Regression-based normative data for social health scale for the elderly (short version) in eastern China

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Abstract

Backgrounds: Social Health Scale for the Elderly short version (SHSE-S) is a psychometrically sound instrument that comprehensively assesses the social health status of older adults in China. The aim of the present study was to establish continuous normative data of SHSE-S. Methods: We conducted a multicenter cross-sectional study among 31 communities in eastern China. Older adults aged 60 years and above were invited to participate in the study. Each participant was interviewed in-person to finish a structured questionnaire. The SHES-S score was calculated and standardized for each participant. We split the sample into generation and validation datasets and compared the distribution of SHSE-S score between two datasets. Multivariable linear regression was used to assess the SHSE-S score and demographic variables. Regression-based norms were built using a four-step process. Results: A total of 6089 participants (51.2% females) aged 60 years old and above (mean age = 71.3, SD = 8.0) were enrolled as the normative sample. No significant difference was found between the distribution of SHSE-S standardized score in the generation (N = 2392) and validation (N = 3697) datasets. Multivariable linear regression showed that females, higher education levels were positive indicators while aging, living alone, divorced or never married, multimorbidity were negative factors. The regression-based norm which taking demographic factors into account was established and a user-friendly worksheet was also provided to facilitate the scoring and norming of the SHSE-S. Conclusions: The population-based regression norm of SHSE-S can be a useful tool for assessing the social health status of the Chinese elderly population.

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Yu, Z. B., Bao, C. Z., Wu, M. Y., Jiang, D. J., Zhang, X. C., Lin, S. J., … Chen, K. (2020). Regression-based normative data for social health scale for the elderly (short version) in eastern China. Health and Quality of Life Outcomes, 18(1). https://doi.org/10.1186/s12955-020-01306-2

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