JMIR Publications

ABSTRACT

Background:

Digital therapeutics are increasingly used to manage prediabetes due to their accessibility and potential for personalization. Their success depends heavily on applying behavioral science and integrating theoretical models into digital platforms. However, there has not been a comprehensive account of how behavioral science has been applied in digital therapeutics for individuals with prediabetes.

Objective:

This scoping review aimed to examine the use of behavioral theories and techniques in digital therapeutic interventions for individuals with prediabetes, and to identify opportunities to optimize theory-driven and technology-supported strategies.

Methods:

A scoping review was conducted following the Arksey and O'Malley framework and guided by the PRISMA-ScR checklist. We systematically searched PubMed, Embase, Web of Science, the Cochrane Library, Scopus, China National Knowledge Infrastructure (CNKI), and VIP Database for Chinese Technical Periodicals for studies published up to March 10th, 2025. Eligible studies included those involving adults (≥18 years) with prediabetes and examining digital therapeutic interventions informed by behavioral science. Studies of all design types were eligible for inclusion. All included studies were screened and charted for key characteristics.

Results:

A total of 21 studies were included. Frequently used behavioral theories included Social Cognitive Theory, Theory of Planned Behavior, and Transtheoretical Model. Eleven studies applied behavior change techniques (BCTs) without explicitly stating a theoretical framework. Common digital modalities included smartphone apps, messaging tools, wearable devices, web platforms, and human coaching. Core intervention components involved goal setting, self-monitoring, feedback, social support, reminders, and health education. The most commonly used BCTs were self-monitoring of behavior, instruction on performing the behavior, goal setting (behavior), information about health consequences, and unspecified social support. Outcomes covered glycemic control, metabolic indicators, body composition, cardiovascular risk, behavioral outcomes, and general health.

Conclusions:

Behavioral science plays a vital role in shaping effective digital therapeutics for prediabetes. However, greater clarity in theory selection, better integration between models and digital functions, and more culturally inclusive research are needed to improve the scalability and impact of these interventions.