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. We test the boundaries of this effect (Experiment 4), finding that including a small amount of information beyond that related to the target answer has a detrimental effect. Finally, we examine whether people know what information they need (Experiment 5). We find that simple, targeted, information still leads to the best decisions, while participants who believe they do not need information or seek out the most complex information performed worse.

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. We present data on the relations of insect knowledge (both propositional and causal), associated emotional valences, and political orientation to concern for insect conservation, for samples of American college students and U.S. and U.K. Prolific workers. We asked whether concern for insect conservation is more associated with knowledge than emotional valence or political orientation, and whether this is especially so for U.K. residents, who have a reputation for a love of nature that is not linked to political identity. We found that U.K. participants did show greater overall concern, consistent with the national reputation. Causal knowledge mattered, but political orientation was the strongest predictor of concern for insect conservation for both U.S. and U.K. participants. Valence contributed for U.S. participants but not for U.K. participants. Our results suggest that politicized public discourse penetrates attitudes toward insects even when it does not explicitly concern insects, and knowledge variation has less impact. However, the emotional reaction has a reduced influence where relevant discourse is less polarized. Insects may often evoke negative emotions and motivations, but it is not impossible to love a bug.

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. METHODS: We surveyed 200 different individuals at 12 time points from March through September 2020. At each time point, we elicited participants' knowledge about causes, risk factors, and preventative interventions for 8 viral (Ebola, common cold, COVID-19, Zika) and nonviral (food allergies, amyotrophic lateral sclerosis [ALS], strep throat, stroke) illnesses. Participants were further asked how they learned about each illness and to rate how much they trust various sources of health information. RESULTS: We found that participants used different information sources to obtain health information about common illnesses (food allergies, strep throat, stroke) compared to emerging illnesses (Ebola, common cold, COVID-19, Zika). Participants relied mainly on news media, government agencies, and social media for information about emerging illnesses, while learning about common illnesses from family, friends, and medical professionals. Participants relied on social media for information about COVID-19, with their knowledge accuracy of COVID-19 declining over the course of the pandemic. The number of information sources participants used was positively correlated with health knowledge quality, though there was no relationship with the specific source types consulted. CONCLUSIONS: Building on prior work on health information seeking and factors affecting health knowledge, we now find that people systematically consult different types of information sources by illness type and that the number of information sources people use affects the quality of individuals' health knowledge. Interventions to disseminate health information may need to be targeted to where individuals are likely to seek out information, and these information sources differ systematically by illness type.

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. We found that thinking the COVID-19 pandemic was similar to other serious disease outbreaks predicted greater social distancing and mask-wearing, whereas likening COVID-19 to the seasonal flu predicted engaging in significantly fewer of these behaviors. Thinking of COVID-19 as similar to zombie apocalypse scenarios or moments of major societal upheaval predicted stocking-up behaviors, but not disease mitigation behaviors. These early category comparisons influenced behaviors over a six-month span of longitudinal data collection. Our findings suggest that early conceptual comparisons track with emergent disease categories over time and influence the behaviors people engage in related to the disease. Our research illustrates how early concept formation influences behaviors over time, and suggests ways for public health experts to communicate with the public about emergent diseases.

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. We found that perceiving experts to understand the causal mechanism of transmission was predictive of engaging in more social distancing, advice following, hand washing, and mask wearing. Believing experts could intervene and treat the symptoms or underlying cause of COVID-19 was negatively associated with these same behaviors, but to a lesser degree. These results held above and beyond political ideology and were overall similar for people who perceived themselves to be at high or low risk for COVID-19. This research provides new insights into how people's behaviors are guided by perceptions of others' understanding and highlights important implications for expert health-risk communication. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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. That is, causal inference methods have been evaluated on their accuracy at uncovering ground truth, but not the utility of such output for human consumption. Simply presenting more information to people may not have the intended effects, particularly when they must combine this information with their existing knowledge and beliefs. While psychological studies have shown that causal models can be used to choose interventions and predict outcomes, that work has not tested structures of the complexity found in machine learning, or how such information is interpreted in the context of existing knowledge. RESULTS: Through experiments on Amazon Mechanical Turk, we study how people use causal information to make everyday decisions about diet, health, and personal finance. Our first experiment, using decisions about maintaining bodyweight, shows that causal information can actually lead to worse decisions than no information at all. In Experiment 2, we test decisions about diabetes management, where some participants have personal domain experience and others do not. We find that individuals without such experience are aided by causal information, while individuals with experience do worse. Finally, our last two experiments probe how prior experience interacts with causal information. We find that while causal information reduces confidence in individuals with prior experience, it has the opposite effect on those without experience. In Experiment 4 we show that our results are not due to an inability to use causal models, and that they may be due to familiarity with a domain rather than actual knowledge. CONCLUSION: While causal inference can potentially lead to more informed decisions, we find that more work is needed to make causal models useful for the types of decisions found in daily life.

