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Tseng VWS, Tharp JA, Reiter JE, Ferrer W, Hong DS, Doraiswamy PM, Nickels S. Identifying a stable and generalizable factor structure of major depressive disorder across three large longitudinal cohorts. Psychiatry Res 2024; 333:115702. [PMID: 38219346 DOI: 10.1016/j.psychres.2023.115702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 12/21/2023] [Accepted: 12/26/2023] [Indexed: 01/16/2024]
Abstract
The Patient Health Questionnaire 9 (PHQ-9) is the current standard outpatient screening tool for measuring and tracking the nine symptoms of major depressive disorder (MDD). While the PHQ-9 was originally conceptualized as a unidimensional measure, it has become clear that MDD is not a monolithic construct, as evidenced by high comorbidities with other theoretically distinct diagnoses and common symptom overlap between depression and other diagnoses. Therefore, identifying reliable and temporally stable subfactors of depressive symptoms could allow research and care to be tailored to different depression phenotypes. This study improved on previous factor analysis studies of the PHQ-9 by leveraging samples that were clinical (participants with depression only), large (N = 1483 depressed individuals in total), longitudinal (up to 5 years), and from three diverse (matching racial distribution of the United States) datasets. By refraining from assuming the number of factors or item loadings a priori, and thus utilizing a solely data-driven approach, we identified a ranked list of best-fitting models, with the parsimonious one achieving good model fit across studies at most timepoints (average TLI >= 0.90). This model categorizes the PHQ-9 items into four factors: (1) Affective (Anhedonia + Depressed Mood), (2) Somatic (Sleep + Fatigue + Appetite), (3) Internalizing (Worth/Guilt + Suicidality), (4) Sensorimotor (Concentration + Psychomotor), which may be used to further precision psychiatry by testing factor-specific interventions in research and clinical settings.
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Affiliation(s)
- Vincent W S Tseng
- Verily Life Sciences LLC, 269 E Grand Ave, South San Francisco, CA, USA.
| | - Jordan A Tharp
- Verily Life Sciences LLC, 269 E Grand Ave, South San Francisco, CA, USA
| | - Jacob E Reiter
- Verily Life Sciences LLC, 269 E Grand Ave, South San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA, USA
| | - Weston Ferrer
- Verily Life Sciences LLC, 269 E Grand Ave, South San Francisco, CA, USA
| | - David S Hong
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA, USA
| | - P Murali Doraiswamy
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Stefanie Nickels
- Verily Life Sciences LLC, 269 E Grand Ave, South San Francisco, CA, USA
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