JMIR Publications

ABSTRACT

Background:

Digital therapeutics have shown increasing potential in the management of prediabetes, offering a viable alternative to traditional interventions due to their accessibility and personalized nature. However, the effectiveness of such interventions largely depends on the theoretical underpinnings of behavioral science and the successful integration of these theories into digital platforms. There is a lack of comprehensive reviews evaluating the systematic application, intervention pathways, and practical outcomes of behavioral science within digital therapeutics for prediabetes.

Objective:

This scoping review examines the application of behavioral science in digital therapeutics targeting individuals with prediabetes. The goal is to inform the development of theoretically grounded, technologically adaptable, and scalable precision intervention strategies.

Methods:

A systematic search was conducted across PubMed, Embase, Web of Science, the Cochrane Library, Scopus, China National Knowledge Infrastructure (CNKI), VIP Database, and the Chinese Biomedical Literature Database. The search covered studies published up to March 10, 2025. Eligible studies were screened, selected, and synthesized narratively.

Results:

A total of 21 studies were included. Frequently adopted behavioral science theories included Social Cognitive Theory, the Theory of Planned Behavior, and the Transtheoretical Model—notably, 11 studies employed theory-informed behavior change techniques without explicitly specifying their theoretical frameworks. Digital therapeutic modalities encompass smartphone applications, communication tools, web-based platforms, app-integrated wearable devices, and guidance from health coaches. Intervention components involved goal setting, self-monitoring, real-time feedback and reinforcement, social support and peer interaction, reminders and prompts, and health education. The most commonly utilized behavior change techniques included self-monitoring of behavior, instruction on how to perform the behavior, goal setting (behavior-specific), information about health consequences, and social support (unspecified). Outcome measures assessed glycemic control, metabolic and body composition indicators, cardiovascular risk, physiological functions, behavioral and cognitive outcomes, and overall health outcomes.

Conclusions:

Behavioral science demonstrates significant potential in enhancing digital therapeutics for individuals with prediabetes. However, current studies face multiple challenges in practical implementation. Future research should prioritize high-quality, large-scale, multicenter randomized controlled trials to establish precise intervention models, thereby enhancing the effectiveness of digital management strategies for individuals with prediabetes.