Clinical high risk for psychosis: The effects of labelling on public stigma in a undergraduate population.

AIM: Schizophrenia is a highly stigmatized disorder. Identification of youth at high risk for psychosis has the potential for improved outcomes. However, identifying youth at risk could subject them to increased public stigma. Using an experimental vignette design, this study examined relative levels of public stigma elicited by the labels "schizophrenia," "clinical high risk (CHR)," "attenuated psychotic symptoms syndrome (APSS)," a label implying normative adolescent development ("a bad breakup"), and a no-label control condition. METHODS: Ninety-six undergraduates (age: 18.8 + 1.1, range: 18-22) read a vignette describing an adolescent experiencing symptoms typical of CHR for psychosis. The vignette label (APSS, CHR, schizophrenia, a bad breakup or no label) was counterbalanced between participants. Participants answered questions assessing stigma toward the individual and their prior knowledge of and familiarity with psychosis. RESULTS: Overall stigma did not differ across conditions. Only ratings of personal responsibility were higher for the breakup label than the schizophrenia label (P < .05). More prior knowledge about, and higher familiarity with, psychotic symptoms predicted lower overall stigma. CONCLUSION: We did not find that schizophrenia, CHR or APSS labels elicited elevated stigma in this sample relative to the control labels. This may reflect relatively low levels of mental health stigma in the group studied, a new finding inconsistent with earlier work. Greater levels of knowledge about and familiarity with psychosis were associated with lower stigma. These findings reinforce the potential for mental health awareness campaigns to reduce stigma but also raise questions about factors contributing to lower rates of stigma.

Systematic distortions in clinicians' memories for client cases: Increasing causal coherence.

In accord with classic schema theory, people are susceptible to forming false memories that align with stored schema representations (Brewer & Treyens, 1981). Furthermore, clinicians schematize mental disorders as causal networks of features (de Kwaadsteniet, Hagmayer, Krol, & Witteman, 2010; Kim & Ahn, 2002). We asked whether one important consequence of this representation is that clinicians tend to misremember client cases as being more causally coherent than they actually are. We tested this hypothesis by manipulating the causal coherence of case descriptions via a well-documented cue-to-causality, the proportionality between features (Einhorn & Hogarth, 1986). Clinicians read hypothetical cases describing three pieces of clinically relevant client information presented in causal order: recent life events, the clients' emotional reactions to those events, and their behaviors following those reactions. Each piece of information (event, reaction, behaviors) was manipulated to either be severely or mildly negative, rendering it proportionate or disproportionate to the other pieces of information. The clinicians offered diagnoses for these client cases, and then completed an unexpected recognition task. Clinicians were significantly more likely to misremember causally incoherent cases (i.e., in which the severity of the client's emotional reaction did not match the severity of the life event or behaviors) as having been coherent, compared to their likelihood of misremembering coherent cases as having been incoherent. They also incorrectly recognized false reaction lures more frequently overall than false event lures or false behavior lures. We discuss potential implications for the proportionate-response effect, schema theory, inference, causal coherence, and expert judgments. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

How Robust is the Influence of Causal Explanation on Clinical Judgments? Assessments in Structured Clinical Interviews.

When causal life-event explanations for disorder symptoms are available, clinicians tend to explain away those symptoms (Ahn, Novick, & Kim, 2003 ; Meehl, 1973 ), eschewing formal diagnostic guidelines such as the DSM-5 (American Psychiatric Association, 2013 ). We asked whether this effect is attenuated in the context of a structured diagnostic clinical interview procedure, which deliberately directs evaluators' attention to symptoms alone, or whether it is robust enough to continue to emerge. Across two experiments, lay evaluators given causal life-event explanations for disordered behaviors gave them lower judgments of abnormality and need for treatment compared to evaluators not given such explanations, regardless of whether they used a structured clinical interview. Thus, causal life-event explanations may have significant impact on clinical evaluations regardless of the mode of assessment. Implications for the clinical utility of structured interviews and the role of life-event context in diagnosis and classification are discussed.

The effect of abstract versus concrete framing on judgments of biological and psychological bases of behavior.

