Reflexive control in emergency medicine

Emergency physicians (EPs) navigate high-pressure environments, making rapid decisions amidst ambiguity. Their choices are informed by a complex interplay of experience, information, and external forces. While cognitive shortcuts (heuristics) expedite assessments, there are multiple ways they can be subtly manipulated, potentially leading to reflexive control: external actors steering EPs' decisions for their own benefit. Pharmaceutical companies, device manufacturers, and media narratives are among the numerous factors that influence the EPs' information landscape. Using tactics such as selective data dissemination, framing, and financial incentives, these actors can exploit pre-existing cognitive biases like anchoring, confirmation, and availability. This creates fertile ground for reflexive control, where EPs may believe they are acting independently while unknowingly serving the goals of external influencers. The consequences of manipulated decision making can be severe: misdiagnoses, inappropriate treatments, and increased healthcare costs. Ethical dilemmas arise when external pressures conflict with patient well-being. Recognizing these dangers empowers EPs to resist reflexive control through (1) critical thinking: examining information for potential biases and prioritizing evidence-based practices, (2) continuous education: learning about cognitive biases and mitigation strategies, and (3) institutional policies: implementing regulations to reduce external influence and to promote transparency. This vulnerability of emergency medicine decision making highlights the need for awareness, education, and robust ethical frameworks. Understanding reflexive control techniques is crucial for safeguarding patient care and promoting independent, ethical decision making in emergency medicine.

Inconsistencies in rater-based assessments mainly affect borderline candidates: but using simple heuristics might improve pass-fail decisions

INTRODUCTION

Research in various areas indicates that expert judgment can be highly inconsistent. However, expert judgment is indispensable in many contexts. In medical education, experts often function as examiners in rater-based assessments. Here, disagreement between examiners can have far-reaching consequences. The literature suggests that inconsistencies in ratings depend on the level of performance a to-be-evaluated candidate shows. This possibility has not been addressed deliberately and with appropriate statistical methods. By adopting the theoretical lens of ecological rationality, we evaluate if easily implementable strategies can enhance decision making in real-world assessment contexts.

METHODS

We address two objectives. First, we investigate the dependence of rater-consistency on performance levels. We recorded videos of mock-exams and had examiners (N=10) evaluate four students' performances and compare inconsistencies in performance ratings between examiner-pairs using a bootstrapping procedure. Our second objective is to provide an approach that aids decision making by implementing simple heuristics.

RESULTS

We found that discrepancies were largely a function of the level of performance the candidates showed. Lower performances were rated more inconsistently than excellent performances. Furthermore, our analyses indicated that the use of simple heuristics might improve decisions in examiner pairs.

DISCUSSION

Inconsistencies in performance judgments continue to be a matter of concern, and we provide empirical evidence for them to be related to candidate performance. We discuss implications for research and the advantages of adopting the perspective of ecological rationality. We point to directions both for further research and for development of assessment practices.

A heuristic-based approach for assessing usability in electric powered wheelchairs: A preliminary investigation

OBJECTIVE

An important issue related to electric powered wheelchair (EPW) is usability. Recent studies did not use heuristic evaluation and did not consider users' and developers' participation in the usability evaluation process of the EPW, especially when it has to be driven using alternative commands. Thus, this study investigates the use of heuristics to evaluate the usability of EPW driven by alternative commands, considering the opinion of users and assistive technology (AT) development professionals.

METHODS

The study was carried out with 54 participants: 28 EPW users (Group I) and 26 AT developers (Group II). We built a set of 25 heuristics that affects EPW usability. Participants rated each of the 25 heuristics according to their importance for the usability of EPW using the five-point Likert scale. We used the R Software to perform the Wilcoxon Mann-Whitney test as a statistical comparisons test between Group I and II.

RESULTS

The results showed a statistically significant difference (p<0.05) between Group I and II in the evaluation of 16 heuristics. We identified an important set of heuristics that could help evaluate and improve the usability of EPW.

CONCLUSION

The findings highlighted the importance of considering users' and developers' points of view in developing an EPW and its evaluation criteria. It could help the design of the device match the user's needs and expectations. The set of heuristics in this study can be adapted to evaluate other devices' usability using the heuristic evaluation approach.

By Design: How People Adapt to Cognitive Limitations in Politics

Elections, jury deliberations, lawmaking, high-stakes negotiations and related activities are human attempts to answer the question "How should we live?" Collectively, we know these activities as politics. Politics are how societies attempt to reconcile diverse individual needs with potential benefits of social coordination. People's beliefs about what others will do ainfluence many political strategies and outcomes. This article reviews how properties of cognition affect these political phenomena. Contrary to the common belief that many citizens are too ignorant to make competent political decisions, we focus on a central finding of social science-how societies can design contexts and environments to overcome individual cognitive limitations. These adaptations expand societal capacities to provide essential goods, services, and protections. In addition to explaining these adaptations, we also show how greater collaborations between cognitive science and the social sciences can help societies do even better.

Heuristics in sport: A scoping review

Judgement and decision-making under uncertainty often rely on simplistic" rules of thumb", known as "heuristics". The purpose of this scoping review is to explore the extant literature focussed on heuristics and sport. This study employed a five-stage scoping review methodology. The databases searched were Scopus, Web of Science, SPORTDiscus, and PsycInfo. The search terms were sport*, heuristic* (and its synonyms: cognitive shortcut, shortcut, rule of thumb, mental rule, cognitive rule) plus cognitive bias. The search identified 2019 studies, of which 38 were included in the analysis. Studies based in USA and Germany were most common. The use of heuristics by players were most common, while football (soccer) and basketball were the most frequently researched sport contexts. Both males and females were commonly included in most studies, but there were no studies with an explicit focus on females. The research was contextualized within several academic disciplines (e.g., psychology, forecasting, JDM, organization behavior, sports marketing and sponsorship, coaching science, risk analysis and sociology). Approximately 80 % of the studies were quantitative. Sixteen studies examined the fast and frugal heuristics approach (i.e., take-the-first heuristic (n = 8), recognition heuristic (n = 7), or gut instinct (n = 1), whereas eleven articles embraced the heuristics and biases approach. Future research should pursue a greater variety of heuristics, investigate the use of heuristics by selectors and boards of directors, and how best to design, implement, and evaluate heuristic education programs.

Using a theory-based, customized video game as an educational tool to improve physicians' trauma triage decisions: study protocol for a randomized cluster trial

BACKGROUND

Transfer of severely injured patients to trauma centers, either directly from the field or after evaluation at non-trauma centers, reduces preventable morbidity and mortality. Failure to transfer these patients appropriately (i.e., under-triage) remains common, and occurs in part because physicians at non-trauma centers make diagnostic errors when evaluating the severity of patients' injuries. We developed Night Shift, a theory-based adventure video game, to recalibrate physician heuristics (intuitive judgments) in trauma triage and established its efficacy in the laboratory. We plan a type 1 hybrid effectiveness-implementation trial to determine whether the game changes physician triage decisions in real-life and hypothesize that it will reduce the proportion of patients under-triaged.

