BMC Geriatrics (Apr 2022)

Association between using social media WeChat and depressive symptoms among middle-aged and older people: findings from a national survey

  • Xing Qu,
  • Shannon H. Houser,
  • Jian Zhang,
  • Jin Wen,
  • Wei Zhang

DOI
https://doi.org/10.1186/s12877-022-03054-y
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 10

Abstract

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Abstract Objectives We aimed to assess the characteristics and health status of a study sample using social media WeChat and to identify the association between social media usage and depressive symptoms among people aged 45 and older in China. Methods Data were drawn from the China Health and Retirement Longitudinal Study (CHARLS). Depressive symptoms were measured by the 10-item form of the Center for Epidemiologic Studies Depression Scale (CES-D-10). The propensity score matching method (PSM) was performed to balance the characteristics of WeChat users and non-WeChat users. Multilevel logistic regression was used to test the association between the incidence of depressive symptoms and WeChat usage by introducing covariates step by step. Sensitivity analysis was conducted to estimate the robustness of the primary findings. Results A total of 5415 matching cases out of 11,338 total sample were used in this study to generate the final analysis. A multilevel logistic regression model showed that a significantly lower incidence of depression was related to WeChat usage after adjusting for all possible covariates (OR: 0.76, 95% CI: 0.62–0.94). The most popular WeChat functions used by the study population were watching news (80.4%), posting Moment messages (75.5%), chatting with friends (66.0%), and watching videos (65.2%). The sensitivity analysis yielded similar findings to the primary analyses. Conclusions Using social media WeChat showed an association with lower depressive symptoms among people aged ≥45 and older in our study sample. Further studies need to be explored on the promotion and education of social media WeChat usage, targeting the improvement of mental health-related issues through social network connections.

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