ArticleThe International journal of eating disorders2023
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.
Article in The International journal of eating disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.
- Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review.Frontiers in digital health · 2025Pooled it
- The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
objectiveAdjunctive 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).
methodTwo 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.
resultsResults 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.