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Establishing score equivalence of the GDS-30 scale and International Classification of Functioning, Disability and Health range, using Rasch analysis

Depression is a common problem among older adults. The Geriatric Depression Scale (GDS- 30) is a recommended tool for assessing the emotional state of the elderly. To-date, there are no data in literature on the description of GDS-30, according to the International Classification of Functioning, Dis...

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Bibliographic Details
Published in:Annals of Agricultural and Environmental Medicine 2023-03, Vol.30 (1), p.105-110
Main Authors: Sozański, Bernard, Ćwirlej-Sozańska, Agnieszka Beata, Wilmowska-Pietruszyńska, Anna, Spalek, Renata, de Sire, Alessandro, Wiśniowska-Szurlej, Agnieszka
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Language:English
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Summary:Depression is a common problem among older adults. The Geriatric Depression Scale (GDS- 30) is a recommended tool for assessing the emotional state of the elderly. To-date, there are no data in literature on the description of GDS-30, according to the International Classification of Functioning, Disability and Health (ICF). The aim of the study is to transform the data obtained using the GDS-30 scale into the common scale of the ICF by applying the Rasch measurement theory. The study was conducted based on the results of 775 measurements made on people aged 65 and over. The Rasch model with the unconstrained Rasch parameter was used for the study. The GDS-30 scale was transformed into the ICF scale, where 0 points on the ICF scale were assigned to 0 points on the GDS-30 scale, 1 on the ICF scale - 1-4 points on the GDS-30 scale, 2 on the ICF scale - 5-7 on the GDS-30, 3 on the ICF scale, and 8-19 points on the GDS-30, whereas 4 on the ICF scale, 20-30 points on the GDS-30. Taken together, the results showed that the GDS-30 scale can be reliably transferred to the universal ICF scale for the b152 Emotional functions code. The ability to transfer the results into the universal language of the ICF category provides a coding system for more efficient information management in health systems, allows for data aggregation, and offers the possibility to compare them. It is also invaluable for clinical practice and research, including creating meta-analyses.
ISSN:1232-1966
1898-2263
DOI:10.26444/aaem/156021