In three studies, we tested whether icon arrays-which are a popular method of presenting risk information-can reduce predecisional information distortion that arises when early emerging preferences bias the evaluation of subsequently shown information. In Study 1, using traditional measures of information distortion, we found that risk-of-death information about two potential treatment options that was presented via icon arrays was distorted in favor of participants' leading alternative. The magnitude of distortion was similar to the level of distortion for other treatment information in the treatment scenario. Study 2 directly tested whether the presence versus absence of icon arrays when presenting risk information had any impact on levels of information distortion, this time using a dependent measure that targeted people's intuitive perceptions of risk. We found that the extent to which a 6% risk of death seemed riskier than a 3% risk of death was greater when the former risk was from a treatment option that was relatively undesired. This distortion was not significantly reduced by the presence of icon arrays. We replicated this pattern of results in a third study. These findings highlight the need for developing new tools and methods for presenting risk/likelihood information that can protect against the influence of predecisional information distortion. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Across three studies, we examined how outcome preferences shape predictions when prediction-relevant information must be actively acquired through search versus passively received. Participants in our studies predicted the color of randomly selected squares from grids that either were fully visible or required self-directed search to uncover. Consistent with prior work on confirmation bias and selective exposure, Study 1 found that outcome preferences biased search behavior: participants preferentially sampled evidence associated with preferred outcomes and adjusted how much information they gathered based on early evidence. Surprisingly, however, these search biases did not translate into stronger wishful thinking compared with a passive search context, in which all information was immediately available. At first glance, this appears inconsistent with theories of motivated reasoning (e.g., Kunda, 1990), which suggest that flexibility in search should amplify the impact of directional motives. Closer inspection, however, revealed a countervailing process: the magnitude of desirability bias in predictions decreased as participants searched more extensively. In other words, while outcome preferences shaped both the direction and extent of search, prolonged search also attenuated wishful thinking, producing comparable overall bias across active and passive search conditions. Follow-up Studies 2 and 3 suggest that mechanisms related to effort justification and selective stopping of search could account for this pattern of results. Together, these findings highlight a more nuanced view of motivated cognition, in which outcome preferences, search strategies, and effort jointly determine the expression of motivated bias in predictions.

Responses to Likert-type behavioral frequency (LBF) questions often do not consistently map onto objective numerical estimates. Prior research suggests that social and other comparisons may underlie this divergence, but the relative influence of different comparison standards—and the cognitive processes supporting them—remains unclear. Across two studies, we examined how comparisons to peers, averages, experts, past selves, and conceptually irrelevant standards shape LBF responses for common health behaviors (e.g., hand washing, flossing). Participants provided LBF judgments, absolute frequency estimates, and comparative judgments for each behavior. Study 1 showed that direct comparisons predicted LBF judgments above and beyond participants’ own absolute frequency estimates, with comparisons to experts and average others being especially influential. Even when controlling for shared methodological variance, all comparison types explained unique variance in LBF responses. Study 2 replicated this pattern of results. Moreover, additional analyses in Study 2 suggest that participants were not making precise, pairwise comparisons between numeric estimates, but were instead relying on more abstract, gist-like impressions of how their behavior compared to others’. Together, these findings underscore the importance of considering the comparative and interpretive nature of self-report measures, particularly in contexts where behavioral frequency carries social, normative, or evaluative meaning.

BackgroundIcon arrays, which visually depict frequencies, are commonly recommended for communicating risk information such as survival rates. However, they have been found to be ineffective at buffering against motivated reasoning that can lead to undue optimism. To determine whether the impersonal frequency format of icon arrays (reporting a number affected out of a reference class) makes them vulnerable to motivated reasoning, a novel intervention is tested as a means for reducing undue optimism.MethodsFemale US participants from Amazon's MTurk (N = 399) imagined a scenario in which their infant would be born extremely preterm. They were presented with icon array information about the survival chances (15-in-100 or 45-in-100) of prematurely born infants with intensive care. For the key intervention, some participants were asked a reflection question immediately after seeing the icon array, which prompted them to indicate what the information meant for their own infant's percent-chance of survival (i.e., they converted a frequency about a reference class to a probability value about the personal outcome of interest). For other participants, the reflection question merely asked about frequency. The main dependent measure came next and assessed gut-level optimism.ResultsPeople's gut-level beliefs about their infant's chances of survival were optimistically biased; the intervention did not reduce this. These gut-level beliefs, rather than the objective survival rate information conveyed through icon arrays, were predictive of subsequent treatment choices.ConclusionsThe results suggest that the inability of icon arrays to buffer against motivated reasoning is not due to their frequency format. Moreover, the findings highlight the usefulness of measuring gut-level interpretations of likelihood, which can reveal significant insights into the psychological mechanisms driving patient-treatment choices.HighlightsIcon arrays, which visually depict frequencies, are commonly recommended as best-practice for communicating risk information in health contexts.However, recent work has found that they are ineffective at reducing the extent to which people engage in motivated reasoning when processing likelihood information.We find that the frequency format of icon arrays-depicting a rate for outcomes in a group of people rather than a case-specific probability-is not a primary reason why they are ineffective at reducing optimism biasWe also find that measures of gut-level beliefs of likelihood are particularly well suited for detecting optimism bias, yet also predict subsequent treatment decisions.

