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.

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.

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

Using APEX to Model Anticipated Human Error: Analysis of a GPS Navigational Aid

NASA Technical Reports Server (NTRS)

VanSelst, Mark; Freed, Michael; Shefto, Michael (Technical Monitor)

1997-01-01

The interface development process can be dramatically improved by predicting design facilitated human error at an early stage in the design process. The approach we advocate is to SIMULATE the behavior of a human agent carrying out tasks with a well-specified user interface, ANALYZE the simulation for instances of human error, and then REFINE the interface or protocol to minimize predicted error. This approach, incorporated into the APEX modeling architecture, differs from past approaches to human simulation in Its emphasis on error rather than e.g. learning rate or speed of response. The APEX model consists of two major components: (1) a powerful action selection component capable of simulating behavior in complex, multiple-task environments; and (2) a resource architecture which constrains cognitive, perceptual, and motor capabilities to within empirically demonstrated limits. The model mimics human errors arising from interactions between limited human resources and elements of the computer interface whose design falls to anticipate those limits. We analyze the design of a hand-held Global Positioning System (GPS) device used for radical and navigational decisions in small yacht recalls. The analysis demonstrates how human system modeling can be an effective design aid, helping to accelerate the process of refining a product (or procedure).

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.…

A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

DTIC Science & Technology

2014-07-01

Macmillan & Creelman , 2005). This is a quite high degree of discriminability and it means that when the decision model predicts a probability of...ROC analysis. Pattern Recognition Letters, 27(8), 861-874. Retrieved from Google Scholar. Macmillan, N. A., & Creelman , C. D. (2005). Detection

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.

Exploring human error in military aviation flight safety events using post-incident classification systems.

PubMed

Hooper, Brionny J; O'Hare, David P A

2013-08-01

Human error classification systems theoretically allow researchers to analyze postaccident data in an objective and consistent manner. The Human Factors Analysis and Classification System (HFACS) framework is one such practical analysis tool that has been widely used to classify human error in aviation. The Cognitive Error Taxonomy (CET) is another. It has been postulated that the focus on interrelationships within HFACS can facilitate the identification of the underlying causes of pilot error. The CET provides increased granularity at the level of unsafe acts. The aim was to analyze the influence of factors at higher organizational levels on the unsafe acts of front-line operators and to compare the errors of fixed-wing and rotary-wing operations. This study analyzed 288 aircraft incidents involving human error from an Australasian military organization occurring between 2001 and 2008. Action errors accounted for almost twice (44%) the proportion of rotary wing compared to fixed wing (23%) incidents. Both classificatory systems showed significant relationships between precursor factors such as the physical environment, mental and physiological states, crew resource management, training and personal readiness, and skill-based, but not decision-based, acts. The CET analysis showed different predisposing factors for different aspects of skill-based behaviors. Skill-based errors in military operations are more prevalent in rotary wing incidents and are related to higher level supervisory processes in the organization. The Cognitive Error Taxonomy provides increased granularity to HFACS analyses of unsafe acts.

Investigating the Link Between Radiologists Gaze, Diagnostic Decision, and Image Content

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

Tourassi, Georgia; Voisin, Sophie; Paquit, Vincent C

2013-01-01

Objective: To investigate machine learning for linking image content, human perception, cognition, and error in the diagnostic interpretation of mammograms. Methods: Gaze data and diagnostic decisions were collected from six radiologists who reviewed 20 screening mammograms while wearing a head-mounted eye-tracker. Texture analysis was performed in mammographic regions that attracted radiologists attention and in all abnormal regions. Machine learning algorithms were investigated to develop predictive models that link: (i) image content with gaze, (ii) image content and gaze with cognition, and (iii) image content, gaze, and cognition with diagnostic error. Both group-based and individualized models were explored. Results: By poolingmore » the data from all radiologists machine learning produced highly accurate predictive models linking image content, gaze, cognition, and error. Merging radiologists gaze metrics and cognitive opinions with computer-extracted image features identified 59% of the radiologists diagnostic errors while confirming 96.2% of their correct diagnoses. The radiologists individual errors could be adequately predicted by modeling the behavior of their peers. However, personalized tuning appears to be beneficial in many cases to capture more accurately individual behavior. Conclusions: Machine learning algorithms combining image features with radiologists gaze data and diagnostic decisions can be effectively developed to recognize cognitive and perceptual errors associated with the diagnostic interpretation of mammograms.« less

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.

Neural basis of decision making guided by emotional outcomes

PubMed Central

Matsuda, Yoshi-Taka; Fujimura, Tomomi; Ueno, Kenichi; Asamizuya, Takeshi; Suzuki, Chisato; Cheng, Kang; Okanoya, Kazuo; Okada, Masato

2015-01-01

Emotional events resulting from a choice influence an individual's subsequent decision making. Although the relationship between emotion and decision making has been widely discussed, previous studies have mainly investigated decision outcomes that can easily be mapped to reward and punishment, including monetary gain/loss, gustatory stimuli, and pain. These studies regard emotion as a modulator of decision making that can be made rationally in the absence of emotions. In our daily lives, however, we often encounter various emotional events that affect decisions by themselves, and mapping the events to a reward or punishment is often not straightforward. In this study, we investigated the neural substrates of how such emotional decision outcomes affect subsequent decision making. By using functional magnetic resonance imaging (fMRI), we measured brain activities of humans during a stochastic decision-making task in which various emotional pictures were presented as decision outcomes. We found that pleasant pictures differentially activated the midbrain, fusiform gyrus, and parahippocampal gyrus, whereas unpleasant pictures differentially activated the ventral striatum, compared with neutral pictures. We assumed that the emotional decision outcomes affect the subsequent decision by updating the value of the options, a process modeled by reinforcement learning models, and that the brain regions representing the prediction error that drives the reinforcement learning are involved in guiding subsequent decisions. We found that some regions of the striatum and the insula were separately correlated with the prediction error for either pleasant pictures or unpleasant pictures, whereas the precuneus was correlated with prediction errors for both pleasant and unpleasant pictures. PMID:25695644

Neural basis of decision making guided by emotional outcomes.

PubMed

Katahira, Kentaro; Matsuda, Yoshi-Taka; Fujimura, Tomomi; Ueno, Kenichi; Asamizuya, Takeshi; Suzuki, Chisato; Cheng, Kang; Okanoya, Kazuo; Okada, Masato

2015-05-01

Emotional events resulting from a choice influence an individual's subsequent decision making. Although the relationship between emotion and decision making has been widely discussed, previous studies have mainly investigated decision outcomes that can easily be mapped to reward and punishment, including monetary gain/loss, gustatory stimuli, and pain. These studies regard emotion as a modulator of decision making that can be made rationally in the absence of emotions. In our daily lives, however, we often encounter various emotional events that affect decisions by themselves, and mapping the events to a reward or punishment is often not straightforward. In this study, we investigated the neural substrates of how such emotional decision outcomes affect subsequent decision making. By using functional magnetic resonance imaging (fMRI), we measured brain activities of humans during a stochastic decision-making task in which various emotional pictures were presented as decision outcomes. We found that pleasant pictures differentially activated the midbrain, fusiform gyrus, and parahippocampal gyrus, whereas unpleasant pictures differentially activated the ventral striatum, compared with neutral pictures. We assumed that the emotional decision outcomes affect the subsequent decision by updating the value of the options, a process modeled by reinforcement learning models, and that the brain regions representing the prediction error that drives the reinforcement learning are involved in guiding subsequent decisions. We found that some regions of the striatum and the insula were separately correlated with the prediction error for either pleasant pictures or unpleasant pictures, whereas the precuneus was correlated with prediction errors for both pleasant and unpleasant pictures. Copyright © 2015 the American Physiological Society.

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

Decision support system for determining the contact lens for refractive errors patients with classification ID3

NASA Astrophysics Data System (ADS)

Situmorang, B. H.; Setiawan, M. P.; Tosida, E. T.

2017-01-01

Refractive errors are abnormalities of the refraction of light so that the shadows do not focus precisely on the retina resulting in blurred vision [1]. Refractive errors causing the patient should wear glasses or contact lenses in order eyesight returned to normal. The use of glasses or contact lenses in a person will be different from others, it is influenced by patient age, the amount of tear production, vision prescription, and astigmatic. Because the eye is one organ of the human body is very important to see, then the accuracy in determining glasses or contact lenses which will be used is required. This research aims to develop a decision support system that can produce output on the right contact lenses for refractive errors patients with a value of 100% accuracy. Iterative Dichotomize Three (ID3) classification methods will generate gain and entropy values of attributes that include code sample data, age of the patient, astigmatic, the ratio of tear production, vision prescription, and classes that will affect the outcome of the decision tree. The eye specialist test result for the training data obtained the accuracy rate of 96.7% and an error rate of 3.3%, the result test using confusion matrix obtained the accuracy rate of 96.1% and an error rate of 3.1%; for the data testing obtained accuracy rate of 100% and an error rate of 0.

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.

Automation bias and verification complexity: a systematic review.

PubMed

Lyell, David; Coiera, Enrico

2017-03-01

While potentially reducing decision errors, decision support systems can introduce new types of errors. Automation bias (AB) happens when users become overreliant on decision support, which reduces vigilance in information seeking and processing. Most research originates from the human factors literature, where the prevailing view is that AB occurs only in multitasking environments. This review seeks to compare the human factors and health care literature, focusing on the apparent association of AB with multitasking and task complexity. EMBASE, Medline, Compendex, Inspec, IEEE Xplore, Scopus, Web of Science, PsycINFO, and Business Source Premiere from 1983 to 2015. Evaluation studies where task execution was assisted by automation and resulted in errors were included. Participants needed to be able to verify automation correctness and perform the task manually. Tasks were identified and grouped. Task and automation type and presence of multitasking were noted. Each task was rated for its verification complexity. Of 890 papers identified, 40 met the inclusion criteria; 6 were in health care. Contrary to the prevailing human factors view, AB was found in single tasks, typically involving diagnosis rather than monitoring, and with high verification complexity. The literature is fragmented, with large discrepancies in how AB is reported. Few studies reported the statistical significance of AB compared to a control condition. AB appears to be associated with the degree of cognitive load experienced in decision tasks, and appears to not be uniquely associated with multitasking. Strategies to minimize AB might focus on cognitive load reduction. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Effects of noise on the performance of a memory decision response task

NASA Technical Reports Server (NTRS)

Lawton, B. W.

1972-01-01

An investigation has been made to determine the effects of noise on human performance. Fourteen subjects performed a memory-decision-response task in relative quiet and while listening to tape recorded noises. Analysis of the data obtained indicates that performance was degraded in the presence of noise. Significant increases in problem solution times were found for impulsive noise conditions as compared with times found for the no-noise condition. Performance accuracy was also degraded. Significantly more error responses occurred at higher noise levels; a direct or positive relation was found between error responses and noise level experienced by the subjects.

Integrating Safety in the Aviation System: Interdepartmental Training for Pilots and Maintenance Technicians

NASA Technical Reports Server (NTRS)

Mattson, Marifran; Petrin, Donald A.; Young, John P.

2001-01-01

The study of human factors has had a decisive impact on the aviation industry. However, the entire aviation system often is not considered in researching, training, and evaluating human factors issues especially with regard to safety. In both conceptual and practical terms, we argue for the proactive management of human error from both an individual and organizational systems perspective. The results of a multidisciplinary research project incorporating survey data from professional pilots and maintenance technicians and an exploratory study integrating students from relevant disciplines are reported. Survey findings suggest that latent safety errors may occur during the maintenance discrepancy reporting process because pilots and maintenance technicians do not effectively interact with one another. The importance of interdepartmental or cross-disciplinary training for decreasing these errors and increasing safety is discussed as a primary implication.

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.

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.

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.

Error rates in forensic DNA analysis: definition, numbers, impact and communication.

PubMed

Kloosterman, Ate; Sjerps, Marjan; Quak, Astrid

2014-09-01

Forensic DNA casework is currently regarded as one of the most important types of forensic evidence, and important decisions in intelligence and justice are based on it. However, errors occasionally occur and may have very serious consequences. In other domains, error rates have been defined and published. The forensic domain is lagging behind concerning this transparency for various reasons. In this paper we provide definitions and observed frequencies for different types of errors at the Human Biological Traces Department of the Netherlands Forensic Institute (NFI) over the years 2008-2012. Furthermore, we assess their actual and potential impact and describe how the NFI deals with the communication of these numbers to the legal justice system. We conclude that the observed relative frequency of quality failures is comparable to studies from clinical laboratories and genetic testing centres. Furthermore, this frequency is constant over the five-year study period. The most common causes of failures related to the laboratory process were contamination and human error. Most human errors could be corrected, whereas gross contamination in crime samples often resulted in irreversible consequences. Hence this type of contamination is identified as the most significant source of error. Of the known contamination incidents, most were detected by the NFI quality control system before the report was issued to the authorities, and thus did not lead to flawed decisions like false convictions. However in a very limited number of cases crucial errors were detected after the report was issued, sometimes with severe consequences. Many of these errors were made in the post-analytical phase. The error rates reported in this paper are useful for quality improvement and benchmarking, and contribute to an open research culture that promotes public trust. However, they are irrelevant in the context of a particular case. Here case-specific probabilities of undetected errors are needed. These should be reported, separately from the match probability, when requested by the court or when there are internal or external indications for error. It should also be made clear that there are various other issues to consider, like DNA transfer. Forensic statistical models, in particular Bayesian networks, may be useful to take the various uncertainties into account and demonstrate their effects on the evidential value of the forensic DNA results. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

[Risk and risk management in aviation].

PubMed

Müller, Manfred

2004-10-01

RISK MANAGEMENT: The large proportion of human errors in aviation accidents suggested the solution--at first sight brilliant--to replace the fallible human being by an "infallible" digitally-operating computer. However, even after the introduction of the so-called HITEC-airplanes, the factor human error still accounts for 75% of all accidents. Thus, if the computer is ruled out as the ultimate safety system, how else can complex operations involving quick and difficult decisions be controlled? OPTIMIZED TEAM INTERACTION/PARALLEL CONNECTION OF THOUGHT MACHINES: Since a single person is always "highly error-prone", support and control have to be guaranteed by a second person. The independent work of mind results in a safety network that more efficiently cushions human errors. NON-PUNITIVE ERROR MANAGEMENT: To be able to tackle the actual problems, the open discussion of intervened errors must not be endangered by the threat of punishment. It has been shown in the past that progress is primarily achieved by investigating and following up mistakes, failures and catastrophes shortly after they happened. HUMAN FACTOR RESEARCH PROJECT: A comprehensive survey showed the following result: By far the most frequent safety-critical situation (37.8% of all events) consists of the following combination of risk factors: 1. A complication develops. 2. In this situation of increased stress a human error occurs. 3. The negative effects of the error cannot be corrected or eased because there are deficiencies in team interaction on the flight deck. This means, for example, that a negative social climate has the effect of a "turbocharger" when a human error occurs. It needs to be pointed out that a negative social climate is not identical with a dispute. In many cases the working climate is burdened without the responsible person even noticing it: A first negative impression, too much or too little respect, contempt, misunderstandings, not expressing unclear concern, etc. can considerably reduce the efficiency of a team.

Human-Agent Teaming for Multi-Robot Control: A Literature Review

DTIC Science & Technology

2013-02-01

neurophysiological devices are becoming more cost effective and less invasive, future systems will most likely take advantage of this technology to monitor...Parasuraman et al., 1993). It has also been reported that both the cost of automation errors and the cost of verification affect humans’ reliance on...decision aids, and the effects are also moderated by age (Ezer et al., 2008). Generally, reliance is reduced as the cost of error increases and it

HRA Aerospace Challenges

NASA Technical Reports Server (NTRS)

DeMott, Diana

2013-01-01

Compared to equipment designed to perform the same function over and over, humans are just not as reliable. Computers and machines perform the same action in the same way repeatedly getting the same result, unless equipment fails or a human interferes. Humans who are supposed to perform the same actions repeatedly often perform them incorrectly due to a variety of issues including: stress, fatigue, illness, lack of training, distraction, acting at the wrong time, not acting when they should, not following procedures, misinterpreting information or inattention to detail. Why not use robots and automatic controls exclusively if human error is so common? In an emergency or off normal situation that the computer, robotic element, or automatic control system is not designed to respond to, the result is failure unless a human can intervene. The human in the loop may be more likely to cause an error, but is also more likely to catch the error and correct it. When it comes to unexpected situations, or performing multiple tasks outside the defined mission parameters, humans are the only viable alternative. Human Reliability Assessments (HRA) identifies ways to improve human performance and reliability and can lead to improvements in systems designed to interact with humans. Understanding the context of the situation that can lead to human errors, which include taking the wrong action, no action or making bad decisions provides additional information to mitigate risks. With improved human reliability comes reduced risk for the overall operation or project.

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

Sanfilippo, Antonio P.; Riensche, Roderick M.; Haack, Jereme N.

“Gamification”, the application of gameplay to real-world problems, enables the development of human computation systems that support decision-making through the integration of social and machine intelligence. One of gamification’s major benefits includes the creation of a problem solving environment where the influence of cognitive and cultural biases on human judgment can be curtailed through collaborative and competitive reasoning. By reducing biases on human judgment, gamification allows human computation systems to exploit human creativity relatively unhindered by human error. Operationally, gamification uses simulation to harvest human behavioral data that provide valuable insights for the solution of real-world problems.

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

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.…

[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.

Review of Significant Incidents and Close Calls in Human Spaceflight from a Human Factors Perspective

NASA Technical Reports Server (NTRS)

Silva-Martinez, Jackelynne; Ellenberger, Richard; Dory, Jonathan

2017-01-01

This project aims to identify poor human factors design decisions that led to error-prone systems, or did not facilitate the flight crew making the right choices; and to verify that NASA is effectively preventing similar incidents from occurring again. This analysis was performed by reviewing significant incidents and close calls in human spaceflight identified by the NASA Johnson Space Center Safety and Mission Assurance Flight Safety Office. The review of incidents shows whether the identified human errors were due to the operational phase (flight crew and ground control) or if they initiated at the design phase (includes manufacturing and test). This classification was performed with the aid of the NASA Human Systems Integration domains. This in-depth analysis resulted in a tool that helps with the human factors classification of significant incidents and close calls in human spaceflight, which can be used to identify human errors at the operational level, and how they were or should be minimized. Current governing documents on human systems integration for both government and commercial crew were reviewed to see if current requirements, processes, training, and standard operating procedures protect the crew and ground control against these issues occurring in the future. Based on the findings, recommendations to target those areas are provided.

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

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.

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.

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

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.

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…

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 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.

A Theoretical Foundation for the Study of Inferential Error in Decision-Making Groups.

ERIC Educational Resources Information Center

Gouran, Dennis S.

To provide a theoretical base for investigating the influence of inferential error on group decision making, current literature on both inferential error and decision making is reviewed and applied to the Watergate incident. Although groups tend to make fewer inferential errors because members' inferences are generally not biased in the same…

Anatomy of an incident

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

Cournoyer, Michael E.; Trujillo, Stanley; Lawton, Cindy M.

A traditional view of incidents is that they are caused by shortcomings in human competence, attention, or attitude. It may be under the label of “loss of situational awareness,” procedure “violation,” or “poor” management. A different view is that human error is not the cause of failure, but a symptom of failure – trouble deeper inside the system. In this perspective, human error is not the conclusion, but rather the starting point of investigations. During an investigation, three types of information are gathered: physical, documentary, and human (recall/experience). Through the causal analysis process, apparent cause or apparent causes are identifiedmore » as the most probable cause or causes of an incident or condition that management has the control to fix and for which effective recommendations for corrective actions can be generated. A causal analysis identifies relevant human performance factors. In the following presentation, the anatomy of a radiological incident is discussed, and one case study is presented. We analyzed the contributing factors that caused a radiological incident. When underlying conditions, decisions, actions, and inactions that contribute to the incident are identified. This includes weaknesses that may warrant improvements that tolerate error. Measures that reduce consequences or likelihood of recurrence are discussed.« less

Anatomy of an incident

DOE PAGES

Cournoyer, Michael E.; Trujillo, Stanley; Lawton, Cindy M.; ...

2016-03-23

A traditional view of incidents is that they are caused by shortcomings in human competence, attention, or attitude. It may be under the label of “loss of situational awareness,” procedure “violation,” or “poor” management. A different view is that human error is not the cause of failure, but a symptom of failure – trouble deeper inside the system. In this perspective, human error is not the conclusion, but rather the starting point of investigations. During an investigation, three types of information are gathered: physical, documentary, and human (recall/experience). Through the causal analysis process, apparent cause or apparent causes are identifiedmore » as the most probable cause or causes of an incident or condition that management has the control to fix and for which effective recommendations for corrective actions can be generated. A causal analysis identifies relevant human performance factors. In the following presentation, the anatomy of a radiological incident is discussed, and one case study is presented. We analyzed the contributing factors that caused a radiological incident. When underlying conditions, decisions, actions, and inactions that contribute to the incident are identified. This includes weaknesses that may warrant improvements that tolerate error. Measures that reduce consequences or likelihood of recurrence are discussed.« less

Diagnostic decision-making and strategies to improve diagnosis.

PubMed

Thammasitboon, Satid; Cutrer, William B

2013-10-01

A significant portion of diagnostic errors arises through cognitive errors resulting from inadequate knowledge, faulty data gathering, and/or faulty verification. Experts estimate that 75% of diagnostic failures can be attributed to clinician diagnostic thinking failure. The cognitive processes that underlie diagnostic thinking of clinicians are complex and intriguing, and it is imperative that clinicians acquire explicit appreciation and application of different cognitive approaches to make decisions better. A dual-process model that unifies many theories of decision-making has emerged as a promising template for understanding how clinicians think and judge efficiently in a diagnostic reasoning process. The identification and implementation of strategies for decreasing or preventing such diagnostic errors has become a growing area of interest and research. Suggested strategies to decrease diagnostic error incidence include increasing clinician's clinical expertise and avoiding inherent cognitive errors to make decisions better. Implementing Interventions focused solely on avoiding errors may work effectively for patient safety issues such as medication errors. Addressing cognitive errors, however, requires equal effort on expanding the individual clinician's expertise. Providing cognitive support to clinicians for robust diagnostic decision-making serves as the final strategic target for decreasing diagnostic errors. Clinical guidelines and algorithms offer another method for streamlining decision-making and decreasing likelihood of cognitive diagnostic errors. Addressing cognitive processing errors is undeniably the most challenging task in reducing diagnostic errors. While many suggested approaches exist, they are mostly based on theories and sciences in cognitive psychology, decision-making, and education. The proposed interventions are primarily suggestions and very few of them have been tested in the actual practice settings. Collaborative research effort is required to effectively address cognitive processing errors. Researchers in various areas, including patient safety/quality improvement, decision-making, and problem solving, must work together to make medical diagnosis more reliable. © 2013 Mosby, Inc. All rights reserved.

The Sustained Influence of an Error on Future Decision-Making.

PubMed

Schiffler, Björn C; Bengtsson, Sara L; Lundqvist, Daniel

2017-01-01

Post-error slowing (PES) is consistently observed in decision-making tasks after negative feedback. Yet, findings are inconclusive as to whether PES supports performance accuracy. We addressed the role of PES by employing drift diffusion modeling which enabled us to investigate latent processes of reaction times and accuracy on a large-scale dataset (>5,800 participants) of a visual search experiment with emotional face stimuli. In our experiment, post-error trials were characterized by both adaptive and non-adaptive decision processes. An adaptive increase in participants' response threshold was sustained over several trials post-error. Contrarily, an initial decrease in evidence accumulation rate, followed by an increase on the subsequent trials, indicates a momentary distraction of task-relevant attention and resulted in an initial accuracy drop. Higher values of decision threshold and evidence accumulation on the post-error trial were associated with higher accuracy on subsequent trials which further gives credence to these parameters' role in post-error adaptation. Finally, the evidence accumulation rate post-error decreased when the error trial presented angry faces, a finding suggesting that the post-error decision can be influenced by the error context. In conclusion, we demonstrate that error-related response adaptations are multi-component processes that change dynamically over several trials post-error.

Applying human factors principles to alert design increases efficiency and reduces prescribing errors in a scenario-based simulation

PubMed Central

Russ, Alissa L; Zillich, Alan J; Melton, Brittany L; Russell, Scott A; Chen, Siying; Spina, Jeffrey R; Weiner, Michael; Johnson, Elizabette G; Daggy, Joanne K; McManus, M Sue; Hawsey, Jason M; Puleo, Anthony G; Doebbeling, Bradley N; Saleem, Jason J

2014-01-01

Objective To apply human factors engineering principles to improve alert interface design. We hypothesized that incorporating human factors principles into alerts would improve usability, reduce workload for prescribers, and reduce prescribing errors. Materials and methods We performed a scenario-based simulation study using a counterbalanced, crossover design with 20 Veterans Affairs prescribers to compare original versus redesigned alerts. We redesigned drug–allergy, drug–drug interaction, and drug–disease alerts based upon human factors principles. We assessed usability (learnability of redesign, efficiency, satisfaction, and usability errors), perceived workload, and prescribing errors. Results Although prescribers received no training on the design changes, prescribers were able to resolve redesigned alerts more efficiently (median (IQR): 56 (47) s) compared to the original alerts (85 (71) s; p=0.015). In addition, prescribers rated redesigned alerts significantly higher than original alerts across several dimensions of satisfaction. Redesigned alerts led to a modest but significant reduction in workload (p=0.042) and significantly reduced the number of prescribing errors per prescriber (median (range): 2 (1–5) compared to original alerts: 4 (1–7); p=0.024). Discussion Aspects of the redesigned alerts that likely contributed to better prescribing include design modifications that reduced usability-related errors, providing clinical data closer to the point of decision, and displaying alert text in a tabular format. Displaying alert text in a tabular format may help prescribers extract information quickly and thereby increase responsiveness to alerts. Conclusions This simulation study provides evidence that applying human factors design principles to medication alerts can improve usability and prescribing outcomes. PMID:24668841

Applying human factors principles to alert design increases efficiency and reduces prescribing errors in a scenario-based simulation.

PubMed

Russ, Alissa L; Zillich, Alan J; Melton, Brittany L; Russell, Scott A; Chen, Siying; Spina, Jeffrey R; Weiner, Michael; Johnson, Elizabette G; Daggy, Joanne K; McManus, M Sue; Hawsey, Jason M; Puleo, Anthony G; Doebbeling, Bradley N; Saleem, Jason J

2014-10-01

To apply human factors engineering principles to improve alert interface design. We hypothesized that incorporating human factors principles into alerts would improve usability, reduce workload for prescribers, and reduce prescribing errors. We performed a scenario-based simulation study using a counterbalanced, crossover design with 20 Veterans Affairs prescribers to compare original versus redesigned alerts. We redesigned drug-allergy, drug-drug interaction, and drug-disease alerts based upon human factors principles. We assessed usability (learnability of redesign, efficiency, satisfaction, and usability errors), perceived workload, and prescribing errors. Although prescribers received no training on the design changes, prescribers were able to resolve redesigned alerts more efficiently (median (IQR): 56 (47) s) compared to the original alerts (85 (71) s; p=0.015). In addition, prescribers rated redesigned alerts significantly higher than original alerts across several dimensions of satisfaction. Redesigned alerts led to a modest but significant reduction in workload (p=0.042) and significantly reduced the number of prescribing errors per prescriber (median (range): 2 (1-5) compared to original alerts: 4 (1-7); p=0.024). Aspects of the redesigned alerts that likely contributed to better prescribing include design modifications that reduced usability-related errors, providing clinical data closer to the point of decision, and displaying alert text in a tabular format. Displaying alert text in a tabular format may help prescribers extract information quickly and thereby increase responsiveness to alerts. This simulation study provides evidence that applying human factors design principles to medication alerts can improve usability and prescribing outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Natural Language Techniques for Decision Support Based on Patient Complaints

ERIC Educational Resources Information Center

ElMessiry, Adel Magdi

2016-01-01

Complaining is a fundamental human characteristic that has prevailed throughout the ages. We normally complain about something that went wrong. Patient complaints are no exception; they focus on problems that occurred during the episode of care. The Institute of Medicine estimated that each year thousands of patients die due to medical errors. The…

Microscopic saw mark analysis: an empirical approach.

PubMed

Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles

2015-01-01

Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62-17.82%. © 2014 American Academy of Forensic Sciences.

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

Learning relative values in the striatum induces violations of normative decision making

PubMed Central

Klein, Tilmann A.; Ullsperger, Markus; Jocham, Gerhard

2017-01-01

To decide optimally between available options, organisms need to learn the values associated with these options. Reinforcement learning models offer a powerful explanation of how these values are learnt from experience. However, human choices often violate normative principles. We suggest that seemingly counterintuitive decisions may arise as a natural consequence of the learning mechanisms deployed by humans. Here, using fMRI and a novel behavioural task, we show that, when suddenly switched to novel choice contexts, participants’ choices are incongruent with values learnt by standard learning algorithms. Instead, behaviour is compatible with the decisions of an agent learning how good an option is relative to an option with which it had previously been paired. Striatal activity exhibits the characteristics of a prediction error used to update such relative option values. Our data suggest that choices can be biased by a tendency to learn option values with reference to the available alternatives. PMID:28631734

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.

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

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.

Property and the human body: a proposal for posthumous conception.

PubMed

Ball, Eli Byron Stuart

2008-02-01

There is no greater error in law and bioethics than the continuing opposition to applying the concept of property to posthumous conception cases and the human body generally. The aim of this article is to challenge this error and the assumptions underpinning it. The language of property, conceived of as a "web of interests", can be used to capture and identify the social, moral and ethical concerns that arise in cases concerning the human body, a position that finds support from a correct reading of the early High Court of Australia's decision in Doodeward v Spence (1908) 6 CLR 406. However, a key issue on which the language of property is silent is how to quantify the various competing interests in the posthumous conception case: the concept is useful only insofar as it provides the device for capturing the entirety of the posthumous conception problem.

Human performance in the modern cockpit

NASA Technical Reports Server (NTRS)

Dismukes, R. K.; Cohen, M. M.

1992-01-01

This panel was organized by the Aerospace Human Factors Committee to illustrate behavioral research on the perceptual, cognitive, and group processes that determine crew effectiveness in modern cockpits. Crew reactions to the introduction of highly automated systems in the cockpit will be reported on. Automation can improve operational capabilities and efficiency and can reduce some types of human error, but may also introduce entirely new opportunities for error. The problem solving and decision making strategies used by crews led by captains with various personality profiles will be discussed. Also presented will be computational approaches to modeling the cognitive demands of cockpit operations and the cognitive capabilities and limitations of crew members. Factors contributing to aircrew deviations from standard operating procedures and misuse of checklist, often leading to violations, incidents, or accidents will be examined. The mechanisms of visual perception pilots use in aircraft control and the implications of these mechanisms for effective design of visual displays will be discussed.

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

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.

Normal accidents: human error and medical equipment design.

PubMed

Dain, Steven

2002-01-01

High-risk systems, which are typical of our technologically complex era, include not just nuclear power plants but also hospitals, anesthesia systems, and the practice of medicine and perfusion. In high-risk systems, no matter how effective safety devices are, some types of accidents are inevitable because the system's complexity leads to multiple and unexpected interactions. It is important for healthcare providers to apply a risk assessment and management process to decisions involving new equipment and procedures or staffing matters in order to minimize the residual risks of latent errors, which are amenable to correction because of the large window of opportunity for their detection. This article provides an introduction to basic risk management and error theory principles and examines ways in which they can be applied to reduce and mitigate the inevitable human errors that accompany high-risk systems. The article also discusses "human factor engineering" (HFE), the process which is used to design equipment/ human interfaces in order to mitigate design errors. The HFE process involves interaction between designers and endusers to produce a series of continuous refinements that are incorporated into the final product. The article also examines common design problems encountered in the operating room that may predispose operators to commit errors resulting in harm to the patient. While recognizing that errors and accidents are unavoidable, organizations that function within a high-risk system must adopt a "safety culture" that anticipates problems and acts aggressively through an anonymous, "blameless" reporting mechanism to resolve them. We must continuously examine and improve the design of equipment and procedures, personnel, supplies and materials, and the environment in which we work to reduce error and minimize its effects. Healthcare providers must take a leading role in the day-to-day management of the "Perioperative System" and be a role model in promoting a culture of safety in their organizations.

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.

Effect of thematic map misclassification on landscape multi-metric assessment.

PubMed

Kleindl, William J; Powell, Scott L; Hauer, F Richard

2015-06-01

Advancements in remote sensing and computational tools have increased our awareness of large-scale environmental problems, thereby creating a need for monitoring, assessment, and management at these scales. Over the last decade, several watershed and regional multi-metric indices have been developed to assist decision-makers with planning actions of these scales. However, these tools use remote-sensing products that are subject to land-cover misclassification, and these errors are rarely incorporated in the assessment results. Here, we examined the sensitivity of a landscape-scale multi-metric index (MMI) to error from thematic land-cover misclassification and the implications of this uncertainty for resource management decisions. Through a case study, we used a simplified floodplain MMI assessment tool, whose metrics were derived from Landsat thematic maps, to initially provide results that were naive to thematic misclassification error. Using a Monte Carlo simulation model, we then incorporated map misclassification error into our MMI, resulting in four important conclusions: (1) each metric had a different sensitivity to error; (2) within each metric, the bias between the error-naive metric scores and simulated scores that incorporate potential error varied in magnitude and direction depending on the underlying land cover at each assessment site; (3) collectively, when the metrics were combined into a multi-metric index, the effects were attenuated; and (4) the index bias indicated that our naive assessment model may overestimate floodplain condition of sites with limited human impacts and, to a lesser extent, either over- or underestimated floodplain condition of sites with mixed land use.

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.

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.

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

A Sensemaking Perspective on Situation Awareness in Power Grid Operations

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

Greitzer, Frank L.; Schur, Anne; Paget, Mia L.

2008-07-21

With increasing complexity and interconnectivity of the electric power grid, the scope and complexity of grid operations continues to grow. New paradigms are needed to guide research to improve operations by enhancing situation awareness of operators. Research on human factors/situation awareness is described within a taxonomy of tools and approaches that address different levels of cognitive processing. While user interface features and visualization approaches represent the predominant focus of human factors studies of situation awareness, this paper argues that a complementary level, sensemaking, deserves further consideration by designers of decision support systems for power grid operations. A sensemaking perspective onmore » situation aware-ness may reveal new insights that complement ongoing human factors research, where the focus of the investigation of errors is to understand why the decision makers experienced the situation the way they did, or why what they saw made sense to them at the time.« less

Cognition in Space Workshop. 1; Metrics and Models

NASA Technical Reports Server (NTRS)

Woolford, Barbara; Fielder, Edna

2005-01-01

"Cognition in Space Workshop I: Metrics and Models" was the first in a series of workshops sponsored by NASA to develop an integrated research and development plan supporting human cognition in space exploration. The workshop was held in Chandler, Arizona, October 25-27, 2004. The participants represented academia, government agencies, and medical centers. This workshop addressed the following goal of the NASA Human System Integration Program for Exploration: to develop a program to manage risks due to human performance and human error, specifically ones tied to cognition. Risks range from catastrophic error to degradation of efficiency and failure to accomplish mission goals. Cognition itself includes memory, decision making, initiation of motor responses, sensation, and perception. Four subgoals were also defined at the workshop as follows: (1) NASA needs to develop a human-centered design process that incorporates standards for human cognition, human performance, and assessment of human interfaces; (2) NASA needs to identify and assess factors that increase risks associated with cognition; (3) NASA needs to predict risks associated with cognition; and (4) NASA needs to mitigate risk, both prior to actual missions and in real time. This report develops the material relating to these four subgoals.

Artificial intelligence in medicine: humans need not apply?

PubMed

Diprose, William; Buist, Nicholas

2016-05-06

Artificial intelligence (AI) is a rapidly growing field with a wide range of applications. Driven by economic constraints and the potential to reduce human error, we believe that over the coming years AI will perform a significant amount of the diagnostic and treatment decision-making traditionally performed by the doctor. Humans would continue to be an important part of healthcare delivery, but in many situations, less expensive fit-for-purpose healthcare workers could be trained to 'fill the gaps' where AI are less capable. As a result, the role of the doctor as an expensive problem-solver would become redundant.

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.

Error affect inoculation for a complex decision-making task.

PubMed

Tabernero, Carmen; Wood, Robert E

2009-05-01

Individuals bring knowledge, implicit theories, and goal orientations to group meetings. Group decisions arise out of the exchange of these orientations. This research explores how a trainee's exploratory and deliberate process (an incremental theory and learning goal orientation) impacts the effectiveness of individual and group decision-making processes. The effectiveness of this training program is compared with another program that included error affect inoculation (EAI). Subjects were 40 Spanish Policemen in a training course. They were distributed in two training conditions for an individual and group decision-making task. In one condition, individuals received the Self-Guided Exploration plus Deliberation Process instructions, which emphasised exploring the options and testing hypotheses. In the other condition, individuals also received instructions based on Error Affect Inoculation (EAI), which emphasised positive affective reactions to errors and mistakes when making decisions. Results show that the quality of decisions increases when the groups share their reasoning. The AIE intervention promotes sharing information, flexible initial viewpoints, and improving the quality of group decisions. Implications and future directions are discussed.

[Medical errors: inevitable but preventable].

PubMed

Giard, R W

2001-10-27

Medical errors are increasingly reported in the lay press. Studies have shown dramatic error rates of 10 percent or even higher. From a methodological point of view, studying the frequency and causes of medical errors is far from simple. Clinical decisions on diagnostic or therapeutic interventions are always taken within a clinical context. Reviewing outcomes of interventions without taking into account both the intentions and the arguments for a particular action will limit the conclusions from a study on the rate and preventability of errors. The interpretation of the preventability of medical errors is fraught with difficulties and probably highly subjective. Blaming the doctor personally does not do justice to the actual situation and especially the organisational framework. Attention for and improvement of the organisational aspects of error are far more important then litigating the person. To err is and will remain human and if we want to reduce the incidence of faults we must be able to learn from our mistakes. That requires an open attitude towards medical mistakes, a continuous effort in their detection, a sound analysis and, where feasible, the institution of preventive measures.

The Relationship Between Technical Errors and Decision Making Skills in the Junior Resident

PubMed Central

Nathwani, J. N.; Fiers, R.M.; Ray, R.D.; Witt, A.K.; Law, K. E.; DiMarco, S.M.; Pugh, C.M.

2017-01-01

Objective The purpose of this study is to co-evaluate resident technical errors and decision-making capabilities during placement of a subclavian central venous catheter (CVC). We hypothesize that there will be significant correlations between scenario based decision making skills, and technical proficiency in central line insertion. We also predict residents will have problems in anticipating common difficulties and generating solutions associated with line placement. Design Participants were asked to insert a subclavian central line on a simulator. After completion, residents were presented with a real life patient photograph depicting CVC placement and asked to anticipate difficulties and generate solutions. Error rates were analyzed using chi-square tests and a 5% expected error rate. Correlations were sought by comparing technical errors and scenario based decision making. Setting This study was carried out at seven tertiary care centers. Participants Study participants (N=46) consisted of largely first year research residents that could be followed longitudinally. Second year research and clinical residents were not excluded. Results Six checklist errors were committed more often than anticipated. Residents performed an average of 1.9 errors, significantly more than the 1 error, at most, per person expected (t(44)=3.82, p<.001). The most common error was performance of the procedure steps in the wrong order (28.5%, P<.001). Some of the residents (24%) had no errors, 30% committed one error, and 46 % committed more than one error. The number of technical errors committed negatively correlated with the total number of commonly identified difficulties and generated solutions (r(33)= −.429, p=.021, r(33)= −.383, p=.044 respectively). Conclusions Almost half of the surgical residents committed multiple errors while performing subclavian CVC placement. The correlation between technical errors and decision making skills suggests a critical need to train residents in both technique and error management. ACGME Competencies Medical Knowledge, Practice Based Learning and Improvement, Systems Based Practice PMID:27671618

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.

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

Routes to failure: analysis of 41 civil aviation accidents from the Republic of China using the human factors analysis and classification system.

