The Effectiveness of a Custom AI Chatbot for Type 2 Diabetes Mellitus Health Literacy: Development and Evaluation Study
A RAG-based large language model chatbot can deliver contextually appropriate, empathetic, and clinically credible responses to T2DM queries. By consistently citing trusted sources and notifying users when relying on general knowledge, this approach enhances transparency and trust. The findings have relevance for health educators, highlighting that patient-centric reference documents-structured to address frequent patient questions-are particularly effective. Moreover, instances in which the chatbot signals that it has drawn on general knowledge can provide opportunities for health educators to refine and expand their materials, ensuring that more future queries are answered from trusted sources. The findings suggest that such chatbots may support patient education, promote self-management, and be readily adapted to other health contexts.
Authors
- Lorna Ryan
- Pepijn W.J. van de Ven (ORCID: https://orcid.org/0000-0003-3321-450X)
- Eoin Noctor (ORCID: https://orcid.org/0000-0002-8173-4289)
- Anthony Kelly (ORCID: https://orcid.org/0000-0003-1798-1506)
Institutions
- University of Limerick (IE)
- University Hospital Limerick (IE)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-03-25
- DOI
- https://doi.org/10.2196/70131
- Citations
- 10
- Primary Topic
- Mobile Health and mHealth Applications
- Type
- article
- Field-Weighted Citation Impact
- 28.15