The perception of dramatic risks: Biased media, but unbiased minds.

In their famous study on risk judgments, Lichtenstein, Slovic, Fischhoff, Layman, and Combs (1978) concluded that people tend to overestimate the frequencies of dramatic causes of death (e.g., homicide, tornado) and underestimate the frequencies of nondramatic ones (e.g., diabetes, heart disease). Further, their analyses of newspapers indicated that dramatic risks are overrepresented in the media-suggesting that people's distorted risk perceptions might be driven by distortions in media coverage. Although these patterns were not evaluated statistically in the original analyses, the conclusions have become a staple in the social sciences. How reliable are they? And are they replicable? In a systematic literature search, I identified existing replications of Lichtenstein et al.'s investigation and submitted both the original data and the data from the replications to a Bayesian statistical analysis. All datasets indicated very strong evidence for an overrepresentation of dramatic risks and an underrepresentation of nondramatic risks in media coverage. However, a reliable overestimation (underestimation) of dramatic (nondramatic) risks in people's frequency judgments emerged only in Lichtenstein et al.'s dataset; it did not replicate in the other datasets. In fact, aggregated across all datasets, there was evidence for the absence of a differential distortion of dramatic and nondramatic causes of death in people's risk frequency judgments. Additional analyses suggest that when judging risk frequency, people rely on samples from their personal social networks rather than from the media. The results reveal a limited empirical basis for the common notion that distortions in people's risk judgments echo distortions in media coverage. They also suggest that processes of risk frequency judgments include a metacognitive mechanism that is sensitive to the source of mentally available samples.

Over- and underweighting of extreme values in decisions from sequential samples.

People routinely make decisions based on samples of numerical values. A common conclusion from the literature in psychophysics and behavioral economics is that observers subjectively compress magnitudes, such that extreme values have less sway over people's decisions than prescribed by a normative model (underweighting). However, recent studies have reported evidence for anti-compression, that is, the relative overweighting of extreme values. Here, we investigate potential reasons for this discrepancy in findings and propose that it might reflect adaptive responses to different task requirements. We performed a large-scale study (n = 586) of sequential numerical integration, manipulating (a) the task requirement (averaging a single stream or comparing two interleaved streams of numbers), (b) the distribution of sample values (uniform or Gaussian), and (c) their range (1-9 or 100-900). The data showed compression of subjective values in the averaging task, but anticompression in the comparison task. This pattern held for both distribution types and for both ranges. In model simulations, we show that either compression or anticompression can be beneficial for noisy observers, depending on the sample-level processing demands imposed by the task. This suggests that the empirically observed patterns of over- and underweighting might reflect adaptive responses. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Knowledge updating in real-world estimation: Connecting hindsight bias and seeding effects.

When people estimate the quantities of objects (e.g., country populations), are then presented with the objects' actual quantities, and subsequently asked to remember their initial estimates, responses are often distorted towards the actual quantities. This hindsight bias-traditionally considered to reflect a cognitive error-has more recently been proposed to result from adaptive knowledge updating. But how to conceptualize such knowledge-updating processes and their potentially beneficial consequences? Here, we provide a framework that conceptualizes knowledge updating in the context of hindsight bias in real-world estimation by connecting it with research on seeding effects-improvements in people's estimation accuracy after exposure to numerical facts. This integrative perspective highlights a previously neglected facet of knowledge updating, namely, recalibration of metric domain knowledge, which can be expected to lead to transfer learning and thus improve estimation for objects from a domain more generally. We develop an experimental paradigm to investigate the association of hindsight bias with improved estimation accuracy. In Experiment 1, we demonstrate that the classical approach to induce hindsight bias indeed produces transfer learning. In Experiment 2, we provide evidence for the novel prediction that hindsight bias can be triggered via transfer learning; this establishes a direct link from knowledge updating to hindsight bias. Our work integrates two prominent but previously unconnected research programs on the effects of knowledge updating in real-world estimation and supports the notion that hindsight bias is driven by adaptive learning processes. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

How are mental representations of asthma triggers and symptoms related to interpersonal risk perceptions? A psychometric investigation of caregivers of children with asthma.