Wishful thinking or desirability bias refers to instances where the desire for an outcome inflates the expectation that it will occur. Although studies have demonstrated influences of outcome desirability on people's predictions, the cognitive mechanisms behind such an effect have remained unclear. Both biased criteria for evidence judgment and biased evidence search/accumulation have been suggested as possible mechanisms. In the present work, we used drift-diffusion modeling to examine on which levels of processing desirability has its impact. Participants (N = 147) made predictions about the color of a randomly selected square from 2-color grids. Crucially, certain color outcomes were made more desirable than others, and the strength of evidence was manipulated by varying the proportion of desired-color squares in the grid. We found that both manipulations-and their interaction-significantly affected predictions. More importantly, drift-diffusion model analyses showed that outcome desirability resulted in a judgment-level bias, where participants required less evidence to predict a desired outcome. Notably, we also found that desirability impacted the evidence accumulation process itself. Participants more readily construed evidence as supporting the desired outcome, indicating that desirability had a top-down influence on how prediction-relevant evidence was accumulated. The present results have implications for existing accounts of how desire impacts expectations and highlight the utility of drift diffusion modeling as a tool for assessing the mechanisms underlying motivated biases.

During a global crisis, does the desire for good news also mean an endorsement of an optimistic bias? Five pre-registered studies, conducted at the start of the COVID pandemic, examined people’s lay prescriptions for thinking about uncertainty—specifically whether they thought forecasters should be optimistic, realistic, or pessimistic in how they estimated key likelihoods. Participants gave prescriptions for forecasters with different roles (e.g., self, family member, public official) and for several key outcomes (e.g., contracting COVID, vaccine development). Overall, prescribed optimism was not the norm. In fact, for negative outcomes that were of high concern, participants generally wanted others to have a pessimistic bias in how they estimated likelihoods. For positive outcomes, people favored more accurate estimation. These patterns held regardless of the assumed forecaster’s role. A common justification for advocating for a pessimistic bias in forecasts was to increase others' engagement in protective or preventative behaviors.

Background To assess the impact of risk perceptions on prevention efforts or behavior change, best practices involve conditional risk measures, which ask people to estimate their risk contingent on a course of action (e.g., “if not vaccinated”). Purpose To determine whether the use of conditional wording—and its drawing of attention to one specific contingency—has an important downside that could lead researchers to overestimate the true relationship between perceptions of risk and intended prevention behavior. Methods In an online experiment, US participants from Amazon’s MTurk ( N = 750) were presented with information about an unfamiliar fungal disease and then randomly assigned among 3 conditions. In all conditions, participants were asked to estimate their risk for the disease (i.e., subjective likelihood) and to decide whether they would get vaccinated. In 2 conditional-wording conditions (1 of which involved a delayed decision), participants were asked about their risk if they did not get vaccinated. For an unconditional/benchmark condition, this conditional was not explicitly stated but was still formally applicable because participants had not yet been informed that a vaccine was even available for this disease. Results When people gave risk estimates to a conditionally worded risk question after making a decision, the observed relationship between perceived risk and prevention decisions was inflated (relative to in the unconditional/benchmark condition). Conclusions The use of conditionals in risk questions can lead to overestimates of the impact of perceived risk on prevention decisions but not necessarily to a degree that should call for their omission. Highlights Conditional wording, which is commonly recommended for eliciting risk perceptions, has a potential downside. It can produce overestimates of the true relationship between perceived risk and prevention behavior, as established in the current work. Though concerning, the biasing effect of conditional wording was small—relative to the measurement benefits that conditioning usually provides—and should not deter researchers from conditioning risk perceptions. More research is needed to determine when the biasing impact of conditional wording is strongest.

