How Robust Is the p Factor? Using Multitrait-Multimethod Modeling to Inform the Meaning of General Factors of Youth Psychopathology. (July 2022)

• Record Type: Journal Article
• Authors: Watts, Ashley L.; Makol, Bridget A.; Palumbo, Isabella M.; De Los Reyes, Andres; Olino, Thomas M.; Latzman, Robert D.; DeYoung, Colin G.; Wood, Phillip K.; Sher, Kenneth J.
• Is Part Of: Clinical psychological science. Volume 10:Number 4(2022)
• Page Start: 640
• Page End: 661
• Publication Date: 2022-07
• Subjects: p factor -- general factor of psychopathology -- multitrait-multimethod modeling -- multi-informant psychopathology structures; Clinical psychology -- Periodicals; 616.89
• DOI: 10.1177/21677026211055170
• Languages: English
• ISSNs: 2167-7026

Abstract

We used multitrait-multimethod (MTMM) modeling to examine general factors of psychopathology in three samples of youths ( N s = 2, 119, 303, and 592) for whom three informants reported on the youth's psychopathology (e.g., child, parent, teacher). Empirical support for the p -factor diminished in multi-informant models compared with mono-informant models: The correlation between externalizing and internalizing factors decreased, and the general factor in bifactor models essentially reflected externalizing. Widely used MTMM-informed approaches for modeling multi-informant data cannot distinguish between competing interpretations of the patterns of effects we observed, including that the p factor reflects, in part, evaluative consistency bias or that psychopathology manifests differently across contexts (e.g., home vs. school). Ultimately, support for the p factor may be stronger in mono-informant designs, although it does not entirely vanish in multi-informant models. Instead, the general factor of psychopathology in any given mono-informant model likely reflects a complex mix of variances, some substantive and some methodological.