Intergenerational digital feedback and digital social integration of older adults: an empirical study from personal initiative perspective - Wenjia Hong; Changyong Liang; Yiming Ma; Junhong Zhu (Humanities & Social Sciences Communications)
Abstract Amid rapid population aging and the swift progress of artificial intelligence technology, the use of artificial intelligence products (AIPs) can improve older adults’ well-being by helping them integrate into digital society. However, limited research has explored the influence mechanism of this social integration. This study builds a theoretical model to explore the influence mechanism of different sources of intergenerational digital feedback on older adults’ digital social integration (DSI) from personal initiative perspective. An explanatory sequential mixed-method design is used, including a quantitative study (questionnaire survey with 549 respondents) and qualitative study (semi-structured interviews with 11 participants). A structural equation model is used for quantitative data analysis, and the quantitative results are explained by the qualitative results. Our results show that societal feedback has the greatest impact on older adults’ motivation and capability to use AIPs, and that motivation to use has a greater impact on personal initiative than capability to use. In addition, the results confirm that the key to DSI of older adults is their own initiative to use AIPs. Accordingly, this study proposes that the whole society should actively help older adults use AIPs, better integrating them into digital society.