AI-ESRs show promise in facilitating social interactions among patients with dementia, with their effectiveness influenced by participant characteristics, intervention design, and contextual factors.
Abstract
Background The global rise in dementia, closely linked to aging populations, necessitates innovative interventions to address care challenges. Artificial Intelligence-Enabled Social Robots (AI-ESRs) present a promising approach by leveraging multi-modal communication to enhance social engagement and alleviate isolation. However, evidence regarding their efficacy remains inconsistent and fragmented. This systematic review evaluates the effectiveness of AI-ESRs in enhancing social interactions among people with dementia, examines factors contributing to outcome variability, and provides recommendations for optimizing their integration into care models. Methodology A comprehensive search was conducted across five electronic databases (PubMed, Web of Science Core Collection, EBSCO, Scopus, and Cochrane Library) for peer-reviewed articles published up to May 2026. Inclusion criteria encompassed studies addressing AI-ESRs interventions in dementia care, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Data extraction was standardized to ensure consistency across selected studies. Results 16 studies met the inclusion criteria, comprising seven randomized controlled trials (RCTs) and 9 pre-post studies. 15 studies demonstrated the potential of AI-ESRs to significantly enhance multiple dimensions of social interactions. These included verbal and non-verbal communication, the frequency and quality of interactions with caregivers, peers, and robotic systems, as well as behavioral indicators (e.g., smiling and laughter) and participation in activities. One study reported no statistically significant differences between intervention and control groups (p = 0.18) but noted a marginal improvement in communication scores. Conclusions AI-ESRs show promise in facilitating social interactions among patients with dementia, with their effectiveness influenced by participant characteristics, intervention design, and contextual factors. Further research is warranted to explore long-term outcomes, tailor interventions to individual needs, and address ethical and implementation challenges, thereby advancing the integration of AI-ESRs into dementia care.
A structural imbalance favoring functional over psychosocial support, a predominantly medical-model orientation in AI development, and systematic underrepresentation of persons with intellectual and psychosocial disabilities are revealed.
Wei Du, Xi-Yuan Peng, Wei Li et al.· Rehabilitation Psychology· 0 citations
Although the reviewed studies report encouraging findings concerning feasibility, engagement, acceptance, and preliminary cognitive outcomes, the evidence remains insufficient to identify the most effective robotic embodiment or confirm long-term clinical benefits.
Muhammad Zubair, C. Tamantini, Riccardo De Benedictis et al.· Robotics· 0 citations
Based on the findings, AI seems highly promising for patient-specific ASD therapy via proactive, data-driven scaffolding, but more RCTs and crucial augmentation of representation gaps concerning adult and female ASD phenotype studies are required.
Julia Kuca, Magdalena Stencel, Błażej Pilarski et al.· Frontiers in Psychiatry· 0 citations
Eotional reliance on AI represents an emerging clinical phenomenon with addiction-like features requiring specific diagnostic frameworks, evidence-based interventions, and ethical design guidelines and future research should prioritize longitudinal studies examining developmental impacts and neurobiological investigati...
M. Lastretti, M. Manchia, Matteo Fraschini et al.· Psychiatry International· 0 citations
Artificial intelligence-based pets should currently be considered facilitator-supported adjuncts rather than validated standalone treatments, and Experimental findings indicate that interactivity contributes to engagement and some sensory outcomes, while simpler non-interactive comparators can produce overlapping affec...
Rosita Louis, Trishalla Udhayakumar, Bibi Zainab Muttur· Asian Journal of Medicine an...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.