the latter. Study 2 considers more complex decision situations where further conflict arises due to reinforcement processes. We find the same effects of decision inertia when reinforcement is aligned with Bayesian updating, but if the two latter processes conflict, the effects are limited to autonomous choices. Additionally, both studies show that the tendency to rely on decision inertia is positively associated with preference for consistency. PMID:26909061

Systematic biases in group decision-making: implications for patient safety.

PubMed

Mannion, Russell; Thompson, Carl

2014-12-01

Key decisions in modern health care systems are often made by groups of people rather than lone individuals. However, group decision-making can be imperfect and result in organizational and clinical errors which may harm patients-a fact highlighted graphically in recent (and historical) health scandals and inquiries such as the recent report by Sir Robert Francis into the serious failures in patient care and safety at Mid Staffordshire Hospitals NHS Trust in the English NHS. In this article, we draw on theories from organization studies and decision science to explore the ways in which patient safety may be undermined or threatened in health care contexts as a result of four systematic biases arising from group decision-making: 'groupthink', 'social loafing', 'group polarization' and 'escalation of commitment'. For each group bias, we describe its antecedents, illustrate how it can impair group decisions with regard to patient safety, outline a range of possible remedial organizational strategies that can be used to attenuate the potential for adverse consequences and look forward at the emerging research agenda in this important but hitherto neglected area of patient safety research. © The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

The good doctor: the carer's perspective.

PubMed

Levine, Carol

2004-01-01

Carers are family members, friends, and neighbours who perform medical tasks and personal care, manage housekeeping and financial affairs, and provide emotional support to people who are ill, disabled, or elderly. From a carer's perspective, the primary requisite for a good doctor is competence. Assuming equal technical skills and knowledge, the difference between 'good' and 'bad' doctors comes down to attitudes and behaviour-communication. An important aspect of communication is what doctors say to carers, and how they interpret what carers say to them. Body language-stances, gestures and expression-communicates as well. Good doctors are surrounded by courteous, helpful and efficient assistants. Doctors can make two types of errors in dealing with carers. Type 1 errors occur when doctors exclude the carer from decision making and information. Type 2 errors occur when doctors speak only to the carer and ignore the patient. Good doctors, patients and carers confront the existential meaning of illness together.

Graphical user interface for a neonatal parenteral nutrition decision support system.

PubMed Central

Peverini, R. L.; Beach, D. S.; Wan, K. W.; Vyhmeister, N. R.

2000-01-01

We developed and implemented a decision support system for prescribing parenteral nutrition (PN) solutions for infants in our neonatal intensive care unit. We employed a graphical user interface to provide clinical guidelines and aid the understanding of the interaction among the various ingredients that make up a PN solution. In particular, by displaying the interaction between the PN total solution volume, protein, calcium and phosphorus, we have eliminated PN orders that previously would have resulted in calcium-phosphorus precipitation errors. PMID:11079964

Predicting performance on the Columbia Card Task: effects of personality characteristics, mood, and executive functions.

PubMed

Buelow, Melissa T

2015-04-01

Behavioral measures of risky decision making are frequently used by researchers and clinicians; however, most of these measures are strongly associated with personality characteristics and state mood. The present study sought to examine personality, mood, and executive function predictors of performance on a newer measure of decision making, the Columbia Card Task (CCT). Participants were 489 undergraduate students who completed either the hot or cold version of the CCT as well as measures of state mood, impulsive sensation seeking, behavioral inhibition and activation systems, and executive functions (Wisconsin Card Sort Task; Digit Span). Results indicated that performance on the CCT-cold was predicted by Wisconsin Card Sort Task errors, and Digit Span predicted the CCT-hot. In addition, significant correlations were found between the CCT information use variables and the predictor variables. Implications for the utility of the CCT as a clinical instrument and its relationship with other measures of decision making are discussed. © The Author(s) 2014.

The Psychology of Superorganisms: Collective Decision Making by Insect Societies.

PubMed

Sasaki, Takao; Pratt, Stephen C

2018-01-07

Under the superorganism concept, insect societies are so tightly integrated that they possess features analogous to those of single organisms, including collective cognition. If so, colony function might fruitfully be studied using methods developed to understand individual animals. Here, we review research that uses psychological approaches to understand decision making by colonies. The application of neural models to collective choice shows fundamental similarities between how brains and colonies balance speed/accuracy trade-offs in decision making. Experimental analyses have explored collective rationality, cognitive capacity, and perceptual discrimination at both individual and colony levels. A major theme is the emergence of improved colony-level function from interactions among relatively less capable individuals. However, colonies also encounter performance costs due to their reliance on positive feedback, which generates consensus but can also amplify errors. Collective learning is a nascent field for the further application of psychological methods to colonies. The research strategy reviewed here shows how the superorganism concept can serve as more than an illustrative analogy.

Adaptive error detection for HDR/PDR brachytherapy: Guidance for decision making during real-time in vivo point dosimetry

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

Kertzscher, Gustavo, E-mail: guke@dtu.dk; Andersen, Claus E., E-mail: clan@dtu.dk; Tanderup, Kari, E-mail: karitand@rm.dk

Purpose: This study presents an adaptive error detection algorithm (AEDA) for real-timein vivo point dosimetry during high dose rate (HDR) or pulsed dose rate (PDR) brachytherapy (BT) where the error identification, in contrast to existing approaches, does not depend on an a priori reconstruction of the dosimeter position. Instead, the treatment is judged based on dose rate comparisons between measurements and calculations of the most viable dosimeter position provided by the AEDA in a data driven approach. As a result, the AEDA compensates for false error cases related to systematic effects of the dosimeter position reconstruction. Given its nearly exclusivemore » dependence on stable dosimeter positioning, the AEDA allows for a substantially simplified and time efficient real-time in vivo BT dosimetry implementation. Methods: In the event of a measured potential treatment error, the AEDA proposes the most viable dosimeter position out of alternatives to the original reconstruction by means of a data driven matching procedure between dose rate distributions. If measured dose rates do not differ significantly from the most viable alternative, the initial error indication may be attributed to a mispositioned or misreconstructed dosimeter (false error). However, if the error declaration persists, no viable dosimeter position can be found to explain the error, hence the discrepancy is more likely to originate from a misplaced or misreconstructed source applicator or from erroneously connected source guide tubes (true error). Results: The AEDA applied on twoin vivo dosimetry implementations for pulsed dose rate BT demonstrated that the AEDA correctly described effects responsible for initial error indications. The AEDA was able to correctly identify the major part of all permutations of simulated guide tube swap errors and simulated shifts of individual needles from the original reconstruction. Unidentified errors corresponded to scenarios where the dosimeter position was sufficiently symmetric with respect to error and no-error source position constellations. The AEDA was able to correctly identify all false errors represented by mispositioned dosimeters contrary to an error detection algorithm relying on the original reconstruction. Conclusions: The study demonstrates that the AEDA error identification during HDR/PDR BT relies on a stable dosimeter position rather than on an accurate dosimeter reconstruction, and the AEDA’s capacity to distinguish between true and false error scenarios. The study further shows that the AEDA can offer guidance in decision making in the event of potential errors detected with real-timein vivo point dosimetry.« less

Training Attention Improves Decision Making in Individuals with Elevated Self-Reported Depressive Symptoms

PubMed Central

Cooper, Jessica A.; Gorlick, Marissa A.; Denny, Taylor; Worthy, Darrell A.; Beevers, Christopher G.; Maddox, W. Todd

2013-01-01

Depression is often characterized by attentional biases toward negative items and away from positive items, which likely affects reward and punishment processing. Recent work reported that training attention away from negative stimuli reduced this bias and reduced depressive symptoms. However, the effect of attention training on subsequent learning has yet to be explored. In the current study, participants were required to learn to maximize reward during decision-making. Undergraduates with elevated self-reported depressive symptoms received attention training toward positive stimuli prior to performing the decision-making task (n=20; active training). The active training group was compared to two groups: undergraduates with elevated self-reported depressive symptoms who received placebo training (n=22; placebo training) and control subjects with low levels of depressive symptoms (n=33; non-depressive control). The placebo-training depressive group performed worse and switched between options more than non-depressive controls on the reward maximization task. However, depressives that received active training performed as well as non-depressive controls. Computational modeling indicated that the placebo-trained group learned more from negative than from positive prediction errors, leading to more frequent switching. The non-depressive control and active training depressive groups showed similar learning from positive and negative prediction errors, leading to less frequent switching and better performance. Our results indicate that individuals with elevated depressive symptoms are impaired at reward maximization, but that the deficit can be improved with attention training toward positive stimuli. PMID:24197612

Training attention improves decision making in individuals with elevated self-reported depressive symptoms.

PubMed

Cooper, Jessica A; Gorlick, Marissa A; Denny, Taylor; Worthy, Darrell A; Beevers, Christopher G; Maddox, W Todd

2014-06-01

Depression is often characterized by attentional biases toward negative items and away from positive items, which likely affects reward and punishment processing. Recent work has reported that training attention away from negative stimuli reduced this bias and reduced depressive symptoms. However, the effect of attention training on subsequent learning has yet to be explored. In the present study, participants were required to learn to maximize reward during decision making. Undergraduates with elevated self-reported depressive symptoms received attention training toward positive stimuli prior to performing the decision-making task (n = 20; active training). The active-training group was compared to two other groups: undergraduates with elevated self-reported depressive symptoms who received placebo training (n = 22; placebo training) and a control group with low levels of depressive symptoms (n = 33; nondepressive control). The placebo-training depressive group performed worse and switched between options more than did the nondepressive controls on the reward maximization task. However, depressives that received active training performed as well as the nondepressive controls. Computational modeling indicated that the placebo-trained group learned more from negative than from positive prediction errors, leading to more frequent switching. The nondepressive control and active-training depressive groups showed similar learning from positive and negative prediction errors, leading to less-frequent switching and better performance. Our results indicate that individuals with elevated depressive symptoms are impaired at reward maximization, but that the deficit can be improved with attention training toward positive stimuli.

Uncertainty and the difficulty of thinking through disjunctions.

PubMed

Shafir, E

1994-01-01

This paper considers the relationship between decision under uncertainty and thinking through disjunctions. Decision situations that lead to violations of Savage's sure-thing principle are examined, and a variety of simple reasoning problems that often generate confusion and error are reviewed. The common difficulty is attributed to people's reluctance to think through disjunctions. Instead of hypothetically traveling through the branches of a decision tree, it is suggested, people suspend judgement and remain at the node. This interpretation is applied to instances of decision making, information search, deductive and inductive reasoning, probabilistic judgement, games, puzzles and paradoxes. Some implications of the reluctance to think through disjunctions, as well as potential corrective procedures, are discussed.

Driving difficulties in Parkinson's disease

PubMed Central

Rizzo, Matthew; Uc, Ergun Y; Dawson, Jeffrey; Anderson, Steven; Rodnitzky, Robert

2011-01-01

Safe driving requires the coordination of attention, perception, memory, motor and executive functions (including decision-making) and self-awareness. PD and other disorders may impair these abilities. Because age or medical diagnosis alone is often an unreliable criterion for licensure, decisions on fitness to drive should be based on empirical observations of performance. Linkages between cognitive abilities measured by neuropsychological tasks, and driving behavior assessed using driving simulators, and natural and naturalistic observations in instrumented vehicles, can help standardize the assessment of fitness-to-drive. By understanding the patterns of driver safety errors that cause crashes, it may be possible to design interventions to reduce these errors and injuries and increase mobility. This includes driver performance monitoring devices, collision alerting and warning systems, road design, and graded licensure strategies. PMID:20187237

Do juries meet our expectations?

PubMed

Arkes, Hal R; Mellers, Barbara A

2002-12-01

Surveys of public opinion indicate that people have high expectations for juries. When it comes to serious crimes, most people want errors of convicting the innocent (false positives) or acquitting the guilty (false negatives) to fall well below 10%. Using expected utility theory, Bayes' Theorem, signal detection theory, and empirical evidence from detection studies of medical decision making, eyewitness testimony, and weather forecasting, we argue that the frequency of mistakes probably far exceeds these "tolerable" levels. We are not arguing against the use of juries. Rather, we point out that a closer look at jury decisions reveals a serious gap between what we expect from juries and what probably occurs. When deciding issues of guilt and/or punishing convicted criminals, we as a society should recognize and acknowledge the abundance of error.

Electrophysiological correlates reflect the integration of model-based and model-free decision information.

PubMed

Eppinger, Ben; Walter, Maik; Li, Shu-Chen

2017-04-01

In this study, we investigated the interplay of habitual (model-free) and goal-directed (model-based) decision processes by using a two-stage Markov decision task in combination with event-related potentials (ERPs) and computational modeling. To manipulate the demands on model-based decision making, we applied two experimental conditions with different probabilities of transitioning from the first to the second stage of the task. As we expected, when the stage transitions were more predictable, participants showed greater model-based (planning) behavior. Consistent with this result, we found that stimulus-evoked parietal (P300) activity at the second stage of the task increased with the predictability of the state transitions. However, the parietal activity also reflected model-free information about the expected values of the stimuli, indicating that at this stage of the task both types of information are integrated to guide decision making. Outcome-related ERP components only reflected reward-related processes: Specifically, a medial prefrontal ERP component (the feedback-related negativity) was sensitive to negative outcomes, whereas a component that is elicited by reward (the feedback-related positivity) increased as a function of positive prediction errors. Taken together, our data indicate that stimulus-locked parietal activity reflects the integration of model-based and model-free information during decision making, whereas feedback-related medial prefrontal signals primarily reflect reward-related decision processes.

Model-based influences on humans' choices and striatal prediction errors.

PubMed

Daw, Nathaniel D; Gershman, Samuel J; Seymour, Ben; Dayan, Peter; Dolan, Raymond J

2011-03-24

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. Copyright © 2011 Elsevier Inc. All rights reserved.

"Racial bias in mock juror decision-making: A meta-analytic review of defendant treatment": Correction to Mitchell et al. (2005).

PubMed

2017-06-01

Reports an error in "Racial Bias in Mock Juror Decision-Making: A Meta-Analytic Review of Defendant Treatment" by Tara L. Mitchell, Ryann M. Haw, Jeffrey E. Pfeifer and Christian A. Meissner ( Law and Human Behavior , 2005[Dec], Vol 29[6], 621-637). In the article, all of the numbers in Appendix A were correct, but the signs were reversed for z' in a number of studies, which are listed. Also, in Appendix B, some values were incorrect, some signs were reversed, and some values were missing. The corrected appendix is included. (The following abstract of the original article appeared in record 2006-00971-001.) Common wisdom seems to suggest that racial bias, defined as disparate treatment of minority defendants, exists in jury decision-making, with Black defendants being treated more harshly by jurors than White defendants. The empirical research, however, is inconsistent--some studies show racial bias while others do not. Two previous meta-analyses have found conflicting results regarding the existence of racial bias in juror decision-making (Mazzella & Feingold, 1994, Journal of Applied Social Psychology, 24, 1315-1344; Sweeney & Haney, 1992, Behavioral Sciences and the Law, 10, 179-195). This research takes a meta-analytic approach to further investigate the inconsistencies within the empirical literature on racial bias in juror decision-making by defining racial bias as disparate treatment of racial out-groups (rather than focusing upon the minority group alone). Our results suggest that a small, yet significant, effect of racial bias in decision-making is present across studies, but that the effect becomes more pronounced when certain moderators are considered. The state of the research will be discussed in light of these findings. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

External audit of clinical practice and medical decision making in a new Asian oncology center: Results and implications for both developing and developed nations

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

Shakespeare, Thomas P.; Back, Michael F.; Lu, Jiade J.

2006-03-01

Purpose: The external audit of oncologist clinical practice is increasingly important because of the incorporation of audits into national maintenance of certification (MOC) programs. However, there are few reports of external audits of oncology practice or decision making. Our institution (The Cancer Institute, Singapore) was asked to externally audit an oncology department in a developing Asian nation, providing a unique opportunity to explore the feasibility of such a process. Methods and Materials: We audited 100 randomly selected patients simulated for radiotherapy in 2003, using a previously reported audit instrument assessing clinical documentation/quality assurance and medical decision making. Results: Clinical documentation/qualitymore » assurance, decision making, and overall performance criteria were adequate 74.4%, 88.3%, and 80.2% of the time, respectively. Overall 52.0% of cases received suboptimal management. Multivariate analysis revealed palliative intent was associated with improved documentation/clinical quality assurance (p = 0.07), decision making (p 0.007), overall performance (p = 0.003), and optimal treatment rates (p 0.07); non-small-cell lung cancer or central nervous system primary sites were associated with better decision making (p = 0.001), overall performance (p = 0.03), and optimal treatment rates (p = 0.002). Conclusions: Despite the poor results, the external audit had several benefits. It identified learning needs for future targeting, and the auditor provided facilitating feedback to address systematic errors identified. Our experience was also helpful in refining our national revalidation audit instrument. The feasibility of the external audit supports the consideration of including audit in national MOC programs.« less

Affective decision making under uncertainty during a plausible aviation task: an fMRI study.

PubMed

Causse, Mickaël; Péran, Patrice; Dehais, Frédéric; Caravasso, Chiara Falletta; Zeffiro, Thomas; Sabatini, Umberto; Pastor, Josette

2013-05-01

In aeronautics, plan continuation error (PCE) represents failure to revise a flight plan despite emerging evidence suggesting that it is no longer safe. Assuming that PCE may be associated with a shift from cold to hot reasoning, we hypothesized that this transition may result from a large range of strong negative emotional influences linked with the decision to abort a landing and circle for a repeat attempt, referred to as a "go-around". We investigated this hypothesis by combining functional neuroimaging with an ecologically valid aviation task performed under contextual variation in incentive and situational uncertainty. Our goal was to identify regional brain activity related to the sorts of conservative or liberal decision-making strategies engaged when participants were both exposed to a financial payoff matrix constructed to bias responses in favor of landing acceptance, while they were simultaneously experiencing maximum levels of uncertainty related to high levels of stimulus ambiguity. Combined with the observed behavioral outcomes, our neuroimaging results revealed a shift from cold to hot decision making in response to high uncertainty when participants were exposed to the financial incentive. Most notably, while we observed activity increases in response to uncertainty in many frontal regions such as dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC), less overall activity was observed when the reward was combined with uncertainty. Moreover, participants with poor decision making, quantified as a lower discriminability index d', exhibited riskier behavior coupled with lower activity in the right DLPFC. These outcomes suggest a disruptive effect of biased financial incentive and high uncertainty on the rational decision-making neural network, and consequently, on decision relevance. Copyright © 2013 Elsevier Inc. All rights reserved.

Reduced activation in the ventral striatum during probabilistic decision-making in patients in an at-risk mental state

PubMed Central

Rausch, Franziska; Mier, Daniela; Eifler, Sarah; Fenske, Sabrina; Schirmbeck, Frederike; Englisch, Susanne; Schilling, Claudia; Meyer-Lindenberg, Andreas; Kirsch, Peter; Zink, Mathias

2015-01-01

Background Patients with schizophrenia display metacognitive impairments, such as hasty decision-making during probabilistic reasoning — the “jumping to conclusion” bias (JTC). Our recent fMRI study revealed reduced activations in the right ventral striatum (VS) and the ventral tegmental area (VTA) to be associated with decision-making in patients with schizophrenia. It is unclear whether these functional alterations occur in the at-risk mental state (ARMS). Methods We administered the classical beads task and fMRI among ARMS patients and healthy controls matched for age, sex, education and premorbid verbal intelligence. None of the ARMS patients was treated with antipsychotics. Both tasks request probabilistic decisions after a variable amount of stimuli. We evaluated activation during decision-making under certainty versus uncertainty and the process of final decision-making. Results We included 24 AMRS patients and 24 controls in our study. Compared with controls, ARMS patients tended to draw fewer beads and showed significantly more JTC bias in the classical beads task, mirroring findings in patients with schizophrenia. During fMRI, ARMS patients did not demonstrate JTC bias on the behavioural level, but showed a significant hypoactivation in the right VS during the decision stage. Limitations Owing to the cross-sectional design of the study, results are constrained to a better insight into the neurobiology of risk constellations, but not pre-psychotic stages. Nine of the ARMS patients were treated with antidepressants and/or lorazepam. Conclusion As in patients with schizophrenia, a striatal hypoactivation was found in ARMS patients. Confounding effects of antipsychotic medication can be excluded. Our findings indicate that error prediction signalling and reward anticipation may be linked to striatal dysfunction during prodromal stages and should be examined for their utility in predicting transition risk. PMID:25622039

Reduced activation in the ventral striatum during probabilistic decision-making in patients in an at-risk mental state.

PubMed

Rausch, Franziska; Mier, Daniela; Eifler, Sarah; Fenske, Sabrina; Schirmbeck, Frederike; Englisch, Susanne; Schilling, Claudia; Meyer-Lindenberg, Andreas; Kirsch, Peter; Zink, Mathias

2015-05-01

Patients with schizophrenia display metacognitive impairments, such as hasty decision-making during probabilistic reasoning - the "jumping to conclusion" bias (JTC). Our recent fMRI study revealed reduced activations in the right ventral striatum (VS) and the ventral tegmental area (VTA) to be associated with decision-making in patients with schizophrenia. It is unclear whether these functional alterations occur in the at-risk mental state (ARMS). We administered the classical beads task and fMRI among ARMS patients and healthy controls matched for age, sex, education and premorbid verbal intelligence. None of the ARMS patients was treated with antipsychotics. Both tasks request probabilistic decisions after a variable amount of stimuli. We evaluated activation during decision-making under certainty versus uncertainty and the process of final decision-making. We included 24 AMRS patients and 24 controls in our study. Compared with controls, ARMS patients tended to draw fewer beads and showed significantly more JTC bias in the classical beads task, mirroring findings in patients with schizophrenia. During fMRI, ARMS patients did not demonstrate JTC bias on the behavioural level, but showed a significant hypoactivation in the right VS during the decision stage. Owing to the cross-sectional design of the study, results are constrained to a better insight into the neurobiology of risk constellations, but not prepsychotic stages. Nine of the ARMS patients were treated with antidepressants and/or lorazepam. As in patients with schizophrenia, a striatal hypoactivation was found in ARMS patients. Confounding effects of antipsychotic medication can be excluded. Our findings indicate that error prediction signalling and reward anticipation may be linked to striatal dysfunction during prodromal stages and should be examined for their utility in predicting transition risk.

Colour coding for blood collection tube closures - a call for harmonisation.

PubMed

Simundic, Ana-Maria; Cornes, Michael P; Grankvist, Kjell; Lippi, Giuseppe; Nybo, Mads; Ceriotti, Ferruccio; Theodorsson, Elvar; Panteghini, Mauro

2015-02-01

At least one in 10 patients experience adverse events while receiving hospital care. Many of the errors are related to laboratory diagnostics. Efforts to reduce laboratory errors over recent decades have primarily focused on the measurement process while pre- and post-analytical errors including errors in sampling, reporting and decision-making have received much less attention. Proper sampling and additives to the samples are essential. Tubes and additives are identified not only in writing on the tubes but also by the colour of the tube closures. Unfortunately these colours have not been standardised, running the risk of error when tubes from one manufacturer are replaced by the tubes from another manufacturer that use different colour coding. EFLM therefore supports the worldwide harmonisation of the colour coding for blood collection tube closures and labels in order to reduce the risk of pre-analytical errors and improve the patient safety.

When is an error not a prediction error? An electrophysiological investigation.

PubMed

Holroyd, Clay B; Krigolson, Olave E; Baker, Robert; Lee, Seung; Gibson, Jessica

2009-03-01

A recent theory holds that the anterior cingulate cortex (ACC) uses reinforcement learning signals conveyed by the midbrain dopamine system to facilitate flexible action selection. According to this position, the impact of reward prediction error signals on ACC modulates the amplitude of a component of the event-related brain potential called the error-related negativity (ERN). The theory predicts that ERN amplitude is monotonically related to the expectedness of the event: It is larger for unexpected outcomes than for expected outcomes. However, a recent failure to confirm this prediction has called the theory into question. In the present article, we investigated this discrepancy in three trial-and-error learning experiments. All three experiments provided support for the theory, but the effect sizes were largest when an optimal response strategy could actually be learned. This observation suggests that ACC utilizes dopamine reward prediction error signals for adaptive decision making when the optimal behavior is, in fact, learnable.

Improving specialist drug prescribing in primary care using task and error analysis: an observational study.

PubMed

Chana, Narinder; Porat, Talya; Whittlesea, Cate; Delaney, Brendan

2017-03-01

Electronic prescribing has benefited from computerised clinical decision support systems (CDSSs); however, no published studies have evaluated the potential for a CDSS to support GPs in prescribing specialist drugs. To identify potential weaknesses and errors in the existing process of prescribing specialist drugs that could be addressed in the development of a CDSS. Semi-structured interviews with key informants followed by an observational study involving GPs in the UK. Twelve key informants were interviewed to investigate the use of CDSSs in the UK. Nine GPs were observed while performing case scenarios depicting requests from hospitals or patients to prescribe a specialist drug. Activity diagrams, hierarchical task analysis, and systematic human error reduction and prediction approach analyses were performed. The current process of prescribing specialist drugs by GPs is prone to error. Errors of omission due to lack of information were the most common errors, which could potentially result in a GP prescribing a specialist drug that should only be prescribed in hospitals, or prescribing a specialist drug without reference to a shared care protocol. Half of all possible errors in the prescribing process had a high probability of occurrence. A CDSS supporting GPs during the process of prescribing specialist drugs is needed. This could, first, support the decision making of whether or not to undertake prescribing, and, second, provide drug-specific parameters linked to shared care protocols, which could reduce the errors identified and increase patient safety. © British Journal of General Practice 2017.

Target Uncertainty Mediates Sensorimotor Error Correction

PubMed Central

Vijayakumar, Sethu; Wolpert, Daniel M.

2017-01-01

Human movements are prone to errors that arise from inaccuracies in both our perceptual processing and execution of motor commands. We can reduce such errors by both improving our estimates of the state of the world and through online error correction of the ongoing action. Two prominent frameworks that explain how humans solve these problems are Bayesian estimation and stochastic optimal feedback control. Here we examine the interaction between estimation and control by asking if uncertainty in estimates affects how subjects correct for errors that may arise during the movement. Unbeknownst to participants, we randomly shifted the visual feedback of their finger position as they reached to indicate the center of mass of an object. Even though participants were given ample time to compensate for this perturbation, they only fully corrected for the induced error on trials with low uncertainty about center of mass, with correction only partial in trials involving more uncertainty. The analysis of subjects’ scores revealed that participants corrected for errors just enough to avoid significant decrease in their overall scores, in agreement with the minimal intervention principle of optimal feedback control. We explain this behavior with a term in the loss function that accounts for the additional effort of adjusting one’s response. By suggesting that subjects’ decision uncertainty, as reflected in their posterior distribution, is a major factor in determining how their sensorimotor system responds to error, our findings support theoretical models in which the decision making and control processes are fully integrated. PMID:28129323

Target Uncertainty Mediates Sensorimotor Error Correction.

PubMed

Acerbi, Luigi; Vijayakumar, Sethu; Wolpert, Daniel M

2017-01-01

Human movements are prone to errors that arise from inaccuracies in both our perceptual processing and execution of motor commands. We can reduce such errors by both improving our estimates of the state of the world and through online error correction of the ongoing action. Two prominent frameworks that explain how humans solve these problems are Bayesian estimation and stochastic optimal feedback control. Here we examine the interaction between estimation and control by asking if uncertainty in estimates affects how subjects correct for errors that may arise during the movement. Unbeknownst to participants, we randomly shifted the visual feedback of their finger position as they reached to indicate the center of mass of an object. Even though participants were given ample time to compensate for this perturbation, they only fully corrected for the induced error on trials with low uncertainty about center of mass, with correction only partial in trials involving more uncertainty. The analysis of subjects' scores revealed that participants corrected for errors just enough to avoid significant decrease in their overall scores, in agreement with the minimal intervention principle of optimal feedback control. We explain this behavior with a term in the loss function that accounts for the additional effort of adjusting one's response. By suggesting that subjects' decision uncertainty, as reflected in their posterior distribution, is a major factor in determining how their sensorimotor system responds to error, our findings support theoretical models in which the decision making and control processes are fully integrated.

A Flexible Latent Class Approach to Estimating Test-Score Reliability

ERIC Educational Resources Information Center

van der Palm, Daniël W.; van der Ark, L. Andries; Sijtsma, Klaas

2014-01-01

The latent class reliability coefficient (LCRC) is improved by using the divisive latent class model instead of the unrestricted latent class model. This results in the divisive latent class reliability coefficient (DLCRC), which unlike LCRC avoids making subjective decisions about the best solution and thus avoids judgment error. A computational…

"Are We Almost There, Captain?" The Geographical Errors of Christopher Columbus.

ERIC Educational Resources Information Center

Edwards, Glenn M.

1992-01-01

Discusses the scientific knowledge available to Christopher Columbus and how it influenced his geographically flawed, yet historically significant, decision to sail west in order to travel east. Factors discussed include Aristotle's conclusion that the earth was round, early measurements of latitude and longitude, and early map-making attempts.…

What Comes before Report Writing? Attending to Clinical Reasoning and Thinking Errors in School Psychology

ERIC Educational Resources Information Center

Wilcox, Gabrielle; Schroeder, Meadow

2015-01-01

Psychoeducational assessment involves collecting, organizing, and interpreting a large amount of data from various sources. Drawing upon psychological and medical literature, we review two main approaches to clinical reasoning (deductive and inductive) and how they synergistically guide diagnostic decision-making. In addition, we discuss how the…

Physician Interaction with Electronic Medical Records: A Qualitative Study

ERIC Educational Resources Information Center

Noteboom, Cherie Bakker

2010-01-01

The integration of EHR (Electronic Health Records) in IT infrastructures supporting organizations enable improved access to and recording of patient data, enhanced ability to make better and more-timely decisions, and improved quality and reduced errors. Despite these benefits, there are mixed results as to the use of EHR. The literature suggests…

Neurobiologically Validated Models of Errors in Decision-Making: Strategies for Remediation and Detection

DTIC Science & Technology

2015-03-20

performed a series of bid trials where they reported their willingness-to-pay for each of 30 snack food items; potential trial realization was...willingness-to-pay for each of 30 snack food items; potential trial realization was conducted at the end of the experiment via an auction procedure

The explanatory power of Schema Theory: theoretical foundations and future applications in Ergonomics.

PubMed

Plant, Katherine L; Stanton, Neville A

2013-01-01

Schema Theory is intuitively appealing although it has not always received positive press; critics of the approach argue that the concept is too ambiguous and vague and there are inherent difficulties associated with measuring schemata. As such, the term schema can be met with scepticism and wariness. The purpose of this paper is to address the criticisms that have been levelled at Schema Theory by demonstrating how Schema Theory has been utilised in Ergonomics research, particularly in the key areas of situation awareness, naturalistic decision making and error. The future of Schema Theory is also discussed in light of its potential roles as a unifying theory in Ergonomics and in contributing to our understanding of distributed cognition. We conclude that Schema Theory has made a positive contribution to Ergonomics and with continued refinement of methods to infer and represent schemata it is likely that this trend will continue. This paper reviews the contribution that Schema Theory has made to Ergonomics research. The criticisms of the theory are addressed using examples from the areas of situation awareness, decision making and error.

Social and monetary reward learning engage overlapping neural substrates.

PubMed

Lin, Alice; Adolphs, Ralph; Rangel, Antonio

2012-03-01

Learning to make choices that yield rewarding outcomes requires the computation of three distinct signals: stimulus values that are used to guide choices at the time of decision making, experienced utility signals that are used to evaluate the outcomes of those decisions and prediction errors that are used to update the values assigned to stimuli during reward learning. Here we investigated whether monetary and social rewards involve overlapping neural substrates during these computations. Subjects engaged in two probabilistic reward learning tasks that were identical except that rewards were either social (pictures of smiling or angry people) or monetary (gaining or losing money). We found substantial overlap between the two types of rewards for all components of the learning process: a common area of ventromedial prefrontal cortex (vmPFC) correlated with stimulus value at the time of choice and another common area of vmPFC correlated with reward magnitude and common areas in the striatum correlated with prediction errors. Taken together, the findings support the hypothesis that shared anatomical substrates are involved in the computation of both monetary and social rewards. © The Author (2011). Published by Oxford University Press.