PubMed

Li, Wen-Chin; Harris, Don; Yu, Chung-San

2008-03-01

The human factors analysis and classification system (HFACS) is based upon Reason's organizational model of human error. HFACS was developed as an analytical framework for the investigation of the role of human error in aviation accidents, however, there is little empirical work formally describing the relationship between the components in the model. This research analyses 41 civil aviation accidents occurring to aircraft registered in the Republic of China (ROC) between 1999 and 2006 using the HFACS framework. The results show statistically significant relationships between errors at the operational level and organizational inadequacies at both the immediately adjacent level (preconditions for unsafe acts) and higher levels in the organization (unsafe supervision and organizational influences). The pattern of the 'routes to failure' observed in the data from this analysis of civil aircraft accidents show great similarities to that observed in the analysis of military accidents. This research lends further support to Reason's model that suggests that active failures are promoted by latent conditions in the organization. Statistical relationships linking fallible decisions in upper management levels were found to directly affect supervisory practices, thereby creating the psychological preconditions for unsafe acts and hence indirectly impairing the performance of pilots, ultimately leading to accidents.

Defining health information technology-related errors: new developments since to err is human.

PubMed

Sittig, Dean F; Singh, Hardeep

2011-07-25

Despite the promise of health information technology (HIT), recent literature has revealed possible safety hazards associated with its use. The Office of the National Coordinator for HIT recently sponsored an Institute of Medicine committee to synthesize evidence and experience from the field on how HIT affects patient safety. To lay the groundwork for defining, measuring, and analyzing HIT-related safety hazards, we propose that HIT-related error occurs anytime HIT is unavailable for use, malfunctions during use, is used incorrectly by someone, or when HIT interacts with another system component incorrectly, resulting in data being lost or incorrectly entered, displayed, or transmitted. These errors, or the decisions that result from them, significantly increase the risk of adverse events and patient harm. We describe how a sociotechnical approach can be used to understand the complex origins of HIT errors, which may have roots in rapidly evolving technological, professional, organizational, and policy initiatives.

Automation: Decision Aid or Decision Maker?

NASA Technical Reports Server (NTRS)

Skitka, Linda J.

1998-01-01

This study clarified that automation bias is something unique to automated decision making contexts, and is not the result of a general tendency toward complacency. By comparing performance on exactly the same events on the same tasks with and without an automated decision aid, we were able to determine that at least the omission error part of automation bias is due to the unique context created by having an automated decision aid, and is not a phenomena that would occur even if people were not in an automated context. However, this study also revealed that having an automated decision aid did lead to modestly improved performance across all non-error events. Participants in the non- automated condition responded with 83.68% accuracy, whereas participants in the automated condition responded with 88.67% accuracy, across all events. Automated decision aids clearly led to better overall performance when they were accurate. People performed almost exactly at the level of reliability as the automation (which across events was 88% reliable). However, also clear, is that the presence of less than 100% accurate automated decision aids creates a context in which new kinds of errors in decision making can occur. Participants in the non-automated condition responded with 97% accuracy on the six "error" events, whereas participants in the automated condition had only a 65% accuracy rate when confronted with those same six events. In short, the presence of an AMA can lead to vigilance decrements that can lead to errors in decision making.

The thinking doctor: clinical decision making in contemporary medicine.

PubMed

Trimble, Michael; Hamilton, Paul

2016-08-01

Diagnostic errors are responsible for a significant number of adverse events. Logical reasoning and good decision-making skills are key factors in reducing such errors, but little emphasis has traditionally been placed on how these thought processes occur, and how errors could be minimised. In this article, we explore key cognitive ideas that underpin clinical decision making and suggest that by employing some simple strategies, physicians might be better able to understand how they make decisions and how the process might be optimised. © 2016 Royal College of Physicians.

Automated Identification of Abnormal Adult EEGs

PubMed Central

López, S.; Suarez, G.; Jungreis, D.; Obeid, I.; Picone, J.

2016-01-01

The interpretation of electroencephalograms (EEGs) is a process that is still dependent on the subjective analysis of the examiners. Though interrater agreement on critical events such as seizures is high, it is much lower on subtler events (e.g., when there are benign variants). The process used by an expert to interpret an EEG is quite subjective and hard to replicate by machine. The performance of machine learning technology is far from human performance. We have been developing an interpretation system, AutoEEG, with a goal of exceeding human performance on this task. In this work, we are focusing on one of the early decisions made in this process – whether an EEG is normal or abnormal. We explore two baseline classification algorithms: k-Nearest Neighbor (kNN) and Random Forest Ensemble Learning (RF). A subset of the TUH EEG Corpus was used to evaluate performance. Principal Components Analysis (PCA) was used to reduce the dimensionality of the data. kNN achieved a 41.8% detection error rate while RF achieved an error rate of 31.7%. These error rates are significantly lower than those obtained by random guessing based on priors (49.5%). The majority of the errors were related to misclassification of normal EEGs. PMID:27195311

Risk-sensitive reinforcement learning.

PubMed

Shen, Yun; Tobia, Michael J; Sommer, Tobias; Obermayer, Klaus

2014-07-01

We derive a family of risk-sensitive reinforcement learning methods for agents, who face sequential decision-making tasks in uncertain environments. By applying a utility function to the temporal difference (TD) error, nonlinear transformations are effectively applied not only to the received rewards but also to the true transition probabilities of the underlying Markov decision process. When appropriate utility functions are chosen, the agents' behaviors express key features of human behavior as predicted by prospect theory (Kahneman & Tversky, 1979 ), for example, different risk preferences for gains and losses, as well as the shape of subjective probability curves. We derive a risk-sensitive Q-learning algorithm, which is necessary for modeling human behavior when transition probabilities are unknown, and prove its convergence. As a proof of principle for the applicability of the new framework, we apply it to quantify human behavior in a sequential investment task. We find that the risk-sensitive variant provides a significantly better fit to the behavioral data and that it leads to an interpretation of the subject's responses that is indeed consistent with prospect theory. The analysis of simultaneously measured fMRI signals shows a significant correlation of the risk-sensitive TD error with BOLD signal change in the ventral striatum. In addition we find a significant correlation of the risk-sensitive Q-values with neural activity in the striatum, cingulate cortex, and insula that is not present if standard Q-values are used.

Overcoming status quo bias in the human brain.

PubMed

Fleming, Stephen M; Thomas, Charlotte L; Dolan, Raymond J

2010-03-30

Humans often accept the status quo when faced with conflicting choice alternatives. However, it is unknown how neural pathways connecting cognition with action modulate this status quo acceptance. Here we developed a visual detection task in which subjects tended to favor the default when making difficult, but not easy, decisions. This bias was suboptimal in that more errors were made when the default was accepted. A selective increase in subthalamic nucleus (STN) activity was found when the status quo was rejected in the face of heightened decision difficulty. Analysis of effective connectivity showed that inferior frontal cortex, a region more active for difficult decisions, exerted an enhanced modulatory influence on the STN during switches away from the status quo. These data suggest that the neural circuits required to initiate controlled, nondefault actions are similar to those previously shown to mediate outright response suppression. We conclude that specific prefrontal-basal ganglia dynamics are involved in rejecting the default, a mechanism that may be important in a range of difficult choice scenarios.

Usability and feasibility of a tablet-based Decision-Support and Integrated Record-keeping (DESIRE) tool in the nurse management of hypertension in rural western Kenya.

PubMed

Vedanthan, Rajesh; Blank, Evan; Tuikong, Nelly; Kamano, Jemima; Misoi, Lawrence; Tulienge, Deborah; Hutchinson, Claire; Ascheim, Deborah D; Kimaiyo, Sylvester; Fuster, Valentin; Were, Martin C

2015-03-01

Mobile health (mHealth) applications have recently proliferated, especially in low- and middle-income countries, complementing task-redistribution strategies with clinical decision support. Relatively few studies address usability and feasibility issues that may impact success or failure of implementation, and few have been conducted for non-communicable diseases such as hypertension. To conduct iterative usability and feasibility testing of a tablet-based Decision Support and Integrated Record-keeping (DESIRE) tool, a technology intended to assist rural clinicians taking care of hypertension patients at the community level in a resource-limited setting in western Kenya. Usability testing consisted of "think aloud" exercises and "mock patient encounters" with five nurses, as well as one focus group discussion. Feasibility testing consisted of semi-structured interviews of five nurses and two members of the implementation team, and one focus group discussion with nurses. Content analysis was performed using both deductive codes and significant inductive codes. Critical incidents were identified and ranked according to severity. A cause-of-error analysis was used to develop corresponding design change suggestions. Fifty-seven critical incidents were identified in usability testing, 21 of which were unique. The cause-of-error analysis yielded 23 design change suggestions. Feasibility themes included barriers to implementation along both human and technical axes, facilitators to implementation, provider issues, patient issues and feature requests. This participatory, iterative human-centered design process revealed previously unaddressed usability and feasibility issues affecting the implementation of the DESIRE tool in western Kenya. In addition to well-known technical issues, we highlight the importance of human factors that can impact implementation of mHealth interventions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Usability and Feasibility of a Tablet-Based Decision-Support and Integrated Record-Keeping (DESIRE) Tool in the Nurse Management of Hypertension in Rural Western Kenya

PubMed Central

Vedanthan, Rajesh; Blank, Evan; Tuikong, Nelly; Kamano, Jemima; Misoi, Lawrence; Tulienge, Deborah; Hutchinson, Claire; Ascheim, Deborah D.; Kimaiyo, Sylvester; Fuster, Valentin; Were, Martin C.

2015-01-01

Background Mobile health (mHealth) applications have recently proliferated, especially in low- and middle-income countries, complementing task-redistribution strategies with clinical decision support. Relatively few studies address usability and feasibility issues that may impact success or failure of implementation, and few have been conducted for non-communicable diseases such as hypertension. Objective To conduct iterative usability and feasibility testing of a tablet-based Decision Support and Integrated Record-keeping (DESIRE) tool, a technology intended to assist rural clinicians taking care of hypertension patients at the community level in a resource-limited setting in western Kenya. Methods Usability testing consisted of “think aloud” exercises and “mock patient encounters” with five nurses, as well as one focus group discussion. Feasibility testing consisted of semi-structured interviews of five nurses and two members of the implementation team, and one focus group discussion with nurses. Content analysis was performed using both deductive codes and significant inductive codes. Critical incidents were identified and ranked according to severity. A cause-of-error analysis was used to develop corresponding design change suggestions. Results Fifty-seven critical incidents were identified in usability testing, 21 of which were unique. The cause-of-error analysis yielded 23 design change suggestions. Feasibility themes included barriers to implementation along both human and technical axes, facilitators to implementation, provider issues, patient issues and feature requests. Conclusions This participatory, iterative human-centered design process revealed previously unaddressed usability and feasibility issues affecting the implementation of the DESIRE tool in western Kenya. In addition to well-known technical issues, we highlight the importance of human factors that can impact implementation of mHealth interventions. PMID:25612791

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.

Patient safety in otolaryngology: a descriptive review.

PubMed

Danino, Julian; Muzaffar, Jameel; Metcalfe, Chris; Coulson, Chris

2017-03-01

Human evaluation and judgement may include errors that can have disastrous results. Within medicine and healthcare there has been slow progress towards major changes in safety. Healthcare lags behind other specialised industries, such as aviation and nuclear power, where there have been significant improvements in overall safety, especially in reducing risk of errors. Following several high profile cases in the USA during the 1990s, a report titled "To Err Is Human: Building a Safer Health System" was published. The report extrapolated that in the USA approximately 50,000 to 100,000 patients may die each year as a result of medical errors. Traditionally otolaryngology has always been regarded as a "safe specialty". A study in the USA in 2004 inferred that there may be 2600 cases of major morbidity and 165 deaths within the specialty. MEDLINE via PubMed interface was searched for English language articles published between 2000 and 2012. Each combined two or three of the keywords noted earlier. Limitations are related to several generic topics within patient safety in otolaryngology. Other areas covered have been current relevant topics due to recent interest or new advances in technology. There has been a heightened awareness within the healthcare community of patient safety; it has become a major priority. Focus has shifted from apportioning blame to prevention of the errors and implementation of patient safety mechanisms in healthcare delivery. Type of Errors can be divided into errors due to action and errors due to knowledge or planning. In healthcare there are several factors that may influence adverse events and patient safety. Although technology may improve patient safety, it also introduces new sources of error. The ability to work with people allows for the increase in safety netting. Team working has been shown to have a beneficial effect on patient safety. Any field of work involving human decision-making will always have a risk of error. Within Otolaryngology, although patient safety has evolved along similar themes as other surgical specialties; there are several specific high-risk areas. Medical error is a common problem and its human cost is of immense importance. Steps to reduce such errors require the identification of high-risk practice within a complex healthcare system. The commitment to patient safety and quality improvement in medicine depend on personal responsibility and professional accountability.

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

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

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.

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.

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,...

Clinical errors that can occur in the treatment decision-making process in psychotherapy.

PubMed

Park, Jake; Goode, Jonathan; Tompkins, Kelley A; Swift, Joshua K

2016-09-01

Clinical errors occur in the psychotherapy decision-making process whenever a less-than-optimal treatment or approach is chosen when working with clients. A less-than-optimal approach may be one that a client is unwilling to try or fully invest in based on his/her expectations and preferences, or one that may have little chance of success based on contraindications and/or limited research support. The doctor knows best and the independent choice models are two decision-making models that are frequently used within psychology, but both are associated with an increased likelihood of errors in the treatment decision-making process. In particular, these models fail to integrate all three components of the definition of evidence-based practice in psychology (American Psychological Association, 2006). In this article we describe both models and provide examples of clinical errors that can occur in each. We then introduce the shared decision-making model as an alternative that is less prone to clinical errors. PsycINFO Database Record (c) 2016 APA, all rights reserved

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

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...

Flood Forecast Accuracy and Decision Support System Approach: the Venice Case

NASA Astrophysics Data System (ADS)

Canestrelli, A.; Di Donato, M.

2016-02-01

In the recent years numerical models for weather predictions have experienced continuous advances in technology. As a result, all the disciplines making use of weather forecasts have made significant steps forward. In the case of the Safeguard of Venice, a large effort has been put in order to improve the forecast of tidal levels. In this context, the Istituzione Centro Previsioni e Segnalazioni Maree (ICPSM) of the Venice Municipality has developed and tested many different forecast models, both of the statistical and deterministic type, and has shown to produce very accurate forecasts. For Venice, the maximum admissible forecast error should be (ideally) of the order of ten centimeters at 24 hours. The entity of the forecast error clearly affects the decisional process, which mainly consists of alerting the population, activating the movable barriers installed at the three tidal inlets and contacting the port authority. This process becomes more challenging whenever the weather predictions, and therefore the water level forecasts, suddenly change. These new forecasts have to be quickly transformed into operational tasks. Therefore, it is of the utter importance to set up scheduled alerts and emergency plans by means of easy-to-follow procedures. On this direction, Technital has set up a Decision Support System based on expert procedures that minimizes the human mistakes and, as a consequence, reduces the risk of flooding of the historical center. Moreover, the Decision Support System can communicate predefined alerts to all the interested subjects. The System uses the water levels forecasts produced by the ICPSM by taking into account the accuracy at different leading times. The Decision Support System has been successfully tested with 8 years of data, 6 of them in real time. Venice experience shows that the Decision Support System is an essential tool which assesses the risks associated with a particular event, provides clear operational procedures and minimizes the impact of natural floods on human lives, private properties and historical monuments.

Four principles for user interface design of computerised clinical decision support systems.

PubMed

Kanstrup, Anne Marie; Christiansen, Marion Berg; Nøhr, Christian

2011-01-01

The paper presents results from a design research project of a user interface (UI) for a Computerised Clinical Decision Support System (CDSS). The ambition has been to design Human-Computer Interaction (HCI) that can minimise medication errors. Through an iterative design process a digital prototype for prescription of medicine has been developed. This paper presents results from the formative evaluation of the prototype conducted in a simulation laboratory with ten participating physicians. Data from the simulation is analysed by use of theory on how users perceive information. The conclusion is a model, which sum up four principles of interaction for design of CDSS. The four principles for design of user interfaces for CDSS are summarised as four A's: All in one, At a glance, At hand and Attention. The model emphasises integration of all four interaction principles in the design of user interfaces for CDSS, i.e. the model is an integrated model which we suggest as a guide for interaction design when working with preventing medication errors.

"First, know thyself": cognition and error in medicine.

PubMed

Elia, Fabrizio; Aprà, Franco; Verhovez, Andrea; Crupi, Vincenzo

2016-04-01

Although error is an integral part of the world of medicine, physicians have always been little inclined to take into account their own mistakes and the extraordinary technological progress observed in the last decades does not seem to have resulted in a significant reduction in the percentage of diagnostic errors. The failure in the reduction in diagnostic errors, notwithstanding the considerable investment in human and economic resources, has paved the way to new strategies which were made available by the development of cognitive psychology, the branch of psychology that aims at understanding the mechanisms of human reasoning. This new approach led us to realize that we are not fully rational agents able to take decisions on the basis of logical and probabilistically appropriate evaluations. In us, two different and mostly independent modes of reasoning coexist: a fast or non-analytical reasoning, which tends to be largely automatic and fast-reactive, and a slow or analytical reasoning, which permits to give rationally founded answers. One of the features of the fast mode of reasoning is the employment of standardized rules, termed "heuristics." Heuristics lead physicians to correct choices in a large percentage of cases. Unfortunately, cases exist wherein the heuristic triggered fails to fit the target problem, so that the fast mode of reasoning can lead us to unreflectively perform actions exposing us and others to variable degrees of risk. Cognitive errors arise as a result of these cases. Our review illustrates how cognitive errors can cause diagnostic problems in clinical practice.

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...

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

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.

Goal-oriented Site Characterization in Hydrogeological Applications: An Overview

NASA Astrophysics Data System (ADS)

Nowak, W.; de Barros, F.; Rubin, Y.

2011-12-01

In this study, we address the importance of goal-oriented site characterization. Given the multiple sources of uncertainty in hydrogeological applications, information needs of modeling, prediction and decision support should be satisfied with efficient and rational field campaigns. In this work, we provide an overview of an optimal sampling design framework based on Bayesian decision theory, statistical parameter inference and Bayesian model averaging. It optimizes the field sampling campaign around decisions on environmental performance metrics (e.g., risk, arrival times, etc.) while accounting for parametric and model uncertainty in the geostatistical characterization, in forcing terms, and measurement error. The appealing aspects of the framework lie on its goal-oriented character and that it is directly linked to the confidence in a specified decision. We illustrate how these concepts could be applied in a human health risk problem where uncertainty from both hydrogeological and health parameters are accounted.

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

Clinical decision support systems for addressing information needs of physicians.

PubMed

Denekamp, Yaron

2007-11-01

Clinicians routinely practice in a state of incomplete information--about the patient, and about medical knowledge pertaining to patients' care. Consequently, there is now growing interest in the use of CDSS to bring decision support to the point of care. CDSS can impact physician behavior in routine practice. Nonetheless, CDSSs are meant to support humans who are ultimately responsible for the clinical decisions, rather than replace them. Although the adoption of CDSS has proceeded at a slow pace, there is a widespread recognition that CDSSs are expected to play a crucial role in reducing medical errors and improving the quality and efficacy of health care. This will be facilitated by the gradual maturation of electronic health record systems and the emergence of standard terminologies and messaging standards for the exchange of clinical data.

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

U.S. Navy Fault-Tolerant Microcomputer.

DTIC Science & Technology

1982-07-01

105 8929 SEPULVEDA BLVD. LOS ANGELES, CALIFORNIA 90045 To: DEFENSE TECHNICAL INFORMATION CENTER Fal-ae Technoog Corporation MILITARY STANDARD FAULT...maintainability. Com- puter errors at any significant level can be disastrous in terms of human injury, aborted missions, loss of critical information and...employed to resolve the question "who checks the checker?" The IOC votes on information received from the bus and outputs the maiority decision. Thus no

Outbreak Column 16: Cognitive errors in outbreak decision making.

PubMed

Curran, Evonne T

2015-01-01

During outbreaks, decisions must be made without all the required information. People, including infection prevention and control teams (IPCTs), who have to make decisions during uncertainty use heuristics to fill the missing data gaps. Heuristics are mental model short cuts that by-and-large enable us to make good decisions quickly. However, these heuristics contain biases and effects that at times lead to cognitive (thinking) errors. These cognitive errors are not made to deliberately misrepresent any given situation; we are subject to heuristic biases when we are trying to perform optimally. The science of decision making is large; there are over 100 different biases recognised and described. Outbreak Column 16 discusses and relates these heuristics and biases to decision making during outbreak prevention, preparedness and management. Insights as to how we might recognise and avoid them are offered.

Automatic Recognition of Phonemes Using a Syntactic Processor for Error Correction.

DTIC Science & Technology

1980-12-01

OF PHONEMES USING A SYNTACTIC PROCESSOR FOR ERROR CORRECTION THESIS AFIT/GE/EE/8D-45 Robert B. ’Taylor 2Lt USAF Approved for public release...distribution unlimilted. AbP AFIT/GE/EE/ 80D-45 AUTOMATIC RECOGNITION OF PHONEMES USING A SYNTACTIC PROCESSOR FOR ERROR CORRECTION THESIS Presented to the...Testing ..................... 37 Bayes Decision Rule for Minimum Error ........... 37 Bayes Decision Rule for Minimum Risk ............ 39 Mini Max Test

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

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.

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

PubMed

Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

2015-01-01

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

Shades of Gray: Releasing the Cognitive Binds that Blind Us

DTIC Science & Technology

2016-09-01

The availability heuristic is the cognitive process of problem solving based on learning and experience. This intuitive thinking process requires...describe a person’s systematic but flawed patterns of response to both judgment and decision problems .2 Research on the effects of cognitive bias on the...errors made. The ICArUS sensemaking model currently being developed could provide the IC with software that has the ability to mirror human cognitive

Reducing diagnostic errors in medicine: what's the goal?

PubMed

Graber, Mark; Gordon, Ruthanna; Franklin, Nancy

2002-10-01

This review considers the feasibility of reducing or eliminating the three major categories of diagnostic errors in medicine: "No-fault errors" occur when the disease is silent, presents atypically, or mimics something more common. These errors will inevitably decline as medical science advances, new syndromes are identified, and diseases can be detected more accurately or at earlier stages. These errors can never be eradicated, unfortunately, because new diseases emerge, tests are never perfect, patients are sometimes noncompliant, and physicians will inevitably, at times, choose the most likely diagnosis over the correct one, illustrating the concept of necessary fallibility and the probabilistic nature of choosing a diagnosis. "System errors" play a role when diagnosis is delayed or missed because of latent imperfections in the health care system. These errors can be reduced by system improvements, but can never be eliminated because these improvements lag behind and degrade over time, and each new fix creates the opportunity for novel errors. Tradeoffs also guarantee system errors will persist, when resources are just shifted. "Cognitive errors" reflect misdiagnosis from faulty data collection or interpretation, flawed reasoning, or incomplete knowledge. The limitations of human processing and the inherent biases in using heuristics guarantee that these errors will persist. Opportunities exist, however, for improving the cognitive aspect of diagnosis by adopting system-level changes (e.g., second opinions, decision-support systems, enhanced access to specialists) and by training designed to improve cognition or cognitive awareness. Diagnostic error can be substantially reduced, but never eradicated.

Lateral habenula neurons signal errors in the prediction of reward information

PubMed Central

Bromberg-Martin, Ethan S.; Hikosaka, Okihide

2011-01-01

Humans and animals have a remarkable ability to predict future events, which they achieve by persistently searching their environment for sources of predictive information. Yet little is known about the neural systems that motivate this behavior. We hypothesized that information-seeking is assigned value by the same circuits that support reward-seeking, so that neural signals encoding conventional “reward prediction errors” include analogous “information prediction errors”. To test this we recorded from neurons in the lateral habenula, a nucleus which encodes reward prediction errors, while monkeys chose between cues that provided different amounts of information about upcoming rewards. We found that a subpopulation of lateral habenula neurons transmitted signals resembling information prediction errors, responding when reward information was unexpectedly cued, delivered, or denied. Their signals evaluated information sources reliably even when the animal’s decisions did not. These neurons could provide a common instructive signal for reward-seeking and information-seeking behavior. PMID:21857659

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.

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.

Physician's error: medical or legal concept?

PubMed

Mujovic-Zornic, Hajrija M

2010-06-01

This article deals with the common term of different physician's errors that often happen in daily practice of health care. Author begins with the term of medical malpractice, defined broadly as practice of unjustified acts or failures to act upon the part of a physician or other health care professionals, which results in harm to the patient. It is a common term that includes many types of medical errors, especially physician's errors. The author also discusses the concept of physician's error in particular, which is understood no more in traditional way only as classic error in acting something manually wrong without necessary skills (medical concept), but as an error which violates patient's basic rights and which has its final legal consequence (legal concept). In every case the essential element of liability is to establish this error as a breach of the physician's duty. The first point to note is that the standard of procedure and the standard of due care against which the physician will be judged is not going to be that of the ordinary reasonable man who enjoys no medical expertise. The court's decision should give finale answer and legal qualification in each concrete case. The author's conclusion is that higher protection of human rights in the area of health equaly demands broader concept of physician's error with the accent to its legal subject matter.

When idols look into the future: fair treatment modulates the affective forecasting error in talent show candidates.

PubMed

Feys, Marjolein; Anseel, Frederik

2015-03-01

People's affective forecasts are often inaccurate because they tend to overestimate how they will feel after an event. As life decisions are often based on affective forecasts, it is crucial to find ways to manage forecasting errors. We examined the impact of a fair treatment on forecasting errors in candidates in a Belgian reality TV talent show. We found that perceptions of fair treatment increased the forecasting error for losers (a negative audition decision) but decreased it for winners (a positive audition decision). For winners, this effect was even more pronounced when candidates were highly invested in their self-view as a future pop idol whereas for losers, the effect was more pronounced when importance was low. The results in this study point to a potential paradox between maximizing happiness and decreasing forecasting errors. A fair treatment increased the forecasting error for losers, but actually made them happier. © 2014 The British Psychological Society.

How beliefs about self-creation inflate value in the human brain.

PubMed

Koster, Raphael; Sharot, Tali; Yuan, Rachel; De Martino, Benedetto; Norton, Michael I; Dolan, Raymond J

2015-01-01

Humans have a tendency to overvalue their own ideas and creations. Understanding how these errors in judgement emerge is important for explaining suboptimal decisions, as when individuals and groups choose self-created alternatives over superior or equal ones. We show that such overvaluation is a reconstructive process that emerges when participants believe they have created an item, regardless of whether this belief is true or false. This overvaluation is observed both when false beliefs of self-creation are elicited (Experiment 1) or implanted (Experiment 2). Using brain imaging data we highlight the brain processes mediating an interaction between value and belief of self-creation. Specifically, following the creation manipulation there is an increased functional connectivity during valuation between the right caudate nucleus, where we show BOLD activity correlated with subjective value, and the left amygdala, where we show BOLD activity is linked to subjective belief. Our study highlights psychological and neurobiological processes through which false beliefs alter human valuation and in doing so throw light on a common source of error in judgements of value.

How beliefs about self-creation inflate value in the human brain

PubMed Central

Koster, Raphael; Sharot, Tali; Yuan, Rachel; De Martino, Benedetto; Norton, Michael I.; Dolan, Raymond J.

2015-01-01

Humans have a tendency to overvalue their own ideas and creations. Understanding how these errors in judgement emerge is important for explaining suboptimal decisions, as when individuals and groups choose self-created alternatives over superior or equal ones. We show that such overvaluation is a reconstructive process that emerges when participants believe they have created an item, regardless of whether this belief is true or false. This overvaluation is observed both when false beliefs of self-creation are elicited (Experiment 1) or implanted (Experiment 2). Using brain imaging data we highlight the brain processes mediating an interaction between value and belief of self-creation. Specifically, following the creation manipulation there is an increased functional connectivity during valuation between the right caudate nucleus, where we show BOLD activity correlated with subjective value, and the left amygdala, where we show BOLD activity is linked to subjective belief. Our study highlights psychological and neurobiological processes through which false beliefs alter human valuation and in doing so throw light on a common source of error in judgements of value. PMID:26388755

From conflict management to reward-based decision making: actors and critics in primate medial frontal cortex.

PubMed

Silvetti, Massimo; Alexander, William; Verguts, Tom; Brown, Joshua W

2014-10-01

The role of the medial prefrontal cortex (mPFC) and especially the anterior cingulate cortex has been the subject of intense debate for the last decade. A number of theories have been proposed to account for its function. Broadly speaking, some emphasize cognitive control, whereas others emphasize value processing; specific theories concern reward processing, conflict detection, error monitoring, and volatility detection, among others. Here we survey and evaluate them relative to experimental results from neurophysiological, anatomical, and cognitive studies. We argue for a new conceptualization of mPFC, arising from recent computational modeling work. Based on reinforcement learning theory, these new models propose that mPFC is an Actor-Critic system. This system is aimed to predict future events including rewards, to evaluate errors in those predictions, and finally, to implement optimal skeletal-motor and visceromotor commands to obtain reward. This framework provides a comprehensive account of mPFC function, accounting for and predicting empirical results across different levels of analysis, including monkey neurophysiology, human ERP, human neuroimaging, and human behavior. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Probabilistic models in human sensorimotor control

PubMed Central

Wolpert, Daniel M.

2009-01-01

Sensory and motor uncertainty form a fundamental constraint on human sensorimotor control. Bayesian decision theory (BDT) has emerged as a unifying framework to understand how the central nervous system performs optimal estimation and control in the face of such uncertainty. BDT has two components: Bayesian statistics and decision theory. Here we review Bayesian statistics and show how it applies to estimating the state of the world and our own body. Recent results suggest that when learning novel tasks we are able to learn the statistical properties of both the world and our own sensory apparatus so as to perform estimation using Bayesian statistics. We review studies which suggest that humans can combine multiple sources of information to form maximum likelihood estimates, can incorporate prior beliefs about possible states of the world so as to generate maximum a posteriori estimates and can use Kalman filter-based processes to estimate time-varying states. Finally, we review Bayesian decision theory in motor control and how the central nervous system processes errors to determine loss functions and optimal actions. We review results that suggest we plan movements based on statistics of our actions that result from signal-dependent noise on our motor outputs. Taken together these studies provide a statistical framework for how the motor system performs in the presence of uncertainty. PMID:17628731

User type certification for advanced flight control systems

NASA Technical Reports Server (NTRS)

Gilson, Richard D.; Abbott, David W.

1994-01-01

Advanced avionics through flight management systems (FMS) coupled with autopilots can now precisely control aircraft from takeoff to landing. Clearly, this has been the most important improvement in aircraft since the jet engine. Regardless of the eventual capabilities of this technology, it is doubtful that society will soon accept pilotless airliners with the same aplomb they accept driverless passenger trains. Flight crews are still needed to deal with inputing clearances, taxiing, in-flight rerouting, unexpected weather decisions, and emergencies; yet it is well known that the contribution of human errors far exceed those of current hardware or software systems. Thus human errors remain, and are even increasing in percentage as the largest contributor to total system error. Currently, the flight crew is regulated by a layered system of certification: by operation, e.g., airline transport pilot versus private pilot; by category, e.g., airplane versus helicopter; by class, e.g., single engine land versus multi-engine land; and by type (for larger aircraft and jet powered aircraft), e.g., Boeing 767 or Airbus A320. Nothing in the certification process now requires an in-depth proficiency with specific types of avionics systems despite their prominent role in aircraft control and guidance.

STARS Proceedings (3-4 December 1991)

DTIC Science & Technology

1991-12-04

PROJECT PROCESS OBJECTIVES & ASSOCIATED METRICS: Prioritize ECPs: complexity & error-history measures 0 Make vs Buy decisions: Effort & Quality (or...history measures, error- proneness and past histories of trouble with particular modules are very useful measures. Make vs Buy decisions: Does the...Effort offset the gain in Quality relative to buy ... Effort and Quality (or defect rate) histories give helpful indications of how to make this decision

IMU-Based Gait Recognition Using Convolutional Neural Networks and Multi-Sensor Fusion.

PubMed

Dehzangi, Omid; Taherisadr, Mojtaba; ChangalVala, Raghvendar

2017-11-27

The wide spread usage of wearable sensors such as in smart watches has provided continuous access to valuable user generated data such as human motion that could be used to identify an individual based on his/her motion patterns such as, gait. Several methods have been suggested to extract various heuristic and high-level features from gait motion data to identify discriminative gait signatures and distinguish the target individual from others. However, the manual and hand crafted feature extraction is error prone and subjective. Furthermore, the motion data collected from inertial sensors have complex structure and the detachment between manual feature extraction module and the predictive learning models might limit the generalization capabilities. In this paper, we propose a novel approach for human gait identification using time-frequency (TF) expansion of human gait cycles in order to capture joint 2 dimensional (2D) spectral and temporal patterns of gait cycles. Then, we design a deep convolutional neural network (DCNN) learning to extract discriminative features from the 2D expanded gait cycles and jointly optimize the identification model and the spectro-temporal features in a discriminative fashion. We collect raw motion data from five inertial sensors placed at the chest, lower-back, right hand wrist, right knee, and right ankle of each human subject synchronously in order to investigate the impact of sensor location on the gait identification performance. We then present two methods for early (input level) and late (decision score level) multi-sensor fusion to improve the gait identification generalization performance. We specifically propose the minimum error score fusion (MESF) method that discriminatively learns the linear fusion weights of individual DCNN scores at the decision level by minimizing the error rate on the training data in an iterative manner. 10 subjects participated in this study and hence, the problem is a 10-class identification task. Based on our experimental results, 91% subject identification accuracy was achieved using the best individual IMU and 2DTF-DCNN. We then investigated our proposed early and late sensor fusion approaches, which improved the gait identification accuracy of the system to 93.36% and 97.06%, respectively.

[Cognitive errors in diagnostic decision making].

PubMed

Gäbler, Martin

2017-10-01

Approximately 10-15% of our diagnostic decisions are faulty and may lead to unfavorable and dangerous outcomes, which could be avoided. These diagnostic errors are mainly caused by cognitive biases in the diagnostic reasoning process.Our medical diagnostic decision-making is based on intuitive "System 1" and analytical "System 2" diagnostic decision-making and can be deviated by unconscious cognitive biases.These deviations can be positively influenced on a systemic and an individual level. For the individual, metacognition (internal withdrawal from the decision-making process) and debiasing strategies, such as verification, falsification and rule out worst-case scenarios, can lead to improved diagnostic decisions making.

How infants' reaches reveal principles of sensorimotor decision making

NASA Astrophysics Data System (ADS)

Dineva, Evelina; Schöner, Gregor

2018-01-01

In Piaget's classical A-not-B-task, infants repeatedly make a sensorimotor decision to reach to one of two cued targets. Perseverative errors are induced by switching the cue from A to B, while spontaneous errors are unsolicited reaches to B when only A is cued. We argue that theoretical accounts of sensorimotor decision-making fail to address how motor decisions leave a memory trace that may impact future sensorimotor decisions. Instead, in extant neural models, perseveration is caused solely by the history of stimulation. We present a neural dynamic model of sensorimotor decision-making within the framework of Dynamic Field Theory, in which a dynamic instability amplifies fluctuations in neural activation into macroscopic, stable neural activation states that leave memory traces. The model predicts perseveration, but also a tendency to repeat spontaneous errors. To test the account, we pool data from several A-not-B experiments. A conditional probabilities analysis accounts quantitatively how motor decisions depend on the history of reaching. The results provide evidence for the interdependence among subsequent reaching decisions that is explained by the model, showing that by amplifying small differences in activation and affecting learning, decisions have consequences beyond the individual behavioural act.

Public Speaking Apprehension, Decision-Making Errors in the Selection of Speech Introduction Strategies and Adherence to Strategy.

ERIC Educational Resources Information Center

Beatty, Michael J.

1988-01-01

Examines the choice-making processes of students engaged in the selection of speech introduction strategies. Finds that the frequency of students making decision-making errors was a positive function of public speaking apprehension. (MS)

Decision-problem state analysis methodology

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

A methodology for analyzing a decision-problem state is presented. The methodology is based on the analysis of an incident in terms of the set of decision-problem conditions encountered. By decomposing the events that preceded an unwanted outcome, such as an accident, into the set of decision-problem conditions that were resolved, a more comprehensive understanding is possible. All human-error accidents are not caused by faulty decision-problem resolutions, but it appears to be one of the major areas of accidents cited in the literature. A three-phase methodology is presented which accommodates a wide spectrum of events. It allows for a systems content analysis of the available data to establish: (1) the resolutions made, (2) alternatives not considered, (3) resolutions missed, and (4) possible conditions not considered. The product is a map of the decision-problem conditions that were encountered as well as a projected, assumed set of conditions that should have been considered. The application of this methodology introduces a systematic approach to decomposing the events that transpired prior to the accident. The initial emphasis is on decision and problem resolution. The technique allows for a standardized method of accident into a scenario which may used for review or the development of a training simulation.

The Effect of Information Level on Human-Agent Interaction for Route Planning

DTIC Science & Technology

2015-12-01

13 Fig. 4 Experiment 1 shows regression results for time spent at DP predicting posttest trust group membership for the high LOI...decision time by pretest trust group membership. Bars denote standard error (SE). DT at DP was evaluated to see if it predicted posttest trust... group . Linear regression indicated that DT at DP was not a significant predictor of posttest trust for the Low or the Medium LOI conditions; however, it

Human factors analysis and classification system applied to civil aircraft accidents in India.

PubMed

Gaur, Deepak

2005-05-01

The Human Factors Analysis and Classification System (HFACS) has gained wide acceptance as a tool to classify human factors in aircraft accidents and incidents. This study on application of HFACS to civil aircraft accident reports at Directorate General Civil of Aviation (DGCA), India, was conducted to ascertain the practicability of applying HFACS to existing investigation reports and to analyze the trends of human factor causes of civil aircraft accidents. Accident investigation reports held at DGCA, New Delhi, for the period 1990--99 were scrutinized. In all, 83 accidents occurred during this period, of which 48 accident reports were evaluated in this study. One or more human factors contributed to 37 of the 48 (77.1%) accidents. The commonest unsafe act was 'skill based errors' followed by 'decision errors.' Violations of laid down rules were contributory in 16 cases (33.3%). 'Preconditions for unsafe acts' were seen in 23 of the 48 cases (47.9%). A fairly large number (52.1%) had 'organizational influences' contributing to the accident. These results are in consonance with larger studies of accidents in the U.S. Navy and general aviation. Such a high percentage of 'organizational influences' has not been reported in other studies. This is a healthy sign for Indian civil aviation, provided effective remedial action for the same is undertaken.

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.

Situation assessment in the Paladin tactical decision generation system

NASA Technical Reports Server (NTRS)

Mcmanus, John W.; Chappell, Alan R.; Arbuckle, P. Douglas

1992-01-01

Paladin is a real-time tactical decision generator for air combat engagements. Paladin uses specialized knowledge-based systems and other Artificial Intelligence (AI) programming techniques to address the modern air combat environment and agile aircraft in a clear and concise manner. Paladin is designed to provide insight into both the tactical benefits and the costs of enhanced agility. The system was developed using the Lisp programming language on a specialized AI workstation. Paladin utilizes a set of air combat rules, an active throttle controller, and a situation assessment module that have been implemented as a set of highly specialized knowledge-based systems. The situation assessment module was developed to determine the tactical mode of operation (aggressive, defensive, neutral, evasive, or disengagement) used by Paladin at each decision point in the air combat engagement. Paladin uses the situation assessment module; the situationally dependent modes of operation to more accurately represent the complex decision-making process of human pilots. This allows Paladin to adapt its tactics to the current situation and improves system performance. Discussed here are the details of Paladin's situation assessment and modes of operation. The results of simulation testing showing the error introduced into the situation assessment module due to estimation errors in positional and geometric data for the opponent aircraft are presented. Implementation issues for real-time performance are discussed and several solutions are presented, including Paladin's use of an inference engine designed for real-time execution.

Reducing cognitive skill decay and diagnostic error: theory-based practices for continuing education in health care.