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. We set out to understand health beliefs of Hispanic adults and, with that knowledge, facilitate tailored messaging to promote patient activation and lifestyle change. Using the Risk Perception Survey for Developing Diabetes along with demographic and lifestyle intervention interest questions, a 34-question survey was mailed to a registry of Hispanic adults with a diagnosis of prediabetes and an HbA1c between 5.7 and 6.4% (N = 414). Despite more than three-quarters of respondents (n = 92; 77%) indicating they had prior knowledge of their diagnosis, overall diabetes risk knowledge was low. A significant difference in diabetes risk knowledge was found between groups stratified by education level. High scores in personal control and worry were reported. Respondents overwhelmingly reported interest in exercise (n = 92; 77%) and healthy eating interventions (n = 60; 50%) over technology-based interventions. High levels of worry and personal control, combined with low to intermediate levels of risk knowledge, indicate an opportunity for education and activation in this community. Healthy eating and exercise programs are possible interventions that may slow the progression from prediabetes to diabetes.

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

Background: 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. Objective: Our objective was to explore how laypeople judged the helpfulness of treatments when a limited set of mental health symptoms is presented. Method: Across four experiments, Mechanical Turk and college undergraduate participants (N = 331) read descriptions displaying sets of three mental health symptoms and rated how helpful pharmaceuticals, counseling, or alternative medicine would be on a 0 (not at all helpful) to 100 (completely helpful) scale. We measured judgments for perceived mental and medical symptoms (Experiment 1) and how judgments were influenced by symptom severity (Experiment 2), duration (Experiment 3), and if alternative medicine and conventional treatments were used in conjunction (Experiment 4). Results: Perceived mental symptoms were rated as helped by counseling, while perceived medical symptoms were rated as helped by medication. Alternative medicine was never rated as extremely helpful. For example, in Experiment 1, counseling (mean [M] = 80.1) was rated more helpful than pharmaceuticals (M = 50.5; P < 0.001) or alternative medicine (M = 45.1; P < 0.001) for mental symptoms, and pharmaceuticals (M = 62.6) was rated more helpful than counseling (M = 36.1; P < 0.001) or alternative medicine (M = 47.5; P < 0.001) for medical symptoms. This pattern held regardless of severity, duration, or the adjunct use of alternative medicine. Limitations: We employed a general population sample and measured hypothetical treatment judgments. Conclusions: Mental health symptoms viewed as problems of the mind are thought to need different treatment than mental health symptoms seen as problems of the body.

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., child associates with deviant peers) relative to a low-risk environment (e.g., child associates with normative peer group). Importantly, not all symptoms are influenced by context to the same extent, and there is low agreement across people as to how this influence manifests. In this paper, we explore what factors predict the extent to which clinicians and laypeople interpret mental disorder symptoms as a function of diagnosis-congruent versus incongruent contextual information. We tested the impact of 2 statistical factors (prevalence and diagnosticity) and 2 more intuitive factors (diagnostic importance and abnormality) on the degree to which a symptom is interpreted differently in different contexts. Clinicians' impressions of the diagnosticity and importance of a symptom evidenced a curvilinear relationship with the use of context, with extremely important and unimportant as well as extremely diagnostic and nondiagnostic symptoms being less influenced by context. Laypeople showed a similar curvilinear relation between diagnosticity judgments and context effects. Additionally, clinicians showed a linear relationship between abnormality judgments and context use, with extremely abnormal symptoms being influenced less by context, whereas laypeople showed a curvilinear relationship between symptom abnormality and context use, with extremely abnormal and normal symptoms being influenced the most by context. We discuss implications of these findings for clinical diagnosis. (PsycINFO Database Record

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). We found differences between these groups in beliefs held concerning the necessity of removing shared category features to effectively cure disorders. While laypeople endorsed the idea that the cause needed to be removed to cure both mental and medical disorders, this endorsement decreased with expertise. Primary care providers were less willing to endorse this for mental disorders than for medical disorders. Our results support the notion that the reduction of beliefs concerning the existence of essences is a unique effect of expertise in the mental health domain, and does not extend to other areas of expertise. In physicians, this reduction of essentialist beliefs was most evident in questions regarding treatment. Similarities and differences to the results from Ahn et al. (2006) are discussed.