A case of the birth and death of a high reliability healthcare organisation.

PubMed

Roberts, K H; Madsen, P; Desai, V; Van Stralen, D

2005-06-01

High reliability organisations (HROs) are those in which errors rarely occur. To accomplish this they conduct relatively error free operations over long periods of time and make consistently good decisions resulting in high quality and reliability. Some organisational processes that characterise HROs are process auditing, implementing appropriate reward systems, avoiding quality degradation, appropriately perceiving that risk exists and developing strategies to deal with it, and command and control. Command and control processes include migrating decision making, redundancy in people or hardware, developing situational awareness, formal rules and procedures, and training. These processes must be tailored to the specific organisation implementing them. These processes were applied to a paediatric intensive care unit (PICU) where care was derived from problem solving methodology rather than protocol. After a leadership change, the unit returned to the hierarchical medical model of care. Important outcome variables such as infant mortality, patient return to the PICU after discharge, days on the PICU, air transports, degraded. Implications for clinical practice include providing caregivers with sufficient flexibility to meet changing situations, encouraging teamwork, and avoiding shaming, naming, and blaming.

Distinct alterations in value-based decision-making and cognitive control in suicide attempters: toward a dual neurocognitive model.

PubMed

Richard-Devantoy, Stéphane; Olié, Emilie; Guillaume, Sébastien; Bechara, Antoine; Courtet, Philippe; Jollant, Fabrice

2013-12-01

The literature suggests that many suicide attempters show impairment in both decision-making and cognitive control. However, it is not clear if these deficits are linked to each other, and if they may be related to more basic alterations in attention. This is a relevant question in the perspective of future interventions targeting cognitive deficits to prevent suicidal acts. Two different populations of patients with histories of suicide attempts were assessed (N=142 and 119). The Iowa Gambling Task (IGT) was used to measure decision-making in both populations. We used a D2 cancellation task and a verbal working memory task in population 1; the Stroop test, the N-Back task, the Trail Making Test, and the Hayling Sentence Completion test in population 2. Regarding decision-making, we only found a small negative correlation between the Hayling test error score (r=-0.24; p=0.01), and the net score from the second half of the IGT. In contrast, working memory, cognitive flexibility and cognitive inhibition measures were largely inter-correlated. Most patients were medicated. Only patients with mood disorders. These results add to previous findings suggesting that the neurocognitive vulnerability to suicidal behavior may rely on impairments in two distinct anatomical systems, one processing value-based decision-making (associated with ventral prefrontal cortex, among others) and one underlying cognitive control (associated with more dorsal prefrontal regions). This distinction may result in tailored-made cognitive interventions. Copyright © 2013 Elsevier B.V. All rights reserved.

A robotic approach to understanding the role and the mechanism of vicarious trial-and-error in a T-maze task.

PubMed

Matsuda, Eiko; Hubert, Julien; Ikegami, Takashi

2014-01-01

Vicarious trial-and-error (VTE) is a behavior observed in rat experiments that seems to suggest self-conflict. This behavior is seen mainly when the rats are uncertain about making a decision. The presence of VTE is regarded as an indicator of a deliberative decision-making process, that is, searching, predicting, and evaluating outcomes. This process is slower than automated decision-making processes, such as reflex or habituation, but it allows for flexible and ongoing control of behavior. In this study, we propose for the first time a robotic model of VTE to see if VTE can emerge just from a body-environment interaction and to show the underlying mechanism responsible for the observation of VTE and the advantages provided by it. We tried several robots with different parameters, and we have found that they showed three different types of VTE: high numbers of VTE at the beginning of learning, decreasing numbers afterward (similar VTE pattern to experiments with rats), low during the whole learning period, and high numbers all the time. Therefore, we were able to reproduce the phenomenon of VTE in a model robot using only a simple dynamical neural network with Hebbian learning, which suggests that VTE is an emergent property of a plastic and embodied neural network. From a comparison of the three types of VTE, we demonstrated that 1) VTE is associated with chaotic activity of neurons in our model and 2) VTE-showing robots were robust to environmental perturbations. We suggest that the instability of neuronal activity found in VTE allows ongoing learning to rebuild its strategy continuously, which creates robust behavior. Based on these results, we suggest that VTE is caused by a similar mechanism in biology and leads to robust decision making in an analogous way.

Group Augmentation in Realistic Visual-Search Decisions via a Hybrid Brain-Computer Interface.

PubMed

Valeriani, Davide; Cinel, Caterina; Poli, Riccardo

2017-08-10

Groups have increased sensing and cognition capabilities that typically allow them to make better decisions. However, factors such as communication biases and time constraints can lead to less-than-optimal group decisions. In this study, we use a hybrid Brain-Computer Interface (hBCI) to improve the performance of groups undertaking a realistic visual-search task. Our hBCI extracts neural information from EEG signals and combines it with response times to build an estimate of the decision confidence. This is used to weigh individual responses, resulting in improved group decisions. We compare the performance of hBCI-assisted groups with the performance of non-BCI groups using standard majority voting, and non-BCI groups using weighted voting based on reported decision confidence. We also investigate the impact on group performance of a computer-mediated form of communication between members. Results across three experiments suggest that the hBCI provides significant advantages over non-BCI decision methods in all cases. We also found that our form of communication increases individual error rates by almost 50% compared to non-communicating observers, which also results in worse group performance. Communication also makes reported confidence uncorrelated with the decision correctness, thereby nullifying its value in weighing votes. In summary, best decisions are achieved by hBCI-assisted, non-communicating groups.

Inhibition of Pre-Supplementary Motor Area by Continuous Theta Burst Stimulation Leads to More Cautious Decision-making and More Efficient Sensory Evidence Integration.

PubMed

Tosun, Tuğçe; Berkay, Dilara; Sack, Alexander T; Çakmak, Yusuf Ö; Balcı, Fuat

2017-08-01

Decisions are made based on the integration of available evidence. The noise in evidence accumulation leads to a particular speed-accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed-accuracy tradeoff, provide evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the sensory evidence integration.

Application of Exactly Linearized Error Transport Equations to AIAA CFD Prediction Workshops

NASA Technical Reports Server (NTRS)

Derlaga, Joseph M.; Park, Michael A.; Rallabhandi, Sriram

2017-01-01

The computational fluid dynamics (CFD) prediction workshops sponsored by the AIAA have created invaluable opportunities in which to discuss the predictive capabilities of CFD in areas in which it has struggled, e.g., cruise drag, high-lift, and sonic boom pre diction. While there are many factors that contribute to disagreement between simulated and experimental results, such as modeling or discretization error, quantifying the errors contained in a simulation is important for those who make decisions based on the computational results. The linearized error transport equations (ETE) combined with a truncation error estimate is a method to quantify one source of errors. The ETE are implemented with a complex-step method to provide an exact linearization with minimal source code modifications to CFD and multidisciplinary analysis methods. The equivalency of adjoint and linearized ETE functional error correction is demonstrated. Uniformly refined grids from a series of AIAA prediction workshops demonstrate the utility of ETE for multidisciplinary analysis with a connection between estimated discretization error and (resolved or under-resolved) flow features.

Gunslingers, poker players, and chickens 3: Decision making under mental performance pressure in junior elite athletes.

PubMed

Parkin, Beth L; Walsh, Vincent

2017-01-01

Having investigated the decision making of world class elite and subelite athletes (see Parkin and Walsh, 2017; Parkin et al., 2017), here the abilities of those at the earliest stage of entry to elite sport are examined. Junior elite athletes have undergone initial national selection and are younger than athletes examined previously (mean age 13 years). Decision making under mental pressure is explored in this sample. During performance an athlete encounters a wide array of mental pressures; these include the psychological impact of errors, negative feedback, and requirements for sustained attention in a dynamic environment (Anshel and Wells, 2000; Mellalieu et al., 2009). Such factors increase the cognitive demands of the athletes, inducing distracting anxiety-related thoughts known as rumination (Beilock and Gray, 2007). Mental pressure has been shown to reduce performance of decision-making tasks where reward and loss contingencies are explicit, with a shift toward increased risk taking (Pabst et al., 2013; Starcke et al., 2011). Mental pressure has been shown to be detrimental to decision-making speed in comparison to physical stress, highlighting the importance of considering a range of different pressures encountered by athletes (Hepler, 2015). To investigate the influence of mental pressure on key indicators of decision making in junior elite athletes. This chapter concludes a wider project examining decision making across developmental stages in elite sport. The work further explores how psychological insights can be applied in an elite sporting environment and in particular tailored to the requirements of junior athletes. Seventeen junior elite athletes (10 males, mean age: 13.80 years) enrolled on a national youth athletic development program participated in the study. Performance across three categories of decision making was assessed under conditions of low and high mental pressure. Decision making under risk was measured via the Cambridge Gambling Task (CGT; Rogers et al., 1999), decision making under uncertainty via the Balloon Analogue Risk Task (BART; Lejuez et al., 2002), and fast reactive responses to perceptual stimuli via the Visual Search Task (Treisman, 1982). Mental pressure was induced with the addition of a concurrent verbal memory task, used to increase cognitive load and mimic the distracting effects of anxiety-related rumination. In junior elite athletes, fast reactive responses to perceptual stimuli (on the Visual Search Task) were slower under conditions of mental pressure. For decision making under risk there was an interaction of mental pressure and gender on the amount of points gambled, under pressure there was a higher level of risk taking in male athletes compared to females. There was no influence of mental pressure on decision making under uncertainity. There were no significant correlations in the degree to which individual's responses changed under pressure across the three measures of decision making. When assessing the applicability of results based on group averages there were no junior elite athletes who showed an "average" response (within 1SD of the mean) to mental pressure across all the three decision-making tasks. Mental pressure affects decision making in a sample of junior elite athletes, with a slowing of response times, and modulations to performance of decision making under risk that have a high requirement for working memory. In relation to sport, these findings suggest that novel situations that place high cognitive demands on the athlete may be particularly influenced by mental pressure. The application of this work in junior elite athletes included the feedback of individual results and the implementation of a decision-making taxonomy. © 2017 Elsevier B.V. All rights reserved.

Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety.

PubMed

Seshia, Shashi S; Bryan Young, G; Makhinson, Michael; Smith, Preston A; Stobart, Kent; Croskerry, Pat

2018-02-01

Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care-related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive-affective biases plus cascade could advance the understanding of cognitive-affective processes that underlie decisions and organizational cultures across the continuum of care. Thematic analysis, qualitative information from several sources being used to support argumentation. Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive-affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive-affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive-affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error-provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error-provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive-affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. © 2017 The Authors. Journal of Evaluation in Clinical Practice published by John Wiley & Sons, Ltd.

Automation bias: a systematic review of frequency, effect mediators, and mitigators

PubMed Central

Roudsari, Abdul; Wyatt, Jeremy C

2011-01-01

Automation bias (AB)—the tendency to over-rely on automation—has been studied in various academic fields. Clinical decision support systems (CDSS) aim to benefit the clinical decision-making process. Although most research shows overall improved performance with use, there is often a failure to recognize the new errors that CDSS can introduce. With a focus on healthcare, a systematic review of the literature from a variety of research fields has been carried out, assessing the frequency and severity of AB, the effect mediators, and interventions potentially mitigating this effect. This is discussed alongside automation-induced complacency, or insufficient monitoring of automation output. A mix of subject specific and freetext terms around the themes of automation, human–automation interaction, and task performance and error were used to search article databases. Of 13 821 retrieved papers, 74 met the inclusion criteria. User factors such as cognitive style, decision support systems (DSS), and task specific experience mediated AB, as did attitudinal driving factors such as trust and confidence. Environmental mediators included workload, task complexity, and time constraint, which pressurized cognitive resources. Mitigators of AB included implementation factors such as training and emphasizing user accountability, and DSS design factors such as the position of advice on the screen, updated confidence levels attached to DSS output, and the provision of information versus recommendation. By uncovering the mechanisms by which AB operates, this review aims to help optimize the clinical decision-making process for CDSS developers and healthcare practitioners. PMID:21685142

Automation bias: a systematic review of frequency, effect mediators, and mitigators.

PubMed

Goddard, Kate; Roudsari, Abdul; Wyatt, Jeremy C

2012-01-01

Automation bias (AB)--the tendency to over-rely on automation--has been studied in various academic fields. Clinical decision support systems (CDSS) aim to benefit the clinical decision-making process. Although most research shows overall improved performance with use, there is often a failure to recognize the new errors that CDSS can introduce. With a focus on healthcare, a systematic review of the literature from a variety of research fields has been carried out, assessing the frequency and severity of AB, the effect mediators, and interventions potentially mitigating this effect. This is discussed alongside automation-induced complacency, or insufficient monitoring of automation output. A mix of subject specific and freetext terms around the themes of automation, human-automation interaction, and task performance and error were used to search article databases. Of 13 821 retrieved papers, 74 met the inclusion criteria. User factors such as cognitive style, decision support systems (DSS), and task specific experience mediated AB, as did attitudinal driving factors such as trust and confidence. Environmental mediators included workload, task complexity, and time constraint, which pressurized cognitive resources. Mitigators of AB included implementation factors such as training and emphasizing user accountability, and DSS design factors such as the position of advice on the screen, updated confidence levels attached to DSS output, and the provision of information versus recommendation. By uncovering the mechanisms by which AB operates, this review aims to help optimize the clinical decision-making process for CDSS developers and healthcare practitioners.

Group-sequential three-arm noninferiority clinical trial designs

PubMed Central

Ochiai, Toshimitsu; Hamasaki, Toshimitsu; Evans, Scott R.; Asakura, Koko; Ohno, Yuko

2016-01-01

We discuss group-sequential three-arm noninferiority clinical trial designs that include active and placebo controls for evaluating both assay sensitivity and noninferiority. We extend two existing approaches, the fixed margin and fraction approaches, into a group-sequential setting with two decision-making frameworks. We investigate the operating characteristics including power, Type I error rate, maximum and expected sample sizes, as design factors vary. In addition, we discuss sample size recalculation and its’ impact on the power and Type I error rate via a simulation study. PMID:26892481

Reconciling uncertain costs and benefits in bayes nets for invasive species management

USGS Publications Warehouse

Burgman, M.A.; Wintle, B.A.; Thompson, C.A.; Moilanen, A.; Runge, M.C.; Ben-Haim, Y.

2010-01-01

Bayes nets are used increasingly to characterize environmental systems and formalize probabilistic reasoning to support decision making. These networks treat probabilities as exact quantities. Sensitivity analysis can be used to evaluate the importance of assumptions and parameter estimates. Here, we outline an application of info-gap theory to Bayes nets that evaluates the sensitivity of decisions to possibly large errors in the underlying probability estimates and utilities. We apply it to an example of management and eradication of Red Imported Fire Ants in Southern Queensland, Australia and show how changes in management decisions can be justified when uncertainty is considered. ?? 2009 Society for Risk Analysis.

Relationship between Recent Flight Experience and Pilot Error General Aviation Accidents

NASA Astrophysics Data System (ADS)

Nilsson, Sarah J.

Aviation insurance agents and fixed-base operation (FBO) owners use recent flight experience, as implied by the 90-day rule, to measure pilot proficiency in physical airplane skills, and to assess the likelihood of a pilot error accident. The generally accepted premise is that more experience in a recent timeframe predicts less of a propensity for an accident, all other factors excluded. Some of these aviation industry stakeholders measure pilot proficiency solely by using time flown within the past 90, 60, or even 30 days, not accounting for extensive research showing aeronautical decision-making and situational awareness training decrease the likelihood of a pilot error accident. In an effort to reduce the pilot error accident rate, the Federal Aviation Administration (FAA) has seen the need to shift pilot training emphasis from proficiency in physical airplane skills to aeronautical decision-making and situational awareness skills. However, current pilot training standards still focus more on the former than on the latter. The relationship between pilot error accidents and recent flight experience implied by the FAA's 90-day rule has not been rigorously assessed using empirical data. The intent of this research was to relate recent flight experience, in terms of time flown in the past 90 days, to pilot error accidents. A quantitative ex post facto approach, focusing on private pilots of single-engine general aviation (GA) fixed-wing aircraft, was used to analyze National Transportation Safety Board (NTSB) accident investigation archival data. The data were analyzed using t-tests and binary logistic regression. T-tests between the mean number of hours of recent flight experience of tricycle gear pilots involved in pilot error accidents (TPE) and non-pilot error accidents (TNPE), t(202) = -.200, p = .842, and conventional gear pilots involved in pilot error accidents (CPE) and non-pilot error accidents (CNPE), t(111) = -.271, p = .787, indicate there is no statistically significant relationship between groups. Binary logistic regression indicate that recent flight experience does not reliably distinguish between pilot error and non-pilot error accidents for TPE/TNPE, chi2 = 0.040 (df=1, p = .841) and CPE/CNPE, chi2= 0.074 (df =1, p = .786). Future research could focus on different pilot populations, and to broaden the scope, analyze several years of data.

Decision making in child protective services: a risky business?

PubMed

Camasso, Michael J; Jagannathan, Radha

2013-09-01

Child Protective Services (CPS) in the United States has received a torrent of criticism from politicians, the media, child advocate groups, and the general public for a perceived propensity to make decisions that are detrimental to children and families. This perception has resulted in numerous lawsuits and court takeovers of CPS in 35 states, and calls for profound restructuring in other states. A widely prescribed remedy for decision errors and faulty judgments is an improvement of risk assessment strategies that enhance hazard evaluation through an improved understanding of threat potentials and exposure likelihoods. We examine the reliability and validity problems that continue to plague current CPS risk assessment and discuss actions that can be taken in the field, including the use of receiver operating characteristic (ROC) curve technology to improve the predictive validity of risk assessment strategies. © 2012 Society for Risk Analysis.

Investment decision making in the health care industry: the future.

PubMed Central

Long, H W

1979-01-01

The economic and political environment in which providers of health care will operate during the 1980s will continue to be increasingly restrictive. Any private-sector organization's long-run survival depends directly on the quality of its investment decisions, broadly defined. This decision making will require three major innovations if private sector health care providers are to survive: 1) traditional biases about the economics of not-for-profit entities must be abandoned; 2) standard data, procedures, and personnel from the accounting discipline must be supplemented with information, methodologies, and people from the discipline of corporate finance; and 3) economic and fiscal risk must be measured and incorporated into both investment decisions and interactions with external regulators. Practitioners can begin to implement these innovations immediately. Although substantial literature exists developing all these concepts generally and applying them to for-profit settings, the literature purporting to treat investment decision making for private-sector health care providers is, on average, replete with conceptual error, simplistic thinking, erroneous applications, and out-of-date methodologies. The literature is, in a word, horrid. Authors, both practitioner and academic, should stop writing terrible books and booklike periodicals for easy royalty dollars, and, instead, pursue sound applied research and disseminate their results in classrooms and in refereed journals. PMID:391771

Evaluation of the performance of statistical tests used in making cleanup decisions at Superfund sites. Part 1: Choosing an appropriate statistical test

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

Berman, D.W.; Allen, B.C.; Van Landingham, C.B.

1998-12-31

The decision rules commonly employed to determine the need for cleanup are evaluated both to identify conditions under which they lead to erroneous conclusions and to quantify the rate that such errors occur. Their performance is also compared with that of other applicable decision rules. The authors based the evaluation of decision rules on simulations. Results are presented as power curves. These curves demonstrate that the degree of statistical control achieved is independent of the form of the null hypothesis. The loss of statistical control that occurs when a decision rule is applied to a data set that does notmore » satisfy the rule`s validity criteria is also clearly demonstrated. Some of the rules evaluated do not offer the formal statistical control that is an inherent design feature of other rules. Nevertheless, results indicate that such informal decision rules may provide superior overall control of error rates, when their application is restricted to data exhibiting particular characteristics. The results reported here are limited to decision rules applied to uncensored and lognormally distributed data. To optimize decision rules, it is necessary to evaluate their behavior when applied to data exhibiting a range of characteristics that bracket those common to field data. The performance of decision rules applied to data sets exhibiting a broader range of characteristics is reported in the second paper of this study.« less

The decision of out-of-home placement in residential care after parental neglect: Empirically testing a psychosocial model.

PubMed

Rodrigues, Leonor; Calheiros, Manuela; Pereira, Cícero

2015-11-01

Out-of-home placement decisions in residential care are complex, ambiguous and full of uncertainty, especially in cases of parental neglect. Literature on this topic is so far unable to understand and demonstrate the source of errors involved in those decisions and still fails to focus on professional's decision making process. Therefore, this work intends to test a socio-psychological model of decision-making that is a more integrated, dualistic and ecological version of the Theory of Planned Behavior's model. It describes the process through which the decision maker takes into account personal, contextual and social factors of the Decision-Making Ecology in the definition of his/her decision threshold. One hundred and ninety-five professionals from different Children and Youth Protection Units, throughout the Portuguese territory, participated in this online study. After reading a vignette of a (psychological and physical) neglect case toward a one-year-old child, participants were presented with a group of questions that measured worker's assessment of risk, intention, attitude, subjective norm, behavior control and beliefs toward residential care placement decision, as well as worker's behavior experience, emotions and family/child-related-values involved in that decision. A set of structural equation modeling analyses have proven the good fit of the proposed model. The intention to propose a residential care placement decision was determined by cognitive, social, affective, value-laden and experience variables and the perceived risk. Altogether our model explained 61% of professional's decision toward a parental neglect case. The theoretical and practical implications of these results are discussed, namely the importance of raising awareness about the existence of these biased psychosocial determinants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Preventing Errors in Clinical Practice: A Call for Self-Awareness

PubMed Central

Borrell-Carrió, Francesc; Epstein, Ronald M.

2004-01-01

While ascribing medical errors primarily to systems factors can free clinicians from individual blame, there are elements of medical errors that can and should be attributed to individual factors. These factors are related less commonly to lack of knowledge and skill than to the inability to apply the clinician’s abilities to situations under certain circumstances. In concert with efforts to improve health care systems, refining physicians’ emotional and cognitive capacities might also prevent many errors. In general, physicians have the sensation of making a mistake because of the interference of emotional elements. We propose a so-called rational-emotive model that emphasizes 2 factors in error causation: (1) difficulty in reframing the first hypothesis that goes to the physician’s mind in an automatic way, and (2) premature closure of the clinical act to avoid confronting inconsistencies, low-level decision rules, and emotions. We propose a teaching strategy based on developing the physician’s insight and self-awareness to detect the inappropriate use of low-level decision rules, as well as detecting the factors that limit a physician’s capacity to tolerate the tension of uncertainty and ambiguity. Emotional self-awareness and self-regulation of attention can be consciously cultivated as habits to help physicians function better in clinical situations. PMID:15335129

Preventing errors in clinical practice: a call for self-awareness.

PubMed

Borrell-Carrió, Francesc; Epstein, Ronald M

2004-01-01

While ascribing medical errors primarily to systems factors can free clinicians from individual blame, there are elements of medical errors that can and should be attributed to individual factors. These factors are related less commonly to lack of knowledge and skill than to the inability to apply the clinician's abilities to situations under certain circumstances. In concert with efforts to improve health care systems, refining physicians' emotional and cognitive capacities might also prevent many errors. In general, physicians have the sensation of making a mistake because of the interference of emotional elements. We propose a so-called rational-emotive model that emphasizes 2 factors in error causation: (1) difficulty in reframing the first hypothesis that goes to the physician's mind in an automatic way, and (2) premature closure of the clinical act to avoid confronting inconsistencies, low-level decision rules, and emotions. We propose a teaching strategy based on developing the physician's insight and self-awareness to detect the inappropriate use of low-level decision rules, as well as detecting the factors that limit a physician's capacity to tolerate the tension of uncertainty and ambiguity. Emotional self-awareness and self-regulation of attention can be consciously cultivated as habits to help physicians function better in clinical situations.

Currie detection limits in gamma-ray spectroscopy.

PubMed

De Geer, Lars-Erik

2004-01-01

Currie Hypothesis testing is applied to gamma-ray spectral data, where an optimum part of the peak is used and the background is considered well known from nearby channels. With this, the risk of making Type I errors is about 100 times lower than commonly assumed. A programme, PeakMaker, produces random peaks with given characteristics on the screen and calculations are done to facilitate a full use of Poisson statistics in spectrum analyses. SHORT TECHNICAL NOTE SUMMARY: The Currie decision limit concept applied to spectral data is reinterpreted, which gives better consistency between the selected error risk and the observed error rates. A PeakMaker program is described and the few count problem is analyzed.

The anatomy of choice: dopamine and decision-making

PubMed Central

Friston, Karl; Schwartenbeck, Philipp; FitzGerald, Thomas; Moutoussis, Michael; Behrens, Timothy; Dolan, Raymond J.

2014-01-01

This paper considers goal-directed decision-making in terms of embodied or active inference. We associate bounded rationality with approximate Bayesian inference that optimizes a free energy bound on model evidence. Several constructs such as expected utility, exploration or novelty bonuses, softmax choice rules and optimism bias emerge as natural consequences of free energy minimization. Previous accounts of active inference have focused on predictive coding. In this paper, we consider variational Bayes as a scheme that the brain might use for approximate Bayesian inference. This scheme provides formal constraints on the computational anatomy of inference and action, which appear to be remarkably consistent with neuroanatomy. Active inference contextualizes optimal decision theory within embodied inference, where goals become prior beliefs. For example, expected utility theory emerges as a special case of free energy minimization, where the sensitivity or inverse temperature (associated with softmax functions and quantal response equilibria) has a unique and Bayes-optimal solution. Crucially, this sensitivity corresponds to the precision of beliefs about behaviour. The changes in precision during variational updates are remarkably reminiscent of empirical dopaminergic responses—and they may provide a new perspective on the role of dopamine in assimilating reward prediction errors to optimize decision-making. PMID:25267823

The anatomy of choice: dopamine and decision-making.

PubMed

Friston, Karl; Schwartenbeck, Philipp; FitzGerald, Thomas; Moutoussis, Michael; Behrens, Timothy; Dolan, Raymond J

2014-11-05

This paper considers goal-directed decision-making in terms of embodied or active inference. We associate bounded rationality with approximate Bayesian inference that optimizes a free energy bound on model evidence. Several constructs such as expected utility, exploration or novelty bonuses, softmax choice rules and optimism bias emerge as natural consequences of free energy minimization. Previous accounts of active inference have focused on predictive coding. In this paper, we consider variational Bayes as a scheme that the brain might use for approximate Bayesian inference. This scheme provides formal constraints on the computational anatomy of inference and action, which appear to be remarkably consistent with neuroanatomy. Active inference contextualizes optimal decision theory within embodied inference, where goals become prior beliefs. For example, expected utility theory emerges as a special case of free energy minimization, where the sensitivity or inverse temperature (associated with softmax functions and quantal response equilibria) has a unique and Bayes-optimal solution. Crucially, this sensitivity corresponds to the precision of beliefs about behaviour. The changes in precision during variational updates are remarkably reminiscent of empirical dopaminergic responses-and they may provide a new perspective on the role of dopamine in assimilating reward prediction errors to optimize decision-making.

The Association Between Psychological Distress and Decision Regret During Armed Conflict Among Hospital Personnel.

PubMed

Ben-Ezra, Menachem; Bibi, Haim

2016-09-01

The association between psychological distress and decision regret during armed conflict among hospital personnel is of interest. The objective of this study was to learn of the association between psychological distress and decision regret during armed conflict. Data was collected from 178 hospital personnel in Barzilai Medical Center in Ashkelon, Israel during Operation Protective Edge. The survey was based on intranet data collection about: demographics, self-rated health, life satisfaction, psychological distress and decision regret. Among hospital personnel, having higher psychological distress and being young were associated with higher decision regret. This study adds to the existing knowledge by providing novel data about the association between psychological distress and decision regret among hospital personnel during armed conflict. This data opens a new venue of future research to other potentially detrimental factor on medical decision making and medical error done during crisis.

Liability of physicians supervising nonphysician clinicians.

PubMed

Paterick, Barbara B; Waterhouse, Blake E; Paterick, Timothy E; Sanbar, Sandy S

2014-01-01

Physicians confront a variety of liability issues when supervising nonphysician clinicians (NPC) including: (1) direct liability resulting from a failure to meet the state-defined standards of supervision/collaboration with NPCs; (2) vicarious liability, arising from agency law, where physicians are held accountable for NPC clinical care that does not meet the national standard of care; and (3) responsibility for medical errors when the NPC and physician are co-employees of the corporate enterprise. Physician-NPC co-employee relationships are highlighted because they are new and becoming predominant in existing healthcare models. Because of their novelty, there is a paucity of judicial decisions determining liability for NPC errors in this setting. Knowledge of the existence of these risks will allow physicians to make informed decisions on what relationships they will enter with NPCs and how these relationships will be structured and monitored.

Prefrontal neural correlates of memory for sequences.

PubMed

Averbeck, Bruno B; Lee, Daeyeol

2007-02-28

The sequence of actions appropriate to solve a problem often needs to be discovered by trial and error and recalled in the future when faced with the same problem. Here, we show that when monkeys had to discover and then remember a sequence of decisions across trials, ensembles of prefrontal cortex neurons reflected the sequence of decisions the animal would make throughout the interval between trials. This signal could reflect either an explicit memory process or a sequence-planning process that begins far in advance of the actual sequence execution. This finding extended to error trials such that, when the neural activity during the intertrial interval specified the wrong sequence, the animal also attempted to execute an incorrect sequence. More specifically, we used a decoding analysis to predict the sequence the monkey was planning to execute at the end of the fore-period, just before sequence execution. When this analysis was applied to error trials, we were able to predict where in the sequence the error would occur, up to three movements into the future. This suggests that prefrontal neural activity can retain information about sequences between trials, and that regardless of whether information is remembered correctly or incorrectly, the prefrontal activity veridically reflects the animal's action plan.

An MEG signature corresponding to an axiomatic model of reward prediction error.

PubMed

Talmi, Deborah; Fuentemilla, Lluis; Litvak, Vladimir; Duzel, Emrah; Dolan, Raymond J

2012-01-02

Optimal decision-making is guided by evaluating the outcomes of previous decisions. Prediction errors are theoretical teaching signals which integrate two features of an outcome: its inherent value and prior expectation of its occurrence. To uncover the magnetic signature of prediction errors in the human brain we acquired magnetoencephalographic (MEG) data while participants performed a gambling task. Our primary objective was to use formal criteria, based upon an axiomatic model (Caplin and Dean, 2008a), to determine the presence and timing profile of MEG signals that express prediction errors. We report analyses at the sensor level, implemented in SPM8, time locked to outcome onset. We identified, for the first time, a MEG signature of prediction error, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability. This signal followed earlier, separate signals for outcome valence and probability, which emerged approximately 200 ms after an outcome. Strikingly, the time course of the prediction error signal, as well as the early valence signal, resembled the Feedback-Related Negativity (FRN). In simultaneously acquired EEG data we obtained a robust FRN, but the win and loss signals that comprised this difference wave did not comply with the axiomatic model. Our findings motivate an explicit examination of the critical issue of timing embodied in computational models of prediction errors as seen in human electrophysiological data. Copyright © 2011 Elsevier Inc. All rights reserved.