Human behavior is frequently described both in abstract, general terms and in concrete, specific terms. We asked whether these two ways of framing equivalent behaviors shift the inferences people make about the biological and psychological bases of those behaviors. In five experiments, we manipulated whether behaviors are presented concretely (i.e. with reference to a specific person, instantiated in the particular context of that person's life) or abstractly (i.e. with reference to a category of people or behaviors across generalized contexts). People judged concretely framed behaviors to be less biologically based and, on some dimensions, more psychologically based than the same behaviors framed in the abstract. These findings held true for both mental disorders (Experiments 1 and 2) and everyday behaviors (Experiments 4 and 5), and yielded downstream consequences for the perceived efficacy of disorder treatments (Experiment 3). Implications for science educators, students of science, and members of the lay public are discussed.

The influence of framing on clinicians' judgments of the biological basis of behaviors.

Practicing clinicians frequently think about behaviors both abstractly (i.e., in terms of symptoms, as in the Diagnostic and Statistical Manual of Mental Disorders, 5th ed., DSM-5; American Psychiatric Association, 2013) and concretely (i.e., in terms of individual clients, as in DSM-5 Clinical Cases; Barnhill, 2013). Does abstract/concrete framing influence clinical judgments about behaviors? Practicing mental health clinicians (N = 74) were presented with hallmark symptoms of 6 disorders framed abstractly versus concretely, and provided ratings of their biological and psychological bases (Experiment 1) and the likely effectiveness of medication and psychotherapy in alleviating them (Experiment 2). Clinicians perceived behavioral symptoms in the abstract to be more biologically and less psychologically based than when concretely described, and medication was viewed as more effective for abstractly than concretely described symptoms. These findings suggest a possible basis for miscommunication and misalignment of views between primarily research-oriented and primarily practice-oriented clinicians; furthermore, clinicians may accept new neuroscience research more strongly in the abstract than for individual clients.

Understanding Lay Assessments of Alcohol Use Disorder: Need for Treatment and Associated Stigma.

AIMS: Three-quarters of people with an alcohol use disorder in the USA never receive treatment. Our understandings of who receives care are informed by sociological perspectives, theories and models, each of which discuss the role of lay people's understanding of illness. However, comparatively little work has been done to unpack the cognitive processes underlying lay assessment. In the context of the Framework Integrating Normative Influences on Stigma (FINIS), we aim to understand key factors guiding lay people's stigmatizing attitudes, perceptions and assessments of alcohol use disorder behaviors. METHODS: Lay people read a vignette depicting a male or female adult with a diagnosable alcohol use disorder, along with either a causal life-event explanation for the alcohol use disorder behaviors or no explanation. They then made judgments of the need for treatment, psychological abnormality and the stigma they felt toward the person depicted. RESULTS: Causal life-event explanations decreased lay judgments of the need for treatment, psychological abnormality and stigma. CONCLUSIONS: The results suggest that the availability of a causal life-event explanation may have a complex effect on lay judgments, decreasing the likelihood of recommending treatment for alcohol use disorders, yet simultaneously reducing stigmatizing perceptions (and presumably social distance).

Visual causal models enhance clinical explanations of treatments for generalized anxiety disorder.

A daily challenge in clinical practice is to adequately explain disorders and treatments to patients of varying levels of literacy in a time-limited situation. Drawing jointly upon research on causal reasoning and multimodal theory, the authors asked whether adding visual causal models to clinical explanations promotes patient learning. Participants were 86 people currently or formerly diagnosed with a mood disorder and 104 lay people in Boston, Massachusetts, USA, who were randomly assigned to receive either a visual causal model (dual-mode) presentation or auditory-only presentation of an explanation about generalized anxiety disorder and its treatment. Participants' knowledge was tested before, immediately after, and 4 weeks after the presentation. Patients and lay people learned significantly more from visual causal model presentations than from auditory-only presentations, and visual causal models were perceived to be helpful. Participants retained some information 4 weeks after the presentation, although the advantage of visual causal models did not persist in the long term. In conclusion, dual-mode presentations featuring visual causal models yield significant relative gains in patient comprehension immediately after the clinical session, at a time when the authors suggest that patients may be most willing to begin the recommended treatment plan.

How do practising clinicians and students apply newly learned causal information about mental disorders?

