Depression prevalence of the Geriatric Depression Scale-15 was compared to Structured Clinical Interview for DSM using individual participant data meta-analysis.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
29 Jul 2024
29 Jul 2024
Historique:
received:
21
01
2024
accepted:
24
07
2024
medline:
30
7
2024
pubmed:
30
7
2024
entrez:
29
7
2024
Statut:
epublish
Résumé
Depression questionnaire cutoffs are calibrated for screening accuracy and not to assess prevalence, but the Geriatric Depression Scale (GDS-15) is often used to estimate diagnostic prevalence among older adults, most commonly with scores of ≥ 5. We conducted an individual participant data meta-analysis to compare depression prevalence based on GDS-15 ≥ 5 to Structured Clinical Interview for Diagnostic and Statistical Manual (SCID) diagnoses and assessed whether an alternative cutoff could be more accurate. We used generalized linear mixed models to estimate prevalence. Data from 14 studies (3602 participants, 434 SCID major depression) were included. Pooled GDS-15 ≥ 5 prevalence was 34.2% (95% confidence interval [CI] 27.5-41.6%), and pooled SCID prevalence was 14.8% (95% CI 10.0-21.5%; difference of 17.6%, 95% CI 11.6-23.6%). GDS-15 ≥ 8 provided the closest estimate to SCID with mean difference of - 0.3% (95% prediction interval - 17.0-16.5%). Prevalence estimate differences were not associated with study or participant characteristics. In sum, GDS-15 ≥ 5 substantially overestimated depression prevalence. A cutoff of ≥ 8 was accurate overall, but heterogeneity was too high for implementation in practice. Validated diagnostic interviews should be used to estimate major depression prevalence among older adults.
Identifiants
pubmed: 39075146
doi: 10.1038/s41598-024-68496-3
pii: 10.1038/s41598-024-68496-3
doi:
Types de publication
Journal Article
Meta-Analysis
Comparative Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
17430Subventions
Organisme : CIHR
ID : PJT-156365
Pays : Canada
Organisme : CIHR
ID : PJT-156365
Pays : Canada
Investigateurs
Ankur Krishnan
(A)
Chen He
(C)
Tiffany Dal Santo
(TD)
Dipika Neupane
(D)
Nadia González Domínguez
(NG)
Eliana Brehaut
(E)
Parash M Bhandari
(PM)
Xia Qiu
(X)
Letong Li
(L)
Mahrukh Imran
(M)
Elsa-Lynn Nassar
(EL)
John P A Ioannidis
(JPA)
Antje-Kathrin Allgaier
(AK)
Marcos H N Chagas
(MHN)
Ahmet Turan Isik
(AT)
Nathalie Jetté
(N)
Hans-Helmut König
(HH)
Margrit Löbner
(M)
Laura Marsh
(L)
Ioannis Michopoulos
(I)
Antonis A Mougias
(AA)
Christian J Nelson
(CJ)
Alexander Pabst
(A)
Terence J Quinn
(TJ)
Steffi G Riedel-Heller
(SG)
Rebecca Saracino
(R)
Martin Scherer
(M)
Martin Taylor-Rowan
(M)
Matthias Volz
(M)
Katja Werheid
(K)
Siegfried B Weyerer
(SB)
Informations de copyright
© 2024. The Author(s).
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