Medication errors: definitions and classification

PubMed Central

Aronson, Jeffrey K

2009-01-01

To understand medication errors and to identify preventive strategies, we need to classify them and define the terms that describe them. The four main approaches to defining technical terms consider etymology, usage, previous definitions, and the Ramsey–Lewis method (based on an understanding of theory and practice). A medication error is ‘a failure in the treatment process that leads to, or has the potential to lead to, harm to the patient’. Prescribing faults, a subset of medication errors, should be distinguished from prescription errors. A prescribing fault is ‘a failure in the prescribing [decision-making] process that leads to, or has the potential to lead to, harm to the patient’. The converse of this, ‘balanced prescribing’ is ‘the use of a medicine that is appropriate to the patient's condition and, within the limits created by the uncertainty that attends therapeutic decisions, in a dosage regimen that optimizes the balance of benefit to harm’. This excludes all forms of prescribing faults, such as irrational, inappropriate, and ineffective prescribing, underprescribing and overprescribing. A prescription error is ‘a failure in the prescription writing process that results in a wrong instruction about one or more of the normal features of a prescription’. The ‘normal features’ include the identity of the recipient, the identity of the drug, the formulation, dose, route, timing, frequency, and duration of administration. Medication errors can be classified, invoking psychological theory, as knowledge-based mistakes, rule-based mistakes, action-based slips, and memory-based lapses. This classification informs preventive strategies. PMID:19594526

Heuristic Reasoning and Beliefs on Immigration: An Approach to an Intercultural Education Programme

ERIC Educational Resources Information Center

Navarro, Santiago Palacios; Lopez de Arechavaleta, Blanca Olalde

2010-01-01

People use mental shortcuts to simplify the amount of information they receive from the environment. Heuristic reasoning can be included among these mental shortcuts. In general, heuristics is useful for making fast decisions and judgements, but in certain cases, it may lead to systematic errors because some relevant aspects presented in the given…

A Tale of Two Tests (and of Two Examinees)

ERIC Educational Resources Information Center

Clauser, Amanda L.; Wainer, Howard

2016-01-01

It is widely accepted dogma that consequential decisions are better made with multiple measures, because using but a single one is thought more likely to be laden with biases and errors that can be better controlled with a wider source of evidence for making judgments. Unfortunately, advocates of using multiple measures too rarely provide detailed…

Individual Differences Underlying Pilot Cockpit Error

DTIC Science & Technology

1991-04-01

introverted than extroverted (Sellards, Corbi, & Sellards, 1989). The authors state: The introverted style is one of making decisions somewhat...environment, resulting in an accurate situational awareness, and introverts are better at tasks requiring diligence. Accordingly, extroverts could be...cited in Farmer, 1984) postulates that extroverts are under aroused and therefore seek stimulation; introverts are over aroused and thus avoid

Practical Functional Approach to Quality Assessment in Subtitling: "Pocahontas II--Case Study"

ERIC Educational Resources Information Center

Hussain, Alaa Eddin; Khuddro, Ahmad

2016-01-01

The present research work deals with subtitling errors encountered by simulators and proof-readers. The resultant work is of significant contribution to problem decision makings in the field of quality assessment of audiovisual translation (AVT). The outcome of this paper is the result of accumulated working experience in this domain. The relevant…

Divorce Injustices: Perceptions of Formerly Wealthy Women of the Stressors, Crises, and Traumas

ERIC Educational Resources Information Center

Rettig, Kathryn D.

2007-01-01

The current study was funded by the Minnesota Agricultural Experiment Station, Project 53-054 Decision Making Integral to Relationship Transitions in Families. The perspectives presented in the paper do not represent views of the funding agency and errors remain the sole responsibility of the author. This article is a major revision of a…

Aeronautical Decision Making for Instrument Pilots.

DTIC Science & Technology

1987-05-01

psychological stressors. o Sociological stressors include: a death in the family, divorce, sick child , demotion or pressure from your boss. Sociological...Error, Editors of Flying Weather Flying, Robert Buck Illusions, Richard Bach " The Bush Pilot Syndrome ," Dr. Michael Mitchell Briefs of Accidents, National... The Impulsivity Hazardous Attitude...........................35 The Invulnerability Hazardous Attitude ................. .... 37 The Macho Hazardous

Active Learning and Threshold Concepts in Multiple Testing That Can Further Develop Student Critical Statistical Thinking

ERIC Educational Resources Information Center

White, Desley

2015-01-01

Two practical activities are described, which aim to support critical thinking about statistics as they concern multiple outcomes testing. Formulae are presented in Microsoft Excel spreadsheets, which are used to calculate the inflation of error associated with the quantity of tests performed. This is followed by a decision-making exercise, where…

Communication for the Workplace: An Integrated Language Approach. Second Edition. Job Skills. Net Effect Series.

ERIC Educational Resources Information Center

Ettinger, Blanche; Perfetto, Edda

Using a developmental, hands-on approach, this text/workbook helps students master the basic English skills that are essential to write effective business correspondence, to recognize language errors, and to develop decision-making and problem-solving skills. Its step-by-step focus and industry-specific format encourages students to review,…

L1 Differences and L2 Similarities: Teaching Verb Tenses in English

ERIC Educational Resources Information Center

Collins, Laura

2007-01-01

In making decisions regarding the focus for grammar teaching, ESL instructors may take into consideration errors that appear to result from the influence of their students' first language(s) (L1). There is also evidence from language acquisition research suggesting that for some grammatical features, learners of different L1 backgrounds may face…

Skill Transfer and Virtual Training for IND Response Decision-Making: Game Design for Disaster Response Training

DTIC Science & Technology

2016-01-01

Guild Awards: Videogame Nominees,” Writer’s Guild of America, 2015. [Online]. Available: http://www.wga.org/wga-awards/nominees- winners.aspx... videogame . [Accessed 2015]. [22] S. Jackson, “Amazing Errors in Prototyping,” in Kobold Guide to Board Game Design, Open Design LLC / Wolfgang Baur, 2011

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.

Neuroscientific Model of Motivational Process

PubMed Central

Kim, Sung-il

2013-01-01

Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment. PMID:23459598

Neuroscientific model of motivational process.

PubMed

Kim, Sung-Il

2013-01-01

Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.

Characterising bias in regulatory risk and decision analysis: An analysis of heuristics applied in health technology appraisal, chemicals regulation, and climate change governance.

PubMed

MacGillivray, Brian H

2017-08-01

In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases; and basing decision rules on clearly articulated values and evidence, rather than convention. Copyright © 2017. Published by Elsevier Ltd.

Measurement Error and Environmental Epidemiology: A Policy Perspective

PubMed Central

Edwards, Jessie K.; Keil, Alexander P.

2017-01-01

Purpose of review Measurement error threatens public health by producing bias in estimates of the population impact of environmental exposures. Quantitative methods to account for measurement bias can improve public health decision making. Recent findings We summarize traditional and emerging methods to improve inference under a standard perspective, in which the investigator estimates an exposure response function, and a policy perspective, in which the investigator directly estimates population impact of a proposed intervention. Summary Under a policy perspective, the analysis must be sensitive to errors in measurement of factors that modify the effect of exposure on outcome, must consider whether policies operate on the true or measured exposures, and may increasingly need to account for potentially dependent measurement error of two or more exposures affected by the same policy or intervention. Incorporating approaches to account for measurement error into such a policy perspective will increase the impact of environmental epidemiology. PMID:28138941

First- and second-language phonological representations in the mental lexicon.

PubMed

Sebastian-Gallés, Núria; Rodríguez-Fornells, Antoni; de Diego-Balaguer, Ruth; Díaz, Begoña

2006-08-01

Performance-based studies on the psychological nature of linguistic competence can conceal significant differences in the brain processes that underlie native versus nonnative knowledge of language. Here we report results from the brain activity of very proficient early bilinguals making a lexical decision task that illustrates this point. Two groups of Spanish-Catalan early bilinguals (Spanish-dominant and Catalan-dominant) were asked to decide whether a given form was a Catalan word or not. The nonwords were based on real words, with one vowel changed. In the experimental stimuli, the vowel change involved a Catalan-specific contrast that previous research had shown to be difficult for Spanish natives to perceive. In the control stimuli, the vowel switch involved contrasts common to Spanish and Catalan. The results indicated that the groups of bilinguals did not differ in their behavioral and event-related brain potential measurements for the control stimuli; both groups made very few errors and showed a larger N400 component for control nonwords than for control words. However, significant differences were observed for the experimental stimuli across groups: Specifically, Spanish-dominant bilinguals showed great difficulty in rejecting experimental nonwords. Indeed, these participants not only showed very high error rates for these stimuli, but also did not show an error-related negativity effect in their erroneous nonword decisions. However, both groups of bilinguals showed a larger correct-related negativity when making correct decisions about the experimental nonwords. The results suggest that although some aspects of a second language system may show a remarkable lack of plasticity (like the acquisition of some foreign contrasts), first-language representations seem to be more dynamic in their capacity of adapting and incorporating new information.

The alcoholic brain: neural bases of impaired reward-based decision-making in alcohol use disorders.

PubMed

Galandra, Caterina; Basso, Gianpaolo; Cappa, Stefano; Canessa, Nicola

2018-03-01

Neuroeconomics is providing insights into the neural bases of decision-making in normal and pathological conditions. In the neuropsychiatric domain, this discipline investigates how abnormal functioning of neural systems associated with reward processing and cognitive control promotes different disorders, and whether such evidence may inform treatments. This endeavor is crucial when studying different types of addiction, which share a core promoting mechanism in the imbalance between impulsive subcortical neural signals associated with immediate pleasurable outcomes and inhibitory signals mediated by a prefrontal reflective system. The resulting impairment in behavioral control represents a hallmark of alcohol use disorders (AUDs), a chronic relapsing disorder characterized by excessive alcohol consumption despite devastating consequences. This review aims to summarize available magnetic resonance imaging (MRI) evidence on reward-related decision-making alterations in AUDs, and to envision possible future research directions. We review functional MRI (fMRI) studies using tasks involving monetary rewards, as well as MRI studies relating decision-making parameters to neurostructural gray- or white-matter metrics. The available data suggest that excessive alcohol exposure affects neural signaling within brain networks underlying adaptive behavioral learning via the implementation of prediction errors. Namely, weaker ventromedial prefrontal cortex activity and altered connectivity between ventral striatum and dorsolateral prefrontal cortex likely underpin a shift from goal-directed to habitual actions which, in turn, might underpin compulsive alcohol consumption and relapsing episodes despite adverse consequences. Overall, these data highlight abnormal fronto-striatal connectivity as a candidate neurobiological marker of impaired choice in AUDs. Further studies are needed, however, to unveil its implications in the multiple facets of decision-making.

Differential performance on tasks of affective processing and decision-making in patients with Panic Disorder and Panic Disorder with comorbid Major Depressive Disorder.

PubMed

Kaplan, Johanna S; Erickson, Kristine; Luckenbaugh, David A; Weiland-Fiedler, Petra; Geraci, Marilla; Sahakian, Barbara J; Charney, Dennis; Drevets, Wayne C; Neumeister, Alexander

2006-10-01

Neuropsychological studies have provided evidence for deficits in psychiatric disorders, such as schizophrenia and mood disorders. However, neuropsychological function in Panic Disorder (PD) or PD with a comorbid diagnosis of Major Depressive Disorder (MDD) has not been comprehensively studied. The present study investigated neuropsychological functioning in patients with PD and PD + MDD by focusing on tasks that assess attention, psychomotor speed, executive function, decision-making, and affective processing. Twenty-two unmedicated patients with PD, eleven of whom had a secondary diagnosis of MDD, were compared to twenty-two healthy controls, matched for gender, age, and intelligence on tasks of attention, memory, psychomotor speed, executive function, decision-making, and affective processing from the Cambridge Neuropsychological Test Automated Battery (CANTAB), Cambridge Gamble Task, and Affective Go/No-go Task. Relative to matched healthy controls, patients with PD + MDD displayed an attentional bias toward negatively-valenced verbal stimuli (Affective Go/No-go Task) and longer decision-making latencies (Cambridge Gamble Task). Furthermore, the PD + MDD group committed more errors on a task of memory and visual discrimination compared to their controls. In contrast, no group differences were found for PD patients relative to matched control subjects. The sample size was limited, however, all patients were drug-free at the time of testing. The PD + MDD patients demonstrated deficits on a task involving visual discrimination and working memory, and an attentional bias towards negatively-valenced stimuli. In addition, patients with comorbid depression provided qualitatively different responses in the areas of affective and decision-making processes.

You Are the Danger: Attenuated Insula Response in Methamphetamine Users During Aversive Interoceptive Decision-Making*

PubMed Central

Stewart, Jennifer L.; May, April C.; Poppa, Tasha; Davenport, Paul W.; Tapert, Susan F.; Paulus, Martin P.

2014-01-01

Background Drug dependent individuals often make drug-taking decisions when they do not feel well. Yet, few studies have examined the influence of an aversive state on decision-making related neural processing. Methods We investigate brain activation to decision-making during an aversive interoceptive challenge in methamphetamine users using functional magnetic resonance imaging (fMRI). Recently abstinent inpatients with methamphetamine use disorder (METH; n=20) and healthy comparison subjects (CTL; n=22) performed a two-choice prediction task at three fixed error rates (ER; 20%=reward, 50%=uncertainty, 80%=punishment) while anticipating and experiencing episodes of inspiratory breathing load during fMRI. Results METH exhibited higher trait anxiety in conjunction with lower anterior insula (AI) and inferior frontal gyrus (IFG) activation than CTL across trials. METH also showed lower posterior insula (PI) and anterior cingulate cortex (ACC) activation than CTL during breathing load independent of ER. For the crucial ER by interoception interaction, METH displayed lower ACC activation to punishment/loss than CTL during breathing load. Within METH, lower trait anxiety was linked to bilateral AI/IFG attenuation across trials. Conclusions AI/IFG attenuations in METH are suggestive of an executive functioning deficit, particularly in users with low anxiety, reflecting reduced resources allocated to choice selection. In contrast, PI/ACC reductions in METH appear specific to impairments in registering and evaluating interoceptive experiences. Taken together, inadequate activation of brain areas that are important for regulating when one does not feel well may be the neural basis for poor decision-making by METH. PMID:24993186

From the shadows into the light: How pretrial publicity and deliberation affect mock jurors' decisions, impressions, and memory.

PubMed

Ruva, Christine L; Guenther, Christina C

2015-06-01

This 2-part study explored how exposure to negative pretrial publicity (Neg-PTP) influences the jury process, as well as possible mechanisms responsible for its biasing effects on decisions. Study Part A explored how PTP and jury deliberations affect juror/jury verdicts, memory, and impressions of the defendant and attorneys. One week before viewing a criminal trial mock-jurors (N = 320 university students) were exposed to Neg-PTP or unrelated crime stories (No-PTP). Two days later deliberating jurors came to a group decision, whereas nondeliberating jurors completed an unrelated task before making an individual decision. Neg-PTP jurors were more likely to vote guilty, make memory errors, and rate the defendant lower in credibility. Deliberation reduced Neg-PTP jurors' memory accuracy and No-PTP jurors' guilty verdicts (leniency bias). Jurors' memory and ratings of the defendant and prosecuting attorney significantly mediated the effect of PTP on guilt ratings. Study Part B content analyzed 30 mock-jury deliberations and explored how PTP influenced deliberations and ultimately jury decisions. Neg-PTP juries were more likely than No-PTP juries to discuss ambiguous trial evidence in a proprosecution manner and less likely to discuss judicial instructions and lack of evidence. All Neg-PTP juries mentioned PTP, after instructed otherwise, and rarely corrected jury members who mentioned PTP. Discussion of ambiguous trial evidence in a proprosecution manner and lack of evidence significantly mediated the effect of PTP on jury-level guilt ratings. Together the findings suggest that judicial admonishments and deliberations may not be sufficient to reduce PTP bias, because of memory errors, biased impressions, and predecisional distortion. (c) 2015 APA, all rights reserved).

A model of supervisor decision-making in the accommodation of workers with low back pain

PubMed Central

Williams-Whitt, Kelly; Kristman, Vicki; Shaw, William S.; Soklaridis, Sophie; Reguly, Paula

2016-01-01

PURPOSE To explore supervisors’ perspectives and decision-making processes in the accommodation of back injured workers. METHODS Twenty-three semi-structured, in-depth interviews were conducted with supervisors from eleven Canadian organizations about their role in providing job accommodations. Supervisors were identified through an on-line survey and interviews were recorded, transcribed and entered into NVivo software. The initial analyses identified common units of meaning, which were used to develop a coding guide. Interviews were coded, and a model of supervisor decision-making was developed based on the themes, categories and connecting ideas identified in the data. RESULTS The decision-making model includes a process element that is described as iterative “trial and error” decision-making. Medical restrictions are compared to job demands, employee abilities and available alternatives. A feasible modification is identified through brainstorming and then implemented by the supervisor. Resources used for brainstorming include information, supervisor experience and autonomy, and organizational supports. The model also incorporates the experience of accommodation as a job demand that causes strain for the supervisor. Accommodation demands affect the supervisor’s attitude, brainstorming and monitoring effort and communication with returning employees. Resources and demands have a combined effect on accommodation decision complexity, which in turn affects the quality of the accommodation option selected. If the employee is unable to complete the tasks or is reinjured during the accommodation, the decision cycle repeats. More frequent iteration through the trial and error process reduces the likelihood of return to work success. CONCLUSIONS A series of propositions is developed to illustrate the relationships among categories in the model. The model and propositions show: a) the iterative, problem solving nature of the RTW process; b) decision resources necessary for accommodation planning, and c) the impact accommodation demands may have on supervisors and RTW quality. PMID:26811170

Case-based clinical reasoning in feline medicine: 3: Use of heuristics and illness scripts.

PubMed

Whitehead, Martin L; Canfield, Paul J; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-05-01

This is Article 3 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. Article 1, published in the January 2016 issue of JFMS, discussed the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). In Article 2, published in the March 2016 issue, ways of managing cognitive error, particularly the negative impact of bias, in making a diagnosis were examined. This final article explores the use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Uncertainty quantification in downscaling procedures for effective decisions in energy systems

NASA Astrophysics Data System (ADS)

Constantinescu, E. M.

2010-12-01

Weather is a major driver both of energy supply and demand, and with the massive adoption of renewable energy sources and changing economic and producer-consumer paradigms, the management of the next-generation energy systems is becoming ever more challenging. The operational and planning decisions in energy systems are guided by efficiency and reliability, and therefore a central role in these decisions will be played by the ability to obtain weather condition forecasts with accurate uncertainty estimates. The appropriate temporal and spatial resolutions needed for effective decision-making, be it operational or planning, is not clear. It is arguably certain however, that such temporal scales as hourly variations of temperature or wind conditions and ramp events are essential in this process. Planning activities involve decade or decades-long projections of weather. One sensible way to achieve this is to embed regional weather models in a global climate system. This strategy acts as a downscaling procedure. Uncertainty modeling techniques must be developed in order to quantify and minimize forecast errors as well as target variables that impact the decision-making process the most. We discuss the challenges of obtaining a realistic uncertainty quantification estimate using mathematical algorithms based on scalable matrix-free computations and physics-based statistical models. The process of making decisions for energy management systems based on future weather scenarios is a very complex problem. We shall focus on the challenges in generating wind power predictions based on regional weather predictions, and discuss the implications of making the common assumptions about the uncertainty models.

Heuristic reasoning and cognitive biases: Are they hindrances to judgments and decision making in orthodontics?

PubMed

Hicks, E Preston; Kluemper, G Thomas

2011-03-01

Studies show that our brains use 2 modes of reasoning: heuristic (intuitive, automatic, implicit processing) and analytic (deliberate, rule-based, explicit processing). The use of intuition often dominates problem solving when innovative, creative thinking is required. Under conditions of uncertainty, we default to an even greater reliance on the heuristic processing. In health care settings and other such environments of increased importance, this mode becomes problematic. Since choice heuristics are quickly constructed from fragments of memory, they are often biased by prior evaluations of and preferences for the alternatives being considered. Therefore, a rigorous and systematic decision process notwithstanding, clinical judgments under uncertainty are often flawed by a number of unwitting biases. Clinical orthodontics is as vulnerable to this fundamental failing in the decision-making process as any other health care discipline. Several of the more common cognitive biases relevant to clinical orthodontics are discussed in this article. By raising awareness of these sources of cognitive errors in our clinical decision making, our intent was to equip the clinician to take corrective action to avoid them. Our secondary goal was to expose this important area of empirical research and encourage those with expertise in the cognitive sciences to explore, through further research, the possible relevance and impact of cognitive heuristics and biases on the accuracy of orthodontic judgments and decision making. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Medicine, psychiatry and euthanasia: an argument against mandatory psychiatric review.

PubMed

Parker, M

2000-04-01

The paper critically appraises the argument that requests for active assistance to die should be subject to mandatory psychiatric assessment. The argument for mandatory psychiatric assessment is usually supported by an appeal to the need for safeguards against errors and omissions in both the diagnosis of psychiatric conditions affecting the terminally ill and the exploration of the meanings of their requests. This intuitively appealing view is challenged through a broader analysis which examines connections between medicine's traditional adherence to the moral distinction between acts and omissions and the following issues: the historical relationship between medical practice and dying, the recent development of research into treatment-withdrawal decisions, the scientific status of psychiatry, the logic of rationality and decision-making competence. The analysis reveals a number of hitherto unexamined and unacknowledged influences which would make psychiatric review of requests for assisted death a much less objective and impartial process than is assumed. Mandatory psychiatric review is an instance of the medicalisation of death and dying which could abridge the freedom of certain individuals to make decisions about their deaths.

Pattern of eyelid motion predictive of decision errors during drowsiness: oculomotor indices of altered states.

PubMed

Lobb, M L; Stern, J A

1986-08-01

Sequential patterns of eye and eyelid motion were identified in seven subjects performing a modified serial probe recognition task under drowsy conditions. Using simultaneous EOG and video recordings, eyelid motion was divided into components above, within, and below the pupil and the durations in sequence were recorded. A serial probe recognition task was modified to allow for distinguishing decision errors from attention errors. Decision errors were found to be more frequent following a downward shift in the gaze angle which the eyelid closing sequence was reduced from a five element to a three element sequence. The velocity of the eyelid moving over the pupil during decision errors was slow in the closing and fast in the reopening phase, while on decision correct trials it was fast in closing and slower in reopening. Due to the high variability of eyelid motion under drowsy conditions these findings were only marginally significant. When a five element blink occurred, the velocity of the lid over pupil motion component of these endogenous eye blinks was significantly faster on decision correct than on decision error trials. Furthermore, the highly variable, long duration closings associated with the decision response produced slow eye movements in the horizontal plane (SEM) which were more frequent and significantly longer in duration on decision error versus decision correct responses.

Decisions without blinders.

PubMed

Bazerman, Max H; Chugh, Dolly

2006-01-01

By the time Merck withdrew its pain relief drug Vioxx from the market in 2004, more than 100 million prescriptions had been filled in the United States alone. Yet researchers now estimate that Vioxx may have been associated with as many as 25,000 heart attacks and strokes. Evidence of the drug's risks was available as early as 2000, so why did so many doctors keep prescribing it? The answer, say the authors, involves the phenomenon of bounded awareness--when cognitive blinders prevent a person from seeing, seeking, using, or sharing highly relevant, easily accessible, and readily perceivable information during the decision-making process. Doctors prescribing Vioxx, for instance, more often than not received positive feedback from patients. So, despite having access to information about the risks, physicians may have been blinded to the actual extent of the risks. Bounded awareness can occur at three points in the decision-making process. First, executives may fail to see or seek out the important information needed to make a sound decision. Second, they may fail to use the information that they do see because they aren't aware of its relevance. Third, executives may fail to share information with others, thereby bounding the organization's awareness. Drawing on examples such as the Challenger disaster and Citibank's failures in Japan, this article examines what prevents executives from seeing what's right in front of them and offers advice on how to increase awareness. Of course, not every decision requires executives to consciously broaden their focus. Collecting too much information for every decision would waste time and other valuable resources. The key is being mindful. If executives think an error could generate almost irrecoverable damage, then they should insist on getting all the information they need to make a wise decision.

Autonomous mechanism of internal choice estimate underlies decision inertia.

PubMed

Akaishi, Rei; Umeda, Kazumasa; Nagase, Asako; Sakai, Katsuyuki

2014-01-08

Our choice is influenced by choices we made in the past, but the mechanism responsible for the choice bias remains elusive. Here we show that the history-dependent choice bias can be explained by an autonomous learning rule whereby an estimate of the likelihood of a choice to be made is updated in each trial by comparing between the actual and expected choices. We found that in perceptual decision making without performance feedback, a decision on an ambiguous stimulus is repeated on the subsequent trial more often than a decision on a salient stimulus. This inertia of decision was not accounted for by biases in motor response, sensory processing, or attention. The posterior cingulate cortex and frontal eye field represent choice prediction error and choice estimate in the learning algorithm, respectively. Interactions between the two regions during the intertrial interval are associated with decision inertia on a subsequent trial. Copyright © 2014 Elsevier Inc. All rights reserved.

Individual differences in the anterior insula are associated with the likelihood of financially helping versus harming others.

PubMed

Greening, Steven; Norton, Loretta; Virani, Karim; Ty, Ambrose; Mitchell, Derek; Finger, Elizabeth

2014-03-01

The neural basis of individual differences in positive and negative social decisions and behaviors in healthy populations is yet undetermined. Recent work has focused on the potential role of the anterior insula in guiding social and nonsocial decision making, but the specific nature of its activation during such decision making remains unclear. To identify the neural regions mediating individual differences in helpful and harmful decisions and to assess the nature of insula activation during such decisions, in the present study we used a novel fMRI task featuring intentional and unintentional decisions to financially harm or help persons in need. Based on a whole-brain, unbiased approach, our findings indicate that individual differences in dorsal anterior insula, anterior cingulate cortex (ACC), and right temporo-parietal junction activation are associated with behavioral tendencies to financially harm or help another. Furthermore, activity in the dorsal anterior insula and ACC was greatest during unintended outcomes, whether these were gains or losses for a charity or for oneself, supporting models of the role of these regions in salience prediction error signaling. Together, the results suggest that individual differences in risk anticipation, as reflected in the dorsal anterior insula and dorsal ACC, guide social decisions to refrain from harming others.

Future of electronic health records: implications for decision support.

PubMed

Rothman, Brian; Leonard, Joan C; Vigoda, Michael M

2012-01-01

The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data in real-time for decision support and process automation has the potential to both reduce costs and improve the quality of patient care. © 2012 Mount Sinai School of Medicine.

An image-guided radiotherapy decision support framework incorporating a Bayesian network and visualization tool.

PubMed

Hargrave, Catriona; Deegan, Timothy; Bednarz, Tomasz; Poulsen, Michael; Harden, Fiona; Mengersen, Kerrie

2018-05-17

To describe a Bayesian network (BN) and complementary visualization tool that aim to support decision-making during online cone-beam computed tomography (CBCT)-based image-guided radiotherapy (IGRT) for prostate cancer patients. The BN was created to represent relationships between observed prostate, proximal seminal vesicle (PSV), bladder and rectum volume variations, an image feature alignment score (FAS TV _ OAR ), delivered dose, and treatment plan compliance (TPC). Variables influencing tumor volume (TV) targeting accuracy such as intrafraction motion, and contouring and couch shift errors were also represented. A score of overall TPC (FAS global ) and factors such as image quality were used to inform the BN output node providing advice about proceeding with treatment. The BN was quantified using conditional probabilities generated from published studies, FAS TV _ OAR /global modeling, and a survey of IGRT decision-making practices. A new IGRT visualization tool (IGRT REV ), in the form of Mollweide projection plots, was developed to provide a global summary of residual errors after online CBCT-planning CT registration. Sensitivity and scenario analyses were undertaken to evaluate the performance of the BN and the relative influence of the network variables on TPC and the decision to proceed with treatment. The IGRT REV plots were evaluated in conjunction with the BN scenario testing, using additional test data generated from retrospective CBCT-planning CT soft-tissue registrations for 13/36 patients whose data were used in the FAS TV _ OAR /global modeling. Modeling of the TV targeting errors resulted in a very low probability of corrected distances between the CBCT and planning CT prostate or PSV volumes being within their thresholds. Strength of influence evaluation with and without the BN TV targeting error nodes indicated that rectum- and bladder-related network variables had the highest relative importance. When the TV targeting error nodes were excluded from the BN, TPC was sensitive to observed PSV and rectum variations while the decision to treat was sensitive to observed prostate and PSV variations. When root nodes were set so the PSV and rectum variations exceeded thresholds, the probability of low TPC increased to 40%. Prostate and PSV variations exceeding thresholds increased the likelihood of repositioning or repeating patient preparation to 43%. Scenario testing using the test data from 13 patients, demonstrated two cases where the BN provided increased high TPC probabilities, despite some of the prostate and PSV volume variation metrics not being within tolerance. The IGRT REV tool was effective in highlighting and quantifying where TV and OAR variations occurred, supporting the BN recommendation to reposition the patient or repeat their bladder and bowel preparation. In another case, the IGRT REV tool was also effective in highlighting where PSV volume variation significantly exceeded tolerance when the BN had indicated to proceed with treatment. This study has demonstrated that both the BN and IGRT REV plots are effective tools for inclusion in a decision support system for online CBCT-based IGRT for prostate cancer patients. Alternate approaches to modeling TV targeting errors need to be explored as well as extension of the BN to support offline IGRT decisions related to adaptive radiotherapy. © 2018 American Association of Physicists in Medicine.

Error Analysis of CM Data Products Sources of Uncertainty

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

Hunt, Brian D.; Eckert-Gallup, Aubrey Celia; Cochran, Lainy Dromgoole

This goal of this project is to address the current inability to assess the overall error and uncertainty of data products developed and distributed by DOE’s Consequence Management (CM) Program. This is a widely recognized shortfall, the resolution of which would provide a great deal of value and defensibility to the analysis results, data products, and the decision making process that follows this work. A global approach to this problem is necessary because multiple sources of error and uncertainty contribute to the ultimate production of CM data products. Therefore, this project will require collaboration with subject matter experts across amore » wide range of FRMAC skill sets in order to quantify the types of uncertainty that each area of the CM process might contain and to understand how variations in these uncertainty sources contribute to the aggregated uncertainty present in CM data products. The ultimate goal of this project is to quantify the confidence level of CM products to ensure that appropriate public and worker protections decisions are supported by defensible analysis.« less

HL7 Structured Product Labeling - electronic prescribing information for provider order entry decision support.

PubMed

Schadow, Gunther

2005-01-01

Prescribing errors are an important cause of adverse events, and lack of knowledge of the drug is a root cause for prescribing errors. The FDA is issuing new regulations that will make the drug labels much more useful not only to physicians, but also to computerized order entry systems that support physicians to practice safe prescribing. For this purpose, FDA works with HL7 to create the Structured Product Label (SPL) standard that includes a document format as well as a drug knowledge representation, this poster introduces the basic concepts of SPL.

[Error prevention through management of complications in urology: standard operating procedures from commercial aviation as a model].

PubMed

Kranz, J; Sommer, K-J; Steffens, J

2014-05-01

Patient safety and risk/complication management rank among the current megatrends in modern medicine, which has undoubtedly become more complex. In time-critical, error-prone and difficult situations, which often occur repeatedly in everyday clinical practice, guidelines are inappropriate for acting rapidly and intelligently. With the establishment and consistent use of standard operating procedures like in commercial aviation, a possible strategic approach is available. These medical aids to decision-making - quick reference cards - are short, optimized instructions that enable a standardized procedure in case of medical claims.

Expanding the base for teaching of percutaneous coronary interventions: the explicit approach.

PubMed

Lanzer, Peter; Prechelt, Lutz

2011-02-15

Accelerate and improve the training and learning process of operators performing percutaneous coronary interventions (PCI). Operator cognitive, in particular decision-making skills and technical skills are a major factor for the success of coronary interventions. Currently, cognitive skills are commonly developed by three methods: (1) Cognitive learning of rules for which statistical evidence is available. This is very incomprehensive and isolates cognitive learning from skill acquisition. (2) Informal tutoring received from experienced operators, and (3) personal experience by trial-and-error are both very slow. We propose in this concept article a conceptual framework to elicit, capture, and transfer expert PCI skills to complement the current approach. This includes the development of an in-depth understanding of the nature of PCI skills, terminology, and nomenclature needed to streamline communication, propensity of reproducible performance assessment, and in particular an explication of intervention planning and intra-intervention decision-making. We illustrate the impact of improved decision-making by simulation results based on a stochastic model of intervention risk. We identify several key concepts that form the basis of this conceptual framework, in particular different risk types and the notions of strategy, interventional module, and tactic. The increasing complexity of cases have brought PCI to the point where the decision-making skills of master operators need to be made explicit to make them systematically learnable such that the skills of beginner and intermediate operators can be improved much faster than is currently possible. Copyright © 2010 Wiley-Liss, Inc.

Pupil dilation signals uncertainty and surprise in a learning gambling task.

PubMed

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2013-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.

