Journal article
Using Continuous Glucose Monitoring to Passively Classify Naturalistic Binge Eating and Vomiting Among Adults With Binge-Spectrum Eating Disorders: A Preliminary Investigation
The International journal of eating disorders, v 57(11), pp 2285-2291
01 Nov 2024
PMID: 39031922
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
ObjectiveBinge eating and self-induced vomiting are common, transdiagnostic eating disorder (ED) symptoms. Efforts to understand these behaviors in research and clinical settings have historically relied on self-report measures, which may be biased and have limited ecological validity. It may be possible to passively detect binge eating and vomiting using data collected by continuous glucose monitors (CGMs; minimally invasive sensors that measure blood glucose levels), as these behaviors yield characteristic glucose responses.MethodThis study developed machine learning classification algorithms to classify binge eating and vomiting among 22 adults with binge-spectrum EDs using CGM data. Participants wore Dexcom G6 CGMs and reported eating episodes and disordered eating symptoms using ecological momentary assessment for 2 weeks. Group-level random forest models were generated to distinguish binge eating from typical eating episodes and to classify instances of vomiting.ResultsThe binge eating model had accuracy of 0.88 (95% CI: 0.83, 0.92), sensitivity of 0.56, and specificity of 0.90. The vomiting model demonstrated accuracy of 0.79 (95% CI: 0.62, 0.91), sensitivity of 0.88, and specificity of 0.71.DiscussionResults suggest that CGM may be a promising avenue for passively classifying binge eating and vomiting, with implications for innovative research and clinical applications.
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Details
- Title
- Using Continuous Glucose Monitoring to Passively Classify Naturalistic Binge Eating and Vomiting Among Adults With Binge-Spectrum Eating Disorders: A Preliminary Investigation
- Creators
- Emily K. Presseller - Drexel University, Psychological and Brain Sciences (Psychology)Elizabeth A. Velkoff - Drexel University, Center for Weight, Eating and Lifestyle Science (WELL) [Historical]Devyn R. Riddle - Drexel University, Center for Weight, Eating and Lifestyle Science (WELL) [Historical]Jianyi Liu - Drexel UniversityFengqing Zhang - Drexel University, Psychological and Brain Sciences (Psychology)Adrienne S. Juarascio - Drexel University, Psychological and Brain Sciences (Psychology)
- Publication Details
- The International journal of eating disorders, v 57(11), pp 2285-2291
- Publisher
- Wiley
- Number of pages
- 7
- Grant note
- Coulter-Drexel Translational Research Partnership Program Hilda and Preston Davis Foundation F31MH131262 / National Institute of Mental Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Mental Health (NIMH)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology); Center for Weight, Eating and Lifestyle Science (WELL) [Historical]
- Web of Science ID
- WOS:001272127900001
- Scopus ID
- 2-s2.0-85198825307
- Other Identifier
- 991021894215604721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Nutrition & Dietetics
- Psychiatry
- Psychology
- Psychology, Clinical