Meta-analysis of structural evidence for the Hierarchical Taxonomy of Psychopathology (HiTOP) model

Background: The Hierarchical Taxonomy of Psychopathology (HiTOP) is a classification system that seeks to organize psychopathology using quantitative evidence—yet the current model was established by narrative review. This meta-analysis provides a quantitative synthesis of literature on transdiagnostic dimensions of psychopathology to evaluate the validity of the HiTOP framework. Methods: Published studies estimating factor-analytic models from DSM diagnoses were screened. A total of 120,596 participants from 35 studies assessing twenty-three DSM diagnoses were included in the meta-analytic models. Data were pooled into a meta-analytic correlation matrix using a random effects model. Exploratory factor analyses were conducted using the pooled correlation matrix. A hierarchical structure was estimated by extracting one to five factors representing levels of the HiTOP framework, then calculating congruence coefficients between factors at sequential levels. Results: Five transdiagnostic dimensions fit the DSM diagnoses well (comparative fit index [CFI] = .92, root mean square-error of approximation [RMSEA] = .07, and standardized root-mean-square residual [SRMR] = .03). Most diagnoses had factor loadings > |.30| on the expected factors, and congruence coefficients between factors indicated a hierarchical structure consistent with the HiTOP framework. Conclusions: A model closely resembling the HiTOP framework fit the data well and placement of DSM diagnoses within transdiagnostic dimensions were largely confirmed, supporting it as valid structure for conceptualizing and organizing psychopathology. Results also suggest transdiagnostic research should 1) use traits, narrow symptoms, and dimensional measures of psychopathology instead of DSM diagnoses, 2) assess a broader array of constructs, and 3) increase focus on understudied pathologies.