In order to minimize the risk of infection during the Covid-19 pandemic, people are recommended to keep interpersonal distance (e.g., 1 m, 2 m, 6 feet), wash their hands frequently, limit social contacts and sometimes to wear a face mask. We investigated how people judge the protective effect of interpersonal distance against the Corona virus. The REM model, based on earlier empirical studies, describes how a person’s virus exposure decreases with the square of the distance to another person emitting a virus in a face to face situation. In a comparison with model predictions, most participants underestimated the protective effect of moving further away from another person. Correspondingly, most participants were not aware of how much their exposure would increase if they moved closer to the other person. Spectral analysis of judgments showed that a linear ratio model with the independent variable = (initial distance)/(distance to which a person moves) was the most frequently used judgment rule. It leads to insensitivity to change in exposure compared with the REM model. The present study indicated a need for information about the effects of keeping interpersonal distance and about the importance of virus carrying aerosols in environments with insufficient air ventilation. Longer conversations emitting aerosols in a closed environment may lead to ambient concentrations of aerosols in the air that no distance can compensate for. The results of the study are important for risk communications in countries where people do not wear a mask and when authorities consider removal of a recommendation or a requirement to wear a face mask.

In the context of the COVID-19 pandemic, French public opinion has been divided about Pr. Didier Raoult and his hydroxychloroquine-based treatment against COVID-19. In this paper, our aim is to contribute to the understanding of this polarization of public opinion by investigating the relationship between (analytic vs. intuitive) cognitive style and trust in Didier Raoult and his treatment. Through three studies (total N after exclusion = 950), we found that a more intuitive cognitive style predicted higher trust in Didier Raoult and his treatment. Moreover, we found that Trust in Raoult was positively associated with belief that truth is political, belief in conspiracy theories, belief in pseudo-medicines and pseudo-medical and conspiratorial beliefs regarding the COVID-19 pandemic. We also found a negative association with knowledge of scientific methods and regard for scientific method over personal experience. However, higher trust in Didier Raoult was not associated with self-reported compliance with official regulations concerning the COVID-19 pandemic.

While they usually should, people do not revise their beliefs more to expert (economist) opinion than to lay opinion. The present research sought to better understand the factors that make it more likely for an individual to change their mind when faced with the opinions of expert economists versus the general public. Across five studies we examined the role that overestimation of knowledge plays in this behavior. We replicated the finding that people fail to privilege the opinion of experts over the public across two different (Study 1) and five different (Study 5) economic issues. We further find that undermining an illusion of both topic-relevant (Studies 2–4) and -irrelevant knowledge (Studies 3 and 4) leads to greater normative belief revision in response to expert rather than lay opinion. We suggest one reason that people fail to revise their beliefs more in response to experts is because people think they know more than they really do.

Manipulations for activating reflective thinking, although regularly used in the literature, have not previously been systematically compared. There are growing concerns about the effectiveness of these methods as well as increasing demand for them. Here, we study five promising reflection manipulations using an objective performance measure — the Cognitive Reflection Test 2 (CRT-2). In our large-scale preregistered online experiment (N = 1,748), we compared a passive and an active control condition with time delay, memory recall, decision justification, debiasing training, and combination of debiasing training and decision justification. We found no evidence that online versions of the two regularly used reflection conditions — time delay and memory recall — improve cognitive performance. Instead, our study isolated two less familiar methods that can effectively and rapidly activate reflective thinking: (1) a brief debiasing training, designed to avoid common cognitive biases and increase reflection, and (2) simply asking participants to justify their decisions.

Although the Analysis of Competing Hypotheses method (ACH) is a structured analytic technique promoted in several intelligence communities for improving the quality of probabilistic hypothesis testing, it has received little empirical testing. Whereas previous evaluations have used numerical evidence assumed to be perfectly accurate, in the present experiment we tested the effectiveness of ACH using a judgment task that presented participants with uncertain evidence varying in source reliability and information credibility. Participants (N = 227) assigned probabilities to two alternative hypotheses across six cases that systematically varied case features. Across multiple tests of coherence, the ACH group showed no advantage over a no-technique control group. Both groups showed evidence of subadditivity, unreliability, and overly conservative non-Bayesian judgments. The ACH group also showed pseudo-diagnostic weighting of evidence. The findings do not support the claim that ACH is effective at improving probabilistic judgment.

