ArticleClinical psychological science : a journal of the Association for Psychological Science2025
Relationship Between Intensive Passive Data Signals and Patterns of Binge-Eating Behaviors: From a Dynamical-System Approach.
Article in Clinical psychological science : a journal of the Association for Psychological Science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Detecting Binge Eating Risk With Naturalistic Data and Machine Learning: A Comparative Observational Study.The International journal of eating disorders · 2026Observational
- Distinct Patterns of Dynamical Regulation in Passive Sensor Data Following Binge and Purge Behaviors.The International journal of eating disorders · 2025Article
- Ecological momentary interventions for eating disorders: a systematic review of the nascent science and recommendations for future research.Journal of eating disorders · 2025Article
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Authors and funding
11 authors.
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Abstract
In this study, we investigate using passive data, specifically, heart rate and actigraphy, for individuals with binge-type eating disorders such as bulimia nervosa (BN) and binge-eating disorder (BED). By applying dynamical-system theory and incorporating advancements in technology-based health care, we explored the relationship between passive data patterns as potential indicators of binge-eating episodes. Over 30 days, 1,019 participants with BN or BED symptoms used the Recovery Record app on iPhone and Apple Watches for real-time eating-behavior logging. Apple Watches simultaneously recorded heart rate and actigraphy. Results show no marked difference in heart and step averages 2 hr before a binge versus a control period. However, significant momentum and stability differences emerged when examining the changing dynamics leading up to a binge event. These findings suggest that the stability of step, rather than their average value, may serve as a detectable indicator of approaching binge events.
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Registered trials
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