Valerie F. Reyna

Courts have dramatically increased their use of virtual jury trials, but empirical research has yet to examine differences between in-person and virtual jury deliberations. We tested competing hypotheses that in-person juries would be better (or worse) than virtual juries in terms of attention and engagement, deliberation, and diversity. Community members (N = 317; 61% women; 86.1% White; mean age = 48.68 years) watched a videotaped trial involving an automobile accident and then deliberated either in person or virtually in 54 mock juries (N_{in person} = 24; N_virtual = 30). In-person and virtual juries did not differ significantly across most outcomes. However, regarding attention and engagement, virtual juries reported expending greater cognitive effort (d = 0.59) than in-person juries. Regarding deliberation, in-person juries interrupted each other significantly more often than virtual juries (d = 1.93), and they discussed more topics than virtual juries (d = 0.59-1.02). Regarding diversity, virtual jurors were younger (d = 0.55), wealthier (d = 0.66), and more educated (φ = .14) than in-person jurors, although both samples were recruited in the same manner. Despite concerns that virtual formats substantially reduce jurors' attention/engagement and change the nature of their deliberations, virtual jurors thoroughly processed relevant evidence and reportedly expended more effort in doing so. Although virtual formats may require more technologically savvy jurors (expected to correlate with a juror's age, wealth, and education), this study provides little evidence that virtual jury participation fundamentally alters core aspects of jury deliberation. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Although viral outbreaks are increasing, vaccination rates are decreasing. Our aim was to explain this baffling behavior that seems to contradict rational self-interest, and, thus, be beyond the purview of rational choice theories. We integrated fuzzy-trace theory and major theoretical alternatives and applied them to influenza, testing theoretical predictions in two samples: young adults (who are major viral vectors), N = 722, and community members, N = 185. Controlling for prior knowledge and other psychosocial factors that influence vaccination, explained variance jumped significantly when key predictors from fuzzy-trace theory were added, reaching 62% and 80% for vaccination intentions and 37% and 59% for behavior for each sample, respectively. Single items assessing global gist perceptions of risks and benefits achieved remarkable levels of diagnosticity. Key predictors were intuitive in that they were gisty, imprecise, and non-analytical. In contrast, rational system 2 measures—numeracy and cognitive reflection—were not predictive. These results provide new insights into why individuals vaccinate or not and new avenues for interventions to improve shared clinical decision-making.

Background: Previous research suggests that physicians’ inclination to refer patients for suspected cancer is a relatively stable characteristic of their decision making. We aimed to identify its psychological determinants in the presence of a risk-prediction algorithm. Methods: We presented 200 UK general practitioners with online vignettes describing patients with possible colorectal cancer. Per the vignette, GPs indicated the likelihood of referral (from highly unlikely to highly likely) and level of cancer risk (negligible/low/medium/high), received an algorithmic risk estimate, and could then revise their responses. After completing the vignettes, GPs responded to questions about their values with regard to harms and benefits of cancer referral for different stakeholders, perceived severity of errors, acceptance of false alarms, and attitudes to uncertainty. We tested whether these values and attitudes predicted their earlier referral decisions. Results: The algorithm significantly reduced both referral likelihood ( b = −0.06 [−0.10, −0.007], P = 0.025) and risk level ( b = −0.14 [−0.17, −0.11], P < 0.001). The strongest predictor of referral was the value GPs attached to patient benefits ( b = 0.30 [0.23, 0.36], P < 0.001), followed by benefits ( b = 0.18 [0.11, 0.24], P < 0.001) and harms ( b = −0.14 [−0.21, −0.08], P < 0.001) to the health system/society. The perceived severity of missing a cancer vis-à-vis overreferring also predicted referral ( b = 0.004 [0.001, 0.007], P = 0.009). The algorithm did not significantly reduce the impact of these variables on referral decisions. Conclusions: The decision to refer patients who might have cancer can be influenced by how physicians perceive and value the potential benefits and harms of referral primarily for patients and the moral seriousness of missing a cancer vis-à-vis over-referring. These values contribute to an internal threshold for action and are important even when an algorithm informs risk judgments. Highlights: Physicians’ inclination to refer patients for suspected cancer is determined by their assessment of cancer risk but also their core values; specifically, their values in relation to the perceived benefits and harms of referrals and the seriousness of missing a cancer compared with overreferring. We observed a moral prioritization of referral decision making, in which considerations about benefits to the patient were foremost, considerations about benefits but also harms to the health system or the society were second, while considerations about oneself carried little or no weight. Having an algorithm informing assessments of risk influences referral decisions but does not remove or significantly reduce the influence of physicians’ core values.

