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Published on: December 23, 2025
Effectiveness of AI-based conversational and socially assistive agents in older adults: a systematic review and
Wenling Gou1, Florian Lefebvre2, Tongping Yang3
1Santesih UR_UM211, University of Montpellier, Montpellier, France.
Background:
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.
Methods:
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.
Results:
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.
Conclusions:
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.
Protocol Registration:
The protocol for this systematic review was registered in International Prospective Register of Systematic Reviews (PROSPERO identifier: CRD420261283098).
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