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Center for Excellence in Assisted Living

Center for Excellence in Assisted Living CEAL@UNC

Advancing the well-being of the people who live and work in assisted living through research, practice, and policy.

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Psychometric Evaluation of the Nursing Homes Short Depression Inventory (NH-SDI) Across Long-Term Care Facilities in Lebanon

Date: July 2025Topics: Mental HealthType: Academic PublicationPublication: BMC PsychiatryAuthors: Mohsen, H., Abbas, L. A., Calvet, B., & Salameh, P.
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Background: The Nursing Homes Short Depression Inventory (NH-SDI) is an observer-reported measure used to identify depressive symptoms in older adults living in nursing homes. This study aimed to test the psychometric properties of the NH-SDI (Arabic version) in long-term care facilities (LTCF).

Methods: The NH-SDI was translated to Arabic, assessed by a panel of experts, and pilot-tested. Data were collected from 21 nursing homes and assisted-living centers over a period of 9 months in 2022. The psychometric properties of the 16-item scale were examined via principal component analysis (PCA), confirmatory factor analysis (CFA), receiver operating characteristic (ROC), Cronbach’s α, and intraclass correlation coefficient (ICC).

Results: A total of 245 individuals, ranging in age from 65 to 100 years, were included in the study. The mean age of participants was 77.8 ± 8.4 years and the prevalence of depression was 31.8%, based on physicians’ diagnosis. The PCA produced a four-factor model, accounting for 63.3% of the overall variance. A good model fit in CFA was achieved for a 13-item model (χ2/df = 1.95, RMSEA = 0.07, GFI = 0.91, AGFI = 0.89, CFI = 0.90, NFI = 0.86, and TLI = 0.89). A positive correlation was found between NH-SDI and WHO-5 Well-being Index (r = 0.46, p < 0.001). The cut-off point was 3.5 (area under the curve = 0.83, sensitivity = 88.5%, specificity = 69.5%). The Cronbach’s α and ICC achieved good values (0.83 and 0.93, respectively).

Conclusion: The Arabic version of the NH-SDI (13 items) is valid and reliable for detecting depressive symptoms among elderly residents in Lebanon.

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