METHODS

We will recruit 800 physicians who work in the emergency departments (EDs) of non-trauma centers in the US and will randomize them to the game (intervention) or to usual education and training (control). We will ask those in the intervention group to play Night Shift for 2 h within 2 weeks of enrollment and again for 20 min at quarterly intervals. Those in the control group will receive only usual education (i.e., nothing supplemental). We will then assess physicians' triage practices for older, severely injured adults in the 1-year following enrollment, using Medicare claims, and will compare under-triage (primary outcome), 30-day mortality and re-admissions, functional independence, and over-triage between the two groups. We will evaluate contextual factors influencing reach, adoption, implementation, and maintenance with interviews of a subset of trial participants (n = 20) and of other key decision makers (e.g., patients, first responders, administrators [n = 100]).

DISCUSSION

The results of the trial will inform future efforts to improve the implementation of clinical practice guidelines in trauma triage and will provide deeper understanding of effective strategies to reduce diagnostic errors during time-sensitive decision making.

TRIAL REGISTRATION

ClinicalTrials.gov; NCT06063434 . Registered 26 September 2023.

Heuristics and semantic spaces for the analysis of students' work in mathematical problem solving

In this research, our objective is to characterize the problem-solving procedures of primary and lower secondary students when they solve problems in real class conditions. To do so, we rely first on the concept of heuristics. As this term is very polysemic, we exploit the definition proposed by Rott (2014) to develop a coding manual and thus analyze students' procedures. Then, we interpret the results of these analyses in a qualitative way by mobilizing the concept of semantic space (Poitrenaud, 1998). This detailed analysis of students' procedures is made possible by collecting audiovisual data as close as possible to the students' work using an action camera mounted on the students' heads. We thus succeed in highlighting three different investigation profiles that we have named explorer, butterfly, and prospector. Our first results tend to show a correlation with these profiles and the success in problem-solving, yet this would need more investigation.

Comparing heuristic valuation processes between health state valuation from child and adult perspectives

OBJECTIVES

Health state valuation assumes that respondents trade off between all aspects of choice tasks and maximize their utility. Yet, respondents may use heuristic valuation processes, i.e., strategies to simplify or avoid the trade-offs that are core to health state valuation. The objective of this study is to explore if heuristic valuation processes are more prevalent for valuation from a 10-year-old child's perspective compared to the use of an adult perspective.

METHODS

We reused existing data in which EQ-5D health states were valued from adult and child perspectives with composite time trade-off (cTTO) and discrete choice experiment (DCE) tasks. Our analyses focused on comparing completion time and responding patterns across both perspectives. We also explored how reflective of a set of heuristic strategies respondents' choices were in both perspectives.

RESULTS

We found no evidence for systematic differences in completion time across perspectives. Generally, we find different responding patterns in child perspectives, e.g., more speeding, dominance violations, and clustering of utilities at 1.0, 0.8, and 0. Very few heuristic strategies provide a coherent explanation for the observed DCE responses.

CONCLUSION

Our results provide some, albeit indirect, evidence for differences in heuristic valuation processes between perspectives, although not across all data sources. Potential effects of heuristic valuation processes, such as transfer of responsibility, may be identified through studying responding patterns in cTTO and DCE responses.

The impact of cognitive resource constraints on goal prioritization

Many decisions we face daily entail deliberation about how to coordinate resources shared between multiple, competing goals. When time permits, people appear to approach these goal prioritization problems by analytically considering all goal-relevant information to arrive at a prioritization decision. However, it is not yet clear if this normative strategy extends to situations characterized by resource constraints such as when deliberation time is scarce or cognitive load is high. We evaluated the questions of how limited deliberation time and cognitive load affect goal prioritization decisions across a series of experiments using a gamified experimental task, which required participants to make a series of interdependent goal prioritization decisions. We fit several candidate models to experimental data to identify decision strategy adaptations at the individual subject-level. Results indicated that participants tended to opt for a simple heuristic strategy when cognitive resources were constrained rather than making a general tradeoff between speed and accuracy (e.g., the type of tradeoff that would be predicted by evidence accumulation models). The most common heuristic strategy involved disproportionately weighing information about goal deadlines compared to other goal-relevant information such as the goal's difficulty and the goal's subjective value.

A Modified Differential Evolution Algorithm Based on Improving A New Mutation Strategy and Self-Adaptation Crossover

The differential evolution algorithm is one of the promising natural inspired population-based metaheuristic algorithms that attracted the attention of researchers in the recent years. This paper presents a new mutation strategy called DE/current-to-best/2 that presents a new mutated vector based on utilizing the distance between the best vector and the current vector along with another random vector. In addition, the crossover procedure is self-adapted to cover low locality and high locality based on the iteration number. To obtain the best results of the proposed modified differential evolution algorithm, design of experiments is done to optimize its parameters. The comparative results are done using 11 optimization problems to compare the classical version of differential evolution algorithm with the new modified version and the results show high efficiency of the proposed DE algorithm in terms of CPU time, evaluation, and accuracy The outline of the work done in this paper can be shown as follows:•The paper produces a new modification of one of the most promising metaheuristics algorithms, the differential evolution algorithm.•The mutation strategy of the algorithm is modified to work with the current solution, the global best solution, and a random solution. The resulted mutated vector from this procedure is used to produce a new modified crossover solution.•The crossover procedure is self-adapted to cover low locality and high locality based on the iteration number, where in case of the odd iterations, the high locality is applied to obtain more diversity, and in case of the even iterations the low locality is applied to obtain local neighbor solutions. The comparison is done with the classical version of the algorithm, and the results show efficiency in terms of CPU time, evaluation, and accuracy.

The less-is-better effect: a developmental perspective

The less-is-better effect emerges when an option of lesser quantitative value is preferred or overvalued relative to a quantitively greater alternative (e.g., 24-piece dinnerware set > 24-piece dinnerware set with 16 additional broken dishes; Hsee, 1998, Journal of Behavioral Decision Making, 11, 107-121). This decisional bias emerges when the option of lesser quantitative value is perceived as qualitatively better (e.g., smaller set of intact dishes > larger set of partially broken dishes). Interestingly, this effect emerges for adult humans when options are evaluated separately but dissipates when options are considered simultaneously. The less-is-better bias has been attributed to the evaluability hypothesis: individuals judge objects on the basis of easy-to-evaluate attributes when judged in isolation, such as the brokenness of items within a set, yet shift to quantitative information when evaluated jointly, such as the overall number of dishes. This bias emerges for adult humans and chimpanzees in a variety of experimental settings but has not yet been evaluated among children. In the current study, we presented a joint evaluation task (larger yet qualitatively inferior option vs. smaller yet qualitatively superior option) to children aged 3 to 9 years old to better understand the developmental trajectory of the less-is-better effect. Children demonstrated the bias across all choice trials, preferring an objectively smaller set relative to a larger yet qualitatively poorer alternative. These developmental findings suggest that young children rely upon salient features of a set to guide decision-making under joint evaluation versus more objective attributes such as quantity/value.

