Expectations and acceptability of a smart nursing home model among a group of urban and physically able Chinese older adults - Zhao, Yuanyuan (2023)
Nursing homes integrated with smart technologies such as the Internet of Things, cloud computing, artificial intelligence, and digital health could improve the quality of care and benefit the residents and health professionals through improved effective and efficient medical services. However, the clear concept of a smart nursing home, its expectations, and acceptability from the perspectives of a group of urban and physically able Chinese older adults and their family members are still unclear. In addition, instruments to measure the expectations and acceptability of a smart nursing home are also lacking. The study aims to explore and determine the levels of these expectations, acceptability, and associated sociodemographic factors. The concept of smart nursing homes and associated technologies were extracted and defined through a scoping review of 177 literature. An exploratory sequential mixed methods study guided by the framework method and theoretical model of smart technology adoption behaviours of elder consumers was performed. A qualitative study (Phase I) was carried out among 28 older adults aged 60-75 years old and 6 adult children until data saturation was reached. Findings showed that all participants had a positive perception towards the smart nursing home model. An expected smart nursing home model has to provide quality nursing care with smart functional technologies, ensure safety, integrate medical services from hospitals, and offer skilled caregivers and affordable services. The business care model involves the multidiscipline of health and computer sciences, engineering and business administration. Subsequently, the themes and codes related to the expectations and acceptability of smart nursing homes were developed into a questionnaire with a five-point Likert scale from 1 to 5 (low to high). (Phase II). Due to the lack of similar instruments or existing questionnaires, content and face validity were evaluated among ten experts and one item on willingness to move to nursing homes. A newly developed questionnaire with a total 49 of items was then subjected to exploratory and confirmatory factor analysis, and the final version with 24 items progressed to the next phase. The sociodemographic factors associated with different categories of expectations and acceptability of smart nursing homes were determined through a quantitative study using a survey (Phase III) in four major cities of mainland China among 264 respondents. The overall mean (SD) of expectations and acceptability were 4.0 (0.60) (Min-Max: 2.0-5.0) and 4.0 (0.60) (Min-Max: 1.6-4.9). The result of the multinomial logistic regression analysis comparing the highest tertile of the expectation group to the lowest tertile group showed that older adults with a moderate degree of familiarity with technology were 2.57 times more likely to have the highest tertile of expectation compared to those with a high degree of familiarity (OR: 2.57, 95% CI: 1.00-6.57). Older adults with no self-efficacy in applying smart technologies had only 4% of the odds of having the highest tertile of expectation compared to those who had self-efficacy (OR: 0.04, 95% CI: 0.01-0.17). Older adults with no self-efficacy in applying smart technologies had only 7% of the odds of having the highest tertile of acceptability compared to those who had self-efficacy (OR: 0.07, 95% CI: 0.02-0.23). Additionally, the results of hypothesis-testing revealed a positive association between the highest tertile of the expectations and acceptability towards smart nursing homes and the willingness to move to such facilities among older adults. The odds of moving to a nursing home were three times higher among older adults with the highest tertile of expectations towards smart nursing homes compared to those with the lowest tertile (OR: 3.02, 95% CI: 1.18-7.73). Similarly, those with the highest tertile of acceptability towards smart nursing homes were twice as likely to move to a nursing home (OR: 2.43, 95% CI: 1.10-5.39). The significance of this study is that the concept of smart nursing homes, its expectations and acceptability were explored and formulated from the qualitative evidence with Chinese older adults and their family members. The quantitative study using survey among Chinese older adults in four major cities provided confirmation of the expectations and acceptability of smart nursing homes and associated sociodemographic factors. Finally, a feasible smart nursing home model was recommended as a solution for the rapidly ageing societies in China. It also has the potential to be generalized in other developed and developing countries.