PubMed

Weaver, Sallie J; Newman-Toker, David E; Rosen, Michael A

2012-01-01

Missed, delayed, or wrong diagnoses can have a severe impact on patients, providers, and the entire health care system. One mechanism implicated in such diagnostic errors is the deterioration of cognitive diagnostic skills that are used rarely or not at all over a prolonged period of time. Existing evidence regarding maintenance of effective cognitive reasoning skills in the clinical education, organizational training, and human factors literatures suggest that continuing education plays a critical role in mitigating and managing diagnostic skill decay. Recent models also underscore the role of system level factors (eg, cognitive decision support tools, just-in-time training opportunities) in supporting clinical reasoning process. The purpose of this manuscript is to offer a multidisciplinary review of cognitive models of clinical decision making skills in order to provide a list of best practices for supporting continuous improvement and maintenance of cognitive diagnostic processes through continuing education. Copyright © 2012 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on CME, Association for Hospital Medical Education.

C-fuzzy variable-branch decision tree with storage and classification error rate constraints

NASA Astrophysics Data System (ADS)

Yang, Shiueng-Bien

2009-10-01

The C-fuzzy decision tree (CFDT), which is based on the fuzzy C-means algorithm, has recently been proposed. The CFDT is grown by selecting the nodes to be split according to its classification error rate. However, the CFDT design does not consider the classification time taken to classify the input vector. Thus, the CFDT can be improved. We propose a new C-fuzzy variable-branch decision tree (CFVBDT) with storage and classification error rate constraints. The design of the CFVBDT consists of two phases-growing and pruning. The CFVBDT is grown by selecting the nodes to be split according to the classification error rate and the classification time in the decision tree. Additionally, the pruning method selects the nodes to prune based on the storage requirement and the classification time of the CFVBDT. Furthermore, the number of branches of each internal node is variable in the CFVBDT. Experimental results indicate that the proposed CFVBDT outperforms the CFDT and other methods.

Cognitive level and health decision-making in children: A preliminary study.

PubMed

Okwumabua, J O; Okwumabua, T M; Hayes, A; Stovall, K

1994-06-01

The study examines children's stage of cognitive development in relation to their patterns of health decision-making, including their cognitive capabilities in integrating the sequential stages of the decision-making process. A sample of 81 male (N=33) and female (N=48) students were drawn from two urban public schools in West Tennessee. All participants in the study were of African-American descent. The Centers for Disease Control Decision-Making Instrument was used to assess students' decision-making as well as their understanding of the decision-making process. The children's cognitive level was determined by their performance on three Piagetian conservation tasks. Findings revealed that both the preoperational and concrete operational children performed significantly below the formal operational children in terms of total correct responses to the decision-making scenarios. Error type analyses indicated that the preoperational children made more errors involving "skipped step" than did either the concrete or formal operational children. There were no significant differences between children's level of cognitive development and any other error type. Implications for health promotion and disease prevention programs among prevention practitioners who work regularly with children are discussed.

Claims for compensation after alleged birth asphyxia: a nationwide study covering 15 years.

PubMed

Andreasen, Stine; Backe, Bjørn; Øian, Pål

2014-02-01

To analyze compensation claims with neurological sequela or death following alleged birth asphyxia. A cohort study. A nationwide study in Norway. All claims made to The Norwegian System of Compensation to Patients (NPE) concerning sequela related to alleged birth asphyxia, between 1994 and 2008. A total of 315 claims of which 161 were awarded compensation. Examination of hospital records, experts' assessments and the decisions made by the NPE, the appeal body and courts of law. Characteristics of deliveries resulting in intrapartum asphyxia and causes of substandard care categorized in eight groups. In the 161 compensated cases, 107 children survived (96 with neurological sequela), and 54 children died. Human error was a frequent reason of substandard care, seen as inadequate fetal monitoring (50%), lack of clinical knowledge and skills (14%), noncompliance with clinical guidelines (11%), failure in referral for senior medical help (10%) and error in drug administration (4%). System errors were registered in only 3%, seen as poor organization of the department, lack of guidelines and time conflicts. The health personnel held responsible for substandard care was an obstetrician in 49% and a midwife in 46%. Substandard care is common in birth asphyxia, and human error is the cause in most cases. Inadequate fetal monitoring and lack of clinical knowledge and skills are the most frequent reasons for compensation after birth asphyxia. © 2013 Nordic Federation of Societies of Obstetrics and Gynecology.

Crew decision making under stress

NASA Technical Reports Server (NTRS)

Orasanu, J.

1992-01-01

Flight crews must make decisions and take action when systems fail or emergencies arise during flight. These situations may involve high stress. Full-missiion flight simulation studies have shown that crews differ in how effectively they cope in these circumstances, judged by operational errors and crew coordination. The present study analyzed the problem solving and decision making strategies used by crews led by captains fitting three different personality profiles. Our goal was to identify more and less effective strategies that could serve as the basis for crew selection or training. Methods: Twelve 3-member B-727 crews flew a 5-leg mission simulated flight over 1 1/2 days. Two legs included 4 abnormal events that required decisions during high workload periods. Transcripts of videotapes were analyzed to describe decision making strategies. Crew performance (errors and coordination) was judged on-line and from videotapes by check airmen. Results: Based on a median split of crew performance errors, analyses to date indicate a difference in general strategy between crews who make more or less errors. Higher performance crews showed greater situational awareness - they responded quickly to cues and interpreted them appropriately. They requested more decision relevant information and took into account more constraints. Lower performing crews showed poorer situational awareness, planning, constraint sensitivity, and coordination. The major difference between higher and lower performing crews was that poorer crews made quick decisions and then collected information to confirm their decision. Conclusion: Differences in overall crew performance were associated with differences in situational awareness, information management, and decision strategy. Captain personality profiles were associated with these differences, a finding with implications for crew selection and training.

Using 3D printed eggs to examine the egg-rejection behaviour of wild birds

PubMed Central

Nunez, Valerie; Voss, Henning U.; Croston, Rebecca; Aidala, Zachary; López, Analía V.; Van Tatenhove, Aimee; Holford, Mandë E.; Shawkey, Matthew D.; Hauber, Mark E.

2015-01-01

The coevolutionary relationships between brood parasites and their hosts are often studied by examining the egg rejection behaviour of host species using artificial eggs. However, the traditional methods for producing artificial eggs out of plasticine, plastic, wood, or plaster-of-Paris are laborious, imprecise, and prone to human error. As an alternative, 3D printing may reduce human error, enable more precise manipulation of egg size and shape, and provide a more accurate and replicable protocol for generating artificial stimuli than traditional methods. However, the usefulness of 3D printing technology for egg rejection research remains to be tested. Here, we applied 3D printing technology to the extensively studied egg rejection behaviour of American robins, Turdus migratorius. Eggs of the robin’s brood parasites, brown-headed cowbirds, Molothrus ater, vary greatly in size and shape, but it is unknown whether host egg rejection decisions differ across this gradient of natural variation. We printed artificial eggs that encompass the natural range of shapes and sizes of cowbird eggs, painted them to resemble either robin or cowbird egg colour, and used them to artificially parasitize nests of breeding wild robins. In line with previous studies, we show that robins accept mimetically coloured and reject non-mimetically coloured artificial eggs. Although we found no evidence that subtle differences in parasitic egg size or shape affect robins’ rejection decisions, 3D printing will provide an opportunity for more extensive experimentation on the potential biological or evolutionary significance of size and shape variation of foreign eggs in rejection decisions. We provide a detailed protocol for generating 3D printed eggs using either personal 3D printers or commercial printing services, and highlight additional potential future applications for this technology in the study of egg rejection. PMID:26038720

Socializing the human factors analysis and classification system: incorporating social psychological phenomena into a human factors error classification system.

PubMed

Paletz, Susannah B F; Bearman, Christopher; Orasanu, Judith; Holbrook, Jon

2009-08-01

The presence of social psychological pressures on pilot decision making was assessed using qualitative analyses of critical incident interviews. Social psychological phenomena have long been known to influence attitudes and behavior but have not been highlighted in accident investigation models. Using a critical incident method, 28 pilots who flew in Alaska were interviewed. The participants were asked to describe a situation involving weather when they were pilot in command and found their skills challenged. They were asked to describe the incident in detail but were not explicitly asked to identify social pressures. Pressures were extracted from transcripts in a bottom-up manner and then clustered into themes. Of the 28 pilots, 16 described social psychological pressures on their decision making, specifically, informational social influence, the foot-in-the-door persuasion technique, normalization of deviance, and impression management and self-consistency motives. We believe accident and incident investigations can benefit from explicit inclusion of common social psychological pressures. We recommend specific ways of incorporating these pressures into theHuman Factors Analysis and Classification System.

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.

Human Factors Research in Anesthesia Patient Safety

PubMed Central

Weinger, Matthew B.; Slagle, Jason

2002-01-01

Patient safety has become a major public concern. Human factors research in other high-risk fields has demonstrated how rigorous study of factors that affect job performance can lead to improved outcome and reduced errors after evidence-based redesign of tasks or systems. These techniques have increasingly been applied to the anesthesia work environment. This paper describes data obtained recently using task analysis and workload assessment during actual patient care and the use of cognitive task analysis to study clinical decision making. A novel concept of “non-routine events” is introduced and pilot data are presented. The results support the assertion that human factors research can make important contributions to patient safety. Information technologies play a key role in these efforts.

Human factors research in anesthesia patient safety.

PubMed Central

Weinger, M. B.; Slagle, J.

2001-01-01

Patient safety has become a major public concern. Human factors research in other high-risk fields has demonstrated how rigorous study of factors that affect job performance can lead to improved outcome and reduced errors after evidence-based redesign of tasks or systems. These techniques have increasingly been applied to the anesthesia work environment. This paper describes data obtained recently using task analysis and workload assessment during actual patient care and the use of cognitive task analysis to study clinical decision making. A novel concept of "non-routine events" is introduced and pilot data are presented. The results support the assertion that human factors research can make important contributions to patient safety. Information technologies play a key role in these efforts. PMID:11825287

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.

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.

Organizational Culture and Safety

NASA Technical Reports Server (NTRS)

Adams, Catherine A.

2003-01-01

'..only a fool perseveres in error.' Cicero. Humans will break the most advanced technological devices and override safety and security systems if they are given the latitude. Within the workplace, the operator may be just one of several factors in causing accidents or making risky decisions. Other variables considered for their involvement in the negative and often catastrophic outcomes include the organizational context and culture. Many organizations have constructed and implemented safety programs to be assimilated into their culture to assure employee commitment and understanding of the importance of everyday safety. The purpose of this paper is to examine literature on organizational safety cultures and programs that attempt to combat vulnerability, risk taking behavior and decisions and identify the role of training in attempting to mitigate unsafe acts.

The Effect of Information Level on Human-Agent Interaction for Route Planning

DTIC Science & Technology

2015-12-01

χ2 (4, 60) = 11.41, p = 0.022, and Cramer’s V = 0.308, indicating there was no effect of experiment on posttest trust. Pretest trust was not a...decision time by pretest trust group membership. Bars denote standard error (SE). DT at DP was evaluated to see if it predicted posttest trust...0.007, Cramer’s V = 0.344, indicating there was no effect of experiment on posttest trust. Pretest trust was not a significant prediction of total DT

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.

A decision support system and rule-based algorithm to augment the human interpretation of the 12-lead electrocardiogram.

PubMed

Cairns, Andrew W; Bond, Raymond R; Finlay, Dewar D; Guldenring, Daniel; Badilini, Fabio; Libretti, Guido; Peace, Aaron J; Leslie, Stephen J

The 12-lead Electrocardiogram (ECG) has been used to detect cardiac abnormalities in the same format for more than 70years. However, due to the complex nature of 12-lead ECG interpretation, there is a significant cognitive workload required from the interpreter. This complexity in ECG interpretation often leads to errors in diagnosis and subsequent treatment. We have previously reported on the development of an ECG interpretation support system designed to augment the human interpretation process. This computerised decision support system has been named 'Interactive Progressive based Interpretation' (IPI). In this study, a decision support algorithm was built into the IPI system to suggest potential diagnoses based on the interpreter's annotations of the 12-lead ECG. We hypothesise semi-automatic interpretation using a digital assistant can be an optimal man-machine model for ECG interpretation. To improve interpretation accuracy and reduce missed co-abnormalities. The Differential Diagnoses Algorithm (DDA) was developed using web technologies where diagnostic ECG criteria are defined in an open storage format, Javascript Object Notation (JSON), which is queried using a rule-based reasoning algorithm to suggest diagnoses. To test our hypothesis, a counterbalanced trial was designed where subjects interpreted ECGs using the conventional approach and using the IPI+DDA approach. A total of 375 interpretations were collected. The IPI+DDA approach was shown to improve diagnostic accuracy by 8.7% (although not statistically significant, p-value=0.1852), the IPI+DDA suggested the correct interpretation more often than the human interpreter in 7/10 cases (varying statistical significance). Human interpretation accuracy increased to 70% when seven suggestions were generated. Although results were not found to be statistically significant, we found; 1) our decision support tool increased the number of correct interpretations, 2) the DDA algorithm suggested the correct interpretation more often than humans, and 3) as many as 7 computerised diagnostic suggestions augmented human decision making in ECG interpretation. Statistical significance may be achieved by expanding sample size. Copyright © 2017 Elsevier Inc. All rights reserved.

Uncertainty and equipoise: at interplay between epistemology, decision making and ethics.

PubMed

Djulbegovic, Benjamin

2011-10-01

In recent years, various authors have proposed that the concept of equipoise be abandoned because it conflates the practice of clinical care with clinical research. At the same time, the equipoise opponents acknowledge the necessity of clinical research if there are unresolved uncertainties about the effects of proposed healthcare interventions. As equipoise represents just 1 measure of uncertainty, proposals to abandon equipoise while maintaining a requirement for addressing uncertainties are contradictory and ultimately not valid. As acknowledgment and articulation of uncertainties represent key scientific and moral requirements for human experimentation, the concept of equipoise remains the most useful framework to link the theory of human experimentation with the theory of rational choice. In this article, I show how uncertainty (equipoise) is at the intersection between epistemology, decision making and ethics of clinical research. In particular, I show how our formulation of responses to uncertainties of hoped-for benefits and unknown harms of testing is a function of the way humans cognitively process information. This approach is based on the view that considerations of ethics and rationality cannot be separated. I analyze the response to uncertainties as it relates to the dual-processing theory, which postulates that rational approach to (clinical research) decision making depends both on analytical, deliberative processes embodied in scientific method (system II), and good human intuition (system I). Ultimately, our choices can only become wiser if we understand a close and intertwined relationship between irreducible uncertainty, inevitable errors and unavoidable injustice.

Uncertainty and Equipoise: At Interplay Between Epistemology, Decision-Making and Ethics

PubMed Central

Djulbegovic, Benjamin

2011-01-01

In recent years, various authors have proposed that the concept of equipoise be abandoned since it conflates the practice of clinical care with clinical research. At the same time, the equipoise opponents acknowledge the necessity of clinical research if there are unresolved uncertainties about the effects of proposed healthcare interventions. Since equipoise represents just one measure of uncertainty, proposals to abandon equipoise while maintaining a requirement for addressing uncertainties are contradictory and ultimately not valid. As acknowledgment and articulation of uncertainties represent key scientific and moral requirements for human experimentation, the concept of equipoise remains the most useful framework to link the theory of human experimentation with the theory of rational choice. In this paper, I show how uncertainty (equipoise) is at the intersection between epistemology, decision-making and ethics of clinical research. In particular, I show how our formulation of responses to uncertainties of hoped-for benefits and unknown harms of testing is a function of the way humans cognitively process information. This approach is based on the view that considerations of ethics and rationality cannot be separated. I analyze the response to uncertainties as it relates to the dual-processing theory, which postulates that rational approach to (clinical research) decision-making depends both on analytical, deliberative processes embodied in scientific method (system II) and “good” human intuition (system I). Ultimately, our choices can only become wiser if we understand a close and intertwined relationship between irreducible uncertainty, inevitable errors, and unavoidable injustice. PMID:21817885

Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

PubMed

Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

2018-06-01

Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

Commentary: Reducing diagnostic errors: another role for checklists?

PubMed

Winters, Bradford D; Aswani, Monica S; Pronovost, Peter J

2011-03-01

Diagnostic errors are a widespread problem, although the true magnitude is unknown because they cannot currently be measured validly. These errors have received relatively little attention despite alarming estimates of associated harm and death. One promising intervention to reduce preventable harm is the checklist. This intervention has proven successful in aviation, in which situations are linear and deterministic (one alarm goes off and a checklist guides the flight crew to evaluate the cause). In health care, problems are multifactorial and complex. A checklist has been used to reduce central-line-associated bloodstream infections in intensive care units. Nevertheless, this checklist was incorporated in a culture-based safety program that engaged and changed behaviors and used robust measurement of infections to evaluate progress. In this issue, Ely and colleagues describe how three checklists could reduce the cognitive biases and mental shortcuts that underlie diagnostic errors, but point out that these tools still need to be tested. To be effective, they must reduce diagnostic errors (efficacy) and be routinely used in practice (effectiveness). Such tools must intuitively support how the human brain works, and under time pressures, clinicians rarely think in conditional probabilities when making decisions. To move forward, it is necessary to accurately measure diagnostic errors (which could come from mapping out the diagnostic process as the medication process has done and measuring errors at each step) and pilot test interventions such as these checklists to determine whether they work.

Cognitive engineering models in space systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1992-01-01

NASA space systems, including mission operations on the ground and in space, are complex, dynamic, predominantly automated systems in which the human operator is a supervisory controller. The human operator monitors and fine-tunes computer-based control systems and is responsible for ensuring safe and efficient system operation. In such systems, the potential consequences of human mistakes and errors may be very large, and low probability of such events is likely. Thus, models of cognitive functions in complex systems are needed to describe human performance and form the theoretical basis of operator workstation design, including displays, controls, and decision support aids. The operator function model represents normative operator behavior-expected operator activities given current system state. The extension of the theoretical structure of the operator function model and its application to NASA Johnson mission operations and space station applications is discussed.

Error-Related Negativities During Spelling Judgments Expose Orthographic Knowledge

PubMed Central

Harris, Lindsay N.; Perfetti, Charles A.; Rickles, Benjamin

2014-01-01

In two experiments, we demonstrate that error-related negativities (ERNs) recorded during spelling decisions can expose individual differences in lexical knowledge. The first experiment found that the ERN was elicited during spelling decisions and that its magnitude was correlated with independent measures of subjects’ spelling knowledge. In the second experiment, we manipulated the phonology of misspelled stimuli and observed that ERN magnitudes were larger when misspelled words altered the phonology of their correctly spelled counterparts than when they preserved it. Thus, when an error is made in a decision about spelling, the brain processes indexed by the ERN reflect both phonological and orthographic input to the decision process. In both experiments, ERN effect sizes were correlated with assessments of lexical knowledge and reading, including offline spelling ability and spelling-mediated vocabulary knowledge. These results affirm the interdependent nature of orthographic, semantic, and phonological knowledge components while showing that spelling knowledge uniquely influences the ERN during spelling decisions. Finally, the study demonstrates the value of ERNs in exposing individual differences in lexical knowledge. PMID:24389506

Individual differences in conflict detection during reasoning.

PubMed

Frey, Darren; Johnson, Eric D; De Neys, Wim

2018-05-01

Decades of reasoning and decision-making research have established that human judgment is often biased by intuitive heuristics. Recent "error" or bias detection studies have focused on reasoners' abilities to detect whether their heuristic answer conflicts with logical or probabilistic principles. A key open question is whether there are individual differences in this bias detection efficiency. Here we present three studies in which co-registration of different error detection measures (confidence, response time and confidence response time) allowed us to assess bias detection sensitivity at the individual participant level in a range of reasoning tasks. The results indicate that although most individuals show robust bias detection, as indexed by increased latencies and decreased confidence, there is a subgroup of reasoners who consistently fail to do so. We discuss theoretical and practical implications for the field.

Complacency and bias in human use of automation: an attentional integration.

PubMed

Parasuraman, Raja; Manzey, Dietrich H

2010-06-01

Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation. Automation-related complacency and automation bias have typically been considered separately and independently. Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved. Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator's attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect. Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams. While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency. Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics. The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems.

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...

Administration and Organizational Influences on AFDC Case Decision Errors: An Empirical Analysis.

ERIC Educational Resources Information Center

Piliavin, Irving; And Others

The quality of effort among public assistance personnel has been criticized virtually since the inception of welfare programs for the poor. However, until recently, empirical information on the performance of these workers has been nonexistent. The present study, concerned with Aid to Families with Dependent Children (AFDC) case decision errors,…

An fMRI and effective connectivity study investigating miss errors during advice utilization from human and machine agents.

PubMed

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; de Visser, Ewart; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2017-10-01

As society becomes more reliant on machines and automation, understanding how people utilize advice is a necessary endeavor. Our objective was to reveal the underlying neural associations during advice utilization from expert human and machine agents with fMRI and multivariate Granger causality analysis. During an X-ray luggage-screening task, participants accepted or rejected good or bad advice from either the human or machine agent framed as experts with manipulated reliability (high miss rate). We showed that the machine-agent group decreased their advice utilization compared to the human-agent group and these differences in behaviors during advice utilization could be accounted for by high expectations of reliable advice and changes in attention allocation due to miss errors. Brain areas involved with the salience and mentalizing networks, as well as sensory processing involved with attention, were recruited during the task and the advice utilization network consisted of attentional modulation of sensory information with the lingual gyrus as the driver during the decision phase and the fusiform gyrus as the driver during the feedback phase. Our findings expand on the existing literature by showing that misses degrade advice utilization, which is represented in a neural network involving salience detection and self-processing with perceptual integration.

Study on relationship of performance shaping factor in human error probability with prevalent stress of PUSPATI TRIGA reactor operators

NASA Astrophysics Data System (ADS)

Rahim, Ahmad Nabil Bin Ab; Mohamed, Faizal; Farid, Mohd Fairus Abdul; Fazli Zakaria, Mohd; Sangau Ligam, Alfred; Ramli, Nurhayati Binti

2018-01-01

Human factor can be affected by prevalence stress measured using Depression, Anxiety and Stress Scale (DASS). From the respondents feedback can be summarized that the main factor causes the highest prevalence stress is due to the working conditions that require operators to handle critical situation and make a prompt critical decisions. The relationship between the prevalence stress and performance shaping factors found that PSFFitness and PSFWork Process showed positive Pearson’s Correlation with the score of .763 and .826 while the level of significance, p = .028 and p = .012. These positive correlations with good significant values between prevalence stress and human performance shaping factor (PSF) related to fitness, work processes and procedures. The higher the stress level of the respondents, the higher the score of selected for the PSFs. This is due to the higher levels of stress lead to deteriorating physical health and cognitive also worsened. In addition, the lack of understanding in the work procedures can also be a factor that causes a growing stress. The higher these values will lead to the higher the probabilities of human error occur. Thus, monitoring the level of stress among operators RTP is important to ensure the safety of RTP.

Human Error: A Concept Analysis

NASA Technical Reports Server (NTRS)

Hansen, Frederick D.

2007-01-01

Human error is the subject of research in almost every industry and profession of our times. This term is part of our daily language and intuitively understood by most people however, it would be premature to assume that everyone's understanding of human error s the same. For example, human error is used to describe the outcome or consequence of human action, the causal factor of an accident, deliberate violations,a nd the actual action taken by a human being. As a result, researchers rarely agree on the either a specific definition or how to prevent human error. The purpose of this article is to explore the specific concept of human error using Concept Analysis as described by Walker and Avant (1995). The concept of human error is examined as currently used in the literature of a variety of industries and professions. Defining attributes and examples of model, borderline, and contrary cases are described. The antecedents and consequences of human error are also discussed and a definition of human error is offered.

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.

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

Limitations of Medical Research and Evidence at the Patient-Clinician Encounter Scale

PubMed Central

Ioannidis, John P. A.

2013-01-01

We explore some philosophical and scientific underpinnings of clinical research and evidence at the patient-clinician encounter scale. Insufficient evidence and a common failure to use replicable and sound research methods limit us. Both patients and health care may be, in part, complex nonlinear chaotic systems, and predicting their outcomes is a challenge. When trustworthy (credible) evidence is lacking, making correct clinical choices is often a low-probability exercise. Thus, human (clinician) error and consequent injury to patients appear inevitable. Individual clinician decision-makers operate under the philosophical influence of Adam Smith’s “invisible hand” with resulting optimism that they will eventually make the right choices and cause health benefits. The presumption of an effective “invisible hand” operating in health-care delivery has supported a model in which individual clinicians struggle to practice medicine, as they see fit based on their own intuitions and preferences (and biases) despite the obvious complexity, errors, noise, and lack of evidence pervading the system. Not surprisingly, the “invisible hand” does not appear to produce the desired community health benefits. Obtaining a benefit at the patient-clinician encounter scale requires human (clinician) behavior modification. We believe that serious rethinking and restructuring of the clinical research and care delivery systems is necessary to assure the profession and the public that we continue to do more good than harm. We need to evaluate whether, and how, detailed decision-support tools may enable reproducible clinician behavior and beneficial use of evidence. PMID:23546485

No unified reward prediction error in local field potentials from the human nucleus accumbens: evidence from epilepsy patients

PubMed Central

Rutledge, Robb B.; Zaehle, Tino; Schmitt, Friedhelm C.; Kopitzki, Klaus; Kowski, Alexander B.; Voges, Jürgen; Heinze, Hans-Jochen; Dolan, Raymond J.

2015-01-01

Functional magnetic resonance imaging (fMRI), cyclic voltammetry, and single-unit electrophysiology studies suggest that signals measured in the nucleus accumbens (Nacc) during value-based decision making represent reward prediction errors (RPEs), the difference between actual and predicted rewards. Here, we studied the precise temporal and spectral pattern of reward-related signals in the human Nacc. We recorded local field potentials (LFPs) from the Nacc of six epilepsy patients during an economic decision-making task. On each trial, patients decided whether to accept or reject a gamble with equal probabilities of a monetary gain or loss. The behavior of four patients was consistent with choices being guided by value expectations. Expected value signals before outcome onset were observed in three of those patients, at varying latencies and with nonoverlapping spectral patterns. Signals after outcome onset were correlated with RPE regressors in all subjects. However, further analysis revealed that these signals were better explained as outcome valence rather than RPE signals, with gamble gains and losses differing in the power of beta oscillations and in evoked response amplitudes. Taken together, our results do not support the idea that postsynaptic potentials in the Nacc represent a RPE that unifies outcome magnitude and prior value expectation. We discuss the generalizability of our findings to healthy individuals and the relation of our results to measurements of RPE signals obtained from the Nacc with other methods. PMID:26019312

No unified reward prediction error in local field potentials from the human nucleus accumbens: evidence from epilepsy patients.

PubMed

Stenner, Max-Philipp; Rutledge, Robb B; Zaehle, Tino; Schmitt, Friedhelm C; Kopitzki, Klaus; Kowski, Alexander B; Voges, Jürgen; Heinze, Hans-Jochen; Dolan, Raymond J

2015-08-01

Functional magnetic resonance imaging (fMRI), cyclic voltammetry, and single-unit electrophysiology studies suggest that signals measured in the nucleus accumbens (Nacc) during value-based decision making represent reward prediction errors (RPEs), the difference between actual and predicted rewards. Here, we studied the precise temporal and spectral pattern of reward-related signals in the human Nacc. We recorded local field potentials (LFPs) from the Nacc of six epilepsy patients during an economic decision-making task. On each trial, patients decided whether to accept or reject a gamble with equal probabilities of a monetary gain or loss. The behavior of four patients was consistent with choices being guided by value expectations. Expected value signals before outcome onset were observed in three of those patients, at varying latencies and with nonoverlapping spectral patterns. Signals after outcome onset were correlated with RPE regressors in all subjects. However, further analysis revealed that these signals were better explained as outcome valence rather than RPE signals, with gamble gains and losses differing in the power of beta oscillations and in evoked response amplitudes. Taken together, our results do not support the idea that postsynaptic potentials in the Nacc represent a RPE that unifies outcome magnitude and prior value expectation. We discuss the generalizability of our findings to healthy individuals and the relation of our results to measurements of RPE signals obtained from the Nacc with other methods. Copyright © 2015 the American Physiological Society.

Understanding Human Error in Naval Aviation Mishaps.

PubMed

Miranda, Andrew T

2018-04-01

To better understand the external factors that influence the performance and decisions of aviators involved in Naval aviation mishaps. Mishaps in complex activities, ranging from aviation to nuclear power operations, are often the result of interactions between multiple components within an organization. The Naval aviation mishap database contains relevant information, both in quantitative statistics and qualitative reports, that permits analysis of such interactions to identify how the working atmosphere influences aviator performance and judgment. Results from 95 severe Naval aviation mishaps that occurred from 2011 through 2016 were analyzed using Bayes' theorem probability formula. Then a content analysis was performed on a subset of relevant mishap reports. Out of the 14 latent factors analyzed, the Bayes' application identified 6 that impacted specific aspects of aviator behavior during mishaps. Technological environment, misperceptions, and mental awareness impacted basic aviation skills. The remaining 3 factors were used to inform a content analysis of the contextual information within mishap reports. Teamwork failures were the result of plan continuation aggravated by diffused responsibility. Resource limitations and risk management deficiencies impacted judgments made by squadron commanders. The application of Bayes' theorem to historical mishap data revealed the role of latent factors within Naval aviation mishaps. Teamwork failures were seen to be considerably damaging to both aviator skill and judgment. Both the methods and findings have direct application for organizations interested in understanding the relationships between external factors and human error. It presents real-world evidence to promote effective safety decisions.

Limitations of medical research and evidence at the patient-clinician encounter scale.

PubMed

Morris, Alan H; Ioannidis, John P A

2013-04-01

We explore some philosophical and scientific underpinnings of clinical research and evidence at the patient-clinician encounter scale. Insufficient evidence and a common failure to use replicable and sound research methods limit us. Both patients and health care may be, in part, complex nonlinear chaotic systems, and predicting their outcomes is a challenge. When trustworthy (credible) evidence is lacking, making correct clinical choices is often a low-probability exercise. Thus, human (clinician) error and consequent injury to patients appear inevitable. Individual clinician decision-makers operate under the philosophical influence of Adam Smith's "invisible hand" with resulting optimism that they will eventually make the right choices and cause health benefits. The presumption of an effective "invisible hand" operating in health-care delivery has supported a model in which individual clinicians struggle to practice medicine, as they see fit based on their own intuitions and preferences (and biases) despite the obvious complexity, errors, noise, and lack of evidence pervading the system. Not surprisingly, the "invisible hand" does not appear to produce the desired community health benefits. Obtaining a benefit at the patient-clinician encounter scale requires human (clinician) behavior modification. We believe that serious rethinking and restructuring of the clinical research and care delivery systems is necessary to assure the profession and the public that we continue to do more good than harm. We need to evaluate whether, and how, detailed decision-support tools may enable reproducible clinician behavior and beneficial use of evidence.

Climate change air toxic co-reduction in the context of macroeconomic modelling.

PubMed

Crawford-Brown, Douglas; Chen, Pi-Cheng; Shi, Hsiu-Ching; Chao, Chia-Wei

2013-08-15

This paper examines the health implications of global PM reduction accompanying greenhouse gas emissions reductions in the 180 national economies of the global macroeconomy. A human health effects module based on empirical data on GHG emissions, PM emissions, background PM concentrations, source apportionment and human health risk coefficients is used to estimate reductions in morbidity and mortality from PM exposures globally as co-reduction of GHG reductions. These results are compared against the "fuzzy bright line" that often underlies regulatory decisions for environmental toxics, and demonstrate that the risk reduction through PM reduction would usually be considered justified in traditional risk-based decisions for environmental toxics. It is shown that this risk reduction can be on the order of more than 4 × 10(-3) excess lifetime mortality risk, with global annual cost savings of slightly more than $10B, when uniform GHG reduction measures across all sectors of the economy form the basis for climate policy ($2.2B if only Annex I nations reduce). Consideration of co-reduction of PM-10 within a climate policy framework harmonized with other environmental policies can therefore be an effective driver of climate policy. An error analysis comparing results of the current model against those of significantly more spatially resolved models at city and national scales indicates errors caused by the low spatial resolution of the global model used here may be on the order of a factor of 2. Copyright © 2013 Elsevier Ltd. All rights reserved.

A model of the human supervisor

NASA Technical Reports Server (NTRS)

Kok, J. J.; Vanwijk, R. A.

1977-01-01

A general model of the human supervisor's behavior is given. Submechanisms of the model include: the observer/reconstructor; decision-making; and controller. A set of hypothesis is postulated for the relations between the task variables and the parameters of the different submechanisms of the model. Verification of the model hypotheses is considered using variations in the task variables. An approach is suggested for the identification of the model parameters which makes use of a multidimensional error criterion. Each of the elements of this multidimensional criterion corresponds to a certain aspect of the supervisor's behavior, and is directly related to a particular part of the model and its parameters. This approach offers good possibilities for an efficient parameter adjustment procedure.

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

Understanding and responding when things go wrong: key principles for primary care educators.

PubMed

McNab, Duncan; Bowie, Paul; Ross, Alastair; Morrison, Jill

2016-07-01

Learning from events with unwanted outcomes is an important part of workplace based education and providing evidence for medical appraisal and revalidation. It has been suggested that adopting a 'systems approach' could enhance learning and effective change. We believe the following key principles should be understood by all healthcare staff, especially those with a role in developing and delivering educational content for safety and improvement in primary care. When things go wrong, professional accountability involves accepting there has been a problem, apologising if necessary and committing to learn and change. This is easier in a 'Just Culture' where wilful disregard of safe practice is not tolerated but where decisions commensurate with training and experience do not result in blame and punishment. People usually attempt to achieve successful outcomes, but when things go wrong the contribution of hindsight and attribution bias as well as a lack of understanding of conditions and available information (local rationality) can lead to inappropriately blame 'human error'. System complexity makes reduction into component parts difficult; thus attempting to 'find-and-fix' malfunctioning components may not always be a valid approach. Finally, performance variability by staff is often needed to meet demands or cope with resource constraints. We believe understanding these core principles is a necessary precursor to adopting a 'systems approach' that can increase learning and reduce the damaging effects on morale when 'human error' is blamed. This may result in 'human error' becoming the starting point of an investigation and not the endpoint.

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.

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…

Practical Procedures for Constructing Mastery Tests to Minimize Errors of Classification and to Maximize or Optimize Decision Reliability.

ERIC Educational Resources Information Center

Byars, Alvin Gregg

The objectives of this investigation are to develop, describe, assess, and demonstrate procedures for constructing mastery tests to minimize errors of classification and to maximize decision reliability. The guidelines are based on conditions where item exchangeability is a reasonable assumption and the test constructor can control the number of…

Economics of human performance and systems total ownership cost.

PubMed

Onkham, Wilawan; Karwowski, Waldemar; Ahram, Tareq Z

2012-01-01

Financial costs of investing in people is associated with training, acquisition, recruiting, and resolving human errors have a significant impact on increased total ownership costs. These costs can also affect the exaggerate budgets and delayed schedules. The study of human performance economical assessment in the system acquisition process enhances the visibility of hidden cost drivers which support program management informed decisions. This paper presents the literature review of human total ownership cost (HTOC) and cost impacts on overall system performance. Economic value assessment models such as cost benefit analysis, risk-cost tradeoff analysis, expected value of utility function analysis (EV), growth readiness matrix, multi-attribute utility technique, and multi-regressions model were introduced to reflect the HTOC and human performance-technology tradeoffs in terms of the dollar value. The human total ownership regression model introduces to address the influencing human performance cost component measurement. Results from this study will increase understanding of relevant cost drivers in the system acquisition process over the long term.

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.

Human factors in aviation crashes involving older pilots.

PubMed

Li, Guohua; Baker, Susan P; Lamb, Margaret W; Grabowski, Jurek G; Rebok, George W

2002-02-01

Pilot errors are recognized as a contributing factor in as many as 80% of aviation crashes. Experimental studies using flight simulators indicate that due to decreased working memory capacity, older pilots are outperformed by their younger counterparts in communication tasks and flight summary scores. This study examines age-related differences in crash circumstances and pilot errors in a sample of pilots who flew commuter aircraft or air taxis and who were involved in airplane or helicopter crashes. A historical cohort of 3306 pilots who in 1987 flew commuter aircraft or air taxis and were 45-54 yr of age was constructed using the Federal Aviation Administration's airmen information system. Crash records of the study subjects for the years 1983-1997 were obtained from the National Transportation Safety Board (NTSB) by matching name and date of birth. NTSB's investigation reports were reviewed to identify pilot errors and other contributing factors. Comparisons of crash circumstances and human factors were made between pilots aged 40-49 yr and pilots aged 50-63 yr. A total of 165 crash records were studied, with 52% of these crashes involving pilots aged 50-63 yr. Crash circumstances, such as time and location of crash, type and phase of flight, and weather conditions, were similar between the two age groups. Pilot error was a contributing factor in 73% of the crashes involving younger pilots and in 69% of the crashes involving older pilots (p = 0.50). Age-related differences in the pattern of pilot errors were statistically insignificant. Overall, 23% of pilot errors were attributable to inattentiveness, 20% to flawed decisions, 18% to mishandled aircraft kinetics, and 18% to mishandled wind/runway conditions. Neither crash circumstances nor the prevalence and patterns of pilot errors appear to change significantly as age increases from the 40s to the 50s and early 60s.

Incidence of patient safety events and process-related human failures during intra-hospital transportation of patients: retrospective exploration from the institutional incident reporting system.

PubMed

Yang, Shu-Hui; Jerng, Jih-Shuin; Chen, Li-Chin; Li, Yu-Tsu; Huang, Hsiao-Fang; Wu, Chao-Ling; Chan, Jing-Yuan; Huang, Szu-Fen; Liang, Huey-Wen; Sun, Jui-Sheng

2017-11-03

Intra-hospital transportation (IHT) might compromise patient safety because of different care settings and higher demand on the human operation. Reports regarding the incidence of IHT-related patient safety events and human failures remain limited. To perform a retrospective analysis of IHT-related events, human failures and unsafe acts. A hospital-wide process for the IHT and database from the incident reporting system in a medical centre in Taiwan. All eligible IHT-related patient safety events between January 2010 to December 2015 were included. Incidence rate of IHT-related patient safety events, human failure modes, and types of unsafe acts. There were 206 patient safety events in 2 009 013 IHT sessions (102.5 per 1 000 000 sessions). Most events (n=148, 71.8%) did not involve patient harm, and process events (n=146, 70.9%) were most common. Events at the location of arrival (n=101, 49.0%) were most frequent; this location accounted for 61.0% and 44.2% of events with patient harm and those without harm, respectively (p<0.001). Of the events with human failures (n=186), the most common related process step was the preparation of the transportation team (n=91, 48.9%). Contributing unsafe acts included perceptual errors (n=14, 7.5%), decision errors (n=56, 30.1%), skill-based errors (n=48, 25.8%), and non-compliance (n=68, 36.6%). Multivariate analysis showed that human failure found in the arrival and hand-off sub-process (OR 4.84, p<0.001) was associated with increased patient harm, whereas the presence of omission (OR 0.12, p<0.001) was associated with less patient harm. This study shows a need to reduce human failures to prevent patient harm during intra-hospital transportation. We suggest that the transportation team pay specific attention to the sub-process at the location of arrival and prevent errors other than omissions. Long-term monitoring of IHT-related events is also warranted. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Study on Network Error Analysis and Locating based on Integrated Information Decision System

NASA Astrophysics Data System (ADS)

Yang, F.; Dong, Z. H.

2017-10-01

Integrated information decision system (IIDS) integrates multiple sub-system developed by many facilities, including almost hundred kinds of software, which provides with various services, such as email, short messages, drawing and sharing. Because the under-layer protocols are different, user standards are not unified, many errors are occurred during the stages of setup, configuration, and operation, which seriously affect the usage. Because the errors are various, which may be happened in different operation phases, stages, TCP/IP communication protocol layers, sub-system software, it is necessary to design a network error analysis and locating tool for IIDS to solve the above problems. This paper studies on network error analysis and locating based on IIDS, which provides strong theory and technology supports for the running and communicating of IIDS.

Human reliability assessment: tools for law enforcement

NASA Astrophysics Data System (ADS)

Ryan, Thomas G.; Overlin, Trudy K.

