Objective: To determine whether the four-factor category-based obsessive-compulsive disorder (OCD) symptom structure from a previous confirmatory factor analysis (CFA) may be appropriately used in child, adolescent, and adult groups. Symptom dimensions are increasingly used as quantitative traits in genetic, neuroimaging, and treatment studies of OCD across all ages. Identification of a category-based OCD symptom dimension structure that is validated for use across child, adolescent, and adult age groups is necessary to guide ongoing translational research.
Method: Four OCD samples comprising 356 individuals were divided into child, adolescent, and adult groups. The fit of the only CFA-defined four-factor model was compared across these independent age group samples. Multiple-group CFA using maximum likelihood estimation assessed adequacy of fit comparing unconstrained and measurement weight-constrained models. The fit of previous exploratory factor analysis-defined three- and five-factor models on adults was also examined using CFA.
Results: A four-factor solution provided adequate but imperfect fit across age groups, with comparable indices to the only previous OCD CFA: factor 1 (aggressive/sexual/religious/somatic/checking); factor 2 (symmetry/ordering/counting/repeating); factor 3 (contamination/cleaning), and factor 4 (hoarding). Models in which factor loadings were constrained and unconstrained across the three age groups yielded comparable model fit. Factors were highly correlated and were not mutually exclusive. The four-factor solution provided an improved fit to both three- and five-factor solutions using CFA across the three age groups.
Conclusions: A four-factor, CFA-defined, category-based model of OCD symptom dimensions is adequate for use in children, adolescents, and adult age groups. The factor structure of this multiple age group sample has limitations and is imperfect, but current findings support the comparability of the defined latent OCD dimensions across age groups. Further work is needed to optimize a comprehensive symptom dimension model reflecting clinical heterogeneity for use in emergent translational studies.