Exploring mobile health applications for self-management of Diabetes Mellitus

Abstract

The increasing number of diabetes mellitus (DM) m-health applications (apps) reveals a panoramaof different approaches to the subject matter. Available applications have various functions and capabilities. Especially in the daily treatment of Type 1 Diabetes Mellitus (T1DM), the patientneeds to deal with many data and consider many variables to perform actions, decisions, and regimen adjustments. There is a need to apply filtering techniques to extract relevant information and provide appropriate data visualization methods to assist in clinical tasks and decisionmaking. Therefore, this master’s thesis presents the development of Soins DM, an m-Health tool for monitoring the linkage among treatment factors of T1DM with an interactive data visualization approach. Initially, we systematically reviewed the literature to investigate DM app’s features, the basis for its design and testing. After, we searched the Internet and tested interactive resourcesof diabetes-related technologies. Hence, the approaches and key characteristics of a novel app were discussed and identified. Next, we built a prototype with high-fidelity level, full-featured, and interactive, in order to test and gather feedback, when 76 users participated. After analyzing the feedback obtained, we made the necessary adjustments to the project and implemented the software using React Native framework, Firebase server, and Angular framework. With the app and its website version built, we move on to the assessment phase. We conducted a pilot experiment with 4 patients, an online experiment for satisfaction assessment with 97 patients, and an online assessment by 9 health professionals. As a result, in the systematic review, 679 studies were screened for eligibility, when 39 studies met the inclusion criteria. In this regard, we present tables summarizing the functionalities, features, and fundamental techniques of the existing apps. Prototyping and feedback facilitated the app’s design refinement. Soins DM enables the recording of data from glycemia, insulin applications, meals, and physical exercises. From these logs, the app builds two different ways of interactive data visualization, a timeline and an integrated chart, providing personalized feedback on bad glycemia with its possible causes. The assessments revealed overall satisfaction with the app’s characteristics. The test scenario with patients and health professionals indicates Soins DM as a useful and reliable tool.