Examining the Hierarchical Taxonomy of Psychopathology in a Nationally Representative Epidemiological Sample with a Quantitative Intersectional Approach

The Hierarchical Taxonomy of Psychopathology (HiTOP) framework addresses psychometric limitations posed by categorical models of psychopathology in empirically modeling the dimensional structure of psychopathology. As the empirical basis of the framework relied on samples with underrepresentation of minoritized identities, it is important to examine the degree to which the hierarchical dimensional model of psychopathology proposed by the framework remains applicable across intersections of identities in diverse samples. To this aim, the present study examined the extent to which demographic covariates and their interactions moderate parameters of structural models as assessed with 30-day, 12-month, and lifetime DSM- IV-TR diagnostic data available in the Collaborative Psychiatric Epidemiological Studies dataset. The dimensional factor structure of psychopathology assessed with 30-day, 12-month, and lifetime diagnostic data via conducting extended bass-ackward exploratory factor analyses were consistent with the structural framework of internalizing and externalizing spectra proposed by the HiTOP framework. Additionally, results of moderated nonlinear factor analysis (MNLFA) demonstrated significant intercept and loading DIF as well as main and interaction effects of demographic covariates on factor means in the final scoring model. Implications for generalizability of dimensional structural models of psychopathology are discussed in addition to limitations of the current study and future directions.