Lay beliefs about the causes and treatment of depression: Tests of measurement models and associations.

Background: There is reason to expect beliefs about depression's causes and treatment to influence use of psychotherapy, but the literature is marked by theoretical, methodological, and empirical inconsistencies. This study assessed the factorial validity of measures of beliefs about depression's causes and formal treatment versus self-management. It also tested the links of causal attributions to general treatment/self-management beliefs and endorsement of specific interventions.

Methods: The revised Illness Perception Questionnaire (IPQ-R) adapted for depression was administered online to a non-patient, U.S. sample (N = 319).

Results: Confirmatory factor analyses yielded three causal dimensions, Environmental Stressors, Biological Factors, and Personal Attributes, and two control dimensions, (Formal) Treatment and Personal. Both models fit irrespective of whether respondents believed they had ever experienced depression. A structural equation model (SEM) showed a positive relationship for Environmental and Biological attributions, and an inverse relationship for Personal attributions, in predicting general preferences for Formal Treatment. A second SEM, focusing on specific interventions, linked Environmental causation to endorsement of psychotherapy, dietary changes, and self-help, and Biological causation to endorsement of medication and exercise, with Personal causation inversely associated with endorsement of psychotherapy.

Limitations: A cross-sectional, correlational design precludes causal inferences. Potential sociocultural influences were not assessed.

Conclusions: Modifications to the IPQ-R suggested by this study improved its psychometric properties, validated its distinction between Treatment and Personal Control beliefs, and supported examination of both general and specific beliefs about ways to deal with depression. Relationships linking cause and treatment beliefs warrant further investigation as potential intervention targets to increase treatment utilization.