Perceived Penalties for Sharing Patient Beliefs with Health Care Providers.

Background: Health care interactions may require patients to share with a physician information they believe but is incorrect. While a key piece of physicians' work is educating their patients, people's concerns of being seen as uninformed or incompetent by physicians may lead them to think that sharing incorrect health beliefs comes with a penalty. We tested people's perceptions of patients who share incorrect information and how these perceptions vary by the reasonableness of the belief and its centrality to the patient's disease.

Less is more: information needs, information wants, and what makes causal models useful.

Each day people make decisions about complex topics such as health and personal finances. Causal models of these domains have been created to aid decisions, but the resulting models are often complex and it is not known whether people can use them successfully. We investigate the trade-off between simplicity and complexity in decision making, testing diagrams tailored to target choices (Experiments 1 and 2), and with relevant causal paths highlighted (Experiment 3), finding that simplicity or directing attention to simple causal paths leads to better decisions.

What Does it Take to Love a Bug? Knowledge, Emotional Valence, and Politics in Attitudes Toward Insect Conservation.

Domain knowledge is often considered a minor contributor to environmental attitudes, with social and motivational factors dominating. Yet, domains may differ. Declining insect populations are a critical conservation concern but are not prominent in public discourse, potentially reducing the impact of social and motivational variables.

Crowdsourced Perceptions of Human Behavior to Improve Computational Forecasts of US National Incident Cases of COVID-19: Survey Study.

Background: Past research has shown that various signals associated with human behavior (eg, social media engagement) can benefit computational forecasts of COVID-19. One behavior that has been shown to reduce the spread of infectious agents is compliance with nonpharmaceutical interventions (NPIs). However, the extent to which the public adheres to NPIs is difficult to measure and consequently difficult to incorporate into computational forecasts of infectious diseases.

Health Information Sourcing and Health Knowledge Quality: Repeated Cross-sectional Survey.

Background: People's health-related knowledge influences health outcomes, as this knowledge may influence whether individuals follow advice from their doctors or public health agencies. Yet, little attention has been paid to where people obtain health information and how these information sources relate to the quality of knowledge.

Objective: We aim to discover what information sources people use to learn about health conditions, how these sources relate to the quality of their health knowledge, and how both the number of information sources and health knowledge change over time.

Bring out your experts: The relationship between perceived expert causal understanding and pandemic behaviors.

In the complex modern world, people's understanding of how things work is often outsourced to other people. We explore how people's perceptions of expert causal understanding of the coronavirus disease (COVID-19) pandemic predicted their pandemic-related behaviors. As part of a larger longitudinal study, we collected data at four time points that measured participants' perceptions of experts' causal understanding of COVID-19, along with those participants' self-reported pandemic-related health behaviors.

Of Pandemics and Zombies: The Influence of Prior Concepts on COVID-19 Pandemic-Related Behaviors.

We use a concepts and categories research perspective to explore how prior conceptual knowledge influences thinking about a novel disease, namely COVID-19. We collected measures of how similar people thought COVID-19 was to several existing concepts that may have served as other possible comparison points for the pandemic. We also collected participants' self-reported engagement in pandemic-related behaviors.

How causal information affects decisions.

Background: Causality is inherently linked to decision-making, as causes let us better predict the future and intervene to change it by showing which variables have the capacity to affect others. Recent advances in machine learning have made it possible to learn causal models from observational data. While these models have the potential to aid human decisions, it is not yet known whether the output of these algorithms improves decision-making.

Exploring Health Beliefs Among Hispanic Adults with Prediabetes.

Diabetes and prediabetes are increasing in prevalence, corresponding to epidemic rates of obesity. Hispanic adults with prediabetes are 1.7 times more likely than non-Hispanic whites to progress to diabetes.

Lay Judgments of Mental Health Treatment Options: The Mind Versus Body Problem.

Past research shows that people believe psychologically caused mental disorders are helped by different treatments than biologically caused mental disorders. However, it is unknown how people think about treatment when limited information is known to identify the disorder. Our objective was to explore how laypeople judged the helpfulness of treatments when a limited set of mental health symptoms is presented.

The influence of expertise on essence beliefs for mental and medical disorder categories.

Research suggests that expertise in a specific category domain influences categorization. Work related to beliefs about mental disorders finds that laypeople treat mental disorders as if they do have causal essences, while clinicians do not-differences that may be attributable to expertise (Ahn, Flanagan, Marsh, & Sanislow, 2006). To test whether reduced beliefs in essences are indicative of an overall influence of expertise or a demonstration of a phenomenon specific to expertise in the mental health domain we compared beliefs about mental and medical disorders held by practicing physicians (n = 43; 19 primary care and 24 non-psychiatry specialists) and laypeople (n = 40).

