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Abstract Alzheimer's disease and related dementias (ADRD) significantly impact patients and their caregivers, causing emotional stress, lack of training, and financial strain for the latter. Addressing the need for effective support, this research developed and validated ADQueryAid, a conversational AI system designed to empower ADRD caregivers. Built on a Large Language Model (LLM) and enriched with authoritative ADRD information through a knowledge graph, ADQueryAid uses Retrieval Augmented Generation (RAG) techniques to retrieve relevant information from both structured and unstructured data sources. Prompt engineering and conversation policies ensure the delivery of informative, empathetic, and personalized responses. Evaluated via a Blind Within-Subjects Design study with 20 ADRD caregivers interacting with both ADQueryAid and a baseline model (ChatGPT 3.5) in fictional caregiving scenarios, the system's usability was assessed using the Chatbot Usability Questionnaire (CUQ). Results showed ADQueryAid significantly outperformed the baseline model across all CUQ metrics, offering more contextually relevant information, accurate guidance, and emotional support, which enhanced the caregiving experience. This study highlights the potential of AI to support ADRD caregivers by providing personalized assistance, with future research focusing on expanding the knowledge base, refining conversational strategies, and exploring the long-term impact on caregiver well-being and patient outcomes.
Hasan et al. (Sat,) studied this question.
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