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Background: Cognitive biases seem to play an important role in the development and maintenance of emotional disorders such as depression and anxiety. Novel procedures, known as Cognitive Bias Modification (CBM), aim to reduce these dysfunctional information processing modes. This study aims to develop a brief online intervention program to modify biased interpretations in depression and anxiety overcoming some methodological issues that have been addressed in previous literature. Methods: Volunteer participants will be recruited via social media, posters and universities. They will be randomly assigned to the experimental group or a waiting list control group. Both groups will attend two assessment sessions at the lab. The assessment will consist of questionnaires measuring cognitive and emotional variables as well as three experimental tasks to measure cognitive biases (i.e., attention, memory and interpretation). After the first assessment session only participants in the experimental group will receive a link to follow the four-sessions program at home. All participants will receive, via email, follow-up questionnaires two weeks and three months after the second assessment session.Discussion: This study will test an online program potentially beneficial to modify cognitive variables in disorders such as depression and anxiety. Several limitations of previous CBM procedures are addressed and the impact of the program both on cognitive performance and clinical symptoms will be explored.Trial registration: This trial was prospectively registered on June 17, 2019 with the ClinicalTrials.gov NCT03987477

The ability to navigate social systems efficiently is critical to our species. Humans appear endowed with a cognitive system that has at least partially formed to best meet the unique cognitive challenges that emerge in a highly social species. Bullshitting, a style of communication characterised by an intent to be convincing or impressive without concern for the truth, is ubiquitous within human societies. Across two studies (N = 1,017), we assess whether participants’ ability to produce satisfying and seemingly accurate bullshit (i.e., explanations of fake concepts) acts as an honest signal of their intelligence. Consistent with our hypotheses, we find that bullshit ability is predictive of participants’ intelligence and individuals capable of producing more satisfying bullshit are judged by second-hand observers to be higher in intelligence. We interpret these results as adding further evidence for human intelligence being naturally geared towards the efficient navigation of social systems. The ability to produce satisfying bullshit may serve to assist individuals in negotiating their social world, both as an energetically efficient strategy for impressing others and as an honest signal of one’s intelligence.

Subjective value for food rewards guide our dietary choices. There is growing evidence that value signals are constructed in the brain by integrating multiple types of information about flavour, taste, and nutritional attributes of the foods. However, much less is known about the influence of food-extrinsic factors such as labels, brands, prices, and packaging designs. In this mini review, we outline recent findings in decision neuroscience, consumer psychology, and food science with regard to the effect of extrinsic factors on food value computations in the human brain. To date, studies have demonstrated that, while the integrated value signal is encoded in the ventromedial prefrontal cortex, information on the extrinsic factors of the food is encoded in diverse brain regions previously implicated in a wide range of functions: cognitive control, memory, emotion and reward processing. We suggest that a comprehensive understanding of food valuation requires elucidation of the mechanisms behind integrating extrinsic factors in the brain to compute an overall subjective value signal.

Changes to our social settings caused by migration, cultural change or pandemics mean that we must learn and adapt to new social norms. Building on the notion that social norms provide a group of individuals with behavioural prescriptions and therefore can be inferred from individuals’ behaviour, I examined how two features of the behavioural patterns of social norms— saliency and valence —affect learning and adaptation. Using a multiplayer star-harvest game, I found that participants initially complied with a variety of social norms exhibited by the other players in the game. Yet after gaining experience with competitive norms, participants did not adapt their behaviour when playing with polite players. This lack of adaptation was explained by the combined contribution of an active and salient behavioural pattern and its negative outcome for others. A computational model fitting procedure suggested that saliency affected learning rates as players learned more from active behaviour than from passive behaviour, while negative outcomes were more readily generalized from one player to others. These results provide a novel cognitive foundation for social norm learning and adaptation and can inform future investigations of cross-cultural differences and social adaptation.

People find positive attribute frames (e.g., 75% lean) more persuasive than negative ones (e.g., 25% fat). In three pre-registered experiments, we tested whether this effect would be magnified by using verbal quantifiers instead of numerical ones (e.g., ‘high % lean’ vs. ‘75% lean’). This moderating effect of quantifier format was predicted based on previous empirical work and two non-exclusive accounts of framing effects. First, verbal quantifiers are presumed to be a more intuitive format than numerical quantifiers, so might predispose people more to judgement biases such as the framing effect. Second, verbal quantifiers draw a greater focus to the attributes they describe. This could provide a linguistic signal that the positive frame is better than the negative one. In three experiments, we manipulated the attribute frame (positive or negative) and the quantifier format (verbal or numerical) between-subjects, and quantity pairs (e.g., 5% fat and 95% lean or 25% fat and 75% lean) within-subjects. We also tested if participants focused more on the attributes in the frame, by measuring whether participants selected causal sentence completions about the beef that focused on why it had fat meat or lean meat. Results showed a robust framing effect, which was partially mediated by the focus of the sentence completions. However, the verbal format did not increase the magnitude of the framing effect. These results suggest that a focus on the attribute contributes to the framing effect, but contrary to past work, this focus is not different between verbal and numerical quantifiers.

The coronavirus disease 2019 (COVID-19) outbreak is threatening not only health but also life worldwide. It is important to encourage citizens to voluntarily practise infection prevention (IP) behaviours such as social distancing and self-restraint. Previous research on social cognition suggested that emphasising self-identity is key to changing a person’s behaviour. The present study investigated whether reminders that highlight self-identity would be effective in changing intention and behaviour related to the COVID-19 outbreak, and hypothesised that those who read reminders highlighting self-identity (‘Don’t be a spreader’) would change IP intention and behaviour better than those who read ‘Don’t spread’ or no reminder. We conducted a two-wave survey of the same participants with a one-week interval, during which we assigned one of three reminder conditions to the participants: ‘Don’t spread’ (spreading condition), ‘Don’t be a spreader’ (spreader condition), and no reminder (control condition). Participants marked their responses to IP intentions and actual behaviours each week based on the Japanese Ministry of Health, Labour, and Welfare guidelines. While the results did not show significant differences between the conditions, the post-hoc analyses showed significant equivalence in either IP intentions or behavioural scores. We discussed the results from the perspective of the effect size, ceiling effects, and ways of manipulation checks as future methods with more effective persuasive messaging. Following in-principle acceptance, the approved Stage 1 version of this manuscript was preregistered on the OSF at https://doi.org/10.17605/OSF.IO/KZ5Y4. This preregistration was performed prior to data collection and analysis.