The sweet spot of clinical intuitions: Predictors of the effects of context on impressions of conduct disorder symptoms.

How people interpret a mental disorder symptom has been shown to depend on the contextual life factors surrounding its presentation. Specifically, people are more likely to judge a symptom as clinically relevant if that symptom presents in a high-risk environment (e.g.

The influence of contextual information on lay judgments of childhood mental health concerns.

Decisions about whether a person is in need of mental health care are often made by laypeople with no training in the identification of mental health concerns. For example, the parent of a child displaying problematic behavior has to decide whether this behavior is likely related to mental health concerns and necessitates professional care. The process of identifying mental health concerns is made more complicated by the rich background of real-world environmental factors or contexts in which concerns can present-contexts that might or might not relate to the presence of mental health concerns.

Thinking you can catch mental illness: how beliefs about membership attainment and category structure influence interactions with mental health category members.

We explored beliefs about mental disorder categories that influence potential interactions with category members. Specifically, we investigated beliefs related to how membership in a mental disorder category is obtained (communicability and causal origin) as well as beliefs related to the underlying reality of disorder categories (essentialism and controllability). In Experiment 1, participants' interaction-willingness decisions were predicted by their beliefs that a mental disorder category was (1) communicable, (2) psychologically caused, (3) environmentally caused, and (4) possessed all-or-none membership.

The selective power of causality on memory errors.

We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation.

Memory for Patient Information as a Function of Experience in Mental Health.

Mental health clinicians are tasked to diagnose and treat the millions of people worldwide seeking help for mental health issues. This paper investigates the memory clinicians have for patient information. We hypothesize that clinicians encapsulate mental health knowledge through experience into more abstract concepts, as in other domains changing what clinicians remember about patients compared with non-professionals.

Causal essentialism in kinds.

The current study examines causal essentialism, derived from psychological essentialism of concepts. We examine whether people believe that members of a category share some underlying essence that is both necessary and sufficient for category membership and that also causes surface features. The main claim is that causal essentialism is restricted to categories that correspond to our intuitive notions of existing kinds and hence is more attenuated for categories that are based on arbitrary criteria.

Patients' contexts and their effects on clinicians' impressions of conduct disorder symptoms.

The purpose of this study was to examine whether contextual information about patients' clinical presentations affected clinicians' judgments of conduct disorder symptoms. Forty-five clinicians read vignettes describing hypothetical patients who displayed one conduct disorder symptom alongside information about the patients' home, school, and peer contexts. Clinicians judged the likelihood of patients meeting conduct disorder criteria.

Spontaneous assimilation of continuous values and temporal information in causal induction.

Existing models of causal induction primarily rely on the contingency between the presence and the absence of a causal candidate and an effect. Yet, classification of observations into these four types of covariation data may not be straightforward because (a) most causal candidates, in real life, are continuous with ambiguous, intermediate values and because (b) effects may unfold after some temporal lag, providing ambiguous contingency information. Although past studies suggested various reasons why ambiguous information may not be used during causal induction, the authors examined whether learners spontaneously use ambiguous information through a process called causal assimilation.

Beliefs about essences and the reality of mental disorders.

Do people believe mental disorders are real and possess underlying essences? The current study found that both novices and practicing clinicians held weaker essentialist beliefs about mental disorders than about medical disorders. They were also unwilling to endorse the idea that mental disorders are real and natural. Furthermore, compared with novices, mental health clinicians were less likely to endorse the view that there is a shared cause underlying a mental disorder and that one needs to remove the cause to get rid of the mental disorder.

Order effects in contingency learning: the role of task complexity.

Dennis and Ahn (2001) found that during contingency learning, initial evidence influences causal judgments more than does later evidence (a primacy effect), whereas López, Shanks, Almaraz, and Fernández (1998) found the opposite (a recency effect). We propose that in contingency learning, people use initial evidence to develop an anchoring hypothesis that tends to be underadjusted by later evidence, resulting in a primacy effect. Thus, factors interfering with initial hypothesis development, such as simultaneously learning too many contingencies, as in López et al.

Effect of theory-based feature correlations on typicality judgments.

In the present study, we examine what types of feature correlations are salient in our conceptual representations. It was hypothesized that of all possible feature pairs, those that are explicitly recognized as correlated (i.e.