1997-01-01

This paper suggests ways in which human reliability analysis (HRA) can assist the United State Justice System, and more specifically law enforcement, in enhancing the reliability of the process from evidence gathering through adjudication. HRA is an analytic process identifying, describing, quantifying, and interpreting the state of human performance, and developing and recommending enhancements based on the results of individual HRA. It also draws on lessons learned from compilations of several HRA. Given the high legal standards the Justice System is bound to, human errors that might appear to be trivial in other venues can make the difference between a successful and unsuccessful prosecution. HRA has made a major contribution to the efficiency, favorable cost-benefit ratio, and overall success of many enterprises where humans interface with sophisticated technologies, such as the military, ground transportation, chemical and oil production, nuclear power generation, commercial aviation and space flight. Each of these enterprises presents similar challenges to the humans responsible for executing action and action sequences, especially where problem solving and decision making are concerned. Nowhere are humans confronted, to a greater degree, with problem solving and decision making than are the diverse individuals and teams responsible for arrest and adjudication of criminal proceedings. This paper concludes that because of the parallels between the aforementioned technologies and the adjudication process, especially crime scene evidence gathering, there is reason to believe that the HRA technology, developed and enhanced in other applications, can be transferred to the Justice System with minimal cost and with significant payoff.

Decisions to shoot in a weapon identification task: The influence of cultural stereotypes and perceived threat on false positive errors.

PubMed

Fleming, Kevin K; Bandy, Carole L; Kimble, Matthew O

2010-01-01

The decision to shoot a gun engages executive control processes that can be biased by cultural stereotypes and perceived threat. The neural locus of the decision to shoot is likely to be found in the anterior cingulate cortex (ACC), where cognition and affect converge. Male military cadets at Norwich University (N=37) performed a weapon identification task in which they made rapid decisions to shoot when images of guns appeared briefly on a computer screen. Reaction times, error rates, and electroencephalogram (EEG) activity were recorded. Cadets reacted more quickly and accurately when guns were primed by images of Middle-Eastern males wearing traditional clothing. However, cadets also made more false positive errors when tools were primed by these images. Error-related negativity (ERN) was measured for each response. Deeper ERNs were found in the medial-frontal cortex following false positive responses. Cadets who made fewer errors also produced deeper ERNs, indicating stronger executive control. Pupil size was used to measure autonomic arousal related to perceived threat. Images of Middle-Eastern males in traditional clothing produced larger pupil sizes. An image of Osama bin Laden induced the largest pupil size, as would be predicted for the exemplar of Middle East terrorism. Cadets who showed greater increases in pupil size also made more false positive errors. Regression analyses were performed to evaluate predictions based on current models of perceived threat, stereotype activation, and cognitive control. Measures of pupil size (perceived threat) and ERN (cognitive control) explained significant proportions of the variance in false positive errors to Middle-Eastern males in traditional clothing, while measures of reaction time, signal detection response bias, and stimulus discriminability explained most of the remaining variance.

Decisions to Shoot in a Weapon Identification Task: The Influence of Cultural Stereotypes and Perceived Threat on False Positive Errors

PubMed Central

Fleming, Kevin K.; Bandy, Carole L.; Kimble, Matthew O.

2014-01-01

The decision to shoot engages executive control processes that can be biased by cultural stereotypes and perceived threat. The neural locus of the decision to shoot is likely to be found in the anterior cingulate cortex (ACC) where cognition and affect converge. Male military cadets at Norwich University (N=37) performed a weapon identification task in which they made rapid decisions to shoot when images of guns appeared briefly on a computer screen. Reaction times, error rates, and EEG activity were recorded. Cadets reacted more quickly and accurately when guns were primed by images of middle-eastern males wearing traditional clothing. However, cadets also made more false positive errors when tools were primed by these images. Error-related negativity (ERN) was measured for each response. Deeper ERN’s were found in the medial-frontal cortex following false positive responses. Cadets who made fewer errors also produced deeper ERN’s, indicating stronger executive control. Pupil size was used to measure autonomic arousal related to perceived threat. Images of middle-eastern males in traditional clothing produced larger pupil sizes. An image of Osama bin Laden induced the largest pupil size, as would be predicted for the exemplar of Middle East terrorism. Cadets who showed greater increases in pupil size also made more false positive errors. Regression analyses were performed to evaluate predictions based on current models of perceived threat, stereotype activation, and cognitive control. Measures of pupil size (perceived threat) and ERN (cognitive control) explained significant proportions of the variance in false positive errors to middle-eastern males in traditional clothing, while measures of reaction time, signal detection response bias, and stimulus discriminability explained most of the remaining variance. PMID:19813139

Error-related negativities during spelling judgments expose orthographic knowledge.

PubMed

Harris, Lindsay N; Perfetti, Charles A; Rickles, Benjamin

2014-02-01

In two experiments, we demonstrate that error-related negativities (ERNs) recorded during spelling decisions can expose individual differences in lexical knowledge. The first experiment found that the ERN was elicited during spelling decisions and that its magnitude was correlated with independent measures of subjects' spelling knowledge. In the second experiment, we manipulated the phonology of misspelled stimuli and observed that ERN magnitudes were larger when misspelled words altered the phonology of their correctly spelled counterparts than when they preserved it. Thus, when an error is made in a decision about spelling, the brain processes indexed by the ERN reflect both phonological and orthographic input to the decision process. In both experiments, ERN effect sizes were correlated with assessments of lexical knowledge and reading, including offline spelling ability and spelling-mediated vocabulary knowledge. These results affirm the interdependent nature of orthographic, semantic, and phonological knowledge components while showing that spelling knowledge uniquely influences the ERN during spelling decisions. Finally, the study demonstrates the value of ERNs in exposing individual differences in lexical knowledge. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

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.

Incorporating metacognition into morbidity and mortality rounds: The next frontier in quality improvement.

PubMed

Katz, David; Detsky, Allan S

2016-02-01

This Perspective proposes the introduction of metacognition (thinking about thinking) into the existing format of hospital-based morbidity and mortality rounds. It is placed in the context of historical movements to advance quality improvement by expanding the spectrum of the causes of medical error from systems-based issues to flawed human decision-making capabilities. We suggest that the current approach that focuses on systems-based issues can be improved by exploiting the opportunities to educate physicians about predictable errors committed by reliance on cognitive heuristics. In addition, because the field of educating clinicians about cognitive heuristics has shown mixed results, this proposal represents fertile ground for further research. Educating clinicians about cognitive heuristics may improve metacognition and perhaps be the next frontier in quality improvement. © 2015 Society of Hospital Medicine.

A biometric identification system based on eigenpalm and eigenfinger features.

PubMed

Ribaric, Slobodan; Fratric, Ivan

2005-11-01

This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).

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

Carlson, J.J.; Bouchard, A.M.; Osbourn, G.C.

Future generation automated human biometric identification and verification will require multiple features/sensors together with internal and external information sources to achieve high performance, accuracy, and reliability in uncontrolled environments. The primary objective of the proposed research is to develop a theoretical and practical basis for identifying and verifying people using standoff biometric features that can be obtained with minimal inconvenience during the verification process. The basic problem involves selecting sensors and discovering features that provide sufficient information to reliably verify a person`s identity under the uncertainties caused by measurement errors and tactics of uncooperative subjects. A system was developed formore » discovering hand, face, ear, and voice features and fusing them to verify the identity of people. The system obtains its robustness and reliability by fusing many coarse and easily measured features into a near minimal probability of error decision algorithm.« less

Automatic detection and notification of "wrong patient-wrong location'' errors in the operating room.

PubMed

Sandberg, Warren S; Häkkinen, Matti; Egan, Marie; Curran, Paige K; Fairbrother, Pamela; Choquette, Ken; Daily, Bethany; Sarkka, Jukka-Pekka; Rattner, David

2005-09-01

When procedures and processes to assure patient location based on human performance do not work as expected, patients are brought incrementally closer to a possible "wrong patient-wrong procedure'' error. We developed a system for automated patient location monitoring and management. Real-time data from an active infrared/radio frequency identification tracking system provides patient location data that are robust and can be compared with an "expected process'' model to automatically flag wrong-location events as soon as they occur. The system also generates messages that are automatically sent to process managers via the hospital paging system, thus creating an active alerting function to annunciate errors. We deployed the system to detect and annunciate "patient-in-wrong-OR'' events. The system detected all "wrong-operating room (OR)'' events, and all "wrong-OR'' locations were correctly assigned within 0.50+/-0.28 minutes (mean+/-SD). This corresponded to the measured latency of the tracking system. All wrong-OR events were correctly annunciated via the paging function. This experiment demonstrates that current technology can automatically collect sufficient data to remotely monitor patient flow through a hospital, provide decision support based on predefined rules, and automatically notify stakeholders of errors.

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.

A simulator study of the interaction of pilot workload with errors, vigilance, and decisions

NASA Technical Reports Server (NTRS)

Smith, H. P. R.

1979-01-01

A full mission simulation of a civil air transport scenario that had two levels of workload was used to observe the actions of the crews and the basic aircraft parameters and to record heart rates. The results showed that the number of errors was very variable among crews but the mean increased in the higher workload case. The increase in errors was not related to rise in heart rate but was associated with vigilance times as well as the days since the last flight. The recorded data also made it possible to investigate decision time and decision order. These also varied among crews and seemed related to the ability of captains to manage the resources available to them on the flight deck.

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.

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).

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

Human striatal activation during adjustment of the response criterion in visual word recognition.

PubMed

Kuchinke, Lars; Hofmann, Markus J; Jacobs, Arthur M; Frühholz, Sascha; Tamm, Sascha; Herrmann, Manfred

2011-02-01

Results of recent computational modelling studies suggest that a general function of the striatum in human cognition is related to shifting decision criteria in selection processes. We used functional magnetic resonance imaging (fMRI) in 21 healthy subjects to examine the hemodynamic responses when subjects shift their response criterion on a trial-by-trial basis in the lexical decision paradigm. Trial-by-trial criterion setting is obtained when subjects respond faster in trials following a word trial than in trials following nonword trials - irrespective of the lexicality of the current trial. Since selection demands are equally high in the current trials, we expected to observe neural activations that are related to response criterion shifting. The behavioural data show sequential effects with faster responses in trials following word trials compared to trials following nonword trials, suggesting that subjects shifted their response criterion on a trial-by-trial basis. The neural responses revealed a signal increase in the striatum only in trials following word trials. This striatal activation is therefore likely to be related to response criterion setting. It demonstrates a role of the striatum in shifting decision criteria in visual word recognition, which cannot be attributed to pure error-related processing or the selection of a preferred response. Copyright © 2010 Elsevier Inc. All rights reserved.

Errors Affect Hypothetical Intertemporal Food Choice in Women

PubMed Central

Sellitto, Manuela; di Pellegrino, Giuseppe

2014-01-01

Growing evidence suggests that the ability to control behavior is enhanced in contexts in which errors are more frequent. Here we investigated whether pairing desirable food with errors could decrease impulsive choice during hypothetical temporal decisions about food. To this end, healthy women performed a Stop-signal task in which one food cue predicted high-error rate, and another food cue predicted low-error rate. Afterwards, we measured participants’ intertemporal preferences during decisions between smaller-immediate and larger-delayed amounts of food. We expected reduced sensitivity to smaller-immediate amounts of food associated with high-error rate. Moreover, taking into account that deprivational states affect sensitivity for food, we controlled for participants’ hunger. Results showed that pairing food with high-error likelihood decreased temporal discounting. This effect was modulated by hunger, indicating that, the lower the hunger level, the more participants showed reduced impulsive preference for the food previously associated with a high number of errors as compared with the other food. These findings reveal that errors, which are motivationally salient events that recruit cognitive control and drive avoidance learning against error-prone behavior, are effective in reducing impulsive choice for edible outcomes. PMID:25244534

"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.

Human Error In Complex Systems

NASA Technical Reports Server (NTRS)

Morris, Nancy M.; Rouse, William B.

1991-01-01

Report presents results of research aimed at understanding causes of human error in such complex systems as aircraft, nuclear powerplants, and chemical processing plants. Research considered both slips (errors of action) and mistakes (errors of intention), and influence of workload on them. Results indicated that: humans respond to conditions in which errors expected by attempting to reduce incidence of errors; and adaptation to conditions potent influence on human behavior in discretionary situations.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps/incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Quality within space exploration ground processing operations, the identification and or classification of underlying contributors and causes of human error must be identified, in order to manage human error.This presentation will provide a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

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)

48 CFR 6101.29 - Clerical mistakes; harmless error [Rule 29].

Code of Federal Regulations, 2010 CFR

2010-10-01

...; harmless error [Rule 29]. 6101.29 Section 6101.29 Federal Acquisition Regulations System CIVILIAN BOARD OF...; harmless error [Rule 29]. (a) Clerical mistakes. Clerical mistakes in decisions, orders, or other parts of... error in anything done or not done by the Board will be a ground for granting a new hearing or for...

Using Clinical Decision Support Software in Health Insurance Company

NASA Astrophysics Data System (ADS)

Konovalov, R.; Kumlander, Deniss

This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.

Commonly Unrecognized Error Variance in Statewide Assessment Programs: Sources of Error Variance and What Can Be Done to Reduce Them

ERIC Educational Resources Information Center

Brockmann, Frank

2011-01-01

State testing programs today are more extensive than ever, and their results are required to serve more purposes and high-stakes decisions than one might have imagined. Assessment results are used to hold schools, districts, and states accountable for student performance and to help guide a multitude of important decisions. This report describes…

Mechanisms underlying the influence of saliency on value-based decisions

PubMed Central

Chen, Xiaomo; Mihalas, Stefan; Niebur, Ernst; Stuphorn, Veit

2013-01-01

Objects in the environment differ in their low-level perceptual properties (e.g., how easily a fruit can be recognized) as well as in their subjective value (how tasty it is). We studied the influence of visual salience on value-based decisions using a two alternative forced choice task, in which human subjects rapidly chose items from a visual display. All targets were equally easy to detect. Nevertheless, both value and salience strongly affected choices made and reaction times. We analyzed the neuronal mechanisms underlying these behavioral effects using stochastic accumulator models, allowing us to characterize not only the averages of reaction times but their full distributions. Independent models without interaction between the possible choices failed to reproduce the observed choice behavior, while models with mutual inhibition between alternative choices produced much better results. Mutual inhibition thus is an important feature of the decision mechanism. Value influenced the amount of accumulation in all models. In contrast, increased salience could either lead to an earlier start (onset model) or to a higher rate (speed model) of accumulation. Both models explained the data from the choice trials equally well. However, salience also affected reaction times in no-choice trials in which only one item was present, as well as error trials. Only the onset model could explain the observed reaction time distributions of error trials and no-choice trials. In contrast, the speed model could not, irrespective of whether the rate increase resulted from more frequent accumulated quanta or from larger quanta. Visual salience thus likely provides an advantage in the onset, not in the processing speed, of value-based decision making. PMID:24167161

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

PubMed

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

2008-12-01

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

Case Study: Influences of Uncertainties and Traffic Scenario Difficulties in a Human-in-the-Loop Simulation

NASA Technical Reports Server (NTRS)

Bienert, Nancy; Mercer, Joey; Homola, Jeffrey; Morey, Susan; Prevot, Thomas

2014-01-01

This paper presents a case study of how factors such as wind prediction errors and metering delays can influence controller performance and workload in Human-In-The-Loop simulations. Retired air traffic controllers worked two arrival sectors adjacent to the terminal area. The main tasks were to provide safe air traffic operations and deliver the aircraft to the metering fix within +/- 25 seconds of the scheduled arrival time with the help of provided decision support tools. Analyses explore the potential impact of metering delays and system uncertainties on controller workload and performance. The results suggest that trajectory prediction uncertainties impact safety performance, while metering fix accuracy and workload appear subject to the scenario difficulty.

Understanding human management of automation errors

PubMed Central

McBride, Sara E.; Rogers, Wendy A.; Fisk, Arthur D.

2013-01-01

Automation has the potential to aid humans with a diverse set of tasks and support overall system performance. Automated systems are not always reliable, and when automation errs, humans must engage in error management, which is the process of detecting, understanding, and correcting errors. However, this process of error management in the context of human-automation interaction is not well understood. Therefore, we conducted a systematic review of the variables that contribute to error management. We examined relevant research in human-automation interaction and human error to identify critical automation, person, task, and emergent variables. We propose a framework for management of automation errors to incorporate and build upon previous models. Further, our analysis highlights variables that may be addressed through design and training to positively influence error management. Additional efforts to understand the error management process will contribute to automation designed and implemented to support safe and effective system performance. PMID:25383042

Understanding human management of automation errors.

PubMed

McBride, Sara E; Rogers, Wendy A; Fisk, Arthur D

2014-01-01

Automation has the potential to aid humans with a diverse set of tasks and support overall system performance. Automated systems are not always reliable, and when automation errs, humans must engage in error management, which is the process of detecting, understanding, and correcting errors. However, this process of error management in the context of human-automation interaction is not well understood. Therefore, we conducted a systematic review of the variables that contribute to error management. We examined relevant research in human-automation interaction and human error to identify critical automation, person, task, and emergent variables. We propose a framework for management of automation errors to incorporate and build upon previous models. Further, our analysis highlights variables that may be addressed through design and training to positively influence error management. Additional efforts to understand the error management process will contribute to automation designed and implemented to support safe and effective system performance.

An analysis of four error detection and correction schemes for the proposed Federal standard 1024 (land mobile radio)

NASA Astrophysics Data System (ADS)

Lohrmann, Carol A.

1990-03-01

Interoperability of commercial Land Mobile Radios (LMR) and the military's tactical LMR is highly desirable if the U.S. government is to respond effectively in a national emergency or in a joint military operation. This ability to talk securely and immediately across agency and military service boundaries is often overlooked. One way to ensure interoperability is to develop and promote Federal communication standards (FS). This thesis surveys one area of the proposed FS 1024 for LMRs; namely, the error detection and correction (EDAC) of the message indicator (MI) bits used for cryptographic synchronization. Several EDAC codes are examined (Hamming, Quadratic Residue, hard decision Golay and soft decision Golay), tested on three FORTRAN programmed channel simulations (INMARSAT, Gaussian and constant burst width), compared and analyzed (based on bit error rates and percent of error-free super-frame runs) so that a best code can be recommended. Out of the four codes under study, the soft decision Golay code (24,12) is evaluated to be the best. This finding is based on the code's ability to detect and correct errors as well as the relative ease of implementation of the algorithm.

[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.

Human operator response to error-likely situations in complex engineering systems

NASA Technical Reports Server (NTRS)

Morris, Nancy M.; Rouse, William B.

1988-01-01

The causes of human error in complex systems are examined. First, a conceptual framework is provided in which two broad categories of error are discussed: errors of action, or slips, and errors of intention, or mistakes. Conditions in which slips and mistakes might be expected to occur are identified, based on existing theories of human error. Regarding the role of workload, it is hypothesized that workload may act as a catalyst for error. Two experiments are presented in which humans' response to error-likely situations were examined. Subjects controlled PLANT under a variety of conditions and periodically provided subjective ratings of mental effort. A complex pattern of results was obtained, which was not consistent with predictions. Generally, the results of this research indicate that: (1) humans respond to conditions in which errors might be expected by attempting to reduce the possibility of error, and (2) adaptation to conditions is a potent influence on human behavior in discretionary situations. Subjects' explanations for changes in effort ratings are also explored.

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.

A cascaded coding scheme for error control

NASA Technical Reports Server (NTRS)

Shu, L.; Kasami, T.

1985-01-01

A cascade coding scheme for error control is investigated. The scheme employs a combination of hard and soft decisions in decoding. Error performance is analyzed. If the inner and outer codes are chosen properly, extremely high reliability can be attained even for a high channel bit-error-rate. Some example schemes are evaluated. They seem to be quite suitable for satellite down-link error control.

A cascaded coding scheme for error control

NASA Technical Reports Server (NTRS)

Kasami, T.; Lin, S.

1985-01-01

A cascaded coding scheme for error control was investigated. The scheme employs a combination of hard and soft decisions in decoding. Error performance is analyzed. If the inner and outer codes are chosen properly, extremely high reliability can be attained even for a high channel bit-error-rate. Some example schemes are studied which seem to be quite suitable for satellite down-link error control.

A Novel Design for Drug-Drug Interaction Alerts Improves Prescribing Efficiency.

PubMed

Russ, Alissa L; Chen, Siying; Melton, Brittany L; Johnson, Elizabette G; Spina, Jeffrey R; Weiner, Michael; Zillich, Alan J

2015-09-01

Drug-drug interactions (DDIs) are common in clinical care and pose serious risks for patients. Electronic health records display DDI alerts that can influence prescribers, but the interface design of DDI alerts has largely been unstudied. In this study, the objective was to apply human factors engineering principles to alert design. It was hypothesized that redesigned DDI alerts would significantly improve prescribers' efficiency and reduce prescribing errors. In a counterbalanced, crossover study with prescribers, two DDI alert designs were evaluated. Department of Veterans Affairs (VA) prescribers were video recorded as they completed fictitious patient scenarios, which included DDI alerts of varying severity. Efficiency was measured from time-stamped recordings. Prescribing errors were evaluated against predefined criteria. Efficiency and prescribing errors were analyzed with the Wilcoxon signed-rank test. Other usability data were collected on the adequacy of alert content, prescribers' use of the DDI monograph, and alert navigation. Twenty prescribers completed patient scenarios for both designs. Prescribers resolved redesigned alerts in about half the time (redesign: 52 seconds versus original design: 97 seconds; p<.001). Prescribing errors were not significantly different between the two designs. Usability results indicate that DDI alerts might be enhanced by facilitating easier access to laboratory data and dosing information and by allowing prescribers to cancel either interacting medication directly from the alert. Results also suggest that neither design provided adequate information for decision making via the primary interface. Applying human factors principles to DDI alerts improved overall efficiency. Aspects of DDI alert design that could be further enhanced prior to implementation were also identified.

Human error and human factors engineering in health care.

PubMed

Welch, D L

1997-01-01

Human error is inevitable. It happens in health care systems as it does in all other complex systems, and no measure of attention, training, dedication, or punishment is going to stop it. The discipline of human factors engineering (HFE) has been dealing with the causes and effects of human error since the 1940's. Originally applied to the design of increasingly complex military aircraft cockpits, HFE has since been effectively applied to the problem of human error in such diverse systems as nuclear power plants, NASA spacecraft, the process control industry, and computer software. Today the health care industry is becoming aware of the costs of human error and is turning to HFE for answers. Just as early experimental psychologists went beyond the label of "pilot error" to explain how the design of cockpits led to air crashes, today's HFE specialists are assisting the health care industry in identifying the causes of significant human errors in medicine and developing ways to eliminate or ameliorate them. This series of articles will explore the nature of human error and how HFE can be applied to reduce the likelihood of errors and mitigate their effects.

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.

Accuracy and reliability of forensic latent fingerprint decisions

PubMed Central

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

2011-01-01

The interpretation of forensic fingerprint evidence relies on the expertise of latent print examiners. The National Research Council of the National Academies and the legal and forensic sciences communities have called for research to measure the accuracy and reliability of latent print examiners’ decisions, a challenging and complex problem in need of systematic analysis. Our research is focused on the development of empirical approaches to studying this problem. Here, we report on the first large-scale study of the accuracy and reliability of latent print examiners’ decisions, in which 169 latent print examiners each compared approximately 100 pairs of latent and exemplar fingerprints from a pool of 744 pairs. The fingerprints were selected to include a range of attributes and quality encountered in forensic casework, and to be comparable to searches of an automated fingerprint identification system containing more than 58 million subjects. This study evaluated examiners on key decision points in the fingerprint examination process; procedures used operationally include additional safeguards designed to minimize errors. Five examiners made false positive errors for an overall false positive rate of 0.1%. Eighty-five percent of examiners made at least one false negative error for an overall false negative rate of 7.5%. Independent examination of the same comparisons by different participants (analogous to blind verification) was found to detect all false positive errors and the majority of false negative errors in this study. Examiners frequently differed on whether fingerprints were suitable for reaching a conclusion. PMID:21518906

Accuracy and reliability of forensic latent fingerprint decisions.

PubMed

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

2011-05-10

The interpretation of forensic fingerprint evidence relies on the expertise of latent print examiners. The National Research Council of the National Academies and the legal and forensic sciences communities have called for research to measure the accuracy and reliability of latent print examiners' decisions, a challenging and complex problem in need of systematic analysis. Our research is focused on the development of empirical approaches to studying this problem. Here, we report on the first large-scale study of the accuracy and reliability of latent print examiners' decisions, in which 169 latent print examiners each compared approximately 100 pairs of latent and exemplar fingerprints from a pool of 744 pairs. The fingerprints were selected to include a range of attributes and quality encountered in forensic casework, and to be comparable to searches of an automated fingerprint identification system containing more than 58 million subjects. This study evaluated examiners on key decision points in the fingerprint examination process; procedures used operationally include additional safeguards designed to minimize errors. Five examiners made false positive errors for an overall false positive rate of 0.1%. Eighty-five percent of examiners made at least one false negative error for an overall false negative rate of 7.5%. Independent examination of the same comparisons by different participants (analogous to blind verification) was found to detect all false positive errors and the majority of false negative errors in this study. Examiners frequently differed on whether fingerprints were suitable for reaching a conclusion.

Applications of integrated human error identification techniques on the chemical cylinder change task.

PubMed

Cheng, Ching-Min; Hwang, Sheue-Ling

2015-03-01

This paper outlines the human error identification (HEI) techniques that currently exist to assess latent human errors. Many formal error identification techniques have existed for years, but few have been validated to cover latent human error analysis in different domains. This study considers many possible error modes and influential factors, including external error modes, internal error modes, psychological error mechanisms, and performance shaping factors, and integrates several execution procedures and frameworks of HEI techniques. The case study in this research was the operational process of changing chemical cylinders in a factory. In addition, the integrated HEI method was used to assess the operational processes and the system's reliability. It was concluded that the integrated method is a valuable aid to develop much safer operational processes and can be used to predict human error rates on critical tasks in the plant. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Building blocks for automated elucidation of metabolites: machine learning methods for NMR prediction.

PubMed

Kuhn, Stefan; Egert, Björn; Neumann, Steffen; Steinbeck, Christoph

2008-09-25

Current efforts in Metabolomics, such as the Human Metabolome Project, collect structures of biological metabolites as well as data for their characterisation, such as spectra for identification of substances and measurements of their concentration. Still, only a fraction of existing metabolites and their spectral fingerprints are known. Computer-Assisted Structure Elucidation (CASE) of biological metabolites will be an important tool to leverage this lack of knowledge. Indispensable for CASE are modules to predict spectra for hypothetical structures. This paper evaluates different statistical and machine learning methods to perform predictions of proton NMR spectra based on data from our open database NMRShiftDB. A mean absolute error of 0.18 ppm was achieved for the prediction of proton NMR shifts ranging from 0 to 11 ppm. Random forest, J48 decision tree and support vector machines achieved similar overall errors. HOSE codes being a notably simple method achieved a comparatively good result of 0.17 ppm mean absolute error. NMR prediction methods applied in the course of this work delivered precise predictions which can serve as a building block for Computer-Assisted Structure Elucidation for biological metabolites.

Controller Strategies for Automation Tool Use under Varying Levels of Trajectory Prediction Uncertainty

NASA Technical Reports Server (NTRS)

Morey, Susan; Prevot, Thomas; Mercer, Joey; Martin, Lynne; Bienert, Nancy; Cabrall, Christopher; Hunt, Sarah; Homola, Jeffrey; Kraut, Joshua

2013-01-01

A human-in-the-loop simulation was conducted to examine the effects of varying levels of trajectory prediction uncertainty on air traffic controller workload and performance, as well as how strategies and the use of decision support tools change in response. This paper focuses on the strategies employed by two controllers from separate teams who worked in parallel but independently under identical conditions (airspace, arrival traffic, tools) with the goal of ensuring schedule conformance and safe separation for a dense arrival flow in en route airspace. Despite differences in strategy and methods, both controllers achieved high levels of schedule conformance and safe separation. Overall, results show that trajectory uncertainties introduced by wind and aircraft performance prediction errors do not affect the controllers' ability to manage traffic. Controller strategies were fairly robust to changes in error, though strategies were affected by the amount of delay to absorb (scheduled time of arrival minus estimated time of arrival). Using the results and observations, this paper proposes an ability to dynamically customize the display of information including delay time based on observed error to better accommodate different strategies and objectives.

Effective Prediction of Errors by Non-native Speakers Using Decision Tree for Speech Recognition-Based CALL System

NASA Astrophysics Data System (ADS)

Wang, Hongcui; Kawahara, Tatsuya

CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it still remains a challenge to achieve high speech recognition performance, including accurate detection of erroneous utterances by non-native speakers. Conventionally, possible error patterns, based on linguistic knowledge, are added to the lexicon and language model, or the ASR grammar network. However, this approach easily falls in the trade-off of coverage of errors and the increase of perplexity. To solve the problem, we propose a method based on a decision tree to learn effective prediction of errors made by non-native speakers. An experimental evaluation with a number of foreign students learning Japanese shows that the proposed method can effectively generate an ASR grammar network, given a target sentence, to achieve both better coverage of errors and smaller perplexity, resulting in significant improvement in ASR accuracy.

Dual processing and diagnostic errors.

PubMed

Norman, Geoff

2009-09-01

In this paper, I review evidence from two theories in psychology relevant to diagnosis and diagnostic errors. "Dual Process" theories of thinking, frequently mentioned with respect to diagnostic error, propose that categorization decisions can be made with either a fast, unconscious, contextual process called System 1 or a slow, analytical, conscious, and conceptual process, called System 2. Exemplar theories of categorization propose that many category decisions in everyday life are made by unconscious matching to a particular example in memory, and these remain available and retrievable individually. I then review studies of clinical reasoning based on these theories, and show that the two processes are equally effective; System 1, despite its reliance in idiosyncratic, individual experience, is no more prone to cognitive bias or diagnostic error than System 2. Further, I review evidence that instructions directed at encouraging the clinician to explicitly use both strategies can lead to consistent reduction in error rates.

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.

Human error in airway facilities.

DOT National Transportation Integrated Search

2001-01-01

This report examines human errors in Airway Facilities (AF) with the intent of preventing these errors from being : passed on to the new Operations Control Centers. To effectively manage errors, they first have to be identified. : Human factors engin...

The potential for intelligent decision support systems to improve the quality and consistency of medication reviews.

PubMed

Bindoff, I; Stafford, A; Peterson, G; Kang, B H; Tenni, P

2012-08-01

Drug-related problems (DRPs) are of serious concern worldwide, particularly for the elderly who often take many medications simultaneously. Medication reviews have been demonstrated to improve medication usage, leading to reductions in DRPs and potential savings in healthcare costs. However, medication reviews are not always of a consistently high standard, and there is often room for improvement in the quality of their findings. Our aim was to produce computerized intelligent decision support software that can improve the consistency and quality of medication review reports, by helping to ensure that DRPs relevant to a patient are overlooked less frequently. A system that largely achieved this goal was previously published, but refinements have been made. This paper examines the results of both the earlier and newer systems. Two prototype multiple-classification ripple-down rules medication review systems were built, the second being a refinement of the first. Each of the systems was trained incrementally using a human medication review expert. The resultant knowledge bases were analysed and compared, showing factors such as accuracy, time taken to train, and potential errors avoided. The two systems performed well, achieving accuracies of approximately 80% and 90%, after being trained on only a small number of cases (126 and 244 cases, respectively). Through analysis of the available data, it was estimated that without the system intervening, the expert training the first prototype would have missed approximately 36% of potentially relevant DRPs, and the second 43%. However, the system appeared to prevent the majority of these potential expert errors by correctly identifying the DRPs for them, leaving only an estimated 8% error rate for the first expert and 4% for the second. These intelligent decision support systems have shown a clear potential to substantially improve the quality and consistency of medication reviews, which should in turn translate into improved medication usage if they were implemented into routine use. © 2011 Blackwell Publishing Ltd.

Understanding adverse events: human factors.

PubMed Central

Reason, J

1995-01-01

(1) Human rather than technical failures now represent the greatest threat to complex and potentially hazardous systems. This includes healthcare systems. (2) Managing the human risks will never be 100% effective. Human fallibility can be moderated, but it cannot be eliminated. (3) Different error types have different underlying mechanisms, occur in different parts of the organisation, and require different methods of risk management. The basic distinctions are between: Slips, lapses, trips, and fumbles (execution failures) and mistakes (planning or problem solving failures). Mistakes are divided into rule based mistakes and knowledge based mistakes. Errors (information-handling problems) and violations (motivational problems) Active versus latent failures. Active failures are committed by those in direct contact with the patient, latent failures arise in organisational and managerial spheres and their adverse effects may take a long time to become evident. (4) Safety significant errors occur at all levels of the system, not just at the sharp end. Decisions made in the upper echelons of the organisation create the conditions in the workplace that subsequently promote individual errors and violations. Latent failures are present long before an accident and are hence prime candidates for principled risk management. (5) Measures that involve sanctions and exhortations (that is, moralistic measures directed to those at the sharp end) have only very limited effectiveness, especially so in the case of highly trained professionals. (6) Human factors problems are a product of a chain of causes in which the individual psychological factors (that is, momentary inattention, forgetting, etc) are the last and least manageable links. Attentional "capture" (preoccupation or distraction) is a necessary condition for the commission of slips and lapses. Yet, its occurrence is almost impossible to predict or control effectively. The same is true of the factors associated with forgetting. States of mind contributing to error are thus extremely difficult to manage; they can happen to the best of people at any time. (7) People do not act in isolation. Their behaviour is shaped by circumstances. The same is true for errors and violations. The likelihood of an unsafe act being committed is heavily influenced by the nature of the task and by the local workplace conditions. These, in turn, are the product of "upstream" organisational factors. Great gains in safety can ve achieved through relatively small modifications of equipment and workplaces. (8) Automation and increasing advanced equipment do not cure human factors problems, they merely relocate them. In contrast, training people to work effectively in teams costs little, but has achieved significant enhancements of human performance in aviation. (9) Effective risk management depends critically on a confidential and preferable anonymous incident monitoring system that records the individual, task, situational, and organisational factors associated with incidents and near misses. (10) Effective risk management means the simultaneous and targeted deployment of limited remedial resources at different levels of the system: the individual or team, the task, the situation, and the organisation as a whole. PMID:10151618

Closed-Loop Analysis of Soft Decisions for Serial Links

NASA Technical Reports Server (NTRS)

Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlesinger, Adam M.

2013-01-01

We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

Soft Decision Analyzer

NASA Technical Reports Server (NTRS)

Lansdowne, Chatwin; Steele, Glen; Zucha, Joan; Schlesinger, Adam

2013-01-01

We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

The role of usability in the evaluation of accidents: human error or design flaw?

PubMed

Correia, Walter; Soares, Marcelo; Barros, Marina; Campos, Fábio

2012-01-01

This article aims to highlight the role of consumer products companies in the heart and the extent of accidents involving these types of products, and as such undesired events take part as an agent in influencing decision making for the purchase of a product that nature on the part of consumers and users. The article demonstrates, by reference, interviews and case studies such as the development of poorly designed products and design errors of design can influence the usage behavior of users, thus leading to accidents, and also negatively affect the next image of a company. The full explanation of these types of questions aims to raise awareness, plan on a reliable usability, users and consumers in general about the safe use of consumer products, and also safeguard their rights before a legal system of consumer protection, even far away by the CDC--Code of Consumer Protection.

Metrological Support in Technosphere Safety

NASA Astrophysics Data System (ADS)

Akhobadze, G. N.

2017-11-01

The principle of metrological support in technosphere safety is considered. It is based on the practical metrology. The theoretical aspects of accuracy and errors of the measuring instruments intended for diagnostics and control of the technosphere under the influence of factors harmful to human beings are presented. The necessity to choose measuring devices with high metrological characteristics according to the accuracy class and contact of sensitive elements with a medium under control is shown. The types of additional errors in measuring instruments that arise when they are affected by environmental influences are described. A specific example of the analyzers application to control industrial emissions and measure the oil and particulate matter in wastewater is shown; it allows assessing advantages and disadvantages of analyzers. Besides, the recommendations regarding the missing metrological characteristics of the instruments in use are provided. The technosphere continuous monitoring taking into account the metrological principles is expected to efficiently forecast the technosphere development and make appropriate decisions.

Understanding sources of uncertainty and bias error in models of human response to low amplitude sonic booms

NASA Astrophysics Data System (ADS)

Collmar, M.; Cook, B. G.; Cowart, R.; Freund, D.; Gavin, J.

2015-10-01

A pool of 240 subjects was exposed to a library of waveforms consisting of example signatures of low boom aircraft. The signature library included intentional variations in both loudness and spectral content, and were auralized using the Gulfstream SASS-II sonic boom simulator. Post-processing was used to quantify the impacts of test design decisions on the "quality" of the resultant database. Specific lessons learned from this study include insight regarding potential for bias error due to variations in loudness or peak over-pressure, sources of uncertainty and their relative importance on objective measurements and robustness of individual metrics to wide variations in spectral content. Results provide clear guidance for design of future large scale community surveys, where one must optimize the complex tradeoffs between the size of the surveyed population, spatial footprint of those participants, and the fidelity/density of objective measurements.

Latent human error analysis and efficient improvement strategies by fuzzy TOPSIS in aviation maintenance tasks.

PubMed

Chiu, Ming-Chuan; Hsieh, Min-Chih

2016-05-01

The purposes of this study were to develop a latent human error analysis process, to explore the factors of latent human error in aviation maintenance tasks, and to provide an efficient improvement strategy for addressing those errors. First, we used HFACS and RCA to define the error factors related to aviation maintenance tasks. Fuzzy TOPSIS with four criteria was applied to evaluate the error factors. Results show that 1) adverse physiological states, 2) physical/mental limitations, and 3) coordination, communication, and planning are the factors related to airline maintenance tasks that could be addressed easily and efficiently. This research establishes a new analytic process for investigating latent human error and provides a strategy for analyzing human error using fuzzy TOPSIS. Our analysis process complements shortages in existing methodologies by incorporating improvement efficiency, and it enhances the depth and broadness of human error analysis methodology. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

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.

Frogs Exploit Statistical Regularities in Noisy Acoustic Scenes to Solve Cocktail-Party-like Problems.

PubMed

Lee, Norman; Ward, Jessica L; Vélez, Alejandro; Micheyl, Christophe; Bee, Mark A

2017-03-06

Noise is a ubiquitous source of errors in all forms of communication [1]. Noise-induced errors in speech communication, for example, make it difficult for humans to converse in noisy social settings, a challenge aptly named the "cocktail party problem" [2]. Many nonhuman animals also communicate acoustically in noisy social groups and thus face biologically analogous problems [3]. However, we know little about how the perceptual systems of receivers are evolutionarily adapted to avoid the costs of noise-induced errors in communication. In this study of Cope's gray treefrog (Hyla chrysoscelis; Hylidae), we investigated whether receivers exploit a potential statistical regularity present in noisy acoustic scenes to reduce errors in signal recognition and discrimination. We developed an anatomical/physiological model of the peripheral auditory system to show that temporal correlation in amplitude fluctuations across the frequency spectrum ("comodulation") [4-6] is a feature of the noise generated by large breeding choruses of sexually advertising males. In four psychophysical experiments, we investigated whether females exploit comodulation in background noise to mitigate noise-induced errors in evolutionarily critical mate-choice decisions. Subjects experienced fewer errors in recognizing conspecific calls and in selecting the calls of high-quality mates in the presence of simulated chorus noise that was comodulated. These data show unequivocally, and for the first time, that exploiting statistical regularities present in noisy acoustic scenes is an important biological strategy for solving cocktail-party-like problems in nonhuman animal communication. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

"Replicable effects of primes on human behavior": Correction to Payne et al. (2016).

PubMed

2016-12-01

Reports an error in "Replicable effects of primes on human behavior" by B. Keith Payne, Jazmin L. Brown-Iannuzzi and Chris Loersch ( Journal of Experimental Psychology: General , 2016[Oct], Vol 145[10], 1269-1279). In the article, the graph in Figure 5 did not contain the asterisk mentioned in the figure caption, which was intended to indicate a statistically significant difference between bet and pass prime. The online version of this article has been corrected. (The following abstract of the original article appeared in record 2016-46925-002.) The effect of primes (i.e., incidental cues) on human behavior has become controversial. Early studies reported counterintuitive findings, suggesting that primes can shape a wide range of human behaviors. Recently, several studies failed to replicate some earlier priming results, raising doubts about the reliability of those effects. We present a within-subjects procedure for priming behavior, in which participants decide whether to bet or pass on each trial of a gambling game. We report 6 replications (N = 988) showing that primes consistently affected gambling decisions when the decision was uncertain. Decisions were influenced by primes presented visibly, with a warning to ignore the primes (Experiments 1 through 3) and with subliminally presented masked primes (Experiment 4). Using a process dissociation procedure, we found evidence that primes influenced responses through both automatic and controlled processes (Experiments 5 and 6). Results provide evidence that primes can reliably affect behavior, under at least some conditions, without intention. The findings suggest that the psychological question of whether behavior priming effects are real should be separated from methodological issues affecting how easily particular experimental designs will replicate. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Individual variation in the neural processes of motor decisions in the stop signal task: the influence of novelty seeking and harm avoidance personality traits.

