Digital and offline social participation configurations and depressive symptoms and life satisfaction among older adults in China.
Social participation is a key determinant of mental well-being in later life, yet population based research tends to focus on overall activity rather than on how participation is configured. In digitalized societies, unequal access to digital technologies shapes how older adults combine online and offline participation, with important but poorly understood implications for mental health.
Using data from 8,427 adults aged 60 years and older in China, this study applied latent class analysis to identify patterns of digital and offline social participation based on eight indicators. Multinomial logistic regression was used to examine sociodemographic and health correlates of class membership. Multiple linear regression and covariate adjusted means were used to assess associations between participation patterns, depressive symptoms, and life satisfaction.
Four participation classes were identified: Digital active, Offline active, Digital-offline active, and Low participation. Participation configurations were strongly stratified by age, education, residence, and health status. After adjusting for covariates, older adults in the Digital active and Digital-offline active classes reported significantly lower depressive symptoms and higher life satisfaction than those in the Offline active class, while individuals in the Low participation class showed intermediate mental health outcomes.
Mental well-being in later life depends not only on whether older adults are socially active but on how digital and offline participation are configured. In a digitally transforming society, digital engagement appears to function as a socially structured psychosocial resource, contributing to inequalities in mental well-being across later life.
Using data from 8,427 adults aged 60 years and older in China, this study applied latent class analysis to identify patterns of digital and offline social participation based on eight indicators. Multinomial logistic regression was used to examine sociodemographic and health correlates of class membership. Multiple linear regression and covariate adjusted means were used to assess associations between participation patterns, depressive symptoms, and life satisfaction.
Four participation classes were identified: Digital active, Offline active, Digital-offline active, and Low participation. Participation configurations were strongly stratified by age, education, residence, and health status. After adjusting for covariates, older adults in the Digital active and Digital-offline active classes reported significantly lower depressive symptoms and higher life satisfaction than those in the Offline active class, while individuals in the Low participation class showed intermediate mental health outcomes.
Mental well-being in later life depends not only on whether older adults are socially active but on how digital and offline participation are configured. In a digitally transforming society, digital engagement appears to function as a socially structured psychosocial resource, contributing to inequalities in mental well-being across later life.