Abstract
Prediabetes represents a critical global health challenge, demanding innovative and empathetic digital solutions for effective self-management. This research-in-progress paper, grounded in Design Science Research (DSR) methodology, presents the design and development of a personalised empathetic chatbot for young adults’ prediabetes self-management. The chatbot integrates the CARE framework’s core constructs—Compassion, Assistance, Respect, and Empathy—to empower users in preventive healthcare. It explores blending humanistic principles into AI-driven systems to enhance digital health interventions. A scoping review informed the prototype’s design, refined through expert review to ensure responsible development. A future evaluation protocol will combine Task Technology Fit (TTF) and Unified Theory of Acceptance and Use of Technology (UTAUT) frameworks with machine learning to assess usability, usefulness, and satisfaction. This mixed-methods study aims to bridge technology and human-centered care, advancing AI applications in chronic disease management and establishing new paradigms for empathetic digital health solutions.
Recommended Citation
Thanthrige, Ayesha and Wickramasinghe, Nilmini, "Personalised Empathetic Chatbots for Prediabetes
Self‑Management: Integrating the CARE Framework with AI" (2025). ACIS 2025 Proceedings. 2.
https://aisel.aisnet.org/acis2025/2