Framing effects (risk preferences reverse for gains vs. losses) and the Allais paradox (risk preferences reverse when an option is certain vs. not) are major violations of rational choice theory. In contrast to typical samples, certified public accountants who are competent in working with probabilities and expected values should be an ideal test case for rational choice, especially high scorers on the cognitive reflection test (CRT). Although dual-process theories emphasize numeracy and cognitive reflection, fuzzy-trace theory emphasizes gist-based intuition to explain these effects among cognitively advanced decision-makers. Thus, we recruited a high-numeracy sample of certified public accountants (N = 259) and students (N = 648). We administered classic dread-disease framing, business framing, and Allais paradox problems and the CRT. Each participant received a gain and loss framing problem from different domains (one disease and one business), with presentation order counterbalanced across participants. Order of Allais problems was counterbalanced within participants. Within-participants (cross-domain) framing, between-participants (within-domain) framing, and the Allais paradox were observed for both samples. Accountants did not show domain-specific attenuation (differentially smaller framing) for business problems. Despite large expected-value differences between Allais problem options, accountants' choices resembled students' choices. Contrary to dual-process theories, CRT scores were positively related to framing for students (more framing with higher CRT) and inconsistently related for accountants, but high scorers had robust framing effects; high scorers also showed the Allais paradox. Results are consistent with fuzzy-trace theory's expectation that experts show framing effects because they rely primarily on gist-based intuition, not because they lack numeracy or cognitive reflection. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Three scholars take interdisciplinary perspectives on plea decision‐making, which resolves more than 95% of criminal cases. Wolfe (2025) draws out lessons from findings in medical decision‐making research and explains how findings and theory bridge domains. Wilson (2025) draws out lessons from behavioral economics for plea decision‐making and explains how perceptions of fairness could influence plea bargaining beyond economics, providing novel predictions. Faigman (2025) emphasizes the uncertainties surrounding plea bargaining in actual cases, and how considering plea bargaining as decision‐making “put[s] fairness top of mind.” I take up the challenges outlined by these scholars and extend fuzzy‐trace theory in new ways to account for qualitative and quantitative features of plea‐bargaining options encompassing meaningful bottom‐line gist, ambiguity of options, positive and negative valence of outcomes, and core social and moral values, such as fairness and justice.

About 95% of criminal convictions in the United States are obtained through plea decisions, a growing global practice. Courts justify these convictions based on defendant choice—defendants, as rational agents, can freely choose to plead guilty or go to trial. However, a fundamental axiom of rational choice—descriptive invariance—has never been effectively tested for plea decisions. To test this axiom, we manipulated gain–loss framing of plea options. The shadow‐of‐trial model, the leading theory of plea decision‐making, is predicated on expected utility theory which is in turn predicated on the invariance axiom; if the axiom is falsified, the entire structure collapses. Thus, framing effects are important as a test of fundamental assumptions undergirding practice and as an empirical phenomenon revealing effects of context. We tested framing effects in students and community members including those with criminal involvement for whom plea bargaining has personal relevance. Varying subtle changes in wording of outcomes, we produced pronounced differences in choices to accept a plea rather than proceed to trial. These framing effects were robust to age, sex, educational attainment, risk propensity (DOSPERT and sensation seeking), and loss aversion. Perceived fairness of the legal system increased acceptance and risk propensity decreased it (each about 32%). However, controlling for those effects, loss (compared to gain) framing increased the odds of going to trial by 664%. Criminal involvement did not account for additional variance. These results are consistent with prospect theory and fuzzy‐trace theory, but they challenge the legal theory of bargaining in “the shadow of trial.”

