ArticleThe International journal of eating disorders2025
Distinct Patterns of Dynamical Regulation in Passive Sensor Data Following Binge and Purge Behaviors.
Article in The International journal of eating disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
- Integrating Artificial Intelligence and Smartphone Technology to Enhance Personalized Assessment and Treatment for Eating Disorders.The International journal of eating disorders · 2025Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundBinge eating is a cardinal symptom of binge-eating disorder (BED) and bulimia nervosa (BN), while recurrent purging is specific to BN (American Psychiatric Association, 2022). These behaviors are associated with health consequences (e.g., gastrointestinal, cardiovascular, and metabolic problems; Sheehan & Herman, 2015). The distress-regulating effects of binge and purge behaviors are important targets for intervention. The aims of this examination were to characterize the regulatory dynamics of heart rate (HR) and physical activity following binge and purge behaviors, test whether these dynamics were different from control periods, and test whether these dynamics were different from one another.
methodsA subsample of participants (n = 295) from the BEGIN study reported binges and purges using the Recovery Record app for 30 days; Apple Watch devices were used to measure steps and HR. Regulatory dynamics of the velocity and acceleration of HR and steps were modeled using multilevel models.
resultsRegulatory dynamics of HR were different following binges (dysregulated) relative to control periods (homeostatic) and relative to those following purges (mixed). Regulatory dynamics of steps were significantly different following binges (dysregulated) and following purges (homeostatic) relative to control periods (different type of homeostatic) as well as with respect to one another.
conclusionsRegulatory dynamics of HR and physical activity can be captured using smart watches and modeled using systems models. Regulatory dynamics of HR have promise as a marker of treatment progress in reducing binge eating frequency, and regulatory dynamics of steps have promise as a digital marker of binge and purge behaviors. PUBLIC SIGNIFICANCE: Measures from commercial smart watches are able to detect changes in the complex patterning of heart rate and physical activity following binge eating and purging for individuals with BED. Given the cycle of past dynamics relating to future dynamics, the results suggest that these commercial devices could be useful for tracking treatment progress in reducing binge and purge frequency.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.