RATIONALE, AIMS AND OBJECTIVES: New causal theories explaining the aetiology of psychiatric disorders continuously appear in the literature. How might such new information directly impact clinical practice, to the degree that clinicians are aware of it and accept it? We investigated whether expert clinical psychologists and students use new causal information about psychiatric disorders according to rationalist norms in their diagnostic reasoning. Specifically, philosophical and Bayesian analyses suggest that it is rational to draw stronger inferences about the presence of a disorder when a client's presenting symptoms are from disparate locations in a causal theory of the disorder than when they are from proximal locations. METHOD: In a controlled experiment, we presented experienced clinical psychologists and students with recently published causal theories for different disorders; specifically, these theories proposed how the symptoms of each disorder stem from a root cause. Participants viewed hypothetical clients with presenting proximal or diverse symptoms, and indicated either the likelihood that the client has the disorder, or what additional information they would seek out to help inform a diagnostic decision. RESULTS: Clinicians and students alike showed a strong preference for diverse evidence, over proximal evidence, in making diagnostic judgments and in seeking additional information. They did not show this preference in the control condition, in which they gave their own opinions prior to learning the causal information. CONCLUSION: These findings suggest that experienced clinical psychologists and students are likely to use newly learned causal knowledge in a normative, rational way in diagnostic reasoning.

Do clinical psychologists extend the bereavement exclusion for major depression to other stressful life events?

BACKGROUND: In assessing potential cases of major depressive disorder (MDD), to what extent do clinicians interpret symptoms within the explanatory context of major life stressors? Past research suggests that when clinicians know a plausible life event cause for a person's disordered symptoms, they generally judge that person to be less abnormal than if the cause was unknown. However, the current, fourth edition of the Diagnostic and Statistical Manual of Mental Disorders specifies that only bereavement-related life events exclude a client from a diagnosis of MDD, and the upcoming fifth edition of the manual (DSM-V) is currently slated to eliminate this bereavement clause altogether. OBJECTIVE: To systematically examine whether clinicians' judgments reflect agreement with either of these formal DSM specifications. METHOD: In a controlled experiment, 72 practicing, licensed clinical psychologists made judgments about realistic MDD vignettes that included a bereavement event, stressful non-bereavement event, neutral event, or no event. RESULTS: Bonferroni-corrected paired comparisons revealed that both bereavement and non-bereavement life events led MDD symptoms to be rated as significantly less indicative of a depression diagnosis, less abnormal, less rare, and less culturally unacceptable (all P ≤ 0.001) relative to control conditions. LIMITATIONS: Clinicians made judgments of realistic, controlled vignettes rather than patients. CONCLUSIONS: The results suggest that practicing clinical psychologists assess symptoms within the explanatory context of bereavement and non-bereavement life stressors, indicating a departure from the DSM's recommendations, both current and proposed. IMPLICATIONS: for diagnostic decision making and the clinical utility of the DSM's recommendations are discussed.

Hindsight bias and causal reasoning: a minimalist approach.

What factors contribute to hindsight bias, the phenomenon whereby the known outcome of an event appears obvious only after the fact? The Causal Model Theory (CMT) of hindsight bias (Nestler et al. in Soc Psychol 39:182-188, 2008a; in J Expl Psychol: Learn Mem Cog 34:1043-1054, 2008b; Pezzo in Mem 11:421-441, 2003; Wasserman et al. in Pers Soc Psychol Bull 17:30-35, 1991) posits that hindsight bias can occur when people have the opportunity to identify potential causal antecedents and evaluate whether they could have led to the outcome. Two experiments incorporating highly controlled minimalist scenarios supported the CMT. As predicted by the CMT, hindsight bias occurred when the causal factor explained the actual outcome better than the alternative outcome, and reverse hindsight bias occurred when the causal factor explained the alternative outcome better than the actual outcome. Moreover, we found new evidence that outcome knowledge alone was insufficient to elicit hindsight bias in the absence of a potential causal antecedent. Implications for future directions in hindsight bias research are discussed.

Proportionate responses to life events influence clinicians' judgments of psychological abnormality.

