Clinicians' Personal Theories of Developmental Disorders Explain Their Judgments of Effectiveness of Interventions.

Evidence-based psychotherapy requires clinicians to consider theories of psychopathology and evidence about effectiveness, and their experience when choosing interventions. Research on clinical decision making indicates that clinicians' theories of disorders might be personal and inform judgments and choices beyond current scientific theory and evidence. We asked 20 child therapists to draw models of how they believed that biological, psychological, environmental, and behavioral factors interact to cause and maintain four common developmental disorders. They were also asked to judge the effectiveness of interventions recommended in the literature. Therapists showed only fair agreement about the factors and a slight to fair agreement about the causal relations between these, and just fair agreement about interventions' effectiveness. Despite these disagreements, we could predict effectiveness judgments from therapists' personal theories, which indicates that clinicians use personal theories in decision making. We discuss the implications of these findings for evidence-based practice.

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.

Causal client models in selecting effective interventions: a cognitive mapping study.

An important reason to choose an intervention to treat psychological problems of clients is the expectation that the intervention will be effective in alleviating the problems. The authors investigated whether clinicians base their ratings of the effectiveness of interventions on models that they construct representing the factors causing and maintaining a client's problems. Forty clinical child psychologists drew causal models and rank ordered interventions according to their expected effectiveness for 2 cases. The authors found that different clinicians constructed different causal models for the same client. Also, the authors found low to moderate agreement about the effectiveness of different interventions. Nevertheless, the authors could predict clinicians' ratings of effectiveness from their individual causal models.

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).