Research on the Identification of Loneliness and Social Support Intervention of the Elderly Driven by Artificial Intelligence-Taking the Hexi District of Tianjin as an example
Based on the data, this paper explores the application path of artificial intelligence technology in the evaluation and intervention of elderly loneliness and reveals differences in the effects of social support on loneliness. Methods: A questionnaire survey was conducted among 109 elderly people in the Hexi District, Tianjin, using multi-stage stratified sampling. The data were collected using the UCLA Loneliness Scale and the Social Support Rating Scale, and analyzed using descriptive statistics, correlation analysis, hierarchical regression analysis, and a moderating effect test. Results: (1) Most elderly people have moderate or above loneliness, and the loneliness of those aged 80 and above is significantly higher than that of other age groups (P < 0.05). (2) There is a significant negative correlation between social support and loneliness, and the effect of objective support (number of people who can ask for help) (r=-0.45) is greater than that of emotional support (social frequency, r =-0.38); (3) Age (β=-0.18, p=0.042), self-rated health (β=0.15, p=0.038) and living conditions (β=-0.22, p=0.009) significantly regulate the relationship between social support and loneliness; (4) There is a positive correlation between the use of smart phones and living alone (r=0.24, p=0.012), suggesting the compensatory function of digital technology. Conclusion: The loneliness of the elderly is universal, and the scale of the social support network is the core protective factor. Intervention should give priority to high-risk groups who are old, live alone, have poor health, and have a support network of ≤2 people. Digital technology can be used as a supplementary tool for traditional support.
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