Background: Prediabetes, Digital Therapeutics, and the Behavioral Lens
Prediabetes is a transitional metabolic state characterized by elevated blood glucose levels that fall short of diabetes criteria. Without targeted intervention, many individuals with prediabetes progress to type 2 diabetes and related complications. Digital therapeutics (DTx) offer software-based interventions—often powered by mobile apps, wearables, and telehealth—that support lifestyle changes and self-management. The core promise of DTx lies in translating evidence from behavioral science into scalable, personalized tools that help individuals adopt healthier eating, increase physical activity, and sustain these habits over time. This scoping review synthesizes how behavioral science informs the design, delivery, and evaluation of DTx for people with prediabetes, identifying what works, for whom, and under what conditions.
The Behavioral Science Backbone of DTx for Prediabetes
Behavioral science provides the theories, models, and techniques that drive user engagement, motivation, and habit formation within digital interventions. Frameworks such as the COM-B model (Capability, Opportunity, Motivation) help teams diagnose barriers to behavior change and tailor digital features accordingly. Other theories—Self-Determination Theory, Social Cognitive Theory, and the Health Belief Model—offer guidance on autonomy, perceived competence, social support, and risk perception. When embedded in DTx, these concepts shape content, messaging, and feedback loops, ensuring that interventions address not just knowledge, but the cognitive and environmental drivers of sustained lifestyle change relevant to prediabetes management.
Key Behavioral Techniques (BCTs) in DTx for Prediabetes
Goal setting and action planning
Clear, measurable goals paired with concrete action plans help users convert intentions into daily actions. Digital platforms often guide users to set SMART goals (Specific, Measurable, Achievable, Relevant, Time-bound) for meals, activity, and sleep, with stepwise action plans that adapt to progress and context.
Self-monitoring and feedback
Regular self-monitoring of glucose (when provided), weight, activity, and dietary intake creates awareness and accountability. Real-time or near-real-time feedback—showing trends, what’s working, and what needs adjustment—enhances learning and motivation, particularly when feedback is tailored to the user’s stage of change and personal preferences.
Prompts, reminders, and social support
Personalized prompts (push notifications, reminders linked to routines) help maintain consistency, while social features—peer groups, coaching, or family involvement—provide encouragement and accountability, which are especially important for behavior maintenance in prediabetes care.
Problem solving and relapse prevention
Digital programs that help users anticipate challenges (e.g., vacations, social events) and develop coping strategies support resilience and long-term adherence, a critical factor given the chronic nature of prediabetes lifestyle changes.
Engagement, Usability, and Equity in DTx
For behavioral science to translate into real-world impact, DTx must balance complexity with usability. Onboarding that clarifies goals, intuitive interfaces, and culturally sensitive content improve engagement across diverse populations. Equitable access requires considering digital literacy, device availability, and language preferences. When these factors align with robust behavioral design, digital therapeutics can sustain healthy behaviors beyond initial adoption and reduce disparities in prediabetes outcomes.
Evidence, Gaps, and Practical Implications
Current evidence suggests that theory-informed DTx can improve short-term behavioral outcomes and weight loss in prediabetes, yet methodologic heterogeneity and short follow-up limit conclusions about long-term health benefits. Common gaps include inconsistent reporting of behavior change techniques, insufficient measurement of adherence, and limited data on diverse populations. Practitioners should prioritize transparent reporting of theoretical underpinnings, user-centered design processes, and equity considerations. For developers and clinicians, the implication is clear: embed behavioral science throughout the product lifecycle—from ideation and prototyping to randomized evaluation and real-world implementation.
Future Directions and Research Priorities
Future work should focus on rigorous comparative studies of different BCTs within DTx for prediabetes, standardized reporting of behavioral constructs, and adaptive interventions that respond to individual progress and life context. Integrating objective digital biomarkers with self-reported outcomes will enhance measurement precision. Equally important is exploring scalability in diverse health systems, ensuring data privacy, and training multidisciplinary teams that combine clinical knowledge with behavioral science and software development.
Conclusion
Applying behavioral science in digital therapeutics offers a pathway to meaningful, scalable change for individuals with prediabetes. By grounding DTx in robust theories, leveraging effective behavior change techniques, and prioritizing user-centered design and equity, the field can move closer to preventing diabetes at scale while improving quality of life for at-risk populations.