OBJECTIVE: Parents and guardians (hereafter caregivers) make decisions for their children's medical care. However, many caregivers of children with asthma struggle to understand their child's illness. We used the psychometric paradigm to investigate how caregivers conceptualize, or mentally represent, asthma triggers and symptoms and how these representations are linked to perceived asthma exacerbation risk. METHODS: We asked 377 caregivers of children with asthma across the U.S. to rate 20 triggers or 20 symptoms along 15 characteristics. Caregivers also indicated their perceived risk of their child having an asthma exacerbation (hereafter interpersonal risk perceptions). Using principal components analysis, we extracted key dimensions underlying caregivers' ratings on the characteristics. Then we related the triggers' and symptoms' scores on the dimensions to caregivers' interpersonal risk perceptions. RESULTS: Interpersonal risk perceptions were higher for triggers with high ratings for the dimensions severe and relevant, and negative affect-yet manageable, but not chronic-yet unpredictable. Risk perceptions were also higher for symptoms with high ratings for the dimensions severe and unpredictable, and relevant and common, but not self-blame or manageable despite unknown cause. CONCLUSION: By identifying key dimensions underlying caregivers' mental representations of asthma triggers and symptoms, these findings can inform a new approach to asthma education.

Attribute attention and option attention in risky choice.

Probability weighting is one of the most powerful theoretical constructs in descriptive models of risky choice and constitutes a central component of cumulative prospect theory (CPT). Probability weighting has been shown to be related to two facets of attention allocation: one analysis showed that differences in the shape of CPT's probability-weighting function are linked to differences in how attention is allocated across attributes (i.e., probabilities vs. outcomes); another analysis (that used a different measure of attention) showed a link between probability weighting and differences in how attention is allocated across options. However, the relationship between these two links is unclear. We investigate to what extent attribute attention and option attention independently contribute to probability weighting. Reanalyzing data from a process-tracing study, we first demonstrate links between probability weighting and both attribute attention and option attention within the same data set and the same measure of attention. We then find that attribute attention and option attention are at best weakly related and have independent and distinct effects on probability weighting. Moreover, deviations from linear weighting mainly emerged when attribute attention or option attention were imbalanced. Our analyses enrich the understanding of the cognitive underpinnings of preferences and illustrate that similar probability-weighting patterns can be associated with very different attentional policies. This complicates an unambiguous psychological interpretation of psycho-economic functions. Our findings indicate that cognitive process models of decision making should aim to concurrently account for the effects of different facets of attention allocation on preference. In addition, we argue that the origins of biases in attribute attention and option attention need to be better understood.

Linking cognitive and affective heuristic cues to interpersonal risk perceptions and behavior.

People often use cognitive and affective heuristics when judging the likelihood of a health outcome and making health decisions. However, little research has examined how heuristics shape risk perceptions and behavior among people who make decisions on behalf of another person. We examined associations between heuristic cues and caregivers' perceptions of their child's asthma risk, the frequency of caregivers' asthma management behaviors, and child health outcomes. We used Ipsos KnowledgePanel to recruit 814 U.S. adult caregivers of children with asthma of the age <18 years. Participants completed a survey at baseline (T1) and 3 months later (T2). Caregivers who, at T1, reported greater negative affect about their child's asthma (affect heuristic cue), greater ease of imagining their child experiencing asthma symptoms (availability heuristic cue), and greater perceived similarity between their child and a child who has ever experienced asthma symptoms (representativeness heuristic cue) reported statistically significantly (p < 0.05) higher interpersonal perceived risk of their child having an exacerbation or uncontrolled asthma at T1. They also indicated at T2 that their child had poorer asthma control and more frequent exacerbations. Greater T1 negative affect was associated with more frequent T2 actions to reduce inflammation, manage triggers, and manage symptoms, and with poorer T2 child health outcomes. Heuristic cues are likely important for interpersonal-not just personal-risk perceptions. However, the interrelationship between caregivers' ratings of heuristic cues (in particular, negative affect) and risk judgments may signify a struggle with managing their child's asthma and need for extra support from health care providers or systems.

Toward an attentional turn in research on risky choice.

For a long time, the dominant approach to studying decision making under risk has been to use psychoeconomic functions to account for how behavior deviates from the normative prescriptions of expected value maximization. While this neo-Bernoullian tradition has advanced the field in various ways-such as identifying seminal phenomena of risky choice (e.g., Allais paradox, fourfold pattern)-it contains a major shortcoming: Psychoeconomic curves are mute with regard to the cognitive mechanisms underlying risky choice. This neglect of the mechanisms both limits the explanatory value of neo-Bernoullian models and fails to provide guidance for designing effective interventions to improve decision making. Here we showcase a recent "attentional turn" in research on risk choice that elaborates how deviations from normative prescriptions can result from imbalances in attention allocation (rather than distortions in the representation or processing of probability and outcome information) and that thus promises to overcome the challenges of the neo-Bernoullian tradition. We argue that a comprehensive understanding of preference formation in risky choice must provide an account on a mechanistic level, and we delineate directions in which existing theories that rely on attentional processes may be extended to achieve this objective.

