Effectiveness of AI-based conversational and socially assistive agents in older adults: a systematic review and meta-analysis.
Depression and loneliness are highly prevalent among older adults, yet access to timely and adequate mental health care remains limited in this population. Artificial intelligence-based conversational and socially assistive agents have emerged as a potentially scalable and cost-effective intervention; however, their effectiveness in alleviating depression and loneliness among older adults has not been comprehensively established. This systematic review and meta-analysis aimed to synthesize evidence from randomized controlled trials (RCTs) examining the effects of AI-based conversational and socially assistive agent interventions on depressive symptoms and loneliness in older adults.
A systematic search of five electronic databases was conducted from inception to November 15, 2025, to identify RCTs evaluating AI-based conversational and socially assistive agent interventions targeting depression and/or loneliness in older adults. Random-effects meta-analyses were performed using standardized mean differences. Statistical heterogeneity was assessed using the I² statistic and further explored through subgroup analyses. Risk of bias was evaluated using the Cochrane Risk of Bias 2 tool, and the certainty of evidence was appraised using the GRADE framework.
Eight RCTs comprising 611 participants met the inclusion criteria. Compared with control conditions, AI-based conversational and socially assistive agent interventions were associated with a statistically significant reduction in depressive symptoms (Hedges' g = - 0.25, 95% CI - 0.48 to - 0.02; I² = 10.7%). In contrast, no significant effect was observed for loneliness, and substantial heterogeneity was detected across studies (Hedges' g = - 0.67, 95% CI - 2.57 to 1.23; I² = 89%). Subgroup analyses suggested that interventions with a cognitive focus yielded more consistent effects than companionship-focused approaches, while no clear differences were observed between home-based and institutional settings.
AI-based conversational and socially assistive agent interventions appear to be effective in reducing depressive symptoms among older adults, whereas current evidence does not support a significant effect on loneliness. The effectiveness of these interventions may depend on their theoretical orientation and implementation characteristics. AI-based conversational and socially assistive agents may serve as a promising adjunct to conventional mental health care for older adults; however, further high-quality trials are needed to clarify their role in addressing loneliness and to optimize intervention design.
The protocol for this systematic review was registered in International Prospective Register of Systematic Reviews (PROSPERO identifier: CRD420261283098).
A systematic search of five electronic databases was conducted from inception to November 15, 2025, to identify RCTs evaluating AI-based conversational and socially assistive agent interventions targeting depression and/or loneliness in older adults. Random-effects meta-analyses were performed using standardized mean differences. Statistical heterogeneity was assessed using the I² statistic and further explored through subgroup analyses. Risk of bias was evaluated using the Cochrane Risk of Bias 2 tool, and the certainty of evidence was appraised using the GRADE framework.
Eight RCTs comprising 611 participants met the inclusion criteria. Compared with control conditions, AI-based conversational and socially assistive agent interventions were associated with a statistically significant reduction in depressive symptoms (Hedges' g = - 0.25, 95% CI - 0.48 to - 0.02; I² = 10.7%). In contrast, no significant effect was observed for loneliness, and substantial heterogeneity was detected across studies (Hedges' g = - 0.67, 95% CI - 2.57 to 1.23; I² = 89%). Subgroup analyses suggested that interventions with a cognitive focus yielded more consistent effects than companionship-focused approaches, while no clear differences were observed between home-based and institutional settings.
AI-based conversational and socially assistive agent interventions appear to be effective in reducing depressive symptoms among older adults, whereas current evidence does not support a significant effect on loneliness. The effectiveness of these interventions may depend on their theoretical orientation and implementation characteristics. AI-based conversational and socially assistive agents may serve as a promising adjunct to conventional mental health care for older adults; however, further high-quality trials are needed to clarify their role in addressing loneliness and to optimize intervention design.
The protocol for this systematic review was registered in International Prospective Register of Systematic Reviews (PROSPERO identifier: CRD420261283098).