Psychological abnormality is a fundamental concept in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000) and in all clinical evaluations. How do practicing clinical psychologists use the context of life events to judge the abnormality of a person's current behaviors? The appropriate role of life-event context in assessment has long been the subject of intense debate and scrutiny among clinical theorists, yet relatively little is known about clinicians' own judgments in practice. The authors propose a proportionate-response hypothesis, such that judgments of abnormality are influenced by whether the behaviors are a disproportionate response to past events, rendering them difficult to understand or explain. Licensed, practicing clinical psychologists (N = 77) were presented with vignettes describing hypothetical people's behaviors (disordered, mildly distressed, or unaffected) that had been preceded by either traumatic or mildly distressing events. Experts' judgments of abnormality were strongly and systematically influenced by the degree of mismatch between the past event and current behaviors in strength and valence, such that the greater the mismatch, the more abnormal the person seemed. A separate, additional group of clinical psychologists (N = 20) further confirmed that the greater the degree of mismatch, the greater the perceived difficulty in understanding the patient. These findings held true across clinicians of different theoretical orientations and in disorders for which these patterns of judgments ran contrary to formal recommendations in the DSM-IV-TR (American Psychiatric Association, 2000). The rationality of these effects and implications for clinical decision science are discussed.

Can personality disorder experts recognize DSM-IV personality disorders from five-factor model descriptions of patient cases?

BACKGROUND: Dimensional models of personality are under consideration for integration into the next Diagnostic and Statistical Manual of Mental Disorders (DSM-5), but the clinical utility of such models is unclear. OBJECTIVE: To test the ability of clinical researchers who specialize in personality disorders to diagnose personality disorders using dimensional assessments and to compare those researchers' ratings of clinical utility for a dimensional system versus for the DSM-IV. METHOD: A sample of 73 researchers who had each published at least 3 (median = 15) articles on personality disorders participated between December 2008 and January 2009. The Five-Factor Model (FFM), one of the most-studied dimensional models to date, was compared to the DSM-IV. Participants provided diagnoses for case profiles in DSM-IV and FFM formats and then rated the DSM-IV and FFM on 6 aspects of clinical utility. RESULTS: Overall, participants had difficulty identifying correct diagnoses from FFM profiles (t72 = 12.36, P < .01), and the same held true for a subset reporting equal familiarity with the DSM-IV and FFM (t23 = 6.96, P < .01). Participants rated the FFM as less clinically useful than the DSM for making prognoses, devising treatment plans, and communicating with professionals (all t69 > 2.19, all P < .05), but more useful for communicating with patients (t69 = 3.03, P < .01). CONCLUSIONS: The results suggest that personality disorder expertise and familiarity with the FFM are insufficient to correctly diagnose personality disorders using FFM profiles. Because of ambiguity inherent in FFM profile descriptors, this insufficiency may prove unlikely to be attenuated with increased clinical familiarity with the FFM.

The conceptual centrality of causal cycles.

How do causal cycles affect judgments of conceptual centrality? Generally, a feature is central to a concept to the extent that other features in the concept depend on it, thereby rendering it immutable from the concept (Sloman, Love, & Ahn, 1998). Previous research on conceptual centrality has focused primarily on features involved in four major types of dependency structures: simple cause-effect relations, causal chains, common-cause structures, and common-effect structures. Causal cycles are a fifth type of dependency structure commonly reported in people's real-life concepts, yet to date, they have been relatively ignored in research on conceptual centrality. The results of six experiments suggest that previously held assumptions about the conceptual representation of cycles are incorrect. We discuss the implications of these findings for our understanding of theory-based concepts.

Can clinicians recognize DSM-IV personality disorders from five-factor model descriptions of patient cases?

OBJECTIVE: This article examined, using theories from cognitive science, the clinical utility of the Five-Factor Model (FFM) of Personality, an assessment and classification system under consideration for integration into the forthcoming fifth edition of the Diagnostic and Statistical Manual (DSM) of Mental Disorders. Specifically, the authors sought to test whether FFM descriptors are specific enough to allow practicing clinicians to capture core features of personality disorders. METHOD: In two studies, a large nationwide sample of clinical psychologists, psychiatrists, and clinical social workers (N=187 and N=191) were presented case profiles based on symptom formats from either the DSM-IV and/or FFM. Ratings for six aspects of clinical utility for DSM-IV and FFM profiles were obtained and participants provided DSM-IV diagnoses. Prototypic cases (only one personality disorder) and comorbid cases were tested in separate studies. RESULTS: Participants rated the DSM-IV as more clinically useful than the FFM on five out of six clinical utility questions. Despite demonstrating considerable background knowledge of DSM-IV diagnoses, participants had difficulty identifying correct diagnoses from FFM profiles. CONCLUSION: The FFM descriptors may be more ambiguous than the criteria of the DSM-IV and the FFM may therefore be less able to convey important clinical details than the DSM-IV. The findings flag challenges to clinical utility for dimensional-trait systems such as the FFM.

