Do-It-yourself Artificial Pancreas Systems: User Perspectives, Glycemic Control, and Quality of Life in Type 1 Diabetes

Introduction and Objective: The emergence of open-source automated insulin delivery (AID) systems, often developed and supported by patient communities, has introduced a transformative approach to diabetes management. These systems integrate continuous glucose monitoring (CGM), insulin pumps, and algorithm-driven smartphone applications to automate insulin delivery. This study aimed to explore the usage patterns, glycemic outcomes, and user perceptions of DIY AID systems (DIYAPS), specifically focusing on their effectiveness and impact on quality of life (QOL) in individuals with type 1 diabetes (T1D). Methods: A cross-sectional study was conducted using a structured questionnaire distributed among members of the Loopers Community WhatsApp group from May to August 2024. The survey collected data on demographics, computer literacy, DIYAPS components, duration of use, CGM metrics before and after adoption, and user feedback on system usability. One of the coauthors, who is a DIYAPS user, also contributed a detailed user perspective, providing firsthand insights to enrich the study findings. Responses were anonymized, and ethical research protocols were adhered to throughout the study. Results: A total of 10 participants (50% male, 50% female) from different parts of the country completed the survey. The average time in range improved significantly from 63% ±10% to 80% ±12%, while time above range and time below range decreased from 28% ±12% to 17% ±14% and 13% ±11% to 7% ±6%, respectively. Mean hemoglobin A1C levels dropped from 8.02% to 6.75%. Participants reported reduced fear of hypoglycemia, better sleep quality, and greater flexibility in daily routines. The coauthor’s user perspective highlighted additional benefits, such as improved overnight glycemic control and reduced dependence on manual adjustments, alongside practical challenges like device maintenance. Conclusion: DIYAPS demonstrates significant potential in improving glycemic control and enhancing QOL for individuals with T1D. Despite technical challenges, the systems provide a cost-effective and customizable alternative to commercial AID options. The findings support further integration of open-source AID systems into clinical practice while advocating for collaborative care and longitudinal studies to assess long-term outcomes and safety.