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. 2023 Feb;56(2):470-477.
doi: 10.1002/eat.23864. Epub 2022 Nov 30.

Optimizing digital health technologies to improve therapeutic skill use and acquisition alongside enhanced cognitive-behavior therapy for binge-spectrum eating disorders: Protocol for a randomized controlled trial

Adrienne S Juarascio  1   2 , Emily K Presseller  1   2 , Claire Trainor  1   2 , Sneha Boda  2 , Stephanie M Manasse  2 , Paakhi Srivastava  2 , Evan M Forman  1   2 , Fengqing Zhang  1
Affiliations

Optimizing digital health technologies to improve therapeutic skill use and acquisition alongside enhanced cognitive-behavior therapy for binge-spectrum eating disorders: Protocol for a randomized controlled trial

Adrienne S Juarascio et al. Int J Eat Disord. 2023 Feb.

Abstract

Objective: Adjunctive mobile health (mHealth) technologies offer promise for improving treatment response to enhanced cognitive-behavior therapy (CBT-E) among individuals with binge-spectrum eating disorders, but research on the key "active" components of these technologies has been very limited. The present study will use a full factorial design to (1) evaluate the optimal combination of complexity of two commonly used mHealth components (i.e., self-monitoring and microinterventions) alongside CBT-E and (2) test whether the optimal complexity level of these interventions is moderated by baseline self-regulation. Secondary aims of the present study include evaluating target engagement associated with each level of these intervention components and quantifying the component interaction effects (i.e., partially additive, fully additive, or synergistic effects).

Method: Two hundred and sixty-four participants with binge-spectrum eating disorders will be randomized to six treatment conditions determined by the combination of self-monitoring condition (i.e., standard self-monitoring or skills monitoring) and microinterventions condition (i.e., no microinterventions, automated microinterventions, or just-in-time adaptive interventions) as an augmentation to 16 sessions of CBT-E. Treatment outcomes will be measured using the Eating Disorder Examination and compared by treatment condition using multilevel models.

Results: Results will clarify the "active" components in mHealth interventions for binge eating.

Discussion: The present study will provide critical insight into the efficacy of commonly used digital intervention components (i.e., skills monitoring and microinterventions) alongside CBT-E. Furthermore, results of this study may inform personalization of digital intervention intensity based on patient profiles of self-regulation.

Public significance: This study will examine the relative effectiveness of commonly used components of application-based interventions as an augmentation to cognitive-behavioral therapy for binge eating. Findings from this study will inform the development of an optimized digital intervention for individuals with binge eating.

Trial registration: ClinicalTrials.gov NCT05473013.

Keywords: binge eating; binge eating disorder; bulimia nervosa; enhanced cognitive behavioral therapy; mHealth; technology; treatment outcome.

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Conflict of interest statement

Conflict of Interest Disclosure: The authors have no conflicts of interest to disclose.

References

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