Breaking Barriers: A Dual-Factor Model Unraveling Ageism in Socially Assistive Robot Adoption among Older Chinese Adults

Abstract

Despite the promising potential of socially assistive robots (SARs) in serving the aging population, older adults demonstrate lower uptake rates and motivation to use SARs compared to other technological advancements. To address this issue, this study proposes a dual-factor model that draws upon the Risks of Ageism Model (RAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine the crucial enablers and inhibitors of SAR adoption among older adults. Survey results from 400 older Chinese adults highlighted the significant roles of performance expectancy and robot self-efficacy in facilitating older adults’ intentions to use SARs. Additionally, digital belongingness emerged as a crucial enabler of SAR acceptance. Notably, age discrimination was positively associated with robot anxiety, which in turn was negatively associated with older adults’ intention to use SARs. Furthermore, this study identified the significant moderating role of concerns about being bothersome in the mediating mechanism of robot anxiety, which links older adults’ negative self-perceptions of aging with SAR usage intention. The findings contribute to theoretical knowledge about the mechanisms bridging (self-)ageism with robotic technology acceptance and provide practical recommendations to foster the inclusion of older adults in today’s AI technology-enabled society.

Keywords:

• Socially assistive robots
• older adults
• technology acceptance
• ageism
• robot anxiety

Ethics approval

All the survey respondents have provided informed consent. The study protocol was approved by the Institutional Review Board (IRB) of Shanghai Jiao Tong University (approval number: H20230368I).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the Shanghai Philosophy and Social Science Program [grant number: 2022ZXW005].

Notes on contributors

Lianshan Zhang

Lianshan Zhang is an assistant professor in the School of Media and Communication at Shanghai Jiao Tong University. Her research centers on human-computer interaction, health communication, psychological effects and social impact of emerging media.