Using Continuous Glucose Monitoring to Detect and Intervene on Maintenance Factors for Transdiagnostic Binge Eating Pathology

PROJECT SUMMARY Although CBT is an effective treatment for many individuals with transdiagnostic binge eating, recent systematic reviews and meta-analyses have found that 40-50% of patients with binge eating disorder (BED) and nearly 70% of patients with bulimia nervosa (BN) remain fully or partially symptomatic after a full course of CBT. Reducing rigid dietary restriction is one of the only mechanisms of action that has been consistently identified in treatments for binge eating. In particular, adherence to a regular eating schedule (e.g. eating three meals and one-two snacks per day and not going more than four waking hours without eating) is one of the biggest predictors of treatment success in both BN and BED. Although one of the primary goals of CBT for binge eating is the reduction of dietary restriction (with over 50% of session content dedicated to this goal in most treatment manuals), many patients continue to engage in restrictive eating behaviors during and after treatment, suggesting that CBT is failing to sufficiently improve this clinical target. This pattern of results suggests a critical need both to understand why many individuals fail to improve in existing treatments and to develop new intervention approaches or augmentations that can produce superior treatment outcomes. The primary goal of this STTR Phase 1 application is to develop and pilot an mHealth intervention system (SenseSupport) that can be used as an augmentation to traditional CBT for transdiagnostic binge eating that can better target dietary restriction. Our proposed mHealth intervention system will use continuous glucose monitoring (CGM) to 1) accurately detect dietary restriction as it occurs, 2) accurately detect known risk-factors for a reoccurrence of dietary restriction (e.g. binge eating and self-induced vomiting episodes), 3) deliver real- time push notifications linked to brief CBT-based interventions when dietary restriction, binge eating, or self- induced vomiting is detected, and 4) share objective data on eating behaviors with a treatment provider to enhance the therapeutic work occurring during in-person CBT. In months 0-6, we will collect data from 30 individuals with clinically significant binge eating who will wear a Dexcom G6 CGM for four weeks while electronically tracking all eating behaviors and disordered eating symptoms. While data collection is ongoing, we will also use months 0-6 to the SenseSupport system. During months 7-24, we will conduct a small (n=30) clinical trial using an ABAB design (A= SenseSupport On, B=SenseSupport Off) to test the feasibility, acceptability, and target engagement of the SenseSupport System. Receipt of this award will allow members of PromptWorks, Drexel University, the University of Pennsylvania, and Dexcom to develop an innovative intervention system that we believe can reduce dietary restriction and improve treatment outcomes for individuals with clinically significant binge eating. The proposed system would be the first of its kind for the treatment of eating pathology with high potential to market to the over 42 million individuals who experience clinically significant binge eating in the United States as well as to treatment facilities that could use our tool as a way to augment existing treatment approaches.PROJECT NARRATIVE Although cognitive behavioral therapy (CBT) can be an effective treatment for transdiagnostic binge eating pathology, a large percent of individuals do not experience clinically significant improvements in rigid dietary restriction (a well-established maintenance factor for binge eating) and treatment outcomes suffer as a result. The primary goal of this STTR Phase 1 application is to develop and pilot an mHealth intervention system (SenseSupport) that can be used as an augmentation to traditional CBT for transdiagnostic binge eating that can better target dietary restriction. Our proposed mHealth intervention system will use continuous glucose monitoring to 1) accurately detect dietary restriction as it occurs, 2) accurately detect known risk-factors for a reoccurrence of dietary restriction (e.g. binge eating and self-induced vomiting episodes), 3) deliver real-time push notifications linked to brief CBT-based interventions when dietary restriction, binge eating, or self-induced vomiting is detected, and 4) share objective data on eating behaviors with a treatment provider to enhance the therapeutic work occurring during in-person CBT.