Novel variable neighborhood search heuristics for truck management in distribution warehouses problem

Logistics and sourcing management are core in any supply chain operation and are among the critical challenges facing any economy. The specialists classify transport operations and warehouse management as two of the biggest and costliest challenges in logistics and supply chain operations. Therefore, an effective warehouse management system is a legend to the success of timely delivery of products and the reduction of operational costs. The proposed scheme aims to discuss truck unloading operations problems. It focuses on cases where the number of warehouses is limited, and the number of trucks and the truck unloading time need to be manageable or unknown. The contribution of this article is to present a solution that: (i) enhances the efficiency of the supply chain process by reducing the overall time for the truck unloading problem; (ii) presents an intelligent metaheuristic warehouse management solution that uses dispatching rules, randomization, permutation, and iteration methods; (iii) proposes four heuristics to deal with the proposed problem; and (iv) measures the performance of the proposed solution using two uniform distribution classes with 480 trucks' unloading times instances. Our result shows that the best algorithm is O I S ~ , as it has a percentage of 78.7% of the used cases, an average gap of 0.001, and an average running time of 0.0053 s.

Investigating the impact of cognitive biases in radiologists' image interpretation: A scoping review

RATIONALE AND OBJECTIVE

Image interpretation is a fundamental aspect of radiology. The treatment and management of patients relies on accurate and timely imaging diagnosis. However, errors in radiological reports can negatively impact on patient health outcomes. These misdiagnoses can be caused by several different errors, but cognitive biases account for 74 % of all image interpretation errors. There are many biases that can impact on a radiologist's perception and cognitive processes. Several recent narrative reviews have discussed these cognitive biases and have offered possible strategies to mitigate their effects. However, these strategies remain untested. Therefore, the purpose of this scoping review is to evaluate the current knowledge on the extent that cognitive biases impact on medical image interpretation.

MATERIAL AND METHODS

Scopus and Medline Databases were searched using relevant keywords to identify papers published between 2012 and 2022. A subsequent hand search of the narrative reviews was also performed. All studies collected were screened and assessed against the inclusion and exclusion criteria.

RESULTS

Twenty-four publications were included and categorised into five main themes: satisfaction of search, availability bias, hindsight bias, framing bias and other biases. From these studies, there were mixed results regarding the impact of cognitive biases, highlighting the need for further investigation in this area. Moreover, the limited and untested debiasing methods offered by a minority of the publications and narrative reviews also suggests the need for further research. The potential of role of artificial intelligence is also highlighted to further assist radiologists in identifying and mitigating these cognitive biases.

CONCLUSION

Cognitive biases can impact radiologists' image interpretation, however the effectiveness of debiasing strategies remain largely untested.

No food left behind: foraging route choices among free-ranging Japanese macaques (Macaca fuscata) in a multi-destination array at the Awajishima Monkey Center, Japan

Animals must make route choices every day when moving through their habitat while foraging. Choosing an optimal route can be cognitively costly, and primates and other animals have been shown to use simple heuristics, "rules of thumb", to make foraging route choices. We investigated the potential use of heuristics among foraging free-ranging Japanese monkeys (Macaca fuscata) during solitary foraging trials. We also investigated the potential influence of individual variables (age and sex) and social variables (presence in the central group, presence of potential inter- and intraspecific competitors), on the use of heuristics, route length and trial time. We used a multi-destination foraging experiment with 6 platforms in a (4 m × 8 m) Z-array, completed by 29 Japanese macaques in 155 runs at the Awajishima Monkey Center in Japan. Our results showed that the macaques chose routes consistent with heuristics (e.g. nearest neighbour heuristic 19.4%, convex hull heuristic 4.5%) and selected optimal routes (shortest path in 23.9% of the trials). We also identified a potential new heuristic that was used most frequently, that we termed the "sweep heuristic" (27.1% of trials), which we interpreted as a strategy to deal with competitive foraging trade-offs - choosing routes to prioritize not leaving isolated food pieces behind. Age was significantly related to trial time; juvenile macaques were faster than adults and young adults, using speed to gain access to resources. Solitary trials with conspecifics present took significantly longer routes. Our results suggest that contextual factors led to variation in Japanese macaque decision-making, and we suggest that the preferential use of a sweep heuristic may have been a response to high intragroup competition.

Design, validation and piloting of clinical vignettes to analyze critical care clinical decision processes during the COVID-19 pandemic in three different countries (Spain, Chile and United States)

Background

The use of heuristics in clinical decision-making processes increases in contexts of high uncertainty, such as those in Intensive Care Units (ICU. Given the impossibility of empirically studying their impact on real-world conditions, clinical vignettes were developed with the goal of identifying the use of heuristics in the care of critically ill patients during the COVID-19 pandemic in different clinical contexts.

Methodology

Vignettes were designed by critical care physicians in Spain to assess the use of representativeness, availability, and status quo heuristics in the care of critically ill patients during the COVID-19 pandemic. The construct, internal and external validity of the vignettes designed in Spain, the United States and Chile were evaluated. A questionnaire was piloted with the vignettes being validated in the three aforementioned countries through a computer application built for this purpose.

Results

16 study vignettes grouped into 5 models were created: each model included between 2 and 4 vignettes. The vignettes designed were closed-response vignettes with 2-3 possible alternatives. The vignettes, initially developed in Spain in Spanish, were translated to English and adapted to the Spanish used in Chile. The clinical content of the vignettes was not modified during the translation process.

Conclusions

The vignettes allow for the study of the use of heuristics in critical care clinical decision making in the context of the COVID-19 pandemic. The piloting and validation process used can serve as a model for similar multinational studies exploring clinical decision making.

The conjunction fallacy in rats

Humans and other animals are capable of reasoning. However, there are overwhelming examples of errors or anomalies in reasoning. In two experiments, we studied if rats, like humans, estimate the conjunction of two events as more likely than each event independently, a phenomenon that has been called conjunction fallacy. In both experiments, rats learned through food reinforcement to press a lever under some cue conditions but not others. Sound B was rewarded whereas Sound A was not. However, when B was presented with the visual cue Y was not rewarded, whereas AX was rewarded (i.e., A-, AX+, B+, BY-). Both visual cues were presented in the same bulb. After training, rats received test sessions in which A and B were presented with the bulb explicitly off or occluded by a metal piece. Thus, on the occluded condition, it was ambiguous whether the trials were of the elements alone (A or B) or of the compounds (AX or BY). Rats responded on the occluded condition as if the compound cues were most likely present. The second experiment investigated if this error in probability estimation in Experiment 1, could be due to a conjunction fallacy, and if this could be attenuated by increasing the ratio of element/compound trials from the original 50-50 to 70-30 and 90-10. Only the 90-10 condition (where 90% of the training trials were of just A or just B) did not show a conjunction fallacy, though it emerged in all groups with additional training. These findings open new avenues for exploring the mechanisms behind the conjunction fallacy effect.

