Artificial intelligence products (AIPs) for older adults enhance the functions of traditional products and improve the quality of their lives. However, AIPs are not popular among this population, and limited attempts have been made to investigate these users’ negative tendencies regarding AIPs. This study explores the causes of avoidance and exit behaviors toward AIPs among older people from both a functional and socio-emotional mismatch perspective. Data were collected from 1102 older AIP users to verify the research model and hypotheses. The results indicate that perceived control and expectation disconfirmation affect the functional mismatch, while public stigma has the greatest impact on the socio-emotional mismatch. Furthermore, the results highlight a mixed influence of the functional and socio-emotional mismatches on negative behaviors. This study explores older people’s negative tendencies toward AIPs, comprehensively considering the functions of AIPs and the socio-emotions they evoke. Thus, it provides new empirical evidence for the systematic relationship between the functional mismatch and the socio-emotional mismatch and fills the research gap on the influence on the subsequent behaviors of older adults. Additionally, this study sheds light on the specific methods of designing, developing, and promoting AIPs.

Older people with hearing impairment are more likely to develop depressive symptoms due to physical disability and loss of social communication. This study investigated the effects of social media on social relations, subjective aging, and depressive symptoms in these older adults based on the stimulus-organism-response (S-O-R) framework. It provides new empirical evidence to support improving the mental health and rebuilding the social relations of older people. A formal questionnaire was designed using the Wenjuanxing platform and distributed online through WeChat; 643 valid questionnaires were received from older people with self-reported hearing impairments, and SmartPLS 3.28 was used to analyze the data. The results show that (1) social media significantly impacts the social relations of older people with hearing impairment (social networks, β = 0.132, T = 3.444; social support, β = 0.129, T = 2.95; social isolation, β = 0.107, T = 2.505). (2) For these older people, social isolation has the biggest impact on their psychosocial loss (β = 0.456, T = 10.458), followed by the impact of social support (β = 0.103, T = 2.014); a hypothesis about social network size was not confirmed (β = 0.007, T = 0.182). Both social media (β = 0.096, T = 2.249) and social support (β = 0.174, T = 4.434) significantly affect the self-efficacy of hearing-impaired older people. (3) Both subjective aging (psychosocial loss, β = 0.260, T = 6.036; self-efficacy, β = 0.106, T = 3.15) and social isolation (β = 0.268, T = 6.307) significantly affect depressive symptoms in older people with hearing impairment. This study expands the theories of social media aging cognition, social support, and social networks and can provide practical contributions to the social media use and mental health of special persons 60 years and older.

Background: With the increased older population in China and the subsequent reduced labor force, the “demographic bonus” is disappearing. The Chinese government proposed a Healthy China strategy in 2017. The transfer of the demographic bonus to a “health bonus” extended the working life of people and reduced the negative impact of the population’s aging on the labor force structure. Objective: This research focuses on the effect of older workers’ social media usage at work on their work ability (related to both physical and mental health) and thus their willingness to delay retirement. Methods: The questionnaire respondents were older than 55 years, and they obtained the questionnaire from social media, from June to July 2018. A total of 1020 valid questionnaires were collected, and SmartPLS 3.28 (SmartPLS GmbH) was used to analyze the data. Effects were analyzed using 2-tailed t tests. Results: (1) Use of social media at work can improve information support (t14=13.318, P<.001), emotional support (t14=13.184, P<.001), and self-efficacy (t14=6.364, P<.001) for older people; (2) information support is the main factor affecting the self-efficacy of older workers (t14=23.304, P<.001), as compared with emotional support (t14=1.799, P=0.07); (3) the impacts of emotional support on work ability (t14=8.876, P<.001) and work stress (t14=9.545, P<.001) are generally higher than those of information support (t14=4.394, P<.001; t14=5.002, P<.001); (4) self-efficacy has an impact on work ability (t14=5.658, P<.001) and work stress (t14=4.717, P<.001); and (5) the impacts of work ability (t14=8.586, P<.001) and work stress (t14=8.579, P<.001) on retirement willingness are greater than those of emotional support (t14=2.112, P=.04) and information support (t14=4.314, P<.001). Conclusions: Our study confirms that the use of social media at work has a positive impact on older workers. Based on the findings, we have put forward proposals to extend people’s working lives and help governments implement health bonus policies. In the future, we will compare the different values of willingness to delay retirement among older people in different occupations and different cultures.

Population aging has become an important factor restricting China′s social and economic development. The smart health and elderly care industry has developed rapidly in the past five years. However, the service resources among various elderly service providers are relatively isolated and scattered. In other words, the core management problem in the components of the smart elderly care service ecosystem is how to deal with the relationships of interest among multiple resource agents. Thus, the main contribution of this study is to employ symbiosis theory and the logistic growth model to construct a model of the evolution of the symbiosis of multiple resource agents in the smart elderly care service ecosystem. Then, we carry out a stability analysis, and analyze the evolutionary model of two resource agents′ symbiosis under different values of interdependence coefficients. Finally, we use computer simulations to dynamically simulate the model and comparatively analyze the population density of the hospital–nursing home symbiotic relationship using real cases in China. According to the study, we find that the enterprise goal in the smart elderly care service ecosystem should be to maximize the overall value of the multiple resource agents, and the result of the symbiotic evolution between different resource agents depends on the symbiotic interdependence coefficient, while the resource agent uses different strategies under different symbiosis models. Therefore, regulation is needed to ensure the relative fairness of the distribution of value co-creation in the smart elderly care service ecosystem when the resource agent takes actions that benefit itself. Of course, when the ecosystem is in a reciprocal symbiosis model, each resource agent benefits from the activities of the other resource agents, which is ideal in reality; in other words, the best symbiosis model between the two resource agents should be the similar reciprocal symbiosis model.