PubMed

Hu, Jianping; Lee, Dianne; Hu, Sien; Zhang, Sheng; Chao, Herta; Li, Chiang-Shan R

2016-06-01

Personality traits contribute to variation in human behavior, including the propensity to take risk. Extant work targeted risk-taking processes with an explicit manipulation of reward, but it remains unclear whether personality traits influence simple decisions such as speeded versus delayed responses during cognitive control. We explored this issue in an fMRI study of the stop signal task, in which participants varied in response time trial by trial, speeding up and risking a stop error or slowing down to avoid errors. Regional brain activations to speeded versus delayed motor responses (risk-taking) were correlated to novelty seeking (NS), harm avoidance (HA) and reward dependence (RD), with age and gender as covariates, in a whole brain regression. At a corrected threshold, the results showed a positive correlation between NS and risk-taking responses in the dorsomedial prefrontal, bilateral orbitofrontal, and frontopolar cortex, and between HA and risk-taking responses in the parahippocampal gyrus and putamen. No regional activations varied with RD. These findings demonstrate that personality traits influence the neural processes of executive control beyond behavioral tasks that involve explicit monetary reward. The results also speak broadly to the importance of characterizing inter-subject variation in studies of cognition and brain functions.

Soft-decision decoding techniques for linear block codes and their error performance analysis

NASA Technical Reports Server (NTRS)

Lin, Shu

1996-01-01

The first paper presents a new minimum-weight trellis-based soft-decision iterative decoding algorithm for binary linear block codes. The second paper derives an upper bound on the probability of block error for multilevel concatenated codes (MLCC). The bound evaluates difference in performance for different decompositions of some codes. The third paper investigates the bit error probability code for maximum likelihood decoding of binary linear codes. The fourth and final paper included in this report is concerns itself with the construction of multilevel concatenated block modulation codes using a multilevel concatenation scheme for the frequency non-selective Rayleigh fading channel.

An Approach for Implementing a Microcomputer Based Report Origination System in the Ada Programming Language

DTIC Science & Technology

1983-03-01

Decision Tree -------------------- 62 4-E. PACKAGE unitrep Action/Area Selection flow Chart 82 4-7. PACKAGE unitrep Control Flow Chart...the originetor wculd manually draft simple, readable, formatted iressages using "-i predef.ined forms and decision logic trees . This alternative was...Study Analysis DATA CCNTENT ERRORS PERCENT OF ERRORS Character Type 2.1 Calcvlations/Associations 14.3 Message Identification 4.? Value Pisiratch 22.E

A selective-update affine projection algorithm with selective input vectors

NASA Astrophysics Data System (ADS)

Kong, NamWoong; Shin, JaeWook; Park, PooGyeon

2011-10-01

This paper proposes an affine projection algorithm (APA) with selective input vectors, which based on the concept of selective-update in order to reduce estimation errors and computations. The algorithm consists of two procedures: input- vector-selection and state-decision. The input-vector-selection procedure determines the number of input vectors by checking with mean square error (MSE) whether the input vectors have enough information for update. The state-decision procedure determines the current state of the adaptive filter by using the state-decision criterion. As the adaptive filter is in transient state, the algorithm updates the filter coefficients with the selected input vectors. On the other hand, as soon as the adaptive filter reaches the steady state, the update procedure is not performed. Through these two procedures, the proposed algorithm achieves small steady-state estimation errors, low computational complexity and low update complexity for colored input signals.

Using Computational Cognitive Modeling to Diagnose Possible Sources of Aviation Error

NASA Technical Reports Server (NTRS)

Byrne, M. D.; Kirlik, Alex

2003-01-01

We present a computational model of a closed-loop, pilot-aircraft-visual scene-taxiway system created to shed light on possible sources of taxi error. Creating the cognitive aspects of the model using ACT-R required us to conduct studies with subject matter experts to identify experiential adaptations pilots bring to taxiing. Five decision strategies were found, ranging from cognitively-intensive but precise, to fast, frugal but robust. We provide evidence for the model by comparing its behavior to a NASA Ames Research Center simulation of Chicago O'Hare surface operations. Decision horizons were highly variable; the model selected the most accurate strategy given time available. We found a signature in the simulation data of the use of globally robust heuristics to cope with short decision horizons as revealed by errors occurring most frequently at atypical taxiway geometries or clearance routes. These data provided empirical support for the model.

Prediction of the compression ratio for municipal solid waste using decision tree.

PubMed

Heshmati R, Ali Akbar; Mokhtari, Maryam; Shakiba Rad, Saeed

2014-01-01

The compression ratio of municipal solid waste (MSW) is an essential parameter for evaluation of waste settlement and landfill design. However, no appropriate model has been proposed to estimate the waste compression ratio so far. In this study, a decision tree method was utilized to predict the waste compression ratio (C'c). The tree was constructed using Quinlan's M5 algorithm. A reliable database retrieved from the literature was used to develop a practical model that relates C'c to waste composition and properties, including dry density, dry weight water content, and percentage of biodegradable organic waste using the decision tree method. The performance of the developed model was examined in terms of different statistical criteria, including correlation coefficient, root mean squared error, mean absolute error and mean bias error, recommended by researchers. The obtained results demonstrate that the suggested model is able to evaluate the compression ratio of MSW effectively.

Information systems and human error in the lab.

PubMed

Bissell, Michael G

2004-01-01

Health system costs in clinical laboratories are incurred daily due to human error. Indeed, a major impetus for automating clinical laboratories has always been the opportunity it presents to simultaneously reduce cost and improve quality of operations by decreasing human error. But merely automating these processes is not enough. To the extent that introduction of these systems results in operators having less practice in dealing with unexpected events or becoming deskilled in problemsolving, however new kinds of error will likely appear. Clinical laboratories could potentially benefit by integrating findings on human error from modern behavioral science into their operations. Fully understanding human error requires a deep understanding of human information processing and cognition. Predicting and preventing negative consequences requires application of this understanding to laboratory operations. Although the occurrence of a particular error at a particular instant cannot be absolutely prevented, human error rates can be reduced. The following principles are key: an understanding of the process of learning in relation to error; understanding the origin of errors since this knowledge can be used to reduce their occurrence; optimal systems should be forgiving to the operator by absorbing errors, at least for a time; although much is known by industrial psychologists about how to write operating procedures and instructions in ways that reduce the probability of error, this expertise is hardly ever put to use in the laboratory; and a feedback mechanism must be designed into the system that enables the operator to recognize in real time that an error has occurred.

Human Research Program Space Human Factors Engineering (SHFE) Standing Review Panel (SRP)

NASA Technical Reports Server (NTRS)

Wichansky, Anna; Badler, Norman; Butler, Keith; Cummings, Mary; DeLucia, Patricia; Endsley, Mica; Scholtz, Jean

2009-01-01

The Space Human Factors Engineering (SHFE) Standing Review Panel (SRP) evaluated 22 gaps and 39 tasks in the three risk areas assigned to the SHFE Project. The area where tasks were best designed to close the gaps and the fewest gaps were left out was the Risk of Reduced Safety and Efficiency dire to Inadequate Design of Vehicle, Environment, Tools or Equipment. The areas where there were more issues with gaps and tasks, including poor or inadequate fit of tasks to gaps and missing gaps, were Risk of Errors due to Poor Task Design and Risk of Error due to Inadequate Information. One risk, the Risk of Errors due to Inappropriate Levels of Trust in Automation, should be added. If astronauts trust automation too much in areas where it should not be trusted, but rather tempered with human judgment and decision making, they will incur errors. Conversely, if they do not trust automation when it should be trusted, as in cases where it can sense aspects of the environment such as radiation levels or distances in space, they will also incur errors. This will be a larger risk when astronauts are less able to rely on human mission control experts and are out of touch, far away, and on their own. The SRP also identified 11 new gaps and five new tasks. Although the SRP had an extremely large quantity of reading material prior to and during the meeting, we still did not feel we had an overview of the activities and tasks the astronauts would be performing in exploration missions. Without a detailed task analysis and taxonomy of activities the humans would be engaged in, we felt it was impossible to know whether the gaps and tasks were really sufficient to insure human safety, performance, and comfort in the exploration missions. The SRP had difficulty evaluating many of the gaps and tasks that were not as quantitative as those related to concrete physical danger such as excessive noise and vibration. Often the research tasks for cognitive risks that accompany poor task or information design addressed only part, but not all, of the gaps they were programmed to fill. In fact the tasks outlined will not close the gap but only scratch the surface in many cases. In other cases, the gap was written too broadly, and really should be restated in a more constrained way that can be addressed by a well-organized and complementary set of tasks. In many cases, the research results should be turned into guidelines for design. However, it was not clear whether the researchers or another group would construct and deliver these guidelines.

Explanation of asymmetric dynamics of human water consumption in arid regions: prospect theory versus expected utility theory

NASA Astrophysics Data System (ADS)

Tian, F.; Lu, Y.

2017-12-01

Based on socioeconomic and hydrological data in three arid inland basins and error analysis, the dynamics of human water consumption (HWC) are analyzed to be asymmetric, i.e., HWC increase rapidly in wet periods while maintain or decrease slightly in dry periods. Besides the qualitative analysis that in wet periods great water availability inspires HWC to grow fast but the now expanded economy is managed to sustain by over-exploitation in dry periods, two quantitative models are established and tested, based on expected utility theory (EUT) and prospect theory (PT) respectively. EUT states that humans make decisions based on the total expected utility, namely the sum of utility function multiplied by probability of each result, while PT states that the utility function is defined over gains and losses separately, and probability should be replaced by probability weighting function.

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.

A forward error correction technique using a high-speed, high-rate single chip codec

NASA Astrophysics Data System (ADS)

Boyd, R. W.; Hartman, W. F.; Jones, Robert E.

The authors describe an error-correction coding approach that allows operation in either burst or continuous modes at data rates of multiple hundreds of megabits per second. Bandspreading is low since the code rate is 7/8 or greater, which is consistent with high-rate link operation. The encoder, along with a hard-decision decoder, fits on a single application-specific integrated circuit (ASIC) chip. Soft-decision decoding is possible utilizing applique hardware in conjunction with the hard-decision decoder. Expected coding gain is a function of the application and is approximately 2.5 dB for hard-decision decoding at 10-5 bit-error rate with phase-shift-keying modulation and additive Gaussian white noise interference. The principal use envisioned for this technique is to achieve a modest amount of coding gain on high-data-rate, bandwidth-constrained channels. Data rates of up to 300 Mb/s can be accommodated by the codec chip. The major objective is burst-mode communications, where code words are composed of 32 n data bits followed by 32 overhead bits.

Dual Processing and Diagnostic Errors

ERIC Educational Resources Information Center

Norman, Geoff

2009-01-01

In this paper, I review evidence from two theories in psychology relevant to diagnosis and diagnostic errors. "Dual Process" theories of thinking, frequently mentioned with respect to diagnostic error, propose that categorization decisions can be made with either a fast, unconscious, contextual process called System 1 or a slow, analytical,…

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

DOE PAGES

Liao, Huafei N.; Groth, Katrina; Stevens-Adams, Susan

2015-07-29

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification aremore » discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.« less

Towards an evaluation framework for Laboratory Information Systems.

PubMed

Yusof, Maryati M; Arifin, Azila

Laboratory testing and reporting are error-prone and redundant due to repeated, unnecessary requests and delayed or missed reactions to laboratory reports. Occurring errors may negatively affect the patient treatment process and clinical decision making. Evaluation on laboratory testing and Laboratory Information System (LIS) may explain the root cause to improve the testing process and enhance LIS in supporting the process. This paper discusses a new evaluation framework for LIS that encompasses the laboratory testing cycle and the socio-technical part of LIS. Literature review on discourses, dimensions and evaluation methods of laboratory testing and LIS. A critical appraisal of the Total Testing Process (TTP) and the human, organization, technology-fit factors (HOT-fit) evaluation frameworks was undertaken in order to identify error incident, its contributing factors and preventive action pertinent to laboratory testing process and LIS. A new evaluation framework for LIS using a comprehensive and socio-technical approach is outlined. Positive relationship between laboratory and clinical staff resulted in a smooth laboratory testing process, reduced errors and increased process efficiency whilst effective use of LIS streamlined the testing processes. The TTP-LIS framework could serve as an assessment as well as a problem-solving tool for the laboratory testing process and system. Copyright © 2016 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

What triggers catch-up saccades during visual tracking?

PubMed

de Brouwer, Sophie; Yuksel, Demet; Blohm, Gunnar; Missal, Marcus; Lefèvre, Philippe

2002-03-01

When tracking moving visual stimuli, primates orient their visual axis by combining two kinds of eye movements, smooth pursuit and saccades, that have very different dynamics. Yet, the mechanisms that govern the decision to switch from one type of eye movement to the other are still poorly understood, even though they could bring a significant contribution to the understanding of how the CNS combines different kinds of control strategies to achieve a common motor and sensory goal. In this study, we investigated the oculomotor responses to a large range of different combinations of position error and velocity error during visual tracking of moving stimuli in humans. We found that the oculomotor system uses a prediction of the time at which the eye trajectory will cross the target, defined as the "eye crossing time" (T(XE)). The eye crossing time, which depends on both position error and velocity error, is the criterion used to switch between smooth and saccadic pursuit, i.e., to trigger catch-up saccades. On average, for T(XE) between 40 and 180 ms, no saccade is triggered and target tracking remains purely smooth. Conversely, when T(XE) becomes smaller than 40 ms or larger than 180 ms, a saccade is triggered after a short latency (around 125 ms).

Stochastic Models of Human Errors

NASA Technical Reports Server (NTRS)

Elshamy, Maged; Elliott, Dawn M. (Technical Monitor)

2002-01-01

Humans play an important role in the overall reliability of engineering systems. More often accidents and systems failure are traced to human errors. Therefore, in order to have meaningful system risk analysis, the reliability of the human element must be taken into consideration. Describing the human error process by mathematical models is a key to analyzing contributing factors. Therefore, the objective of this research effort is to establish stochastic models substantiated by sound theoretic foundation to address the occurrence of human errors in the processing of the space shuttle.

Operational Interventions to Maintenance Error

NASA Technical Reports Server (NTRS)

Kanki, Barbara G.; Walter, Diane; Dulchinos, VIcki

1997-01-01

A significant proportion of aviation accidents and incidents are known to be tied to human error. However, research of flight operational errors has shown that so-called pilot error often involves a variety of human factors issues and not a simple lack of individual technical skills. In aircraft maintenance operations, there is similar concern that maintenance errors which may lead to incidents and accidents are related to a large variety of human factors issues. Although maintenance error data and research are limited, industry initiatives involving human factors training in maintenance have become increasingly accepted as one type of maintenance error intervention. Conscientious efforts have been made in re-inventing the team7 concept for maintenance operations and in tailoring programs to fit the needs of technical opeRAtions. Nevertheless, there remains a dual challenge: 1) to develop human factors interventions which are directly supported by reliable human error data, and 2) to integrate human factors concepts into the procedures and practices of everyday technical tasks. In this paper, we describe several varieties of human factors interventions and focus on two specific alternatives which target problems related to procedures and practices; namely, 1) structured on-the-job training and 2) procedure re-design. We hope to demonstrate that the key to leveraging the impact of these solutions comes from focused interventions; that is, interventions which are derived from a clear understanding of specific maintenance errors, their operational context and human factors components.

Reduction of Maintenance Error Through Focused Interventions

NASA Technical Reports Server (NTRS)

Kanki, Barbara G.; Walter, Diane; Rosekind, Mark R. (Technical Monitor)

1997-01-01

It is well known that a significant proportion of aviation accidents and incidents are tied to human error. In flight operations, research of operational errors has shown that so-called "pilot error" often involves a variety of human factors issues and not a simple lack of individual technical skills. In aircraft maintenance operations, there is similar concern that maintenance errors which may lead to incidents and accidents are related to a large variety of human factors issues. Although maintenance error data and research are limited, industry initiatives involving human factors training in maintenance have become increasingly accepted as one type of maintenance error intervention. Conscientious efforts have been made in re-inventing the "team" concept for maintenance operations and in tailoring programs to fit the needs of technical operations. Nevertheless, there remains a dual challenge: to develop human factors interventions which are directly supported by reliable human error data, and to integrate human factors concepts into the procedures and practices of everyday technical tasks. In this paper, we describe several varieties of human factors interventions and focus on two specific alternatives which target problems related to procedures and practices; namely, 1) structured on-the-job training and 2) procedure re-design. We hope to demonstrate that the key to leveraging the impact of these solutions comes from focused interventions; that is, interventions which are derived from a clear understanding of specific maintenance errors, their operational context and human factors components.

Human substantia nigra and ventral tegmental area involvement in computing social error signals during the ultimatum game

PubMed Central

Hétu, Sébastien; Luo, Yi; D’Ardenne, Kimberlee; Lohrenz, Terry

2017-01-01

Abstract As models of shared expectations, social norms play an essential role in our societies. Since our social environment is changing constantly, our internal models of it also need to change. In humans, there is mounting evidence that neural structures such as the insula and the ventral striatum are involved in detecting norm violation and updating internal models. However, because of methodological challenges, little is known about the possible involvement of midbrain structures in detecting norm violation and updating internal models of our norms. Here, we used high-resolution cardiac-gated functional magnetic resonance imaging and a norm adaptation paradigm in healthy adults to investigate the role of the substantia nigra/ventral tegmental area (SN/VTA) complex in tracking signals related to norm violation that can be used to update internal norms. We show that the SN/VTA codes for the norm’s variance prediction error (PE) and norm PE with spatially distinct regions coding for negative and positive norm PE. These results point to a common role played by the SN/VTA complex in supporting both simple reward-based and social decision making. PMID:28981876

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,…

Human Factors Process Task Analysis: Liquid Oxygen Pump Acceptance Test Procedure at the Advanced Technology Development Center

NASA Technical Reports Server (NTRS)

Diorio, Kimberly A.; Voska, Ned (Technical Monitor)

2002-01-01

This viewgraph presentation provides information on Human Factors Process Failure Modes and Effects Analysis (HF PFMEA). HF PFMEA includes the following 10 steps: Describe mission; Define System; Identify human-machine; List human actions; Identify potential errors; Identify factors that effect error; Determine likelihood of error; Determine potential effects of errors; Evaluate risk; Generate solutions (manage error). The presentation also describes how this analysis was applied to a liquid oxygen pump acceptance test.

A theory of human error

NASA Technical Reports Server (NTRS)

Mcruer, D. T.; Clement, W. F.; Allen, R. W.

1981-01-01

Human errors tend to be treated in terms of clinical and anecdotal descriptions, from which remedial measures are difficult to derive. Correction of the sources of human error requires an attempt to reconstruct underlying and contributing causes of error from the circumstantial causes cited in official investigative reports. A comprehensive analytical theory of the cause-effect relationships governing propagation of human error is indispensable to a reconstruction of the underlying and contributing causes. A validated analytical theory of the input-output behavior of human operators involving manual control, communication, supervisory, and monitoring tasks which are relevant to aviation, maritime, automotive, and process control operations is highlighted. This theory of behavior, both appropriate and inappropriate, provides an insightful basis for investigating, classifying, and quantifying the needed cause-effect relationships governing propagation of human error.

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…

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...

The contributions of human factors on human error in Malaysia aviation maintenance industries

NASA Astrophysics Data System (ADS)

Padil, H.; Said, M. N.; Azizan, A.

2018-05-01

Aviation maintenance is a multitasking activity in which individuals perform varied tasks under constant pressure to meet deadlines as well as challenging work conditions. These situational characteristics combined with human factors can lead to various types of human related errors. The primary objective of this research is to develop a structural relationship model that incorporates human factors, organizational factors, and their impact on human errors in aviation maintenance. Towards that end, a questionnaire was developed which was administered to Malaysian aviation maintenance professionals. Structural Equation Modelling (SEM) approach was used in this study utilizing AMOS software. Results showed that there were a significant relationship of human factors on human errors and were tested in the model. Human factors had a partial effect on organizational factors while organizational factors had a direct and positive impact on human errors. It was also revealed that organizational factors contributed to human errors when coupled with human factors construct. This study has contributed to the advancement of knowledge on human factors effecting safety and has provided guidelines for improving human factors performance relating to aviation maintenance activities and could be used as a reference for improving safety performance in the Malaysian aviation maintenance companies.

Decision theory, motor planning, and visual memory: deciding where to reach when memory errors are costly.

PubMed

Lerch, Rachel A; Sims, Chris R

2016-06-01

Limitations in visual working memory (VWM) have been extensively studied in psychophysical tasks, but not well understood in terms of how these memory limits translate to performance in more natural domains. For example, in reaching to grasp an object based on a spatial memory representation, overshooting the intended target may be more costly than undershooting, such as when reaching for a cup of hot coffee. The current body of literature lacks a detailed account of how the costs or consequences of memory error influence what we encode in visual memory and how we act on the basis of remembered information. Here, we study how externally imposed monetary costs influence behavior in a motor decision task that involves reach planning based on recalled information from VWM. We approach this from a decision theoretic perspective, viewing decisions of where to aim in relation to the utility of their outcomes given the uncertainty of memory representations. Our results indicate that subjects accounted for the uncertainty in their visual memory, showing a significant difference in their reach planning when monetary costs were imposed for memory errors. However, our findings indicate that subjects memory representations per se were not biased by the imposed costs, but rather subjects adopted a near-optimal post-mnemonic decision strategy in their motor planning.

A theory of human error

NASA Technical Reports Server (NTRS)

Mcruer, D. T.; Clement, W. F.; Allen, R. W.

1980-01-01

Human error, a significant contributing factor in a very high proportion of civil transport, general aviation, and rotorcraft accidents is investigated. Correction of the sources of human error requires that one attempt to reconstruct underlying and contributing causes of error from the circumstantial causes cited in official investigative reports. A validated analytical theory of the input-output behavior of human operators involving manual control, communication, supervisory, and monitoring tasks which are relevant to aviation operations is presented. This theory of behavior, both appropriate and inappropriate, provides an insightful basis for investigating, classifying, and quantifying the needed cause-effect relationships governing propagation of human error.

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.

Human Reliability and the Cost of Doing Business

NASA Technical Reports Server (NTRS)

DeMott, Diana

2014-01-01

Most businesses recognize that people will make mistakes and assume errors are just part of the cost of doing business, but does it need to be? Companies with high risk, or major consequences, should consider the effect of human error. In a variety of industries, Human Errors have caused costly failures and workplace injuries. These have included: airline mishaps, medical malpractice, administration of medication and major oil spills have all been blamed on human error. A technique to mitigate or even eliminate some of these costly human errors is the use of Human Reliability Analysis (HRA). Various methodologies are available to perform Human Reliability Assessments that range from identifying the most likely areas for concern to detailed assessments with human error failure probabilities calculated. Which methodology to use would be based on a variety of factors that would include: 1) how people react and act in different industries, and differing expectations based on industries standards, 2) factors that influence how the human errors could occur such as tasks, tools, environment, workplace, support, training and procedure, 3) type and availability of data and 4) how the industry views risk & reliability influences ( types of emergencies, contingencies and routine tasks versus cost based concerns). The Human Reliability Assessments should be the first step to reduce, mitigate or eliminate the costly mistakes or catastrophic failures. Using Human Reliability techniques to identify and classify human error risks allows a company more opportunities to mitigate or eliminate these risks and prevent costly failures.

Human reinforcement learning subdivides structured action spaces by learning effector-specific values

PubMed Central

Gershman, Samuel J.; Pesaran, Bijan; Daw, Nathaniel D.

2009-01-01

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable, due to the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning – such as prediction error signals for action valuation associated with dopamine and the striatum – can cope with this “curse of dimensionality.” We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and BOLD activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to “divide and conquer” reinforcement learning over high-dimensional action spaces. PMID:19864565

Human reinforcement learning subdivides structured action spaces by learning effector-specific values.

PubMed

Gershman, Samuel J; Pesaran, Bijan; Daw, Nathaniel D

2009-10-28

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable because of the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning-such as prediction error signals for action valuation associated with dopamine and the striatum-can cope with this "curse of dimensionality." We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and blood oxygen level-dependent (BOLD) activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to "divide and conquer" reinforcement learning over high-dimensional action spaces.

Human Reliability and the Cost of Doing Business

NASA Technical Reports Server (NTRS)

DeMott, D. L.

2014-01-01

Human error cannot be defined unambiguously in advance of it happening, it often becomes an error after the fact. The same action can result in a tragic accident for one situation or a heroic action given a more favorable outcome. People often forget that we employ humans in business and industry for the flexibility and capability to change when needed. In complex systems, operations are driven by their specifications of the system and the system structure. People provide the flexibility to make it work. Human error has been reported as being responsible for 60%-80% of failures, accidents and incidents in high-risk industries. We don't have to accept that all human errors are inevitable. Through the use of some basic techniques, many potential human error events can be addressed. There are actions that can be taken to reduce the risk of human error.

Comparative study of multimodal biometric recognition by fusion of iris and fingerprint.

PubMed

Benaliouche, Houda; Touahria, Mohamed

2014-01-01

This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

Comparative Study of Multimodal Biometric Recognition by Fusion of Iris and Fingerprint

PubMed Central

Benaliouche, Houda; Touahria, Mohamed

2014-01-01

This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results. PMID:24605065

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.

Compact disk error measurements

NASA Technical Reports Server (NTRS)

Howe, D.; Harriman, K.; Tehranchi, B.

1993-01-01

The objectives of this project are as follows: provide hardware and software that will perform simple, real-time, high resolution (single-byte) measurement of the error burst and good data gap statistics seen by a photoCD player read channel when recorded CD write-once discs of variable quality (i.e., condition) are being read; extend the above system to enable measurement of the hard decision (i.e., 1-bit error flags) and soft decision (i.e., 2-bit error flags) decoding information that is produced/used by the Cross Interleaved - Reed - Solomon - Code (CIRC) block decoder employed in the photoCD player read channel; construct a model that uses data obtained via the systems described above to produce meaningful estimates of output error rates (due to both uncorrected ECC words and misdecoded ECC words) when a CD disc having specific (measured) error statistics is read (completion date to be determined); and check the hypothesis that current adaptive CIRC block decoders are optimized for pressed (DAD/ROM) CD discs. If warranted, do a conceptual design of an adaptive CIRC decoder that is optimized for write-once CD discs.

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

Human Error Analysis in a Permit to Work System: A Case Study in a Chemical Plant

PubMed Central

Jahangiri, Mehdi; Hoboubi, Naser; Rostamabadi, Akbar; Keshavarzi, Sareh; Hosseini, Ali Akbar

2015-01-01

Background A permit to work (PTW) is a formal written system to control certain types of work which are identified as potentially hazardous. However, human error in PTW processes can lead to an accident. Methods This cross-sectional, descriptive study was conducted to estimate the probability of human errors in PTW processes in a chemical plant in Iran. In the first stage, through interviewing the personnel and studying the procedure in the plant, the PTW process was analyzed using the hierarchical task analysis technique. In doing so, PTW was considered as a goal and detailed tasks to achieve the goal were analyzed. In the next step, the standardized plant analysis risk-human (SPAR-H) reliability analysis method was applied for estimation of human error probability. Results The mean probability of human error in the PTW system was estimated to be 0.11. The highest probability of human error in the PTW process was related to flammable gas testing (50.7%). Conclusion The SPAR-H method applied in this study could analyze and quantify the potential human errors and extract the required measures for reducing the error probabilities in PTW system. Some suggestions to reduce the likelihood of errors, especially in the field of modifying the performance shaping factors and dependencies among tasks are provided. PMID:27014485

Separate neural representations of prediction error valence and surprise: Evidence from an fMRI meta-analysis.

PubMed

Fouragnan, Elsa; Retzler, Chris; Philiastides, Marios G

2018-03-25

Learning occurs when an outcome differs from expectations, generating a reward prediction error signal (RPE). The RPE signal has been hypothesized to simultaneously embody the valence of an outcome (better or worse than expected) and its surprise (how far from expectations). Nonetheless, growing evidence suggests that separate representations of the two RPE components exist in the human brain. Meta-analyses provide an opportunity to test this hypothesis and directly probe the extent to which the valence and surprise of the error signal are encoded in separate or overlapping networks. We carried out several meta-analyses on a large set of fMRI studies investigating the neural basis of RPE, locked at decision outcome. We identified two valence learning systems by pooling studies searching for differential neural activity in response to categorical positive-versus-negative outcomes. The first valence network (negative > positive) involved areas regulating alertness and switching behaviours such as the midcingulate cortex, the thalamus and the dorsolateral prefrontal cortex whereas the second valence network (positive > negative) encompassed regions of the human reward circuitry such as the ventral striatum and the ventromedial prefrontal cortex. We also found evidence of a largely distinct surprise-encoding network including the anterior cingulate cortex, anterior insula and dorsal striatum. Together with recent animal and electrophysiological evidence this meta-analysis points to a sequential and distributed encoding of different components of the RPE signal, with potentially distinct functional roles. © 2018 Wiley Periodicals, Inc.

Managing human fallibility in critical aerospace situations

NASA Astrophysics Data System (ADS)

Tew, Larry

2014-11-01

Human fallibility is pervasive in the aerospace industry with over 50% of errors attributed to human error. Consider the benefits to any organization if those errors were significantly reduced. Aerospace manufacturing involves high value, high profile systems with significant complexity and often repetitive build, assembly, and test operations. In spite of extensive analysis, planning, training, and detailed procedures, human factors can cause unexpected errors. Handling such errors involves extensive cause and corrective action analysis and invariably schedule slips and cost growth. We will discuss success stories, including those associated with electro-optical systems, where very significant reductions in human fallibility errors were achieved after receiving adapted and specialized training. In the eyes of company and customer leadership, the steps used to achieve these results lead to in a major culture change in both the workforce and the supporting management organization. This approach has proven effective in other industries like medicine, firefighting, law enforcement, and aviation. The roadmap to success and the steps to minimize human error are known. They can be used by any organization willing to accept human fallibility and take a proactive approach to incorporate the steps needed to manage and minimize error.

Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123

Defining the Relationship Between Human Error Classes and Technology Intervention Strategies

NASA Technical Reports Server (NTRS)

Wiegmann, Douglas A.; Rantanen, Eas M.

2003-01-01

The modus operandi in addressing human error in aviation systems is predominantly that of technological interventions or fixes. Such interventions exhibit considerable variability both in terms of sophistication and application. Some technological interventions address human error directly while others do so only indirectly. Some attempt to eliminate the occurrence of errors altogether whereas others look to reduce the negative consequences of these errors. In any case, technological interventions add to the complexity of the systems and may interact with other system components in unforeseeable ways and often create opportunities for novel human errors. Consequently, there is a need to develop standards for evaluating the potential safety benefit of each of these intervention products so that resources can be effectively invested to produce the biggest benefit to flight safety as well as to mitigate any adverse ramifications. The purpose of this project was to help define the relationship between human error and technological interventions, with the ultimate goal of developing a set of standards for evaluating or measuring the potential benefits of new human error fixes.

Applying lessons learned to enhance human performance and reduce human error for ISS operations

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

Nelson, W.R.

1999-01-01

A major component of reliability, safety, and mission success for space missions is ensuring that the humans involved (flight crew, ground crew, mission control, etc.) perform their tasks and functions as required. This includes compliance with training and procedures during normal conditions, and successful compensation when malfunctions or unexpected conditions occur. A very significant issue that affects human performance in space flight is human error. Human errors can invalidate carefully designed equipment and procedures. If certain errors combine with equipment failures or design flaws, mission failure or loss of life can occur. The control of human error during operation ofmore » the International Space Station (ISS) will be critical to the overall success of the program. As experience from Mir operations has shown, human performance plays a vital role in the success or failure of long duration space missions. The Department of Energy{close_quote}s Idaho National Engineering and Environmental Laboratory (INEEL) is developing a systematic approach to enhance human performance and reduce human errors for ISS operations. This approach is based on the systematic identification and evaluation of lessons learned from past space missions such as Mir to enhance the design and operation of ISS. This paper will describe previous INEEL research on human error sponsored by NASA and how it can be applied to enhance human reliability for ISS. {copyright} {ital 1999 American Institute of Physics.}« less

Applying lessons learned to enhance human performance and reduce human error for ISS operations

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

Nelson, W.R.

1998-09-01

A major component of reliability, safety, and mission success for space missions is ensuring that the humans involved (flight crew, ground crew, mission control, etc.) perform their tasks and functions as required. This includes compliance with training and procedures during normal conditions, and successful compensation when malfunctions or unexpected conditions occur. A very significant issue that affects human performance in space flight is human error. Human errors can invalidate carefully designed equipment and procedures. If certain errors combine with equipment failures or design flaws, mission failure or loss of life can occur. The control of human error during operation ofmore » the International Space Station (ISS) will be critical to the overall success of the program. As experience from Mir operations has shown, human performance plays a vital role in the success or failure of long duration space missions. The Department of Energy`s Idaho National Engineering and Environmental Laboratory (INEEL) is developed a systematic approach to enhance human performance and reduce human errors for ISS operations. This approach is based on the systematic identification and evaluation of lessons learned from past space missions such as Mir to enhance the design and operation of ISS. This paper describes previous INEEL research on human error sponsored by NASA and how it can be applied to enhance human reliability for ISS.« less

Wings: A New Paradigm in Human-Centered Design

NASA Technical Reports Server (NTRS)

Schutte, Paul C.

1997-01-01

Many aircraft accidents/incidents investigations cite crew error as a causal factor (Boeing Commercial Airplane Group 1996). Human factors experts suggest that crew error has many underlying causes and should be the start of an accident investigation and not the end. One of those causes, the flight deck design, is correctable. If a flight deck design does not accommodate the human's unique abilities and deficits, crew error may simply be the manifestation of this mismatch. Pilots repeatedly report that they are "behind the aircraft" , i.e., they do not know what the automated aircraft is doing or how the aircraft is doing it until after the fact. Billings (1991) promotes the concept of "human-centered automation"; calling on designers to allocate appropriate control and information to the human. However, there is much ambiguity regarding what it mean's to be human-centered. What often are labeled as "human-centered designs" are actually designs where a human factors expert has been involved in the design process or designs where tests have shown that humans can operate them. While such designs may be excellent, they do not represent designs that are systematically produced according to some set of prescribed methods and procedures. This paper describes a design concept, called Wings, that offers a clearer definition for human-centered design. This new design concept is radically different from current design processes in that the design begins with the human and uses the human body as a metaphor for designing the aircraft. This is not because the human is the most important part of the aircraft (certainly the aircraft would be useless without lift and thrust), but because he is the least understood, the least programmable, and one of the more critical elements. The Wings design concept has three properties: a reversal in the design process, from aerodynamics-, structures-, and propulsion-centered to truly human-centered; a design metaphor that guides function allocation and control and display design; and a deliberate distinction between two fundamental functions of design, to complement and to interpret human performance. The complementary function extends the human's capabilities beyond his or her current limitations - this includes sensing, computation, memory, physical force, and human decision making styles and skills. The interpretive (or hermeneutic, Hollnagel 1991) function translates information, functionality, and commands between the human and the aircraft. The Wings design concept allows the human to remain aware of the aircraft through natural interpretation. It also affords great improvements in system performance by maximizing the human's natural abilities and complementing the human's skills in a natural way. This paper will discuss the Wings design concept by describing the reversal in the traditional design process, the function allocation strategy of Wings, and the functions of complementing and interpreting the human.

Structured methods for identifying and correcting potential human errors in aviation operations

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

Nelson, W.R.

1997-10-01

Human errors have been identified as the source of approximately 60% of the incidents and accidents that occur in commercial aviation. It can be assumed that a very large number of human errors occur in aviation operations, even though in most cases the redundancies and diversities built into the design of aircraft systems prevent the errors from leading to serious consequences. In addition, when it is acknowledged that many system failures have their roots in human errors that occur in the design phase, it becomes apparent that the identification and elimination of potential human errors could significantly decrease the risksmore » of aviation operations. This will become even more critical during the design of advanced automation-based aircraft systems as well as next-generation systems for air traffic management. Structured methods to identify and correct potential human errors in aviation operations have been developed and are currently undergoing testing at the Idaho National Engineering and Environmental Laboratory (INEEL).« less

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)…

Human errors and violations in computer and information security: the viewpoint of network administrators and security specialists.

PubMed

Kraemer, Sara; Carayon, Pascale

2007-03-01

This paper describes human errors and violations of end users and network administration in computer and information security. This information is summarized in a conceptual framework for examining the human and organizational factors contributing to computer and information security. This framework includes human error taxonomies to describe the work conditions that contribute adversely to computer and information security, i.e. to security vulnerabilities and breaches. The issue of human error and violation in computer and information security was explored through a series of 16 interviews with network administrators and security specialists. The interviews were audio taped, transcribed, and analyzed by coding specific themes in a node structure. The result is an expanded framework that classifies types of human error and identifies specific human and organizational factors that contribute to computer and information security. Network administrators tended to view errors created by end users as more intentional than unintentional, while errors created by network administrators as more unintentional than intentional. Organizational factors, such as communication, security culture, policy, and organizational structure, were the most frequently cited factors associated with computer and information security.

Intervention strategies for the management of human error

NASA Technical Reports Server (NTRS)

Wiener, Earl L.

1993-01-01

This report examines the management of human error in the cockpit. The principles probably apply as well to other applications in the aviation realm (e.g. air traffic control, dispatch, weather, etc.) as well as other high-risk systems outside of aviation (e.g. shipping, high-technology medical procedures, military operations, nuclear power production). Management of human error is distinguished from error prevention. It is a more encompassing term, which includes not only the prevention of error, but also a means of disallowing an error, once made, from adversely affecting system output. Such techniques include: traditional human factors engineering, improvement of feedback and feedforward of information from system to crew, 'error-evident' displays which make erroneous input more obvious to the crew, trapping of errors within a system, goal-sharing between humans and machines (also called 'intent-driven' systems), paperwork management, and behaviorally based approaches, including procedures, standardization, checklist design, training, cockpit resource management, etc. Fifteen guidelines for the design and implementation of intervention strategies are included.

Bayesian network models for error detection in radiotherapy plans

NASA Astrophysics Data System (ADS)

Kalet, Alan M.; Gennari, John H.; Ford, Eric C.; Phillips, Mark H.

2015-04-01

The purpose of this study is to design and develop a probabilistic network for detecting errors in radiotherapy plans for use at the time of initial plan verification. Our group has initiated a multi-pronged approach to reduce these errors. We report on our development of Bayesian models of radiotherapy plans. Bayesian networks consist of joint probability distributions that define the probability of one event, given some set of other known information. Using the networks, we find the probability of obtaining certain radiotherapy parameters, given a set of initial clinical information. A low probability in a propagated network then corresponds to potential errors to be flagged for investigation. To build our networks we first interviewed medical physicists and other domain experts to identify the relevant radiotherapy concepts and their associated interdependencies and to construct a network topology. Next, to populate the network’s conditional probability tables, we used the Hugin Expert software to learn parameter distributions from a subset of de-identified data derived from a radiation oncology based clinical information database system. These data represent 4990 unique prescription cases over a 5 year period. Under test case scenarios with approximately 1.5% introduced error rates, network performance produced areas under the ROC curve of 0.88, 0.98, and 0.89 for the lung, brain and female breast cancer error detection networks, respectively. Comparison of the brain network to human experts performance (AUC of 0.90 ± 0.01) shows the Bayes network model performs better than domain experts under the same test conditions. Our results demonstrate the feasibility and effectiveness of comprehensive probabilistic models as part of decision support systems for improved detection of errors in initial radiotherapy plan verification procedures.

Estimating the designated use attainment decision error rates of US Environmental Protection Agency's proposed numeric total phosphorus criteria for Florida, USA, colored lakes.

