On top or underneath: Where does the general factor of psychopathology fit within a dimensional model of psychopathology?

Philip Hyland, Jamie Murphy, Mark Shevlin, Richard P. Bentall, Thanos Karatzias, Grace W.K. Ho, Daniel Boduszek, Eoin McElroy

Research output: Contribution to journalArticle

Abstract

Background: Dimensional models of psychopathology are increasingly common, and there is evidence for the existence of a general dimension of psychopathology (‘p’). The existing literature presented two ways to model p: as a bifactor or as a higher-order dimension. Bifactor models typically fit sample data better than higher-order models, and are often selected as better fitting alternatives but there are reasons to be cautious of such an approach to model selection. In this study, the bifactor and higher-order models of p were compared in relation to associations with established risk variables for mental illness.

Methods: A trauma-exposed community sample from the United Kingdom (N = 1,051) completed self-report measures of 49 symptoms of psychopathology.

Results: A higher-order model with four first-order dimensions (Fear, Distress, Externalizing, and Thought Disorder) and a higher-order p dimension provided satisfactory model fit, and a bifactor representation provided superior model fit. Bifactor p and higher-order p were highly correlated (r = .97) indicating that both parametrizations produce near equivalent general dimensions of psychopathology. Latent variable models including predictor variables showed that the risk variables explained more variance in higher-order p than bifactor p. The higher-order model produced more interpretable associations for the first-order/specific dimensions compared to the bifactor model.

Conclusions: The higher-order representation of p, as described in the Hierarchical Taxonomy of Psychopathology, appears to be a more appropriate way to conceptualise the general dimension of psychopathology than the bifactor approach. The research and clinical implications of these discrepant ways of modelling p are discussed.
Original languageEnglish
JournalPsychological Medicine
Early online date23 Apr 2020
DOIs
Publication statusE-pub ahead of print - 23 Apr 2020

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