Transforming dementia caregiver support with AI-powered social robotics

Introduction: Informal dementia caregivers face significant emotional and physical burdens, yet evidence-based interventions like REACH are often limited by high labor costs and scalability constraints. Methods: We design a Robot-based Information and Support to Enhance Alzheimer's Caregiver Health (RISE) system, which uses novel social robotics and generative AI to deliver automated and personalized caregiver training and stress management. RISE uses retrieval-augmented generative AI (RAG-AI) grounded in the verified REACH Caregiver Notebook to ensure content safety and minimize hallucinations. It employs the social robot Pepper to deliver interactive presentations, Q&A sessions, review quizzes, and stress reduction activities. A technical evaluation and a two-phase user evaluation was conducted. Results: We found that the RISE's RAG-AI backend achieved 87% correctness and 92% relevancy when compared to ground truth. User feedback indicated strong acceptance, with Likert-scale usability scores ranging from 3.6 to 4.6 out of 5 across all components. Discussion: These results suggest that combining verifiable AI architectures with embodied social robotics offers a feasible, scalable solution for enhancing caregiver support and wellbeing. Future work could include a larger scale user study involving real informal dementia caregivers.