A latent profile analysis and network analysis of social adaptation among retired older adults

This study aims to explore latent subgroups, influencing factors and core nodes in the social adaptation of retired older adults. The data for this study were drawn from the China Longitudinal Aging Social Survey, using the social adaptation scale. Latent profile analysis was used to classify the social adaptation of retired older adults. The Mann-Whitney U test, chi-square test and logistic regression were employed to investigate influencing factors. Finally, network analysis was used to identify the core nodes within each subgroup. This study included a total of 4,158 retired older adults, who were divided into two latent subgroups: High personal development–low mental and cultural adaptation (HPD-LMCA) (2,405, 57.8%) and Low personal development–high mental and cultural adaptation (LPD-HMCA) (1,753, 42.2%). Factors influencing social adaptation included internet usage, depression and social activities. SA2 ‘Contribution to society’ was the core node for both subgroups. Given the differences in characteristics between these two subgroups, it will be necessary in future to explore how to reconcile the personal experiences of retired older people with the demands of social development; intervention measures could be designed around core nodes.