Human decision-making is often swayed by irrecoverable investments even though it should only be based on future – and not past – costs and benefits. Although this sunk cost effect is widely documented and can lead to devastating losses, the underlying psychological mechanisms are unclear. To tease apart possible explanations through a comparative approach, we assessed capuchin and rhesus monkeys’ susceptibility to sunk costs in a psychomotor task. Monkeys needed to track a moving target with a joystick-controlled cursor for variable durations. They could stop at any time, ending the trial without reward. To minimize the work required for a reward, monkeys should have always persisted for at least 1 second, but should have abandoned the trial if that did not yield a reward. Capuchin monkeys and especially rhesus macaques persisted to trial completion even when it was suboptimal, and were more likely to complete the trial the longer they had already tracked the target. These effects were less pronounced, although still present, when the change in expected tracking duration was signalled visually. These results show that sunk cost effects can arise in the absence of human-unique factors and may emerge, in part, because persisting can resolve uncertainty.

A core proposition in economics is that voluntary exchanges benefit both parties. We show that people often deny the mutually beneficial nature of exchange, instead espousing the belief that one or both parties fail to benefit from the exchange. Across 4 studies (and 8 further studies in the Supplementary Materials), participants read about simple exchanges of goods and services, judging whether each party to the transaction was better off or worse off afterwards. These studies revealed that win–win denial is pervasive, with buyers consistently seen as less likely to benefit from transactions than sellers. Several potential psychological mechanisms underlying win–win denial are considered, with the most important influences being mercantilist theories of value (confusing wealth for money) and theory of mind limits (failing to observe that people do not arbitrarily enter exchanges). We argue that these results have widespread implications for politics and society.

Some issues that have been settled by the scientific community, such as evolution, the effectiveness of vaccinations, and the role of CO2 emissions in climate change, continue to be rejected by segments of the public. This rejection is typically driven by people's worldviews, and to date most research has found that conservatives are uniformly more likely to reject scientific findings than liberals across a number of domains. We report a large (N>1,000) preregistered study that addresses two questions: First, can we find science denial on the left?Endorsement of pseudoscientific complementary and alternative medicines (CAM) has been anecdotally cited as being more consonant with liberals than conservatives. Against this claim, we found more support for CAM among conservatives than liberals. Second, we asked how liberals and conservatives resolve dilemmas in which an issue triggers two opposing facets of their worldviews. We probed attitudes on gender equality and the evolution of sex differences---two constructs that may create conflicts for liberals (who endorse evolution but also equality) and conservatives (who endorse gender differences but are sceptical of evolution). We find that many conservatives reject both gender equality and evolution of sex differences, and instead embrace ``naturally occurring'' gender differences. Many liberals, by contrast, reject evolved gender differences, as well as naturally occurring gender differences, while nonetheless strongly endorsing evolution.

The COVID-19 pandemic entails challenging psychological conditions for the population, requiring them to make many decisions under stress. In this study, 641 participants were presented with different moral decision-making tasks, and completed a survey on mental health status and experiences, concerns, behaviors and beliefs related to the COVID-19. Results showed that the pandemic is placing a great psychological burden on the population. Also, that decision-making processes are being affected during the crisis, in a dichotomous way. Altruistic behaviors are promoted when people are suffering with high levels of psychological impact, and when they are concerned about others contracting the disease. However, egoistic behaviors are facilitated when concerns affect the self. Similarly, psychological impact, concerns about the self, and worsened physical health predict more automatic responses to framing problems and moral dilemmas. Nevertheless, when concerns relate to the others, or when people are more informed and/or carefree, more controlled responses emerge.

We examine the extent to which perceptual decision-making processes differ as a function of the time in the academic term in which the participant enrolls in the experiment and whether the participant is an undergraduate who completes the experiment for course credit, a paid participant who completes the experiment in the lab, or a paid participant recruited via Amazon Mechanical Turk who completes the experiment online. In Study 1, we conducted a survey to examine cognitive psychologists expectations regarding the quality of data obtained from these different groups of participants. We find that cognitive psychologists expect performance and response caution to be lowest among undergraduate participants who enroll at the end of the academic term, and highest among paid in-lab participants. Studies 2 and 3 tested these expectations using two common perceptual decision-making paradigms. Overall, we found little evidence for systematic time-of-term effects among undergraduate participants. The different participant groups responded to standard stimulus quality and speed/accuracy emphasis manipulations in similar ways. Among participants recruited via Mechanical Turk, the effect of speed/accuracy emphasis on response caution was strongest. This group also showed poorer discrimination performance than the other groups in a motion discrimination task, but not in a brightness discrimination task. We conclude that online crowdsourcing platforms can provide high quality perceptual decision-making data, but give recommendations for how data quality can be maximized when using these platforms for recruitment.

Retail investors increasingly have access to both platforms that allow for sophisticated trading strategies - those profit in ways other than by selling an owned stock after price increase – and to financial-analyst reports upon which to build investment strategies. Building on the predecisional distortion literature, we study how consumers of financial-analyst reports bias information to support emerging preferences, both directional and volatility-based trades. We then present the results of two experiments conducted with retail investors with high financial literacy asked to develop investment strategies based financial-analyst reports. We find that those tend to who develop preferences toward bearish trades (i.e., profits from a stock price decrease) tend to bias new information more strongly those who develop preferences toward bullish trades (i.e., profits from a stock price increase). We also show that those leaning toward volatility-based trades (i.e., profit from either small or large price movements) tend to evaluate information in a less biased way and those leaning toward directional trades (bullish or bearish).

For many types of behaviors, whether a specific instance of that behavior is either blame or praiseworthy depends on how much of the behavior is done or how people go about doing it. For instance, for a behavior such as “replying quickly to emails”, whether a specific reply is blame or praiseworthy will depend on the timeliness of that reply. Such behaviors lie on a continuum in which part of the continuum is praiseworthy (replying quickly) and another part of the continuum is blameworthy (replying late). As praise shifts towards blame along such behavioral continua, the resulting blame-praise curve must have a specific shape. A number of questions therefore arise. What determines the shape of that curve? And what determines “the neutral point”, i.e., the point along a behavioral continuum at which people neither blame nor praise? Seven studies explore these issues, focusing specifically on the impact of statistical information, and provide evidence for a hypothesis we call the “asymmetric frequency hypothesis.”

