Factors Affecting the Willingness of Urban Elderly to Adopt Smart Home Care: Based on Logistic Regression

Abstract 

Background and purpose: With the aggravating trend of aging in China, the imbalance between supply and demand of pension services is serious. Beijing is in the moderate aging and estimating into severe aging in 2030. Most recently, smart home care for the elderly connects supply more efficiently with demand relying on “Internet Plus”, which has been becoming a new trend. Most studies at home and abroad of in the field of development and application of intelligent production for elderly and disabled have been done, while empirical study on elderly demand of smart home care is less. However, elderly attitude towards intelligent services is rarely deeply considered. Based on social stratification theory and efficacy theory, the objective of this study is to investigate major factors influencing adoption of smart home care to provide guidance for related aging policies and market to benefit the elderly.

Methods: The 132 valid data were collected via 150 questionnaires sent by cluster sampling to the elderly of 3 districts in Beijing. Respondents between the ages of 60 and 93 years, 64.4% female, 68.2% from families of monthly income below 6,000 yuan. According to the different economic development situation in Beijing, districts are divided into good, medium and poor three levels to determine the scope of the survey. Logistic regression in STATA was used to assess the key latent variables to adopt smart home care.

Results: The data were analyzed utilizing education, gender, age and marriage as control variables, and using the margins command to correct the model. The results indicate that 74% of older adults(n=97) is unwilling to adopt smart home car, 26% of older adults (n=35) prefer to accept. Income (r=.66, p=.000), awareness of smart home care (r=.45, p=.000), health status (r=.37, p=.001) and user experience (r=.64, p=.001) were proved to be the influential factors of adopting smart home care by logistic regression. Privacy (r=0.09, p=0.952) has less significance for the willingness.   

Conclusions and Implications: Most older adults are unwilling to accept smart home care. Adoption of smart home care is largely determined by income, health status, user experience and awareness of smart home care. Privacy cannot be a barrier for older adults to accept smart home care. Obviously, smart home care is still need to be accepted gradually. It is suggested to enhance smart home care propaganda and extension and to adjust a more reasonable price to fit in unaffordable older adults. In addition, social workers as caregiver have inescapable responsibility in caring the disabled to narrow the temporary care gap.