Neural correlations between cognitive deficits and emotion regulation strategies:understanding emotion dysregulation in depression from the perspective of cognitive control and cognitive biases

The link between cognitive function and emotion regulation may be helpful in better understanding the onset,maintenance,and treatment for depression.However,it remains unclear whether there are neural correlates between emotion dysregulation and cognitive deficits in depression.To address this question,we first review the neural representations of emotion dysregulation and cognitive deficits in depression(including deficits in cognitive control and cognitive biases).Based on the comparisons of neural representations of emotion dysregulation versus cognitive deficits,we propose an accessible and reasonable link between emotion dysregulation,cognitive control,and cognitive biases in depression.Specifically,cognitive control serves the whole process of emotion regulation,whereas cognitive biases are engaged in emotion regulation processes at different stages.Moreover,the abnormal implementation of different emotion regulation strategies in depression is consistently affected by cognitive control,which is involved in the dorsolateral,the dorsomedial prefrontal cortex,and the anterior cingulate cortex.Besides,the relationship between different emotion regulation strategies and cognitive biases in depression may be distinct:the orbitofrontal cortex contributes to the association between ineffective reappraisal and negative interpretation bias,while the subgenual prefrontal cortex and the posterior cingulate cortex underline the tendency of depressed individuals to ruminate and overly engage in self-referential bias.This review sheds light on the relationship between cognitive deficits and emotion dysregulation in depression and identifies directions in need of future attention.

Appraising the Manifestation of Optimism Bias and Its Impact on Human Perception of Cyber Security: A Meta Analysis

Cyber threats and risks are increasing exponentially with time. For preventing and defense against these threats and risks, precise risk perception for effective mitigation is the first step. Risk perception is necessary requirement to mitigate risk as it drives the security strategy at the organizational level and human attitude at individual level. Sometime, individuals understand there is a risk that a negative event or incident can occur, but they do not believe there will be a personal impact if the risk comes to realization but instead, they believe that the negative event will impact others. This belief supports the common belief that individuals tend to think of themselves as invulnerable, i.e., optimistically bias about the situation, thus affecting their attitude for taking preventive measures due to inappropriate risk perception or overconfidence. The main motivation of this meta-analysis is to assess that how the cyber optimistic bias or cyber optimism bias affects individual’s cyber security risk perception and how it changes their decisions. Applying a meta-analysis, this study found that optimistic bias has an overall negative impact on the cyber security due to the inappropriate risk perception and considering themselves invulnerable by biasing that the threat will not occur to them. Due to the cyber optimism bias, the individual will sometimes share passwords by considering it will not be maliciously used, lack in adopting of preventive measures, ignore security incidents, wrong perception of cyber threats and overconfidence on themselves in the context of cyber security.

Ten misconceptions regarding decision-making in critical care

Diagnostic errors are prevalent in critical care practice and are associated with patient harm and costs for providers and the healthcare system.Patient complexity,illness severity,and the urgency in initiating proper treatment all contribute to decision-making errors.Clinician-related factors such as fatigue,cognitive overload,and inexperience further interfere with effective decision-making.Cognitive science has provided insight into the clinical decision-making process that can be used to reduce error.This evidence-based review discusses ten common misconceptions regarding critical care decision-making.By understanding how practitioners make clinical decisions and examining how errors occur,strategies may be developed and implemented to decrease errors in Decision-making and improve patient outcomes.

Empirical Analysis of Software Success Rate Forecasting During Requirement Engineering Processes

Forecasting on success or failure of software has become an interesting and,in fact,an essential task in the software development industry.In order to explore the latest data on successes and failures,this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework?What human factors contribute to success or failure of a software?What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work?In order to conduct this empirical analysis a total of 104 practitioners were recruited to determine how human factors,misinterpretation,and miscommunication of requirements and decision-making processes play their roles in software success forecasting.We discussed a potential relationship between forecasting of software success or failure and the development processes.We noticed that experienced participants had more confidence in their practices and responded to the questionnaire in this empirical study,and they were more likely to rate software success forecasting linking to the development processes.Our analysis also shows that cognitive bias is the central human factor that negatively affects forecasting of software success rate.The results of this empirical study also validated that requirements’misinterpretation and miscommunication were themain causes behind software systems’failure.It has been seen that reliable,relevant,and trustworthy sources of information help in decision-making to predict software systems’success in the software industry.This empirical study highlights a need for other software practitioners to avoid such bias while working on software projects.Future investigation can be performed to identify the other human factors that may impact software systems’success.