It is unknown whether children enjoy punishing transgressors and whether they are motivated by retribution, as adults frequently are. Children’s approaches to compensation of victims have been little studied. British, Colombian and Italian 7- to 11-year-old children (N = 123) operated a Justice System in which they viewed different moral transgressions in Minecraft, a globally popular videogame, either face-to-face with an experimenter or over the internet. Children could respond to transgressions by punishing transgressors and compensating victims. The purpose of the system was framed in three ways (between-subject): retribution; deterrence; or compensation. We measured children’s punitive and compensatory tendencies, their enjoyment of punishment and compensation, and their endorsement of retribution vs deterrence as punishment justifications, during and/or after justice administration. Children overwhelmingly endorsed deterrence over retribution as their punishment justification, irrespective of age, country and frame. When asked to reproduce the presented frame, children more reliably reproduced the deterrence than retribution frame. Punishment enjoyment decreased while compensation enjoyment increased over time. Despite enjoying compensation more, children preferentially endorsed punishment over compensation, especially with increasing age (after justice administration) and increasing transgression severity (during justice administration). Reported deterrent justifications, superior reproduction of deterrence framing, lower enjoyment of punishment compared to compensation, and higher endorsement of punishment over compensation together suggest that children’s punishment behaviour is primarily motivated by deterrence and sense of duty. Face-to-face and internet-mediated responses were not distinguishable, suggesting a route to social psychology research with primary school-aged children in times of social distancing.

In early March 2020, two crises quickly emerged: the COVID-19 public health crisis and a corresponding economic crisis resulting from business closures and skyrocketing job losses. While the link between socioeconomic status and infectious disease is well-documented, the psychological impacts of financial constraint on perceptions of disease spread and subsequent actions is not well understood. We show that financial constraint predicts people’s beliefs about both their personal risk of infection and the national spread of the virus as well as their social distancing behavior. In addition, we compare the predictive utility of financial constraint to two other commonly studied factors: political partisanship and local disease severity. The strength of the effect of financial constraint equals or eclipses the influence of partisanship on beliefs and is much larger than that of local disease severity. We also show that negative affect partially mediates the relationship between financial constraint and COVID-19 beliefs and social distancing behaviors. These results suggest the economic crisis created by COVID-19 is spilling over into people’s beliefs about the health crisis and their behaviors. Correspondingly, variables related to the economic crisis created by COVID-19 can be used to predict both people’s beliefs about the health crisis as well as relevant behaviors.

Previous work has shown that the cognitive processes involved in mental arithmetic can bedecomposed into three stages: encoding, calculation, and production. Models of mental arithmetic hypothesize varying degrees of independence between these processes of encoding and calculation. In the present study, we tested whether encoding and calculation are independent by having participants complete an addition verification task. We manipulated problem size (small, large) as well as problem format, having participants verify equations presented either as Arabic digits (e.g., “3 + 7 = 10”) or using words (e.g., “three + seven = ten”). In addition, we collected trial-by-trial strategy reports. Though we found main effects of both problem size and format on response times, we found no interaction between the two factors, supporting the hypothesis that encoding and calculation function independently. However, strategy reports indicated that manipulating format caused a shift from retrieval based strategies to procedural strategies, particularly on large problems. We discuss these results in light of two competing models of mental arithmetic.

One of the oldest debates in psychological research into politicized science such as nanotechnology, vaccination, or climate change centers around the role of knowledge. Does increased knowledge of the science affect beliefs about it? While research has traditionally focused on the role of object-level knowledge, here we highlight the importance of meta-knowledge: How much people believe they know about the science. Specifically, we demonstrate the importance of meta-knowledge (measured as confidence in knowledge) for explaining beliefs about science with one of the most contested examples: climate change. For a national Germany sample (N = 509), frequentist and Bayesian analyses demonstrated that climate change meta-knowledge was predictive of climate change beliefs, above and beyond object-level climate change knowledge. These results held for both the belief that climate change is risky, and the belief that climate change is anthropogenic, and when controlling for political attitude, and demographic variables. Furthermore, for a second national German sample (N = 588), confidence in climate change knowledge was a stronger predictor of climate change beliefs compared to confidence in other-domain (biological and physical) science knowledge, suggesting that outside of the respective domain, metacognitive confidence did not explain beliefs. These results highlight the relevance of domain-specific metacognition for explaining beliefs about the contested science of climate change. By demonstrating the relevance of metacognitive, rather than solely object-level thought, these results add to our understanding of the cognitive mechanisms involved in the formation of beliefs about politicized science.

In a recent issue of Earth’s Future [vol. 7, pp. 1020-1026], S. C. Lewis et al. recommended a numerically bounded linguistic probability (NBLP) scheme for communicating probabilistic information in extreme event attribution studies. We provide a critique of NBLP schemes in general and of Lewis et al.’s in particular, noting two key points. First, evidence from voluminous behavioral science research on the interpretation of linguistic probabilities indicates that NBLP schemes are an ineffective means of communicating uncertainty to others. Second, where the motivation to implement such schemes nevertheless persists, the schemes should be developed through an evidence-based approach that seeks to optimize interpretational agreement between the scheme and users.

Alcohol use is a considerable public health concern which can lead to negative health and social consequences. Despite wide knowledge and acceptance of these consequences many individuals continue to drink above lower risk guidelines. A lack of regret for these consequences may partially explain this. In two studies (one cross-sectional online and one ecological momentary assessment study) we examined the prevalence of regrettable experiences; from common regrets (e.g. hangover), and risky behaviours (e.g. drug taking) to serious regrets (e.g. driving under the influence), over a two-week period. We also examined whether alcohol consumption predicted the quantity of different regrets, but also whether the quantity of regrettable experiences predicted future intentions to consume alcohol. Prevalence of regrettable experiences was high (e.g. 79.0% of individuals in study 1 and 66.9% of individuals in study two experienced a hangover). Prevalence was higher for common regrets compared to risky behaviours and serious regrets. In study one, units of alcohol consumed over the previous fortnight predicted the number of different regrettable experiences over the same period. In study two, units consumed on a day-to-day basis predicted the number of regrets on that same basis. Neither study demonstrated evidence for the predictive utility of regrets for intentions to consume alcohol in the future. These findings suggest a high prevalence of regrettable experiences, that are predicted by increased levels of alcohol consumption. However, there was little evidence that increased number of experiences predicted future drinking intentions. Regrettable experiences are prevalent following consumption, however a focus on these regrets to deter future alcohol consumption may not be an effective psychological intervention.