Pupil dilation signals uncertainty and surprise in a learning gambling task

PubMed Central

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2014-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

NASA Astrophysics Data System (ADS)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

Repeatability and Reproducibility of Decisions by Latent Fingerprint Examiners

PubMed Central

Ulery, Bradford T.; Hicklin, R. Austin; Buscaglia, JoAnn; Roberts, Maria Antonia

2012-01-01

The interpretation of forensic fingerprint evidence relies on the expertise of latent print examiners. We tested latent print examiners on the extent to which they reached consistent decisions. This study assessed intra-examiner repeatability by retesting 72 examiners on comparisons of latent and exemplar fingerprints, after an interval of approximately seven months; each examiner was reassigned 25 image pairs for comparison, out of total pool of 744 image pairs. We compare these repeatability results with reproducibility (inter-examiner) results derived from our previous study. Examiners repeated 89.1% of their individualization decisions, and 90.1% of their exclusion decisions; most of the changed decisions resulted in inconclusive decisions. Repeatability of comparison decisions (individualization, exclusion, inconclusive) was 90.0% for mated pairs, and 85.9% for nonmated pairs. Repeatability and reproducibility were notably lower for comparisons assessed by the examiners as “difficult” than for “easy” or “moderate” comparisons, indicating that examiners' assessments of difficulty may be useful for quality assurance. No false positive errors were repeated (n = 4); 30% of false negative errors were repeated. One percent of latent value decisions were completely reversed (no value even for exclusion vs. of value for individualization). Most of the inter- and intra-examiner variability concerned whether the examiners considered the information available to be sufficient to reach a conclusion; this variability was concentrated on specific image pairs such that repeatability and reproducibility were very high on some comparisons and very low on others. Much of the variability appears to be due to making categorical decisions in borderline cases. PMID:22427888

Using cognitive task analysis to identify critical decisions in the laparoscopic environment.

PubMed

Craig, Curtis; Klein, Martina I; Griswold, John; Gaitonde, Krishnanath; McGill, Thomas; Halldorsson, Ari

2012-12-01

The aim of this study was to identify the critical decisions surgeons need to make regarding laparoscopic surgery, the information these decisions are based on, the strategies employed by surgeons to reach their objectives, and the difficulties experienced by novices. Laparoscopic training focuses on the development of technical skills. However, successful surgical outcomes are also dependent on appropriate decisions made during surgery, which are influenced by critical cues and the use of appropriate strategies. Novices might not be as adept at cue detection and strategy use. Participants were eight attending surgeons. The authors employed task-analytic techniques to identify critical decisions inherent in laparoscopy and the cues, strategies, and novice traps associated with these decisions. The authors used decision requirements tables to organize the data into the key decisions made during the preoperative, operative, and postoperative phases as well as the cues, strategies, and novice traps associated with these decisions. Key decisions identified for the preoperative phase included but were not limited to the decision of performing a laparoscopic versus open surgery, necessity to review the literature, practicing the procedure, and trocar placement. Some key decisions identified for the operative phase included converting to open surgery, performing angiograms, cutting tissue or organs, and reevaluation of the approach. Only one key decision was identified for the postoperative phrase: whether the surgeon's technique needs to be evaluated and revised. The laparoscopic environment requires complex decision making, and novices are prone to errors in their decisions. The information elicited in this study is applicable to laparoscopic training.

Eyewitness identification evidence and innocence risk.

PubMed

Clark, Steven E; Godfrey, Ryan D

2009-02-01

It is well known that the frailties of human memory and vulnerability to suggestion lead to eyewitness identification errors. However, variations in different aspects of the eyewitnessing conditions produce different kinds of errors that are related to wrongful convictions in very different ways. We present a review of the eyewitness identification literature, organized around underlying cognitive mechanisms, memory, similarity, and decision processes, assessing the effects on both correct and mistaken identification. In addition, we calculate a conditional probability we call innocence risk, which is the probability that the suspect is innocent, given that the suspect was identified. Assessment of innocence risk is critical to the theoretical development of eyewitness identification research, as well as to legal decision making and policy evaluation. Our review shows a complex relationship between misidentification and innocence risk, sheds light on some areas of controversy, and suggests that some issues thought to be resolved are in need of additional research.

Decision support tool for diagnosing the source of variation

NASA Astrophysics Data System (ADS)

Masood, Ibrahim; Azrul Azhad Haizan, Mohamad; Norbaya Jumali, Siti; Ghazali, Farah Najihah Mohd; Razali, Hazlin Syafinaz Md; Shahir Yahya, Mohd; Azlan, Mohd Azwir bin

2017-08-01

Identifying the source of unnatural variation (SOV) in manufacturing process is essential for quality control. The Shewhart control chart patterns (CCPs) are commonly used to monitor the SOV. However, a proper interpretation of CCPs associated to its SOV requires a high skill industrial practitioner. Lack of knowledge in process engineering will lead to erroneous corrective action. The objective of this study is to design the operating procedures of computerized decision support tool (DST) for process diagnosis. The DST is an embedded tool in CCPs recognition scheme. Design methodology involves analysis of relationship between geometrical features, manufacturing process and CCPs. The DST contents information about CCPs and its possible root cause error and description on SOV phenomenon such as process deterioration in tool bluntness, offsetting tool, loading error, and changes in materials hardness. The DST will be useful for an industrial practitioner in making effective troubleshooting.

Memory and decision making in the frontal cortex during visual motion processing for smooth pursuit eye movements.

PubMed

Shichinohe, Natsuko; Akao, Teppei; Kurkin, Sergei; Fukushima, Junko; Kaneko, Chris R S; Fukushima, Kikuro

2009-06-11

Cortical motor areas are thought to contribute "higher-order processing," but what that processing might include is unknown. Previous studies of the smooth pursuit-related discharge of supplementary eye field (SEF) neurons have not distinguished activity associated with the preparation for pursuit from discharge related to processing or memory of the target motion signals. Using a memory-based task designed to separate these components, we show that the SEF contains signals coding retinal image-slip-velocity, memory, and assessment of visual motion direction, the decision of whether to pursue, and the preparation for pursuit eye movements. Bilateral muscimol injection into SEF resulted in directional errors in smooth pursuit, errors of whether to pursue, and impairment of initial correct eye movements. These results suggest an important role for the SEF in memory and assessment of visual motion direction and the programming of appropriate pursuit eye movements.

Case-based clinical reasoning in feline medicine: 1: Intuitive and analytical systems.

PubMed

Canfield, Paul J; Whitehead, Martin L; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-01-01

This is Article 1 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. This first article discusses the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). Articles 2 and 3, to appear in the March and May 2016 issues of JFMS, respectively, will examine managing cognitive error, and use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Decision Making Training in the Mission Operations Directorate

NASA Technical Reports Server (NTRS)

O'Keefe, William S.

2013-01-01

At JSC, we train our new flight controllers on a set of team skills that we call Space Flight Resource Management (SFRM). SFRM is akin to Crew Resource Management for the airlines and trains flight controllers to work as an effective team to reduce errors and improve safety. We have developed this training over the years with the assistance of Ames Research Center, Wyle Labs and University of Central Florida. One of the skills we teach is decision making/ problem solving (DM/PS). We teach DM/PS first in several classroom sessions, reinforce it in several part task training environments, and finally practice it in full-mission, full-team simulations. What I am proposing to talk about is this training flow: its content and how we teach it.

Investigating industrial investigation: examining the impact of a priori knowledge and tunnel vision education.

PubMed

Maclean, Carla L; Brimacombe, C A Elizabeth; Lindsay, D Stephen

2013-12-01

The current study addressed tunnel vision in industrial incident investigation by experimentally testing how a priori information and a human bias (generated via the fundamental attribution error or correspondence bias) affected participants' investigative behavior as well as the effectiveness of a debiasing intervention. Undergraduates and professional investigators engaged in a simulated industrial investigation exercise. We found that participants' judgments were biased by knowledge about the safety history of either a worker or piece of equipment and that a human bias was evident in participants' decision making. However, bias was successfully reduced with "tunnel vision education." Professional investigators demonstrated a greater sophistication in their investigative decision making compared to undergraduates. The similarities and differences between these two populations are discussed. (c) 2013 APA, all rights reserved

Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback

PubMed Central

Whitney, Paul; Hinson, John M.; Jackson, Melinda L.; Van Dongen, Hans P.A.

2015-01-01

Study Objectives: To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Design: Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Setting: Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Subjects: Twenty-six subjects (22–40 y of age; 10 women). Interventions: Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Results: Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Conclusions: Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information. Citation: Whitney P, Hinson JM, Jackson ML, Van Dongen HPA. Feedback blunting: total sleep deprivation impairs decision making that requires updating based on feedback. SLEEP 2015;38(5):745–754. PMID:25515105

A Novel Approach to Study Medical Decision Making in the Clinical Setting: The "Own-point-of-view" Perspective.

PubMed

Pelaccia, Thierry; Tardif, Jacques; Triby, Emmanuel; Charlin, Bernard

2017-07-01

Making diagnostic and therapeutic decisions is a critical activity among physicians. It relies on the ability of physicians to use cognitive processes and specific knowledge in the context of a clinical reasoning. This ability is a core competency in physicians, especially in the field of emergency medicine where the rate of diagnostic errors is high. Studies that explore medical decision making in an authentic setting are increasing significantly. They are based on the use of qualitative methods that are applied at two separate times: 1) a video recording of the subject's actual activity in an authentic setting and 2) an interview with the subject, supported by the video recording. Traditionally, activity is recorded from an "external perspective"; i.e., a camera is positioned in the room in which the consultation takes place. This approach has many limits, both technical and with respect to the validity of the data collected. The article aims at 1) describing how decision making is currently being studied, especially from a qualitative standpoint, and the reasons why new methods are needed, and 2) reporting how we used an original, innovative approach to study decision making in the field of emergency medicine and findings from these studies to guide further the use of this method. The method consists in recording the subject's activity from his own point of view, by fixing a microcamera on his temple or the branch of his glasses. An interview is then held on the basis of this recording, so that the subject being interviewed can relive the situation, to facilitate the explanation of his reasoning with respect to his decisions and actions. We describe how this method has been used successfully in investigating medical decision making in emergency medicine. We provide details on how to use it optimally, taking into account the constraints associated with the practice of emergency medicine and the benefits in the study of clinical reasoning. The "own-point-of-view" video technique is a promising method to study clinical decision making in emergency medicine. It is a powerful tool to stimulate recall and help physicians make their reasoning explicit, thanks to a greater psychological immersion. © 2017 by the Society for Academic Emergency Medicine.

Family matters: dyadic agreement in end-of-life medical decision making.

PubMed

Schmid, Bettina; Allen, Rebecca S; Haley, Philip P; Decoster, Jamie

2010-04-01

We examined race/ethnicity and cultural context within hypothetical end-of-life medical decision scenarios and its influence on patient-proxy agreement. Family dyads consisting of an older adult and 1 family member, typically an adult child, responded to questions regarding the older adult's preferences for cardiopulmonary resuscitation, artificial feeding and fluids, and palliative care in hypothetical illness scenarios. The responses of 34 Caucasian dyads and 30 African American dyads were compared to determine the extent to which family members could accurately predict the treatment preferences of their older relative. We found higher treatment preference agreement among African American dyads compared with Caucasian dyads when considering overall raw difference scores (i.e., overtreatment errors can compensate for undertreatment errors). Prior advance care planning moderated the effect such that lower levels of advance care planning predicted undertreatment errors among African American proxies and overtreatment errors among Caucasian proxies. In contrast, no racial/ethnic differences in treatment preference agreement were found within absolute difference scores (i.e., total error, regardless of the direction of error). This project is one of the first to examine the mediators and moderators of dyadic racial/cultural differences in treatment preference agreement for end-of-life care in hypothetical illness scenarios. Future studies should use mixed method approaches to explore underlying factors for racial differences in patient-proxy agreement as a basis for developing culturally sensitive interventions to reduce racial disparities in end-of-life care options.

Human factors in surgery: from Three Mile Island to the operating room.

PubMed

D'Addessi, Alessandro; Bongiovanni, Luca; Volpe, Andrea; Pinto, Francesco; Bassi, PierFrancesco

2009-01-01

Human factors is a definition that includes the science of understanding the properties of human capability, the application of this understanding to the design and development of systems and services, the art of ensuring their successful applications to a program. The field of human factors traces its origins to the Second World War, but Three Mile Island has been the best example of how groups of people react and make decisions under stress: this nuclear accident was exacerbated by wrong decisions made because the operators were overwhelmed with irrelevant, misleading or incorrect information. Errors and their nature are the same in all human activities. The predisposition for error is so intrinsic to human nature that scientifically it is best considered as inherently biologic. The causes of error in medical care may not be easily generalized. Surgery differs in important ways: most errors occur in the operating room and are technical in nature. Commonly, surgical error has been thought of as the consequence of lack of skill or ability, and is the result of thoughtless actions. Moreover the 'operating theatre' has a unique set of team dynamics: professionals from multiple disciplines are required to work in a closely coordinated fashion. This complex environment provides multiple opportunities for unclear communication, clashing motivations, errors arising not from technical incompetence but from poor interpersonal skills. Surgeons have to work closely with human factors specialists in future studies. By improving processes already in place in many operating rooms, safety will be enhanced and quality increased.

Perspective: Uses and misuses of thresholds in diagnostic decision making.

PubMed

Warner, Jeremy L; Najarian, Robert M; Tierney, Lawrence M

2010-03-01

The concept of thresholds plays a vital role in decisions involving the initiation, continuation, and completion of diagnostic testing. Much research has focused on the development of explicit thresholds, in the form of practice guidelines and decision analyses. However, these tools are used infrequently; most medical decisions are made at the bedside, using implicit thresholds. Study of these thresholds can lead to a deeper understanding of clinical decision making. The authors examine some factors constituting individual clinicians' implicit thresholds. They propose a model for static thresholds using the concept of situational gravity to explain why some thresholds are high, and some low. Next, they consider the hypothetical effects of incorrect placement of thresholds (miscalibration) and changes to thresholds during diagnosis (manipulation). They demonstrate these concepts using common clinical scenarios. Through analysis of miscalibration of thresholds, the authors demonstrate some common maladaptive clinical behaviors, which are nevertheless internally consistent. They then explain how manipulation of thresholds gives rise to common cognitive heuristics including premature closure and anchoring. They also discuss the case where no threshold has been exceeded despite exhaustive collection of data, which commonly leads to application of the availability or representativeness heuristics. Awareness of implicit thresholds allows for a more effective understanding of the processes of medical decision making and, possibly, to the avoidance of detrimental heuristics and their associated medical errors. Research toward accurately defining these thresholds for individual physicians and toward determining their dynamic properties during the diagnostic process may yield valuable insights.

The impact of disappointment in decision making: inter-individual differences and electrical neuroimaging.

PubMed

Tzieropoulos, Hélène; de Peralta, Rolando Grave; Bossaerts, Peter; Gonzalez Andino, Sara L

2011-01-01

Disappointment, the emotion experienced when faced to reward prediction errors (RPEs), considerably impacts decision making (DM). Individuals tend to modify their behavior in an often unpredictable way just to avoid experiencing negative emotions. Despite its importance, disappointment remains much less studied than regret and its impact on upcoming decisions largely unexplored. Here, we adapted the Trust Game to effectively elicit, quantify, and isolate disappointment by relying on the formal definition provided by Bell's in economics. We evaluated the effects of experienced disappointment and elation on future cooperation and trust as well as the rationality and utility of the different behavioral and neural mechanisms used to cope with disappointment. All participants in our game trusted less and particularly expected less from unknown opponents as a result of disappointing outcomes in the previous trial but not necessarily after elation indicating that behavioral consequences of positive and negative RPEs are not the same. A large variance in the tolerance to disappointment was observed across subjects, with some participants needing only a small disappointment to impulsively bias their subsequent decisions. As revealed by high-density EEG recordings the most tolerant individuals - who thought twice before making a decision and earned more money - relied on different neural generators to contend with neutral and unexpected outcomes. This study thus provides some support to the idea that different neural systems underlie reflexive and reflective decisions within the same individuals as predicted by the dual-system theory of social judgment and DM.

The Impact of Disappointment in Decision Making: Inter-Individual Differences and Electrical Neuroimaging

PubMed Central

Tzieropoulos, Hélène; de Peralta, Rolando Grave; Bossaerts, Peter; Andino, Sara L. Gonzalez

2011-01-01

Disappointment, the emotion experienced when faced to reward prediction errors (RPEs), considerably impacts decision making (DM). Individuals tend to modify their behavior in an often unpredictable way just to avoid experiencing negative emotions. Despite its importance, disappointment remains much less studied than regret and its impact on upcoming decisions largely unexplored. Here, we adapted the Trust Game to effectively elicit, quantify, and isolate disappointment by relying on the formal definition provided by Bell's in economics. We evaluated the effects of experienced disappointment and elation on future cooperation and trust as well as the rationality and utility of the different behavioral and neural mechanisms used to cope with disappointment. All participants in our game trusted less and particularly expected less from unknown opponents as a result of disappointing outcomes in the previous trial but not necessarily after elation indicating that behavioral consequences of positive and negative RPEs are not the same. A large variance in the tolerance to disappointment was observed across subjects, with some participants needing only a small disappointment to impulsively bias their subsequent decisions. As revealed by high-density EEG recordings the most tolerant individuals – who thought twice before making a decision and earned more money – relied on different neural generators to contend with neutral and unexpected outcomes. This study thus provides some support to the idea that different neural systems underlie reflexive and reflective decisions within the same individuals as predicted by the dual-system theory of social judgment and DM. PMID:21258645

Affective and cognitive mechanisms of risky decision making.

PubMed

Shimp, Kristy G; Mitchell, Marci R; Beas, B Sofia; Bizon, Jennifer L; Setlow, Barry

2015-01-01

The ability to make advantageous decisions under circumstances in which there is a risk of adverse consequences is an important component of adaptive behavior; however, extremes in risk taking (either high or low) can be maladaptive and are characteristic of a number of neuropsychiatric disorders. To better understand the contributions of various affective and cognitive factors to risky decision making, cohorts of male Long-Evans rats were trained in a "Risky Decision making Task" (RDT), in which they made discrete trial choices between a small, "safe" food reward and a large, "risky" food reward accompanied by varying probabilities of footshock. Experiment 1 evaluated the relative contributions of the affective stimuli (i.e., punishment vs. reward) to RDT performance by parametrically varying the magnitudes of the footshock and large reward. Varying the shock magnitude had a significant impact on choice of the large, "risky" reward, such that greater magnitudes were associated with reduced choice of the large reward. In contrast, varying the large, "risky" reward magnitude had minimal influence on reward choice. Experiment 2 compared individual variability in RDT performance with performance in an attentional set shifting task (assessing cognitive flexibility), a delayed response task (assessing working memory), and a delay discounting task (assessing impulsive choice). Rats characterized as risk averse in the RDT made more perseverative errors on the set shifting task than did their risk taking counterparts, whereas RDT performance was not related to working memory abilities or impulsive choice. In addition, rats that showed greater delay discounting (greater impulsive choice) showed corresponding poorer performance in the working memory task. Together, these results suggest that reward-related decision making under risk of punishment is more strongly influenced by the punishment than by the reward, and that risky and impulsive decision making are associated with distinct components of executive function. Copyright © 2014 Elsevier Inc. All rights reserved.

Affective and cognitive mechanisms of risky decision making

PubMed Central

Shimp, Kristy G.; Mitchell, Marci R.; Beas, B. Sofia; Bizon, Jennifer L.; Setlow, Barry

2014-01-01

The ability to make advantageous decisions under circumstances in which there is a risk of adverse consequences is an important component of adaptive behavior; however, extremes in risk taking (either high or low) can be maladaptive and are characteristic of a number of neuropsychiatric disorders. To better understand the contributions of various affective and cognitive factors to risky decision making, cohorts of male Long-Evans rats were trained in a “Risky Decision making Task” (RDT), in which they made discrete trial choices between a small, “safe” food reward and a large, “risky” food reward accompanied by varying probabilities of footshock. Experiment 1 evaluated the relative contributions of the affective stimuli (i.e., punishment vs. reward) to RDT performance by parametrically varying the magnitudes of the footshock and large reward. Varying the shock magnitude had a significant impact on choice of the large, “risky” reward, such that greater magnitudes were associated with reduced choice of the large reward. In contrast, varying the large, “risky” reward magnitude had minimal influence on reward choice. Experiment 2 compared individual variability in RDT performance with performance in an attentional set shifting task (assessing cognitive flexibility), a delayed response task (assessing working memory), and a delay discounting task (assessing impulsive choice). Rats characterized as risk averse in the RDT made more perseverative errors on the set shifting task than did their risk taking counterparts, whereas RDT performance was not related to working memory abilities or impulsive choice. In addition, rats that showed greater delay discounting (greater impulsive choice) showed corresponding poorer performance in the working memory task. Together, these results suggest that reward-related decision making under risk of punishment is more strongly influenced by the punishment than by the reward, and that risky and impulsive decision making are associated with distinct components of executive function. PMID:24642448

Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback.

PubMed

Whitney, Paul; Hinson, John M; Jackson, Melinda L; Van Dongen, Hans P A

2015-05-01

To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Twenty-six subjects (22-40 y of age; 10 women). Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information. © 2015 Associated Professional Sleep Societies, LLC.

Difference in Perseverative Errors during a Visual Attention Task with Auditory Distractors in Alpha-9 Nicotinic Receptor Subunit Wild Type and Knock-Out Mice.

PubMed

Jorratt, Pascal; Delano, Paul H; Delgado, Carolina; Dagnino-Subiabre, Alexies; Terreros, Gonzalo

2017-01-01

The auditory efferent system is a neural network that originates in the auditory cortex and projects to the cochlear receptor through olivocochlear (OC) neurons. Medial OC neurons make cholinergic synapses with outer hair cells (OHCs) through nicotinic receptors constituted by α9 and α10 subunits. One of the physiological functions of the α9 nicotinic receptor subunit (α9-nAChR) is the suppression of auditory distractors during selective attention to visual stimuli. In a recent study we demonstrated that the behavioral performance of alpha-9 nicotinic receptor knock-out (KO) mice is altered during selective attention to visual stimuli with auditory distractors since they made less correct responses and more omissions than wild type (WT) mice. As the inhibition of the behavioral responses to irrelevant stimuli is an important mechanism of the selective attention processes, behavioral errors are relevant measures that can reflect altered inhibitory control. Errors produced during a cued attention task can be classified as premature, target and perseverative errors. Perseverative responses can be considered as an inability to inhibit the repetition of an action already planned, while premature responses can be considered as an index of the ability to wait or retain an action. Here, we studied premature, target and perseverative errors during a visual attention task with auditory distractors in WT and KO mice. We found that α9-KO mice make fewer perseverative errors with longer latencies than WT mice in the presence of auditory distractors. In addition, although we found no significant difference in the number of target error between genotypes, KO mice made more short-latency target errors than WT mice during the presentation of auditory distractors. The fewer perseverative error made by α9-KO mice could be explained by a reduced motivation for reward and an increased impulsivity during decision making with auditory distraction in KO mice.

One night of sleep loss impairs innovative thinking and flexible decision making.

PubMed

Harrison, Y; Horne, J A

1999-05-01

Recent findings with clinically oriented neuropsychological tests suggest that one night without sleep causes particular impairment to tasks requiring flexible thinking and the updating of plans in the light of new information. This relatively little investigated field of sleep deprivation research has real-world implications for decision makers having lost a night's sleep. To explore this latter perspective further, we adapted a dynamic and realistic marketing decision making "game" embodying the need for these skills, and whereby such performance could be measured. As the task relied on the comprehension of a large amount of written information, a critical reasoning test was also administered to ascertain whether any failure at the marketing game might lie with information acquisition rather than with failures in decision making. Ten healthy highly motivated and trained participants underwent two counterbalanced 36 h trials, sleep vs no sleep. The critical reasoning task was unaffected by sleep loss, whereas performance at the game significantly deteri orated after 32-36 h of sleep loss, when sleep deprivation led to more rigid thinking, increased perseverative errors, and marked difficulty in appreciating an updated situation. At this point, and despite the sleep-deprived participants' best efforts to do well, their play collapsed, unlike that of the nonsleep-deprived participants. Copyright 1999 Academic Press.

Risk-taking on the road and in the mind: behavioural and neural patterns of decision making between risky and safe drivers.

PubMed

Ba, Yutao; Zhang, Wei; Peng, QiJia; Salvendy, Gavriel; Crundall, David

2016-01-01

Drivers' risk-taking is a key issue of road safety. This study explored individual differences in drivers' decision-making, linking external behaviours to internal neural activity, to reveal the cognitive mechanisms of risky driving. Twenty-four male drivers were split into two groups (risky vs. safe drivers) via the Drivier Behaviour Questionnaire-violation. The risky drivers demonstrated higher preference for the risky choices in the paradigms of Iowa Gambling Task and Balloon Analogue Risk Task. More importantly, the risky drivers showed lower amplitudes of feedback-related negativity (FRN) and loss-minus-gain FRN in both paradigms, which indicated their neural processing of error-detection. A significant difference of P300 amplitudes was also reported between groups, which indicated their neural processing of reward-evaluation and were modified by specific paradigm and feedback. These results suggested that the neural basis of risky driving was the decision patterns less revised by losses and more motivated by rewards. Risk-taking on the road is largely determined by inherent cognitive mechanisms, which can be indicated by the behavioural and neural patterns of decision-making. In this regard, it is feasible to quantize drivers’ riskiness in the cognitive stage before actual risky driving or accidents, and intervene accordingly.

Canadian drivers' attitudes regarding preventative responses to driving while impaired by alcohol.

PubMed

Vanlaar, Ward; Nadeau, Louise; McKiernan, Anna; Hing, Marisela M; Ouimet, Marie Claude; Brown, Thomas G

2017-09-01

In many jurisdictions, a risk assessment following a first driving while impaired (DWI) offence is used to guide administrative decision making regarding driver relicensing. Decision error in this process has important consequences for public security on one hand, and the social and economic well being of drivers on the other. Decision theory posits that consideration of the costs and benefits of decision error is needed, and in the public health context, this should include community attitudes. The objective of the present study was to clarify whether Canadians prefer decision error that: i) better protects the public (i.e., false positives); or ii) better protects the offender (i.e., false negatives). A random sample of male and female adult drivers (N=1213) from the five most populated regions of Canada was surveyed on drivers' preference for a protection of the public approach versus a protection of DWI drivers approach in resolving assessment decision error, and the relative value (i.e., value ratio) they imparted to both approaches. The role of region, sex and age on drivers' value ratio were also appraised. Seventy percent of Canadian drivers preferred a protection of the public from DWI approach, with the overall relative ratio given to this preference, compared to the alternative protection of the driver approach, being 3:1. Females expressed a significantly higher value ratio (M=3.4, SD=3.5) than males (M=3.0, SD=3.4), p<0.05. Regression analysis showed that both days of alcohol use in the past 30days (CI for B: -0.07, -0.02) and frequency of driving over legal BAC limits in the past year (CI for B=-0.19, -0.01) were significantly but modestly related to lower value ratios, R 2 (adj.)=0.014, p<0.001. Regional differences were also detected. Canadian drivers strongly favour a protection of the public approach to dealing with uncertainty in assessment, even at the risk of false positives. Accounting for community attitudes concerning DWI prevention and the individual differences that influence them could contribute to more informed, coherent and effective regional policies and prevention program development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Videopanorama Frame Rate Requirements Derived from Visual Discrimination of Deceleration During Simulated Aircraft Landing

NASA Technical Reports Server (NTRS)

Furnstenau, Norbert; Ellis, Stephen R.

2015-01-01

In order to determine the required visual frame rate (FR) for minimizing prediction errors with out-the-window video displays at remote/virtual airport towers, thirteen active air traffic controllers viewed high dynamic fidelity simulations of landing aircraft and decided whether aircraft would stop as if to be able to make a turnoff or whether a runway excursion would be expected. The viewing conditions and simulation dynamics replicated visual rates and environments of transport aircraft landing at small commercial airports. The required frame rate was estimated using Bayes inference on prediction errors by linear FRextrapolation of event probabilities conditional on predictions (stop, no-stop). Furthermore estimates were obtained from exponential model fits to the parametric and non-parametric perceptual discriminabilities d' and A (average area under ROC-curves) as dependent on FR. Decision errors are biased towards preference of overshoot and appear due to illusionary increase in speed at low frames rates. Both Bayes and A - extrapolations yield a framerate requirement of 35 < FRmin < 40 Hz. When comparing with published results [12] on shooter game scores the model based d'(FR)-extrapolation exhibits the best agreement and indicates even higher FRmin > 40 Hz for minimizing decision errors. Definitive recommendations require further experiments with FR > 30 Hz.

Point-of-care testing (POCT) and evidence-based laboratory medicine (EBLM) - does it leverage any advantage in clinical decision making?

PubMed

Florkowski, Christopher; Don-Wauchope, Andrew; Gimenez, Nuria; Rodriguez-Capote, Karina; Wils, Julien; Zemlin, Annalise

Point-of-care testing (POCT) is the analysis of patient specimens outside the clinical laboratory, near or at the site of patient care, usually performed by clinical staff without laboratory training, although it also encompasses patient self-monitoring. It is able to provide a rapid result near the patient and which can be acted upon immediately. The key driver is the concept that clinical decision making may be delayed when samples are sent to the clinical laboratory. Balanced against this are considerations of increased costs for purchase and maintenance of equipment, staff training, connectivity to the laboratory information system (LIS), quality control (QC) and external quality assurance (EQA) procedures, all required for accreditation under ISO 22870. The justification for POCT depends upon being able to demonstrate that a more timely result (shorter turnaround times (TATs)) is able to leverage a clinically important advantage in decision making compared with the central laboratory (CL). In the four decades since POCT was adapted for the self-monitoring of blood glucose levels by subjects with diabetes, numerous new POCT methodologies have become available, enabling the clinician to receive results and initiate treatment more rapidly. However, these instruments are often operated by staff not trained in laboratory medicine and hence are prone to errors in the analytical phase (as opposed to laboratory testing where the analytical phase has the least errors). In some environments, particularly remote rural settings, the CL may be at a considerable distance and timely availability of cardiac troponins and other analytes can triage referrals to the main centers, thus avoiding expensive unnecessary patient transportation costs. However, in the Emergency Department, availability of more rapid results with POCT does not always translate into shorter stays due to other barriers to implementation of care. In this review, we apply the principles of evidence-based laboratory medicine (EBLM) looking for high quality systematic reviews and meta-analyses, ideally underpinned by randomized controlled trials (RCTs), looking for evidence of whether POCT confers any advantage in clinical decision making in different scenarios.

The processing course of conflicts in third-party punishment: An event-related potential study.

PubMed

Qu, Lulu; Dou, Wei; You, Cheng; Qu, Chen

2014-09-01

In social decision-making games, uninvolved third parties usually severely punish norm violators, even though the punishment is costly for them. For this irrational behavior, the conflict caused by punishment satisfaction and monetary loss is obvious. In the present study, 18 participants observed a Dictator Game and were asked about their willingness to incur some cost to change the offers by reducing the dictator's money. A response-locked event-related potential (ERP) component, the error negativity or error-related negativity (Ne/ERN), which is evoked by error or conflict, was analyzed to investigate whether a trade-off between irrational punishment and rational private benefit occurred in the brain responses of third parties. We examined the effect of the choice type ("to change the offer" or "not to change the offer") and levels of unfairness (90:10 and 70:30) on Ne/ERN amplitudes. The results indicated that there was an ERN effect for unfair offers as Ne/ERN amplitudes were more negative for not to change the offer choices than for to change the offer choices, which suggested that participants encountered more conflict when they did not change unfair offers. Furthermore, it was implied that altruistic punishment, rather than rational utilitarianism, might be the prepotent tendency for humans that is involved in the early stage of decision-making. © 2014 The Institute of Psychology, Chinese Academy of Sciences and Wiley Publishing Asia Pty Ltd.

Episodic Memory Encoding Interferes with Reward Learning and Decreases Striatal Prediction Errors

PubMed Central

Braun, Erin Kendall; Daw, Nathaniel D.

