A novel approach to investigate depression symptoms in the aging population using generalizability theory.


Journal

Psychological assessment
ISSN: 1939-134X
Titre abrégé: Psychol Assess
Pays: United States
ID NLM: 8915253

Informations de publication

Date de publication:
Jul 2022
Historique:
pubmed: 1 4 2022
medline: 7 7 2022
entrez: 31 3 2022
Statut: ppublish

Résumé

As depression is common in older people and confers significant risk for dementia, its accurate assessment is essential. The 15-item Geriatric Depression Scale (GDS-15) is a widely used assessment tool for measuring depression in aged populations, and its psychometric properties have been recently improved using Rasch analysis. However, its temporal reliability and ability to distinguish between dynamic and enduring symptoms of depression have not been examined using the appropriate methodology. Generalizability theory (G theory) is a suitable method to distinguish between enduring and dynamic symptoms of depression and to evaluate the reliability of the GDS-15 scores and sources of measurement error. We applied G theory to the longitudinal GDS-15 data of 354 participants from the Sydney Memory and Ageing Study, collected biennially over 10 years, from individuals aged 70 years and older. The GDS-15 demonstrated strong reliability and generalizability of its test scores in measuring enduring symptoms of depression (

Identifiants

pubmed: 35357876
pii: 2022-48959-001
doi: 10.1037/pas0001129
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

684-696

Subventions

Organisme : National Health and Medical Research Council

Auteurs

Sruthy S Kumar (SS)

School of Psychology.

Alexander G Merkin (AG)

National Institute for Stroke and Applied Neurosciences.

Katya Numbers (K)

Faculty of Medicine and Health.

Henry Brodaty (H)

Faculty of Medicine and Health.

Nicole A Kochan (NA)

Faculty of Medicine and Health.

Julian N Trollor (JN)

Faculty of Medicine and Health.

Susan Mahon (S)

National Institute for Stroke and Applied Neurosciences.

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Classifications MeSH