A Personalised Digital Health Intervention for Prediabetes.

Area of Science:

• Digital Health Interventions
• Behavioral Science
• Public Health

Background:

• Prediabetes is a critical stage for preventing type 2 diabetes, a growing global health concern.
• Young adults, a key demographic, often lack accessible and engaging preventive health tools.
• Effective digital interventions are needed to address this gap in prediabetes management.

Purpose of the Study:

• To design and evaluate a user-centered web application for prediabetes prevention among young adults.
• To enhance health knowledge, engagement, and self-management skills in this at-risk population.
• To explore the integration of novel features like AI and gamification in digital health tools.

Main Methods:

• Utilizing Design Science Research Methodology (DSRM), Task-Technology Fit (TTF), and Unified Theory of Acceptance and Use of Technology (UTAUT).
• Incorporating features identified through a systematic literature review (SLR), including Machine Learning (ML) recommendations, educational modules, goal setting, gamification, and an AI chatbot.
• Planning a pilot study with surveys to assess usability, usefulness, satisfaction, and health knowledge, analyzed via descriptive and thematic analysis.

Main Results:

• The study presents the current design of the web application, incorporating a blend of evidence-based features.
• Planned scenario-driven use cases demonstrate the application's relevance and potential impact.
• A pilot study is designed to gather empirical data on user experience and effectiveness.

Conclusions:

• This work-in-progress offers a user-centered approach to developing digital health interventions for prediabetes.
• The proposed web application aims to provide personalized and engaging tools for young adults.
• Findings will contribute insights into designing effective personalized digital health interventions for chronic disease prevention.