Past research on advice-taking has suggested that people are often insensitive to the level of advice independence when combining forecasts from advisors. However, this has primarily been tested for cases in which people receive numeric forecasts. Recent work by Mislavsky and Gaertig (2022) shows that people sometimes employ different strategies when combining verbal versus numeric forecasts about the likelihood of future events. Specifically, likelihood judgments based on two verbal forecasts (e.g., "rather likely") are more often extreme (relative to the forecasts) than are likelihood judgments based on two numeric forecasts (e.g., "70% probability"). The goal of the present research was to investigate whether advice-takers' use of combination strategies can be sensitive to advice independence when differences in independence are highly salient and whether sensitivity to advice independence depends on the format in which advice is given. In two studies, we found that advice-takers became more extreme with their own likelihood estimate when combining forecasts from advisors who use separate evidence, as opposed to the same evidence. We also found that two verbal forecasts generally resulted in more extreme combined likelihood estimates than two numeric forecasts. However, the results did not suggest that sensitivity to advice independence depends on the format of advice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Objectives To examine whether presenting a 30% or a 60% chance of survival in different survival information formats would influence hypothetical periviable birth treatment choice and whether treatment choice would be associated with participants' recall or their intuitive beliefs about the chances of survival. Study design An internet sample of women (n = 1052) were randomized to view a vignette with either a 30% or 60% chance of survival with intensive care during the periviable period. Participants were randomized to survival information presented as text-only, in a static pictograph, or in an iterative pictograph. Participants chose intensive care or palliative care and reported their recall of the chance of survival and their intuitive beliefs about their infant's chance of survival. Results There was no difference in treatment choice by presentation with a 30% vs 60% chance of survival (P =.48), by survival information format (P =.80), or their interaction (P =.18). However, participants' intuitive beliefs about chance of survival significantly predicted treatment choice (P <.001) and had the most explanatory power of any participant characteristic. Intuitive beliefs were optimistic and did not differ by presentation of a 30% or 60% chance of survival (P =.65), even among those with accurate recall of the chance of survival (P =.09). Conclusions Physicians should recognize that parents may use more than outcome data to make treatment choices and in forming their own, often- optimistic, intuitive beliefs about their infant's chance of survival.

Assessing perceived vulnerability to a health threat is essential to understanding how people conceptualize their risk, and to predicting how likely they are to engage in protective behaviors. However, there is limited consensus about which of many measures of perceived vulnerability predict behavior best. We tested whether the ability of different measures to predict protective intentions varies as a function of the type of information people learn about their risk. Online participants ( N = 909) read information about a novel respiratory disease before answering measures of perceived vulnerability and vaccination intentions. Type-of-risk information was varied across three between-participant groups. Participants learned either: (1) only information about their comparative standing on the primary risk factors ( comparative-only ), (2) their comparative standing as well as the base-rate of the disease in the population (+ base-rate ), or (3) their comparative standing as well as more specific estimates of their absolute risk (+ absolute-chart ). Experiential and affective measures of perceived vulnerability predicted protective intentions well regardless of how participants learned about their risk, while the predictive ability of deliberative numeric and comparative measures varied based on the type of risk information provided. These results broaden the generalizability of key prior findings (i.e., some prior findings about which measures predict best may apply no matter how people learn about their risk), but the results also reveal boundary conditions and critical points of distinction for determining how to best assess perceived vulnerability.

