Positive affect improves a transdiagnostic model of perinatal depression symptoms

Blaire C. Pingeton, Amy Cochran, Sherryl H. Goodman, Heidemarie Laurent, Marissa D. Sbrilli, Bettina Knight, D. Jeffrey Newport, Zachary N. Stowe

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Introduction: Accurate measurement of perinatal depression is vital. We aimed to 1) test whether a factor that measured positive affect (PA) bettered a transdiagnostic model of depression symptoms and 2) replicate the model in a second sample. Methods: We conducted secondary analyses from two samples (n's = 657 and 142) of women in treatment at perinatal psychiatric clinics. Data were derived from items from seven commonly used measures. We compared fit indices from our original factor model—one general and six specific factors derived from the Research Domain Criteria (Loss, Potential Threat, Frustrative Nonreward, and Sleep-Wakefulness) and depression literatures (Somatic and Coping)—to our novel factor model with a PA factor. The PA factor was created by recategorizing items that measured affective states with a positive valence into a new factor. Sample 1 data were split into six perinatal periods. Results: In both samples, the addition of a PA factor improved model fit. At least partial metric invariance was found between perinatal periods, with the exception of trimester 3 – postpartum period 1. Limitations: Our measures did not operationalize PA in the same way as in the positive valence system in RDoC and we were unable to perform longitudinal analyses on our cross-validation sample. Conclusions: Clinicians and researchers are encouraged to consider these findings as a template for understanding symptoms of depression in perinatal patients, which can be used to guide treatment planning and the development of more effective screening, prevention, and intervention tools to prevent deleterious outcomes.

Original languageEnglish (US)
Pages (from-to)112-119
Number of pages8
JournalJournal of Affective Disorders
Volume336
DOIs
StatePublished - Sep 1 2023

All Science Journal Classification (ASJC) codes

  • Clinical Psychology
  • Psychiatry and Mental health

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