Introduction
Prediabetes is a metabolic state where blood glucose levels are elevated above normal but do not meet the diagnostic thresholds for type 2 diabetes. The American Diabetes Association and other clinical guidelines emphasize early lifestyle intervention to prevent progression to diabetes and to reduce cardiometabolic risk. In recent years, digital therapeutics (DTx) have emerged as scalable tools to support lifestyle change. When infused with behavioral science, DTx can equip individuals with prediabetes to set goals, monitor progress, and sustain healthier behaviors beyond traditional counseling.
This article synthesizes the current landscape of how behavioral science informs digital therapeutics for people with prediabetes, drawing on a scoping-review approach to map theories, techniques, and outcomes reported in the literature. The aim is to highlight what works, for whom, and under what conditions, guiding developers, clinicians, and policymakers toward effective, user-centered solutions.
What is Digital Therapeutics for Prediabetes?
Digital therapeutics refer to evidence-based software interventions that prevent, manage, or treat medical conditions. For prediabetes, DTx platforms typically combine education, self-monitoring (e.g., glucose or weight tracking), personalized feedback, and behavior-change support to promote healthier eating, physical activity, and weight management. When designed with behavioral science in mind, these tools are more likely to engage users, sustain use, and translate digital data into meaningful health outcomes.
The Role of Behavioral Science in DTx
Behavioral science provides guiding theories and practical techniques to catalyze lasting behavior change. In the context of prediabetes, common approaches include the use of specific behavior change techniques (BCTs) such as goal setting, self-monitoring, feedback on performance, and social support. Theoretical frameworks—most notably the COM-B model (capability, opportunity, motivation) and the Behavior Change Wheel, as well as Self-Determination Theory—help designers map user needs to features that enable capability, opportunity, and motivation for healthier choices.
DTx that embed these theories often create feedback loops linking real-time data to adaptable coaching, reminders, and personalized action plans. The result is a more interactive and timely experience than standard education alone, which can influence both short-term engagement and long-term health trajectories.
Methods of the Scoping Review (Overview)
Across studies identified in the literature, researchers examined interventions that explicitly integrate behavioral-science concepts within digital platforms for individuals with prediabetes. Inclusion criteria typically centered on software-based interventions with measurable health or engagement outcomes and explicit use of a theoretical framework, BCT taxonomy, or behavioral coaching component. Data were charted on theoretical basis, BCTs employed, modes of delivery (apps, wearables, tele-coaching), engagement metrics, and clinical outcomes such as weight loss, fasting glucose, or HbA1c changes.
Key Findings
Behavior Change Techniques Employed
Effective DTx often incorporate goal setting, self-monitoring of diet and activity, feedback on progress, and social or peer support. Gamification elements and rewards appear in several programs to sustain motivation. Just-in-time prompts and tailored feedback are associated with higher adherence and better outcome trajectories in multiple studies.
Theoretical Frameworks and Mechanisms
Many interventions draw on the COM-B framework or related Behavior Change Wheel concepts to align features with users’ capabilities, opportunities, and motivation. Self-Determination Theory is used to support autonomous motivation, helping users internalize healthy behaviors beyond extrinsic rewards. The integration of data-driven coaching with these theories supports adaptive, user-centered interventions.
Engagement and Health Outcomes
Several studies report improvements in weight, fasting glucose, or HbA1c with behavioral-science-informed DTx. However, engagement remains a pivotal mediator; barriers such as digital literacy, health equity, and access can limit impact, particularly in diverse or underserved populations.
Design Principles for Effective DTx in Prediabetes
To maximize impact, digital therapeutics should blend rigorous behavioral science with user-centered design. Practical principles include intuitive onboarding, clear and attainable goals, actionable feedback, and seamless integration with routine clinical care. Personalization and adaptive coaching enhance relevance, while attention to privacy, accessibility, and health equity ensures broader applicability.
Implications for Practice and Policy
Clinicians and healthcare systems should consider endorsing DTx that explicitly apply behavioral science to support lifestyle modification in prediabetes. Reimbursement and policy frameworks should reward sustained engagement and demonstrable health outcomes, not merely initial use, to incentivize long-term effectiveness.
Gaps and Future Directions
There is a need for standardized reporting of theoretical foundations, BCT taxonomies, and engagement metrics. Future research should examine long-term outcomes, real-world effectiveness, and integration with primary care workflows. Cross-cultural studies are essential to ensure applicability across diverse populations and healthcare settings.
Conclusion
Behavioral science-informed digital therapeutics hold promise for preventing progression from prediabetes to type 2 diabetes by enabling sustainable lifestyle changes. Realizing this potential requires rigorous evaluation, thoughtful design, and equitable implementation within real-world health systems.