2014-01-01

Learning is essential for adaptive decision making. The striatum and its dopaminergic inputs are known to support incremental reward-based learning, while the hippocampus is known to support encoding of single events (episodic memory). Although traditionally studied separately, in even simple experiences, these two types of learning are likely to co-occur and may interact. Here we sought to understand the nature of this interaction by examining how incremental reward learning is related to concurrent episodic memory encoding. During the experiment, human participants made choices between two options (colored squares), each associated with a drifting probability of reward, with the goal of earning as much money as possible. Incidental, trial-unique object pictures, unrelated to the choice, were overlaid on each option. The next day, participants were given a surprise memory test for these pictures. We found that better episodic memory was related to a decreased influence of recent reward experience on choice, both within and across participants. fMRI analyses further revealed that during learning the canonical striatal reward prediction error signal was significantly weaker when episodic memory was stronger. This decrease in reward prediction error signals in the striatum was associated with enhanced functional connectivity between the hippocampus and striatum at the time of choice. Our results suggest a mechanism by which memory encoding may compete for striatal processing and provide insight into how interactions between different forms of learning guide reward-based decision making. PMID:25378157

Hot and cold executive functions in youth with psychotic symptoms.

PubMed

MacKenzie, L E; Patterson, V C; Zwicker, A; Drobinin, V; Fisher, H L; Abidi, S; Greve, A N; Bagnell, A; Propper, L; Alda, M; Pavlova, B; Uher, R

2017-12-01

Psychotic symptoms are common in children and adolescents and may be early manifestations of liability to severe mental illness (SMI), including schizophrenia. SMI and psychotic symptoms are associated with impairment in executive functions. However, previous studies have not differentiated between 'cold' and 'hot' executive functions. We hypothesized that the propensity for psychotic symptoms is specifically associated with impairment in 'hot' executive functions, such as decision-making in the context of uncertain rewards and losses. In a cohort of 156 youth (mean age 12.5, range 7-24 years) enriched for familial risk of SMI, we measured cold and hot executive functions with the spatial working memory (SWM) task (total errors) and the Cambridge Gambling Task (decision-making), respectively. We assessed psychotic symptoms using the semi-structured Kiddie Schedule for Affective Disorders and Schizophrenia interview, Structured Interview for Prodromal Syndromes, Funny Feelings, and Schizophrenia Proneness Instrument - Child and Youth version. In total 69 (44.23%) youth reported psychotic symptoms on one or more assessments. Cold executive functioning, indexed with SWM errors, was not significantly related to psychotic symptoms [odds ratio (OR) 1.36, 95% confidence interval (CI) 0.85-2.17, p = 0.204). Poor hot executive functioning, indexed as decision-making score, was associated with psychotic symptoms after adjustment for age, sex and familial clustering (OR 2.37, 95% CI 1.25-4.50, p = 0.008). The association between worse hot executive functions and psychotic symptoms remained significant in sensitivity analyses controlling for general cognitive ability and cold executive functions. Impaired hot executive functions may be an indicator of risk and a target for pre-emptive early interventions in youth.

Negative and positive pretrial publicity affect juror memory and decision making.

PubMed

Ruva, Christine L; McEvoy, Cathy

2008-09-01

The experiment examined the effects of exposure to pretrial publicity (PTP) and delay on juror memory and decision-making. Mock jurors read news articles containing negative PTP, positive PTP, or unrelated articles. Five days later, they viewed a videotaped murder trial, after which they made decisions about guilt. Finally, all participants independently attributed specific information as having been presented during the trial or in the news articles. Half of the jurors rendered their verdicts and completed the source-memory test immediately after the trial, while the other half did so after a 2-day delay. Exposure to PTP significantly affected guilty verdicts, perceptions of defendant credibility, juror ratings of the prosecuting and defense attorneys, and misattributions of PTP as having been presented as trial evidence. Similar effects were obtained for negative and positive PTP. Delay significantly increased source-memory errors but did not influence guilt ratings. Defendant's credibility and juror ratings of prosecuting and defense attorneys significantly mediated the effect of PTP on guilt ratings. (c) 2008 APA, all rights reserved.

Psychophysical Laws and the Superorganism.

PubMed

Reina, Andreagiovanni; Bose, Thomas; Trianni, Vito; Marshall, James A R

2018-03-12

Through theoretical analysis, we show how a superorganism may react to stimulus variations according to psychophysical laws observed in humans and other animals. We investigate an empirically-motivated honeybee house-hunting model, which describes a value-sensitive decision process over potential nest-sites, at the level of the colony. In this study, we show how colony decision time increases with the number of available nests, in agreement with the Hick-Hyman law of psychophysics, and decreases with mean nest quality, in agreement with Piéron's law. We also show that colony error rate depends on mean nest quality, and difference in quality, in agreement with Weber's law. Psychophysical laws, particularly Weber's law, have been found in diverse species, including unicellular organisms. Our theoretical results predict that superorganisms may also exhibit such behaviour, suggesting that these laws arise from fundamental mechanisms of information processing and decision-making. Finally, we propose a combined psychophysical law which unifies Hick-Hyman's law and Piéron's law, traditionally studied independently; this unified law makes predictions that can be empirically tested.

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

PubMed Central

Schöner, Gregor; Gail, Alexander

2012-01-01

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations. PMID:23166483

State estimation bias induced by optimization under uncertainty and error cost asymmetry is likely reflected in perception.

PubMed

Shimansky, Y P

2011-05-01

It is well known from numerous studies that perception can be significantly affected by intended action in many everyday situations, indicating that perception and related decision-making is not a simple, one-way sequence, but a complex iterative cognitive process. However, the underlying functional mechanisms are yet unclear. Based on an optimality approach, a quantitative computational model of one such mechanism has been developed in this study. It is assumed in the model that significant uncertainty about task-related parameters of the environment results in parameter estimation errors and an optimal control system should minimize the cost of such errors in terms of the optimality criterion. It is demonstrated that, if the cost of a parameter estimation error is significantly asymmetrical with respect to error direction, the tendency to minimize error cost creates a systematic deviation of the optimal parameter estimate from its maximum likelihood value. Consequently, optimization of parameter estimate and optimization of control action cannot be performed separately from each other under parameter uncertainty combined with asymmetry of estimation error cost, thus making the certainty equivalence principle non-applicable under those conditions. A hypothesis that not only the action, but also perception itself is biased by the above deviation of parameter estimate is supported by ample experimental evidence. The results provide important insights into the cognitive mechanisms of interaction between sensory perception and planning an action under realistic conditions. Implications for understanding related functional mechanisms of optimal control in the CNS are discussed.

Failure detection system design methodology. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chow, E. Y.

1980-01-01

The design of a failure detection and identification system consists of designing a robust residual generation process and a high performance decision making process. The design of these two processes are examined separately. Residual generation is based on analytical redundancy. Redundancy relations that are insensitive to modelling errors and noise effects are important for designing robust residual generation processes. The characterization of the concept of analytical redundancy in terms of a generalized parity space provides a framework in which a systematic approach to the determination of robust redundancy relations are developed. The Bayesian approach is adopted for the design of high performance decision processes. The FDI decision problem is formulated as a Bayes sequential decision problem. Since the optimal decision rule is incomputable, a methodology for designing suboptimal rules is proposed. A numerical algorithm is developed to facilitate the design and performance evaluation of suboptimal rules.

Toward Online Measurement of Decision State

NASA Technical Reports Server (NTRS)

Lachter, Joel; Johnston, James C.; Corrado, Greg S.; McClelland, James L.

2009-01-01

In traditional perceptual decision-making experiments, two pieces of data are collected on each trial: response time and accuracy. But how confident were participants and how did their decision state evolve over time? We asked participants to provide a continuous readout of their decision state by moving a cursor along a sliding scale between a 100% certain left response and a 100% certain right response. Subjects did not terminate the trials; rather, trials were timed out at random and subjects were scored based on the cursor position at that time. Higher rewards for correct responses and higher penalties for errors were associated with extreme responses so that the response with the highest expected value was that which accurately reflected the participant's odds of being correct. This procedure encourages participants to expose the time-course of their evolving decision state. Evidence on how well they can do this will be presented.

Toward Online Measurement of Decision State

NASA Technical Reports Server (NTRS)

Lachter, Joel; Johnston, James C.; Corrado, Greg S.; McClelland, James L.

2009-01-01

In traditional perceptual decision-making experiments, two pieces of data recollected on each trial: response time and accuracy. But how confident were participants and how did their decision state evolve over time? We asked participants to provide a continuous readout of their decision state by moving a cursor along a sliding scale between a 100% certain left response and a 100% certain right response. Subjects did not terminate the trials; rather, trials were timed out at random and subjects were scored based on the cursor position at the time. Higher rewards for correct responses and higher penalties for errors were associated with extreme responses so that the response with the highest ex[pected value was that which accurately reflected the participant's odds of being correct. This procedure encourages participants to expose the time-course of their evolving decision state. Evidence on how well they can do this will be presented.

Nurses' role in medication safety.

PubMed

Choo, Janet; Hutchinson, Alison; Bucknall, Tracey

2010-10-01

To explore the nurse's role in the process of medication management and identify the challenges associated with safe medication management in contemporary clinical practice. Medication errors have been a long-standing factor affecting consumer safety. The nursing profession has been identified as essential to the promotion of patient safety. A review of literature on medication errors and the use of electronic prescribing in medication errors. Medication management requires a multidisciplinary approach and interdisciplinary communication is essential to reduce medication errors. Information technologies can help to reduce some medication errors through eradication of transcription and dosing errors. Nurses must play a major role in the design of computerized medication systems to ensure a smooth transition to such as system. The nurses' roles in medication management cannot be over-emphasized. This is particularly true when designing a computerized medication system. The adoption of safety measures during decision making that parallel those of the aviation industry safety procedures can provide some strategies to prevent medication error. Innovations in information technology offer potential mechanisms to avert adverse events in medication management for nurses. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

A Critical Meta-Analysis of Lens Model Studies in Human Judgment and Decision-Making

PubMed Central

Kaufmann, Esther; Reips, Ulf-Dietrich; Wittmann, Werner W.

2013-01-01

Achieving accurate judgment (‘judgmental achievement’) is of utmost importance in daily life across multiple domains. The lens model and the lens model equation provide useful frameworks for modeling components of judgmental achievement and for creating tools to help decision makers (e.g., physicians, teachers) reach better judgments (e.g., a correct diagnosis, an accurate estimation of intelligence). Previous meta-analyses of judgment and decision-making studies have attempted to evaluate overall judgmental achievement and have provided the basis for evaluating the success of bootstrapping (i.e., replacing judges by linear models that guide decision making). However, previous meta-analyses have failed to appropriately correct for a number of study design artifacts (e.g., measurement error, dichotomization), which may have potentially biased estimations (e.g., of the variability between studies) and led to erroneous interpretations (e.g., with regards to moderator variables). In the current study we therefore conduct the first psychometric meta-analysis of judgmental achievement studies that corrects for a number of study design artifacts. We identified 31 lens model studies (N = 1,151, k = 49) that met our inclusion criteria. We evaluated overall judgmental achievement as well as whether judgmental achievement depended on decision domain (e.g., medicine, education) and/or the level of expertise (expert vs. novice). We also evaluated whether using corrected estimates affected conclusions with regards to the success of bootstrapping with psychometrically-corrected models. Further, we introduce a new psychometric trim-and-fill method to estimate the effect sizes of potentially missing studies correct psychometric meta-analyses for effects of publication bias. Comparison of the results of the psychometric meta-analysis with the results of a traditional meta-analysis (which only corrected for sampling error) indicated that artifact correction leads to a) an increase in values of the lens model components, b) reduced heterogeneity between studies, and c) increases the success of bootstrapping. We argue that psychometric meta-analysis is useful for accurately evaluating human judgment and show the success of bootstrapping. PMID:24391781

A critical meta-analysis of lens model studies in human judgment and decision-making.

PubMed

Kaufmann, Esther; Reips, Ulf-Dietrich; Wittmann, Werner W

2013-01-01

Achieving accurate judgment ('judgmental achievement') is of utmost importance in daily life across multiple domains. The lens model and the lens model equation provide useful frameworks for modeling components of judgmental achievement and for creating tools to help decision makers (e.g., physicians, teachers) reach better judgments (e.g., a correct diagnosis, an accurate estimation of intelligence). Previous meta-analyses of judgment and decision-making studies have attempted to evaluate overall judgmental achievement and have provided the basis for evaluating the success of bootstrapping (i.e., replacing judges by linear models that guide decision making). However, previous meta-analyses have failed to appropriately correct for a number of study design artifacts (e.g., measurement error, dichotomization), which may have potentially biased estimations (e.g., of the variability between studies) and led to erroneous interpretations (e.g., with regards to moderator variables). In the current study we therefore conduct the first psychometric meta-analysis of judgmental achievement studies that corrects for a number of study design artifacts. We identified 31 lens model studies (N = 1,151, k = 49) that met our inclusion criteria. We evaluated overall judgmental achievement as well as whether judgmental achievement depended on decision domain (e.g., medicine, education) and/or the level of expertise (expert vs. novice). We also evaluated whether using corrected estimates affected conclusions with regards to the success of bootstrapping with psychometrically-corrected models. Further, we introduce a new psychometric trim-and-fill method to estimate the effect sizes of potentially missing studies correct psychometric meta-analyses for effects of publication bias. Comparison of the results of the psychometric meta-analysis with the results of a traditional meta-analysis (which only corrected for sampling error) indicated that artifact correction leads to a) an increase in values of the lens model components, b) reduced heterogeneity between studies, and c) increases the success of bootstrapping. We argue that psychometric meta-analysis is useful for accurately evaluating human judgment and show the success of bootstrapping.

Least Reliable Bits Coding (LRBC) for high data rate satellite communications

NASA Technical Reports Server (NTRS)

Vanderaar, Mark; Wagner, Paul; Budinger, James

1992-01-01

An analysis and discussion of a bandwidth efficient multi-level/multi-stage block coded modulation technique called Least Reliable Bits Coding (LRBC) is presented. LRBC uses simple multi-level component codes that provide increased error protection on increasingly unreliable modulated bits in order to maintain an overall high code rate that increases spectral efficiency. Further, soft-decision multi-stage decoding is used to make decisions on unprotected bits through corrections made on more protected bits. Using analytical expressions and tight performance bounds it is shown that LRBC can achieve increased spectral efficiency and maintain equivalent or better power efficiency compared to that of Binary Phase Shift Keying (BPSK). Bit error rates (BER) vs. channel bit energy with Additive White Gaussian Noise (AWGN) are given for a set of LRB Reed-Solomon (RS) encoded 8PSK modulation formats with an ensemble rate of 8/9. All formats exhibit a spectral efficiency of 2.67 = (log2(8))(8/9) information bps/Hz. Bit by bit coded and uncoded error probabilities with soft-decision information are determined. These are traded with with code rate to determine parameters that achieve good performance. The relative simplicity of Galois field algebra vs. the Viterbi algorithm and the availability of high speed commercial Very Large Scale Integration (VLSI) for block codes indicates that LRBC using block codes is a desirable method for high data rate implementations.

Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies

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

Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

2014-04-14

To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation.more » We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.« less

Teaching concepts of clinical measurement variation to medical students.

PubMed

Hodder, R A; Longfield, J N; Cruess, D F; Horton, J A

1982-09-01

An exercise in clinical epidemiology was developed for medical students to demonstrate the process and limitations of scientific measurement using models that simulate common clinical experiences. All scales of measurement (nominal, ordinal and interval) were used to illustrate concepts of intra- and interobserver variation, systematic error, recording error, and procedural error. In a laboratory, students a) determined blood pressures on six videotaped subjects, b) graded sugar content of unknown solutions from 0 to 4+ using Clinitest tablets, c) measured papules that simulated PPD reactions, d) measured heart and kidney size on X-rays and, e) described a model skin lesion (melanoma). Traditionally, measurement variation is taught in biostatistics or epidemiology courses using previously collected data. Use of these models enables students to produce their own data using measurements commonly employed by the clinician. The exercise provided material for a meaningful discussion of the implications of measurement error in clinical decision-making.

Using evidence-based algorithms to improve clinical decision making: the case of a first-time anterior shoulder dislocation.

PubMed

Federer, Andrew E; Taylor, Dean C; Mather, Richard C

2013-09-01

Decision making in health care has evolved substantially over the last century. Up until the late 1970s, medical decision making was predominantly intuitive and anecdotal. It was based on trial and error and involved high levels of problem solving. The 1980s gave way to empirical medicine, which was evidence based probabilistic, and involved pattern recognition and less problem solving. Although this represented a major advance in the quality of medical decision making, limitations existed. The advantages of the gold standard of the randomized controlled clinical trial (RCT) are well-known and this technique is irreplaceable in its ability to answer critical clinical questions. However, the RCT does have drawbacks. RCTs are expensive and can only capture a snapshot in time. As treatments change and new technologies emerge, new expensive clinical trials must be undertaken to reevaluate them. Furthermore, in order to best evaluate a single intervention, other factors must be controlled. In addition, the study population may not match that of another organization or provider. Although evidence-based medicine has provided powerful data for clinicians, effectively and efficiently tailoring it to the individual has not yet evolved. We are now in a period of transition from this evidence-based era to one dominated by the personalization and customization of care. It will be fueled by policy decisions to shift financial responsibility to the patient, creating a powerful and sophisticated consumer, unlike any patient we have known before. The challenge will be to apply medical evidence and personal preferences to medical decisions and deliver it efficiently in the increasingly busy clinical setting. In this article, we provide a robust review of the concepts of customized care and some of techniques to deliver it. We will illustrate this through a personalized decision model for the treatment decision after a first-time anterior shoulder dislocation.

Command Process Modeling & Risk Analysis

NASA Technical Reports Server (NTRS)

Meshkat, Leila

2011-01-01

Commanding Errors may be caused by a variety of root causes. It's important to understand the relative significance of each of these causes for making institutional investment decisions. One of these causes is the lack of standardized processes and procedures for command and control. We mitigate this problem by building periodic tables and models corresponding to key functions within it. These models include simulation analysis and probabilistic risk assessment models.

Project Summaries: Office of Basic Research Contract Program, 1989-1991

DTIC Science & Technology

1990-08-01

OBJECTIVES: This research is an investigation of the impact of error in data on performance in a variety of tasks. While environmental uncertainty is...individual, organizational and environmental /situational factors impacting on senior decisions made a’ critical points in the Israeli events. A...making in the Army personnel system --predictors and measures of soldier performance --family impact on soldier retention and readiness Systems Research

Overcoming Indecision by Changing the Decision Boundary

PubMed Central

2017-01-01

The dominant theoretical framework for decision making asserts that people make decisions by integrating noisy evidence to a threshold. It has recently been shown that in many ecologically realistic situations, decreasing the decision boundary maximizes the reward available from decisions. However, empirical support for decreasing boundaries in humans is scant. To investigate this problem, we used an ideal observer model to identify the conditions under which participants should change their decision boundaries with time to maximize reward rate. We conducted 6 expanded-judgment experiments that precisely matched the assumptions of this theoretical model. In this paradigm, participants could sample noisy, binary evidence presented sequentially. Blocks of trials were fixed in duration, and each trial was an independent reward opportunity. Participants therefore had to trade off speed (getting as many rewards as possible) against accuracy (sampling more evidence). Having access to the actual evidence samples experienced by participants enabled us to infer the slope of the decision boundary. We found that participants indeed modulated the slope of the decision boundary in the direction predicted by the ideal observer model, although we also observed systematic deviations from optimality. Participants using suboptimal boundaries do so in a robust manner, so that any error in their boundary setting is relatively inexpensive. The use of a normative model provides insight into what variable(s) human decision makers are trying to optimize. Furthermore, this normative model allowed us to choose diagnostic experiments and in doing so we present clear evidence for time-varying boundaries. PMID:28406682

Bayesian randomized clinical trials: From fixed to adaptive design.

PubMed

Yin, Guosheng; Lam, Chi Kin; Shi, Haolun

2017-08-01

Randomized controlled studies are the gold standard for phase III clinical trials. Using α-spending functions to control the overall type I error rate, group sequential methods are well established and have been dominating phase III studies. Bayesian randomized design, on the other hand, can be viewed as a complement instead of competitive approach to the frequentist methods. For the fixed Bayesian design, the hypothesis testing can be cast in the posterior probability or Bayes factor framework, which has a direct link to the frequentist type I error rate. Bayesian group sequential design relies upon Bayesian decision-theoretic approaches based on backward induction, which is often computationally intensive. Compared with the frequentist approaches, Bayesian methods have several advantages. The posterior predictive probability serves as a useful and convenient tool for trial monitoring, and can be updated at any time as the data accrue during the trial. The Bayesian decision-theoretic framework possesses a direct link to the decision making in the practical setting, and can be modeled more realistically to reflect the actual cost-benefit analysis during the drug development process. Other merits include the possibility of hierarchical modeling and the use of informative priors, which would lead to a more comprehensive utilization of information from both historical and longitudinal data. From fixed to adaptive design, we focus on Bayesian randomized controlled clinical trials and make extensive comparisons with frequentist counterparts through numerical studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural substrates of updating the prediction through prediction error during decision making.

PubMed

Wang, Ying; Ma, Ning; He, Xiaosong; Li, Nan; Wei, Zhengde; Yang, Lizhuang; Zha, Rujing; Han, Long; Li, Xiaoming; Zhang, Daren; Liu, Ying; Zhang, Xiaochu

2017-08-15

Learning of prediction error (PE), including reward PE and risk PE, is crucial for updating the prediction in reinforcement learning (RL). Neurobiological and computational models of RL have reported extensive brain activations related to PE. However, the occurrence of PE does not necessarily predict updating the prediction, e.g., in a probability-known event. Therefore, the brain regions specifically engaged in updating the prediction remain unknown. Here, we conducted two functional magnetic resonance imaging (fMRI) experiments, the probability-unknown Iowa Gambling Task (IGT) and the probability-known risk decision task (RDT). Behavioral analyses confirmed that PEs occurred in both tasks but were only used for updating the prediction in the IGT. By comparing PE-related brain activations between the two tasks, we found that the rostral anterior cingulate cortex/ventral medial prefrontal cortex (rACC/vmPFC) and the posterior cingulate cortex (PCC) activated only during the IGT and were related to both reward and risk PE. Moreover, the responses in the rACC/vmPFC and the PCC were modulated by uncertainty and were associated with reward prediction-related brain regions. Electric brain stimulation over these regions lowered the performance in the IGT but not in the RDT. Our findings of a distributed neural circuit of PE processing suggest that the rACC/vmPFC and the PCC play a key role in updating the prediction through PE processing during decision making. Copyright © 2017 Elsevier Inc. All rights reserved.

Mitigating Evidentiary Bias in Planning and Policy-Making Comment on "Reflective Practice: How the World Bank Explored Its Own Biases?"

PubMed

Parkhurst, Justin

2016-07-20

The field of cognitive psychology has increasingly provided scientific insights to explore how humans are subject to unconscious sources of evidentiary bias, leading to errors that can affect judgement and decision-making. Increasingly these insights are being applied outside the realm of individual decision-making to the collective arena of policy-making as well. A recent editorial in this journal has particularly lauded the work of the World Bank for undertaking an open and critical reflection on sources of unconscious bias in its own expert staff that could undermine achievement of its key goals. The World Bank case indeed serves as a remarkable case of a global policy-making agency making its own critical reflections transparent for all to see. Yet the recognition that humans are prone to cognitive errors has been known for centuries, and the scientific exploration of such biases provided by cognitive psychology is now well-established. What still remains to be developed, however, is a widespread body of work that can inform efforts to institutionalise strategies to mitigate the multiple sources and forms of evidentiary bias arising within administrative and policy-making environments. Addressing this gap will require a programme of conceptual and empirical work that supports robust development and evaluation of institutional bias mitigation strategies. The cognitive sciences provides a scientific basis on which to proceed, but a critical priority will now be the application of that science to improve policy-making within those agencies taking responsibility for social welfare and development programmes. © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The Impact of Trajectory Prediction Uncertainty on Air Traffic Controller Performance and Acceptability

NASA Technical Reports Server (NTRS)

Mercer, Joey S.; Bienert, Nancy; Gomez, Ashley; Hunt, Sarah; Kraut, Joshua; Martin, Lynne; Morey, Susan; Green, Steven M.; Prevot, Thomas; Wu, Minghong G.

2013-01-01

A Human-In-The-Loop air traffic control simulation investigated the impact of uncertainties in trajectory predictions on NextGen Trajectory-Based Operations concepts, seeking to understand when the automation would become unacceptable to controllers or when performance targets could no longer be met. Retired air traffic controllers staffed two en route transition sectors, delivering arrival traffic to the northwest corner-post of Atlanta approach control under time-based metering operations. Using trajectory-based decision-support tools, the participants worked the traffic under varying levels of wind forecast error and aircraft performance model error, impacting the ground automations ability to make accurate predictions. Results suggest that the controllers were able to maintain high levels of performance, despite even the highest levels of trajectory prediction errors.

Aversion to ambiguity and willingness to take risks affect therapeutic decisions in managing atrial fibrillation for stroke prevention: results of a pilot study in family physicians.

PubMed

Raptis, Stavroula; Chen, Jia Ning; Saposnik, Florencia; Pelyavskyy, Roman; Liuni, Andrew; Saposnik, Gustavo

2017-01-01

Anticoagulation is the therapeutic paradigm for stroke prevention in patients with atrial fibrillation (AF). It is unknown how physicians make treatment decisions in primary stroke prevention for patients with AF. To evaluate the association between family physicians' risk preferences (aversion risk and ambiguity) and therapeutic recommendations (anticoagulation) in the management of AF for primary stroke prevention by applying concepts from behavioral economics. Overall, 73 family physicians participated and completed the study. Our study comprised seven simulated case vignettes, three behavioral experiments, and two validated surveys. Behavioral experiments and surveys incorporated an economic framework to determine risk preferences and biases (e.g., ambiguity aversion, willingness to take risks). The primary outcome was making the correct decision of anticoagulation therapy. Secondary outcomes included medical errors in the management of AF for stroke prevention. Overall, 23.3% (17/73) of the family physicians elected not to escalate the therapy from antiplatelets to anticoagulation when recommended by best practice guidelines. A total of 67.1% of physicians selected the correct therapeutic options in two or more of the three simulated case vignettes. Multivariate analysis showed that aversion to ambiguity was associated with appropriate change to anticoagulation therapy in the management of AF (OR 5.48, 95% CI 1.08-27.85). Physicians' willingness to take individual risk in multiple domains was associated with lower errors (OR 0.16, 95% CI 0.03-0.86). Physicians' aversion to ambiguity and willingness to take risks are associated with appropriate therapeutic decisions in the management of AF for primary stroke prevention. Further large scale studies are needed.

Aversion to ambiguity and willingness to take risks affect therapeutic decisions in managing atrial fibrillation for stroke prevention: results of a pilot study in family physicians

PubMed Central

Saposnik, Florencia; Pelyavskyy, Roman; Liuni, Andrew; Saposnik, Gustavo

2017-01-01

Background Anticoagulation is the therapeutic paradigm for stroke prevention in patients with atrial fibrillation (AF). It is unknown how physicians make treatment decisions in primary stroke prevention for patients with AF. Objectives To evaluate the association between family physicians’ risk preferences (aversion risk and ambiguity) and therapeutic recommendations (anticoagulation) in the management of AF for primary stroke prevention by applying concepts from behavioral economics. Methods Overall, 73 family physicians participated and completed the study. Our study comprised seven simulated case vignettes, three behavioral experiments, and two validated surveys. Behavioral experiments and surveys incorporated an economic framework to determine risk preferences and biases (e.g., ambiguity aversion, willingness to take risks). The primary outcome was making the correct decision of anticoagulation therapy. Secondary outcomes included medical errors in the management of AF for stroke prevention. Results Overall, 23.3% (17/73) of the family physicians elected not to escalate the therapy from antiplatelets to anticoagulation when recommended by best practice guidelines. A total of 67.1% of physicians selected the correct therapeutic options in two or more of the three simulated case vignettes. Multivariate analysis showed that aversion to ambiguity was associated with appropriate change to anticoagulation therapy in the management of AF (OR 5.48, 95% CI 1.08–27.85). Physicians’ willingness to take individual risk in multiple domains was associated with lower errors (OR 0.16, 95% CI 0.03–0.86). Conclusion Physicians’ aversion to ambiguity and willingness to take risks are associated with appropriate therapeutic decisions in the management of AF for primary stroke prevention. Further large scale studies are needed. PMID:28979101

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

PubMed Central

Marcek, Dusan; Durisova, Maria

2016-01-01

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

PubMed

Falat, Lukas; Marcek, Dusan; Durisova, Maria

2016-01-01

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

Real and hypothetical monetary rewards modulate risk taking in the brain.

PubMed

Xu, Sihua; Pan, Yu; Wang, You; Spaeth, Andrea M; Qu, Zhe; Rao, Hengyi

2016-07-07

Both real and hypothetical monetary rewards are widely used as reinforcers in risk taking and decision making studies. However, whether real and hypothetical monetary rewards modulate risk taking and decision making in the same manner remains controversial. In this study, we used event-related potentials (ERP) with a balloon analogue risk task (BART) paradigm to examine the effects of real and hypothetical monetary rewards on risk taking in the brain. Behavioral data showed reduced risk taking after negative feedback (money loss) during the BART with real rewards compared to those with hypothetical rewards, suggesting increased loss aversion with real monetary rewards. The ERP data demonstrated a larger feedback-related negativity (FRN) in response to money loss during risk taking with real rewards compared to those with hypothetical rewards, which may reflect greater prediction error or regret emotion after real monetary losses. These findings demonstrate differential effects of real versus hypothetical monetary rewards on risk taking behavior and brain activity, suggesting a caution when drawing conclusions about real choices from hypothetical studies of intended behavior, especially when large rewards are used. The results have implications for future utility of real and hypothetical monetary rewards in studies of risk taking and decision making.

Trial-by-trial fluctuations in CNV amplitude reflect anticipatory adjustment of response caution.

PubMed

Boehm, Udo; van Maanen, Leendert; Forstmann, Birte; van Rijn, Hedderik

2014-08-01

The contingent negative variation, a slow cortical potential, occurs when humans are warned by a stimulus about an upcoming task. The cognitive processes that give rise to this EEG potential are not yet well understood. To explain these processes, we adopt a recently developed theoretical framework from the area of perceptual decision-making. This framework assumes that the basal ganglia control the tradeoff between fast and accurate decision-making in the cortex. It suggests that an increase in cortical excitability serves to lower response caution, which results in faster but more error prone responding. We propose that the CNV reflects this increased cortical excitability. To test this hypothesis, we conducted an EEG experiment in which participants performed the random dot motion task either under speed or under accuracy stress. Our results show that trial-by-trial fluctuations in participants' response speed as well as model-based estimates of response caution correlated with single-trial CNV amplitude under conditions of speed but not accuracy stress. We conclude that the CNV might reflect adjustments of response caution, which serves to enhance quick decision-making. Copyright © 2014 Elsevier Inc. All rights reserved.

Neural correlates of successful semantic processing during propofol sedation.

PubMed

Adapa, Ram M; Davis, Matthew H; Stamatakis, Emmanuel A; Absalom, Anthony R; Menon, David K

2014-07-01

Sedation has a graded effect on brain responses to auditory stimuli: perceptual processing persists at sedation levels that attenuate more complex processing. We used fMRI in healthy volunteers sedated with propofol to assess changes in neural responses to spoken stimuli. Volunteers were scanned awake, sedated, and during recovery, while making perceptual or semantic decisions about nonspeech sounds or spoken words respectively. Sedation caused increased error rates and response times, and differentially affected responses to words in the left inferior frontal gyrus (LIFG) and the left inferior temporal gyrus (LITG). Activity in LIFG regions putatively associated with semantic processing, was significantly reduced by sedation despite sedated volunteers continuing to make accurate semantic decisions. Instead, LITG activity was preserved for words greater than nonspeech sounds and may therefore be associated with persistent semantic processing during the deepest levels of sedation. These results suggest functionally distinct contributions of frontal and temporal regions to semantic decision making. These results have implications for functional imaging studies of language, for understanding mechanisms of impaired speech comprehension in postoperative patients with residual levels of anesthetic, and may contribute to the development of frameworks against which EEG based monitors could be calibrated to detect awareness under anesthesia. Copyright © 2013 Wiley Periodicals, Inc.

When to Make Mountains out of Molehills: The Pros and Cons of Simple and Complex Model Calibration Procedures

NASA Astrophysics Data System (ADS)

Smith, K. A.; Barker, L. J.; Harrigan, S.; Prudhomme, C.; Hannaford, J.; Tanguy, M.; Parry, S.