How do psychology researchers interpret the results of multiple replication studies?

Employing two vignette studies, we examined how psychology researchers interpret the results of a set of four experiments that all test a given theory. In both studies, we found that participants' belief in the theory increased with the number of statistically significant results, and that the result of a direct replication had a stronger effect on belief in the theory than the result of a conceptual replication. In Study 2, we additionally found that participants' belief in the theory was lower when they assumed the presence of p-hacking, but that belief in the theory did not differ between preregistered and non-preregistered replication studies. In analyses of individual participant data from both studies, we examined the heuristics academics use to interpret the results of four experiments. Only a small proportion (Study 1: 1.6%; Study 2: 2.2%) of participants used the normative method of Bayesian inference, whereas many of the participants' responses were in line with generally dismissed and problematic vote-counting approaches. Our studies demonstrate that many psychology researchers overestimate the evidence in favor of a theory if one or more results from a set of replication studies are statistically significant, highlighting the need for better statistical education.

Biased perception of distributions: Anchoring, interpolation and smoothing as potential causes

Perceiving the degree of variation in the social and non-social environment is a cognitive task that is important for many judgments and decisions. In the present research, we investigated cognitive underpinnings of how people estimate the average value of segments of a statistical distribution (e.g., what is the average income of the richest 25% of a population?). In three experiments (total N = 222), participants learned about the values of experimentally created distributions of income values and city sizes and later estimated the mean value of the four quarters of values. We expected participants to draw on heuristic shortcuts to generate such judgments. More specifically, we hypothesized that participants use the endpoints of the distributions as anchors and determine the mean values by linear interpolation. In addition, we tested the contribution of three further processes (Range-Frequency adjustments, Normal Smoothing, Linear Smoothing). Quantitative model tests suggest that anchoring and Linear Smoothing both affected mean interquartile judgments. This conclusion is corroborated by tests of qualitative predictions of the models under consideration.

On the gap between objective and perceived risks of COVID-19

A survey conducted by the German Socio-Economic Panel during the early phase of the SARS-CoV‑2 pandemic in spring 2020 showed that the perceived risks of SARS-CoV‑2 infection were a massive overestimation of the actual risks. A total of 5783 people (2.3% missing data) stated how likely they thought it was that SARS-CoV‑2 would cause a life-threatening illness in them in the next 12 months. The average subjective probability was 26%. We consider how such an overestimation could have occurred and how a more realistic risk assessment could be achieved in the population in a future pandemic. We show that qualitative attributes of the pandemic, the reporting of the media, and psychological features may have contributed to the overestimation of SARS-CoV‑2 risks. In its early stages, the SARS-CoV‑2 pandemic had qualitative characteristics known to lead to an overestimation of risks: The risks associated with the pandemic were new, unfamiliar, perceived as poorly controllable, and were taken involuntarily. Phenomena known from cognitive psychology such as the availability and anchor heuristics can also explain the overestimation of pandemic risks. Characteristics of media coverage such as the focus on individual fates and the associated neglect of the denominator also contributed to the gap between perceived and objective risk. In a potential future pandemic, people need to be vigilant but not in a panic. Better risk communication-for example, with better prepared figures and graphically presented percentages while avoiding the denominator neglect-could help the population to perceive risks of future pandemics more realistically.

Cognitive Bias and Dissonance in Surgical Practice: A Narrative Review

A cognitive bias describes "shortcuts" subconsciously applied to new scenarios to simplify decision-making. Unintentional introduction of cognitive bias in surgery may result in surgical diagnostic error that leads to delayed surgical care, unnecessary procedures, intraoperative complications, and delayed recognition of postoperative complications. Data suggest that surgical error secondary to the introduction of cognitive bias results in significant harm. Thus, debiasing is a growing area of research which urges practitioners to deliberately slow decision-making to reduce the effects of cognitive bias.

Heuristics Facilitates the Evolution of Transitive Inference and Social Hierarchy in a Large Group

Transitive inference (TI) refers to social cognition that facilitates the discernment of unknown relationships between individuals using known relationships. It is extensively reported that TI evolves in animals living in a large group because TI could assess relative rank without deducing all dyadic relationships, which averts costly fights. The relationships in a large group become so complex that social cognition may not be developed adequately to handle such complexity. If members apply TI to all possible members in the group, TI requires extremely highly developed cognitive abilities especially in a large group. Instead of developing cognitive abilities significantly, animals may apply simplified TI we call reference TI in this study as heuristic approaches. The reference TI allows members to recognize and remember social interactions only among a set of reference members rather than all potential members. Our study assumes that information processes in the reference TI comprises (1) the number of reference members based on which individuals infer transitively, (2) the number of reference members shared by the same strategists, and (3) memory capacity. We examined how information processes evolve in a large group using evolutionary simulations in the hawk-dove game. Information processes with almost any numbers of reference members could evolve in a large group as long as the numbers of shared reference member are high because information from the others' experiences is shared. TI dominates immediate inference, which assesses relative rank on direct interactions, because TI could establish social hierarchy more rapidly applying information from others' experiences.

A novel competitive exact approach to solve assembly line balancing problems based on lexicographic order of vectors

The assembly line balancing problem (ALBP) is an eminent NP-hard topic that is discussed in mass production systems with low diversity. Primarily, two types of ALBPs are discussed in the literature as type I, which aims to find the minimum number of workstations for a given cycle time, and type II, which assigns some tasks to a given number of workstations such that the maximum workstation load is minimized. To solve ALBPs, various exact, heuristic, and metaheuristic methods have been proposed. However, these methods lose their efficiency when handling large-size problems. Therefore, researchers have focused on proposing heuristic and metaheuristic algorithms to solve large-size problems, especially when they deal with real-life case problems in the industry. This study aims to present a novel and competitive exact method for solving ALBP type II based on the lexicographic order of vectors for feasible solutions. To evaluate the performance of the developed method, a group of highly used standard test problems in the literature is utilized, and the results are compared and discussed in detail. The computational results in this study specify that the developed solution approach performs efficiently and yields the best global solution of all the ALB test problems, which proves the proposed method's potential and its competitive advantage.

Student timetabling genetic algorithm accounting for student preferences

Universities face a constant challenge when distributing students and allocating them to their required classes, especially for a large mass of students. Generating feasible timetables is a strenuous task that requires plenty of resources, which makes it impractical to take student preferences into consideration during the process. Timetabling and scheduling problems are proven to be NP-hard due to their complex nature and large search spaces. A genetic algorithm (GA) that assigns students to their classes based on their preferences is proposed as a solution to this problem and is implemented in this article. The GA's performance is enhanced by applying different metaheuristic concepts and by tailoring the genetic operators to the given problem. The quality of the solutions generated is boosted further with the unique repair and improvement functions that were implemented in conjunction with the genetic algorithm. The success of the GA was evaluated by using different datasets of varying complexity and by assessing the quality of the solutions generated. The results obtained were promising and the algorithm guarantees the feasibility of solutions as well as satisfying more than 90% of student preferences even for the most complex problems.

