• 1 Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman (UTAR), Kampar 31900, Malaysia
  • 2 College of Computing & Informatics, Universiti Tenaga Nasional (UNITEN), Kajang 43000, Malaysia
  • 3 Computer & Information Sciences Department, Universiti Teknologi Petronas (UTP), Seri Iskandar 32610, Malaysia
Int J Environ Res Public Health, 2021 Aug 31;18(17).
PMID: 34501750 DOI: 10.3390/ijerph18179160


Type 2 diabetes (T2D) is a chronic condition that can lead to many life-threatening diseases. Prediabetes is defined as a state in which blood glucose levels are elevated but not high enough to be diagnosed as diabetes. This stage can be reversible with appropriate lifestyle and dietary modifications. Existing solutions are mostly developed to deal with T2D instead of preventing it in the first place. In this study, we propose a framework to aid in the development of self-care systems to prevent T2D, which integrates behavioral change theories and techniques and offers features, such as goal setting, activity planning, and health monitoring. We then assessed the feasibility of a prediabetes self-care system designed based on the proposed framework. Quantitative and qualitative methods were adopted in evaluating i-PreventDiabetes, a prototype. Numerous aspects of the prototype were evaluated, including (1) its effectiveness in assisting individuals with prediabetes in improving their health management behaviors, (2) its effect on users' attitudes toward diabetes prevention, (3) users' motivation levels, (4) user acceptability of the system, and (5) user experience. Users viewed i-PreventDiabetes positively and experienced a positive change in their attitude toward their health. Diabetes prevention systems, such as i-PreventDiabetes, have the potential to increase self-care behaviors among individuals with prediabetes, enabling them to manage their lifestyle and nutrition more effectively to avert a variety of potentially fatal conditions.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.