The desirability bias refers to when people's expectations about an uncertain event are biased by outcome preferences. Prior work has provided limited evidence that the magnitude of this motivated bias depends on (is moderated by) how expectations are solicited-as discrete outcome predictions or as likelihood judgments expressed on more continuous scales. The present studies extended the generalizability and understanding of the moderating process. The authors proposed that solicitations of predictions and likelihood judgments have different connotations that ultimately affect how much bias is expressed; this varies from a prior account that attributed the moderation effect to response scale differences (dichotomous vs. continuous). Study 1 confirmed the connotation difference, with predictions being viewed as more affording of hunches. Studies 2-4 directly tested the moderation effect, and unlike prior work focusing on expectations for purely stochastic events, the present studies involved more naturalistic events for which likelihood information was not supplied or directly knowable. Before viewing scenes from a basketball game (Study 2) or an endurance race (Studies 3 and 4), participants were led to prefer one contestant over another. After viewing most of the closely fought contest, they made either a prediction or likelihood judgment about the outcome. Participants' tendency to forecast their preferred contestant to win was significantly stronger among those making predictions rather than likelihood judgments. In support of the proposed account, this effect persisted even when both types of solicitations offered only dichotomous response options. Broader implications for measuring and understanding people's expectations or forecasts are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The phenomenon of ambiguity aversion suggests that people prefer options that offer precisely rather than imprecisely known chances of success. However, past work on people's responses to ambiguity in health treatment contexts found ambiguity seeking rather than aversion. The present work addressed whether such findings reflected a broad tendency for ambiguity seeking in health treatment contexts or whether specific attributions for ambiguity play a substantial role. In three studies, people choose between two treatment options that involved similar underlying probabilities, except that the probabilities for one option involved ambiguity. The attributions offered for the ambiguity played an important role in the results. For example, when the range of probabilities associated with an ambiguous treatment was attributed to the fact that different studies yield different results, participants tended to show ambiguity aversion or indifference. However, when the range was attributed to something that participants could control (e.g., regular application of a cream) or something about which they were overoptimistic (e.g., their immune system function), participants tended to show ambiguity seeking. Health professionals should be mindful of how people will interpret and use information about ambiguity when choosing among treatments.

The desirability bias refers to when people’s expectations about an uncertain event are biased by outcome preferences. Prior work has provided limited evidence that the magnitude of this motivated bias depends on (is moderated by) how expectations are solicited—as discrete outcome predictions or as likelihood judgments expressed on more continuous scales. The present studies extended the generalizability and understanding of the moderating process. The authors proposed that solicitations of predictions and likelihood judgments have different connotations that ultimately affect how much bias is expressed; this varies from a prior account that attributed the moderation effect to response scale differences (dichotomous vs. continuous). Study 1 confirmed the connotation difference, with predictions being viewed as more affording of hunches. Studies 2-4 directly tested the moderation effect, and unlike prior work focusing on expectations for purely stochastic events, the present studies involved more naturalistic events for which likelihood information was not supplied or directly knowable. Before viewing scenes from a basketball game (Study 2) or an endurance race (Studies 3-4), participants were led to prefer one contestant over another. After viewing most of the closely-fought contest, they made either a prediction or likelihood judgment about the outcome. Participants’ tendency to forecast their preferred contestant to win was significantly stronger among those making predictions rather than likelihood judgments. In support of the proposed account, this effect persisted even when both types of solicitations offered only dichotomous response options. Broader implications for measuring and understanding people’s expectations/forecasts are discussed.

The desirability bias (or wishful thinking effect) refers to when a person's desire regarding an event's occurrence has an unwarranted, optimistic influence on expectations about that event. Past experimental tests of this effect have been dominated by paradigms in which uncertainty about the target event is purely stochastic-i.e., involving only aleatory uncertainty. In six studies, we detected desirability biases using two new paradigms in which people made predictions about events for which their uncertainty was both aleatory and epistemic. We tested and meta-analyzed the impact of two potential moderators: the strength of evidence and the level of stochasticity. In support of the first moderator hypothesis, desirability biases were larger when people were making predictions about events for which the evidence for the possible outcomes was of similar strength (vs. not of similar strength). Regarding the second moderator hypothesis, the overall results did not support the notion that the desirability bias would be larger when the target event was higher vs. lower in stochasticity, although there was some significant evidence for moderation in one of the two paradigms. The findings broaden the generalizability of the desirability bias in predictions, yet they also reveal boundaries to an account of how stochasticity might provide affordances for optimistically biased predictions.

Past work has suggested that people prescribe optimism—believing it is better to be optimistic, instead of accurate or pessimistic, about uncertain future events. Here, we identified and addressed an important ambiguity about whether those findings reflect an endorsement of biased beliefs—that is, whether people prescribe likelihood estimates that reflect overoptimism. In three studies, participants (N = 663 U.S. university students) read scenarios about protagonists facing uncertain events with a desired outcome. Results replicated prescriptions of optimism when we used the same solicitations as in past work. However, we found quite different prescriptions when using alternative solicitations that asked about potential bias in likelihood estimations and that did not involve vague terms such as “optimistic.” Participants generally prescribed being optimistic, feeling optimistic, and even thinking optimistically about the events, but they did not prescribe overestimating the likelihood of those events.