Do conspiracy theorists think too much or too little?

Conspiracy theories explain distressing events as malevolent actions by powerful groups. Why do people believe in secret plots when other explanations are more probable? On the one hand, conspiracy theorists seem to disregard accuracy; they tend to endorse mutually incompatible conspiracies, think intuitively, use heuristics, and hold other irrational beliefs. But by definition, conspiracy theorists reject the mainstream explanation for an event, often in favor of a more complex account. They exhibit a general distrust of others and expend considerable effort to find 'evidence' supporting their beliefs. In searching for answers, conspiracy theorists likely expose themselves to misleading information online and overestimate their own knowledge. Understanding when elaboration and cognitive effort might backfire is crucial, as conspiracy beliefs lead to political disengagement, environmental inaction, prejudice, and support for violence.

Georeferenced rural distribution network model considering scalable growth of users in rural areas

This paper presents a georeferenced optimal planning model of a rural distribution network for deploying an underground network considering a real scenario for increasing electrification in this area. A model is presented based on a heuristic process that minimizes the resources required to route the grid for a defined time horizon. Then, the model is scalable according to the population density, the established and georeferenced zone, and the specified period; that is, it adjusts to any of these variables. Additionally, the modeling is presented in CYME software, considering a series of technical criteria to provide the actual scenario with a verifiable planning model of an underground network. Therefore, the voltage drop and level of overload in transformers and feeders are considered to deliver an optimum power quality to the end-user. These results will be tabulated and presented as an alternative to different planning and design models that an electric distribution company may have to minimize the resources used in an underground deployment.

Dyskinesia as a unique presentation of subarachnoid hemorrhage: a case report

BACKGROUND

Subarachnoid hemorrhage (SAH) is a diagnosis that emergency physicians must have a high index of suspicion for. Many common chief complaints such as headache, nausea, altered mental status, and even syncope may alert clinicians to the possibility of a SAH.

CASE PRESENTATION

The authors present an unusual case of SAH in a patient presenting with acute dyskinesia and altered mental status, which has seldom been documented as the presenting feature of SAH, as well as the diagnostic pitfalls encountered in assessing this patient.

CONCLUSION

Emergency physicians should maintain a high index of suspicion for dangerous pathology in cases without a clear etiology; they should also utilize metacognition to assess their own biases and thought patterns so as to avoid missing critical diagnoses.

Machine learning strategy identification: A paradigm to uncover decision strategies with high fidelity

We propose a novel approach, which we call machine learning strategy identification (MLSI), to uncovering hidden decision strategies. In this approach, we first train machine learning models on choice and process data of one set of participants who are instructed to use particular strategies, and then use the trained models to identify the strategies employed by a new set of participants. Unlike most modeling approaches that need many trials to identify a participant's strategy, MLSI can distinguish strategies on a trial-by-trial basis. We examined MLSI's performance in three experiments. In Experiment I, we taught participants three different strategies in a paired-comparison decision task. The best machine learning model identified the strategies used by participants with an accuracy rate above 90%. In Experiment II, we compared MLSI with the multiple-measure maximum likelihood (MM-ML) method that is also capable of integrating multiple types of data in strategy identification, and found that MLSI had higher identification accuracy than MM-ML. In Experiment III, we provided feedback to participants who made decisions freely in a task environment that favors the non-compensatory strategy take-the-best. The trial-by-trial results of MLSI show that during the course of the experiment, most participants explored a range of strategies at the beginning, but eventually learned to use take-the-best. Overall, the results of our study demonstrate that MLSI can identify hidden strategies on a trial-by-trial basis and with a high level of accuracy that rivals the performance of other methods that require multiple trials for strategy identification.

Testing the feasibility, acceptability, and preliminary effect of a novel deliberate practice intervention to reduce diagnostic error in trauma triage: a study protocol for a randomized pilot trial

BACKGROUND

Non-compliance with clinical practice guidelines in trauma remains common, in part because physicians make diagnostic errors when triaging injured patients. Deliberate practice, purposeful participation in a training task under the oversight of a coach, effectively changes behavior in procedural domains of medicine but has rarely been used to improve diagnostic skill. We plan a pilot parallel randomized trial to test the feasibility, acceptability, and preliminary effect of a novel deliberate practice intervention to reduce physician diagnostic errors in trauma triage.

METHODS

We will randomize a national convenience sample of physicians who work at non-trauma centers (n = 60) in a 1:1 ratio to a deliberate practice intervention or to a passive control. We will use a customized, theory-based serious video game as the basis of our training task, selected based on its behavior change techniques and game mechanics, along with a coaching manual to standardize the fidelity of the intervention delivery. The intervention consists of three 30-min sessions with content experts (coaches), conducted remotely, during which physicians (trainees) play the game and receive feedback on their diagnostic processes. We will assess (a) the fidelity with which the intervention is delivered by reviewing video recordings of the coaching sessions; (b) the acceptability of the intervention through surveys and semi-structured interviews, and (c) the effect of the intervention by comparing the performance of trainees and a control group of physicians on a validated virtual simulation. We hypothesize that trainees will make ≥ 25% fewer diagnostic errors on the simulation than control physicians, a large effect size. We additionally hypothesize that ≥ 90% of trainees will receive their intervention as planned.

CONCLUSIONS

The results of the trial will inform the decision to proceed with a future hybrid effectiveness-implementation trial of the intervention. It will also provide a deeper understanding of the challenges of using deliberate practice to modify the diagnostic skill of physicians.

TRIAL REGISTRATION

Clinical trials.gov ( NCT05168579 ); 23 December 2021.

Pursuitworthiness between daring conservatism and procrastination: Wheeler and the path towards black holes

This paper follows the story of how John A. Wheeler became the enthusiastic baptizer and popularizer of black holes, after he overcame his own initial resistance and protracted skepticism about earlier results. However, the present work is not only historical, since its aim is to suggest as well that the notion of pursuitworthiness can but benefit from a close confrontation with actual heuristic paths, examined in their complexity. This specific case, moreover, may suggest some historical-critical insights on the current situation at the most speculative frontiers of theoretical physics.

Canonicity Effect on Sentence Processing of Persian-speaking Broca's Patients

Introduction

Fundamental notions of mapping hypothesis and canonicity were scrutinized in Persian-speaking aphasics.

Methods

To this end, the performance of four age-, education-, and gender matched Persian-speaking Broca's patients and eight matched healthy controls in diverse complex structures were compared via the conduction of two tasks of syntactic comprehension and grammaticality judgment.

Results

The tested structures included subject agentive, agentive passive, object experience, subject experience, subject cleft, and object cleft constructions. Our results, while corroborating the predictions of the mapping hypothesis, showed that in structures, in which linguistic elements were substituted and dislocated out of their canonical syntactic positions, namely, agentive passive, subject experiencer, object experiencer, and object cleft constructions, Broca's problems escalated. In contrast, in those structures whose constituent concatenations were aligned with canonical syntactic structures, namely subject agentive, and cleft structures, patients had above the chance performance. Ultimately, the theoretical and clinical implications of the study were discussed.

