Construction of path analysis model on related factors of social isolation in older people.

Background: With the gradual acceleration of population ageing, social isolation in older people has increasingly become a hot topic of social concern. The reduction of valid social participation will cause older people to weaken their sense of belonging to the community and social acquisition, negatively impacting on older people's quality of life. This study is aimed to explore the main related factors affecting the social isolation of older people, so as to provide a solid scientific basis for improving the health behaviour of older people in China.

Method: A cross-sectional study was conducted among 2267 community residents over 60 years old from four cites in Jiangsu Province, China. Perceived social support scale, Geriatric Depression Scale, Connor-Davidson Resilience Scale, Comprehensive Ability of Older People Assessment Scale and other influencing factors scales were used to investigate the current situation. Social isolation was measured with the Lubben Social Network Scale. Demographic data were evaluated using descriptive statistical analyses and relationships among study variables were determined to use a path analysis. All data were analyzed using SPSS version 22 and AMOS version 26 using T-test, analysis of variance, logistic regression analyses, and path analysis method. The test level was set at alpha = 0.05, and the difference was statistically significant at P-value <0.05.

Results: The results of the model test analysis indicated that the hypothesised paths were supported by data from our samples and demonstrated significance on the path coefficients (P < 0.05). Related factors in the three dimensions of social risk, economic risk and cultural risk have an impact on the social isolation of older people in the community through direct and indirect pathways, and also indirectly through the partially mediated role of depression. Overall, our hypothesised model was retained, indicating empirical support and adequate model fit indices for the theoretical model.

Conclusion: The findings demonstrated the predictive role of related factors of social isolation in older people. In the future, we should focus on developing interventions by uniting many forces such as society, family and older people themselves to reduce social isolation among this vulnerable population and improve the quality of life of older people and promote healthy ageing.