Enhancing dulce digital with CGM-driven personalization, peer support, gamification, and engagement (edge) to improve T2D self-management

The National Institute of Diabetes and Digestive and Kidney Diseases awarded Scripps Health $574,932 on July 1, 2026, under the Diabetes, Digestive, and Kidney Diseases Extramural Research program (CFDA 93.847) to conduct a randomized controlled trial evaluating the Enhancing Dulce Digital with CGM-Driven Personalization, Peer Support, Gamification, and Engagement (EDGE) intervention for type 2 diabetes self-management.

The research will test EDGE's effectiveness in improving clinical and behavioral outcomes in non-insulin-using adults with type 2 diabetes by comparing EDGE, which integrates continuous glucose monitoring–driven personalized messaging, virtual peer health coaching, and gamification, against the standard Dulce Digital platform. The trial will enroll 262 participants and collect clinical outcome data—including HbA1c, continuous glucose monitoring metrics, and medication dosage—at baseline, 6 months, and 12 months. A second aim will evaluate patient-reported outcomes such as diabetes distress, self-care behaviors, and quality of life using validated surveys at the same time points. A third aim will assess implementation potential in primary care settings.

Work is performed in La Jolla, California. The period of performance runs from July 1, 2026, through June 30, 2031.

Abstract

Diabetes affects 12% of the U.S. Population, with over half of individuals failing to meet HBA1C targets, contributing to significant morbidity and mortality. Despite advances in digital health and self-management tools, there remains a critical GAP in integrating personalized, real-time glucose feedback and tailored messaging to sustain engagement and improve glycemic targets, particularly in non-insulin-using adults with type 2 diabetes (T2D). The long-term goal of this research is to develop a scalable, patient-centered digital intervention that combines real-time glucose monitoring, digitally delivered education, and virtual coaching to transform diabetes self-management and improve health outcomes. This study evaluates the enhancing dulce digital with CGM-driven personalization, peer support, gamification, and engagement (edge) intervention, which integrates continuous glucose monitoring (CGM)-driven personalized messaging, virtual peer health coaching, and gamification to address the GAP in sustained engagement and real-time glycemic feedback. This research serves as the first step toward achieving the long-term goal by rigorously testing edge's effectiveness in improving clinical and behavioral outcomes and understanding its implementation potential in primary care settings. In aim 1A, we will assess the effectiveness of edge compared to dulce digital in improving clinical outcomes, including HBA1C, CGM metrics, and medication dosage, through a randomized controlled trial of 262 non-insulin-using adults with T2D, with data collected at baseline, 6 months, and 12 months. In aim 1B, we will evaluate patient-reported outcomes, such as diabetes distress, self-care behaviors, and quality of life, using validated surveys to measure changes at the same time points. In aim 2 we will assess the implementation and sustainability of edge using the RE-aim framework, while leveraging multimodal data (CGM, EMA, wearables, ehrs) analyzed with machine learning methods to identify behavioral patterns and predictors of glycemic improvement. Together, these aims will provide strong evidence that personalized, data-driven interventions can improve clinical outcomes, patient engagement, and scalability of diabetes self-management programs. The findings are expected to improve diabetes care and health system performance on hedis metrics, and deliver innovative, scalable solutions for primary care settings. In addition to improving glycemic targets, edge's integration of peer coaching, gamification, and AI-driven analytics offers unique advantages in addressing barriers to patient engagement and personalization in diabetes care. By demonstrating the effectiveness of edge, this research will advance the field of digital health by laying the foundation for future large-scale, data-driven interventions that optimize diabetes outcomes and care delivery. This study pushes the boundaries of diabetes management by combining proven digital education with advanced technologies and multimodal machine learning data analytics, offering new alternatives to traditional approaches and transforming the way self-management is delivered in individuals with T2D.