Depression poses a significant public health challenge in China, exacerbated by the COVID-19 pandemic. Previous studies, often relying on online convenience samples, have limited insights into the prevalence of depressive disorders among middle-aged and older adults, a population with potentially lower internet access. This study addresses this gap by utilizing data from the nationally representative CHARLS, providing a comprehensive assessment of depressive symptoms among this specific demographic during the pandemic's early stages. The study also explores the under-researched role of social media in mitigating depressive symptoms in this population. Given China's unique social media landscape, integrated with mobile payment systems and widespread smartphone usage, understanding the impact of social media engagement on mental health is particularly crucial. This study aims to estimate the burden of depressive symptoms in this population and analyze the longitudinal association between social media use and changes in depressive symptoms over a two-year period.

Existing literature highlights the increasing burden of depression in China, with the COVID-19 pandemic further worsening the situation. While online surveys suggest a high prevalence of depressive disorders, these often exclude older adults with limited internet access. There's a growing body of research exploring the potential of social media in managing mental health, focusing on its role in social interaction, peer support, and service engagement. However, research on this topic within the middle-aged and older Chinese population is lacking, especially considering the unique characteristics of social media use in China and its connection to cashless transactions. This study bridges this gap by focusing on a nationally representative sample and a longitudinal approach.

This study analyzed data from the China Health and Retirement Longitudinal Study (CHARLS), a biannual panel survey employing a four-stage stratified cluster probability sampling design to represent middle-aged and older Chinese adults. The study focused on data from the 2018 and 2020 surveys. Depressive symptoms were measured using the Center for Epidemiological Studies Depression Scale (CESD) short form, with a cut-off score of 10 defining the presence of depressive symptoms. Social media activities were assessed through four questions covering various online activities, mobile payments, WeChat use, and WeChat Moments posting. Participants were categorized into three social media transition groups: consistently inactive, transition to active, and consistently active. Covariates included demographic, socioeconomic, lifestyle, and comorbidity factors. Bivariate analyses were conducted to explore associations between depressive symptoms and baseline measures. Multivariable logistic regression models assessed the association between baseline social media activity and incident depressive symptoms in participants without baseline depression, and the association between social media transition groups and the conversion to non-depressive symptoms in those with baseline depression, while adjusting for covariates. Statistical analyses were conducted using SAS version 9.3, accounting for the complex survey design.

The study revealed a high prevalence of depressive symptoms (36.0%) in the 2020 CHARLS survey, with increased prevalence among women, rural residents, and western China provinces. Among participants without baseline depressive symptoms, engaging in any social media activity was associated with a 24.0% (95% CI: 10.0–36.0%) lower odds of developing depressive symptoms within two years. Specifically, playing games, mobile pay, and WeChat use showed strong negative associations. Using a cellphone as a method of engagement also showed a significant negative association. Among participants with baseline depressive symptoms, those initiating three or more social media activities had a 1.24 times (95% CI: 1.05–1.46) higher chance of becoming non-depressed, and those using social media all the time were 1.36 times (95% CI: 1.09–1.72) more likely to recover. Geographic variations in depressive symptoms prevalence were observed, with western China provinces showing higher rates, particularly Qinghai Province (78.2%).

The study's findings highlight the considerable burden of depressive symptoms among middle-aged and older Chinese adults, particularly in vulnerable subgroups. The positive association between social media use and reduced risk of depressive symptoms, or recovery from depression, contrasts with some research on younger populations, suggesting that the effects of social media on mental health may vary across age groups. Potential mechanisms for the observed positive effect may involve social connection, access to peer support, and psychological rewards. The high prevalence in rural areas and western provinces underscores the need for targeted interventions, potentially including those that enhance access to technology and social media. The study’s findings have implications for healthcare resource allocation and public health interventions aimed at preventing and managing depressive symptoms.

This study revealed a substantial burden of depressive symptoms among middle-aged and older Chinese adults, with notable disparities across demographic and geographic groups. Social media engagement appears to be associated with a lower risk of developing depressive symptoms and facilitates recovery from existing depression in this population. Future research should explore the mechanisms underlying these findings, investigate the long-term effects of social media use on mental health, and assess the effectiveness of interventions promoting social media engagement among older adults.

The study's limitations include the lack of data on the duration of social media use, which could indicate potential addiction. The two-year follow-up period limits the assessment of long-term effects. Furthermore, depressive symptoms were assessed through self-report, not clinical diagnosis. Finally, potential misclassification of participants based on fluctuating depressive symptoms might have biased the results. Although the misclassification was likely non-differential, future studies should utilize more robust diagnostic methods.