Effectiveness of AI Care Robots in Reducing Social Isolation,Loneliness,and Depression Among Older Adults Living Alone: An Explanatory Sequential Mixed-Methods Study

Abstract

As South Korea enters a super-aged society, the rapid growth of older adults living alone has intensified concerns about social isolation, loneliness, and depression. This study examined whether AI care robots can serve as an effective psychosocial intervention for these three interrelated emotional vulnerabilities using an explanatory sequential mixed-methods design. In the quantitative phase, a quasi-experimental study (n = 60; 30 robot users vs. 30 controls) over 2 months demonstrated significant group-by-time interaction effects across all three outcomes via linear mixed models. In the qualitative phase, in-depth interviews with three participants revealed three mechanisms through which robot interactions produced emotional change: restoration of social presence, emotional companionship, and recovery of daily routine and self-efficacy. The findings extend the Convoy Model to include technology-mediated support and suggest that AI–human interactions activate interpersonal mechanisms analogous to Sullivan’s Interpersonal Theory. Implications for community-based technology-assisted care policy and practice are discussed.