Profiles of digital disability among Chinese older adults and its association with cognitive function: a latent profile analysis

BACKGROUND: The relationship between digital disability patterns and cognitive function among older adults remains complex. This research investigates how different patterns of digital disability were associated with cognitive function, with particular attention to the moderating role of self-perceptions of aging. OBJECTIVE: This study aims to identify distinct patterns of digital disability among older adults, examine their associations with cognitive function, and investigate whether self-perceptions of aging moderate these relationships. METHODS: Data were collected from the 2020 China Longitudinal Aging Social Survey (CLASS), including 2,848 participants aged 60 and above. Latent Profile Analysis (LPA) was employed to systematically identify distinct digital disability patterns. RESULTS: The research identified three distinct digital disability patterns: utilitarian digital disability pattern (Class 1, 24.6%), digital empowerment pattern (Class 2, 35.3%), and high digital disability pattern (Class 3, 40.0%). Compared to the Class 2, Class 1 and Class 3 were significantly associated with lower cognitive function, with self-perceptions of aging found to moderate this relationship. Younger older adults ( < 70) and rural residents experienced stronger negative cognitive effects from Class 3 and Class 1. CONCLUSION: Targeted digital literacy programs and age-friendly technology designs are essential for maintaining cognitive health in older populations.