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. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.

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. With fictitious mental disorders, people were less willing to interact with people described as having a communicable mental disorder than with those described as possessing any of the other factors of interest, highlighting the independent influence of these contagion beliefs (Experiment 2). We further explored beliefs about the communicability of mental disorders in Experiment 3 by asking participants to generate descriptions of how mental disorders are transferred between people. Our findings suggest the importance of understanding contagion beliefs in discovering why people distance themselves from people diagnosed with mental disorders. More generally, our findings help in understanding how our basic category knowledge is used to guide interactions with category members, illustrating how knowledge is translated into action.

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. We investigated whether laypeople use contextual information to make judgments regarding childhood mental health disorder symptoms. In Experiment 1, we demonstrated that laypeople's judgments of the likelihood of a mental disorder are influenced by non-diagnostic contextual information that surrounds symptoms of the disorder. In Experiment 2, we demonstrated that providing a causal origin for such disorder symptoms accentuates the use of context, regardless of the nature of the causal process (i.e., environmental vs. biological). These findings indicate that contextual influences on judgments about mental health concerns may reflect a more general set of mental reasoning processes than indicated by previous work focused on clinicians' judgments. Consequently, these findings have important implications for how we think about the influence of contextual information on decision making more generally as well as for improving our ability to both reliably identify children in need of mental health care and increase children's access to such care.

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. Experiments 1 and 3 found that people overtly endorse causal essences in nonarbitrary kinds but are less likely to do so for arbitrary categories. Experiments 2 and 4 found that people were more willing to generalize a member's known causal relations (or lack thereof) when dealing with a kind than when dealing with an arbitrary category. These differences between kinds and arbitrary categories were found across various domains-not only for categories of living things, but also for artefacts. These findings have certain real-world implications, including how people make sense of mental disorders that are treated as real kinds.

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. We tested memory for realistic patient-therapist interactions in experienced clinicians, intermediately trained graduate students, and laypeople. Clinicians recalled fewer facts than intermediate trainees and as many as laypeople. Furthermore, clinicians reported more abstracted information than all other participants, providing the first empirical demonstration of knowledge encapsulation in the memory of mental health clinicians. We discuss how our results fit into the existing literature on clinical expertise in mental health and the implications of our findings for future research relevant to mental health care.

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. Contextual information highly affected judgments and these effects varied across the 15 conduct disorder symptoms. It is important to note that clinical judgments were not in agreement on the symptoms affected by context.

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. In particular, the authors examined whether learners willingly place ambiguous observations into one of the categories relevant to the causal hypothesis, in accordance with their current causal beliefs. In Experiment 1, people's frequency estimates of contingency data reflected that information ambiguous along a continuous quantity dimension was spontaneously categorized and assimilated in a causal induction task. This assimilation process was moderated by the strength of the upheld causal hypothesis (Experiment 2), could alter the overall perception of a causal relationship (Experiment 3), and could occur over temporal sequences (Experiment 4).

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. Clinicians were polarized on their views about whether mental disorders are categorical or dimensional. These findings reflect current controversies about mental disorders in the field at large.

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., would reduce the primacy effect. Experiment 1 showed a primacy effect with learning contingencies involving only one outcome but no primacy effect with two outcomes. Experiment 2 demonstrated that the magnitude of the primacy effect correlated with participants' verbal working memory capacity. It is concluded that a critical moderator for exhibition of the primacy effect is task complexity, presumably because it interferes with initial hypothesis development.

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., explicit pairs) and affect typicality judgments are the ones that are more likely theory based than are those that are not explicitly recognized (i.e., implicit pairs). Real-world categories and their properties, taken from Malt and Smith (1984), were examined. We found that explicit pairs had a greater number of asymmetric dependency relations (i.e., one feature depends on the other feature, but not vice versa) and stronger dependency relations than did implicit pairs, which were statistically correlated in the environment but were not recognized as such. In addition, people more often provided specific relation labels for explicit pairs than for implicit pairs; these labels were most often causal relations. Finally, typicality judgments were more affected when explicit correlations were broken than when implicit correlations were broken. It is concluded that in natural categories, feature correlations that are explicitly represented and affect typicality judgments are the ones about which people have theories.