The hierarchical structure of common mental disorders: Connecting multiple levels of comorbidity, bifactor models, and predictive validity.

Abstract

Studies of mental disorder comorbidity have produced an unsynthesized literature with multiple competing transdiagnostic models. The current study attempted to (a) integrate these models into an overarching comorbidity hierarchy, (b) link the resulting transdiagnostic factors to the bifactor model of psychopathology, and (c) investigate predictive validity of transdiagnostic factors for important future outcomes. A series of exploratory structural equation models (ESEMs) was conducted on 12 common mental disorders from a large, 2-wave nationally representative sample, using the bass-ackwards method to explore the hierarchical structure of transdiagnostic comorbidity factors. These Wave 1 factors were then linked with the bifactor model and with mental disorders at Wave 2. Results indicated that common mental disorder comorbidity was structured into an interpretable hierarchy. Connections between the hierarchy's general factor of psychopathology (denoted p), internalizing, and distress were very strong; these factors also linked strongly with the bifactor model's p factor. Predictive validity analyses prospectively predicting subsequent diagnoses indicated that, overall: (a) transdiagnostic factors outperformed disorder-specific variance; (b) within hierarchy levels, transdiagnostic factors where disorders optimally loaded outperformed other transdiagnostic factors, but this differed by disorder type; and (c) between hierarchy levels, transdiagnostic factors where disorders optimally loaded showed similar predictive validity. We discuss implications for hierarchical structure modeling, the integration of multiple competing comorbidity models, and benefits of transdiagnostic factors for understanding the continuity of mental disorders over time.