Advancing Diabetes Self-Management: A Novel Smartphone Application Featuring a Scoring Algorithm for Tailored User Engagement

Abstract

Abstract Background: We developed and evaluated an intelligent diabetes assistant application (Diabetter) for the self-management of diabetes. It suggested that increasing the patient’s interest and participation in using smartphone apps is important for the effectiveness of diabetes management apps. Methods: After evaluating all-encompassing features for diabetes management, we divided the selected factors into sub-factors for use in the application. Then, we created the first high-fidelity prototype using related programs and conducted early user testing to validate and improve Diabetter. To handle the user transaction time and keep them motivated, we designed and implemented a scoring system based on the nudge theory rules within the app. Results: To evaluate Diabetter’s impact on diabetes self-management, we measured HbA1c levels after a prolonged period. The Diabetter prototype was developed and modified in a revised version for better user interaction with the app. The scoring system increased the input of users’ information, which resulted in more analysis and recommendations to users. Clinical studies showed that as a result of continuous input of information from users who had been using the application for a longer period of time, their HbA1c levels were within the healthy range. Conclusions: The results demonstrate that the Diabetter application has been able to play an effective role in diabetes self-management by increasing users’ app usage time. However, future study is needed to provide a better interpretation.