Effect of triage on physicians'clinical decision:A prospective,observational,single-center and cross-sectional study

Objective:To investigate the effect of the use of color codes for patient triage on physicians’clinical decision.Methods:This prospective study was conducted among female patients aged 18-65 years who visited the emergency department(ED)with complaints of acute abdominal pain.A 3-level of triage system[red(very urgent),yellow(urgent)and green(less urgent)]was used in our ED.All patients were green level.Half of these patients remained at the green level(the green group),and the remaining patients were re-labeled as false yellow(the false yellow group)in the order of ED visits.Ordering tests,consultation requests,intravenous treatment,length of hospital stay,and cost were compared between the two groups of patients.Results:In total 393 patients were included with 198 patients in the green group and 195 in the false yellow group.There was no statistically significant difference between the two groups in age,temperature,systolic blood pressure,diastolic blood pressure,pulse and oxygen saturation(P>0.05).It was observed that more tests(P=0.001),consultations(P<0.001),and intravenous treatment were requested(P<0.001),and the duration of stay in the ED was longer(P<0.001)and cost(P<0.001)was higher in the false yellow group.Conclusions:Triage do affect the decisions of physicians on female patients with acute abdominal pain.

Operation makalu air crash:influence of cognitive and human factors on decision-making

Two onboard crew members lost their lives in the fatal Makalu Air Cessna Grand Caravan 208B domestic cargo flight crash on May 16,2018.The Disaster Victim Identification(DVI)procedure comprises external examination,photography,DNAcollection,fingerprint collection,postmortem examination,antemortem information collection from the family members,and reconciliation.The major challenge of this operation was dealing with cognitive bias.The antemortem dental information of one of the deceased was revealed to the forensic experts just before the postmortem examination.This influenced the testing strategies.There was a tendency to neglect the complete dental examination presuming the identification was established.Later,during a thorough examination,the forensic odontologist realised that the initial decision was erroneous.Furthermore,there are few experience-based resources available to resolve cognitive bias issues.The authors begin by summarising complicated operations in which they have been involved,followed by a discussion of the key sources of cognitive bias along with the solution to resolve these issues in DVI preparedness planning.

The Intersection of Privacy by Design and Behavioral Economics: Nudging Users towards Privacy-Friendly Choices

This paper conducts a comprehensive review of existing research on Privacy by Design (PbD) and behavioral economics, explores the intersection of Privacy by Design (PbD) and behavioral economics, and how designers can leverage “nudges” to encourage users towards privacy-friendly choices. We analyze the limitations of rational choice in the context of privacy decision-making and identify key opportunities for integrating behavioral economics into PbD. We propose a user-centered design framework for integrating behavioral economics into PbD, which includes strategies for simplifying complex choices, making privacy visible, providing feedback and control, and testing and iterating. Our analysis highlights the need for a more nuanced understanding of user behavior and decision-making in the context of privacy, and demonstrates the potential of behavioral economics to inform the design of more effective PbD solutions.