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

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

Developmental differences in description-based versus experience-based decision making under risk in children.

The willingness to take a risk is shaped by temperaments and cognitive abilities, both of which develop rapidly during childhood. In the adult developmental literature, a distinction is drawn between description-based tasks, which provide explicit choice-reward information, and experience-based tasks, which require decisions from past experience, each emphasizing different cognitive demands. Although developmental trends have been investigated for both types of decisions, few studies have compared description-based and experience-based decision making in the same sample of children. In the current study, children (N = 112; 5-9 years of age) completed both description-based and experience-based decision tasks tailored for use with young children. Child temperament was reported by the children's primary teacher. Behavioral measures suggested that the willingness to take a risk in a description-based task increased with age, whereas it decreased in an experience-based task. However, computational modeling alongside further inspection of the behavioral data suggested that these opposite developmental trends across the two types of tasks both were associated with related capacities: older (vs. younger) children's higher sensitivity to experienced losses and higher outcome sensitivity to described rewards and losses. From the temperamental characteristics, higher attentional focusing was linked with a higher learning rate on the experience-based task and a bias to accept gambles in the gain domain on the description-based task. Our findings demonstrate the importance of comparing children's behavior across qualitatively different tasks rather than studying a single behavior in isolation.

The perception of food products in adolescents, lay adults, and experts: A psychometric approach.

Almost 40% of global mortality is attributable to an unhealthy diet, and adolescents and young adults are particularly affected by growing obesity rates. How do (young) people conceptualize and judge the healthiness of foods and how are the judgments embedded in people's mental representations of the food ecology? We asked respondents to rate a large range of common food products on a diverse set of characteristics and then applied the psychometric paradigm to identify the dimensions structuring people's mental representations of the foods. Respondents were also asked to rate each food in terms of its healthiness, and we used the foods' scores on the extracted dimensions to predict the healthiness judgments. We compared three groups of respondents: adolescents, lay adults, and nutrition experts. Naturalness levels (e.g., processing, artificial additives) and cholesterol and protein content emerged as the two central dimensions structuring respondents' mental representations of the foods. Relative to the other two groups, the adolescents' representations were less differentiated. Judged food healthiness was determined by multiple factors, but naturalness was the strongest predictor across all groups. Overall, the adolescents' responses showed considerable heterogeneity, suggesting a lack of solid food knowledge and the need for tailored nutrition education on specific food products and content characteristics. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Structural parameter interdependencies in computational models of cognition.

Computational modeling of cognition allows latent psychological variables to be measured by means of adjustable model parameters. The estimation and interpretation of the parameters are impaired, however, if parameters are strongly intercorrelated within the model. We point out that strong parameter interdependencies are especially likely to emerge in models that combine a subjective value function with a probabilistic choice rule-a common structure in the literature. We trace structural parameter interdependencies between value function and choice rule parameters across several prominent computational models, including models on risky choice (cumulative prospect theory), categorization (the generalized context model), and memory (the SIMPLE model of free recall). Using simulation studies with a generic choice model, we show that the accuracy in parameter estimation is hampered in the presence of high parameter intercorrelations, particularly the ability to detect group differences on the parameters and associations of the parameters with external variables. We demonstrate that these problems can be alleviated by using a different specification of stochasticity in the model, for example, by assuming parameter stochasticity or a constant error term. In addition, application to two empirical data sets of risky choice shows that alleviating parameter interdependencies in this way can lead to different conclusions about the estimated parameters. Our analyses highlight a common but often neglected problem of computational models of cognition and identify ways in which the design and application of such models can be improved. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Studies in Ecological Rationality.

Ecological rationality represents an alternative to classic frameworks of rationality. Extending on Herbert Simon's concept of bounded rationality, it holds that cognitive processes, including simple heuristics, are not per se rational or irrational, but that their success rests on their degree of fit to relevant environmental structures. The key is therefore to understand how cognitive and environmental structures slot together. In recent years, a growing set of analyses of heuristic-environment systems has deepened the understanding of the human mind and how boundedly rational heuristics can result in successful decision making. This article is concerned with three conceptual challenges in the study of ecological rationality. First, do heuristics also succeed in dynamic contexts involving competitive agents? Second, can the mind adapt to environmental structures via an unsupervised learning process? Third, how can research go beyond mere descriptions of environmental structures to develop theories of the mechanisms that give rise to those structures? In addressing these questions, we illustrate that a successful theory of rationality will focus on the adaptive aspects of the mind and will need to account for three components: the mind's information processing, the environment to which the mind adapts, and the intersection between the environment and the mind.