Problem definitions are defined here as one-sided in the case that while they might take into account one class of negative outcomes, such as those associated with the problem, at the same time they might ignore other classes of negative outcomes, such as those that may be encountered while implementing interventions that try to avoid the problem. An example is amputating all limbs with potentially cancerous moles on them to reduce the risk of mortality due to cancer as much as possible, without considering the increase in mortality due to the amputations. The global response to COVID-19 has been characterized by the availability of mathematical models for the potential mortality due to the spread of the pandemic. However in some cases the researchers guiding the responses of their respective nations with their mathematical models have explicitly pointed out that corresponding mathematical models of the impacts of economic shutdowns or other potential interventions on mortality have not been incorporated, and that there is a critical need to include such models. This paper generalizes this problem of one-sided problem definitions past the COVID-19 response to a wide variety of group problems where the pattern of one-sidedness applies, and explores how in current group decision-making systems one-sided problem definitions might consistently tend to be exploited in a way that is detrimental to collective well-being, as well as how a system of group decision-making meeting the requirements of a General Collective Intelligence solves the problem of one-sidedness to reliably maximize collective well-being.

Impulsive traits, broadly construed, are thought to play a role in under- or over-weight. For example, the behavioural economic factor of delay discounting, which determines the relative value between sooner and later rewards, is thought to be predictive of body composition. However, this evidence is mixed and recently a case against such a connection was made (Veillard & Vincent, 2020). Two studies (N = 384 and 401) explored the potential relationships between discounting for money, weight loss, and food rewards to body mass index or waist-to-height ratio measures. Three forms of models were considered: that discounting and body composition are correlated, that there is a main effect of discounting once the role of age upon body composition is accounted for, or that discounting moderates the rate of weight gain over time. A consistent lack of evidence was found for any connection between discounting (of multiple commodities) and body composition (measured in 2 ways). While some measure of impulsivity may well relate to body composition, our findings suggest that temporal discounting specifically may not be predictive of body composition.

Although human existence is enveloped by ideologies, remarkably little is understood about the relationships between ideological attitudes and psychological traits. Even less is known about how cognitive dispositions – individual differences in how information is perceived and processed – sculpt individuals’ ideological worldviews, proclivities for extremist beliefs, and resistance (or receptivity) to evidence. Using an unprecedented number of cognitive tasks (N=37) and personality surveys (N=22), along with data-driven analyses including drift-diffusion and Bayesian modelling, we uncovered the specific psychological signatures of political, nationalistic, religious, and dogmatic beliefs. Cognitive and personality assessments consistently outperformed demographic predictors in accounting for individual differences in ideological preferences by 4 to 15-fold. Furthermore, data-driven analyses revealed that individuals’ ideological attitudes mirrored their cognitive decision-making strategies. Conservatism and nationalism were related to greater caution in perceptual decision-making tasks and to reduced strategic information processing, while dogmatism was associated with slower evidence accumulation and impulsive tendencies. Religiosity was implicated in heightened agreeableness and risk perception. Extreme pro-group attitudes, including violence endorsement against outgroups, were linked to poorer working memory, slower perceptual strategies, and tendencies towards impulsivity and sensation-seeking – reflecting overlaps with the psychological profiles of conservatism and dogmatism. Cognitive and personality signatures were also generated for ideologies such as authoritarianism, system justification, social dominance orientation, patriotism, and receptivity to evidence or alternative viewpoints; elucidating their underpinnings and highlighting avenues for future research. Together these findings suggest that ideological worldviews may be reflective of low-level perceptual and cognitive functions.

What are the socio-political consequences of infectious diseases? Humans have evolved to avoid disease and infection, resulting in a set of psychological mechanisms that promote disease-avoidance, referred to as the behavioural immune system (BIS). One manifestation of the BIS is the cautious avoidance of unfamiliar, foreign, or potentially contaminating stimuli. Specifically, when disease infection risk is salient or prevalent, authoritarian attitudes can emerge that seek to avoid and reject foreign outgroups while favoring homogenous, familiar ingroups. In the largest study conducted on the topic to date (N>240,000), elevated regional levels of infectious pathogens were related to more authoritarian attitudes on three geographical levels: across US metropolitan regions, US states, and cross-culturally across 47 countries. The link between pathogen prevalence and authoritarian psychological dispositions predicted conservative voting behavior in the 2016 US Presidential Election as well as more authoritarian governance and state laws, in which one group of people imposes asymmetrical laws on others in a hierarchical structure. Furthermore, cross-cultural analysis illustrated that the relationship between infectious diseases and authoritarianism was pronounced for infectious diseases that can be acquired from other humans (nonzoonotic), and does not generalize to other infectious diseases that can only be acquired from non-human species (zoonotic diseases). At a time of heightened awareness of infectious diseases, these findings are important reminders that public health and ecology can have ramifications for socio-political attitudes, and this can shape how citizens vote as well as how they govern and are governed.

Humans can shorten their decisions at the expense of the decisions accuracy, a phenomenon known as speed-accuracy tradeoff (SAT). The dominant account of SAT is the diffusion model, which is often thought to explain all effects related to SAT. However, previous research has typically examined either only a few SAT conditions or only tested a few subjects. Here we collected data from 20 subjects who performed a perceptual discrimination task with five different difficulty levels. We further included five different SAT conditions with each subject completing a total of 5,000 trials over five sessions. We found that the five SAT conditions produced robustly U-shaped curves for (i) the difference between error and correct response times (RTs), (ii) the ratio of the standard deviation and mean of the RT distributions, and (iii) the skewness of the RT distributions. Each of these three effects was present for each of the five difficulty levels. We show the standard diffusion model cannot account for the last two effects and can only account for the first U-shaped function if the starting point of the accumulation is not constrained to always be within the two boundaries. Further, both the SAT and difficulty manipulations resulted in changes in all diffusion model parameters despite the fact that the diffusion model’s “selective influence” assumption postulates that these manipulations should only affect the boundary and drift rate, respectively. These results demonstrate that the diffusion model cannot fully explain the effects of speed-accuracy tradeoff on RT and establishes three robust but challenging effects that models of speed-accuracy tradeoff should account for.

