Perceived Algorithmic Care Intensity and Older Adults’ Autonomy in Community Smart Care: Mixed Methods Study
ABSTRACT
As population aging deepens and digital technologies become increasingly embedded in community care, smart eldercare is shifting from basic information support to more continuous, algorithm driven care. Although prior research has highlighted its benefits for safety, convenience, and service efficiency, less is known about how algorithmic care shapes older adults’ perceived autonomy. Drawing on self determination theory and research on digital health in later life, this study examines how perceived algorithmic care intensity influences perceived autonomy among older adults in community smart eldercare settings, and whether digital literacy moderates this process. A three stage design was adopted. First, a qualitative pre study based on semi structured interviews was used to refine the key constructs and measurement items. Second, a scenario based experiment tested the causal effects of algorithmic care intensity on decisional substitution, perceived surveillance, and perceived autonomy. Third, a community based survey examined the parallel mediation model and the moderating role of digital literacy in a real world context. The results show that higher perceived algorithmic care intensity increases decisional substitution and perceived surveillance while reducing perceived autonomy. Both decisional substitution and perceived surveillance mediate the relationship between perceived algorithmic care intensity and perceived autonomy. In addition, digital literacy weakens the effect of perceived algorithmic care intensity on decisional substitution, but does not significantly moderate its effect on perceived surveillance. This study extends smart eldercare research beyond technology acceptance and clarifies the tension between empowerment and control in algorithmic care.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.