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.

Details

Title
Regression-based normative data for social health scale for the elderly (short version) in eastern China
Author
Zhe-Bin Yu; Cheng-Zhen, Bao; Meng-Yin, Wu; Dan-Jie Jiang; Xiao-Cong, Zhang; Shu-Juan, Lin; Ming-Juan, Jin; Jian-Bing, Wang; Meng-Ling, Tang; Chen, Kun
Pages
1-9
Section
Research
Publication year
2020
Publication date
2020
Publisher
BioMed Central
e-ISSN
14777525
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2379226968
Copyright
© 2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.