Past work has suggested that people prescribe optimism—believing it is better to be optimistic, instead of accurate or pessimistic, about uncertain future events. Here, we identified and addressed an important ambiguity about whether those findings reflect an endorsement of biased beliefs—i.e., whether people prescribe likelihood estimates that reflect overoptimism. In three studies, participants (total N = 663 U.S. university students) read scenarios about protagonists facing uncertain events with a desired outcome. Results replicated prescriptions of optimism when using the same solicitations as in past work. However, we found quite different prescriptions when using alternative solicitations that asked about potential bias in likelihood estimations and that did not involve vague terms like “optimistic.” Participants generally prescribed being optimistic, feeling optimistic, and even thinking optimistically about the events, but they did not prescribe overestimating the likelihood of those events.

When making decisions involving risk, people may learn about the risk from descriptions or from experience. The description-experience gap refers to the difference in decision patterns driven by this discrepancy in learning format. Across two experiments, we investigated whether learning from description versus experience differentially affects the direction and the magnitude of a context effect in risky decision making. In Study 1 and 2, a computerized game called the Decisions about Risk Task (DART) was used to measure people’s risk-taking tendencies toward hazard stimuli that exploded probabilistically. The rate at which a context hazard caused harm was manipulated, while the rate at which a focal hazard caused harm was held constant. The format by which this information was learned was also manipulated; it was learned primarily by experience or by description. The results revealed that participants’ behavior toward the focal hazard varied depending on what they had learned about the context hazard. Specifically, there were contrast effects in which participants were more likely to choose a risky behavior toward the focal hazard when the harm rate posed by the context hazard was high rather than low. Critically, these contrast effects were of similar strength irrespective of whether the risk information was learned from experience or description. Participants’ verbal assessments of risk likelihood also showed contrast effects, irrespective of learning format. Although risk information about a context hazard in DART does nothing to affect the objective expected value of risky versus safe behaviors toward focal hazards, it did affect participants’ perceptions and behaviors—regardless of whether the information was learned from description or experience. Our findings suggest that context has a broad-based role in how people assess and make decisions about hazards.

People often use tools for tasks, and sometimes there is uncertainty about whether a given task can be completed with a given tool. This project explored whether, when, and how people’s optimism about successfully completing a task with a given tool is affected by the contextual salience of a better or worse tool. In six studies, participants were faced with novel tasks. For each task, they were assigned a tool but also exposed to a comparison tool that was better or worse in utility (or sometimes similar in utility). In some studies, the tool comparisons were essentially social comparisons, because the tool was assigned to another person. In other studies, the tool comparisons were merely counterfactual rather than social. The studies revealed contrast effects on optimism, and the effect worked in both directions. That is, worse comparison tools boosted optimism and better tools depressed optimism. The contrast effects were observed regardless of the general type of comparison (e.g., social, counterfactual). The comparisons also influenced discrete decisions about which task to attempt (for a prize), which is an important finding for ruling out superficial scaling explanations for the contrast effects. It appears that people fail to exclude irrelevant tool-comparison information from consideration when assessing their likelihood of success on a task, resulting in biased optimism and decisions.

Risk perception is an important construct in many health behavior theories. Smoking risk perceptions are thoughts and feelings about the harms associated with cigarette smoking. Wide variation in the terminology, definition, and assessment of this construct makes it difficult to draw conclusions about the associations of risk perceptions with smoking behaviors. To understand optimal methods of assessing adults’ cigarette smoking risk perceptions (among both smokers and nonsmokers), we reviewed best practices from the tobacco control literature, and where gaps were identified, we looked more broadly to the research on risk perceptions in other health domains. Based on this review, we suggest assessments of risk perceptions (1) about multiple smoking-related health harms, (2) about harms over a specific timeframe, and (3) for the person affected by the harm. For the measurement of perceived likelihood in particular (ie, the perceived chance of harm from smoking based largely on deliberative thought), we suggest including (4) unconditional and conditional items (stipulating smoking behavior) and (5) absolute and comparative items and including (6) comparisons to specific populations through (7) direct and indirect assessments. We also suggest including (8) experiential (ostensibly automatic, somatic perceptions of vulnerability to a harm) and affective (emotional reactions to a potential harm) risk perception items. We also offer suggestions for (9) response options and (10) the assessment of risk perception at multiple time points. Researchers can use this resource to inform the selection, use, and future development of smoking risk perception measures. Implications Incorporating the measurement suggestions for cigarette smoking risk perceptions that are presented will help researchers select items most appropriate for their research questions and will contribute to greater consistency in the assessment of smoking risk perceptions among adults.