In daily life, humans often perform visual tasks together such as, for instance, solving puzzles or looking for a misplaced key. In such tasks, humans tend to distribute task demands, enabling them to reach a higher performance compared to performing the same task alone – a group benefit. Research on group benefits in joint visual tasks has found that the availability of performance feedback and information about each other’s actions are two important factors influencing group benefits. Yet, no study has systematically investigated for these two factors which information is minimally required for co-actors to 1) attain group benefits, 2) devise collaborative strategies, and 3) further extend an already attained group benefit. Across eight experiments, we systematically varied the information co-actors received in a joint multiple object tracking task along an information continuum to address these three points. We find that co-actors 1) already attained group benefits without receiving any information, 2) minimally required team performance feedback or information about the co-actor’s actions to collaborate, and 3) devised collaborative strategies more quickly with additional information. Furthermore, we used a linear regression to predict group benefits and find that several factors (including personality traits) explain non-redundant variance. Collectively, our findings suggest that group benefits in joint visuospatial tasks come for "free" as no information exchange between co-actors is required to attain them. To further boost group performance, co-actors make use of coordination mechanisms to devise labour division strategies and these mechanisms depend on exchanging action information and/or receiving team performance feedback.

It is recommended that researchers report effect sizes along with statistical results to aid in interpreting the magnitude of results. According to recent surveys of published research, psychologists typically find effect sizes ranging from r = .11 to r = .30. While these numbers may be informative for scientists, no research has examined how lay people perceive the range of effect sizes typically reported in psychological research. In two studies, we showed online participants (N = 1,204) graphs depicting a range of effect sizes in different formats. We demonstrate that lay people perceive psychological effects to be small, rather meaningless, and unconvincing. Even the largest effects we examined (corresponding to a Cohen’s d = .90), which are exceedingly uncommon in reality, were considered small-to-moderate in size by lay people. Science communicators and policymakers should consider this obstacle when attempting to communicate the effectiveness of research results.

Expert opinions admitted by courts are not always valid and reliable. However, we know little about how indicators of opinion quality affect the persuasiveness of an expert. In this study 25 Australian magistrates and 22 jury-eligible lay-people rated the persuasiveness (via credibility, value, and weight) of either a high or a low quality expert opinion. Opinion quality was determined using attributes specified in the Expert Persuasion Expectancy (ExPEx) framework: Field, Specialty, Ability, and Trustworthiness. Both magistrates and jurors were significantly more persuaded by the high than the low quality expert opinion. Magistrates were also significantly more sceptical of the expert opinion than lay-people, and when given the opportunity sought information that was logically relevant to their decision. These results suggest that magistrates can differentiate between high and low quality expert opinions, but it is unclear if the information they need for the task is actually available for use during trials.

Much of the communication around the current pandemic stresses the exponential growth in the number of infections. We observe that this approach may backfire: it becomes difficult to convince people to obey strict constraints when what will be achieved is merely a short delay in that growth. Based on a method we successfully used in a context of pension savings, we suggest how best to frame the gains of delaying tactics

Similarity is one of the most important relations humans perceive, arguably subserving category learning and categorization, generalization and discrimination, judgment and decision making, and other cognitive functions. Researchers have proposed a wide range of representations and processes that could be at play in similarity judgment, yet have not comprehensively compared the power of these representations and processes for predicting similarity within and across different semantic categories. We performed such a comparison by pairing eight prominent vector semantic representations with seven established similarity metrics that could operate on these representations, as well as supervised methods for dimensional weighting in the similarity function. This approach yields a factorial model structure with 56 distinct representation-process pairs, which we tested on a novel dataset of similarity judgments between pairs of co-hyponymic words in eight categories. We found that cosine similarity and Pearson correlation were the overall best performing unweighted similarity functions, and that word vectors derived from free association norms often outperformed word vectors derived from text (including those specialized for similarity). Importantly, models that used human similarity judgments to learn category-specific weights on dimensions yielded substantially better predictions than all unweighted approaches across all types of similarity functions and representations, although dimension weights did not generalize well across semantic categories, suggesting strong category context effects in similarity judgment. We discuss implications of these results for cognitive modeling and natural language processing, as well as for theories of representations and processes involved in similarity.

Our self-concept contributes to our sense of identity over time. Yet, self-perception is motivated and serves survival and thus does not reflect stable inner states or accurate biographical accounts. Literature indicates that different types of comparison standards act as reference frames in evaluating attributes that constitute the self. However, the role of comparisons in self-perception has been underestimated, arguably due to lack of a guiding framework that takes into account relevant aspects of comparison processes and their interdependence. I propose a general comparative model of self-perception that consists of a basic comparison process involving the individual’s prior mental representation of the target dimension, the construal of the comparison standard, and the comparison outcome representing the posterior representation of the target dimension. The generated dimensional construal is then appraised with respect to one’s motives and controllability and goes on to shape emotional, cognitive, and behavioral responses. Contextual and personal factors influence the comparison process. This model may be informative in better understanding comparison processes in our everyday life, their role in shaping self-perception, as well as in designing interventions to assist people overcome undesirable consequences of comparative behavior.

It is widely believed that feedback improves behavior but the mechanisms behind this improvement remain unclear. Different theories postulate that feedback has either a direct effect on performance through automatic reinforcement mechanisms or only an indirect effect mediated by a deliberate change in strategy. To adjudicate between these two competing accounts, we performed a large-scale study including 443 subjects; approximately half of them received trial-by-trial feedback on a perceptual task, while the other half did not receive such feedback. We found that feedback had no effect on either perceptual or metacognitive sensitivity. On the other hand, feedback significantly affected subjects’ response strategies by reducing bias and improving calibration in both the perceptual and metacognitive judgments. These results strongly support the view that feedback does not improve behavior through direct reinforcement mechanisms but that its beneficial effects stem from allowing people to adjust their strategies for performing the task.