2017-12-01

Earth and environmental models are relied upon to investigate system responses that cannot otherwise be examined. In simulating physical processes, models have adjustable parameters which may, or may not, have a physical meaning. Determining the values to assign to these model parameters is an enduring challenge for earth and environmental modellers. Selecting different error metrics by which the models results are compared to observations will lead to different sets of calibrated model parameters, and thus different model results. Furthermore, models may exhibit `equifinal' behaviour, where multiple combinations of model parameters lead to equally acceptable model performance against observations. These decisions in model calibration introduce uncertainty that must be considered when model results are used to inform environmental decision-making. This presentation focusses on the uncertainties that derive from the calibration of a four parameter lumped catchment hydrological model (GR4J). The GR models contain an inbuilt automatic calibration algorithm that can satisfactorily calibrate against four error metrics in only a few seconds. However, a single, deterministic model result does not provide information on parameter uncertainty. Furthermore, a modeller interested in extreme events, such as droughts, may wish to calibrate against more low flows specific error metrics. In a comprehensive assessment, the GR4J model has been run with 500,000 Latin Hypercube Sampled parameter sets across 303 catchments in the United Kingdom. These parameter sets have been assessed against six error metrics, including two drought specific metrics. This presentation compares the two approaches, and demonstrates that the inbuilt automatic calibration can outperform the Latin Hypercube experiment approach in single metric assessed performance. However, it is also shown that there are many merits of the more comprehensive assessment, which allows for probabilistic model results, multi-objective optimisation, and better tailoring to calibrate the model for specific applications such as drought event characterisation. Modellers and decision-makers may be constrained in their choice of calibration method, so it is important that they recognise the strengths and limitations of their chosen approach.

Does improved decision-making ability reduce the physiological demands of game-based activities in field sport athletes?

PubMed

Gabbett, Tim J; Carius, Josh; Mulvey, Mike

2008-11-01

This study investigated the effects of video-based perceptual training on pattern recognition and pattern prediction ability in elite field sport athletes and determined whether enhanced perceptual skills influenced the physiological demands of game-based activities. Sixteen elite women soccer players (mean +/- SD age, 18.3 +/- 2.8 years) were allocated to either a video-based perceptual training group (N = 8) or a control group (N = 8). The video-based perceptual training group watched video footage of international women's soccer matches. Twelve training sessions, each 15 minutes in duration, were conducted during a 4-week period. Players performed assessments of speed (5-, 10-, and 20-m sprint), repeated-sprint ability (6 x 20-m sprints, with active recovery on a 15-second cycle), estimated maximal aerobic power (V O2 max, multistage fitness test), and a game-specific video-based perceptual test of pattern recognition and pattern prediction before and after the 4 weeks of video-based perceptual training. The on-field assessments included time-motion analysis completed on all players during a standardized 45-minute small-sided training game, and assessments of passing, shooting, and dribbling decision-making ability. No significant changes were detected in speed, repeated-sprint ability, or estimated V O2 max during the training period. However, video-based perceptual training improved decision accuracy and reduced the number of recall errors, indicating improved game awareness and decision-making ability. Importantly, the improvements in pattern recognition and prediction ability transferred to on-field improvements in passing, shooting, and dribbling decision-making skills. No differences were detected between groups for the time spent standing, walking, jogging, striding, and sprinting during the small-sided training game. These findings demonstrate that video-based perceptual training can be used effectively to enhance the decision-making ability of field sport athletes; however, it has no effect on the physiological demands of game-based activities.

Medical Decision Making for Patients Without Proxies: The Effect of Personal Experience in the Deliberative Process.

PubMed

Robichaud, Allyson L

2015-01-01

The number of admissions to hospitals of patients without a proxy decision maker is rising. Very often these patients need fairly immediate medical intervention for which informed consent--or informed refusal--is required. Many have recommended that there be a process in place to make these decisions, and that it include a variety of perspectives. People are particularly wary of relying solely on medical staff to make these decisions. The University Hospitals Case Medical Center recruits community members from its Ethics Committee to serve on a subcommittee, the Patients Without Proxies (PWP) Committee, which works with medical staff during the decision-making process for these patients. Generally, the community members go to the bedside to observe patients. This article looks at how those unused to observing hospitalized patients who are sick and/or dying are affected, comparing them to mock jurors in a research study who are exposed to graphic photographs related to a fabricated crime scene. Judgments made by the mock jurors are affected by viewing such images. The personal experience of witnessing unfamiliar and shocking scenes affects their subsequent judgments. While it may be difficult to tease out whether observing patients causes PWP members to be benefited or harmed, they are affected by what they see. If a variety of perspectives is desirable to reduce possible bias or error, this article argues that at least one community member should refrain from seeing the patient in order to add a different and valuable voice to the decision-making process. Members of the subcommittee base their judgments on the various kinds of information available. Sometimes the things they see, hear, or feel may affect them particularly deeply, and affect their judgments as well. In this article I explore the idea that something like this may be happening in a particular kind of clinical ethics case consultation. Copyright 2015 The Journal of Clinical Ethics. All rights reserved.

A contrast between DEMATEL-ANP and ANP methods for six sigma project selection: a case study in healthcare industry.

PubMed

Ortíz, Miguel A; Felizzola, Heriberto A; Nieto Isaza, Santiago

2015-01-01

The project selection process is a crucial step for healthcare organizations at the moment of implementing six sigma programs in both administrative and caring processes. However, six-sigma project selection is often defined as a decision making process with interaction and feedback between criteria; so that it is necessary to explore different methods to help healthcare companies to determine the Six-sigma projects that provide the maximum benefits. This paper describes the application of both ANP (Analytic Network process) and DEMATEL (Decision Making trial and evaluation laboratory)-ANP in a public medical centre to establish the most suitable six sigma project and finally, these methods were compared to evaluate their performance in the decision making process. ANP and DEMATEL-ANP were used to evaluate 6 six sigma project alternatives under an evaluation model composed by 3 strategies, 4 criteria and 15 sub-criteria. Judgement matrixes were completed by the six sigma team whose participants worked in different departments of the medical centre. The improving of care opportunity in obstetric outpatients was elected as the most suitable six sigma project with a score of 0,117 as contribution to the organization goals. DEMATEL-ANP performed better at decision making process since it reduced the error probability due to interactions and feedback. ANP and DEMATEL-ANP effectively supported six sigma project selection processes, helping to create a complete framework that guarantees the prioritization of projects that provide maximum benefits to healthcare organizations. As DEMATEL- ANP performed better, it should be used by practitioners involved in decisions related to the implementation of six sigma programs in healthcare sector accompanied by the adequate identification of the evaluation criteria that support the decision making model. Thus, this comparative study contributes to choosing more effective approaches in this field. Suggestions of further work are also proposed so that these methods can be applied more adequate in six sigma project selection processes in healthcare.

A contrast between DEMATEL-ANP and ANP methods for six sigma project selection: a case study in healthcare industry

PubMed Central

2015-01-01

Background The project selection process is a crucial step for healthcare organizations at the moment of implementing six sigma programs in both administrative and caring processes. However, six-sigma project selection is often defined as a decision making process with interaction and feedback between criteria; so that it is necessary to explore different methods to help healthcare companies to determine the Six-sigma projects that provide the maximum benefits. This paper describes the application of both ANP (Analytic Network process) and DEMATEL (Decision Making trial and evaluation laboratory)-ANP in a public medical centre to establish the most suitable six sigma project and finally, these methods were compared to evaluate their performance in the decision making process. Methods ANP and DEMATEL-ANP were used to evaluate 6 six sigma project alternatives under an evaluation model composed by 3 strategies, 4 criteria and 15 sub-criteria. Judgement matrixes were completed by the six sigma team whose participants worked in different departments of the medical centre. Results The improving of care opportunity in obstetric outpatients was elected as the most suitable six sigma project with a score of 0,117 as contribution to the organization goals. DEMATEL-ANP performed better at decision making process since it reduced the error probability due to interactions and feedback. Conclusions ANP and DEMATEL-ANP effectively supported six sigma project selection processes, helping to create a complete framework that guarantees the prioritization of projects that provide maximum benefits to healthcare organizations. As DEMATEL- ANP performed better, it should be used by practitioners involved in decisions related to the implementation of six sigma programs in healthcare sector accompanied by the adequate identification of the evaluation criteria that support the decision making model. Thus, this comparative study contributes to choosing more effective approaches in this field. Suggestions of further work are also proposed so that these methods can be applied more adequate in six sigma project selection processes in healthcare. PMID:26391445

Cognitive determinants of affective forecasting errors

PubMed Central

Hoerger, Michael; Quirk, Stuart W.; Lucas, Richard E.; Carr, Thomas H.

2011-01-01

Often to the detriment of human decision making, people are prone to an impact bias when making affective forecasts, overestimating the emotional consequences of future events. The cognitive processes underlying the impact bias, and methods for correcting it, have been debated and warrant further exploration. In the present investigation, we examined both individual differences and contextual variables associated with cognitive processing in affective forecasting for an election. Results showed that the perceived importance of the event and working memory capacity were both associated with an increased impact bias for some participants, whereas retrieval interference had no relationship with bias. Additionally, an experimental manipulation effectively reduced biased forecasts, particularly among participants who were most distracted thinking about peripheral life events. These findings have direct theoretical implications for understanding the impact bias, highlight the importance of individual differences in affective forecasting, and have ramifications for future decision making research. The possible functional role of the impact bias is discussed within the context of evolutionary psychology. PMID:21912580

Acceptance threshold theory can explain occurrence of homosexual behaviour.

PubMed

Engel, Katharina C; Männer, Lisa; Ayasse, Manfred; Steiger, Sandra

2015-01-01

Same-sex sexual behaviour (SSB) has been documented in a wide range of animals, but its evolutionary causes are not well understood. Here, we investigated SSB in the light of Reeve's acceptance threshold theory. When recognition is not error-proof, the acceptance threshold used by males to recognize potential mating partners should be flexibly adjusted to maximize the fitness pay-off between the costs of erroneously accepting males and the benefits of accepting females. By manipulating male burying beetles' search time for females and their reproductive potential, we influenced their perceived costs of making an acceptance or rejection error. As predicted, when the costs of rejecting females increased, males exhibited more permissive discrimination decisions and showed high levels of SSB; when the costs of accepting males increased, males were more restrictive and showed low levels of SSB. Our results support the idea that in animal species, in which the recognition cues of females and males overlap to a certain degree, SSB is a consequence of an adaptive discrimination strategy to avoid the costs of making rejection errors. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Advanced Computational Framework for Environmental Management ZEM, Version 1.x

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

Vesselinov, Velimir V.; O'Malley, Daniel; Pandey, Sachin

2016-11-04

Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions).more » To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.« less

Gunslingers, poker players, and chickens 2: Decision-making under physical performance pressure in subelite athletes.

PubMed

Parkin, Beth L; Walsh, Vincent

2017-01-01

Having investigated the influence of acute physical exhaustion on decision-making in world-class elite athletes in Parkin et al. (2017), here a similar method is applied to subelite athletes. These subelite athletes were enrolled on a Team GB talent development program and were undergoing training for possible Olympic competition in 4-8 years. They differ from elite athletes examined previously according to expertise and age. While considered elite (Swann et al., 2015), the subelite athletes had approximately 8 years fewer sporting experience and were yet to obtain sustained success on the international stage. Additionally, the average age of the subelite sample is 20 years; thus, they are still undergoing the behavioral, cognitive, and neuronal changes that occur during the transition from late adolescence to young adulthood (Blakemore and Robbins, 2012). Previous work has used broad definitions of elite status in sport, and as such overlooked different categories within the spectrum of elite athletes (Swann et al., 2015). Therefore it is important to consider subelite athletes as a discrete point on the developmental trajectory of elite sporting expertise. This work aims to investigate the influence of physical pressure on key indicators of decision-making in subelite athletes. It forms part of a wider project examining decision-making across different stages of the developmental trajectory in elite sport. In doing so, it aims to examine how to apply and develop psychological insights useful to an elite sporting environment. 32 subelite athletes (18 males, mean age: 20 years) participated in the study. Performance across three categories of decision-making was assessed under conditions of low and high physical pressure. Decision-making under risk was measured with performance of the Cambridge Gambling Task (CGT; Rogers et al., 1999), decision-making under uncertainty with the Balloon Analogue Risk Task (BART; Lejuez et al., 2002), and fast reactive responses and inhibition via the Stop Signal Reaction Time Task (SSRT; Logan, 1994). Physical exhaustion was induced via intervals of maximal exertion exercise on a wattbike. Under pressure subelite athletes showed increased risk taking for both decisions where probability outcomes were explicit (on the CGT), and those where probability outcomes were unknown (on the BART). Despite making quicker decisions under pressure, with fewer errors, on the CGT, subelite athletes showed a reduced ability to optimally adjust betting behavior according to reward and loss contingencies. Fast reactive responses to perceptual stimuli and response inhibition did not change as a result of physical pressure. Individual responses to pressure showed a negative correlation in that a decrease in reaction times on the SSRT Task under pressure was associated with an increase in risk taking on the BART. When assessing the applicability of results based on group averages to individual athletes, 17% of the sample showed an "average" response (within 1 SD of the mean) to pressure across all three decision-making tasks. Indicators of decision-making in a sample of subelite athletes are influenced by physical pressure, with a shift toward increased indiscriminate risk taking. The influence that physical pressure has on decision-making was different to that observed in world-class elite athletes; this highlights the importance of distinguishing between athletes at the elite level (Swann et al., 2015). The application of this work to a novel subgroup of elite athletes, including the implementation of a decision-making taxonomy, is discussed. © 2017 Elsevier B.V. All rights reserved.

Stressing The Person: Legal and Everyday Person Attributions Under Stress

PubMed Central

Kubota, Jennifer T.; Mojdehbakhsh, Rachel; Raio, Candace; Brosch, Tobias; Uleman, Jim S.; Phelps, Elizabeth A.

2014-01-01

When determining the cause of a person’s behavior, perceivers often overweigh dispositional explanations and underweigh situational explanations, an error known as the Fundamental Attribution Error (FAE). The FAE occurs in part because dispositional explanations are relatively automatic, whereas considering the situation requires additional cognitive effort. Stress is known to impair the prefrontal cortex and executive functions important for the attribution process. We investigated if stress increases dispositional attributions in common place and legal situations. Experiencing a physiological stressor increased participants’ cortisol, dispositional attributions of common everyday behaviors, and negative evaluations. When determining whether a crime was due to the defendant’s disposition or the mitigating situation, self-reported stress correlated with increased dispositional judgments of defendant’s behavior. These findings indicate that stress may makes people more likely to commit the FAE and less favorable in their evaluations of others both in daily life and when making socially consequential judicial decisions. PMID:25175000

Residents' numeric inputting error in computerized physician order entry prescription.

PubMed

Wu, Xue; Wu, Changxu; Zhang, Kan; Wei, Dong

2016-04-01

Computerized physician order entry (CPOE) system with embedded clinical decision support (CDS) can significantly reduce certain types of prescription error. However, prescription errors still occur. Various factors such as the numeric inputting methods in human computer interaction (HCI) produce different error rates and types, but has received relatively little attention. This study aimed to examine the effects of numeric inputting methods and urgency levels on numeric inputting errors of prescription, as well as categorize the types of errors. Thirty residents participated in four prescribing tasks in which two factors were manipulated: numeric inputting methods (numeric row in the main keyboard vs. numeric keypad) and urgency levels (urgent situation vs. non-urgent situation). Multiple aspects of participants' prescribing behavior were measured in sober prescribing situations. The results revealed that in urgent situations, participants were prone to make mistakes when using the numeric row in the main keyboard. With control of performance in the sober prescribing situation, the effects of the input methods disappeared, and urgency was found to play a significant role in the generalized linear model. Most errors were either omission or substitution types, but the proportion of transposition and intrusion error types were significantly higher than that of the previous research. Among numbers 3, 8, and 9, which were the less common digits used in prescription, the error rate was higher, which was a great risk to patient safety. Urgency played a more important role in CPOE numeric typing error-making than typing skills and typing habits. It was recommended that inputting with the numeric keypad had lower error rates in urgent situation. An alternative design could consider increasing the sensitivity of the keys with lower frequency of occurrence and decimals. To improve the usability of CPOE, numeric keyboard design and error detection could benefit from spatial incidence of errors found in this study. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Optimizing α for better statistical decisions: a case study involving the pace-of-life syndrome hypothesis: optimal α levels set to minimize Type I and II errors frequently result in different conclusions from those using α = 0.05.

PubMed

Mudge, Joseph F; Penny, Faith M; Houlahan, Jeff E

2012-12-01

Setting optimal significance levels that minimize Type I and Type II errors allows for more transparent and well-considered statistical decision making compared to the traditional α = 0.05 significance level. We use the optimal α approach to re-assess conclusions reached by three recently published tests of the pace-of-life syndrome hypothesis, which attempts to unify occurrences of different physiological, behavioral, and life history characteristics under one theory, over different scales of biological organization. While some of the conclusions reached using optimal α were consistent to those previously reported using the traditional α = 0.05 threshold, opposing conclusions were also frequently reached. The optimal α approach reduced probabilities of Type I and Type II errors, and ensured statistical significance was associated with biological relevance. Biologists should seriously consider their choice of α when conducting null hypothesis significance tests, as there are serious disadvantages with consistent reliance on the traditional but arbitrary α = 0.05 significance level. Copyright © 2012 WILEY Periodicals, Inc.

A recurrent network mechanism of time integration in perceptual decisions.

PubMed

Wong, Kong-Fatt; Wang, Xiao-Jing

2006-01-25

Recent physiological studies using behaving monkeys revealed that, in a two-alternative forced-choice visual motion discrimination task, reaction time was correlated with ramping of spike activity of lateral intraparietal cortical neurons. The ramping activity appears to reflect temporal accumulation, on a timescale of hundreds of milliseconds, of sensory evidence before a decision is reached. To elucidate the cellular and circuit basis of such integration times, we developed and investigated a simplified two-variable version of a biophysically realistic cortical network model of decision making. In this model, slow time integration can be achieved robustly if excitatory reverberation is primarily mediated by NMDA receptors; our model with only fast AMPA receptors at recurrent synapses produces decision times that are not comparable with experimental observations. Moreover, we found two distinct modes of network behavior, in which decision computation by winner-take-all competition is instantiated with or without attractor states for working memory. Decision process is closely linked to the local dynamics, in the "decision space" of the system, in the vicinity of an unstable saddle steady state that separates the basins of attraction for the two alternative choices. This picture provides a rigorous and quantitative explanation for the dependence of performance and response time on the degree of task difficulty, and the reason for which reaction times are longer in error trials than in correct trials as observed in the monkey experiment. Our reduced two-variable neural model offers a simple yet biophysically plausible framework for studying perceptual decision making in general.

Laboratory testing in primary care: A systematic review of health IT impacts.

PubMed

Maillet, Éric; Paré, Guy; Currie, Leanne M; Raymond, Louis; Ortiz de Guinea, Ana; Trudel, Marie-Claude; Marsan, Josianne

2018-08-01

Laboratory testing in primary care is a fundamental process that supports patient management and care. Any breakdown in the process may alter clinical information gathering and decision-making activities and can lead to medical errors and potential adverse outcomes for patients. Various information technologies are being used in primary care with the goal to support the process, maximize patient benefits and reduce medical errors. However, the overall impact of health information technologies on laboratory testing processes has not been evaluated. To synthesize the positive and negative impacts resulting from the use of health information technology in each phase of the laboratory 'total testing process' in primary care. We conducted a systematic review. Databases including Medline, PubMed, CINAHL, Web of Science and Google Scholar were searched. Studies eligible for inclusion reported empirical data on: 1) the use of a specific IT system, 2) the impacts of the systems to support the laboratory testing process, and were conducted in 3) primary care settings (including ambulatory care and primary care offices). Our final sample consisted of 22 empirical studies which were mapped to a framework that outlines the phases of the laboratory total testing process, focusing on phases where medical errors may occur. Health information technology systems support several phases of the laboratory testing process, from ordering the test to following-up with patients. This is a growing field of research with most studies focusing on the use of information technology during the final phases of the laboratory total testing process. The findings were largely positive. Positive impacts included easier access to test results by primary care providers, reduced turnaround times, and increased prescribed tests based on best practice guidelines. Negative impacts were reported in several studies: paper-based processes employed in parallel to the electronic process increased the potential for medical errors due to clinicians' cognitive overload; systems deemed not reliable or user-friendly hampered clinicians' performance; and organizational issues arose when results tracking relied on the prescribers' memory. The potential of health information technology lies not only in the exchange of health information, but also in knowledge sharing among clinicians. This review has underscored the important role played by cognitive factors, which are critical in the clinician's decision-making, the selection of the most appropriate tests, correct interpretation of the results and efficient interventions. By providing the right information, at the right time to the right clinician, many IT solutions adequately support the laboratory testing process and help primary care clinicians make better decisions. However, several technological and organizational barriers require more attention to fully support the highly fragmented and error-prone process of laboratory testing. Copyright © 2018 Elsevier B.V. All rights reserved.

The value of forecasting key-decision variables for rain-fed farming

NASA Astrophysics Data System (ADS)

Winsemius, Hessel; Werner, Micha

2013-04-01

Rain-fed farmers are highly vulnerable to variability in rainfall. Timely knowledge of the onset of the rainy season, the expected amount of rainfall and the occurrence of dry spells can help rain-fed farmers to plan the cropping season. Seasonal probabilistic weather forecasts may provide such information to farmers, but need to provide reliable forecasts of key variables with which farmers can make decisions. In this contribution, we present a new method to evaluate the value of meteorological forecasts in predicting these key variables. The proposed method measures skill by assessing whether a forecast was useful to this decision. This is done by taking into account the required accuracy of timing of the event to make the decision useful. The method progresses the estimate of forecast skill to forecast value by taking into account the required accuracy that is needed to make the decision valuable, based on the cost/loss ratio of possible decisions. The method is applied over the Limpopo region in Southern Africa. We demonstrate the method using the example of temporary water harvesting techniques. Such techniques require time to construct and must be ready long enough before the occurrence of a dry spell to be effective. The value of the forecasts to the decision used as an example is shown to be highly sensitive to the accuracy in the timing of forecasted dry spells, and the tolerance in the decision to timing error. The skill with which dry spells can be predicted is shown to be higher in some parts of the basin, indicating that these forecasts have higher value for the decision in those parts than in others. Through assessing the skill of forecasting key decision variables to the farmers we show that it is easier to understand if the forecasts have value in reducing risk, or if other adaptation strategies should be implemented.

Which non-technical skills do junior doctors require to prescribe safely? A systematic review.

PubMed

Dearden, Effie; Mellanby, Edward; Cameron, Helen; Harden, Jeni

2015-12-01

Prescribing errors are a major source of avoidable morbidity and mortality. Junior doctors write most in-hospital prescriptions and are the least experienced members of the healthcare team. This puts them at high risk of error and makes them attractive targets for interventions to improve prescription safety. Error analysis has shown a background of complex environments with multiple contributory conditions. Similar conditions in other high risk industries, such as aviation, have led to an increased understanding of so-called human factors and the use of non-technical skills (NTS) training to try to reduce error. To date no research has examined the NTS required for safe prescribing. The aim of this review was to develop a prototype NTS taxonomy for safe prescribing, by junior doctors, in hospital settings. A systematic search identified 14 studies analyzing prescribing behaviours and errors by junior doctors. Framework analysis was used to extract data from the studies and identify behaviours related to categories of NTS that might be relevant to safe and effective prescribing performance by junior doctors. Categories were derived from existing literature and inductively from the data. A prototype taxonomy of relevant categories (situational awareness, decision making, communication and team working, and task management) and elements was constructed. This prototype will form the basis of future work to create a tool that can be used for training and assessment of medical students and junior doctors to reduce prescribing error in the future. © 2015 The British Pharmacological Society.

Descriptive Summaries of the Research, Development, Test and Evaluation, Army Appropriation. Supporting Data FY 1994, Budget Estimates Submitted to Congress, April 1993

DTIC Science & Technology

1993-04-01

determining effective group functioning, leader-group interaction , and decision making; (2) factors that determine effective, low error human performance...infectious disease and biological defense vaccines and drugs , vision, neurotxins, neurochemistry, molecular neurobiology, neurodegenrative diseases...Potential Rotor/Comprehensive Analysis Model for Rotor Aerodynamics-Johnson Aeronautics (FPR/CAMRAD-JA) code to predict Blade Vortex Interaction (BVI

Expert Performance and Time Pressure: Implications for Automation Failures in Aviation

DTIC Science & Technology

2016-09-30

Sciences , 7, 454-459. Fitts, P. M. (Ed.), (1951). Human engineering for an effective air navigation and control system. Washington, DC: National...expert performance. Implications for the aviation domain are discussed. 15. SUBJECT TERMS Decision Making , Time Pressure, Error, Situational Awareness...automation interaction has been a challenge for human factors for quite some time and its relevance continues to grow (e.g., Bainbridge, 1983; de Winter

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.

Cognitive balanced model: a conceptual scheme of diagnostic decision making.

PubMed

Lucchiari, Claudio; Pravettoni, Gabriella

2012-02-01

Diagnostic reasoning is a critical aspect of clinical performance, having a high impact on quality and safety of care. Although diagnosis is fundamental in medicine, we still have a poor understanding of the factors that determine its course. According to traditional understanding, all information used in diagnostic reasoning is objective and logically driven. However, these conditions are not always met. Although we would be less likely to make an inaccurate diagnosis when following rational decision making, as described by normative models, the real diagnostic process works in a different way. Recent work has described the major cognitive biases in medicine as well as a number of strategies for reducing them, collectively called debiasing techniques. However, advances have encountered obstacles in achieving implementation into clinical practice. While traditional understanding of clinical reasoning has failed to consider contextual factors, most debiasing techniques seem to fail in raising sound and safer medical praxis. Technological solutions, being data driven, are fundamental in increasing care safety, but they need to consider human factors. Thus, balanced models, cognitive driven and technology based, are needed in day-to-day applications to actually improve the diagnostic process. The purpose of this article, then, is to provide insight into cognitive influences that have resulted in wrong, delayed or missed diagnosis. Using a cognitive approach, we describe the basis of medical error, with particular emphasis on diagnostic error. We then propose a conceptual scheme of the diagnostic process by the use of fuzzy cognitive maps. © 2011 Blackwell Publishing Ltd.

[Cognitive traps and clinical decisions].

PubMed

Motterlini, Matteo

2017-12-01

We are fallible, we have limited computational capabilities, limited access to information, little memory. Moreover, in everyday life, we feel joy, fear, anger, and other emotions that influence our decisions in a little, "calculated" way. Not everyone, however, is also aware that the mistakes we make are often systematic and therefore, in particular circumstances, are foreseeable. Doctors and patients are constantly called upon to make decisions. They need to identify relevant information (for example, the symptoms or outcome of an examination), formulate a judgment (for example a diagnosis), choose an action course among the various possible ones based on one's own preferences (e.g. medication or surgery), so act. The exact size of the medical error is unknown, but probably huge. In fact, the more we investigate and the more we find. Often these mistakes depend on the cognitive process. Any (rational) decision requires, in particular, an assessment of the possible effects of the action it implements; for example how much pleasure or pain it will cause us. In the medical field, too, the principle of informed consent provides that the patient's preferences and values are to guide clinical choices. Yet, not always the preferences that people express before making an experience match with their preferences after living that experience. Some ingenious experiments suggest (in a seemingly paradoxical way) that before a direct experience, people prefer less pain; after that experience they prefer more, but with a better memory.

Value of information analysis for groundwater quality monitoring network design Case study: Eocene Aquifer, Palestine

NASA Astrophysics Data System (ADS)

Khader, A.; McKee, M.

2010-12-01

Value of information (VOI) analysis evaluates the benefit of collecting additional information to reduce or eliminate uncertainty in a specific decision-making context. It makes explicit any expected potential losses from errors in decision making due to uncertainty and identifies the “best” information collection strategy as one that leads to the greatest expected net benefit to the decision-maker. This study investigates the willingness to pay for groundwater quality monitoring in the Eocene Aquifer, Palestine, which is an unconfined aquifer located in the northern part of the West Bank. The aquifer is being used by 128,000 Palestinians to fulfill domestic and agricultural demands. The study takes into account the consequences of pollution and the options the decision maker might face. Since nitrate is the major pollutant in the aquifer, the consequences of nitrate pollution were analyzed, which mainly consists of the possibility of methemoglobinemia (blue baby syndrome). In this case, the value of monitoring was compared to the costs of treating for methemoglobinemia or the costs of other options like water treatment, using bottled water or importing water from outside the aquifer. And finally, an optimal monitoring network that takes into account the uncertainties in recharge (climate), aquifer properties (hydraulic conductivity), pollutant chemical reaction (decay factor), and the value of monitoring is designed by utilizing a sparse Bayesian modeling algorithm called a relevance vector machine.

Short communication: Prediction of retention pay-off using a machine learning algorithm.

PubMed

Shahinfar, Saleh; Kalantari, Afshin S; Cabrera, Victor; Weigel, Kent

2014-05-01

Replacement decisions have a major effect on dairy farm profitability. Dynamic programming (DP) has been widely studied to find the optimal replacement policies in dairy cattle. However, DP models are computationally intensive and might not be practical for daily decision making. Hence, the ability of applying machine learning on a prerun DP model to provide fast and accurate predictions of nonlinear and intercorrelated variables makes it an ideal methodology. Milk class (1 to 5), lactation number (1 to 9), month in milk (1 to 20), and month of pregnancy (0 to 9) were used to describe all cows in a herd in a DP model. Twenty-seven scenarios based on all combinations of 3 levels (base, 20% above, and 20% below) of milk production, milk price, and replacement cost were solved with the DP model, resulting in a data set of 122,716 records, each with a calculated retention pay-off (RPO). Then, a machine learning model tree algorithm was used to mimic the evaluated RPO with DP. The correlation coefficient factor was used to observe the concordance of RPO evaluated by DP and RPO predicted by the model tree. The obtained correlation coefficient was 0.991, with a corresponding value of 0.11 for relative absolute error. At least 100 instances were required per model constraint, resulting in 204 total equations (models). When these models were used for binary classification of positive and negative RPO, error rates were 1% false negatives and 9% false positives. Applying this trained model from simulated data for prediction of RPO for 102 actual replacement records from the University of Wisconsin-Madison dairy herd resulted in a 0.994 correlation with 0.10 relative absolute error rate. Overall results showed that model tree has a potential to be used in conjunction with DP to assist farmers in their replacement decisions. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Speed versus accuracy in decision-making ants: expediting politics and policy implementation.

PubMed

Franks, Nigel R; Dechaume-Moncharmont, François-Xavier; Hanmore, Emma; Reynolds, Jocelyn K

2009-03-27

Compromises between speed and accuracy are seemingly inevitable in decision-making when accuracy depends on time-consuming information gathering. In collective decision-making, such compromises are especially likely because information is shared to determine corporate policy. This political process will also take time. Speed-accuracy trade-offs occur among house-hunting rock ants, Temnothorax albipennis. A key aspect of their decision-making is quorum sensing in a potential new nest. Finding a sufficient number of nest-mates, i.e. a quorum threshold (QT), in a potential nest site indicates that many ants find it suitable. Quorum sensing collates information. However, the QT is also used as a switch, from recruitment of nest-mates to their new home by slow tandem running, to recruitment by carrying, which is three times faster. Although tandem running is slow, it effectively enables one successful ant to lead and teach another the route between the nests. Tandem running creates positive feedback; more and more ants are shown the way, as tandem followers become, in turn, tandem leaders. The resulting corps of trained ants can then quickly carry their nest-mates; but carried ants do not learn the route. Therefore, the QT seems to set both the amount of information gathered and the speed of the emigration. Low QTs might cause more errors and a slower emigration--the worst possible outcome. This possible paradox of quick decisions leading to slow implementation might be resolved if the ants could deploy another positive-feedback recruitment process when they have used a low QT. Reverse tandem runs occur after carrying has begun and lead ants back from the new nest to the old one. Here we show experimentally that reverse tandem runs can bring lost scouts into an active role in emigrations and can help to maintain high-speed emigrations. Thus, in rock ants, although quick decision-making and rapid implementation of choices are initially in opposition, a third recruitment method can restore rapid implementation after a snap decision. This work reveals a principle of widespread importance: the dynamics of collective decision-making (i.e. the politics) and the dynamics of policy implementation are sometimes intertwined, and only by analysing the mechanisms of both can we understand certain forms of adaptive organization.

