Beyond access: how heterogeneity of internet use differentially shapes cognitive function among Chinese older adults.

The intersection of digitalization and population aging has positioned internet use and cognitive function among older adults as a salient public health concern. However, existing research has predominantly treated internet use as a binary variable, failing to adequately uncover the heterogeneous effects of usage behaviors. Moreover, the moderating role of living arrangement has received insufficient attention.

This study analyzed two-wave panel data from the China Longitudinal Aging Social Survey (CLASS) in 2018 and 2020, comprising 6,800 older adults aged 65 and above, yielding 13,600 person-wave observations. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), encompassing orientation, memory, and calculation. Internet use was operationalized as a four-dimensional construct, including internet adoption, use intensity, device operation proficiency, and function types. Two-way fixed effects models were employed to estimate the associations between multidimensional internet use and cognitive function, and to test the moderating role of living arrangement.

Internet adoption exerted a protective effect on overall cognitive function. Among continuous users, use intensity and instrumental us promoted cognitive improvement, whereas device operation proficiency was negatively associated with cognitive function. These effects exhibited significant heterogeneity across cognitive subdomains, including orientation, memory, and calculation. Living arrangement moderated the association only at the level of internet adoption; specifically, co-residence with children attenuated the protective effect of internet adoption.

Internet use exerts multidimensional and heterogeneous effects on cognitive function among older adults, moderated by living arrangement. These findings provide theoretical guidance for stratified digital intervention design.
Mental Health
Access
Advocacy

Authors

Xiao Xiao, Liang Liang, Liu Liu, Wei Wei
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