Risk-reduction behaviors are the first line of defense in viral epidemics. Choosing to not engage in risk-reduction behaviors produced millions of preventable deaths from COVID-19. Understanding why this happens and how to predict it is important for theory development and public policy. We took four approaches to this problem: experimentally varying theory-driven predictors (social rewards, transmission risk, and mandatory/voluntary regulations) in choice scenarios, further probing choices in specific scenarios predicted to elicit risk-taking, conducting hierarchical regressions with demographic and theory-driven predictors for both scenario types, and conducting corresponding regressions for self-reported protective behaviors. The sample consisted of 247 young adults to test highly publicized predictions about how the virus would spread and who would take risks. Results showed that risky choices for scenarios correlated with self-reported behavior and varied with transmission risk and whether regulations were mandatory. Experimentally varying social reward did not elicit greater risk taking as expected by dual-systems theory but risk taking in specific social scenarios was predicted by individual differences in sensation seeking as predicted by dual-systems theory. Sensation seeking predicted social distancing and impulsivity predicted mask wearing. Fuzzy-trace theory’s predictors of categorical thinking about risk and endorsement of simple gist principles of social responsibility (to not hurt other people) consistently predicted choices and behaviors, accounting for significant variance beyond dual-systems predictors. Both controlled experiments and real-world self-reported behaviors converged on similar conclusions, identifying a major gap in influential theories (the omission of gist-based thinking) and challenging pessimistic predictions about motivations and mandates in public health.

We introduce a multi-step reasoning framework using prompt-based LLMs to examine the relationship between social media language patterns and trends in national health outcomes. Grounded in fuzzy-trace theory, which emphasizes the importance of “gists” of causal coherence in effective health communication, we introduce Role-Based Incremental Coaching (RBIC), a prompt-based LLM framework, to identify gists at-scale. Using RBIC, we systematically extract gists from subreddit discussions opposing COVID-19 health measures (Study 1). We then track how these gists evolve across key events (Study 2) and assess their influence on online engagement (Study 3). Finally, we investigate how the volume of gists is associated with national health trends like vaccine uptake and hospitalizations (Study 4). Our work is the first to empirically link social media linguistic patterns to real-world public health trends, highlighting the potential of prompt-based LLMs in identifying critical online discussion patterns that can form the basis of public health communication strategies.

BackgroundUnderstanding the decision factors that drive harmful alcohol use among young adults is of practical and theoretical importance. We apply fuzzy-trace theory (FTT) to investigate a potential danger that may arise from the arguably correct notion that a single drink carries no meaningful risk. Decisions that are mentally represented as one drink at a time could contribute to excessive drinking.MethodsCollege students (N = 351) made a series of decisions to take or decline eight hypothetical drinks presented one at a time. Outcome measures included each decision, recent alcohol consumption (weekly drinks, peak blood alcohol content, and binges), and alcohol-related harms (scores on the Brief Young Adult Alcohol Consequences Questionnaire and Alcohol Use Disorders Identification Test). Linear regression models predicted each outcome from sex, perceived risk of a single drink, perceived risk of heavy drinking, perceived consequences of drinking, and general health-related risk sensitivity.ResultsConsistent with FTT, decisions to have a first drink and up to four additional drinks in short succession were each associated with lower perceived risk of one drink-a "just-one drink" effect-independent of perceived risks of heavy drinking, perceived consequences of drinking, and general risk sensitivity. Similarly, all measures of recent alcohol consumption and consequent harms were associated with perceived risk of one drink. Participants reporting "zero risk" of a single drink had worse outcomes on all measures than those reporting at least "low risk."ConclusionsResults are consistent with the theoretically informed premise that consumption decisions are typically made one drink at a time rather than by deciding the total number of drinks to be consumed in a sitting. When decisions about alcohol use proceed one drink at a time, a perception of zero risk in a single drink may contribute to heavy drinking.