Psychometric properties of the SDM-Q-9 questionnaire for shared decision-making in multiple sclerosis: item response theory modelling and confirmatory factor analysis.

PubMed

Ballesteros, Javier; Moral, Ester; Brieva, Luis; Ruiz-Beato, Elena; Prefasi, Daniel; Maurino, Jorge

2017-04-22

Shared decision-making is a cornerstone of patient-centred care. The 9-item Shared Decision-Making Questionnaire (SDM-Q-9) is a brief self-assessment tool for measuring patients' perceived level of involvement in decision-making related to their own treatment and care. Information related to the psychometric properties of the SDM-Q-9 for multiple sclerosis (MS) patients is limited. The objective of this study was to assess the performance of the items composing the SDM-Q-9 and its dimensional structure in patients with relapsing-remitting MS. A non-interventional, cross-sectional study in adult patients with relapsing-remitting MS was conducted in 17 MS units throughout Spain. A nonparametric item response theory (IRT) analysis was used to assess the latent construct and dimensional structure underlying the observed responses. A parametric IRT model, General Partial Credit Model, was fitted to obtain estimates of the relationship between the latent construct and item characteristics. The unidimensionality of the SDM-Q-9 instrument was assessed by confirmatory factor analysis. A total of 221 patients were studied (mean age = 42.1 ± 9.9 years, 68.3% female). Median Expanded Disability Status Scale score was 2.5 ± 1.5. Most patients reported taking part in each step of the decision-making process. Internal reliability of the instrument was high (Cronbach's α = 0.91) and the overall scale scalability score was 0.57, indicative of a strong scale. All items, except for the item 1, showed scalability indices higher than 0.30. Four items (items 6 through to 9) conveyed more than half of the SDM-Q-9 overall information (67.3%). The SDM-Q-9 was a good fit for a unidimensional latent structure (comparative fit index = 0.98, root-mean-square error of approximation = 0.07). All freely estimated parameters were statistically significant (P < 0.001). All items presented standardized parameter estimates with salient loadings (>0.40) with the exception of item 1 which presented the lowest loading (0.26). Items 6 through to 8 were the most relevant items for shared decision-making. The SDM-Q-9 presents appropriate psychometric properties and is therefore useful for assessing different aspects of shared decision-making in patients with multiple sclerosis.

Quality of death notification forms in North West Bank/Palestine: a descriptive study.

PubMed

Qaddumi, Jamal A S; Nazzal, Zaher; Yacoup, Allam R S; Mansour, Mahmoud

2017-04-11

The death notification forms (DNFs) are important documents. Thus, inability to fill it properly by physicians will affect the national mortality report and, consequently, the evidence-based decision making. The errors in filling DNFs are common all over the world and are different in types and causes. We aimed to evaluate the quality of DNFs in terms of completeness and types of errors in the cause of death section. A descriptive study was conducted to review 2707 DNFs in North West Bank/Palestine during the year 2012 using data abstraction sheets. SPSS 17.0 was used to show the frequency of major and minor errors committed in filling the DNFs. Surprisingly, only 1% of the examined DNFs had their cause of death section filled completely correct. The immediate cause of death was correctly identified in 5.9% of all DNFs and the underlying cause of death was correctly reported in 55.4% of them. The sequence was incorrect in 41.5% of the DNFs. The most frequently documented minor error was "Not writing Time intervals" error (97.0%). Almost all DNFs contained at least one minor or major error. This high percentage of errors may affect the mortality and morbidity statistics, public health research and the process of providing evidence for health policy. Training workshops on DNF completion for newly recruited employees and at the beginning of the residency program are recommended on a regular basis. As well, we recommend reviewing the national DNFs to simplify it and make it consistent with updated evidence-based guidelines and recommendation.

Psycho-cognitive predictors of burnout in healthcare professionals working in emergency departments.

PubMed

Masiero, Marianna; Cutica, Ilaria; Russo, Selena; Mazzocco, Ketti; Pravettoni, Gabriella

2018-07-01

Healthcare professionals working in emergency departments commonly experience high work pressure and stress due to witnessing human suffering and the unpredictable nature of the work. Several studies have identified variables that affect burnout syndrome, but poor data are available about the predictors of the different dimensions of burnout (depersonalisation, emotional exhaustion, professional inefficacy and disillusionment). Some research has suggested that alexithymia, coping style and decision-making style may predict burnout. We conducted a noninterventional study to investigate whether and how alexithymia, coping style and decision-making style are associated with the different dimensions of burnout. We recruited a convenience sample of 93 healthcare professionals working in an Italian emergency departments. Participants completed a questionnaire assessing their level of burnout (the Link Burnout Questionnaire), and possible burnout predictors: decision-making style, alexithymia and the coping style. Four bivariate linear regressions were performed to define the predictors that characterised the dimensions of burnout. We found that an avoidant decision-making style and a difficulty to identify and describe feelings (a difficulty close to alexithymia even though not as severe) are strong predictors of some burnout dimensions. Individuals who experience relational depersonalisation are more likely to turn to religion as a way to cope. Our research shows that, to some extent, difficulties in emotion regulation and the attitude to avoid or postpone decisions characterised burnout. These results might be used to develop tailored psycho-educational interventions. This might help healthcare professionals to develop personal skills to cope with the critical conditions that characterise their work and to enable them to recognise potential risk factors that favour burnout. This has pivotal implications for the maintenance of the patient-healthcare professional relationship and in reducing clinical errors. © 2018 John Wiley & Sons Ltd.

Non-equilibrium physics of neural networks for leaning, memory and decision making: landscape and flux perspectives

NASA Astrophysics Data System (ADS)

Wang, Jin

Cognitive behaviors are determined by underlying neural networks. Many brain functions, such as learning and memory, can be described by attractor dynamics. We developed a theoretical framework for global dynamics by quantifying the landscape associated with the steady state probability distributions and steady state curl flux, measuring the degree of non-equilibrium through detailed balance breaking. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. Both landscape and flux determine the kinetic paths and speed of decision making. The kinetics and global stability of decision making are explored by quantifying the landscape topography through the barrier heights and the mean first passage time. The theoretical predictions are in agreement with experimental observations: more errors occur under time pressure. We quantitatively explored two mechanisms of the speed-accuracy tradeoff with speed emphasis and further uncovered the tradeoffs among speed, accuracy, and energy cost. Our results show an optimal balance among speed, accuracy, and the energy cost in decision making. We uncovered possible mechanisms of changes of mind and how mind changes improve performance in decision processes. Our landscape approach can help facilitate an understanding of the underlying physical mechanisms of cognitive processes and identify the key elements in neural networks.

Mesolimbic Dopamine Signals the Value of Work

PubMed Central

Hamid, Arif A.; Pettibone, Jeffrey R.; Mabrouk, Omar S.; Hetrick, Vaughn L.; Schmidt, Robert; Vander Weele, Caitlin M.; Kennedy, Robert T.; Aragona, Brandon J.; Berke, Joshua D.

2015-01-01

Dopamine cell firing can encode errors in reward prediction, providing a learning signal to guide future behavior. Yet dopamine is also a key modulator of motivation, invigorating current behavior. Existing theories propose that fast (“phasic”) dopamine fluctuations support learning, while much slower (“tonic”) dopamine changes are involved in motivation. We examined dopamine release in the nucleus accumbens across multiple time scales, using complementary microdialysis and voltammetric methods during adaptive decision-making. We first show that minute-by-minute dopamine levels covary with reward rate and motivational vigor. We then show that second-by-second dopamine release encodes an estimate of temporally-discounted future reward (a value function). We demonstrate that changing dopamine immediately alters willingness to work, and reinforces preceding action choices by encoding temporal-difference reward prediction errors. Our results indicate that dopamine conveys a single, rapidly-evolving decision variable, the available reward for investment of effort, that is employed for both learning and motivational functions. PMID:26595651

Vicarious trial and error

PubMed Central

Redish, A. David

2016-01-01

When rats come to a decision point, they sometimes pause and look back and forth as if deliberating over the choice; at other times, they proceed as if they have already made their decision. In the 1930s, this pause-and-look behaviour was termed ‘vicarious trial and error’ (VTE), with the implication that the rat was ‘thinking about the future’. The discovery in 2007 that the firing of hippocampal place cells gives rise to alternating representations of each of the potential path options in a serial manner during VTE suggested a possible neural mechanism that could underlie the representations of future outcomes. More-recent experiments examining VTE in rats suggest that there are direct parallels to human processes of deliberative decision making, working memory and mental time travel. PMID:26891625

Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms

PubMed Central

List, Christian; Elsholtz, Christian; Seeley, Thomas D.

2008-01-01

Condorcet's jury theorem shows that when the members of a group have noisy but independent information about what is best for the group as a whole, majority decisions tend to outperform dictatorial ones. When voting is supplemented by communication, however, the resulting interdependencies between decision makers can strengthen or undermine this effect: they can facilitate information pooling, but also amplify errors. We consider an intriguing non-human case of independent information pooling combined with communication: the case of nest-site choice by honeybee (Apis mellifera) swarms. It is empirically well documented that when there are different nest sites that vary in quality, the bees usually choose the best one. We develop a new agent-based model of the bees' decision process and show that its remarkable reliability stems from a particular interplay of independence and interdependence between the bees. PMID:19073474

QTest: Quantitative Testing of Theories of Binary Choice.

PubMed

Regenwetter, Michel; Davis-Stober, Clintin P; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of "Random Cumulative Prospect Theory." A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.

From information processing to decisions: Formalizing and comparing psychologically plausible choice models.

PubMed

Heck, Daniel W; Hilbig, Benjamin E; Moshagen, Morten

2017-08-01

Decision strategies explain how people integrate multiple sources of information to make probabilistic inferences. In the past decade, increasingly sophisticated methods have been developed to determine which strategy explains decision behavior best. We extend these efforts to test psychologically more plausible models (i.e., strategies), including a new, probabilistic version of the take-the-best (TTB) heuristic that implements a rank order of error probabilities based on sequential processing. Within a coherent statistical framework, deterministic and probabilistic versions of TTB and other strategies can directly be compared using model selection by minimum description length or the Bayes factor. In an experiment with inferences from given information, only three of 104 participants were best described by the psychologically plausible, probabilistic version of TTB. Similar as in previous studies, most participants were classified as users of weighted-additive, a strategy that integrates all available information and approximates rational decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

The quality of emergency room radiograph interpretations.

PubMed

McLain, P L; Kirkwood, C R

1985-05-01

Primary care physicians often make patient management decisions based in part on their own interpretations of radiographs. This important area of clinical decision making has not been previously analyzed in the literature. In this series of 294 consecutive radiographs from rural practice, interpretative disagreement between primary care providers and backup radiologists occurred 9.2 percent of the time, a discordance rate similar to that seen among radiologists in other studies. Although a majority of the films for which interpretative disagreement occurred had potential implications for influencing patient management, in only seven cases did actual case management vary from appropriate norms. Follow-up of cases where interpretative disagreement occurred revealed that in only two cases did unsatisfactory outcomes occur. Primary care physicians can provide high-quality radiographic interpretations that, when coupled with clinical information, yield extremely low rates of error or potential for poor patient outcomes.

Stochastic Watershed Models for Risk Based Decision Making

NASA Astrophysics Data System (ADS)

Vogel, R. M.

2017-12-01

Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

Ethnic diversity deflates price bubbles

PubMed Central

Levine, Sheen S.; Apfelbaum, Evan P.; Bernard, Mark; Bartelt, Valerie L.; Zajac, Edward J.; Stark, David

2014-01-01

Markets are central to modern society, so their failures can be devastating. Here, we examine a prominent failure: price bubbles. Bubbles emerge when traders err collectively in pricing, causing misfit between market prices and the true values of assets. The causes of such collective errors remain elusive. We propose that bubbles are affected by ethnic homogeneity in the market and can be thwarted by diversity. In homogenous markets, traders place undue confidence in the decisions of others. Less likely to scrutinize others’ decisions, traders are more likely to accept prices that deviate from true values. To test this, we constructed experimental markets in Southeast Asia and North America, where participants traded stocks to earn money. We randomly assigned participants to ethnically homogeneous or diverse markets. We find a marked difference: Across markets and locations, market prices fit true values 58% better in diverse markets. The effect is similar across sites, despite sizeable differences in culture and ethnic composition. Specifically, in homogenous markets, overpricing is higher as traders are more likely to accept speculative prices. Their pricing errors are more correlated than in diverse markets. In addition, when bubbles burst, homogenous markets crash more severely. The findings suggest that price bubbles arise not only from individual errors or financial conditions, but also from the social context of decision making. The evidence may inform public discussion on ethnic diversity: it may be beneficial not only for providing variety in perspectives and skills, but also because diversity facilitates friction that enhances deliberation and upends conformity. PMID:25404313

Ethnic diversity deflates price bubbles.

PubMed

Levine, Sheen S; Apfelbaum, Evan P; Bernard, Mark; Bartelt, Valerie L; Zajac, Edward J; Stark, David

2014-12-30

Markets are central to modern society, so their failures can be devastating. Here, we examine a prominent failure: price bubbles. Bubbles emerge when traders err collectively in pricing, causing misfit between market prices and the true values of assets. The causes of such collective errors remain elusive. We propose that bubbles are affected by ethnic homogeneity in the market and can be thwarted by diversity. In homogenous markets, traders place undue confidence in the decisions of others. Less likely to scrutinize others' decisions, traders are more likely to accept prices that deviate from true values. To test this, we constructed experimental markets in Southeast Asia and North America, where participants traded stocks to earn money. We randomly assigned participants to ethnically homogeneous or diverse markets. We find a marked difference: Across markets and locations, market prices fit true values 58% better in diverse markets. The effect is similar across sites, despite sizeable differences in culture and ethnic composition. Specifically, in homogenous markets, overpricing is higher as traders are more likely to accept speculative prices. Their pricing errors are more correlated than in diverse markets. In addition, when bubbles burst, homogenous markets crash more severely. The findings suggest that price bubbles arise not only from individual errors or financial conditions, but also from the social context of decision making. The evidence may inform public discussion on ethnic diversity: it may be beneficial not only for providing variety in perspectives and skills, but also because diversity facilitates friction that enhances deliberation and upends conformity.

Performance analysis of adaptive equalization for coherent acoustic communications in the time-varying ocean environment.

PubMed

Preisig, James C

2005-07-01

Equations are derived for analyzing the performance of channel estimate based equalizers. The performance is characterized in terms of the mean squared soft decision error (sigma2(s)) of each equalizer. This error is decomposed into two components. These are the minimum achievable error (sigma2(0)) and the excess error (sigma2(e)). The former is the soft decision error that would be realized by the equalizer if the filter coefficient calculation were based upon perfect knowledge of the channel impulse response and statistics of the interfering noise field. The latter is the additional soft decision error that is realized due to errors in the estimates of these channel parameters. These expressions accurately predict the equalizer errors observed in the processing of experimental data by a channel estimate based decision feedback equalizer (DFE) and a passive time-reversal equalizer. Further expressions are presented that allow equalizer performance to be predicted given the scattering function of the acoustic channel. The analysis using these expressions yields insights into the features of surface scattering that most significantly impact equalizer performance in shallow water environments and motivates the implementation of a DFE that is robust with respect to channel estimation errors.

A plastic corticostriatal circuit model of adaptation in perceptual decision making

PubMed Central

Hsiao, Pao-Yueh; Lo, Chung-Chuan

2013-01-01

The ability to optimize decisions and adapt them to changing environments is a crucial brain function that increase survivability. Although much has been learned about the neuronal activity in various brain regions that are associated with decision making, and about how the nervous systems may learn to achieve optimization, the underlying neuronal mechanisms of how the nervous systems optimize decision strategies with preference given to speed or accuracy, and how the systems adapt to changes in the environment, remain unclear. Based on extensive empirical observations, we addressed the question by extending a previously described cortico-basal ganglia circuit model of perceptual decisions with the inclusion of a dynamic dopamine (DA) system that modulates spike-timing dependent plasticity (STDP). We found that, once an optimal model setting that maximized the reward rate was selected, the same setting automatically optimized decisions across different task environments through dynamic balancing between the facilitating and depressing components of the DA dynamics. Interestingly, other model parameters were also optimal if we considered the reward rate that was weighted by the subject's preferences for speed or accuracy. Specifically, the circuit model favored speed if we increased the phasic DA response to the reward prediction error, whereas the model favored accuracy if we reduced the tonic DA activity or the phasic DA responses to the estimated reward probability. The proposed model provides insight into the roles of different components of DA responses in decision adaptation and optimization in a changing environment. PMID:24339814

Self-evaluation of decision-making: A general Bayesian framework for metacognitive computation.

PubMed

Fleming, Stephen M; Daw, Nathaniel D

2017-01-01

People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a "second-order" inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one's own actions to metacognitive judgments. In addition, the model provides insight into why subjects' metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation

PubMed Central

2017-01-01

People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a “second-order” inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one’s own actions to metacognitive judgments. In addition, the model provides insight into why subjects’ metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. PMID:28004960

Airline Crew Training

NASA Technical Reports Server (NTRS)

1989-01-01

The discovery that human error has caused many more airline crashes than mechanical malfunctions led to an increased emphasis on teamwork and coordination in airline flight training programs. Human factors research at Ames Research Center has produced two crew training programs directed toward more effective operations. Cockpit Resource Management (CRM) defines areas like decision making, workload distribution, communication skills, etc. as essential in addressing human error problems. In 1979, a workshop led to the implementation of the CRM program by United Airlines, and later other airlines. In Line Oriented Flight Training (LOFT), crews fly missions in realistic simulators while instructors induce emergency situations requiring crew coordination. This is followed by a self critique. Ames Research Center continues its involvement with these programs.

Cognitive bias in clinical practice - nurturing healthy skepticism among medical students.

PubMed

Bhatti, Alysha

2018-01-01

Errors in clinical reasoning, known as cognitive biases, are implicated in a significant proportion of diagnostic errors. Despite this knowledge, little emphasis is currently placed on teaching cognitive psychology in the undergraduate medical curriculum. Understanding the origin of these biases and their impact on clinical decision making helps stimulate reflective practice. This article outlines some of the common types of cognitive biases encountered in the clinical setting as well as cognitive debiasing strategies. Medical educators should nurture healthy skepticism among medical students by raising awareness of cognitive biases and equipping them with robust tools to circumvent such biases. This will enable tomorrow's doctors to improve the quality of care delivered, thus optimizing patient outcomes.

Decision aids for multiple-decision disease management as affected by weather input errors.

PubMed

Pfender, W F; Gent, D H; Mahaffee, W F; Coop, L B; Fox, A D

2011-06-01

Many disease management decision support systems (DSSs) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation, or estimation from off-site sources, may affect model calculations and management decision recommendations. The extent to which errors in weather inputs affect the quality of the final management outcome depends on a number of aspects of the disease management context, including whether management consists of a single dichotomous decision, or of a multi-decision process extending over the cropping season(s). Decision aids for multi-decision disease management typically are based on simple or complex algorithms of weather data which may be accumulated over several days or weeks. It is difficult to quantify accuracy of multi-decision DSSs due to temporally overlapping disease events, existence of more than one solution to optimizing the outcome, opportunities to take later recourse to modify earlier decisions, and the ongoing, complex decision process in which the DSS is only one component. One approach to assessing importance of weather input errors is to conduct an error analysis in which the DSS outcome from high-quality weather data is compared with that from weather data with various levels of bias and/or variance from the original data. We illustrate this analytical approach for two types of DSS, an infection risk index for hop powdery mildew and a simulation model for grass stem rust. Further exploration of analysis methods is needed to address problems associated with assessing uncertainty in multi-decision DSSs.

Decision making under uncertainty: a quasimetric approach.

PubMed

N'Guyen, Steve; Moulin-Frier, Clément; Droulez, Jacques

2013-01-01

We propose a new approach for solving a class of discrete decision making problems under uncertainty with positive cost. This issue concerns multiple and diverse fields such as engineering, economics, artificial intelligence, cognitive science and many others. Basically, an agent has to choose a single or series of actions from a set of options, without knowing for sure their consequences. Schematically, two main approaches have been followed: either the agent learns which option is the correct one to choose in a given situation by trial and error, or the agent already has some knowledge on the possible consequences of his decisions; this knowledge being generally expressed as a conditional probability distribution. In the latter case, several optimal or suboptimal methods have been proposed to exploit this uncertain knowledge in various contexts. In this work, we propose following a different approach, based on the geometric intuition of distance. More precisely, we define a goal independent quasimetric structure on the state space, taking into account both cost function and transition probability. We then compare precision and computation time with classical approaches.

Intervention decision-making processes and information preferences of parents of children with autism spectrum disorders.

PubMed

Grant, N; Rodger, S; Hoffmann, T

2016-01-01

When a child is diagnosed with autism, parents are faced with the task of choosing from many different intervention options. To find information about the options available, parents turn to a number of different sources. This study explores parents' (n = 23) intervention decision-making processes and information preferences following the diagnosis of ASD for their child. Qualitative thematic analysis of verbatim transcripts from interviews and focus groups involving parents of children with an autism diagnosis was undertaken. Analysis of the results revealed that there are concurrent emotional and pragmatic intervention 'journeys' undertaken by parents post diagnosis, which encompass the primary themes of: (1) information sources used, (2) parents' information preferences and (3) factors influencing intervention decision making. Parents described a journey from the point of diagnosis that involved seeking information on ASD interventions from multiple sources, with the Internet being the primary source. They were overwhelmed by the sheer volume of information available, and their preferences for information varied according to their stage in the journey post diagnosis. Parents had a 'trial and error' approach to choosing ASD interventions, with confidence increasing as they became more familiar with their child's condition, and had opportunities to explore numerous information sources about their child's diagnosis. While confidence increased over time, consideration of the effectiveness or evidence supporting interventions remained largely absent throughout the journey. This study highlights the need for parents of children with ASD to be supported to make informed intervention decisions, particularly with consideration for research evidence. © 2015 John Wiley & Sons Ltd.

Accomplishments of Naturalistic Decision Making Research and Applications to Emerging Defense Challenges

DTIC Science & Technology

2015-07-27

studying an expert physician. In Proceedings of the 8th International Conference on Artificial Intelligence (pp. ###-###). Los Altos, CA: Morgan...incidentally on analogy lo particular past cases (e.g., a fire involving a billboard on a rooftop brought to mind a past case involving a billboard). Rather...Action. Los Angeles, CA: Sage CQ Press. Bums, K. (2005). Mental models and normal errors. In H, Montgomery, R, Lipshitz & B, Brehmer (Eds.), How

Workshop on Aeronautical Decision Making (ADM). Volume 2. Plenary Session with Presentations and Proposed Action Plan

DTIC Science & Technology

1992-08-01

programs have several common functional components dealing with: attention , crew, stress, mental attitude, and risk issues. The role which the five...five interrelated concept areas furnish "rules and tools" to help prevent common errors. For instance: 1. Attention management issues include...pilots must manage his/her attention in a timely manor and sequentially employ the other cockpit management tools (for controlling stress etc.). The text

On the internal target model in a tracking task

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Baron, S.

1981-01-01

An optimal control model for predicting operator's dynamic responses and errors in target tracking ability is summarized. The model, which predicts asymmetry in the tracking data, is dependent on target maneuvers and trajectories. Gunners perception, decision making, control, and estimate of target positions and velocity related to crossover intervals are discussed. The model provides estimates for means, standard deviations, and variances for variables investigated and for operator estimates of future target positions and velocities.

A meta-analytic review of two modes of learning and the description-experience gap.

PubMed

Wulff, Dirk U; Mergenthaler-Canseco, Max; Hertwig, Ralph

2018-02-01

People can learn about the probabilistic consequences of their actions in two ways: One is by consulting descriptions of an action's consequences and probabilities (e.g., reading up on a medication's side effects). The other is by personally experiencing the probabilistic consequences of an action (e.g., beta testing software). In principle, people taking each route can reach analogous states of knowledge and consequently make analogous decisions. In the last dozen years, however, research has demonstrated systematic discrepancies between description- and experienced-based choices. This description-experience gap has been attributed to factors including reliance on a small set of experience, the impact of recency, and different weighting of probability information in the two decision types. In this meta-analysis focusing on studies using the sampling paradigm of decisions from experience, we evaluated these and other determinants of the decision-experience gap by reference to more than 70,000 choices made by more than 6,000 participants. We found, first, a robust description-experience gap but also a key moderator, namely, problem structure. Second, the largest determinant of the gap was reliance on small samples and the associated sampling error: free to terminate search, individuals explored too little to experience all possible outcomes. Third, the gap persisted when sampling error was basically eliminated, suggesting other determinants. Fourth, the occurrence of recency was contingent on decision makers' autonomy to terminate search, consistent with the notion of optional stopping. Finally, we found indications of different probability weighting in decisions from experience versus decisions from description when the problem structure involved a risky and a safe option. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

An exploration of decision aid effectiveness: the impact of promoting affective vs. deliberative processing on a health-related decision.

PubMed

Davis, Esther L; McCaffery, Kirsten; Mullan, Barbara; Juraskova, Ilona

2015-12-01

Decision aids (DAs) are non-directive communication tools that help patients make value-consistent health-care decisions. However, most DAs have been developed without an explicit theoretical framework, resulting in a lack of understanding of how DAs achieve outcomes. To investigate the effect of promoting affective vs. deliberative processing on DA effectiveness based on dual-process theory. One hundred and forty-eight female university students participated in a randomized controlled experiment with three conditions: emotion-focused, information-focused and control. Preference-value consistency, knowledge, decisional conflict and satisfaction were compared across the conditions using planned contrast analyses. The intervention comprised two different DAs and instructional manipulations. The emotion-focused condition received a modified DA with affective content and instructions to induce an affective reaction. The information-focused and control conditions received the same DA without the affective content. The information-focused condition received additional instructions to induce deliberative processing. Controlling for the experiment-wise error rate at P < 0.017, the emotion-focused and information-focused conditions had significantly higher decisional satisfaction than the control condition (P < 0.001). The emotion-focused condition did not demonstrate preference-value consistency. There were no significant differences for decisional conflict and knowledge. Results suggest that the promotion of affective processing may hinder value-consistent decision making, while deliberative processing may enhance decisional satisfaction. This investigation of the effect of affective and deliberative processes in DA-supported decision making has implications for the design and use of DAs. DA effectiveness may be enhanced by incorporating a simple instruction to focus on the details of the information. © 2014 John Wiley & Sons Ltd.

Supplier Selection Using Weighted Utility Additive Method

NASA Astrophysics Data System (ADS)

Karande, Prasad; Chakraborty, Shankar

2015-10-01

Supplier selection is a multi-criteria decision-making (MCDM) problem which mainly involves evaluating a number of available suppliers according to a set of common criteria for choosing the best one to meet the organizational needs. For any manufacturing or service organization, selecting the right upstream suppliers is a key success factor that will significantly reduce purchasing cost, increase downstream customer satisfaction and improve competitive ability. The past researchers have attempted to solve the supplier selection problem employing different MCDM techniques which involve active participation of the decision makers in the decision-making process. This paper deals with the application of weighted utility additive (WUTA) method for solving supplier selection problems. The WUTA method, an extension of utility additive approach, is based on ordinal regression and consists of building a piece-wise linear additive decision model from a preference structure using linear programming (LP). It adopts preference disaggregation principle and addresses the decision-making activities through operational models which need implicit preferences in the form of a preorder of reference alternatives or a subset of these alternatives present in the process. The preferential preorder provided by the decision maker is used as a restriction of a LP problem, which has its own objective function, minimization of the sum of the errors associated with the ranking of each alternative. Based on a given reference ranking of alternatives, one or more additive utility functions are derived. Using these utility functions, the weighted utilities for individual criterion values are combined into an overall weighted utility for a given alternative. It is observed that WUTA method, having a sound mathematical background, can provide accurate ranking to the candidate suppliers and choose the best one to fulfill the organizational requirements. Two real time examples are illustrated to prove its applicability and appropriateness in solving supplier selection problems.

Context affects nestmate recognition errors in honey bees and stingless bees.

PubMed

Couvillon, Margaret J; Segers, Francisca H I D; Cooper-Bowman, Roseanne; Truslove, Gemma; Nascimento, Daniela L; Nascimento, Fabio S; Ratnieks, Francis L W

2013-08-15

Nestmate recognition studies, where a discriminator first recognises and then behaviourally discriminates (accepts/rejects) another individual, have used a variety of methodologies and contexts. This is potentially problematic because recognition errors in discrimination behaviour are predicted to be context-dependent. Here we compare the recognition decisions (accept/reject) of discriminators in two eusocial bees, Apis mellifera and Tetragonisca angustula, under different contexts. These contexts include natural guards at the hive entrance (control); natural guards held in plastic test arenas away from the hive entrance that vary either in the presence or absence of colony odour or the presence or absence of an additional nestmate discriminator; and, for the honey bee, the inside of the nest. For both honey bee and stingless bee guards, total recognition errors of behavioural discrimination made by guards (% nestmates rejected + % non-nestmates accepted) are much lower at the colony entrance (honey bee: 30.9%; stingless bee: 33.3%) than in the test arenas (honey bee: 60-86%; stingless bee: 61-81%; P<0.001 for both). Within the test arenas, the presence of colony odour specifically reduced the total recognition errors in honey bees, although this reduction still fell short of bringing error levels down to what was found at the colony entrance. Lastly, in honey bees, the data show that the in-nest collective behavioural discrimination by ca. 30 workers that contact an intruder is insufficient to achieve error-free recognition and is not as effective as the discrimination by guards at the entrance. Overall, these data demonstrate that context is a significant factor in a discriminators' ability to make appropriate recognition decisions, and should be considered when designing recognition study methodologies.

A New Approach to Detection of Systematic Errors in Secondary Substation Monitoring Equipment Based on Short Term Load Forecasting

PubMed Central

Moriano, Javier; Rodríguez, Francisco Javier; Martín, Pedro; Jiménez, Jose Antonio; Vuksanovic, Branislav

2016-01-01

In recent years, Secondary Substations (SSs) are being provided with equipment that allows their full management. This is particularly useful not only for monitoring and planning purposes but also for detecting erroneous measurements, which could negatively affect the performance of the SS. On the other hand, load forecasting is extremely important since they help electricity companies to make crucial decisions regarding purchasing and generating electric power, load switching, and infrastructure development. In this regard, Short Term Load Forecasting (STLF) allows the electric power load to be predicted over an interval ranging from one hour to one week. However, important issues concerning error detection by employing STLF has not been specifically addressed until now. This paper proposes a novel STLF-based approach to the detection of gain and offset errors introduced by the measurement equipment. The implemented system has been tested against real power load data provided by electricity suppliers. Different gain and offset error levels are successfully detected. PMID:26771613

A pathway linking reward circuitry, impulsive sensation-seeking and risky decision-making in young adults: identifying neural markers for new interventions

PubMed Central

Chase, H W; Fournier, J C; Bertocci, M A; Greenberg, T; Aslam, H; Stiffler, R; Lockovich, J; Graur, S; Bebko, G; Forbes, E E; Phillips, M L

2017-01-01

High trait impulsive sensation seeking (ISS) is common in 18–25-year olds, and is associated with risky decision-making and deleterious outcomes. We examined relationships among: activity in reward regions previously associated with ISS during an ISS-relevant context, uncertain reward expectancy (RE), using fMRI; ISS impulsivity and sensation-seeking subcomponents; and risky decision-making in 100, transdiagnostically recruited 18–25-year olds. ISS, anhedonia, anxiety, depression and mania were measured using self-report scales; clinician-administered scales also assessed the latter four. A post-scan risky decision-making task measured ‘risky' (possible win/loss/mixed/neutral) fMRI-task versus ‘sure thing' stimuli. ‘Bias' reflected risky over safe choices. Uncertain RE-related activity in left ventrolateral prefrontal cortex and bilateral ventral striatum was positively associated with an ISS composite score, comprising impulsivity and sensation-seeking–fun-seeking subcomponents (ISSc; P⩽0.001). Bias positively associated with sensation seeking–experience seeking (ES; P=0.003). This relationship was moderated by ISSc (P=0.009): it was evident only in high ISSc individuals. Whole-brain analyses showed a positive relationship between: uncertain RE-related left ventrolateral prefrontal cortical activity and ISSc; uncertain RE-related visual attention and motor preparation neural network activity and ES; and uncertain RE-related dorsal anterior cingulate cortical activity and bias, specifically in high ISSc participants (all ps<0.05, peak-level, family-wise error corrected). We identify an indirect pathway linking greater levels of uncertain RE-related activity in reward, visual attention and motor networks with greater risky decision-making, via positive relationships with impulsivity, fun seeking and ES. These objective neural markers of high ISS can guide new treatment developments for young adults with high levels of this debilitating personality trait. PMID:28418404

Stimulus-reinforcement Based Decision-making and Anxiety: Impairment in Generalized Anxiety Disorder (GAD), but not in Generalized Social Phobia (GSP)

PubMed Central

DeVido, Jeffrey; Jones, Matthew; Geraci, Marilla; Hollon, Nick; Blair, R. J. R.; Pine, Daniel S.; Blair, Karina

2010-01-01

Background Generalized Social Phobia (GSP) involves the fear/avoidance of social situations while Generalized Anxiety Disorder (GAD) involves an intrusive worry about everyday life circumstances. It remains unclear whether these, highly comorbid, conditions represent distinct disorders or alternative presentations of a single underlying pathology. In this study, we examined stimulus-reinforcement based decision-making in GSP and GAD. Methods Twenty unmedicated patients with GSP, sixteen unmedicated patients with GAD and nineteen age, IQ, and gender matched healthy comparison individuals completed the Differential Reward/ Punishment Learning Task (DRPLT). In this task, the subject chooses between two objects associated with different levels of reward or punishment. Thus, response choice indexes not only reward/ punishment sensitivity but also sensitivity to reward/ punishment level according to between-object reinforcement distance. Results We found that patients with GAD committed a significantly greater number of errors compared to both the patients with GSP and the healthy comparison individuals. In contrast, the patients with GSP and the healthy comparison individuals did not differ in performance on this task. Conclusions These results link GAD with an anomalous non-affective based decision-making. Further, they are indicative that GSP and GAD are associated with distinct pathophysiologies. PMID:19102795

Driving in Early-Stage Alzheimer's Disease: An Integrative Review of the Literature.