Nonlinear probability weighting can reflect attentional biases in sequential sampling.

Nonlinear probability weighting allows cumulative prospect theory (CPT) to account for key phenomena in decision making under risk (e.g., certainty effect, fourfold pattern of risk attitudes). It describes the impact of risky outcomes on preferences in terms of a rank-dependent nonlinear transformation of their objective probabilities. The attentional Drift Diffusion Model (aDDM) formalizes the finding that attentional biases toward an option can shape preferences within a sequential sampling process. Here we link these two influential frameworks. We used the aDDM to simulate choices between two options while systematically varying the strength of attentional biases to either option. The resulting choices were modeled with CPT. Changes in preference due to attentional biases in the aDDM were reflected in highly systematic signatures in the parameters of CPT's weighting function (curvature, elevation). In a re-analysis of a large set of previously published data, we demonstrate that attentional biases are also empirically linked to patterns in probability weighting as suggested by the simulations. Our analyses also revealed a previously overlooked link between patterns in probability weighting and response times. These findings highlight that distortions in probability weighting can arise from simple option-specific attentional biases in information search, and suggest an alternative to common interpretations of weighting-function parameters in terms of probability sensitivity and optimism. They also point to novel, attention-based explanations for empirical phenomena associated with characteristic shapes of CPT's probability-weighting function (e.g., certainty effect, description-experience gap). The results advance the integration of two prominent computational frameworks for decision making. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The intuitive conceptualization and perception of variance.

Statistical concepts (e.g., mean, variance, correlation) offer powerful ways to characterize the structure of the environment. To what extent do statistical concepts also play a role for people assessing the environment? Previous work on the mind as "intuitive statistician" has mainly focused on the judgment of means and correlations (Peterson & Beach, 1967). Much less is known about how people conceptualize and judge variance. In a survey and three experimental studies, we explored people's intuitive understanding of variance as a concept and investigated the factors affecting people's judgments of variance. The survey findings showed that most people hold concepts of variance that they can articulate; these concepts, however, reflect not only statistical variance (i.e., deviations from the average) but also the pairwise distance between stimuli, their range, and their variety. The experimental studies revealed that although people's judgments of variance are sensitive to the statistical variance of stimuli, variety and range also play an important role. The results can inform psychological models of judgments of variance.

Psychological factors shaping public responses to COVID-19 digital contact tracing technologies in Germany.

The COVID-19 pandemic has seen one of the first large-scale uses of digital contact tracing to track a chain of infection and contain the spread of a virus. The new technology has posed challenges both for governments aiming at high and effective uptake and for citizens weighing its benefits (e.g., protecting others' health) against the potential risks (e.g., loss of data privacy). Our cross-sectional survey with repeated measures across four samples in Germany ([Formula: see text]) focused on psychological factors contributing to the public adoption of digital contact tracing. We found that public acceptance of privacy-encroaching measures (e.g., granting the government emergency access to people's medical records or location tracking data) decreased over the course of the pandemic. Intentions to use contact tracing apps-hypothetical ones or the Corona-Warn-App launched in Germany in June 2020-were high. Users and non-users of the Corona-Warn-App differed in their assessment of its risks and benefits, in their knowledge of the underlying technology, and in their reasons to download or not to download the app. Trust in the app's perceived security and belief in its effectiveness emerged as psychological factors playing a key role in its adoption. We incorporate our findings into a behavioral framework for digital contact tracing and provide policy recommendations.

How is the hypothesis space represented? Evidence from young children's active search and predictions in a multiple-cue inference task.

To successfully navigate an uncertain world, one has to learn the relationship between cues (e.g., wind speed, atmospheric pressure) and outcomes (e.g., rain). When learning, it is possible to actively manipulate the cue values to test hypotheses about this relationship directly. Across two studies, we investigated how 5- to 7-year-olds actively learned cue-outcome relationships, and what their behavior revealed about how they represented the hypothesis space. Children learned how two cues (color and shape) predicted some monsters' relative speed, by selecting which monster pairs to see racing. We compared two computational models in their ability to capture children's behavior: a cue-abstraction model, which organizes the hypothesis space based on abstracted cue-outcome relationships, and a permutation-based model, which represents the hypothesis space based on the relative speed of individual monsters. The results of Study 1 (26 five-year-olds, 14 female and 25 six-year-olds, 15 female; predominantly White, fluent in English) provided the first evidence that 5- and 6-year-olds can use cue-abstraction hypothesis space representations when provided with scaffolding. However, Study 2 (65 five-year-olds, 33 female; 67 six-year-olds, 33 female; 68 seven-year-olds, 33 female; predominantly White, fluent in German) showed that young children were best described by the permutation-based model, and that only 7-year-olds, when provided with memory aids, were best captured by the cue-abstraction model. Overall, our results highlight the guiding role of the hypothesis space for active search and learning, suggesting that these two phases might trigger different representations, and indicating a developmental shift in how children represent the hypothesis space. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Boosting people's ability to detect microtargeted advertising.