Moral judgments are typically explained by a combination of either deontological considerations about the nature of actions, or quantitative assessments of the consequences of those actions. These proposals, however, have serious limitations such as being insensitive to personal biases and global circumstances. This study presents an alternative approach based on comparative affective evaluations that modulate responses as more contextual information is presented to the choice set. We show that, when we make a moral decision, we do not simply judge the action and/or its consequences, we judge the protagonist performing the action embedded in a given set of circumstances and we normalize their behavior using the same gain control mechanism that operates in other sensory and motor domains. The explanatory power of this novel approach is broader than that provided by traditional paradigms and can be easily applied to more ecologically relevant scenarios.

We propose that predictability is a key factor for judging the morality of others, one which has so far been neglected by dominant theories of moral psychology. Across four studies (N = 1,457 US residents and 81 traditional people of Papua), participants judged agents acting in sacrificial moral dilemmas. Utilitarian agents, described as opting to sacrifice a single individual for the greater good, were perceived as less predictable and less moral than deontological agents whose inaction resulted in five people being harmed. We show that these effects generalize to a non- Western sample of the Dani people, a traditional indigenous society of Papua. This moral preference for deontological agents was not due to a mere misunderstanding of utilitarian principles, as it persisted even when the underlying logic of utilitarian acts was explained. Furthermore, this preference reverses when the actions of utilitarian agents are made to seem more predictable, such as by presenting scenarios in which utilitarian acts involve an indirect (e.g., redirecting a trolley by flipping a switch) as opposed to direct (e.g., pushing a stranger onto trolley tracks) method of sacrifice. Despite the consequences of the sacrificial choice being identical for both direct and indirect acts, people perceived utilitarian agents to be less predictable, and consequently less moral when a direct sacrificial act was performed.

Research is surprisingly scarce on how people react to the prospect of a sure loss. Do they seek risk or focus on what is left to be saved? We addressed this question in two experiments relying on a financial decision-making framework. Specifically, we asked participants to allocate money between two options: i) a loss option where, for sure, they would end up with less than allocated, or ii) a mixed gamble with a positive expected outcome, but also the possibility of an even larger loss. Participants made multiple choices with varied sizes of sure losses or expected outcomes and, for the majority of choices, were either risk-averse or indifferent. Our findings indicate a surprisingly large tolerance for sure losses at the expense of mixed gambles yielding better expected outcomes. We discuss the implications of this sure-loss tolerance for psychological research.

Our conscious perception of the world is not an instantaneous moment-by-moment construction, but rather the information subsequent in time seems to affect the percept of the prior event, which was known as postdictive effect. A recent study reported this postdictive effect could even occur in choice decision. The present study sought to test whether the striking postdictive effect of choice reflects the modulation of attention on choice, by directly and systematically manipulating attention in two experiments. Specifically, Experiment 1 revealed that the robust postdictive effect of choice was almost completely eliminated when the attentional bias triggered by a sudden color change was removed. More importantly, Experiment 2 demonstrated that the postdictive effect of choice could be modulated by directly manipulating participants’ attention with a spatial cue, in particular when the cue appeared at short time delays (less than 500 ms). These findings suggest that choice decision could be considerably postdicted by attention and this effect was most pronounced within a short time window wherein the decision was most likely in progress.

Factors such as time pressure and psychosocial stress may increase or decrease prosocial behavior, depending on a number of factors. One factor that consistently positively impacts prosocial behavior is relationship status: prosocial behavior is more likely toward kin than toward strangers. The interactions among stress, kin relationships, and prosocial behavior were examined in two separate experiments. In Study 1, 79 university students were asked to decide how much money to donate to family members, friends, or strangers, either under time pressure or with no time constraints. Participants donated more to close kin and friends than to strangers, but time pressure did not increase prosocial behavior. In Study 2, 94 university students completed the Trier Social Stress Task for Groups (TSST-G) or a control task, followed by a similar donation task as used in Study 1. Participants donated more to close kin and friends than to strangers, but stress did not influence donation amounts. These results do not support the hypothesis that stress due to time pressure or psychosocial factors increase prosocial behavior.

Human decisions can be biased by irrelevant information. For example, choices between two preferred alternatives can be swayed by a third option that is inferior or unavailable. Previous work has identified three classic biases, known as the attraction, similarity and compromise effects, which arise during choices between economic alternatives defined by two attributes. However, the reliability, interrelationship, and computational origin of these three biases has been controversial. Here, a large cohort of human participants made incentive-compatible choices among assets that varied in price and quality. Instead of focusing on the three classic effects, we sampled decoy stimuli exhaustively across bidimensional multi-attribute space and constructed a full map of decoy influence on choices between two otherwise preferred target items. Our analysis revealed that the decoy influence map was highly structured even beyond the three classic biases. We identified a very simple model that can fully reproduce the decoy influence map and capture its variability in individual participants. This model reveals that the three decoy effects are not distinct phenomena but are all special cases of a more general principle, by which attribute values are repulsed away from the context provided by rival options. The model helps understand why the biases are typically correlated across participants and allows us to validate a new prediction about their interrelationship. This work helps to clarify the origin of three of the most widely-studied biases in human decision-making.

Computational implementations of Theory of Mind (ToM), the ability to attribute mental states to others, has been used to investigate a variety of issues. This includes the effect of framing effects on, or inter-species differences in, ability to do ToM (Devaine et al., 2014a, 2017), ToM in autists (d’Arc et al., 2018), or providing an explanation for the apparent limits on human ability to do ToM recursively (Devaine et al., 2014b). It has been implemented in the VBA package for Matlab (Daunizeau et al., 2014), but not in any free and open-source software. Therefore this thesis presents the Theory of Mind simulation using Python (tomsup) package. The tomsup package provides accessible tools for running agent-based models in a game theory context, and allows the implementation of a computational model of ToM, either in agent-based models or in interaction with a human player. The implementation of the ToM model was originally proposed by Yoshida et al. (2008), and was developed by drawing on the Free Energy Principle (Friston, 2010) to its current form as it is in Devaine et al. (2017), where it is generalized to any 2-player game which can be operationalized as a 2-by-2 payoff matrix. Importantly, the ToM implementation introduces a sophistication level k, which determines how many recursive simulations of its opponent it can perform, hereby assuming bounded rationality (Kahneman, 2003). An agent using the ToM model, denoted as k-ToM, uses a variational Bayes Laplace approximation (Daunizeau, 2017b) on a turn-by-turn basis to infer its opponent’s model parameters and sophistication level, based on which it predicts the opponent’s choice and acts accordingly. An agent-based model simulation using the competitive matching pennies game was done to perform a prelim- inary investigation of the behaviour of the k-ToM model. Most importantly, it was found that k-ToM’s prior beliefs about its opponent have a notable effect on its performance, even over many trials, warranting further research into how its priors should be formed. Various ways are suggested in which the tomsup package and the k-ToM model could be applied and developed further, as well as a discussion on how to make it broadly available, so as to scaffold future research using computational ToM models.