PubMed

McLaughlin, Douglas B

2012-01-01

The utility of numeric nutrient criteria established for certain surface waters is likely to be affected by the uncertainty that exists in the presence of a causal link between nutrient stressor variables and designated use-related biological responses in those waters. This uncertainty can be difficult to characterize, interpret, and communicate to a broad audience of environmental stakeholders. The US Environmental Protection Agency (USEPA) has developed a systematic planning process to support a variety of environmental decisions, but this process is not generally applied to the development of national or state-level numeric nutrient criteria. This article describes a method for implementing such an approach and uses it to evaluate the numeric total P criteria recently proposed by USEPA for colored lakes in Florida, USA. An empirical, log-linear relationship between geometric mean concentrations of total P (a potential stressor variable) and chlorophyll a (a nutrient-related response variable) in these lakes-that is assumed to be causal in nature-forms the basis for the analysis. The use of the geometric mean total P concentration of a lake to correctly indicate designated use status, defined in terms of a 20 µg/L geometric mean chlorophyll a threshold, is evaluated. Rates of decision errors analogous to the Type I and Type II error rates familiar in hypothesis testing, and a 3rd error rate, E(ni) , referred to as the nutrient criterion-based impairment error rate, are estimated. The results show that USEPA's proposed "baseline" and "modified" nutrient criteria approach, in which data on both total P and chlorophyll a may be considered in establishing numeric nutrient criteria for a given lake within a specified range, provides a means for balancing and minimizing designated use attainment decision errors. Copyright © 2011 SETAC.

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

Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

2015-01-01

Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

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.

Medial prefrontal cortex and the adaptive regulation of reinforcement learning parameters.

PubMed

Khamassi, Mehdi; Enel, Pierre; Dominey, Peter Ford; Procyk, Emmanuel

2013-01-01

Converging evidence suggest that the medial prefrontal cortex (MPFC) is involved in feedback categorization, performance monitoring, and task monitoring, and may contribute to the online regulation of reinforcement learning (RL) parameters that would affect decision-making processes in the lateral prefrontal cortex (LPFC). Previous neurophysiological experiments have shown MPFC activities encoding error likelihood, uncertainty, reward volatility, as well as neural responses categorizing different types of feedback, for instance, distinguishing between choice errors and execution errors. Rushworth and colleagues have proposed that the involvement of MPFC in tracking the volatility of the task could contribute to the regulation of one of RL parameters called the learning rate. We extend this hypothesis by proposing that MPFC could contribute to the regulation of other RL parameters such as the exploration rate and default action values in case of task shifts. Here, we analyze the sensitivity to RL parameters of behavioral performance in two monkey decision-making tasks, one with a deterministic reward schedule and the other with a stochastic one. We show that there exist optimal parameter values specific to each of these tasks, that need to be found for optimal performance and that are usually hand-tuned in computational models. In contrast, automatic online regulation of these parameters using some heuristics can help producing a good, although non-optimal, behavioral performance in each task. We finally describe our computational model of MPFC-LPFC interaction used for online regulation of the exploration rate and its application to a human-robot interaction scenario. There, unexpected uncertainties are produced by the human introducing cued task changes or by cheating. The model enables the robot to autonomously learn to reset exploration in response to such uncertain cues and events. The combined results provide concrete evidence specifying how prefrontal cortical subregions may cooperate to regulate RL parameters. It also shows how such neurophysiologically inspired mechanisms can control advanced robots in the real world. Finally, the model's learning mechanisms that were challenged in the last robotic scenario provide testable predictions on the way monkeys may learn the structure of the task during the pretraining phase of the previous laboratory experiments. Copyright © 2013 Elsevier B.V. All rights reserved.

Exploring Reactions to Pilot Reliability Certification and Changing Attitudes on the Reduction of Errors

ERIC Educational Resources Information Center

Boedigheimer, Dan

2010-01-01

Approximately 70% of aviation accidents are attributable to human error. The greatest opportunity for further improving aviation safety is found in reducing human errors in the cockpit. The purpose of this quasi-experimental, mixed-method research was to evaluate whether there was a difference in pilot attitudes toward reducing human error in the…

Graduate Students' Administration and Scoring Errors on the Woodcock-Johnson III Tests of Cognitive Abilities

ERIC Educational Resources Information Center

Ramos, Erica; Alfonso, Vincent C.; Schermerhorn, Susan M.

2009-01-01

The interpretation of cognitive test scores often leads to decisions concerning the diagnosis, educational placement, and types of interventions used for children. Therefore, it is important that practitioners administer and score cognitive tests without error. This study assesses the frequency and types of examiner errors that occur during the…

Evaluating a medical error taxonomy.

PubMed

Brixey, Juliana; Johnson, Todd R; Zhang, Jiajie

2002-01-01

Healthcare has been slow in using human factors principles to reduce medical errors. The Center for Devices and Radiological Health (CDRH) recognizes that a lack of attention to human factors during product development may lead to errors that have the potential for patient injury, or even death. In response to the need for reducing medication errors, the National Coordinating Council for Medication Errors Reporting and Prevention (NCC MERP) released the NCC MERP taxonomy that provides a standard language for reporting medication errors. This project maps the NCC MERP taxonomy of medication error to MedWatch medical errors involving infusion pumps. Of particular interest are human factors associated with medical device errors. The NCC MERP taxonomy of medication errors is limited in mapping information from MEDWATCH because of the focus on the medical device and the format of reporting.

An Evaluation of Departmental Radiation Oncology Incident Reports: Anticipating a National Reporting System

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

Terezakis, Stephanie A., E-mail: stereza1@jhmi.edu; Harris, Kendra M.; Ford, Eric

Purpose: Systems to ensure patient safety are of critical importance. The electronic incident reporting systems (IRS) of 2 large academic radiation oncology departments were evaluated for events that may be suitable for submission to a national reporting system (NRS). Methods and Materials: All events recorded in the combined IRS were evaluated from 2007 through 2010. Incidents were graded for potential severity using the validated French Nuclear Safety Authority (ASN) 5-point scale. These incidents were categorized into 7 groups: (1) human error, (2) software error, (3) hardware error, (4) error in communication between 2 humans, (5) error at the human-software interface,more » (6) error at the software-hardware interface, and (7) error at the human-hardware interface. Results: Between the 2 systems, 4407 incidents were reported. Of these events, 1507 (34%) were considered to have the potential for clinical consequences. Of these 1507 events, 149 (10%) were rated as having a potential severity of ≥2. Of these 149 events, the committee determined that 79 (53%) of these events would be submittable to a NRS of which the majority was related to human error or to the human-software interface. Conclusions: A significant number of incidents were identified in this analysis. The majority of events in this study were related to human error and to the human-software interface, further supporting the need for a NRS to facilitate field-wide learning and system improvement.« less

Effects of Shame and Guilt on Error Reporting Among Obstetric Clinicians.

PubMed

Zabari, Mara Lynne; Southern, Nancy L

2018-04-17

To understand how the experiences of shame and guilt, coupled with organizational factors, affect error reporting by obstetric clinicians. Descriptive cross-sectional. A sample of 84 obstetric clinicians from three maternity units in Washington State. In this quantitative inquiry, a variant of the Test of Self-Conscious Affect was used to measure proneness to guilt and shame. In addition, we developed questions to assess attitudes regarding concerns about damaging one's reputation if an error was reported and the choice to keep an error to oneself. Both assessments were analyzed separately and then correlated to identify relationships between constructs. Interviews were used to identify organizational factors that affect error reporting. As a group, mean scores indicated that obstetric clinicians would not choose to keep errors to themselves. However, bivariate correlations showed that proneness to shame was positively correlated to concerns about one's reputation if an error was reported, and proneness to guilt was negatively correlated with keeping errors to oneself. Interview data analysis showed that Past Experience with Responses to Errors, Management and Leadership Styles, Professional Hierarchy, and Relationships With Colleagues were influential factors in error reporting. Although obstetric clinicians want to report errors, their decisions to report are influenced by their proneness to guilt and shame and perceptions of the degree to which organizational factors facilitate or create barriers to restore their self-images. Findings underscore the influence of the organizational context on clinicians' decisions to report errors. Copyright © 2018 AWHONN, the Association of Women’s Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.

Sleep quality, posttraumatic stress, depression, and human errors in train drivers: a population-based nationwide study in South Korea.

PubMed

Jeon, Hong Jin; Kim, Ji-Hae; Kim, Bin-Na; Park, Seung Jin; Fava, Maurizio; Mischoulon, David; Kang, Eun-Ho; Roh, Sungwon; Lee, Dongsoo

2014-12-01

Human error is defined as an unintended error that is attributable to humans rather than machines, and that is important to avoid to prevent accidents. We aimed to investigate the association between sleep quality and human errors among train drivers. Cross-sectional. Population-based. A sample of 5,480 subjects who were actively working as train drivers were recruited in South Korea. The participants were 4,634 drivers who completed all questionnaires (response rate 84.6%). None. The Pittsburgh Sleep Quality Index (PSQI), the Center for Epidemiologic Studies Depression Scale (CES-D), the Impact of Event Scale-Revised (IES-R), the State-Trait Anxiety Inventory (STAI), and the Korean Occupational Stress Scale (KOSS). Of 4,634 train drivers, 349 (7.5%) showed more than one human error per 5 y. Human errors were associated with poor sleep quality, higher PSQI total scores, short sleep duration at night, and longer sleep latency. Among train drivers with poor sleep quality, those who experienced severe posttraumatic stress showed a significantly higher number of human errors than those without. Multiple logistic regression analysis showed that human errors were significantly associated with poor sleep quality and posttraumatic stress, whereas there were no significant associations with depression, trait and state anxiety, and work stress after adjusting for age, sex, education years, marital status, and career duration. Poor sleep quality was found to be associated with more human errors in train drivers, especially in those who experienced severe posttraumatic stress. © 2014 Associated Professional Sleep Societies, LLC.

Simplifying and upscaling water resources systems models that combine natural and engineered components

NASA Astrophysics Data System (ADS)

McIntyre, N.; Keir, G.

2014-12-01

Water supply systems typically encompass components of both natural systems (e.g. catchment runoff, aquifer interception) and engineered systems (e.g. process equipment, water storages and transfers). Many physical processes of varying spatial and temporal scales are contained within these hybrid systems models. The need to aggregate and simplify system components has been recognised for reasons of parsimony and comprehensibility; and the use of probabilistic methods for modelling water-related risks also prompts the need to seek computationally efficient up-scaled conceptualisations. How to manage the up-scaling errors in such hybrid systems models has not been well-explored, compared to research in the hydrological process domain. Particular challenges include the non-linearity introduced by decision thresholds and non-linear relations between water use, water quality, and discharge strategies. Using a case study of a mining region, we explore the nature of up-scaling errors in water use, water quality and discharge, and we illustrate an approach to identification of a scale-adjusted model including an error model. Ways forward for efficient modelling of such complex, hybrid systems are discussed, including interactions with human, energy and carbon systems models.

The Cognitive Challenges of Flying a Remotely Piloted Aircraft

NASA Technical Reports Server (NTRS)

Hobbs, Alan; Cardoza, Colleen; Null, Cynthia

2016-01-01

A large variety of Remotely Piloted Aircraft (RPA) designs are currently in production or in development. These aircraft range from small electric quadcopters that are flown close to the ground within visual range of the operator, to larger systems capable of extended flight in airspace shared with conventional aircraft. Before RPA can operate routinely and safely in civilian airspace, we need to understand the unique human factors associated with these aircraft. The task of flying an RPA in civilian airspace involves challenges common to the operation of other highly-automated systems, but also introduces new considerations for pilot perception, decision-making, and action execution. RPA pilots participated in focus groups where they were asked to recall critical incidents that either presented a threat to safety, or highlighted a case where the pilot contributed to system resilience or mission success. Ninety incidents were gathered from focus-groups. Human factor issues included the impact of reduced sensory cues, traffic separation in the absence of an out-the-window view, control latencies, vigilance during monotonous and ultra-long endurance flights, control station design considerations, transfer of control between control stations, the management of lost link procedures, and decision-making during emergencies. Some of these concerns have received significant attention in the literature, or are analogous to human factors of manned aircraft. The presentation will focus on issues that are poorly understood, and have not yet been the subject of extensive human factors study. Although many of the reported incidents were related to pilot error, the participants also provided examples of the positive contribution that humans make to the operation of highly-automated systems.

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.

[Safety culture in orthopedics and trauma surgery : Course concept: interpersonal competence by the German Society for Orthopaedics and Trauma (DGOU) and Lufthansa Aviation Training].

PubMed

Doepfer, A-K; Seemann, R; Merschin, D; Stange, R; Egerth, M; Münzberg, M; Mutschler, M; Bouillon, B; Hoffmann, R

2017-10-01

Patient safety has become a central and measurable key factor in the routine daily medical practice. The human factor plays a decisive role in safety culture and has moved into focus regarding the reduction of treatment errors and undesired critical incidents. Nonetheless, the systematic training in communication and interpersonal competences has so far only played a minor role. The German Society of Orthopaedics and Trauma (DGOU) in cooperation with the Lufthansa Aviation Training initiated a course system for interpersonal competence. Several studies confirmed the reduction of critical incidents and costs after implementation of a regular and targeted human factor training. The interpersonal competence should be an essential component of specialist training within the framework of a 3‑column model.

On framing the research question and choosing the appropriate research design.

PubMed

Parfrey, Patrick S; Ravani, Pietro

2015-01-01

Clinical epidemiology is the science of human disease investigation with a focus on diagnosis, prognosis, and treatment. The generation of a reasonable question requires definition of patients, interventions, controls, and outcomes. The goal of research design is to minimize error, to ensure adequate samples, to measure input and output variables appropriately, to consider external and internal validities, to limit bias, and to address clinical as well as statistical relevance. The hierarchy of evidence for clinical decision-making places randomized controlled trials (RCT) or systematic review of good quality RCTs at the top of the evidence pyramid. Prognostic and etiologic questions are best addressed with longitudinal cohort studies.

On framing the research question and choosing the appropriate research design.

PubMed

Parfrey, Patrick; Ravani, Pietro

2009-01-01

Clinical epidemiology is the science of human disease investigation with a focus on diagnosis, prognosis, and treatment. The generation of a reasonable question requires the definition of patients, interventions, controls, and outcomes. The goal of research design is to minimize error, ensure adequate samples, measure input and output variables appropriately, consider external and internal validities, limit bias, and address clinical as well as statistical relevance. The hierarchy of evidence for clinical decision making places randomized controlled trials (RCT) or systematic review of good quality RCTs at the top of the evidence pyramid. Prognostic and etiologic questions are best addressed with longitudinal cohort studies.

How to minimize perceptual error and maximize expertise in medical imaging

NASA Astrophysics Data System (ADS)

Kundel, Harold L.

2007-03-01

Visual perception is such an intimate part of human experience that we assume that it is entirely accurate. Yet, perception accounts for about half of the errors made by radiologists using adequate imaging technology. The true incidence of errors that directly affect patient well being is not known but it is probably at the lower end of the reported values of 3 to 25%. Errors in screening for lung and breast cancer are somewhat better characterized than errors in routine diagnosis. About 25% of cancers actually recorded on the images are missed and cancer is falsely reported in about 5% of normal people. Radiologists must strive to decrease error not only because of the potential impact on patient care but also because substantial variation among observers undermines confidence in the reliability of imaging diagnosis. Observer variation also has a major impact on technology evaluation because the variation between observers is frequently greater than the difference in the technologies being evaluated. This has become particularly important in the evaluation of computer aided diagnosis (CAD). Understanding the basic principles that govern the perception of medical images can provide a rational basis for making recommendations for minimizing perceptual error. It is convenient to organize thinking about perceptual error into five steps. 1) The initial acquisition of the image by the eye-brain (contrast and detail perception). 2) The organization of the retinal image into logical components to produce a literal perception (bottom-up, global, holistic). 3) Conversion of the literal perception into a preferred perception by resolving ambiguities in the literal perception (top-down, simulation, synthesis). 4) Selective visual scanning to acquire details that update the preferred perception. 5) Apply decision criteria to the preferred perception. The five steps are illustrated with examples from radiology with suggestions for minimizing error. The role of perceptual learning in the development of expertise is also considered.

Analyzing human errors in flight mission operations

NASA Technical Reports Server (NTRS)

Bruno, Kristin J.; Welz, Linda L.; Barnes, G. Michael; Sherif, Josef

1993-01-01

A long-term program is in progress at JPL to reduce cost and risk of flight mission operations through a defect prevention/error management program. The main thrust of this program is to create an environment in which the performance of the total system, both the human operator and the computer system, is optimized. To this end, 1580 Incident Surprise Anomaly reports (ISA's) from 1977-1991 were analyzed from the Voyager and Magellan projects. A Pareto analysis revealed that 38 percent of the errors were classified as human errors. A preliminary cluster analysis based on the Magellan human errors (204 ISA's) is presented here. The resulting clusters described the underlying relationships among the ISA's. Initial models of human error in flight mission operations are presented. Next, the Voyager ISA's will be scored and included in the analysis. Eventually, these relationships will be used to derive a theoretically motivated and empirically validated model of human error in flight mission operations. Ultimately, this analysis will be used to make continuous process improvements continuous process improvements to end-user applications and training requirements. This Total Quality Management approach will enable the management and prevention of errors in the future.

Scaling up high throughput field phenotyping of corn and soy research plots using ground rovers

NASA Astrophysics Data System (ADS)

Peshlov, Boyan; Nakarmi, Akash; Baldwin, Steven; Essner, Scott; French, Jasenka

2017-05-01

Crop improvement programs require large and meticulous selection processes that effectively and accurately collect and analyze data to generate quality plant products as efficiently as possible, develop superior cropping and/or crop improvement methods. Typically, data collection for such testing is performed by field teams using hand-held instruments or manually-controlled devices. Although steps are taken to reduce error, the data collected in such manner can be unreliable due to human error and fatigue, which reduces the ability to make accurate selection decisions. Monsanto engineering teams have developed a high-clearance mobile platform (Rover) as a step towards high throughput and high accuracy phenotyping at an industrial scale. The rovers are equipped with GPS navigation, multiple cameras and sensors and on-board computers to acquire data and compute plant vigor metrics per plot. The supporting IT systems enable automatic path planning, plot identification, image and point cloud data QA/QC and near real-time analysis where results are streamed to enterprise databases for additional statistical analysis and product advancement decisions. Since the rover program was launched in North America in 2013, the number of research plots we can analyze in a growing season has expanded dramatically. This work describes some of the successes and challenges in scaling up of the rover platform for automated phenotyping to enable science at scale.

Uncovering the requirements of cognitive work.

PubMed

Roth, Emilie M

2008-06-01

In this article, the author provides an overview of cognitive analysis methods and how they can be used to inform system analysis and design. Human factors has seen a shift toward modeling and support of cognitively intensive work (e.g., military command and control, medical planning and decision making, supervisory control of automated systems). Cognitive task analysis and cognitive work analysis methods extend traditional task analysis techniques to uncover the knowledge and thought processes that underlie performance in cognitively complex settings. The author reviews the multidisciplinary roots of cognitive analysis and the variety of cognitive task analysis and cognitive work analysis methods that have emerged. Cognitive analysis methods have been used successfully to guide system design, as well as development of function allocation, team structure, and training, so as to enhance performance and reduce the potential for error. A comprehensive characterization of cognitive work requires two mutually informing analyses: (a) examination of domain characteristics and constraints that define cognitive requirements and challenges and (b) examination of practitioner knowledge and strategies that underlie both expert and error-vulnerable performance. A variety of specific methods can be adapted to achieve these aims within the pragmatic constraints of particular projects. Cognitive analysis methods can be used effectively to anticipate cognitive performance problems and specify ways to improve individual and team cognitive performance (be it through new forms of training, user interfaces, or decision aids).

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.

Factors that influence search termination decisions in free recall: an examination of response type and confidence.

PubMed

Unsworth, Nash; Brewer, Gene A; Spillers, Gregory J

2011-09-01

In three experiments search termination decisions were examined as a function of response type (correct vs. incorrect) and confidence. It was found that the time between the last retrieved item and the decision to terminate search (exit latency) was related to the type of response and confidence in the last item retrieved. Participants were willing to search longer when the last retrieved item was a correct item vs. an incorrect item and when the confidence was high in the last retrieved item. It was also found that the number of errors retrieved during the recall period was related to search termination decisions such that the more errors retrieved, the more likely participants were to terminate the search. Finally, it was found that knowledge of overall search set size influenced the time needed to search for items, but did not influence search termination decisions. Copyright © 2011 Elsevier B.V. All rights reserved.

A risk-based approach to flood management decisions in a nonstationary world

NASA Astrophysics Data System (ADS)

Rosner, Ana; Vogel, Richard M.; Kirshen, Paul H.

2014-03-01

Traditional approaches to flood management in a nonstationary world begin with a null hypothesis test of "no trend" and its likelihood, with little or no attention given to the likelihood that we might ignore a trend if it really existed. Concluding a trend exists when it does not, or rejecting a trend when it exists are known as type I and type II errors, respectively. Decision-makers are poorly served by statistical and/or decision methods that do not carefully consider both over- and under-preparation errors, respectively. Similarly, little attention is given to how to integrate uncertainty in our ability to detect trends into a flood management decision context. We show how trend hypothesis test results can be combined with an adaptation's infrastructure costs and damages avoided to provide a rational decision approach in a nonstationary world. The criterion of expected regret is shown to be a useful metric that integrates the statistical, economic, and hydrological aspects of the flood management problem in a nonstationary world.

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

An Iterative Information-Reduced Quadriphase-Shift-Keyed Carrier Synchronization Scheme Using Decision Feedback for Low Signal-to-Noise Ratio Applications

NASA Technical Reports Server (NTRS)

Simon, M.; Tkacenko, A.

2006-01-01

In a previous publication [1], an iterative closed-loop carrier synchronization scheme for binary phase-shift keyed (BPSK) modulation was proposed that was based on feeding back data decisions to the input of the loop, the purpose being to remove the modulation prior to carrier synchronization as opposed to the more conventional decision-feedback schemes that incorporate such feedback inside the loop. The idea there was that, with sufficient independence between the received data and the decisions on it that are fed back (as would occur in an error-correction coding environment with sufficient decoding delay), a pure tone in the presence of noise would ultimately be produced (after sufficient iteration and low enough error probability) and thus could be tracked without any squaring loss. This article demonstrates that, with some modification, the same idea of iterative information reduction through decision feedback can be applied to quadrature phase-shift keyed (QPSK) modulation, something that was mentioned in the previous publication but never pursued.

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.

Development of an autonomous treatment planning strategy for radiation therapy with effective use of population-based prior data.

PubMed

Wang, Huan; Dong, Peng; Liu, Hongcheng; Xing, Lei

2017-02-01

Current treatment planning remains a costly and labor intensive procedure and requires multiple trial-and-error adjustments of system parameters such as the weighting factors and prescriptions. The purpose of this work is to develop an autonomous treatment planning strategy with effective use of prior knowledge and in a clinically realistic treatment planning platform to facilitate radiation therapy workflow. Our technique consists of three major components: (i) a clinical treatment planning system (TPS); (ii) a formulation of decision-function constructed using an assemble of prior treatment plans; (iii) a plan evaluator or decision-function and an outer-loop optimization independent of the clinical TPS to assess the TPS-generated plan and to drive the search toward a solution optimizing the decision-function. Microsoft (MS) Visual Studio Coded UI is applied to record some common planner-TPS interactions as subroutines for querying and interacting with the TPS. These subroutines are called back in the outer-loop optimization program to navigate the plan selection process through the solution space iteratively. The utility of the approach is demonstrated by using clinical prostate and head-and-neck cases. An autonomous treatment planning technique with effective use of an assemble of prior treatment plans is developed to automatically maneuver the clinical treatment planning process in the platform of a commercial TPS. The process mimics the decision-making process of a human planner and provides a clinically sensible treatment plan automatically, thus reducing/eliminating the tedious manual trial-and-errors of treatment planning. It is found that the prostate and head-and-neck treatment plans generated using the approach compare favorably with that used for the patients' actual treatments. Clinical inverse treatment planning process can be automated effectively with the guidance of an assemble of prior treatment plans. The approach has the potential to significantly improve the radiation therapy workflow. © 2016 American Association of Physicists in Medicine.

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

Implementing parallel spreadsheet models for health policy decisions: The impact of unintentional errors on model projections

PubMed Central

Bailey, Stephanie L.; Bono, Rose S.; Nash, Denis; Kimmel, April D.

2018-01-01

Background Spreadsheet software is increasingly used to implement systems science models informing health policy decisions, both in academia and in practice where technical capacity may be limited. However, spreadsheet models are prone to unintentional errors that may not always be identified using standard error-checking techniques. Our objective was to illustrate, through a methodologic case study analysis, the impact of unintentional errors on model projections by implementing parallel model versions. Methods We leveraged a real-world need to revise an existing spreadsheet model designed to inform HIV policy. We developed three parallel versions of a previously validated spreadsheet-based model; versions differed by the spreadsheet cell-referencing approach (named single cells; column/row references; named matrices). For each version, we implemented three model revisions (re-entry into care; guideline-concordant treatment initiation; immediate treatment initiation). After standard error-checking, we identified unintentional errors by comparing model output across the three versions. Concordant model output across all versions was considered error-free. We calculated the impact of unintentional errors as the percentage difference in model projections between model versions with and without unintentional errors, using +/-5% difference to define a material error. Results We identified 58 original and 4,331 propagated unintentional errors across all model versions and revisions. Over 40% (24/58) of original unintentional errors occurred in the column/row reference model version; most (23/24) were due to incorrect cell references. Overall, >20% of model spreadsheet cells had material unintentional errors. When examining error impact along the HIV care continuum, the percentage difference between versions with and without unintentional errors ranged from +3% to +16% (named single cells), +26% to +76% (column/row reference), and 0% (named matrices). Conclusions Standard error-checking techniques may not identify all errors in spreadsheet-based models. Comparing parallel model versions can aid in identifying unintentional errors and promoting reliable model projections, particularly when resources are limited. PMID:29570737

Implementing parallel spreadsheet models for health policy decisions: The impact of unintentional errors on model projections.

PubMed

Bailey, Stephanie L; Bono, Rose S; Nash, Denis; Kimmel, April D

2018-01-01

Spreadsheet software is increasingly used to implement systems science models informing health policy decisions, both in academia and in practice where technical capacity may be limited. However, spreadsheet models are prone to unintentional errors that may not always be identified using standard error-checking techniques. Our objective was to illustrate, through a methodologic case study analysis, the impact of unintentional errors on model projections by implementing parallel model versions. We leveraged a real-world need to revise an existing spreadsheet model designed to inform HIV policy. We developed three parallel versions of a previously validated spreadsheet-based model; versions differed by the spreadsheet cell-referencing approach (named single cells; column/row references; named matrices). For each version, we implemented three model revisions (re-entry into care; guideline-concordant treatment initiation; immediate treatment initiation). After standard error-checking, we identified unintentional errors by comparing model output across the three versions. Concordant model output across all versions was considered error-free. We calculated the impact of unintentional errors as the percentage difference in model projections between model versions with and without unintentional errors, using +/-5% difference to define a material error. We identified 58 original and 4,331 propagated unintentional errors across all model versions and revisions. Over 40% (24/58) of original unintentional errors occurred in the column/row reference model version; most (23/24) were due to incorrect cell references. Overall, >20% of model spreadsheet cells had material unintentional errors. When examining error impact along the HIV care continuum, the percentage difference between versions with and without unintentional errors ranged from +3% to +16% (named single cells), +26% to +76% (column/row reference), and 0% (named matrices). Standard error-checking techniques may not identify all errors in spreadsheet-based models. Comparing parallel model versions can aid in identifying unintentional errors and promoting reliable model projections, particularly when resources are limited.

Dual learning processes underlying human decision-making in reversal learning tasks: functional significance and evidence from the model fit to human behavior

PubMed Central

Bai, Yu; Katahira, Kentaro; Ohira, Hideki

2014-01-01

Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL) has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance in a probabilistic reversal learning task. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against the mistuning of parameters compared with the standard RL model when decision-makers continue to learn stimulus-reward contingencies, which can create abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model. PMID:25161635

Human Error and the International Space Station: Challenges and Triumphs in Science Operations

NASA Technical Reports Server (NTRS)

Harris, Samantha S.; Simpson, Beau C.

2016-01-01

Any system with a human component is inherently risky. Studies in human factors and psychology have repeatedly shown that human operators will inevitably make errors, regardless of how well they are trained. Onboard the International Space Station (ISS) where crew time is arguably the most valuable resource, errors by the crew or ground operators can be costly to critical science objectives. Operations experts at the ISS Payload Operations Integration Center (POIC), located at NASA's Marshall Space Flight Center in Huntsville, Alabama, have learned that from payload concept development through execution, there are countless opportunities to introduce errors that can potentially result in costly losses of crew time and science. To effectively address this challenge, we must approach the design, testing, and operation processes with two specific goals in mind. First, a systematic approach to error and human centered design methodology should be implemented to minimize opportunities for user error. Second, we must assume that human errors will be made and enable rapid identification and recoverability when they occur. While a systematic approach and human centered development process can go a long way toward eliminating error, the complete exclusion of operator error is not a reasonable expectation. The ISS environment in particular poses challenging conditions, especially for flight controllers and astronauts. Operating a scientific laboratory 250 miles above the Earth is a complicated and dangerous task with high stakes and a steep learning curve. While human error is a reality that may never be fully eliminated, smart implementation of carefully chosen tools and techniques can go a long way toward minimizing risk and increasing the efficiency of NASA's space science operations.

Modeling human response errors in synthetic flight simulator domain

NASA Technical Reports Server (NTRS)

Ntuen, Celestine A.

1992-01-01

This paper presents a control theoretic approach to modeling human response errors (HRE) in the flight simulation domain. The human pilot is modeled as a supervisor of a highly automated system. The synthesis uses the theory of optimal control pilot modeling for integrating the pilot's observation error and the error due to the simulation model (experimental error). Methods for solving the HRE problem are suggested. Experimental verification of the models will be tested in a flight quality handling simulation.

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.

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

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.

Conditional Standard Errors, Reliability and Decision Consistency of Performance Levels Using Polytomous IRT.

ERIC Educational Resources Information Center

Wang, Tianyou; And Others

M. J. Kolen, B. A. Hanson, and R. L. Brennan (1992) presented a procedure for assessing the conditional standard error of measurement (CSEM) of scale scores using a strong true-score model. They also investigated the ways of using nonlinear transformation from number-correct raw score to scale score to equalize the conditional standard error along…

Defining the Relationship Between Human Error Classes and Technology Intervention Strategies

NASA Technical Reports Server (NTRS)

Wiegmann, Douglas A.; Rantanen, Esa; Crisp, Vicki K. (Technical Monitor)

2002-01-01

One of the main factors in all aviation accidents is human error. The NASA Aviation Safety Program (AvSP), therefore, has identified several human-factors safety technologies to address this issue. Some technologies directly address human error either by attempting to reduce the occurrence of errors or by mitigating the negative consequences of errors. However, new technologies and system changes may also introduce new error opportunities or even induce different types of errors. Consequently, a thorough understanding of the relationship between error classes and technology "fixes" is crucial for the evaluation of intervention strategies outlined in the AvSP, so that resources can be effectively directed to maximize the benefit to flight safety. The purpose of the present project, therefore, was to examine the repositories of human factors data to identify the possible relationship between different error class and technology intervention strategies. The first phase of the project, which is summarized here, involved the development of prototype data structures or matrices that map errors onto "fixes" (and vice versa), with the hope of facilitating the development of standards for evaluating safety products. Possible follow-on phases of this project are also discussed. These additional efforts include a thorough and detailed review of the literature to fill in the data matrix and the construction of a complete database and standards checklists.

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.

Social learning through prediction error in the brain

NASA Astrophysics Data System (ADS)

Joiner, Jessica; Piva, Matthew; Turrin, Courtney; Chang, Steve W. C.

2017-06-01

Learning about the world is critical to survival and success. In social animals, learning about others is a necessary component of navigating the social world, ultimately contributing to increasing evolutionary fitness. How humans and nonhuman animals represent the internal states and experiences of others has long been a subject of intense interest in the developmental psychology tradition, and, more recently, in studies of learning and decision making involving self and other. In this review, we explore how psychology conceptualizes the process of representing others, and how neuroscience has uncovered correlates of reinforcement learning signals to explore the neural mechanisms underlying social learning from the perspective of representing reward-related information about self and other. In particular, we discuss self-referenced and other-referenced types of reward prediction errors across multiple brain structures that effectively allow reinforcement learning algorithms to mediate social learning. Prediction-based computational principles in the brain may be strikingly conserved between self-referenced and other-referenced information.

Mesolimbic confidence signals guide perceptual learning in the absence of external feedback

PubMed Central

Guggenmos, Matthias; Wilbertz, Gregor; Hebart, Martin N; Sterzer, Philipp

2016-01-01

It is well established that learning can occur without external feedback, yet normative reinforcement learning theories have difficulties explaining such instances of learning. Here, we propose that human observers are capable of generating their own feedback signals by monitoring internal decision variables. We investigated this hypothesis in a visual perceptual learning task using fMRI and confidence reports as a measure for this monitoring process. Employing a novel computational model in which learning is guided by confidence-based reinforcement signals, we found that mesolimbic brain areas encoded both anticipation and prediction error of confidence—in remarkable similarity to previous findings for external reward-based feedback. We demonstrate that the model accounts for choice and confidence reports and show that the mesolimbic confidence prediction error modulation derived through the model predicts individual learning success. These results provide a mechanistic neurobiological explanation for learning without external feedback by augmenting reinforcement models with confidence-based feedback. DOI: http://dx.doi.org/10.7554/eLife.13388.001 PMID:27021283

Development and implementation of a human accuracy program in patient foodservice.

PubMed

Eden, S H; Wood, S M; Ptak, K M

1987-04-01

For many years, industry has utilized the concept of human error rates to monitor and minimize human errors in the production process. A consistent quality-controlled product increases consumer satisfaction and repeat purchase of product. Administrative dietitians have applied the concepts of using human error rates (the number of errors divided by the number of opportunities for error) at four hospitals, with a total bed capacity of 788, within a tertiary-care medical center. Human error rate was used to monitor and evaluate trayline employee performance and to evaluate layout and tasks of trayline stations, in addition to evaluating employees in patient service areas. Long-term employees initially opposed the error rate system with some hostility and resentment, while newer employees accepted the system. All employees now believe that the constant feedback given by supervisors enhances their self-esteem and productivity. Employee error rates are monitored daily and are used to counsel employees when necessary; they are also utilized during annual performance evaluation. Average daily error rates for a facility staffed by new employees decreased from 7% to an acceptable 3%. In a facility staffed by long-term employees, the error rate increased, reflecting improper error documentation. Patient satisfaction surveys reveal satisfaction, for tray accuracy increased from 88% to 92% in the facility staffed by long-term employees and has remained above the 90% standard in the facility staffed by new employees.

Reflections on human error - Matters of life and death

NASA Technical Reports Server (NTRS)

Wiener, Earl L.

1989-01-01

The last two decades have witnessed a rapid growth in the introduction of automatic devices into aircraft cockpits, and eleswhere in human-machine systems. This was motivated in part by the assumption that when human functioning is replaced by machine functioning, human error is eliminated. Experience to date shows that this is far from true, and that automation does not replace humans, but changes their role in the system, as well as the types and severity of the errors they make. This altered role may lead to fewer, but more critical errors. Intervention strategies to prevent these errors, or ameliorate their consequences include basic human factors engineering of the interface, enhanced warning and alerting systems, and more intelligent interfaces that understand the strategic intent of the crew and can detect and trap inconsistent or erroneous input before it affects the system.

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.

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.

A stochastic dynamic model for human error analysis in nuclear power plants

NASA Astrophysics Data System (ADS)

Delgado-Loperena, Dharma

Nuclear disasters like Three Mile Island and Chernobyl indicate that human performance is a critical safety issue, sending a clear message about the need to include environmental press and competence aspects in research. This investigation was undertaken to serve as a roadmap for studying human behavior through the formulation of a general solution equation. The theoretical model integrates models from two heretofore-disassociated disciplines (behavior specialists and technical specialists), that historically have independently studied the nature of error and human behavior; including concepts derived from fractal and chaos theory; and suggests re-evaluation of base theory regarding human error. The results of this research were based on comprehensive analysis of patterns of error, with the omnipresent underlying structure of chaotic systems. The study of patterns lead to a dynamic formulation, serving for any other formula used to study human error consequences. The search for literature regarding error yielded insight for the need to include concepts rooted in chaos theory and strange attractors---heretofore unconsidered by mainstream researchers who investigated human error in nuclear power plants or those who employed the ecological model in their work. The study of patterns obtained from the rupture of a steam generator tube (SGTR) event simulation, provided a direct application to aspects of control room operations in nuclear power plant operations. In doing so, the conceptual foundation based in the understanding of the patterns of human error analysis can be gleaned, resulting in reduced and prevent undesirable events.

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.

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

The Attraction Effect Modulates Reward Prediction Errors and Intertemporal Choices.

PubMed

Gluth, Sebastian; Hotaling, Jared M; Rieskamp, Jörg

2017-01-11

Classical economic theory contends that the utility of a choice option should be independent of other options. This view is challenged by the attraction effect, in which the relative preference between two options is altered by the addition of a third, asymmetrically dominated option. Here, we leveraged the attraction effect in the context of intertemporal choices to test whether both decisions and reward prediction errors (RPE) in the absence of choice violate the independence of irrelevant alternatives principle. We first demonstrate that intertemporal decision making is prone to the attraction effect in humans. In an independent group of participants, we then investigated how this affects the neural and behavioral valuation of outcomes using a novel intertemporal lottery task and fMRI. Participants' behavioral responses (i.e., satisfaction ratings) were modulated systematically by the attraction effect and this modulation was correlated across participants with the respective change of the RPE signal in the nucleus accumbens. Furthermore, we show that, because exponential and hyperbolic discounting models are unable to account for the attraction effect, recently proposed sequential sampling models might be more appropriate to describe intertemporal choices. Our findings demonstrate for the first time that the attraction effect modulates subjective valuation even in the absence of choice. The findings also challenge the prospect of using neuroscientific methods to measure utility in a context-free manner and have important implications for theories of reinforcement learning and delay discounting. Many theories of value-based decision making assume that people first assess the attractiveness of each option independently of each other and then pick the option with the highest subjective value. The attraction effect, however, shows that adding a new option to a choice set can change the relative value of the existing options, which is a violation of the independence principle. Using an intertemporal choice framework, we tested whether such violations also occur when the brain encodes the difference between expected and received rewards (i.e., the reward prediction error). Our results suggest that neither intertemporal choice nor valuation without choice adhere to the independence principle. Copyright © 2017 the authors 0270-6474/17/370371-12$15.00/0.

Human Orbitofrontal Cortex Represents a Cognitive Map of State Space.

PubMed

Schuck, Nicolas W; Cai, Ming Bo; Wilson, Robert C; Niv, Yael

2016-09-21

Although the orbitofrontal cortex (OFC) has been studied intensely for decades, its precise functions have remained elusive. We recently hypothesized that the OFC contains a "cognitive map" of task space in which the current state of the task is represented, and this representation is especially critical for behavior when states are unobservable from sensory input. To test this idea, we apply pattern-classification techniques to neuroimaging data from humans performing a decision-making task with 16 states. We show that unobservable task states can be decoded from activity in OFC, and decoding accuracy is related to task performance and the occurrence of individual behavioral errors. Moreover, similarity between the neural representations of consecutive states correlates with behavioral accuracy in corresponding state transitions. These results support the idea that OFC represents a cognitive map of task space and establish the feasibility of decoding state representations in humans using non-invasive neuroimaging. Copyright © 2016 Elsevier Inc. All rights reserved.

Leveraging human oversight and intervention in large-scale parallel processing of open-source data

NASA Astrophysics Data System (ADS)

Casini, Enrico; Suri, Niranjan; Bradshaw, Jeffrey M.

