My diabetes care: an AI-based mobile app with conversational agent for type 2 diabetes self-management

Despite advancements in modern healthcare, diabetes mellitus remains a lifelong, incurable condition. Empowering patients through health education and self-management is essential in preventing disease progression. This study evaluates the effectiveness of My Diabetes Care, a mobile application featuring an animated conversational agent, Dia-vera, designed to support diabetes self-managementat home. Focusing on non-compliance behaviors, sedentary lifestyle, and uncontrolled HbA1c levels, data were collected from 200 purposively selected participants from rural health clinics in southern Pakistan. This study used artificial intelligence models with built-in explainability features applied to artificial neural networks, achieving 98% training accuracy and 95% testing accuracy. User-chatbot dialogues were analyzed for engagement, thematic queries, fallback responses, and silence periods. Dia-vera successfully answered 88.86% of the 2830 queries. Weekly dialogue averages dropped from 36 to 26.1 between study phases, providing insights for future refinement. High levels of participant acceptability and satisfaction were found using the System Usability Scale. The findings show that, especially in disadvantaged settings, integrating interpretable AI with conversational agents provides a user-friendly and scientifically supported method of diabetes self-managementassistance.In comparison to baseline, participants who used the intervention reported better adherence to medication and food regimens, showed increased involvement in physical activity, and showed small reductions in HbA1c levels. These results make the study's therapeutic relevance stronger and show a stronger connection between the intervention and the desired health behaviors. Using My Diabetes Care as a proof-of-concept implementation, this study offers a reproducible framework for creating intelligent, explainable digital health interventions.