Integrating Causal Analysis into Psychopathology Research

Abstract

Both in psychopathology research and in clinical practice, causal thinking is natural and productive. In the past decades, important progress has been made in the treatment of disorders ranging from attention-deficit/hyperactivity disorder (e.g., Connor, Glatt, Lopez, Jackson, & Melloni, 2002) to depression (e.g., Dobson, 1989; Hansen, Gartlehner, Lohr, Gaynes, & Carey, 2005) to schizophrenia (Hegarty, Baldessarini, Tohen, & Waternaux, 1994). The treatments for these disorders include pharmacological agents as well as behavioral interventions, which have been subjected to clinical trials and other empirical evaluations. Often, the treatments focus on the reduction or elimination of symptoms, but in other cases the interventions are designed to prevent the disorder itself (Brotman et al., 2008). In both instances, the interventions illustrate the best use of causal thinking to advance both scientific theory and clinical practice. When clinicians understand the causal nature of treatments, they can have confidence that their actions will lead to positive outcomes. Moreover, being able to communicate this confidence tends to increase a patient’s comfort and compliance (Becker & Maiman, 1975). Indeed, there seems to be a basic inclination for humans to engage in causal explanation, and such explanations affect both basic thinking, such as identification of categories (Rehder & Kim, 2006), and emotional functioning (Hareli & Hess, 2008). This inclination may lead some to ascribe causal explanations to mere correlations or coincidences, and many scientific texts warn researchers to be cautious about making causal claims (e.g., Maxwell & Delaney, 2004). These warnings have been taken to heart by editors, reviewers, and scientists themselves; and there is often reluctance regarding the use of causal language in the psychopathology literature. As a result, many articles simply report patterns of association and refer to mechanisms with euphemisms that imply causal thinking without addressing causal issues head-on. Over 35 years ago Rubin (1974) began to talk about strong causal inferences that could be made from experimental and nonexperimental studies using the so-called potential outcomes approach. This approach clarified the nature of the effects of causes A vs. B by asking us to consider what would happen to a given subject under these two conditions.