ABSTRACT
Mental disorders are among the leading causes of global disease burden. To respond effectively, a strong understanding of the structure of psychopathology is critical. We empirically compared two competing frameworks, dynamic-mutualism theory and common-cause theory, that vie to explain the development of psychopathology. We formalized these theories in statistical models and applied them to explain change in the general factor of psychopathology (p factor) from early to late adolescence (N = 1,482) and major depression in middle adulthood and old age (N = 6,443). Change in the p factor was better explained by mutualism according to model-fit indices. However, a core prediction of mutualism was not supported (i.e., predominantly positive causal interactions among distinct domains). The evidence for change in depression was more ambiguous. Our results support a multicausal approach to understanding psychopathology and showcase the value of translating theories into testable statistical models for understanding developmental processes in clinical sciences.
ABSTRACT
One of the most discussed recent topics in psychopathology research is the p factor of mental illness. This single dimension is understood to measure "a person's liability to mental disorder, comorbidity among disorders, persistence of disorders over time, and severity of symptoms."1 A recent paper by Constantinou et al.2 published in the Journal investigated the external validity of the p factor. We commend the authors for the contribution to the literature and want to highlight two points: (1) the interpretation of p as a causal entity, and (2) selection of bifactor models over alternative models for reasons of superior fit.