Online platforms' data give advertisers the ability to "microtarget" recipients' personal vulnerabilities by tailoring different messages for the same thing, such as a product or political candidate. One possible response is to raise awareness for and resilience against such manipulative strategies through psychological inoculation. Two online experiments (total [Formula: see text]) demonstrated that a short, simple intervention prompting participants to reflect on an attribute of their own personality-by completing a short personality questionnaire-boosted their ability to accurately identify ads that were targeted at them by up to 26 percentage points. Accuracy increased even without personalized feedback, but merely providing a description of the targeted personality dimension did not improve accuracy. We argue that such a "boosting approach," which here aims to improve people's competence to detect manipulative strategies themselves, should be part of a policy mix aiming to increase platforms' transparency and user autonomy.

Who you know is what you know: Modeling boundedly rational social sampling.

The social environment provides a sampling space for making informed inferences about features of the world at large, such as the distribution of preferences, risks, behaviors, or other events. How do people search this sampling space and make inferences based on the instances sampled? Inspired by existing models of bounded rationality and in accord with research on the structure of social memory, we develop and test the social-circle model, a parameterized, probabilistic process account of how people make inferences about relative event frequencies. The model extends to social sampling the idea that cognitive search is both structured and limited; moreover, it captures individual differences in the order in which sections of the sampling space are probed, in difference thresholds, and in response error. Using a hierarchical Bayesian latent-mixture approach, we submit the model to a rigorous model comparison. In Study 1, a reanalysis of published data, the social-circle model outperformed both a model assuming exhaustive search and a simple heuristic assuming no individual differences in search or difference thresholds. Study 2 establishes the robustness of these findings in a different domain and across age groups (adults and children). We find that children also consult their social memories for inferential purposes and rely on sequential and limited search. Finally, model and parameter recovery analyses (Study 3) demonstrate the ability of the social-circle model to recover the characteristics of the cognitive processes assumed to underlie social sampling. Our analyses establish that social sampling in both children and adults follows key principles of bounded rationality. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Availability, Affect, and Decisions to Seek Information about Cancer Risks.

How do people decide which risks they want to get informed about? The present study examines the role of the availability and affect heuristics on these decisions. Participants (N = 100, aged 19-72 years) selected for which of 23 cancers they would like to receive an information brochure, reported the number of occurrences of each type of cancer in their social circle (availability), and rated their dread reaction to each type of cancer (affect); they also made relative judgments about which of 2 cancers was more common in Germany (judged risk). Participants tended to choose information brochures for those cancers for which they indicated a higher availability within their social networks as well as for cancers they dreaded. Mediation analyses suggested that the influence of availability and affect on information choice was only partly mediated by judged risk. The results demonstrate the operation of 2 key judgment heuristics (availability and affect), previously studied in risk perception, also in decisions about information choice. We discuss how our findings can be used to identify which risks are likely to fall from people's radar.

Age differences in risk attitude are shaped by option complexity.

The canonical conclusion from research on age differences in risky choice is that older adults are more risk averse than younger adults, at least in choices involving gains. Most of the evidence for this conclusion derives from studies that used a specific type of choice problem: choices between a safe and a risky option. However, safe and risky options differ not only in the degree of risk but also in the amount of information to be processed-that is, in their complexity. In both an online and a lab experiment, we demonstrate that differences in option complexity can be a key driver of age differences in risk attitude. When the complexity of the safe option is increased, older adults no longer seem more risk averse than younger adults (in gains). Using computational modeling, we test mechanisms that potentially underlie the effect of option complexity. The results show that participants are not simply averse to complexity, and that increasing the complexity of safe options does more than simply make responses more noisy. Rather, differences in option complexity affect the processing of attribute information: whereas the availability of a simple safe option is associated with the distortion of probability weighting and lower outcome sensitivity, these effects are attenuated when both options are more similar in complexity. We also dissociate these effects of option complexity from an effect of certainty. Our findings may also have implications for age differences in other decision phenomena (e.g., framing effect, loss aversion, immediacy effect). (PsycInfo Database Record (c) 2020 APA, all rights reserved).