Conclusion

The number of predicates in a sentence, predicate types (psychological and agentive), as well as semantic heuristics and canonicity all by all could be regarded as the major culprits for aphasics' poor performance.

Is it a judgment of representativeness? Re-examining the birth sequence problem

Although all birth orders in the "birth sequence problem" are equiprobable, most participants judge the less representative order as less likely than the more representative order. But this well-known problem confounds representativeness with the direction in which birth orders are compared. We hypothesized and corroborated in three experiments (total N = 1,136) that participants pragmatically infer the birth orders' relative prevalence from the direction of comparison. Experiment 1 found that participants judged the less representative sequence as more common when we reversed the comparison. Experiment 2 reproduced these results despite removing representativeness as a cue. In Experiment 3, participants preferred to place the relatively common sequence as the referent in an inverted "speaker" problem. Our results turn the iconic problem's interpretation on its head: Rather than indicating flawed human cognition, the birth sequence problem illustrates people's ability to adaptively extract subtle linguistic meaning beyond the literal content.

Williamson on conditionals and testimony

In Suppose and Tell, Williamson makes a new case for the material conditional account. He tries to explain away apparently countervailing data by arguing that these have been misinterpreted because researchers have overlooked the role of heuristics in the processing of conditionals. Cases involving the receipt of apparently conflicting conditionals play an important dialectical role in Williamson's book: they are supposed to provide evidence for the material conditional account as well as for the defeasibility of a key procedure underlying our everyday assessments of conditionals. We argue that they can serve neither of these purposes and that Williamson overestimates the reach of heuristics. We specifically challenge Williamson's assumption that, in the kind of cases centrally at issue in his book, the recipient of conflicting conditionals will typically accept those at face value, even granting Williamson that conditionals can be freely passed among speakers under normal conditions of testimony.

A Consideration of Alternative Sample Spaces Used in Coin-Toss Problems

This paper examines coin-toss comparison questions from two recent studies involving undergraduate students and high school teachers and connects to findings from two prior studies in the literature. Considering possible sample spaces employed by participants, this is a reflection on whether one sequence could be more likely depending on the interpretation of the question. To critique the choice of sequences and determine possible scenarios in which one sequence may be more likely than the other, three alternative sample spaces were explored. It was determined that different sample spaces can lead to one sequence being more likely to occur than the other. Further evaluation discusses whether alternative sample spaces may have been utilised by the participants in each of the studies, and hence, the paper concludes with an advocacy to enquire deeper into participants' reasoning when investigating coin-toss questions.

Do clinicians follow heuristics in prescribing antidepressants?

BACKGROUND

While clinicians commonly learn heuristics to guide antidepressant treatment selection, surveys suggest real-world prescribing practices vary widely. We aimed to determine the extent to which antidepressant prescriptions were consistent with commonly-advocated heuristics for treatment selection.

METHODS

This retrospective longitudinal cohort study examined electronic health records from psychiatry and non-psychiatry practice networks affiliated with two large academic medical centers between March 2008 and December 2017. Patients included 45,955 individuals with a major depressive disorder or depressive disorder not otherwise specified diagnosis who were prescribed at least one of 11 common antidepressant medications. Specific clinical features that may impact prescribing choices were extracted from coded data, and analyzed for association with index prescription in logistic regression models adjusted for sociodemographic variables and provider type.

RESULTS

Multiple clinical features yielded 10% or greater change in odds of prescribing, including overweight and underweight status and sexual dysfunction. These heuristics were generally applied similarly across hospital systems and psychiatrist and non-psychiatrist providers.

LIMITATIONS

These analyses rely on coded clinical data, which is likely to substantially underestimate prevalence of particular clinical features. Additionally, numerous other features that may impact prescribing choices are not able to be modeled.

CONCLUSION

Our results confirm the hypothesis that clinicians apply heuristics on the basis of clinical features to guide antidepressant prescribing, although the magnitude of these effects is modest, suggesting other patient- or clinician-level factors have larger effects.

FUNDING

This work was funded by NSF GRFP (grant no. DGE1745303), Harvard SEAS, the Center for Research on Computation and Society at Harvard, the Harvard Data Science Initiative, and a grant from the National Institute of Mental Health (grant no. 1R01MH106577).

Strategy selection in decisions from givens: Deciding at a glance?

People deciding between alternatives have at their disposal a toolbox containing both compensatory strategies, which take into account all available attributes of those alternatives, and noncompensatory strategies, which consider only some of the attributes. It is commonly assumed that noncompensatory strategies play only a minor role in decisions from givens, where attribute information is openly presented, because all attributes can be processed automatically "at a glance." Based on a literature review, however, I establish that previous studies on strategy selection in decisions from givens have yielded highly heterogeneous findings, including evidence of widespread use of noncompensatory strategies. Drawing on insights from visual attention research on subitizing, I argue that this heterogeneity might be due to differences across studies in the number of attributes and in whether the same or different symbols are used to represent high/low attribute values across attributes. I tested the impact of these factors in two experiments with decisions from givens in which both the number of attributes shown for each alternative and the coding of attribute values was manipulated. An analysis of participants' strategy use with a Bayesian multimethod approach (taking into account both decisions and response-time patterns) showed that a noncompensatory strategy was more frequently selected in conditions with a higher number of attributes; the type of attribute coding scheme did not affect strategy selection. Using a compensatory strategy in the conditions with eight (vs. four) attributes was associated with rather long response times and a high rate of strategy execution errors. The results suggest that decisions from givens can incur cognitive costs that prohibit reliance on automatic compensatory decision making and that can favor the adaptive selection of a noncompensatory strategy.

Ptolemy's Optics, double-vision, and the technological afterimage

In contrast to earlier theorists within the Greek optical tradition, who relied almost exclusively on geometrical diagrams to articulate and explain vision, Ptolemy employed several material instruments in his investigation of sight. These included rulers, glass cylinders, mirrors, and a bronze plaque designed to measure angles of incidence and reflection. These devices allowed Ptolemy to expand the operational definition of vision far beyond that of his predecessors, as he explicated several previously unexamined visual behaviors, including binocular vision, diplopia, and refraction. This article argues that these tools did more than make new phenomena visible; they also set the parameters for what these phenomena looked like-sometimes to such a degree that features of these instruments merged with the visual behaviors that they rendered visible. In some cases, this occurred as a type of "double-exposure," where the investigative tool became layered over top of the process of sight, such as when Ptolemy's "ruler" for investigating binocular vision became a template for imagining the mechanism of spatial perception employed by the eyes. In other cases, this merging occurred as a type of "technological afterimage," where the instrument provided an implicit model for phenomena it was not directly investigating. Ptolemy's bronze plaque stands as an example of this second type, insofar as it inspired his account of ocular geometry and facilitated novel assertions about the eye's operations, even though it did not directly inspect these features. In general, this article thus outlines how the technologies of investigation can structure patterns of thought and naturalize certain physical arguments, whether for the phenomena that they directly articulate or for those indirectly associated with their particular use cases.