Research on Subjective Bias Cognition Effect in Handwriting Identification

This article starts from the point of view that handwriting examination is dependent on empiricism and by analyzing the core steps ofhandwriting identification explains that it might be influenced by subjective bias.In practice,examiners cannot avoid biases in decision-making;instead,we must accept the existence of subjective bias in handwriting identification and then discuss its impact;for instance,feature selection in the process of comprehensive evaluation,which involves a comparison of the number and quality of similarities and differences between a questioned sample and the references.While we conclude that comprehensive evaluation is the most important step in the identification process,industries in China do not stipulate explicit and transparent criteria for it,making it hard to numerically quantify the characteristics ofhandwriting identification.In this article,forensic examiners5 opinions on handwriting identification were obtained through a survey.One finding was that most handwriting examiners believe that handwriting identification is subject to subjective bias.In addition,they believe that the subjective cognition of handwriting identification can somehow help actively produce the correct opinion;before the examination,most handwriting examiners think that they should understand the context and so on.Finally,through the questionnaire,which contained variations such as the same case with different background information,different cases with the same background information,and the same case with or without context,it was concluded that handwriting identification does have certain subjectivity.However,which kind of factors influence this subjectivity is not presently clear.Furthermore,it is difficult to control uncertainties when fbnnmg an opinion on identification.An alternative way is to perform scrutiny after the formulation ofhandwritmg opinions;for example,internal and external reviews such as appearing in court.

Self-deception can evolve under appropriate costs

Apparent biases in decision making by animals, including humans, seem to present an evolutionary puzzle, since one would expect decisions based on biased （unrealistic） information to be suboptimal. Although cognitive biases are hard to diag- nose in real animals （Marshall et al., 2013b）, we investigate Trivers＇ proposal that individuals should self-deceive first in order to better deceive others （Trivers, 2011）. Although this proposal has been scrutinized extensively （Bandura et al., 2011） it has not been formally modelled. We present the first model designed to investigate Trivers＇ proposal. We introduce an extension to a re- cent model of the evolution of self-deception （Johnson and Fowler, 2011）. In the extended model individuals make decisions by taking directly into account the benefits and costs of each outcome and by choosing the course of action that can be estimated as the best with the information available. It is shown that in certain circumstances self-deceiving decision-makers are the most evolutionarily successful, even when there is no deception between these. In a further extension of this model individuals addi- tionally exhibit deception biases and Trivers＇ premise （that effective deception is less physiologically costly with the aid of self-deception） is incorporated. It is shown that under Trivers＇ hypothesis natural selection favors individuals that self-deceive as they deceive others .

Analyzing the inconsistency in driving patterns between manual and autonomous modes under complex driving scenarios with a VR-enabled simulation platform

Purpose–With the aid of naturalistic simulations,this paper aims to investigate human behavior during manual and autonomous driving modes in complex scenarios.Design/methodology/approach–The simulation environment is established by integrating virtual reality interface with a micro-simulation model.In the simulation,the vehicle autonomy is developed by a framework that integrates artificial neural networks and genetic algorithms.Humansubject experiments are carried,and participants are asked to virtually sit in the developed autonomous vehicle(AV)that allows for both human driving and autopilot functions within a mixed traffic environment.Findings–Not surprisingly,the inconsistency is identified between two driving modes,in which the AV’s driving maneuver causes the cognitive bias and makes participants feel unsafe.Even though only a shallow portion of the cases that the AV ended up with an accident during the testing stage,participants still frequently intervened during the AV operation.On a similar note,even though the statistical results reflect that the AV drives under perceived high-risk conditions,rarely an actual crash can happen.This suggests that the classic safety surrogate measurement,e.g.time-tocollision,may require adjustment for the mixed traffic flow.Research limitations/implications–Understanding the behavior of AVs and the behavioral difference between AVs and human drivers are important,where the developed platform is only the first effort to identify the critical scenarios where the AVs might fail to react.Practical implications–This paper attempts to fill the existing research gap in preparing close-to-reality tools for AV experience and further understanding human behavior during high-level autonomous driving.Social implications–This work aims to systematically analyze the inconsistency in driving patterns between manual and autopilot modes in various driving scenarios(i.e.multiple scenes and various traffic conditions)to facilitate user acceptance of AV technology.Originality/value–A close-to-reality tool for AV experience and AV-related behavioral study.A systematic analysis in relation to the inconsistency in driving patterns between manual and autonomous driving.A foundation for identifying the critical scenarios where the AVs might fail to react.