The digital revolution has fundamentally changed social information exchange and vastly increased exposure to the opinions of others. However, it is unclear whether exchanging such large amounts of information benefits decision making. Exchanging a moderate amount or aggregated forms of social information may indeed avoid information overload and foster better decisions. We performed experiments in which participants were asked to estimate quantities twice, before and after receiving either all of their peers’ estimates or the geometric mean thereof. We find that second estimates were more accurate when participants observed all estimates than when they saw their geometric mean. Using a model, we predict that accuracy improves most when about twelve estimates are exchanged, independent of group size. Taken together, our results thus suggest that to optimise collective decisions, individuals should receive all decisions from a moderate number of group members, rather than aggregated opinions of large crowds.

Evidence accumulation models (EAMs) have become the dominant explanation of how the decision-making process operates, proposing that decisions are the result of a process of evidence accumulation. The primary use of EAMs has been as "measurement tools" of the underlying decision-making process, where researchers apply EAMs to empirical data to estimate participants' task ability (i.e., the "drift rate"), response caution (i.e., the "decision threshold"), and the time taken for other processes (i.e., the "non-decision time"), making EAMs a powerful tool for discriminating between competing psychological theories. Recent studies have brought into question the mapping between the latent parameters of EAMs and the theoretical constructs that they are thought to represent, showing that emphasizing urgent responding -- which intuitively should selectively influence decision threshold -- may also influence drift rate and/or non-decision time. However, these findings have been mixed, leading to differences in opinion between experts in the field. The current study aims to provide a more conclusive answer to the implications of emphasizing urgent responding, providing a re-analyse of 6 data sets from previous studies using two different EAMs -- the diffusion model and the linear ballistic accumulator (LBA) -- with state-of-the-art methods for model selection based inference. The findings display clear evidence for a difference in conclusions between the two models, with the diffusion model suggesting that decision threshold and non-decision time decrease when urgency is emphasized, and the LBA suggesting that decision threshold and drift rate decrease when urgency is emphasized. Furthermore, although these models disagree regarding whether non-decision time or drift rate decrease under urgency emphasis, both show clear evidence that emphasizing urgency does not selectively influence decision threshold. These findings suggest that researchers should revise their assumptions about certain experimental manipulations, the specification of certain EAMs, or perhaps both.

Visual ensembles, like leaves on a tree, often share properties such as shape or color. This redundancy can be quantified as a feature probability distribution whose summary statistics (e.g., mean) observers can report explicitly. Here, we show that such explicit reports underestimate the richness of ensemble perception. Participants (N=12 per condition) searched for an odd-one-out target among heterogeneous distractors and their memory of distractor characteristics was tested explicitly or implicitly. Our observers could explicitly distinguish distractor sets with different mean and variance, but not differently-shaped probability distributions. In contrast, implicit assessment revealed encoding of mean, variance, and importantly, also distribution shape. Furthermore, explicit measures had common noise sources that distinguished them from implicit measures. We conclude that feature distributions are encoded in rich detail and can guide behaviour, while explicit summary judgments are based on information equivalent to a few samples from fully encoded distributions.

Delay-discounting studies in neuroscience, psychology and economics have been mostly focused on concepts of self-control, reward evaluation and discounting. In the meantime, the link between intertemporal choice and time perception has been relatively under-investigated. Compared to the extensive literature on delay discounting, only a handful of studies suggest that individual differences in timing modulate delay discounting behavior. We recently compared subjects discount factors when faced with short (seconds) and long (days) time-horizon decisions. The short delays were experienced by the subjects after each choice. Only one long delay was experienced, after all the choices were made. While the subjects behavior was correlated across the two tasks, there remained a substantial amount of unexplained variance. Here, we set out to test whether individual variation in time perception might contribute to this unexplained variance. In particular, that individual differences in time perception would influence decisions about short experienced delays but not long delays. Using a within-subject experiment to compare timing on the range of seconds to minutes with delay discounting on both the time-scale of seconds and of days, we found that intertemporal choice can be captured by a model that incorporates subjective timing but this model is not significantly better than the one with objective timing. While we found some evidence that internal clock speed accounts for some unexplained variance between choices across time-horizons, overall our findings suggest a nominal contribution of the altered sense of time in intertemporal choice.

A better understanding of how human factors may shape risk perception and risk-taking is key to improve investment performance. This chapter draws on research on the psychology of risk and decision-making under uncertainty to shed light on these issues. The first part focuses on the evaluation of risk and uncertainty. After outlining the different psychological concepts of uncertainty, we review the different factors influencing individuals’ subjective perception of risk as well as the heuristics they may use to gauge risk and uncertainty. The second part of this chapter focuses on the different factors influencing human risk-taking behaviour, ranging from attitudes to risk to the contexts in which risky decisions take place, and the role of emotions in risk-taking.

Driver models help improve and evaluate systems for road crash mitigation and avoidance. As systems develop and address increasingly complex scenarios. Driver models also need to be developed to be able to account for the interactions among these road users. Even as we improve driver modeling with control-theory models and actual data-driven implementations, existing driver models fail to sufficiently take interaction among road users into consideration. This paper addresses this insufficiency by proposing a new operational framework to computationally model interactions among road users. For this purpose, we introduce a definition for interaction among road users. The modeling framework is demonstrated by a specific driving scenario: the overtaking of a cyclist when an oncoming vehicle may be present. In this scenario, modeling driver interaction using Unified modeling language within our framework can lead to improved crash mitigation and avoidance through tailored system activation of automated emergency braking

What kind of dynamic decision process do humans use to make decisions? In this article, two different types of processes are reviewed and compared: Markov and quantum. Markov processes are based on the idea that at any given point in time a decision maker has a definite and specific level of support for available choice alternatives, and the dynamic decision process is represented by a single trajectory that traces out a path across time. When a response is requested, a person's decision or judgment is generated from the current location along the trajectory. By contrast, quantum processes are founded on the idea that a person's state can be represented by a superposition over different degrees of support for available choice options, and that the dynamics of this state form a wave moving across levels of support over time. When a response is requested, a decision or judgment is constructed out of the superposition by "actualizing" a specific degree or range of degrees of support to create a definite state. The purpose of this article is to introduce these two contrasting theories, review empirical studies comparing the two theories, and identify conditions that determine when each theory is more accurate and useful than the other. This article is categorized under: Economics > Individual Decision-Making Psychology > Reasoning and Decision Making Psychology > Theory and Methods.