PubMed

Davis, Rebecca L; Ohman, Jennifer M

2017-03-01

One of the most difficult decisions for individuals with Alzheimer's disease (AD) is when to stop driving. Because driving is a fundamental activity linked to socialization, independent functioning, and well-being, making the decision to stop driving is not easy. Cognitive decline in older adults can lead to getting lost while driving, difficulty detecting and avoiding hazards, as well as increased errors while driving due to compromised judgment and difficulty in making decisions. The purpose of the current literature review was to synthesize evidence regarding how individuals with early-stage AD, their families, and providers make determinations about driving safety, interventions to increase driving safety, and methods to assist cessation and coping for individuals with early-stage AD. The evidence shows that changes in driving ability start early and progress throughout the trajectory of AD. Some individuals with mild cognitive impairment or early-stage AD may be safe to drive for a period of time. Support groups aimed at helping with the transition have been shown to be helpful for individuals who stop driving. Research and practice must support interventions to help individuals maintain safety while driving, as well as cope with driving cessation. [Res Gerontol Nurs. 2017; 10(2):86-100.]. Copyright 2016, SLACK Incorporated.

Identifying Key Performance Indicators for Holistic Hospital Management with a Modified DEMATEL Approach.

PubMed

Si, Sheng-Li; You, Xiao-Yue; Liu, Hu-Chen; Huang, Jia

2017-08-19

Performance analysis is an important way for hospitals to achieve higher efficiency and effectiveness in providing services to their customers. The performance of the healthcare system can be measured by many indicators, but it is difficult to improve them simultaneously due to the limited resources. A feasible way is to identify the central and influential indicators to improve healthcare performance in a stepwise manner. In this paper, we propose a hybrid multiple criteria decision making (MCDM) approach to identify key performance indicators (KPIs) for holistic hospital management. First, through integrating evidential reasoning approach and interval 2-tuple linguistic variables, various assessments of performance indicators provided by healthcare experts are modeled. Then, the decision making trial and evaluation laboratory (DEMATEL) technique is adopted to build an interactive network and visualize the causal relationships between the performance indicators. Finally, an empirical case study is provided to demonstrate the proposed approach for improving the efficiency of healthcare management. The results show that "accidents/adverse events", "nosocomial infection", ''incidents/errors", "number of operations/procedures" are significant influential indicators. Also, the indicators of "length of stay", "bed occupancy" and "financial measures" play important roles in performance evaluation of the healthcare organization. The proposed decision making approach could be considered as a reference for healthcare administrators to enhance the performance of their healthcare institutions.

Cognitive dysfunction in Body Dysmorphic Disorder: New implications for nosological systems & neurobiological models

PubMed Central

Jefferies-Sewell, K; Chamberlain, SR; Fineberg, NA; Laws, KR

2017-01-01

Background Body dysmorphic disorder (BDD) is a debilitating disorder, characterised by obsessions and compulsions relating specifically to perceived appearance, newly classified within the DSM-5 Obsessive-Compulsive and Related Disorders grouping. Until now, little research has been conducted into the cognitive profile of this disorder. Materials and Methods Participants with BDD (n=12) and healthy controls (n=16) were tested using a computerised neurocognitive battery investigating attentional set-shifting (Intra/Extra Dimensional Set Shift Task), decision-making (Cambridge Gamble Task), motor response-inhibition (Stop-Signal Reaction Time Task) and affective processing (Affective Go-No Go Task). The groups were matched for age, IQ and education. Results In comparison to controls, patients with BDD showed significantly impaired attentional set shifting, abnormal decision-making, impaired response inhibition and greater omission and commission errors on the emotional processing task. Conclusions Despite the modest sample size, our results showed that individuals with BDD performed poorly compared to healthy controls on tests of cognitive flexibility, reward and motor impulsivity and affective processing. Results from separate studies in OCD patients suggest similar cognitive dysfunction. Therefore, these findings are consistent with the re-classification of BDD alongside OCD. These data also hint at additional areas of decision-making abnormalities that might contribute specifically to the psychopathology of BDD. PMID:27899165

Cognitive Abilities, Monitoring Confidence, and Control Thresholds Explain Individual Differences in Heuristics and Biases

PubMed Central

Jackson, Simon A.; Kleitman, Sabina; Howie, Pauline; Stankov, Lazar

2016-01-01

In this paper, we investigate whether individual differences in performance on heuristic and biases tasks can be explained by cognitive abilities, monitoring confidence, and control thresholds. Current theories explain individual differences in these tasks by the ability to detect errors and override automatic but biased judgments, and deliberative cognitive abilities that help to construct the correct response. Here we retain cognitive abilities but disentangle error detection, proposing that lower monitoring confidence and higher control thresholds promote error checking. Participants (N = 250) completed tasks assessing their fluid reasoning abilities, stable monitoring confidence levels, and the control threshold they impose on their decisions. They also completed seven typical heuristic and biases tasks such as the cognitive reflection test and Resistance to Framing. Using structural equation modeling, we found that individuals with higher reasoning abilities, lower monitoring confidence, and higher control threshold performed significantly and, at times, substantially better on the heuristic and biases tasks. Individuals with higher control thresholds also showed lower preferences for risky alternatives in a gambling task. Furthermore, residual correlations among the heuristic and biases tasks were reduced to null, indicating that cognitive abilities, monitoring confidence, and control thresholds accounted for their shared variance. Implications include the proposal that the capacity to detect errors does not differ between individuals. Rather, individuals might adopt varied strategies that promote error checking to different degrees, regardless of whether they have made a mistake or not. The results support growing evidence that decision-making involves cognitive abilities that construct actions and monitoring and control processes that manage their initiation. PMID:27790170

Cognitive Abilities, Monitoring Confidence, and Control Thresholds Explain Individual Differences in Heuristics and Biases.

PubMed

Jackson, Simon A; Kleitman, Sabina; Howie, Pauline; Stankov, Lazar

2016-01-01

In this paper, we investigate whether individual differences in performance on heuristic and biases tasks can be explained by cognitive abilities, monitoring confidence, and control thresholds. Current theories explain individual differences in these tasks by the ability to detect errors and override automatic but biased judgments, and deliberative cognitive abilities that help to construct the correct response. Here we retain cognitive abilities but disentangle error detection, proposing that lower monitoring confidence and higher control thresholds promote error checking. Participants ( N = 250) completed tasks assessing their fluid reasoning abilities, stable monitoring confidence levels, and the control threshold they impose on their decisions. They also completed seven typical heuristic and biases tasks such as the cognitive reflection test and Resistance to Framing. Using structural equation modeling, we found that individuals with higher reasoning abilities, lower monitoring confidence, and higher control threshold performed significantly and, at times, substantially better on the heuristic and biases tasks. Individuals with higher control thresholds also showed lower preferences for risky alternatives in a gambling task. Furthermore, residual correlations among the heuristic and biases tasks were reduced to null, indicating that cognitive abilities, monitoring confidence, and control thresholds accounted for their shared variance. Implications include the proposal that the capacity to detect errors does not differ between individuals. Rather, individuals might adopt varied strategies that promote error checking to different degrees, regardless of whether they have made a mistake or not. The results support growing evidence that decision-making involves cognitive abilities that construct actions and monitoring and control processes that manage their initiation.

"Usability of data integration and visualization software for multidisciplinary pediatric intensive care: a human factors approach to assessing technology".

PubMed

Lin, Ying Ling; Guerguerian, Anne-Marie; Tomasi, Jessica; Laussen, Peter; Trbovich, Patricia

2017-08-14

Intensive care clinicians use several sources of data in order to inform decision-making. We set out to evaluate a new interactive data integration platform called T3™ made available for pediatric intensive care. Three primary functions are supported: tracking of physiologic signals, displaying trajectory, and triggering decisions, by highlighting data or estimating risk of patient instability. We designed a human factors study to identify interface usability issues, to measure ease of use, and to describe interface features that may enable or hinder clinical tasks. Twenty-two participants, consisting of bedside intensive care physicians, nurses, and respiratory therapists, tested the T3™ interface in a simulation laboratory setting. Twenty tasks were performed with a true-to-setting, fully functional, prototype, populated with physiological and therapeutic intervention patient data. Primary data visualization was time series and secondary visualizations were: 1) shading out-of-target values, 2) mini-trends with exaggerated maxima and minima (sparklines), and 3) bar graph of a 16-parameter indicator. Task completion was video recorded and assessed using a use error rating scale. Usability issues were classified in the context of task and type of clinician. A severity rating scale was used to rate potential clinical impact of usability issues. Time series supported tracking a single parameter but partially supported determining patient trajectory using multiple parameters. Visual pattern overload was observed with multiple parameter data streams. Automated data processing using shading and sparklines was often ignored but the 16-parameter data reduction algorithm, displayed as a persistent bar graph, was visually intuitive. However, by selecting or automatically processing data, triggering aids distorted the raw data that clinicians use regularly. Consequently, clinicians could not rely on new data representations because they did not know how they were established or derived. Usability issues, observed through contextual use, provided directions for tangible design improvements of data integration software that may lessen use errors and promote safe use. Data-driven decision making can benefit from iterative interface redesign involving clinician-users in simulated environments. This study is a first step in understanding how software can support clinicians' decision making with integrated continuous monitoring data. Importantly, testing of similar platforms by all the different disciplines who may become clinician users is a fundamental step necessary to understand the impact on clinical outcomes of decision aids.

Multiple symbol partially coherent detection of MPSK

NASA Technical Reports Server (NTRS)

Simon, M. K.; Divsalar, D.

1992-01-01

It is shown that by using the known (or estimated) value of carrier tracking loop signal to noise ratio (SNR) in the decision metric, it is possible to improve the error probability performance of a partially coherent multiple phase-shift-keying (MPSK) system relative to that corresponding to the commonly used ideal coherent decision rule. Using a maximum-likeihood approach, an optimum decision metric is derived and shown to take the form of a weighted sum of the ideal coherent decision metric (i.e., correlation) and the noncoherent decision metric which is optimum for differential detection of MPSK. The performance of a receiver based on this optimum decision rule is derived and shown to provide continued improvement with increasing length of observation interval (data symbol sequence length). Unfortunately, increasing the observation length does not eliminate the error floor associated with the finite loop SNR. Nevertheless, in the limit of infinite observation length, the average error probability performance approaches the algebraic sum of the error floor and the performance of ideal coherent detection, i.e., at any error probability above the error floor, there is no degradation due to the partial coherence. It is shown that this limiting behavior is virtually achievable with practical size observation lengths. Furthermore, the performance is quite insensitive to mismatch between the estimate of loop SNR (e.g., obtained from measurement) fed to the decision metric and its true value. These results may be of use in low-cost Earth-orbiting or deep-space missions employing coded modulations.

Enhancing clinical evidence by proactively building quality into clinical trials.

PubMed

Meeker-O'Connell, Ann; Glessner, Coleen; Behm, Mark; Mulinde, Jean; Roach, Nancy; Sweeney, Fergus; Tenaerts, Pamela; Landray, Martin J

2016-08-01

Stakeholders across the clinical trial enterprise have expressed concern that the current clinical trial enterprise is unsustainable. The cost and complexity of trials have continued to increase, threatening our ability to generate reliable evidence essential for making appropriate decisions concerning the benefits and harms associated with clinical interventions. Overcoming this inefficiency rests on improving protocol design, trial planning, and quality oversight. The Clinical Trials Transformation Initiative convened a project to evaluate methods to prospectively build quality into the scientific and operational design of clinical trials ("quality-by-design"), such that trials are feasible to conduct and important errors are prevented rather than remediated. A working group evaluated aspects of trial design and oversight and developed the Clinical Trials Transformation Initiative quality-by-design principles document, outlining a series of factors generally relevant to the reliability of trial conclusions and to patient safety. These principles were then applied and further refined during a series of hands-on workshops to evaluate their utility in facilitating proactive, cross-functional dialogue, and decision-making about trial design and planning. Following these workshops, independent qualitative interviews were conducted with 19 workshop attendees to explore the potential challenges for implementing a quality-by-design approach to clinical trials. The Clinical Trials Transformation Initiative project team subsequently developed recommendations and an online resource guide to support implementation of this approach. The Clinical Trials Transformation Initiative quality-by-design principles provide a framework for assuring that clinical trials adequately safeguard participants and provide reliable information on which to make decisions on the effects of treatments. The quality-by-design workshops highlighted the value of active discussions incorporating the different perspectives within and external to an organization (e.g. clinical investigators, research site staff, and trial participants) in improving trial design. Workshop participants also recognized the value of focusing oversight on those aspects of the trial where errors would have a major impact on participant safety and reliability of results. Applying the Clinical Trials Transformation Initiative quality-by-design recommendations and principles should enable organizations to prioritize the most critical determinants of a trial's quality, identify non-essential activities that can be eliminated to streamline trial conduct and oversight, and formulate appropriate plans to define, avoid, mitigate, monitor, and address important errors. © The Author(s) 2016.

Incorporating ethics into your comprehensive organizational plan.

PubMed

Oetjen, Dawn; Rotarius, Timothy

2005-01-01

Today's health care executives find their organizations facing internal and external environments that are behaving in chaotic and unpredictable ways. From inadequate staffing and an increase in clinical errors to outdated risk management procedures and increased competition for scare reimbursements, these health care managers find themselves making decisions without being fully informed of the ethical ramifications of these decisions. A 6-part Comprehensive Organizational Plan is presented that helps the health care decision maker better understand the key success factors for the organization. The Comprehensive Organizational Plan is an overall plan that is intended to protect and serve your organization. The 6 plans in the Comprehensive Organizational Plan cover the following areas: competition, facilities, finances, human resources, information management, and marketing. The comprehensive organizational plan includes an overlay of the ethical considerations for each part of the plan.

The development rainfall forecasting using kalman filter

NASA Astrophysics Data System (ADS)

Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

2018-04-01

Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

Error Detection-Based Model to Assess Educational Outcomes in Crisis Resource Management Training: A Pilot Study.

PubMed

Bouhabel, Sarah; Kay-Rivest, Emily; Nhan, Carol; Bank, Ilana; Nugus, Peter; Fisher, Rachel; Nguyen, Lily Hp

2017-06-01

Otolaryngology-head and neck surgery (OTL-HNS) residents face a variety of difficult, high-stress situations, which may occur early in their training. Since these events occur infrequently, simulation-based learning has become an important part of residents' training and is already well established in fields such as anesthesia and emergency medicine. In the domain of OTL-HNS, it is gradually gaining in popularity. Crisis Resource Management (CRM), a program adapted from the aviation industry, aims to improve outcomes of crisis situations by attempting to mitigate human errors. Some examples of CRM principles include cultivating situational awareness; promoting proper use of available resources; and improving rapid decision making, particularly in high-acuity, low-frequency clinical situations. Our pilot project sought to integrate CRM principles into an airway simulation course for OTL-HNS residents, but most important, it evaluated whether learning objectives were met, through use of a novel error identification model.

Spatial regression test for ensuring temperature data quality in southern Spain

NASA Astrophysics Data System (ADS)

Estévez, J.; Gavilán, P.; García-Marín, A. P.

2018-01-01

Quality assurance of meteorological data is crucial for ensuring the reliability of applications and models that use such data as input variables, especially in the field of environmental sciences. Spatial validation of meteorological data is based on the application of quality control procedures using data from neighbouring stations to assess the validity of data from a candidate station (the station of interest). These kinds of tests, which are referred to in the literature as spatial consistency tests, take data from neighbouring stations in order to estimate the corresponding measurement at the candidate station. These estimations can be made by weighting values according to the distance between the stations or to the coefficient of correlation, among other methods. The test applied in this study relies on statistical decision-making and uses a weighting based on the standard error of the estimate. This paper summarizes the results of the application of this test to maximum, minimum and mean temperature data from the Agroclimatic Information Network of Andalusia (southern Spain). This quality control procedure includes a decision based on a factor f, the fraction of potential outliers for each station across the region. Using GIS techniques, the geographic distribution of the errors detected has been also analysed. Finally, the performance of the test was assessed by evaluating its effectiveness in detecting known errors.

Emotional experiences and motivating factors associated with fingerprint analysis.

PubMed

Charlton, David; Fraser-Mackenzie, Peter A F; Dror, Itiel E

2010-03-01

In this study, we investigated the emotional and motivational factors involved in fingerprint analysis in day-to-day routine case work and in significant and harrowing criminal investigations. Thematic analysis was performed on interviews with 13 experienced fingerprint examiners from a variety of law enforcement agencies. The data revealed factors relating to job satisfaction and the use of skill. Individual satisfaction related to catching criminals was observed; this was most notable in solving high profile, serious, or long-running cases. There were positive emotional effects associated with matching fingerprints and apparent fear of making errors. Finally, we found evidence for a need of cognitive closure in fingerprint examiner decision-making.

MEF and MEB Red Teams: Required Conditions and Placement Options

DTIC Science & Technology

2013-04-16

aids decision making and influences how the organization views the problems it is facing. Discussion : The 2010 Commandant’s Planning Guidance...the Regional Command (South West) Red Team. Throughout this time, ‘discovery learning ’ and trial and error were the means in which I gained an...who I had the pleasure of working with and learning from during my time as a red teamer. Most importantly, I would like to thank my family for their

The neuropsychology of obsessive-compulsive personality disorder: a new analysis.

PubMed

Fineberg, Naomi A; Day, Grace A; de Koenigswarter, Nica; Reghunandanan, Samar; Kolli, Sangeetha; Jefferies-Sewell, Kiri; Hranov, Georgi; Laws, Keith R

2015-10-01

Obsessive compulsive personality disorder (OCPD) is characterized by perfectionism, need for control, and cognitive rigidity. Currently, little neuropsychological data exist on this condition, though emerging evidence does suggest that disorders marked by compulsivity, including obsessive-compulsive disorder (OCD), are associated with impairment in cognitive flexibility and executive planning on neurocognitive tasks. The current study investigated the neurocognitive profile in a nonclinical community-based sample of people fulfilling diagnostic criteria for OCPD in the absence of major psychiatric comorbidity. Twenty-one nonclinical subjects who fulfilled Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for OCPD were compared with 15 healthy controls on selected clinical and neurocognitive tasks. OCPD was measured using the Compulsive Personality Assessment Scale (CPAS). Participants completed tests from the Cambridge Automated Neuropsychological Test Battery including tests of set shifting (Intra-Extra Dimensional [IED] Set Shifting) executive planning (Stockings of Cambridge [SOC]), and decision making (Cambridge Gamble Task [CGT]). The OCPD group made significantly more IED-ED shift errors and total shift errors, and also showed longer mean initial thinking time on the SOC at moderate levels of difficulty. No differences emerged on the CGT. Nonclinical cases of OCPD showed significant cognitive inflexibility coupled with executive planning deficits, whereas decision-making remained intact. This profile of impairment overlaps with that of OCD and implies that common neuropsychological changes affect individuals with these disorders.

Evaluate the ability of clinical decision support systems (CDSSs) to improve clinical practice.

PubMed

Ajami, Sima; Amini, Fatemeh

2013-01-01

Prevalence of new diseases, medical science promotion and increase of referring to health care centers, provide a good situation for medical errors growth. Errors can involve medicines, surgery, diagnosis, equipment, or lab reports. Medical errors can occur anywhere in the health care system: In hospitals, clinics, surgery centers, doctors' offices, nursing homes, pharmacies, and patients' homes. According to the Institute of Medicine (IOM), 98,000 people die every year from preventable medical errors. In 2010 from all referred medical error records to Iran Legal Medicine Organization, 46/5% physician and medical team members were known as delinquent. One of new technologies that can reduce medical errors is clinical decision support systems (CDSSs). This study was unsystematic-review study. The literature was searched on evaluate the "ability of clinical decision support systems to improve clinical practice" with the help of library, books, conference proceedings, data bank, and also searches engines available at Google, Google scholar. For our searches, we employed the following keywords and their combinations: medical error, clinical decision support systems, Computer-Based Clinical Decision Support Systems, information technology, information system, health care quality, computer systems in the searching areas of title, keywords, abstract, and full text. In this study, more than 100 articles and reports were collected and 38 of them were selected based on their relevancy. The CDSSs are computer programs, designed for help to health care careers. These systems as a knowledge-based tool could help health care manager in analyze evaluation, improvement and selection of effective solutions in clinical decisions. Therefore, it has a main role in medical errors reduction. The aim of this study was to express ability of the CDSSs to improve

Dissociable neural representations of reinforcement and belief prediction errors underlie strategic learning

PubMed Central

Zhu, Lusha; Mathewson, Kyle E.; Hsu, Ming

2012-01-01

Decision-making in the presence of other competitive intelligent agents is fundamental for social and economic behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions of others competing for the same rewards. However, whereas we know much about strategic learning at both theoretical and behavioral levels, we know relatively little about the underlying neural mechanisms. Here, we show using a multi-strategy competitive learning paradigm that strategic choices can be characterized by extending the reinforcement learning (RL) framework to incorporate agents’ beliefs about the actions of their opponents. Furthermore, using this characterization to generate putative internal values, we used model-based functional magnetic resonance imaging to investigate neural computations underlying strategic learning. We found that the distinct notions of prediction errors derived from our computational model are processed in a partially overlapping but distinct set of brain regions. Specifically, we found that the RL prediction error was correlated with activity in the ventral striatum. In contrast, activity in the ventral striatum, as well as the rostral anterior cingulate (rACC), was correlated with a previously uncharacterized belief-based prediction error. Furthermore, activity in rACC reflected individual differences in degree of engagement in belief learning. These results suggest a model of strategic behavior where learning arises from interaction of dissociable reinforcement and belief-based inputs. PMID:22307594

Dissociable neural representations of reinforcement and belief prediction errors underlie strategic learning.

PubMed

Zhu, Lusha; Mathewson, Kyle E; Hsu, Ming

2012-01-31

Decision-making in the presence of other competitive intelligent agents is fundamental for social and economic behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions of others competing for the same rewards. However, whereas we know much about strategic learning at both theoretical and behavioral levels, we know relatively little about the underlying neural mechanisms. Here, we show using a multi-strategy competitive learning paradigm that strategic choices can be characterized by extending the reinforcement learning (RL) framework to incorporate agents' beliefs about the actions of their opponents. Furthermore, using this characterization to generate putative internal values, we used model-based functional magnetic resonance imaging to investigate neural computations underlying strategic learning. We found that the distinct notions of prediction errors derived from our computational model are processed in a partially overlapping but distinct set of brain regions. Specifically, we found that the RL prediction error was correlated with activity in the ventral striatum. In contrast, activity in the ventral striatum, as well as the rostral anterior cingulate (rACC), was correlated with a previously uncharacterized belief-based prediction error. Furthermore, activity in rACC reflected individual differences in degree of engagement in belief learning. These results suggest a model of strategic behavior where learning arises from interaction of dissociable reinforcement and belief-based inputs.

Reader error, object recognition, and visual search

NASA Astrophysics Data System (ADS)

Kundel, Harold L.

2004-05-01

Small abnormalities such as hairline fractures, lung nodules and breast tumors are missed by competent radiologists with sufficient frequency to make them a matter of concern to the medical community; not only because they lead to litigation but also because they delay patient care. It is very easy to attribute misses to incompetence or inattention. To do so may be placing an unjustified stigma on the radiologists involved and may allow other radiologists to continue a false optimism that it can never happen to them. This review presents some of the fundamentals of visual system function that are relevant to understanding the search for and the recognition of small targets embedded in complicated but meaningful backgrounds like chests and mammograms. It presents a model for visual search that postulates a pre-attentive global analysis of the retinal image followed by foveal checking fixations and eventually discovery scanning. The model will be used to differentiate errors of search, recognition and decision making. The implications for computer aided diagnosis and for functional workstation design are discussed.

Calibration of skill and judgment in driving: development of a conceptual framework and the implications for road safety.

PubMed

Horrey, William J; Lesch, Mary F; Mitsopoulos-Rubens, Eve; Lee, John D

2015-03-01

Humans often make inflated or erroneous estimates of their own ability or performance. Such errors in calibration can be due to incomplete processing, neglect of available information or due to improper weighing or integration of the information and can impact our decision-making, risk tolerance, and behaviors. In the driving context, these outcomes can have important implications for safety. The current paper discusses the notion of calibration in the context of self-appraisals and self-competence as well as in models of self-regulation in driving. We further develop a conceptual framework for calibration in the driving context borrowing from earlier models of momentary demand regulation, information processing, and lens models for information selection and utilization. Finally, using the model we describe the implications for calibration (or, more specifically, errors in calibration) for our understanding of driver distraction, in-vehicle automation and autonomous vehicles, and the training of novice and inexperienced drivers. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Missed opportunities for diagnosis: lessons learned from diagnostic errors in primary care.

PubMed

Goyder, Clare R; Jones, Caroline H D; Heneghan, Carl J; Thompson, Matthew J

2015-12-01

Because of the difficulties inherent in diagnosis in primary care, it is inevitable that diagnostic errors will occur. However, despite the important consequences associated with diagnostic errors and their estimated high prevalence, teaching and research on diagnostic error is a neglected area. To ascertain the key learning points from GPs' experiences of diagnostic errors and approaches to clinical decision making associated with these. Secondary analysis of 36 qualitative interviews with GPs in Oxfordshire, UK. Two datasets of semi-structured interviews were combined. Questions focused on GPs' experiences of diagnosis and diagnostic errors (or near misses) in routine primary care and out of hours. Interviews were audiorecorded, transcribed verbatim, and analysed thematically. Learning points include GPs' reliance on 'pattern recognition' and the failure of this strategy to identify atypical presentations; the importance of considering all potentially serious conditions using a 'restricted rule out' approach; and identifying and acting on a sense of unease. Strategies to help manage uncertainty in primary care were also discussed. Learning from previous examples of diagnostic errors is essential if these events are to be reduced in the future and this should be incorporated into GP training. At a practice level, learning points from experiences of diagnostic errors should be discussed more frequently; and more should be done to integrate these lessons nationally to understand and characterise diagnostic errors. © British Journal of General Practice 2015.

Decision Aids for Multiple-Decision Disease Management as Affected by Weather Input Errors

USDA-ARS?s Scientific Manuscript database

Many disease management decision support systems (DSS) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation or estimation from off-site sources, may affect model calculations and manage...

A Two-Stage Approach for Improving the Convergence of Least-Mean-Square Adaptive Decision-Feedback Equalizers in the Presence of Severe Narrowband Interference

NASA Astrophysics Data System (ADS)

Batra, Arun; Zeidler, James R.; Beex, A. A. Louis

2007-12-01

It has previously been shown that a least-mean-square (LMS) decision-feedback filter can mitigate the effect of narrowband interference (L.-M. Li and L. Milstein, 1983). An adaptive implementation of the filter was shown to converge relatively quickly for mild interference. It is shown here, however, that in the case of severe narrowband interference, the LMS decision-feedback equalizer (DFE) requires a very large number of training symbols for convergence, making it unsuitable for some types of communication systems. This paper investigates the introduction of an LMS prediction-error filter (PEF) as a prefilter to the equalizer and demonstrates that it reduces the convergence time of the two-stage system by as much as two orders of magnitude. It is also shown that the steady-state bit-error rate (BER) performance of the proposed system is still approximately equal to that attained in steady-state by the LMS DFE-only. Finally, it is shown that the two-stage system can be implemented without the use of training symbols. This two-stage structure lowers the complexity of the overall system by reducing the number of filter taps that need to be adapted, while incurring a slight loss in the steady-state BER.

Using data to make decisions and drive results: a LEAN implementation strategy.

PubMed

Panning, Rick

2005-03-28

During the process of facility planning, Fairview Laboratory Services utilized LEAN manufacturing to maximize efficiency, simplify processes, and improve laboratory support of patient care services. By incorporating the LEAN program's concepts in our pilot program, we were able to reduce turnaround time by 50%, improve productivity by greater than 40%, reduce costs by 31%, save more than 440 square feet of space, standardize work practices, reduce errors and error potential, continuously measure performance, eliminate excess unused inventory and visual noise, and cross-train 100% of staff in the core laboratory. In addition, we trained a core team of people that is available to coordinate future LEAN projects in the laboratory and other areas of the organization.

"Effects of Stress on Decisions Under Uncertainty: A Meta-Analysis": Correction to Starcke and Brand (2016).

PubMed

2016-09-01

Reports an error in "Effects of Stress on Decisions Under Uncertainty: A Meta-Analysis" by Katrin Starcke and Matthias Brand ( Psychological Bulletin , Advanced Online Publication, May 23, 2016, np). It should have been reported that the inverted u-shaped relationship between cortisol stress responses and decision-making performance was only observed in female, but not in male participants as suggested by the study by van den Bos, Harteveld, and Stoop (2009). Corrected versions of the affected sentences are provided. (The following abstract of the original article appeared in record 2016-25465-001.) The purpose of the present meta-analysis was to quantify the effects that stress has on decisions made under uncertainty. We hypothesized that stress increases reward seeking and risk taking through alterations of dopamine firing rates and reduces executive control by hindering optimal prefrontal cortex functioning. In certain decision situations, increased reward seeking and risk taking is dysfunctional, whereas in others, this is not the case. We also assumed that the type of stressor plays a role. In addition, moderating variables are analyzed, such as the hormonal stress response, the time between stress onset and decisions, and the participants' age and gender. We included studies in the meta-analysis that investigated decision making after a laboratory stress-induction versus a control condition (k = 32 datasets, N = 1829 participants). A random-effects model revealed that overall, stress conditions lead to decisions that can be described as more disadvantageous, more reward seeking, and more risk taking than nonstress conditions (d = .17). In those situations in which increased reward seeking and risk taking is disadvantageous, stress had significant effects (d = .26), whereas in other situations, no effects were observed (d = .01). Effects were observed under processive stressors (d = .19), but not under systemic ones (d = .09). Moderation analyses did not reveal any significant results. We concluded that stress deteriorates overall decision-making performance through the mechanisms proposed. The effects differ, depending on the decision situation and the type of stressor, but not on the characteristics of the individuals. (PsycINFO Database Record (c) 2016 APA, all rights reserved).