2015-05-01

The popularity of cloud computing along with the increased availability of cheap storage have led to the necessity of elaboration and transformation of large volumes of open-source data, all in parallel. One way to handle such extensive volumes of information properly is to take advantage of distributed computing frameworks like Map-Reduce. Unfortunately, an entirely automated approach that excludes human intervention is often unpredictable and error prone. Highly accurate data processing and decision-making can be achieved by supporting an automatic process through human collaboration, in a variety of environments such as warfare, cyber security and threat monitoring. Although this mutual participation seems easily exploitable, human-machine collaboration in the field of data analysis presents several challenges. First, due to the asynchronous nature of human intervention, it is necessary to verify that once a correction is made, all the necessary reprocessing is done in chain. Second, it is often needed to minimize the amount of reprocessing in order to optimize the usage of resources due to limited availability. In order to improve on these strict requirements, this paper introduces improvements to an innovative approach for human-machine collaboration in the processing of large amounts of open-source data in parallel.

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…

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…

Sensitivity of disease management decision aids to temperature input errors associated with out-of-canopy and reduced time-resolution measurements

USDA-ARS?s Scientific Manuscript database

Plant disease management decision aids typically require inputs of weather elements such as air temperature. Whereas many disease models are created based on weather elements at the crop canopy, and with relatively fine time resolution, the decision aids commonly are implemented with hourly weather...

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,…

Applying Model-Based Reasoning to the FDIR of the Command and Data Handling Subsystem of the International Space Station

NASA Technical Reports Server (NTRS)

Robinson, Peter; Shirley, Mark; Fletcher, Daryl; Alena, Rick; Duncavage, Dan; Lee, Charles

2003-01-01

All of the International Space Station (ISS) systems which require computer control depend upon the hardware and software of the Command and Data Handling System (C&DH) system, currently a network of over 30 386-class computers called Multiplexor/Dimultiplexors (MDMs)[18]. The Caution and Warning System (C&W)[7], a set of software tasks that runs on the MDMs, is responsible for detecting, classifying, and reporting errors in all ISS subsystems including the C&DH. Fault Detection, Isolation and Recovery (FDIR) of these errors is typically handled with a combination of automatic and human effort. We are developing an Advanced Diagnostic System (ADS) to augment the C&W system with decision support tools to aid in root cause analysis as well as resolve differing human and machine C&DH state estimates. These tools which draw from sources in model-based reasoning[ 16,291, will improve the speed and accuracy of flight controllers by reducing the uncertainty in C&DH state estimation, allowing for a more complete assessment of risk. We have run tests with ISS telemetry and focus on those C&W events which relate to the C&DH system itself. This paper describes our initial results and subsequent plans.

Gaming against medical errors: methods and results from a design game on CPOE.

PubMed

Kanstrup, Anne Marie; Nøhr, Christian

2009-01-01

The paper presents design game as a technique for participatory design for a Computerized Decision Support System (CDSS) for minimizing medical errors. Design game is used as a technique for working with the skills of users, the complexity of the use practice and the negotiation of design here within the challenging domain of medication. The paper presents a developed design game based on game inspiration from a computer game, theoretical inspiration on electronic decision support, and empirical grounding in scenarios of medical errors. The game has been played in a two-hour workshop with six clinicians. The result is presented as a list of central themes for design of CDSS and derived design principles from these themes. These principles are currently under further exploration in follow up prototype based activities.

Types of errors by referees and perception of injustice by soccer players: a preliminary study.

PubMed

Canovas, Sophie; Reynes, Eric; Ferrand, Claude; Pantaléon, Nathalie; Long, Thierry

2008-02-01

This study investigated the effect of referees' errors on players' perceived injustice in soccer. The conditions investigated were Referee Decision, with three types: Correctly Called a foul vs Wrongly Called a foul vs Did not Call a foul and Repetition of the Situation, with two types: Isolated vs Repeated. Male soccer players at regional and departmental levels of practice (N = 95, M(age) = 23.2, SD = 5.1) were asked to rank six hypothetical situations according to the perceived injustice. Analysis indicated significant effects of Referee Decisions and Repetition of the Situation on the perception of injustice, but showed no differences between the types of error. However, age and years of soccer experience were associated with perception of injustice when the referee correctly called a foul.

Human factors process failure modes and effects analysis (HF PFMEA) software tool

NASA Technical Reports Server (NTRS)

Chandler, Faith T. (Inventor); Relvini, Kristine M. (Inventor); Shedd, Nathaneal P. (Inventor); Valentino, William D. (Inventor); Philippart, Monica F. (Inventor); Bessette, Colette I. (Inventor)

2011-01-01

Methods, computer-readable media, and systems for automatically performing Human Factors Process Failure Modes and Effects Analysis for a process are provided. At least one task involved in a process is identified, where the task includes at least one human activity. The human activity is described using at least one verb. A human error potentially resulting from the human activity is automatically identified, the human error is related to the verb used in describing the task. A likelihood of occurrence, detection, and correction of the human error is identified. The severity of the effect of the human error is identified. The likelihood of occurrence, and the severity of the risk of potential harm is identified. The risk of potential harm is compared with a risk threshold to identify the appropriateness of corrective measures.

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.

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.

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection.

PubMed

Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang

2018-01-15

In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes' (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10 -5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.

Automatic system testing of a decision support system for insulin dosing using Google Android.

PubMed

Spat, Stephan; Höll, Bernhard; Petritsch, Georg; Schaupp, Lukas; Beck, Peter; Pieber, Thomas R

2013-01-01

Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. A framework for high-volume, reproducible and automated system testing of the GlucoTab system was set up applying several Open Source tools for test automation and system time handling. The REACTION insulin titration protocol was investigated in a paper-based clinical trial (PBCT). In order to validate the GlucoTab system, data from this trial was used for simulation and system tests. In total, 1190 decision support action points were identified and simulated. Four data points (0.3%) resulted in a GlucoTab system error caused by a defective implementation. In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards.

Air Force Academy Homepage

Science.gov Websites

Chaplain Corps Cadet Chapel Community Center Chapel Institutional Review Board Not Human Subjects Research Requirements 7 Not Human Subjects Research Form 8 Researcher Instructions - Activities Submitted to DoD IRB 9 Review 18 Not Human Subjects Errors 19 Exempt Research Most Frequent Errors 20 Most Frequent Errors for

Development of an FAA-EUROCONTROL technique for the analysis of human error in ATM : final report.

DOT National Transportation Integrated Search

2002-07-01

Human error has been identified as a dominant risk factor in safety-oriented industries such as air traffic control (ATC). However, little is known about the factors leading to human errors in current air traffic management (ATM) systems. The first s...

Human Error: The Stakes Are Raised.

ERIC Educational Resources Information Center

Greenberg, Joel

1980-01-01

Mistakes related to the operation of nuclear power plants and other technologically complex systems are discussed. Recommendations are given for decreasing the chance of human error in the operation of nuclear plants. The causes of the Three Mile Island incident are presented in terms of the human error element. (SA)

Modelling decision-making by pilots

NASA Technical Reports Server (NTRS)

Patrick, Nicholas J. M.

1993-01-01

Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).

Avoiding Human Error in Mission Operations: Cassini Flight Experience

NASA Technical Reports Server (NTRS)

Burk, Thomas A.

2012-01-01

Operating spacecraft is a never-ending challenge and the risk of human error is ever- present. Many missions have been significantly affected by human error on the part of ground controllers. The Cassini mission at Saturn has not been immune to human error, but Cassini operations engineers use tools and follow processes that find and correct most human errors before they reach the spacecraft. What is needed are skilled engineers with good technical knowledge, good interpersonal communications, quality ground software, regular peer reviews, up-to-date procedures, as well as careful attention to detail and the discipline to test and verify all commands that will be sent to the spacecraft. Two areas of special concern are changes to flight software and response to in-flight anomalies. The Cassini team has a lot of practical experience in all these areas and they have found that well-trained engineers with good tools who follow clear procedures can catch most errors before they get into command sequences to be sent to the spacecraft. Finally, having a robust and fault-tolerant spacecraft that allows ground controllers excellent visibility of its condition is the most important way to ensure human error does not compromise the mission.

Decision Support Alerts for Medication Ordering in a Computerized Provider Order Entry (CPOE) System

PubMed Central

Beccaro, M. A. Del; Villanueva, R.; Knudson, K. M.; Harvey, E. M.; Langle, J. M.; Paul, W.

2010-01-01

Objective We sought to determine the frequency and type of decision support alerts by location and ordering provider role during Computerized Provider Order Entry (CPOE) medication ordering. Using these data we adjusted the decision support tools to reduce the number of alerts. Design Retrospective analyses were performed of dose range checks (DRC), drug-drug interaction and drug-allergy alerts from our electronic medical record. During seven sampling periods (each two weeks long) between April 2006 and October 2008 all alerts in these categories were analyzed. Another audit was performed of all DRC alerts by ordering provider role from November 2008 through January 2009. Medication ordering error counts were obtained from a voluntary error reporting system. Measurement/Results Between April 2006 and October 2008 the percent of medication orders that triggered a dose range alert decreased from 23.9% to 7.4%. The relative risk (RR) for getting an alert was higher at the start of the interventions versus later (RR= 2.40, 95% CI 2.28-2.52; p< 0.0001). The percentage of medication orders that triggered alerts for drug-drug interactions also decreased from 13.5% to 4.8%. The RR for getting a drug interaction alert at the start was 1.63, 95% CI 1.60-1.66; p< 0.0001. Alerts decreased in all clinical areas without an increase in reported medication errors. Conclusion We reduced the quantity of decision support alerts in CPOE using a systematic approach without an increase in reported medication errors PMID:23616845

Good people who try their best can have problems: recognition of human factors and how to minimise error.

PubMed

Brennan, Peter A; Mitchell, David A; Holmes, Simon; Plint, Simon; Parry, David

2016-01-01

Human error is as old as humanity itself and is an appreciable cause of mistakes by both organisations and people. Much of the work related to human factors in causing error has originated from aviation where mistakes can be catastrophic not only for those who contribute to the error, but for passengers as well. The role of human error in medical and surgical incidents, which are often multifactorial, is becoming better understood, and includes both organisational issues (by the employer) and potential human factors (at a personal level). Mistakes as a result of individual human factors and surgical teams should be better recognised and emphasised. Attitudes and acceptance of preoperative briefing has improved since the introduction of the World Health Organization (WHO) surgical checklist. However, this does not address limitations or other safety concerns that are related to performance, such as stress and fatigue, emotional state, hunger, awareness of what is going on situational awareness, and other factors that could potentially lead to error. Here we attempt to raise awareness of these human factors, and highlight how they can lead to error, and how they can be minimised in our day-to-day practice. Can hospitals move from being "high risk industries" to "high reliability organisations"? Copyright © 2015 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Using a Delphi Method to Identify Human Factors Contributing to Nursing Errors.

PubMed

Roth, Cheryl; Brewer, Melanie; Wieck, K Lynn

2017-07-01

The purpose of this study was to identify human factors associated with nursing errors. Using a Delphi technique, this study used feedback from a panel of nurse experts (n = 25) on an initial qualitative survey questionnaire followed by summarizing the results with feedback and confirmation. Synthesized factors regarding causes of errors were incorporated into a quantitative Likert-type scale, and the original expert panel participants were queried a second time to validate responses. The list identified 24 items as most common causes of nursing errors, including swamping and errors made by others that nurses are expected to recognize and fix. The responses provided a consensus top 10 errors list based on means with heavy workload and fatigue at the top of the list. The use of the Delphi survey established consensus and developed a platform upon which future study of nursing errors can evolve as a link to future solutions. This list of human factors in nursing errors should serve to stimulate dialogue among nurses about how to prevent errors and improve outcomes. Human and system failures have been the subject of an abundance of research, yet nursing errors continue to occur. © 2016 Wiley Periodicals, Inc.

Error-related negativities elicited by monetary loss and cues that predict loss.

PubMed

Dunning, Jonathan P; Hajcak, Greg

2007-11-19

Event-related potential studies have reported error-related negativity following both error commission and feedback indicating errors or monetary loss. The present study examined whether error-related negativities could be elicited by a predictive cue presented prior to both the decision and subsequent feedback in a gambling task. Participants were presented with a cue that indicated the probability of reward on the upcoming trial (0, 50, and 100%). Results showed a negative deflection in the event-related potential in response to loss cues compared with win cues; this waveform shared a similar latency and morphology with the traditional feedback error-related negativity.

Decision-making, financial risk aversion, and behavioral biases: The role of testosterone and stress.

PubMed

Nofsinger, John R; Patterson, Fernando M; Shank, Corey A

2018-05-01

We examine the relation between testosterone, cortisol, and financial decisions in a sample of naïve investors. We find that testosterone level is positively related to excess risk-taking, whereas cortisol level is negatively related to excess risk-taking (correlation coefficient [r]: 0.75 and -0.21, respectively). Additionally, we find support for the dual-hormone hypothesis in a financial context. Specifically, the testosterone-to-cortisol ratio is significantly related to loss aversion. Individuals with a higher ratio are 3.4 times more likely to sell losing stocks (standard error [SE]: 1.63). Furthermore, we find a positive feedback loop between financial success, testosterone, and cortisol. Specifically, financial success is significantly related to higher post-trial testosterone and cortisol by a factor of 0.53 (SE: 0.14). Finally, we find that in a competitive environment, testosterone level increases significantly, leading to greater risk-taking than in noncompetitive environment. Overall, this study underscores the importance of the endocrine system on financial decision-making. The results of this study are relevant to a broad audience, including investors looking to optimize financial performance, industry human resources, market regulators, and researchers. Copyright © 2018 Elsevier B.V. All rights reserved.

Visual attention in a complex search task differs between honeybees and bumblebees.

PubMed

Morawetz, Linde; Spaethe, Johannes

2012-07-15

Mechanisms of spatial attention are used when the amount of gathered information exceeds processing capacity. Such mechanisms have been proposed in bees, but have not yet been experimentally demonstrated. We provide evidence that selective attention influences the foraging performance of two social bee species, the honeybee Apis mellifera and the bumblebee Bombus terrestris. Visual search tasks, originally developed for application in human psychology, were adapted for behavioural experiments on bees. We examined the impact of distracting visual information on search performance, which we measured as error rate and decision time. We found that bumblebees were significantly less affected by distracting objects than honeybees. Based on the results, we conclude that the search mechanism in honeybees is serial like, whereas in bumblebees it shows the characteristics of a restricted parallel-like search. Furthermore, the bees differed in their strategy to solve the speed-accuracy trade-off. Whereas bumblebees displayed slow but correct decision-making, honeybees exhibited fast and inaccurate decision-making. We propose two neuronal mechanisms of visual information processing that account for the different responses between honeybees and bumblebees, and we correlate species-specific features of the search behaviour to differences in habitat and life history.

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.

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.

FRamework Assessing Notorious Contributing Influences for Error (FRANCIE): Perspective on Taxonomy Development to Support Error Reporting and Analysis

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

Lon N. Haney; David I. Gertman

2003-04-01

Beginning in the 1980s a primary focus of human reliability analysis was estimation of human error probabilities. However, detailed qualitative modeling with comprehensive representation of contextual variables often was lacking. This was likely due to the lack of comprehensive error and performance shaping factor taxonomies, and the limited data available on observed error rates and their relationship to specific contextual variables. In the mid 90s Boeing, America West Airlines, NASA Ames Research Center and INEEL partnered in a NASA sponsored Advanced Concepts grant to: assess the state of the art in human error analysis, identify future needs for human errormore » analysis, and develop an approach addressing these needs. Identified needs included the need for a method to identify and prioritize task and contextual characteristics affecting human reliability. Other needs identified included developing comprehensive taxonomies to support detailed qualitative modeling and to structure meaningful data collection efforts across domains. A result was the development of the FRamework Assessing Notorious Contributing Influences for Error (FRANCIE) with a taxonomy for airline maintenance tasks. The assignment of performance shaping factors to generic errors by experts proved to be valuable to qualitative modeling. Performance shaping factors and error types from such detailed approaches can be used to structure error reporting schemes. In a recent NASA Advanced Human Support Technology grant FRANCIE was refined, and two new taxonomies for use on space missions were developed. The development, sharing, and use of error taxonomies, and the refinement of approaches for increased fidelity of qualitative modeling is offered as a means to help direct useful data collection strategies.« less

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.

GY SAMPLING THEORY IN ENVIRONMENTAL STUDIES 2: SUBSAMPLING ERROR MEASUREMENTS

EPA Science Inventory

Sampling can be a significant source of error in the measurement process. The characterization and cleanup of hazardous waste sites require data that meet site-specific levels of acceptable quality if scientifically supportable decisions are to be made. In support of this effort,...

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

They all do it, will you? Event-related potential evidence of herding behavior in online peer-to-peer lending.

PubMed

Yu, Haihong; Dan, MengHan; Ma, Qingguo; Jin, Jia

2018-05-14

As herding is a typical characteristic of human behavior, many researchers have found the existence of herding behavior in online peer-to-peer lending through empirical surveys. However, the underlying neural basis of this phenomenon is still unclear. In the current study, we studied the neural activities of herding at decision-making stage and feedback stage using event-related potentials (ERPs). Our results showed that at decision-making stage, larger error related negativity (ERN) amplitude was induced under low-proportion conditions than that of high-proportion conditions. Meanwhile, during feedback stage, negative feedback elicited larger feedback related negativity (FRN) amplitude than that of positive feedback under low-proportion conditions, however, there was no significant FRN difference under high-proportion conditions. The current study suggests that herding behavior in online peer-to-peer lending is related to individual's risk perception and is possible to avoid negative emotions brought by failed investments. Copyright © 2018 Elsevier B.V. All rights reserved.

Neural correlates of reinforcement learning and social preferences in competitive bidding.

PubMed

van den Bos, Wouter; Talwar, Arjun; McClure, Samuel M

2013-01-30

In competitive social environments, people often deviate from what rational choice theory prescribes, resulting in losses or suboptimal monetary gains. We investigate how competition affects learning and decision-making in a common value auction task. During the experiment, groups of five human participants were simultaneously scanned using MRI while playing the auction task. We first demonstrate that bidding is well characterized by reinforcement learning with biased reward representations dependent on social preferences. Indicative of reinforcement learning, we found that estimated trial-by-trial prediction errors correlated with activity in the striatum and ventromedial prefrontal cortex. Additionally, we found that individual differences in social preferences were related to activity in the temporal-parietal junction and anterior insula. Connectivity analyses suggest that monetary and social value signals are integrated in the ventromedial prefrontal cortex and striatum. Based on these results, we argue for a novel mechanistic account for the integration of reinforcement history and social preferences in competitive decision-making.

A usability study of CPOE's medication administration functions: impact on physician-nurse cooperation.

PubMed

Beuscart-Zéphir, Marie Catherine; Pelayo, Sylvia; Degoulet, Patrice; Anceaux, Françoise; Guerlinger, Sandra; Meaux, Jean-Jacques

2004-01-01

Implementation of CPOE systems in Healthcare Institutions has proven efficient in reducing medication errors but it also induces hidden side-effects on Doctor-Nurse cooperation. We propose a usability engineering approach to this problem. An extensive activity analysis of the medication ordering and administration process was performed in several departments of 3 different hospitals. Two of these hospitals are still using paper-based orders, while the 3rd one is in the roll-out phase of medication functions of its CPOE system. We performed a usability assessment of this CPOE system. The usability assessment uncovered usability problems for the entry of medication administration time scheduling by the physician and revealed that the information can be ambiguous for the nurse. The comparison of cooperation models in both situation shows that users tend to adopt a distributed decision making paradigm in the paper-based situation, while the CPOE system supports a centralized decision making process. This analysis can support recommendation for the re-engineering of the Human-Computer Interface.

Can we improve patient safety?

PubMed

Corbally, Martin Thomas

2014-01-01

Despite greater awareness of patient safety issues especially in the operating room and the widespread implementation of surgical time out World Health Organization (WHO), errors, especially wrong site surgery, continue. Most such errors are due to lapses in communication where decision makers fail to consult or confirm operative findings but worryingly where parental concerns over the planned procedure are ignored or not followed through. The WHO Surgical Pause/Time Out aims to capture these errors and prevent them, but the combination of human error and complex hospital environments can overwhelm even robust safety structures and simple common sense. Parents are the ultimate repository of information on their child's condition and planned surgery but are traditionally excluded from the process of Surgical Pause and Time Out, perhaps to avoid additional stress. In addition, surgeons, like pilots, are subject to the phenomenon of "plan-continue-fail" with potentially disastrous outcomes. If we wish to improve patient safety during surgery and avoid wrong site errors then we must include parents in the Surgical Pause/Time Out. A recent pilot study has shown that neither staff nor parents found it added to their stress, but, moreover, 100% of parents considered that it should be a mandatory component of the Surgical Pause nor does it add to the stress of surgery. Surgeons should be required to confirm that the planned procedure is in keeping with the operative findings especially in extirpative surgery and this "step back" should be incorporated into the standard Surgical Pause. It is clear that we must improve patient safety further and these simple measures should add to that potential.

Predicting diagnostic error in Radiology via eye-tracking and image analytics: Application in mammography

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

Voisin, Sophie; Pinto, Frank M; Morin-Ducote, Garnetta

2013-01-01

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels. Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from 4 Radiology residents and 2 breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADsmore » images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated. Results: Diagnostic error can be predicted reliably by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model (AUC=0.79). Personalized user modeling was far more accurate for the more experienced readers (average AUC of 0.837 0.029) than for the less experienced ones (average AUC of 0.667 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features. Conclusions: Diagnostic errors in mammography can be predicted reliably by leveraging the radiologists gaze behavior and image content.« less

Analysis of measured data of human body based on error correcting frequency

NASA Astrophysics Data System (ADS)

Jin, Aiyan; Peipei, Gao; Shang, Xiaomei

2014-04-01

Anthropometry is to measure all parts of human body surface, and the measured data is the basis of analysis and study of the human body, establishment and modification of garment size and formulation and implementation of online clothing store. In this paper, several groups of the measured data are gained, and analysis of data error is gotten by analyzing the error frequency and using analysis of variance method in mathematical statistics method. Determination of the measured data accuracy and the difficulty of measured parts of human body, further studies of the causes of data errors, and summarization of the key points to minimize errors possibly are also mentioned in the paper. This paper analyses the measured data based on error frequency, and in a way , it provides certain reference elements to promote the garment industry development.

Integrity management of offshore structures and its implication on computation of structural action effects and resistance

NASA Astrophysics Data System (ADS)

Moan, T.

2017-12-01

An overview of integrity management of offshore structures, with emphasis on the oil and gas energy sector, is given. Based on relevant accident experiences and means to control the associated risks, accidents are categorized from a technical-physical as well as human and organizational point of view. Structural risk relates to extreme actions as well as structural degradation. Risk mitigation measures, including adequate design criteria, inspection, repair and maintenance as well as quality assurance and control of engineering processes, are briefly outlined. The current status of risk and reliability methodology to aid decisions in the integrity management is briefly reviewed. Finally, the need to balance the uncertainties in data, methods and computational efforts and the cautious use and quality assurance and control in applying high fidelity methods to avoid human errors, is emphasized, and with a plea to develop both high fidelity as well as efficient, simplified methods for design.

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

A Study on Generic Representation of Skeletal Remains Replication of Prehistoric Burial

NASA Astrophysics Data System (ADS)

Shao, C.-W.; Chiu, H.-L.; Chang, S.-K.

2015-08-01

Generic representation of skeletal remains from burials consists of three dimensions which include physical anthropologists, replication technicians, and promotional educators. For the reason that archaeological excavation is irreversible and disruptive, detail documentation and replication technologies are surely needed for many purposes. Unearthed bones during the process of 3D digital scanning need to go through reverse procedure, 3D scanning, digital model superimposition, rapid prototyping, mould making, and the integrated errors generated from the presentation of colours and textures are important issues for the presentation of replicate skeleton remains among professional decisions conducted by physical anthropologists, subjective determination of makers, and the expectations of viewers. This study presents several cases and examines current issues on display and replication technologies for human skeletal remains of prehistoric burials. This study documented detail colour changes of human skeleton over time for the reference of reproduction. The tolerance errors of quantification and required technical qualification is acquired according to the precision of 3D scanning, the specification requirement of rapid prototyping machine, and the mould making process should following the professional requirement for physical anthropological study. Additionally, the colorimeter is adopted to record and analyse the "colour change" of the human skeletal remains from wet to dry condition. Then, the "colure change" is used to evaluate the "real" surface texture and colour presentation of human skeletal remains, and to limit the artistic presentation among the human skeletal remains reproduction. The"Lingdao man No.1", is a well preserved burial of early Neolithic period (8300 B.P.) excavated from Liangdao-Daowei site, Matsu, Taiwan , as the replicating object for this study. In this study, we examined the reproduction procedures step by step for ensuring the surface texture and colour of the replica matches the real human skeletal remains when discovered. The "colour change" of the skeleton documented and quantified in this study could be the reference for the future study and educational exhibition of human skeletal remain reproduction.

Application of human reliability analysis to nursing errors in hospitals.

PubMed

Inoue, Kayoko; Koizumi, Akio

2004-12-01

Adverse events in hospitals, such as in surgery, anesthesia, radiology, intensive care, internal medicine, and pharmacy, are of worldwide concern and it is important, therefore, to learn from such incidents. There are currently no appropriate tools based on state-of-the art models available for the analysis of large bodies of medical incident reports. In this study, a new model was developed to facilitate medical error analysis in combination with quantitative risk assessment. This model enables detection of the organizational factors that underlie medical errors, and the expedition of decision making in terms of necessary action. Furthermore, it determines medical tasks as module practices and uses a unique coding system to describe incidents. This coding system has seven vectors for error classification: patient category, working shift, module practice, linkage chain (error type, direct threat, and indirect threat), medication, severity, and potential hazard. Such mathematical formulation permitted us to derive two parameters: error rates for module practices and weights for the aforementioned seven elements. The error rate of each module practice was calculated by dividing the annual number of incident reports of each module practice by the annual number of the corresponding module practice. The weight of a given element was calculated by the summation of incident report error rates for an element of interest. This model was applied specifically to nursing practices in six hospitals over a year; 5,339 incident reports with a total of 63,294,144 module practices conducted were analyzed. Quality assurance (QA) of our model was introduced by checking the records of quantities of practices and reproducibility of analysis of medical incident reports. For both items, QA guaranteed legitimacy of our model. Error rates for all module practices were approximately of the order 10(-4) in all hospitals. Three major organizational factors were found to underlie medical errors: "violation of rules" with a weight of 826 x 10(-4), "failure of labor management" with a weight of 661 x 10(-4), and "defects in the standardization of nursing practices" with a weight of 495 x 10(-4).

Tailoring a Human Reliability Analysis to Your Industry Needs

NASA Technical Reports Server (NTRS)

DeMott, D. L.

2016-01-01

Companies at risk of accidents caused by human error that result in catastrophic consequences include: airline industry mishaps, medical malpractice, medication mistakes, aerospace failures, major oil spills, transportation mishaps, power production failures and manufacturing facility incidents. Human Reliability Assessment (HRA) is used to analyze the inherent risk of human behavior or actions introducing errors into the operation of a system or process. These assessments can be used to identify where errors are most likely to arise and the potential risks involved if they do occur. Using the basic concepts of HRA, an evolving group of methodologies are used to meet various industry needs. Determining which methodology or combination of techniques will provide a quality human reliability assessment is a key element to developing effective strategies for understanding and dealing with risks caused by human errors. There are a number of concerns and difficulties in "tailoring" a Human Reliability Assessment (HRA) for different industries. Although a variety of HRA methodologies are available to analyze human error events, determining the most appropriate tools to provide the most useful results can depend on industry specific cultures and requirements. Methodology selection may be based on a variety of factors that include: 1) how people act and react in different industries, 2) expectations based on industry standards, 3) factors that influence how the human errors could occur such as tasks, tools, environment, workplace, support, training and procedure, 4) type and availability of data, 5) how the industry views risk & reliability, and 6) types of emergencies, contingencies and routine tasks. Other considerations for methodology selection should be based on what information is needed from the assessment. If the principal concern is determination of the primary risk factors contributing to the potential human error, a more detailed analysis method may be employed versus a requirement to provide a numerical value as part of a probabilistic risk assessment. Industries involved with humans operating large equipment or transport systems (ex. railroads or airlines) would have more need to address the man machine interface than medical workers administering medications. Human error occurs in every industry; in most cases the consequences are relatively benign and occasionally beneficial. In cases where the results can have disastrous consequences, the use of Human Reliability techniques to identify and classify the risk of human errors allows a company more opportunities to mitigate or eliminate these types of risks and prevent costly tragedies.

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.

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.

How to Cope with Gauss's Errors? Motivation for Teaching Data and Uncertainty Analysis from a History of Science Perspective

ERIC Educational Resources Information Center

Heinicke, Susanne

2014-01-01

Every measurement in science, every experimental decision, result and information drawn from it has to cope with something that has long been named by the term "error". In fact, errors describe our limitations when it comes to experimental science and science looks back on a long tradition to cope with them. The widely known way to cope…

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.

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…

File Assignment in a Central Server Computer Network.

DTIC Science & Technology

1979-01-01

somewhat artificial for many applications. Sometimes important variables must be known in advance when they are more appropriately decision variables... intellegently , we must have some notion of the errors that may be introduced. We must account for two types of er:ors. The first is the error

Cognitive science and the law.

PubMed

Busey, Thomas A; Loftus, Geoffrey R

2007-03-01

Numerous innocent people have been sent to jail based directly or indirectly on normal, but flawed, human perception, memory and decision making. Current cognitive-science research addresses the issues that are directly relevant to the connection between normal cognitive functioning and such judicial errors, and suggests means by which the false-conviction rate could be reduced. Here, we illustrate how this can be achieved by reviewing recent work in two related areas: eyewitness testimony and fingerprint analysis. We articulate problems in these areas with reference to specific legal cases and demonstrate how recent findings can be used to address them. We also discuss how researchers can translate their conclusions into language and ideas that can influence and improve the legal system.

Visual detection following retinal damage: predictions of an inhomogeneous retino-cortical model

NASA Astrophysics Data System (ADS)

Arnow, Thomas L.; Geisler, Wilson S.

1996-04-01

A model of human visual detection performance has been developed, based on available anatomical and physiological data for the primate visual system. The inhomogeneous retino- cortical (IRC) model computes detection thresholds by comparing simulated neural responses to target patterns with responses to a uniform background of the same luminance. The model incorporates human ganglion cell sampling distributions; macaque monkey ganglion cell receptive field properties; macaque cortical cell contrast nonlinearities; and a optical decision rule based on ideal observer theory. Spatial receptive field properties of cortical neurons were not included. Two parameters were allowed to vary while minimizing the squared error between predicted and observed thresholds. One parameter was decision efficiency, the other was the relative strength of the ganglion-cell center and surround. The latter was only allowed to vary within a small range consistent with known physiology. Contrast sensitivity was measured for sinewave gratings as a function of spatial frequency, target size and eccentricity. Contrast sensitivity was also measured for an airplane target as a function of target size, with and without artificial scotomas. The results of these experiments, as well as contrast sensitivity data from the literature were compared to predictions of the IRC model. Predictions were reasonably good for grating and airplane targets.

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

Design Study of an Incinerator Ash Conveyor Counting System - 13323

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

Jaederstroem, Henrik; Bronson, Frazier

A design study has been performed for a system that should measure the Cs-137 activity in ash from an incinerator. Radioactive ash, expected to consist of both Cs-134 and Cs-137, will be transported on a conveyor belt at 0.1 m/s. The objective of the counting system is to determine the Cs-137 activity and direct the ash to the correct stream after a diverter. The decision levels are ranging from 8000 to 400000 Bq/kg and the decision error should be as low as possible. The decision error depends on the total measurement uncertainty which depends on the counting statistics and themore » uncertainty in the efficiency of the geometry. For the low activity decision it is necessary to know the efficiency to be able to determine if the signal from the Cs-137 is above the minimum detectable activity and that it generates enough counts to reach the desired precision. For the higher activity decision the uncertainty of the efficiency needs to be understood to minimize decision errors. The total efficiency of the detector is needed to be able to determine if the detector will be able operate at the count rate at the highest expected activity. The design study that is presented in this paper describes how the objectives of the monitoring systems were obtained, the choice of detector was made and how ISOCS (In Situ Object Counting System) mathematical modeling was used to calculate the efficiency. The ISOCS uncertainty estimator (IUE) was used to determine which parameters of the ash was important to know accurately in order to minimize the uncertainty of the efficiency. The examined parameters include the height of the ash on the conveyor belt, the matrix composition and density and relative efficiency of the detector. (authors)« less

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.

The Communication Link and Error ANalysis (CLEAN) simulator

NASA Technical Reports Server (NTRS)

Ebel, William J.; Ingels, Frank M.; Crowe, Shane

1993-01-01

During the period July 1, 1993 through December 30, 1993, significant developments to the Communication Link and Error ANalysis (CLEAN) simulator were completed and include: (1) Soft decision Viterbi decoding; (2) node synchronization for the Soft decision Viterbi decoder; (3) insertion/deletion error programs; (4) convolutional encoder; (5) programs to investigate new convolutional codes; (6) pseudo-noise sequence generator; (7) soft decision data generator; (8) RICE compression/decompression (integration of RICE code generated by Pen-Shu Yeh at Goddard Space Flight Center); (9) Markov Chain channel modeling; (10) percent complete indicator when a program is executed; (11) header documentation; and (12) help utility. The CLEAN simulation tool is now capable of simulating a very wide variety of satellite communication links including the TDRSS downlink with RFI. The RICE compression/decompression schemes allow studies to be performed on error effects on RICE decompressed data. The Markov Chain modeling programs allow channels with memory to be simulated. Memory results from filtering, forward error correction encoding/decoding, differential encoding/decoding, channel RFI, nonlinear transponders and from many other satellite system processes. Besides the development of the simulation, a study was performed to determine whether the PCI provides a performance improvement for the TDRSS downlink. There exist RFI with several duty cycles for the TDRSS downlink. We conclude that the PCI does not improve performance for any of these interferers except possibly one which occurs for the TDRS East. Therefore, the usefulness of the PCI is a function of the time spent transmitting data to the WSGT through the TDRS East transponder.

Medication-related clinical decision support in computerized provider order entry systems: a review.

PubMed

Kuperman, Gilad J; Bobb, Anne; Payne, Thomas H; Avery, Anthony J; Gandhi, Tejal K; Burns, Gerard; Classen, David C; Bates, David W

2007-01-01

While medications can improve patients' health, the process of prescribing them is complex and error prone, and medication errors cause many preventable injuries. Computer provider order entry (CPOE) with clinical decision support (CDS), can improve patient safety and lower medication-related costs. To realize the medication-related benefits of CDS within CPOE, one must overcome significant challenges. Healthcare organizations implementing CPOE must understand what classes of CDS their CPOE systems can support, assure that clinical knowledge underlying their CDS systems is reasonable, and appropriately represent electronic patient data. These issues often influence to what extent an institution will succeed with its CPOE implementation and achieve its desired goals. Medication-related decision support is probably best introduced into healthcare organizations in two stages, basic and advanced. Basic decision support includes drug-allergy checking, basic dosing guidance, formulary decision support, duplicate therapy checking, and drug-drug interaction checking. Advanced decision support includes dosing support for renal insufficiency and geriatric patients, guidance for medication-related laboratory testing, drug-pregnancy checking, and drug-disease contraindication checking. In this paper, the authors outline some of the challenges associated with both basic and advanced decision support and discuss how those challenges might be addressed. The authors conclude with summary recommendations for delivering effective medication-related clinical decision support addressed to healthcare organizations, application and knowledge base vendors, policy makers, and researchers.

The application of SHERPA (Systematic Human Error Reduction and Prediction Approach) in the development of compensatory cognitive rehabilitation strategies for stroke patients with left and right brain damage.

PubMed

Hughes, Charmayne M L; Baber, Chris; Bienkiewicz, Marta; Worthington, Andrew; Hazell, Alexa; Hermsdörfer, Joachim

2015-01-01

Approximately 33% of stroke patients have difficulty performing activities of daily living, often committing errors during the planning and execution of such activities. The objective of this study was to evaluate the ability of the human error identification (HEI) technique SHERPA (Systematic Human Error Reduction and Prediction Approach) to predict errors during the performance of daily activities in stroke patients with left and right hemisphere lesions. Using SHERPA we successfully predicted 36 of the 38 observed errors, with analysis indicating that the proportion of predicted and observed errors was similar for all sub-tasks and severity levels. HEI results were used to develop compensatory cognitive strategies that clinicians could employ to reduce or prevent errors from occurring. This study provides evidence for the reliability and validity of SHERPA in the design of cognitive rehabilitation strategies in stroke populations.

An Analysis of U.S. Army Fratricide Incidents during the Global War on Terror (11 September 2001 to 31 March 2008)

DTIC Science & Technology

2010-03-15

Swiss cheese model of human error causation. ................................................................... 3  2. Results for the classification of...based on Reason’s “ Swiss cheese ” model of human error (1990). Figure 1 describes how an accident is likely to occur when all of the errors, or “holes...align. A detailed description of HFACS can be found in Wiegmann and Shappell (2003). Figure 1. The Swiss cheese model of human error

Operational quality control of daily precipitation using spatio-climatological consistency testing

NASA Astrophysics Data System (ADS)

Scherrer, S. C.; Croci-Maspoli, M.; van Geijtenbeek, D.; Naguel, C.; Appenzeller, C.

2010-09-01

Quality control (QC) of meteorological data is of utmost importance for climate related decisions. The search for an effective automated QC of precipitation data has proven difficult and many weather services still use mainly manual inspection of daily precipitation including MeteoSwiss. However, man power limitations force many weather services to move towards less labour intensive and more automated QC with the challenge to keeping data quality high. In the last decade, several approaches have been presented to objectify daily precipitation QC. Here we present a spatio-climatological approach that will be implemented operationally at MeteoSwiss. It combines the information from the event based spatial distribution of everyday's precipitation field and the historical information of the interpolation error using different precipitation intensity intervals. Expert judgement shows that the system is able to detect potential outliers very well (hardly any missed errors) without creating too many false alarms that need human inspection. 50-80% of all flagged values have been classified as real errors by the data editor. This is much better than the roughly 15-20% using standard spatial regression tests. Very helpful in the QC process is the automatic redistribution of accumulated several day sums. Manual inspection in operations can be reduced and the QC of precipitation objectified substantially.

Building a Lego wall: Sequential action selection.

PubMed

Arnold, Amy; Wing, Alan M; Rotshtein, Pia

2017-05-01

The present study draws together two distinct lines of enquiry into the selection and control of sequential action: motor sequence production and action selection in everyday tasks. Participants were asked to build 2 different Lego walls. The walls were designed to have hierarchical structures with shared and dissociated colors and spatial components. Participants built 1 wall at a time, under low and high load cognitive states. Selection times for correctly completed trials were measured using 3-dimensional motion tracking. The paradigm enabled precise measurement of the timing of actions, while using real objects to create an end product. The experiment demonstrated that action selection was slowed at decision boundary points, relative to boundaries where no between-wall decision was required. Decision points also affected selection time prior to the actual selection window. Dual-task conditions increased selection errors. Errors mostly occurred at boundaries between chunks and especially when these required decisions. The data support hierarchical control of sequenced behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Vectorization of optically sectioned brain microvasculature: learning aids completion of vascular graphs by connecting gaps and deleting open-ended segments.

PubMed

Kaufhold, John P; Tsai, Philbert S; Blinder, Pablo; Kleinfeld, David

2012-08-01

A graph of tissue vasculature is an essential requirement to model the exchange of gasses and nutriments between the blood and cells in the brain. Such a graph is derived from a vectorized representation of anatomical data, provides a map of all vessels as vertices and segments, and may include the location of nonvascular components, such as neuronal and glial somata. Yet vectorized data sets typically contain erroneous gaps, spurious endpoints, and spuriously merged strands. Current methods to correct such defects only address the issue of connecting gaps and further require manual tuning of parameters in a high dimensional algorithm. To address these shortcomings, we introduce a supervised machine learning method that (1) connects vessel gaps by "learned threshold relaxation"; (2) removes spurious segments by "learning to eliminate deletion candidate strands"; and (3) enforces consistency in the joint space of learned vascular graph corrections through "consistency learning." Human operators are only required to label individual objects they recognize in a training set and are not burdened with tuning parameters. The supervised learning procedure examines the geometry and topology of features in the neighborhood of each vessel segment under consideration. We demonstrate the effectiveness of these methods on four sets of microvascular data, each with >800(3) voxels, obtained with all optical histology of mouse tissue and vectorization by state-of-the-art techniques in image segmentation. Through statistically validated sampling and analysis in terms of precision recall curves, we find that learning with bagged boosted decision trees reduces equal-error error rates for threshold relaxation by 5-21% and strand elimination performance by 18-57%. We benchmark generalization performance across datasets; while improvements vary between data sets, learning always leads to a useful reduction in error rates. Overall, learning is shown to more than halve the total error rate, and therefore, human time spent manually correcting such vectorizations. Copyright © 2012 Elsevier B.V. All rights reserved.