Trading is a cornerstone of economic exchange and can take many different forms. In simple trades, one item is often exchanged for another; but in more complex trades, agents can trade different numbers of items, reflecting the differing value of the items being traded. Though young children regularly engage in simple trades, we examine whether they understand a key element involved in more complex trades—the idea that people may subjectively value the same item differently and accept trades that numerically disadvantage themselves in the service of acquiring more of a preferred item. To do so, we ran three studies with 5- to 10-year-old children (N = 314) in which they were asked to predict whether a third party would accept or reject different types of trades. Results revealed that children across this age range predict that a third party will accept a numerically disadvantageous trade when they prefer one resource over another, but not when they have an equal preference for both resources. Importantly, their predictions were not merely a reflection of what they thought was fair, but rather what was in the best interest of the third party—they thought a third party would be more likely to accept an “unfair” trade that benefitted himself rather than someone else. We discuss our findings in terms of what they reveal about children’s early economic intuitions.

The unit in which numerical information is presented can have a strong influence on how decision makers evaluate and choose between available choice options. The present work examines the influence of frequently used default units on judgments and decisions of energy efficiency. Across three experiments (Ntotal = 497), our results provide evidence that value sensitivity increases by about 25% in joint evaluation mode when a product attribute is presented in the default unit versus a non-default unit. As a result, presenting an attribute in the default unit led to more favorable evaluations of superior products and less favorable evaluations of inferior products. This result was robust to changes in the numerical magnitude of the non-default unit. Moreover, when joint evaluation was performed across different units, products described using the default unit were evaluated more favorably than products described using a non-default unit. More favorable evaluations based on the default unit translated into a higher willingness to pay for efficiency advantages. We discuss the theoretical and practical implications of default units to guide informed consumer judgments and effective energy efficiency labeling.

We replicate and extend unit asking – a method to increase donations by first asking donors for their willingness to donate for one unit and then asking for donations for multiple units (Hsee, Zhang & Xu, 2013) We conducted a large scale replication and extension using a 2 (unit asking, control) × 3 (domains; children (original), animals, environment) between-subjects design. Across three domains, we find that unit asking increased donations, suggesting that this method can be used to increase giving to different charitable causes.

We propose that externally induced time limits on a task overly affect predictions of other people’s completion times for that task, due to an over-generalized association between the time available and inferred task scope. We find higher estimates of the time needed to complete a given task by another person when the time limit is longer. While such predictions could be normative when time limits are informative, the effect persists even when the decision-maker knows that the limit is arbitrary and is unknown to the other person, and therefore, cannot affect behavior. Perception of task scope mediates the relationship between time limits and completion time estimates, and weakening the association between time limits and task scope attenuates the effect. The over-learned cognitive bias persists even among experienced decision-makers making estimates in a familiar setting. Our findings have implications for people who make decisions that use judgments of others’ task completion time as an input.

We investigated whether people’s risk taking tendency established in one domain (gains or losses) carries over to the other domain. Participants played a game in which they made repeated decisions between a fixed payoff and a risky option, where the outcome of the risky option depended on whether they had responded correctly on a difficult perceptual-memory task. In some trials, participants played to gain points; on others, they played to avoid losing points. In two studies, we observed the following pattern of results. 1) Participants risked less on gain trials than on loss trials. 2) This difference in risk taking persisted (carried over) when the domain changed from gains to losses and vice versa (with the effect of experiencing losses first being stronger than the effect of experiencing gains first). 3) There was no analogous carryover effect on responses to a delay discounting measure, but there was a carryover effect on responses on a risk attitude measure. We compare these results with those from other recent studies and discuss various ways of explaining them.

Previous research has shown that short-term changes in blood glucose influence our preferences and may affect decisions about risk as well. However, consensus is lacking about whether and how blood glucose influences decision making under risk, and we conduct two experiments and a meta-analysis to examine this question in detail. In Study 1, using a pecuniary valuation method, we find no effect of blood glucose on willingness to pay for risky products that may act as allergens. In Study 2, using risky gambles, we find that low levels of blood glucose increase risk taking for food and to a lesser degree for non-food rewards. Combining our own and previous findings in a meta-analysis, we show that low levels of blood glucose on average increase risk taking about food. Low blood glucose does not increase risk taking about non-food rewards although this is subject to heterogeneity. Overall, our studies suggest that low blood glucose increases our willingness to gamble on how much food we can get, but not our willingness to eat food that can harm us. Our findings are best explained by the energy budget rule.