Partition dependence, the tendency to distribute choices differently based on the way options are grouped, has important implications for decision making. This phenomenon, observed in adults across a variety of contexts such as allocating resources or making selections from a menu of items, can bias decision makers toward some choices and away from others. Only one study to date (Reichelson, Zax, Patalano, & Barth, Quarterly Journal of Experimental Psychology, 72, 1029–1036, 2019) has investigated the developmental trajectory of this phenomenon. In the current study we investigate children’s and adults’ susceptibility to partitioning effects in a child-friendly resource allocation task. In Experiment 1 (N = 80), adults distributed 12 food tokens to animals at the zoo. Based on previous findings that older children show weaker partition dependence in this task, we predicted that adults might exhibit reduced partition dependent behavior: they showed none. In Experiment 2 (N = 272), we used a less transparent task with only five food tokens, predicting that both adults and children (ages 3–10 years) would show partition dependence. Children, but not adults, made partition dependent resource allocations, with younger children exhibiting greater effects than older children. These experiments provide further evidence that children’s decisions, like adults’ (in other tasks), are influenced by the arbitrary partitioning of the available options. This work supports previous findings that younger children may be more susceptible to these effects, and maps developmental change in partition dependent behavior from early childhood to adulthood on this child-friendly partition dependence task.

In this paper we investigate the effect of moral suasion on ingroup favouritism. We report a well-powered, pre-registered, two-stage 2x2 mixed-design experiment. In the first stage, groups are formed on the basis of how participants answer to a set of questions, concerning non-morally relevant issues in one treatment (assorting on non-moral preferences), and morally relevant issues in another treatment (assorting on moral preferences). In the second stage, participants choose how to split a given amount of money between participants of their own group and participants of the other group, first in the baseline setting and then in a setting where they are told to do what they believe to be morally right (moral suasion). Our main results are: (i) in the baseline, participants tend to favour their own group to a greater extent when groups are assorted according to moral preferences, compared to when they are assorted according to non-moral preferences; (ii) the net effect of moral suasion is to decrease ingroup favouritism, but there is also a non-negligible proportion of participants for whom moral suasion increases ingroup favouritism; (iii) the effect of moral suasion is substantially stable across group assorting and four pre-registered individual characteristics (gender, political orientation, religiosity, pro-life vs pro-choice ethical convictions)., Forthcoming in Judgment and Decision Making

Many decisions involve a choice between exploring unknown opportunities and exploiting well-known options. Work across a variety of domains, from animal foraging to human decision making, has suggested that animals solve such ``explore-exploit dilemmas'' with a mixture of two strategies: one driven by information seeking (directed exploration) and the other by behavioral variability (random exploration). Here we propose a unifying account in which these two strategies emerge from a kind of stochastic planning, known in the machine learning literature as Deep Exploration. In this model, the explore-exploit decision is made by stochastic simulation of plausible futures that are deep, in that they extend far into the future, and narrow, in that the number of possible futures they consider is small. By applying Deep Exploration to a simple explore-exploit task we show theoretically how directed and random exploration can emerge in these settings. Moreover, we show that Deep Exploration implies a tradeoff between directed and random exploration that is mediated by the number of simulations, or samples --- with more samples leading to increased directed exploration and decreased random exploration at the expense of greater time taken to respond. By measuring human behavior on the same simple task, we show that this reaction-time-mediated tradeoff exists in human behavior both between and within participants. We therefore suggest that Deep Exploration is a unifying account of explore-exploit behavior in humans.

Recent results have challenged the widespread assumption of dual process models of belief bias that sound reasoning relies on slow, careful reflection, whereas biased reasoning is based on fast intuition. Instead, parallel process models of reasoning suggest that rule- and belief-based problem features are processed in parallel and that reasoning problems that elicit a conflict between rule- and belief-based problem features may also elicit more than one Type 1 response. This theoretical developmental has important implications for individual-differences research on reasoning, because rule-based responses by certain individuals may reflect that these individuals were either more likely to give a rule-based default response or that they successfully inhibited and overrode a belief-based default response. In two studies, we used the diffusion model to describe decision making during syllogistic reasoning and related model parameters to individual differences in cognitive abilities and thinking styles. We found that individuals with a greater need for cognition showed a smaller decrease in drift rates when confronted with a conflict between rule- and belief-based problem features under conflict instruction, which suggests that a greater disposition to engage in reflective thinking facilitated the inhibition and successful override of Type 1 responses. More intelligent individuals, however, showed a greater decrease in drift rates when confronted with a conflict between rule- and belief-based problem features under belief instruction, which suggests that their quickly generated logical response interfered with their ability to evaluate lower-level intrinsic problem features. Taken together, this double dissociation suggests that cognitive abilities and thinking styles affect the processing of conflict information through different mechanisms and at different stages of information-processing: Greater cognitive abilities facilitate the efficient creation of decoupled problem representations, whereas a greater disposition to engage in critical thinking facilitates the successful detection and override of Type 1 responses.

Every year, during the month of Ramadan, people of Muslim faith fast by not eating or drinking between sunrise and sunset. This is likely to have physiological and psychological consequences for the individuals who fast, as well as societal and economic impacts on the wider population. Here, we investigate whether this type of fasting influences fasters’ cognition through a scarcity mindset. In Study 1, we find that during Ramadan but not after, preceding questions about food undermine fasting subjects’ accuracy and reaction times on a subsequent cognitive control task. Study 2 shows that food-related probes impair cognitive control in the fasters who had a meal within the past eight hours. Beyond eight hours, control and food-reminded subjects both perform poorly. Implications for research on cognition under scarcity are discussed.