Robust min-max regret covering problems

This article deals with two min-max regret covering problems: the min-max regret Weighted Set Covering Problem (min-max regret WSCP) and the min-max regret Maximum Benefit Set Covering Problem (min-max regret MSCP). These problems are the robust optimization counterparts, respectively, of the Weighted Set Covering Problem and of the Maximum Benefit Set Covering Problem. In both problems, uncertainty in data is modeled by using an interval of continuous values, representing all the infinite values every uncertain parameter can assume. This study has the following major contributions: (i) a proof that MSCP is Σ p 2 -Hard, (ii) a mathematical formulation for the min-max regret MSCP, (iii) exact and (iv) heuristic algorithms for the min-max regret WSCP and the min-max regret MSCP. We reproduce the main exact algorithms for the min-max regret WSCP found in the literature: a Logic-based Benders decomposition, an extended Benders decomposition and a branch-and-cut. In addition, such algorithms have been adapted for the min-max regret MSCP. Moreover, five heuristics are applied for both problems: two scenario-based heuristics, a path relinking, a pilot method and a linear programming-based heuristic. The goal is to analyze the impact of such methods on handling robust covering problems in terms of solution quality and performance.

On the use of positive test strategies when diagnosing mental disorders

BACKGROUND

Despite the adverse impact diagnostic errors can have, clinical interviewing and decision-making in psychiatric practice have received relatively little empirical attention. When diagnosing patients, clinicians tend to fall back on a specific (heuristic) rule of thumb, the positive test strategy, a confirmatory approach that increases the risk of confirmation bias.

METHOD AND RESULTS

A group of 83 clinical psychologists and psychiatrists was asked to give their diagnostic hypotheses about two vignettes. We found them to self-generate significantly (i.e., p < .01; d = 1.57) more confirming than disconfirming questions to test their initial diagnostic impressions, with supervisors considering significantly more differential diagnoses than the less experienced post-grads/residents. When offered a list of 100 potentially relevant diagnostic queries, the supervisors selected fewer confirming and proportionally more disconfirming themes.

CONCLUSIONS

Our results demonstrate that irrespective of clinical experience mental-health clinicians indeed tend to use a confirmatory thinking style that contrasts with the stricter principle of falsification. More field-based research on this topic is needed, as well as studies probing whether a systematized diagnostic approach is feasible in psychiatric practice and increases diagnostic accuracy and patient satisfaction.

The possibility of an impetus heuristic

Evidence consistent with a belief in impetus is drawn from studies of naïve physics, perception of causality, perception of force, and representational momentum, and the possibility of an impetus heuristic is discussed. An impetus heuristic suggests the motion path of an object that was previously constrained or influenced by an external source (e.g., object, force) appears to exhibit the same constraint or influence even after that constraint or influence is removed. Impetus is not a valid physical principle, but use of an impetus heuristic can in some circumstances provide approximately correct predictions regarding future object motion, and such predictions require less cognitive effort and resources than would predictions based upon objective physical principles. The relationship of an impetus heuristic to naïve impetus theory and to objective physical principles is discussed, and use of an impetus heuristic significantly challenges claims that causality or force can be visually perceived. Alternatives to an impetus heuristic are considered, and potential boundary conditions and falsification of the impetus notion are discussed. Overall, use of an impetus heuristic offers a parsimonious explanation for findings across a wide range of perceptual domains and could potentially be extended to more metaphorical types of motion.

Solving the clustered traveling salesman problem via traveling salesman problem methods

The Clustered Traveling Salesman Problem (CTSP) is a variant of the popular Traveling Salesman Problem (TSP) arising from a number of real-life applications. In this work, we explore a transformation approach that solves the CTSP by converting it to the well-studied TSP. For this purpose, we first investigate a technique to convert a CTSP instance to a TSP and then apply powerful TSP solvers (including exact and heuristic solvers) to solve the resulting TSP instance. We want to answer the following questions: How do state-of-the-art TSP solvers perform on clustered instances converted from the CTSP? Do state-of-the-art TSP solvers compete well with the best performing methods specifically designed for the CTSP? For this purpose, we present intensive computational experiments on various benchmark instances to draw conclusions.

Simple Heuristics for Near-Optimal Appointment Scheduling in Primary Care

In primary care allocating appointments to sequential requests can result in sub-optimal scheduling. Optimal scheduling requires hiring of consultants to analyze historical patterns. Many practices focus their resources on larger problems instead of optimizing appointment schedules. We simulate simple heuristics to compare their performance with optimal schedules uncovered using offline optimization models. We use uncapacitated appointment calendars for a nationally representative heterogeneous primary care panel to meet all patients' requests. The stochastic nature of appointment requests gives a distribution for daily appointments and for the uncovered optimal capacity. The First Minimum heuristic gives near-optimal schedules and can be easily implemented in small practices using pen-and-paper, without any investment in computer-systems.

The earth vibrates with analogies: The Dirac sea and the geology of the vacuum

The debate around analogy in modern physics that focuses on its role as a logical inference often correspondingly overlooks its historical dimension and the other equally important functions and aspects that are intertwined with this dimension. Inspired by a close investigation of the primary sources and archival material of a few historical actors, this paper lays out a framework on analogy-making which preserves as much as possible its historical complexity. While not losing sight of the logical role, our framework puts a special emphasis on the heuristic process, and aims at offering to the historian and philosopher of science as well as the physicist some tools to capture the subtle functions of analogical reasoning involved in such a process. After having traced it out theoretically, we make use of this framework to interpret the growth of the ideas of two remarkable physicists dealing with the multifaceted notion of vacuum in 20th century physics. We first consider the trajectory followed by John A. Wheeler, between the 1960s and 1970s, towards (in his own words) a "geology of the vacuum"; and then examine, starting from the hitherto neglected Japanese reception of the idea of Dirac sea in the early 1930s, the pathway that led Yoichiro Nambu to the discovery of spontaneous symmetry breaking.

A decision support system for prioritised COVID-19 two-dosage vaccination allocation and distribution

This study proposes a decision support system (DSS) that integrates GIS, analytics, and simulation methods to help develop a priority-based distribution of COVID-19 vaccines in a large urban setting. The methodology applies novel hierarchical heuristic-simulation procedures to create a holistic algorithm for prioritising the process of demand allocation and optimising vaccine distribution. The Melbourne metropolitan area in Australia with a population of over five million is used as a case study. Three vaccine supply scenarios, namely limited, excessive, and disruption, were formulated to operationalise a two-dose vaccination program. Vaccine distribution with hard constraints were simulated and then further validated with sensitivity analyses. The results show that vaccines can be prioritised to society's most vulnerable segments and distributed using the current logistics network with 10 vehicles. Compared with other vaccine distribution plans with no prioritisation, such as equal allocation of vaccines to local government areas based on population size or one on a first-come-first-serve basis, the plans generated by the proposed DSS ensure prioritised vaccination of the most needed and vulnerable population. The aim is to curb the spread of the infection and reduce mortality rate more effectively. They also achieve vaccination of the entire population with less logistical resources required. As such, this study contributes to knowledge and practice in pandemic vaccine distribution and enables governments to make real-time decisions and adjustments in daily distribution plans. In this way any unforeseen disruptions in the vaccine supply chain can be coped with.

