Depression prevalence based on the Edinburgh Postnatal Depression Scale compared to Structured Clinical Interview for DSM DIsorders classification: systematic review and individual participant data meta‐analysis

Objectives: Estimates of depression prevalence in pregnancy and postpartum are based on the Edinburgh Postnatal Depression Scale (EPDS) more than on any other method. We aimed to determine if any EPDS cutoff can accurately and consistently estimate depression prevalence in individual studies. Method...

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Veröffentlicht in:International journal of methods in psychiatric research 2021-03, Vol.30 (1), p.1-13, Article 1860
Hauptverfasser: Lyubenova, Anita, Neupane, Dipika, Levis, Brooke, Wu, Yin, Sun, Ying, He, Chen, Krishnan, Ankur, Bhandari, Parash M, Figueiredo, Bárbara, Tendais, Iva Alexandra Barbosa
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Zusammenfassung:Objectives: Estimates of depression prevalence in pregnancy and postpartum are based on the Edinburgh Postnatal Depression Scale (EPDS) more than on any other method. We aimed to determine if any EPDS cutoff can accurately and consistently estimate depression prevalence in individual studies. Methods: We analyzed datasets that compared EPDS scores to Structured Clinical Interview for DSM (SCID) major depression status. Random‐effects meta‐analysis was used to compare prevalence with EPDS cutoffs versus the SCID. Results: Seven thousand three hundred and fifteen participants (1017 SCID major depression) from 29 primary studies were included. For EPDS cutoffs used to estimate prevalence in recent studies (≥9 to ≥14), pooled prevalence estimates ranged from 27.8% (95% CI: 22.0%–34.5%) for EPDS ≥ 9 to 9.0% (95% CI: 6.8%–11.9%) for EPDS ≥ 14; pooled SCID major depression prevalence was 9.0% (95% CI: 6.5%–12.3%). EPDS ≥14 provided pooled prevalence closest to SCID‐based prevalence but differed from SCID prevalence in individual studies by a mean absolute difference of 5.1% (95% prediction interval: 13.7%, 12.3%). Conclusion: EPDS ≥14 approximated SCID‐based prevalence overall, but considerable heterogeneity in individual studies is a barrier to using it for prevalence estimation. This study was funded by the Canadian Institutes of Health Research (CIHR, KRS‐140994). Ms. Lyubenova was supported by the Mitacs Globalink Research Internship Program. Ms. Neupane was supported by G.R. Caverhill Fellowship from the Faculty of Medicine, McGill University. Drs. Levis and Wu were supported by Fonds de recherche du Québec‐Santé (FRQS) Postdoctoral Training Fellowships. Mr. Bhandari was supported by a studentship from the Research Institute of the McGill University Health Centre. Ms. Rice was supported by a Vanier Canada Graduate Scholarship. Ms. Azar was supported by a FRQS Masters Training Award. The primary study by Barnes et al. was supported by a grant from the Health Foundation (1665/608). The primary study by Beck et al. was supported by the Patrick and Catherine Weldon Donaghue Medical Research Foundation and the University of Connecticut Research Foundation. The primary study by Helle et al. was supported by the Werner Otto Foundation, the Kroschke Foundation, and the Feindt Foundation. Prof. Robertas Bunevicius, MD, PhD (1958‐2016) was Principal Investigator of the primary study by Bunevicius et al., but passed away and was unable to participate in this project. T
ISSN:1049-8931
1557-0657
1557-0657
DOI:10.1002/mpr.1860