ConceptBuilder: an open-source software tool for measuring, depicting, and quantifying causal models.

Measurements of people's causal and explanatory models are frequently key dependent variables in investigations of concepts and categories, lay theories, and health behaviors. A variety of challenges are inherent in the pen-and-paper and narrative methods commonly used to measure such causal models. We have attempted to alleviate these difficulties by developing a software tool, ConceptBuilder, for automating the process and ensuring accurate coding and quantification of the data. In this article, we present ConceptBuilder, a multiple-use tool for data gathering, data entry, and diagram display. We describe the program's controls, report the results of a usability test of the program, and discuss some technical aspects of the program. We also describe ConceptAnalysis, a companion program for generating data matrices and analyses, and ConceptViewer, a program for viewing the data exactly as drawn.

The influence of causal information on judgments of treatment efficacy.

How does the causal structure of a problem concept influence judgments of treatment efficacy? We argue that the task of evaluating treatment efficacy involves a combination of causal reasoning and categorization. After an exemplar has been categorized, a treatment task involves judging where to intervene in the causal structure to eradicate the problem, removing the exemplar from category membership. We hypothesized that the processes underlying such category membership removal tasks are not identical to those underlying categorization. Whereas previous experiments have shown that both the root cause (as the most generative feature) and the coherence of the exemplar heavily influence categorization, Experiments 1 and 2 showed that people base category membership removal judgments on the root cause. In Experiment 3, people spontaneously chose to remove an exemplar from category membership when asked to treat the terminal effect. We discuss how our findings are compatible with existing models of categorization. A description of pilot studies for Experiment 1 may be downloaded as supplemental materials from mc.psychonomic-journals.org.

Causal diversity effects in information seeking.

When trying to determine the root cause of an observed effect, people may seek out information with which to test a candidate hypothesis. In two studies, we investigated how knowledge of causal structure influences this information-seeking process. Specifically, we asked whether people would choose to test for pieces of evidence that were far apart or close together in the learned causal structure of a disease category. In parallel with findings showing people's tendency to select diverse evidence in argument testing (López, 1995), our participants tested for evidence distantly located within the causal structure. Simultaneously, they rated the probability of occurrence of such diverse evidence as comparatively low. These findings suggest that rather than seeking out information most likely to confirm the hypothesis, people seek out evidence that they believe will most strongly support the hypothesis if present but that they also believe is relatively unlikely to be present (that is, might disconfirm the hypothesis).

Understanding behavior makes it more normal.

Meehl (1973) has informally observed that clinicians will perceive a patient as being more normal if they can understand the patient's behaviors. In Experiment 1, undergraduate participants received descriptions of 10 people, each with three characteristics (e.g., frequently suffers from insomnia) taken from the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 1994). When the characteristics formed a plausible causal chain, adding a causal explanation increased perceived normality; but when a causal chain was implausible, perceived normality decreased. In Experiments 2 and 3, a negative life event (e.g., is very stressed out due to her workload) was added as an explanation for the first characteristic in a three-characteristic causal chain. Undergraduates, graduate students in clinical psychology, and expert clinicians all reliably perceived the patients as being more normal with these explanations than without them, confirming Meehl's prediction.

From symptoms to causes: diversity effects in diagnostic reasoning.

A single causal agent can often give rise to a cascade of consequences that can be envisioned as a branching pathway in which symptoms are the terminal nodes. In three studies, we investigated whether reasoning about root causes on the basis of such symptoms would conform to a diversity effect analogous to that found in inductive reasoning about properties of hierarchically organized categories. A strong diversity effect was found both for reasoning about medical diseases that drew on existing background knowledge and for reasoning that did not. Specifically, the presence of a root cause was more likely to be induced when the symptoms present were further apart in the branching structure.