Perceived Algorithmic Care Intensity and Older Adults' Autonomy in Community Smart Care: Mixed Methods Study

Area of Science:

• Gerontology and Digital Health
• Human-Computer Interaction
• Sociology of Technology

Background:

• The increasing integration of algorithmic care in smart older adult care systems raises concerns about autonomy.
• Previous research has primarily focused on technology acceptance, neglecting the psychological impact of algorithmic care on perceived autonomy.

Purpose of the Study:

• To investigate how perceived algorithmic care intensity affects older adults' perceived autonomy in community smart care settings.
• To examine the mediating roles of decisional substitution and perceived surveillance.
• To determine the moderating effect of digital literacy.

Main Methods:

• A three-stage research design incorporating qualitative pre-study, vignette-based experiment, and community-based survey.
• Qualitative pre-study with 15 older adults to refine constructs and measures.
• Vignette-based experiment (N=233) and community survey (N=298) to test the moderated mediation model.

Main Results:

• Higher algorithmic care intensity significantly reduced perceived autonomy, increased decisional substitution, and perceived surveillance.
• Indirect effects through decisional substitution and perceived surveillance were significant, indicating their mediating roles.
• Digital literacy selectively weakened the impact of algorithmic care on decisional substitution but not on perceived surveillance.

Conclusions:

• Algorithmic care can diminish older adults' perceived autonomy through decisional substitution and perceived surveillance.
• Digital literacy acts as a partial, selective buffer against the negative impacts of algorithmic care.
• Findings highlight the need to balance empowerment and control in algorithmic care for older adults, extending research beyond mere technology acceptance.