The rapid spread of COVID-19 has emphasized the need for effective health communications to coordinate individual behavior and mitigate disease transmission. Facing a pandemic, individuals may be driven to adopt public health recommendations based on both self-interested desires to protect oneself and prosocial desires to protect others. Although messages can be framed around either, existing research from the social sciences has offered mixed evidence regarding their relative efficacy. Informing this dialogue, in the current study we report on the findings of a field experiment (N = 25,580) conducted March 21–22 on Facebook during the critical initial weeks of the COVID-19 outbreak in the United States. We observed that ad messages using a distant prosocial frame (“protect your community”) were in fact significantly less effective than those using a self-focused frame (“protect yourself”) in eliciting clickthroughs to official CDC recommendations. However, ad messages with a close prosocial frame (“protect your loved ones”) were equally effective as the self-focused frame. These findings catalog the differential efficacy of ad messaging strategies during the early stages of the coronavirus pandemic.

Butler and Pogrebna (2018) devised triples of three-branch gambles theorized to violate transitivity of preference according to a most probable winner model. According to this model, a person chooses the option that has the higher probability to yield a better outcome than the other alternative. They tested 11 triples with 100 participants and found cases that appeared to violate weak stochastic transitivity and the triangle inequality. But tests of weak stochastic transitivity and the triangle inequality do not provide a proper method to compare transitive and intransitive models that allow mixtures of preference patterns and random errors. Those older methods can yield false conclusions regarding transitivity, for example, if different participants have different true preferences or if different choice problems have different rates of error. This paper reanalyzes their data using a true and error (TE) model, which does not require these unrealistic assumptions, and which provides estimates of the incidence of transitive and intransitive behavior in a mixture. Reanalysis indicated that 3 of the 11 triples showed convincing evidence of violations of transitivity in the opposite direction of the predictions of the most probable winner model. Further, these and other triples showed other significant violations of the most probable winner model. Despite some violations of the true and error model, the data of Butler and Pogrebna appear to contradict not only transitive utility models but they also refute the most probable winner model as a descriptive theory of choice behavior.

Birnbaum (2020) reanalyses the data from Butler and Pogrebna (2018) using his ‘true and error’ test of choice patterns. His results generally support the evidence we presented in that paper. Here we reiterate the reasons for our agnosticism as to the direction any cycles might take, even though the paradox that motivated our study takes a ‘probable winner’ direction. We conclude by returning to the potential significance of predictably intransitive preferences for decision theory generally.

The CNI model of moral decision-making is a formal model that quantifies (1) sensitivity to consequences, (2) sensitivity to moral norms, and (3) general preference for inaction versus action in responses to moral dilemmas. Based on a critique of the CNI model’s conceptual assumptions, properties of the moral dilemmas for research using the CNI model, and the robustness of findings obtained with the CNI model against changes in model specifications, Baron and Goodwin (2020) dismissed the CNI model as a valid approach to study moral dilemma judgments. Here, we respond to their critique, showing that Baron and Goodwin’s dismissal of the CNI model is based on: (1) misunderstandings of key aspects of the model; (2) a conceptually problematic conflation of behavioral effects and explanatory mental constructs; (3) arguments that are inconsistent with empirical evidence; and (4) reanalyses that supposedly show inconsistent findings resulting from changes in model specifications, although the reported reanalyses did not actually use the CNI model and proper analyses with the CNI model yield consistent findings across model specifications. Although Baron and Goodwin’s critique reveals a need for greater precision in the description of the three model parameters and for greater attention to properties of individual dilemmas, the available evidence indicates that the CNI model is a valid, robust, and empirically sound approach to gaining deeper insights into the determinants of moral dilemma judgments, overcoming major limitations of the traditional approach that pits moral norms against consequences for the greater good (e.g., trolley dilemma).