A comparison of the predictive abilities of dimensional and categorical models of unipolar depression in the National Comorbidity Survey

Abstract

Taxometric research on depression has yielded mixed results, with some studies supporting dimensional solutions and others supporting taxonic solutions. Although supplementary tests of construct validity might clarify these mixed findings, to date such analyses have not been reported. The present study represents a follow-up to our previous taxometric study of depression designed to evaluate the relative predictive validities of dimensional and categorical models of depression. Two sets of dimensional and categorical models of depression were constructed from the depression items of the Composite International Diagnostic Interview: (1) empirically derived models obtained using latent structure analyses and (2) rationally selected models, including an additive depressive symptoms scale (dimensional) and DSM major depressive episodes (categorical). Both sets of dimensional and categorical models were compared in terms of their abilities to predict various clinically relevant outcomes (psychiatric diagnoses and impairment). Factor analyses suggested a two-factor model ('cognitive-affective' and 'somatic' symptoms) and latent class analyses suggested a three-class model ('severe depression', 'moderate depression' and 'cognitive-affective distress'). In predictive analyses that simultaneously included dimensional and categorical models as predictors, the dimensional models remained significant unique predictors of outcomes while the categorical models did not. Both dimensional models provided superior predictive validity relative to their categorical counterparts. These results provide construct validity evidence for the dimensional findings from our previous taxometric study and thus inspire confidence in dimensional conceptualizations of depression. It remains for future research to evaluate the construct validity of the taxonic solutions reported in the literature.