Visual guidance of locomotor interception is based on nulling changes in target bearing (not egocentric target direction nor target-heading angle)

In two experiments we studied how participants steer to intercept uniformly moving targets in a virtual driving task under hypotheses-differentiating conditions of initial target eccentricity and target motion. In line with our re-analysis of findings from earlier studies, in both experiments the observed interception behavior could not be understood as resulting from reliance on (changes in) egocentric target direction nor from reliance on (changes in) target-heading angle. The overall pattern of results observed was however compatible with a control strategy based on nulling changes in the target's bearing angle. The presence of reversals in movement direction under specific combinations of target eccentricity and motion conditions indicated that the information used was not purely rate-of-change (i.e., first-order) based but carried traces of an influence of initial target position. In Experiment 2 we explicitly tested the potential role of early reliance on perceived egocentric target direction by examining the effects of a 10° rotation of the visual scene (i.e., of both target and environment). While such a rotation gave rise to minor changes in the moment of initiation of the first steering action, contrary to predictions it did not affect the characteristics of the direction-reversal phenomenon. We conclude that the visual guidance of locomotor interception is best understood as resulting from nulling changes in the target's bearing angle, with such nulling perhaps best conceived as being fractional-order (rather integer-order) driven.

The effect of methylphenidate and mixed amphetamine salts on cognitive reflection: a field study

RATIONALE

Methylphenidate (MPH) and mixed D,L-amphetamine salts (MASs; Adderall) were previously found to have unreliable effects on judgment and decision processes.

OBJECTIVE

We predicted that MPH and MASs have a specific effect of reducing heuristic responses, which should lead to increased performance on the cognitive reflection test (CRT). The CRT is considered to be a testbed for heuristic versus deliberative response modes.

METHODS

We recruited a sample of 15,361 individuals using the Prolific Academic crowdsourcing platform. From this initial pool, our final sample consisted of 294 participants (125 MPH users and 169 MASs users) who conformed to the study criteria and completed the experimental tasks. Tasks were performed on days where participants were either medicated or not, allowing to assess the effect of medication status.

RESULTS

There was a strong positive effect of taking MPH on CRT scores (Cohen's d = 0.40) which was not qualified by frequency of MPH usage, ADHD symptoms, and demographic factors. There was also a somewhat weaker effect for MASs (Cohen's d = 0.07). No effects of MPH and MASs were recorded for risk-taking and numeracy.

CONCLUSIONS

The results indicate that MPH enhances decision-making in tasks where heuristic responses typically bias it.

A sustainable-resilience healthcare network for handling COVID-19 pandemic

In this paper, a new production, allocation, location, inventory holding, distribution, and flow problems for a new sustainable-resilient health care network related to the COVID-19 pandemic under uncertainty is developed that also integrated sustainability aspects and resiliency concepts. Then, a multi-period, multi-product, multi-objective, and multi-echelon mixed-integer linear programming model for the current network is formulated and designed. Formulating a new MILP model to design a sustainable-resilience healthcare network during the COVID-19 pandemic and developing three hybrid meta-heuristic algorithms are among the most important contributions of this research. In order to estimate the values of the required demand for medicines, the simulation approach is employed. To cope with uncertain parameters, stochastic chance-constraint programming is proposed. This paper also proposed three meta-heuristic methods including Multi-Objective Teaching-learning-based optimization (TLBO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) to find Pareto solutions. Since heuristic approaches are sensitive to input parameters, the Taguchi approach is suggested to control and tune the parameters. A comparison is performed by using eight assessment metrics to validate the quality of the obtained Pareto frontier by the heuristic methods on the experiment problems. To validate the current model, a set of sensitivity analysis on important parameters and a real case study in the United States are provided. Based on the empirical experimental results, computational time and eight assessment metrics proposed methodology seems to work well for the considered problems. The results show that by raising the transportation costs, the total cost and the environmental impacts of sustainability increased steadily and the trend of the social responsibility of staff rose gradually between - 20 and 0%, but, dropped suddenly from 0 to + 20%. Also in terms of the on-resiliency of the proposed network, the trends climbed slightly and steadily. Applications of this paper can be useful for hospitals, pharmacies, distributors, medicine manufacturers and the Ministry of Health.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10479-021-04238-2.

CurveP Method for Rendering High-Throughput Screening Dose-Response Data into Digital Fingerprints

The nature of high-throughput screening (HTS) puts certain limits on optimal test conditions for each particular sample; therefore, on top of usual data normalization, additional parsing is often needed to account for incomplete read outs or various artifacts that arise from signal interferences.CurveP is a heuristic, user-tunable curve-cleaning algorithm that attempts to find a minimum set of corrections, which would give a monotonic dose-response curve. After applying the corrections, the algorithm proceeds to calculate a set of numeric features, which can be used as a fingerprint characterizing the sample, or as a vector of independent variables (e.g., molecular descriptors in case of chemical substances testing). The resulting output can be a part of HTS data analysis or can be used as input for a broad spectrum of computational applications, such as quantitative structure-activity relationship (QSAR ) modeling, computational toxicology, bioinformatics, and cheminformatics.

Robust priors for regularized regression

Induction benefits from useful priors. Penalized regression approaches, like ridge regression, shrink weights toward zero but zero association is usually not a sensible prior. Inspired by simple and robust decision heuristics humans use, we constructed non-zero priors for penalized regression models that provide robust and interpretable solutions across several tasks. Our approach enables estimates from a constrained model to serve as a prior for a more general model, yielding a principled way to interpolate between models of differing complexity. We successfully applied this approach to a number of decision and classification problems, as well as analyzing simulated brain imaging data. Models with robust priors had excellent worst-case performance. Solutions followed from the form of the heuristic that was used to derive the prior. These new algorithms can serve applications in data analysis and machine learning, as well as help in understanding how people transition from novice to expert performance.

Intuition and exponential growth: bias and the roles of parameterization and complexity

Exponential growth bias is the phenomenon that humans intuitively underestimate exponential growth. This article reports on an experiment where treatments differ in the parameterization of growth: Exponential growth is communicated to one group in terms of growth rates, and in terms of doubling times to the other. Exponential growth bias is much smaller when doubling times are employed. Considering that in many applications, individuals face a choice between different growth rates, rather than between exponential growth and zero growth, we ask a question where growth is reduced from high to low. Subjects vastly underestimate the effect of this reduction, though less so in the parameterization using doubling times. The answers to this question are more severely biased than one would expect from the answers to the exponential growth questions. These biases emerge despite the sample being highly educated and exhibiting awareness of exponential growth bias. Implications for teaching, the usefulness of heuristics, and policy are discussed.