Vectorization of optically sectioned brain microvasculature: Learning aids completion of vascular graphs by connecting gaps and deleting open-ended segments

PubMed Central

Kaufhold, John P.; Tsai, Philbert S.; Blinder, Pablo; Kleinfeld, David

2012-01-01

A graph of tissue vasculature is an essential requirement to model the exchange of gasses and nutriments between the blood and cells in the brain. Such a graph is derived from a vectorized representation of anatomical data, provides a map of all vessels as vertices and segments, and may include the location of nonvascular components, such as neuronal and glial somata. Yet vectorized data sets typically contain erroneous gaps, spurious endpoints, and spuriously merged strands. Current methods to correct such defects only address the issue of connecting gaps and further require manual tuning of parameters in a high dimensional algorithm. To address these shortcomings, we introduce a supervised machine learning method that (1) connects vessel gaps by “learned threshold relaxation”; (2) removes spurious segments by “learning to eliminate deletion candidate strands”; and (3) enforces consistency in the joint space of learned vascular graph corrections through “consistency learning.” Human operators are only required to label individual objects they recognize in a training set and are not burdened with tuning parameters. The supervised learning procedure examines the geometry and topology of features in the neighborhood of each vessel segment under consideration. We demonstrate the effectiveness of these methods on four sets of microvascular data, each with > 8003 voxels, obtained with all optical histology of mouse tissue and vectorization by state-of-the-art techniques in image segmentation. Through statistically validated sampling and analysis in terms of precision recall curves, we find that learning with bagged boosted decision trees reduces equal-error error rates for threshold relaxation by 5 to 21 % and strand elimination performance by 18 to 57 %. We benchmark generalization performance across datasets; while improvements vary between data sets, learning always leads to a useful reduction in error rates. Overall, learning is shown to more than halve the total error rate, and therefore, human time spent manually correcting such vectorizations. PMID:22854035

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.

Sleep-Dependent Reductions in Reality-Monitoring Errors Arise from More Conservative Decision Criteria

ERIC Educational Resources Information Center

Westerberg, Carmen E.; Hawkins, Christopher A.; Rendon, Lauren

2018-01-01

Reality-monitoring errors occur when internally generated thoughts are remembered as external occurrences. We hypothesized that sleep-dependent memory consolidation could reduce them by strengthening connections between items and their contexts during an afternoon nap. Participants viewed words and imagined their referents. Pictures of the…

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.

Multi-Gaussian fitting for pulse waveform using Weighted Least Squares and multi-criteria decision making method.

PubMed

Wang, Lu; Xu, Lisheng; Feng, Shuting; Meng, Max Q-H; Wang, Kuanquan

2013-11-01

Analysis of pulse waveform is a low cost, non-invasive method for obtaining vital information related to the conditions of the cardiovascular system. In recent years, different Pulse Decomposition Analysis (PDA) methods have been applied to disclose the pathological mechanisms of the pulse waveform. All these methods decompose single-period pulse waveform into a constant number (such as 3, 4 or 5) of individual waves. Furthermore, those methods do not pay much attention to the estimation error of the key points in the pulse waveform. The estimation of human vascular conditions depends on the key points' positions of pulse wave. In this paper, we propose a Multi-Gaussian (MG) model to fit real pulse waveforms using an adaptive number (4 or 5 in our study) of Gaussian waves. The unknown parameters in the MG model are estimated by the Weighted Least Squares (WLS) method and the optimized weight values corresponding to different sampling points are selected by using the Multi-Criteria Decision Making (MCDM) method. Performance of the MG model and the WLS method has been evaluated by fitting 150 real pulse waveforms of five different types. The resulting Normalized Root Mean Square Error (NRMSE) was less than 2.0% and the estimation accuracy for the key points was satisfactory, demonstrating that our proposed method is effective in compressing, synthesizing and analyzing pulse waveforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Quality Improvement Project to Decrease Human Milk Errors in the NICU.

PubMed

Oza-Frank, Reena; Kachoria, Rashmi; Dail, James; Green, Jasmine; Walls, Krista; McClead, Richard E

2017-02-01

Ensuring safe human milk in the NICU is a complex process with many potential points for error, of which one of the most serious is administration of the wrong milk to the wrong infant. Our objective was to describe a quality improvement initiative that was associated with a reduction in human milk administration errors identified over a 6-year period in a typical, large NICU setting. We employed a quasi-experimental time series quality improvement initiative by using tools from the model for improvement, Six Sigma methodology, and evidence-based interventions. Scanned errors were identified from the human milk barcode medication administration system. Scanned errors of interest were wrong-milk-to-wrong-infant, expired-milk, or preparation errors. The scanned error rate and the impact of additional improvement interventions from 2009 to 2015 were monitored by using statistical process control charts. From 2009 to 2015, the total number of errors scanned declined from 97.1 per 1000 bottles to 10.8. Specifically, the number of expired milk error scans declined from 84.0 per 1000 bottles to 8.9. The number of preparation errors (4.8 per 1000 bottles to 2.2) and wrong-milk-to-wrong-infant errors scanned (8.3 per 1000 bottles to 2.0) also declined. By reducing the number of errors scanned, the number of opportunities for errors also decreased. Interventions that likely had the greatest impact on reducing the number of scanned errors included installation of bedside (versus centralized) scanners and dedicated staff to handle milk. Copyright © 2017 by the American Academy of Pediatrics.

Treatment algorithms and protocolized care.

PubMed

Morris, Alan H

2003-06-01

Excess information in complex ICU environments exceeds human decision-making limits and likely contributes to unnecessary variation in clinical care, increasing the likelihood of clinical errors. I reviewed recent critical care clinical trials searching for information about the impact of protocol use on clinically pertinent outcomes. Several recently published clinical trials illustrate the importance of distinguishing efficacy and effectiveness trials. One of these trials illustrates the danger of conducting effectiveness trials before the efficacy of an intervention is established. The trials also illustrate the importance of distinguishing guidelines and inadequately explicit protocols from adequately explicit protocols. Only adequately explicit protocols contain enough detail to lead different clinicians to the same decision when faced with the same clinical scenario. Differences between guidelines and protocols are important. Guidelines lack detail and provide general guidance that requires clinicians to fill in many gaps. Computerized or paper-based protocols are detailed and, when used for complex clinical ICU problems, can generate patient-specific, evidence-based therapy instructions that can be carried out by different clinicians with almost no interclinician variability. Individualization of patient therapy can be preserved by these protocols when they are driven by individual patient data. Explicit decision-support tools (eg, guidelines and protocols) have favorable effects on clinician and patient outcomes and can reduce the variation in clinical practice. Guidelines and protocols that aid ICU decision makers should be more widely distributed.

Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error

NASA Astrophysics Data System (ADS)

Khair, Ummul; Fahmi, Hasanul; Hakim, Sarudin Al; Rahim, Robbi

2017-12-01

Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to calculate the percentage of mistakes in the least square method resulted in a percentage of 9.77% and it was decided that the least square method be worked for time series and trend data.

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.

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

Human errors and measurement uncertainty

NASA Astrophysics Data System (ADS)

Kuselman, Ilya; Pennecchi, Francesca

2015-04-01

Evaluating the residual risk of human errors in a measurement and testing laboratory, remaining after the error reduction by the laboratory quality system, and quantifying the consequences of this risk for the quality of the measurement/test results are discussed based on expert judgments and Monte Carlo simulations. A procedure for evaluation of the contribution of the residual risk to the measurement uncertainty budget is proposed. Examples are provided using earlier published sets of expert judgments on human errors in pH measurement of groundwater, elemental analysis of geological samples by inductively coupled plasma mass spectrometry, and multi-residue analysis of pesticides in fruits and vegetables. The human error contribution to the measurement uncertainty budget in the examples was not negligible, yet also not dominant. This was assessed as a good risk management result.

Human factors evaluation of remote afterloading brachytherapy: Human error and critical tasks in remote afterloading brachytherapy and approaches for improved system performance. Volume 1

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

Callan, J.R.; Kelly, R.T.; Quinn, M.L.

1995-05-01

Remote Afterloading Brachytherapy (RAB) is a medical process used in the treatment of cancer. RAB uses a computer-controlled device to remotely insert and remove radioactive sources close to a target (or tumor) in the body. Some RAB problems affecting the radiation dose to the patient have been reported and attributed to human error. To determine the root cause of human error in the RAB system, a human factors team visited 23 RAB treatment sites in the US The team observed RAB treatment planning and delivery, interviewed RAB personnel, and performed walk-throughs, during which staff demonstrated the procedures and practices usedmore » in performing RAB tasks. Factors leading to human error in the RAB system were identified. The impact of those factors on the performance of RAB was then evaluated and prioritized in terms of safety significance. Finally, the project identified and evaluated alternative approaches for resolving the safety significant problems related to human error.« less

Increasing reliability of Gauss-Kronrod quadrature by Eratosthenes' sieve method

NASA Astrophysics Data System (ADS)

Adam, Gh.; Adam, S.

2001-04-01

The reliability of the local error estimates returned by the Gauss-Kronrod quadrature rules can be raised up to the theoretical 100% rate of success, under error estimate sharpening, provided a number of natural validating conditions are required. The self-validating scheme of the local error estimates, which is easy to implement and adds little supplementary computing effort, strengthens considerably the correctness of the decisions within the automatic adaptive quadrature.

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection

PubMed Central

Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang

2018-01-01

In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10−5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced. PMID:29342963

Autoimmunity: a decision theory model.

PubMed Central

Morris, J A

1987-01-01

Concepts from statistical decision theory were used to analyse the detection problem faced by the body's immune system in mounting immune responses to bacteria of the normal body flora. Given that these bacteria are potentially harmful, that there can be extensive cross reaction between bacterial antigens and host tissues, and that the decisions are made in uncertainty, there is a finite chance of error in immune response leading to autoimmune disease. A model of ageing in the immune system is proposed that is based on random decay in components of the decision process, leading to a steep age dependent increase in the probability of error. The age incidence of those autoimmune diseases which peak in early and middle life can be explained as the resultant of two processes: an exponentially falling curve of incidence of first contact with common bacteria, and a rapidly rising error function. Epidemiological data on the variation of incidence with social class, sibship order, climate and culture can be used to predict the likely site of carriage and mode of spread of the causative bacteria. Furthermore, those autoimmune diseases precipitated by common viral respiratory tract infections might represent reactions to nasopharyngeal bacterial overgrowth, and this theory can be tested using monoclonal antibodies to search the bacterial isolates for cross reacting antigens. If this model is correct then prevention of autoimmune disease by early exposure to low doses of bacteria might be possible. PMID:3818985

Human error analysis of commercial aviation accidents using the human factors analysis and classification system (HFACS)

DOT National Transportation Integrated Search

2001-02-01

The Human Factors Analysis and Classification System (HFACS) is a general human error framework : originally developed and tested within the U.S. military as a tool for investigating and analyzing the human : causes of aviation accidents. Based upon ...

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

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.

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.

Working Memory Load Strengthens Reward Prediction Errors.

PubMed

Collins, Anne G E; Ciullo, Brittany; Frank, Michael J; Badre, David

2017-04-19

Reinforcement learning (RL) in simple instrumental tasks is usually modeled as a monolithic process in which reward prediction errors (RPEs) are used to update expected values of choice options. This modeling ignores the different contributions of different memory and decision-making systems thought to contribute even to simple learning. In an fMRI experiment, we investigated how working memory (WM) and incremental RL processes interact to guide human learning. WM load was manipulated by varying the number of stimuli to be learned across blocks. Behavioral results and computational modeling confirmed that learning was best explained as a mixture of two mechanisms: a fast, capacity-limited, and delay-sensitive WM process together with slower RL. Model-based analysis of fMRI data showed that striatum and lateral prefrontal cortex were sensitive to RPE, as shown previously, but, critically, these signals were reduced when the learning problem was within capacity of WM. The degree of this neural interaction related to individual differences in the use of WM to guide behavioral learning. These results indicate that the two systems do not process information independently, but rather interact during learning. SIGNIFICANCE STATEMENT Reinforcement learning (RL) theory has been remarkably productive at improving our understanding of instrumental learning as well as dopaminergic and striatal network function across many mammalian species. However, this neural network is only one contributor to human learning and other mechanisms such as prefrontal cortex working memory also play a key role. Our results also show that these other players interact with the dopaminergic RL system, interfering with its key computation of reward prediction errors. Copyright © 2017 the authors 0270-6474/17/374332-11$15.00/0.

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

Diagnostic Error in Stroke-Reasons and Proposed Solutions.

PubMed

Bakradze, Ekaterina; Liberman, Ava L

2018-02-13

We discuss the frequency of stroke misdiagnosis and identify subgroups of stroke at high risk for specific diagnostic errors. In addition, we review common reasons for misdiagnosis and propose solutions to decrease error. According to a recent report by the National Academy of Medicine, most people in the USA are likely to experience a diagnostic error during their lifetimes. Nearly half of such errors result in serious disability and death. Stroke misdiagnosis is a major health care concern, with initial misdiagnosis estimated to occur in 9% of all stroke patients in the emergency setting. Under- or missed diagnosis (false negative) of stroke can result in adverse patient outcomes due to the preclusion of acute treatments and failure to initiate secondary prevention strategies. On the other hand, the overdiagnosis of stroke can result in inappropriate treatment, delayed identification of actual underlying disease, and increased health care costs. Young patients, women, minorities, and patients presenting with non-specific, transient, or posterior circulation stroke symptoms are at increased risk of misdiagnosis. Strategies to decrease diagnostic error in stroke have largely focused on early stroke detection via bedside examination strategies and a clinical decision rules. Targeted interventions to improve the diagnostic accuracy of stroke diagnosis among high-risk groups as well as symptom-specific clinical decision supports are needed. There are a number of open questions in the study of stroke misdiagnosis. To improve patient outcomes, existing strategies to improve stroke diagnostic accuracy should be more broadly adopted and novel interventions devised and tested to reduce diagnostic errors.

Design of a digital voice data compression technique for orbiter voice channels

NASA Technical Reports Server (NTRS)

1975-01-01

Candidate techniques were investigated for digital voice compression to a transmission rate of 8 kbps. Good voice quality, speaker recognition, and robustness in the presence of error bursts were considered. The technique of delayed-decision adaptive predictive coding is described and compared with conventional adaptive predictive coding. Results include a set of experimental simulations recorded on analog tape. The two FM broadcast segments produced show the delayed-decision technique to be virtually undegraded or minimally degraded at .001 and .01 Viterbi decoder bit error rates. Preliminary estimates of the hardware complexity of this technique indicate potential for implementation in space shuttle orbiters.

Decision feedback equalizer for holographic data storage.

PubMed

Kim, Kyuhwan; Kim, Seung Hun; Koo, Gyogwon; Seo, Min Seok; Kim, Sang Woo

2018-05-20

Holographic data storage (HDS) has attracted much attention as a next-generation storage medium. Because HDS suffers from two-dimensional (2D) inter-symbol interference (ISI), the partial-response maximum-likelihood (PRML) method has been studied to reduce 2D ISI. However, the PRML method has various drawbacks. To solve the problems, we propose a modified decision feedback equalizer (DFE) for HDS. To prevent the error propagation problem, which is a typical problem in DFEs, we also propose a reliability factor for HDS. Various simulations were executed to analyze the performance of the proposed methods. The proposed methods showed fast processing speed after training, superior bit error rate performance, and consistency.

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.

Optimal threshold of error decision related to non-uniform phase distribution QAM signals generated from MZM based on OCS

NASA Astrophysics Data System (ADS)

Han, Xifeng; Zhou, Wen

2018-03-01

Optical vector radio-frequency (RF) signal generation based on optical carrier suppression (OCS) in one Mach-Zehnder modulator (MZM) can realize frequency-doubling. In order to match the phase or amplitude of the recovered quadrature amplitude modulation (QAM) signal, phase or amplitude pre-coding is necessary in the transmitter side. The detected QAM signals usually have one non-uniform phase distribution after square-law detection at the photodiode because of the imperfect characteristics of the optical and electrical devices. We propose to use optimal threshold of error decision for non-uniform phase contribution to reduce the bit error rate (BER). By employing this scheme, the BER of 16 Gbaud (32 Gbit/s) quadrature-phase-shift-keying (QPSK) millimeter wave signal at 36 GHz is improved from 1 × 10-3 to 1 × 10-4 at - 4 . 6 dBm input power into the photodiode.

Compound Stimulus Presentation Does Not Deepen Extinction in Human Causal Learning

PubMed Central

Griffiths, Oren; Holmes, Nathan; Westbrook, R. Fred

2017-01-01

Models of associative learning have proposed that cue-outcome learning critically depends on the degree of prediction error encountered during training. Two experiments examined the role of error-driven extinction learning in a human causal learning task. Target cues underwent extinction in the presence of additional cues, which differed in the degree to which they predicted the outcome, thereby manipulating outcome expectancy and, in the absence of any change in reinforcement, prediction error. These prediction error manipulations have each been shown to modulate extinction learning in aversive conditioning studies. While both manipulations resulted in increased prediction error during training, neither enhanced extinction in the present human learning task (one manipulation resulted in less extinction at test). The results are discussed with reference to the types of associations that are regulated by prediction error, the types of error terms involved in their regulation, and how these interact with parameters involved in training. PMID:28232809

Error rate information in attention allocation pilot models

NASA Technical Reports Server (NTRS)

Faulkner, W. H.; Onstott, E. D.

1977-01-01

The Northrop urgency decision pilot model was used in a command tracking task to compare the optimized performance of multiaxis attention allocation pilot models whose urgency functions were (1) based on tracking error alone, and (2) based on both tracking error and error rate. A matrix of system dynamics and command inputs was employed, to create both symmetric and asymmetric two axis compensatory tracking tasks. All tasks were single loop on each axis. Analysis showed that a model that allocates control attention through nonlinear urgency functions using only error information could not achieve performance of the full model whose attention shifting algorithm included both error and error rate terms. Subsequent to this analysis, tracking performance predictions for the full model were verified by piloted flight simulation. Complete model and simulation data are presented.

Measurements and Characterizations of Mechanical Properties of Human Skins

NASA Astrophysics Data System (ADS)

Song, Han Wook; Park, Yon Kyu

A skin is an indispensible organ for humans because it contributes to metabolism using its own biochemical functions and protects the human body from external stimuli. Recently, mechanical properties such as a thickness, a friction and an elastic coefficient have been used as a decision index in the skin physiology and in the skin care market due to the increased awareness of wellbeing issues. In addition, the use of mechanical properties is known to have good discrimination ability in the classification of human constitutions, which are used in the field of an alternative medicine. In this study, a system that measures mechanical properties such as a friction and an elastic coefficient is designed. The equipment consists of a load cell type (manufactured by the authors) for the measurements of a friction coefficient, a decompression tube for the measurement of an elastic coefficient. Using the proposed system, the mechanical properties of human skins from different constitutions were compared, and the relative repeatability error for measurements of mechanical properties was determined to be less than 2%. Combining the inspection results of medical doctors in the field of an alternative medicine, we could conclude that the proposed system might be applicable to a quantitative constitutional diagnosis between human constitutions within an acceptable level of uncertainty.

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…

Reducing Diagnostic Error with Computer-Based Clinical Decision Support

ERIC Educational Resources Information Center

Greenes, Robert A.

2009-01-01

Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

Applying Recursive Sensitivity Analysis to Multi-Criteria Decision Models to Reduce Bias in Defense Cyber Engineering Analysis

DTIC Science & Technology

2015-10-28

techniques such as regression analysis, correlation, and multicollinearity assessment to identify the change and error on the input to the model...between many of the independent or predictor variables, the issue of multicollinearity may arise [18]. VII. SUMMARY Accurate decisions concerning

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…

20 CFR 404.942 - Prehearing proceedings and decisions by attorney advisors.

Code of Federal Regulations, 2010 CFR

2010-04-01

...-AGE, SURVIVORS AND DISABILITY INSURANCE (1950- ) Determinations, Administrative Review Process, and...) There is an error in the file or some other indication that a fully favorable decision may be issued. (c... additional evidence that may be relevant to the claim, including medical evidence; and (2) If necessary to...

20 CFR 404.942 - Prehearing proceedings and decisions by attorney advisors.

Code of Federal Regulations, 2011 CFR

2011-04-01

...-AGE, SURVIVORS AND DISABILITY INSURANCE (1950- ) Determinations, Administrative Review Process, and...) There is an error in the file or some other indication that a fully favorable decision may be issued. (c... additional evidence that may be relevant to the claim, including medical evidence; and (2) If necessary to...

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…

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...

A framework for simulating map error in ecosystem models

Treesearch

Sean P. Healey; Shawn P. Urbanski; Paul L. Patterson; Chris Garrard

2014-01-01

The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader...

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…

Diagnosis of Cognitive Errors by Statistical Pattern Recognition Methods.

ERIC Educational Resources Information Center

Tatsuoka, Kikumi K.; Tatsuoka, Maurice M.

The rule space model permits measurement of cognitive skill acquisition, diagnosis of cognitive errors, and detection of the strengths and weaknesses of knowledge possessed by individuals. Two ways to classify an individual into his or her most plausible latent state of knowledge include: (1) hypothesis testing--Bayes' decision rules for minimum…

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…

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.

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

Human errors and occupational injuries of older female workers in the residential healthcare facilities for the elderly.

PubMed

Kim, Jun Sik; Jeong, Byung Yong

2018-05-03

The study aimed to describe the characteristics of occupational injuries of female workers in the residential healthcare facilities for the elderly, and analyze human errors as causes of accidents. From the national industrial accident compensation data, 506 female injuries were analyzed by age and occupation. The results showed that medical service worker was the most prevalent (54.1%), followed by social welfare worker (20.4%). Among injuries, 55.7% were <1 year of work experience, and 37.9% were ≥60 years old. Slips/falls were the most common type of accident (42.7%), and proportion of injured by slips/falls increases with age. Among human errors, action errors were the primary reasons, followed by perception errors, and cognition errors. Besides, the ratios of injuries by perception errors and action errors increase with age, respectively. The findings of this study suggest that there is a need to design workplaces that accommodate the characteristics of older female workers.

Performance Effects of Display Incogruity in a Digital and Analog Clock Reading Task

NASA Technical Reports Server (NTRS)

Comstock, J. Raymond, Jr.; Derks, Peter L.

2004-01-01

In an era of increasing automation, it is important to design displays and input devices that minimize human error. In this context, information concerning the human response to the detection of incongruous information is important. Such incongruous information can be operationalized as unexpected (perhaps erroneous) information on which a decision by the human or operation by an automated system is based. In the aviation environment, decision making when faced with inadequate, incomplete, or incongruous information may occur in a failure scenario. An additional challenge facing the human operator in automated environments is maintaining alertness or vigilance. The vigilance issue is of particular concern as a factor that may interact with performance when faced with inadequate, incomplete, or incongruous information. From the literature on eye-scan behavior we know that the time spent looking at a particular display or indicator is a function of the type of information one is trying to discern from the display. For example, quick glances are all it takes for confirming that an indicator is in a normal position or range, whereas a continuous look of several seconds may be required for confirmation that a complex control input is having the desired effect. Important to consider is that while an extended look takes place, visual input from other sources may be missed. Much like an extended look, the interpretation of incongruous information may require extra time. The present experiment was designed to explore the performance consequences of a decision making task when incongruous information was presented. For this experiment a display incongruity was created on a subset of trials of a clock reading laboratory task. Display incongruity was made possible through presentation of 'impossible' times (e.g. 1:65 or 11:90). Subjects made 'same' 'different' decisions and keyboard responses to pairings of Analog-Analog (AA), Digital-Digital (DD), and Analog- Digital (AD), display combinations. For trials during which display incongruities were not presented, based on prior research comparing digital and analog clock displays, it would be expected that the Digital-Digital condition would result in the shortest response times and the Analog-Analog and Analog-Digital conditions would have longer response times. The performance consequence expected on trials with incongruous times would be very long response times.

Linear and Order Statistics Combiners for Pattern Classification

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Ghosh, Joydeep; Lau, Sonie (Technical Monitor)

2001-01-01

Several researchers have experimentally shown that substantial improvements can be obtained in difficult pattern recognition problems by combining or integrating the outputs of multiple classifiers. This chapter provides an analytical framework to quantify the improvements in classification results due to combining. The results apply to both linear combiners and order statistics combiners. We first show that to a first order approximation, the error rate obtained over and above the Bayes error rate, is directly proportional to the variance of the actual decision boundaries around the Bayes optimum boundary. Combining classifiers in output space reduces this variance, and hence reduces the 'added' error. If N unbiased classifiers are combined by simple averaging. the added error rate can be reduced by a factor of N if the individual errors in approximating the decision boundaries are uncorrelated. Expressions are then derived for linear combiners which are biased or correlated, and the effect of output correlations on ensemble performance is quantified. For order statistics based non-linear combiners, we derive expressions that indicate how much the median, the maximum and in general the i-th order statistic can improve classifier performance. The analysis presented here facilitates the understanding of the relationships among error rates, classifier boundary distributions, and combining in output space. Experimental results on several public domain data sets are provided to illustrate the benefits of combining and to support the analytical results.

Intelligent monitoring of critical pathological events during anesthesia.

PubMed

Gohil, Bhupendra; Gholamhhosseini, Hamid; Harrison, Michael J; Lowe, Andrew; Al-Jumaily, Ahmed

2007-01-01

Expert algorithms in the field of intelligent patient monitoring have rapidly revolutionized patient care thereby improving patient safety. Patient monitoring during anesthesia requires cautious attention by anesthetists who are monitoring many modalities, diagnosing clinically critical events and performing patient management tasks simultaneously. The mishaps that occur during day-to-day anesthesia causing disastrous errors in anesthesia administration were classified and studied by Reason [1]. Human errors in anesthesia account for 82% of the preventable mishaps [2]. The aim of this paper is to develop a clinically useful diagnostic alarm system for detecting critical events during anesthesia administration. The development of an expert diagnostic alarm system called ;RT-SAAM' for detecting critical pathological events in the operating theatre is presented. This system provides decision support to the anesthetist by presenting the diagnostic results on an integrative, ergonomic display and thus enhancing patient safety. The performance of the system was validated through a series of offline and real-time testing in the operation theatre. When detecting absolute hypovolaemia (AHV), moderate level of agreement was observed between RT-SAAM and the human expert (anesthetist) during surgical procedures. RT-SAAM is a clinically useful diagnostic tool which can be easily modified for diagnosing additional critical pathological events like relative hypovolaemia, fall in cardiac output, sympathetic response and malignant hyperpyrexia during surgical procedures. RT-SAAM is currently being tested at the Auckland City Hospital with ethical approval from the local ethics committees.

Impact of Pilot Delay and Non-Responsiveness on the Safety Performance of Airborne Separation

NASA Technical Reports Server (NTRS)

Consiglio, Maria; Hoadley, Sherwood; Wing, David; Baxley, Brian; Allen, Bonnie Danette

2008-01-01

Assessing the safety effects of prediction errors and uncertainty on automationsupported functions in the Next Generation Air Transportation System concept of operations is of foremost importance, particularly safety critical functions such as separation that involve human decision-making. Both ground-based and airborne, the automation of separation functions must be designed to account for, and mitigate the impact of, information uncertainty and varying human response. This paper describes an experiment that addresses the potential impact of operator delay when interacting with separation support systems. In this study, we evaluated an airborne separation capability operated by a simulated pilot. The experimental runs are part of the Safety Performance of Airborne Separation (SPAS) experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assistance systems. Pilot actions required by the airborne separation automation to resolve traffic conflicts were delayed within a wide range, varying from five to 240 seconds while a percentage of randomly selected pilots were programmed to completely miss the conflict alerts and therefore take no action. Results indicate that the strategicAirborne Separation Assistance System (ASAS) functions exercised in the experiment can sustain pilot response delays of up to 90 seconds and more, depending on the traffic density. However, when pilots or operators fail to respond to conflict alerts the safety effects are substantial, particularly at higher traffic densities.

Predicting diagnostic error in radiology via eye-tracking and image analytics: Preliminary investigation in mammography

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

Voisin, Sophie; Tourassi, Georgia D.; Pinto, Frank

2013-10-15

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels.Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS imagesmore » features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated.Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features.Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content.« less

Implicit Value Updating Explains Transitive Inference Performance: The Betasort Model

PubMed Central

Jensen, Greg; Muñoz, Fabian; Alkan, Yelda; Ferrera, Vincent P.; Terrace, Herbert S.

2015-01-01

Transitive inference (the ability to infer that B > D given that B > C and C > D) is a widespread characteristic of serial learning, observed in dozens of species. Despite these robust behavioral effects, reinforcement learning models reliant on reward prediction error or associative strength routinely fail to perform these inferences. We propose an algorithm called betasort, inspired by cognitive processes, which performs transitive inference at low computational cost. This is accomplished by (1) representing stimulus positions along a unit span using beta distributions, (2) treating positive and negative feedback asymmetrically, and (3) updating the position of every stimulus during every trial, whether that stimulus was visible or not. Performance was compared for rhesus macaques, humans, and the betasort algorithm, as well as Q-learning, an established reward-prediction error (RPE) model. Of these, only Q-learning failed to respond above chance during critical test trials. Betasort’s success (when compared to RPE models) and its computational efficiency (when compared to full Markov decision process implementations) suggests that the study of reinforcement learning in organisms will be best served by a feature-driven approach to comparing formal models. PMID:26407227

Implicit Value Updating Explains Transitive Inference Performance: The Betasort Model.

PubMed

Jensen, Greg; Muñoz, Fabian; Alkan, Yelda; Ferrera, Vincent P; Terrace, Herbert S

2015-01-01

Transitive inference (the ability to infer that B > D given that B > C and C > D) is a widespread characteristic of serial learning, observed in dozens of species. Despite these robust behavioral effects, reinforcement learning models reliant on reward prediction error or associative strength routinely fail to perform these inferences. We propose an algorithm called betasort, inspired by cognitive processes, which performs transitive inference at low computational cost. This is accomplished by (1) representing stimulus positions along a unit span using beta distributions, (2) treating positive and negative feedback asymmetrically, and (3) updating the position of every stimulus during every trial, whether that stimulus was visible or not. Performance was compared for rhesus macaques, humans, and the betasort algorithm, as well as Q-learning, an established reward-prediction error (RPE) model. Of these, only Q-learning failed to respond above chance during critical test trials. Betasort's success (when compared to RPE models) and its computational efficiency (when compared to full Markov decision process implementations) suggests that the study of reinforcement learning in organisms will be best served by a feature-driven approach to comparing formal models.

Using the EC decision on case definitions for communicable diseases as a terminology source--lessons learned.

PubMed

Balkanyi, Laszlo; Heja, Gergely; Nagy, Attlia

2014-01-01

Extracting scientifically accurate terminology from an EU public health regulation is part of the knowledge engineering work at the European Centre for Disease Prevention and Control (ECDC). ECDC operates information systems at the crossroads of many areas - posing a challenge for transparency and consistency. Semantic interoperability is based on the Terminology Server (TS). TS value sets (structured vocabularies) describe shared domains as "diseases", "organisms", "public health terms", "geo-entities" "organizations" and "administrative terms" and others. We extracted information from the relevant EC Implementing Decision on case definitions for reporting communicable diseases, listing 53 notifiable infectious diseases, containing clinical, diagnostic, laboratory and epidemiological criteria. We performed a consistency check; a simplification - abstraction; we represented lab criteria in triplets: as 'y' procedural result /of 'x' organism-substance/on 'z' specimen and identified negations. The resulting new case definition value set represents the various formalized criteria, meanwhile the existing disease value set has been extended, new signs and symptoms were added. New organisms enriched the organism value set. Other new categories have been added to the public health value set, as transmission modes; substances; specimens and procedures. We identified problem areas, as (a) some classification error(s); (b) inconsistent granularity of conditions; (c) seemingly nonsense criteria, medical trivialities; (d) possible logical errors, (e) seemingly factual errors that might be phrasing errors. We think our hypothesis regarding room for possible improvements is valid: there are some open issues and a further improved legal text might lead to more precise epidemiologic data collection. It has to be noted that formal representation for automatic classification of cases was out of scope, such a task would require other formalism, as e.g. those used by rule-based decision support systems.

Credit Assignment in a Motor Decision Making Task Is Influenced by Agency and Not Sensory Prediction Errors.

PubMed

Parvin, Darius E; McDougle, Samuel D; Taylor, Jordan A; Ivry, Richard B

2018-05-09

Failures to obtain reward can occur from errors in action selection or action execution. Recently, we observed marked differences in choice behavior when the failure to obtain a reward was attributed to errors in action execution compared with errors in action selection (McDougle et al., 2016). Specifically, participants appeared to solve this credit assignment problem by discounting outcomes in which the absence of reward was attributed to errors in action execution. Building on recent evidence indicating relatively direct communication between the cerebellum and basal ganglia, we hypothesized that cerebellar-dependent sensory prediction errors (SPEs), a signal indicating execution failure, could attenuate value updating within a basal ganglia-dependent reinforcement learning system. Here we compared the SPE hypothesis to an alternative, "top-down" hypothesis in which changes in choice behavior reflect participants' sense of agency. In two experiments with male and female human participants, we manipulated the strength of SPEs, along with the participants' sense of agency in the second experiment. The results showed that, whereas the strength of SPE had no effect on choice behavior, participants were much more likely to discount the absence of rewards under conditions in which they believed the reward outcome depended on their ability to produce accurate movements. These results provide strong evidence that SPEs do not directly influence reinforcement learning. Instead, a participant's sense of agency appears to play a significant role in modulating choice behavior when unexpected outcomes can arise from errors in action execution. SIGNIFICANCE STATEMENT When learning from the outcome of actions, the brain faces a credit assignment problem: Failures of reward can be attributed to poor choice selection or poor action execution. Here, we test a specific hypothesis that execution errors are implicitly signaled by cerebellar-based sensory prediction errors. We evaluate this hypothesis and compare it with a more "top-down" hypothesis in which the modulation of choice behavior from execution errors reflects participants' sense of agency. We find that sensory prediction errors have no significant effect on reinforcement learning. Instead, instructions influencing participants' belief of causal outcomes appear to be the main factor influencing their choice behavior. Copyright © 2018 the authors 0270-6474/18/384521-10$15.00/0.

45 Gb/s low complexity optical front-end for soft-decision LDPC decoders.

PubMed

Sakib, Meer Nazmus; Moayedi, Monireh; Gross, Warren J; Liboiron-Ladouceur, Odile

2012-07-30

In this paper a low complexity and energy efficient 45 Gb/s soft-decision optical front-end to be used with soft-decision low-density parity-check (LDPC) decoders is demonstrated. The results show that the optical front-end exhibits a net coding gain of 7.06 and 9.62 dB for post forward error correction bit error rate of 10(-7) and 10(-12) for long block length LDPC(32768,26803) code. The performance over a hard decision front-end is 1.9 dB for this code. It is shown that the soft-decision circuit can also be used as a 2-bit flash type analog-to-digital converter (ADC), in conjunction with equalization schemes. At bit rate of 15 Gb/s using RS(255,239), LDPC(672,336), (672, 504), (672, 588), and (1440, 1344) used with a 6-tap finite impulse response (FIR) equalizer will result in optical power savings of 3, 5, 7, 9.5 and 10.5 dB, respectively. The 2-bit flash ADC consumes only 2.71 W at 32 GSamples/s. At 45 GSamples/s the power consumption is estimated to be 4.95 W.

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 bottom-up model of spatial attention predicts human error patterns in rapid scene recognition.

PubMed

Einhäuser, Wolfgang; Mundhenk, T Nathan; Baldi, Pierre; Koch, Christof; Itti, Laurent

2007-07-20

Humans demonstrate a peculiar ability to detect complex targets in rapidly presented natural scenes. Recent studies suggest that (nearly) no focal attention is required for overall performance in such tasks. Little is known, however, of how detection performance varies from trial to trial and which stages in the processing hierarchy limit performance: bottom-up visual processing (attentional selection and/or recognition) or top-down factors (e.g., decision-making, memory, or alertness fluctuations)? To investigate the relative contribution of these factors, eight human observers performed an animal detection task in natural scenes presented at 20 Hz. Trial-by-trial performance was highly consistent across observers, far exceeding the prediction of independent errors. This consistency demonstrates that performance is not primarily limited by idiosyncratic factors but by visual processing. Two statistical stimulus properties, contrast variation in the target image and the information-theoretical measure of "surprise" in adjacent images, predict performance on a trial-by-trial basis. These measures are tightly related to spatial attention, demonstrating that spatial attention and rapid target detection share common mechanisms. To isolate the causal contribution of the surprise measure, eight additional observers performed the animal detection task in sequences that were reordered versions of those all subjects had correctly recognized in the first experiment. Reordering increased surprise before and/or after the target while keeping the target and distractors themselves unchanged. Surprise enhancement impaired target detection in all observers. Consequently, and contrary to several previously published findings, our results demonstrate that attentional limitations, rather than target recognition alone, affect the detection of targets in rapidly presented visual sequences.

Following Human Footsteps: Proposal of a Decision Theory Based on Human Behavior

NASA Technical Reports Server (NTRS)

Mahmud, Faisal

2011-01-01

Human behavior is a complex nature which depends on circumstances and decisions varying from time to time as well as place to place. The way a decision is made either directly or indirectly related to the availability of the options. These options though appear at random nature, have a solid directional way for decision making. In this paper, a decision theory is proposed which is based on human behavior. The theory is structured with model sets that will show the all possible combinations for making a decision, A virtual and simulated environment is considered to show the results of the proposed decision theory

Competition between learned reward and error outcome predictions in anterior cingulate cortex.

PubMed

Alexander, William H; Brown, Joshua W

2010-02-15

The anterior cingulate cortex (ACC) is implicated in performance monitoring and cognitive control. Non-human primate studies of ACC show prominent reward signals, but these are elusive in human studies, which instead show mainly conflict and error effects. Here we demonstrate distinct appetitive and aversive activity in human ACC. The error likelihood hypothesis suggests that ACC activity increases in proportion to the likelihood of an error, and ACC is also sensitive to the consequence magnitude of the predicted error. Previous work further showed that error likelihood effects reach a ceiling as the potential consequences of an error increase, possibly due to reductions in the average reward. We explored this issue by independently manipulating reward magnitude of task responses and error likelihood while controlling for potential error consequences in an Incentive Change Signal Task. The fMRI results ruled out a modulatory effect of expected reward on error likelihood effects in favor of a competition effect between expected reward and error likelihood. Dynamic causal modeling showed that error likelihood and expected reward signals are intrinsic to the ACC rather than received from elsewhere. These findings agree with interpretations of ACC activity as signaling both perceptions of risk and predicted reward. Copyright 2009 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).

Temporal uncertainty analysis of human errors based on interrelationships among multiple factors: a case of Minuteman III missile accident.

PubMed

Rong, Hao; Tian, Jin; Zhao, Tingdi

2016-01-01

In traditional approaches of human reliability assessment (HRA), the definition of the error producing conditions (EPCs) and the supporting guidance are such that some of the conditions (especially organizational or managerial conditions) can hardly be included, and thus the analysis is burdened with incomprehensiveness without reflecting the temporal trend of human reliability. A method based on system dynamics (SD), which highlights interrelationships among technical and organizational aspects that may contribute to human errors, is presented to facilitate quantitatively estimating the human error probability (HEP) and its related variables changing over time in a long period. Taking the Minuteman III missile accident in 2008 as a case, the proposed HRA method is applied to assess HEP during missile operations over 50 years by analyzing the interactions among the variables involved in human-related risks; also the critical factors are determined in terms of impact that the variables have on risks in different time periods. It is indicated that both technical and organizational aspects should be focused on to minimize human errors in a long run. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.