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Binge eating automated measure (BEAM): development of a novel self-report measure for binge eating
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Binge eating automated measure (BEAM): development of a novel self-report measure for binge eating

Lauren Carleton Taylor
Master of Science (M.S.), Drexel University
Jan 2025
DOI:
https://doi.org/10.17918/00010805
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Abstract

Assessment Binge Eating Eating Disorders
Background: The accurate identification and categorization of binge eating (BE) in those with overweight and obesity is critically important in several respects, including preventative screening, treatment, and research assessment. Clinical interviews, especially the Eating Disorder Examination (EDE), are currently held as the gold-standard for BE assessment due to the ability of these measures to gain a comprehensive understanding of the individual's experience and make a reliable determination on the presence or absence of BE. However, the EDE requires a substantial amount of time for an expert clinician to reliably administer, making the EDE impractical for many settings. Given the limitations of traditional clinical interview, a self-report measure is a promising alternative. Some attempts have been made to develop self-report measures to assess for BE, though each measure has limitations and improvement in validity is still needed. A self-report tool that utilizes vignettes, survey logic, and an automated binge size assessment could retain the benefits of a clinical interview, without the need for trained clinician time. The aim of the current study was to conduct preliminary development of such a measure using an iterative methodology. Methods: To develop preliminary vignettes, we: a) completed an in-depth review of current literature, self-report measures, and clinical interviews that assess BE, b) listened to 50 de-identified EDE audiotapes, and c) interviewed 6 experienced EDE assessors. The preliminary vignettes were validated by recruiting and interviewing 26 individuals who experience overweight and obesity. Of those 26 participants, 9 did not experience BE and 16 did experience BE as determined by the binge module of the EDE. A self-report version of the EDE's binge size assessment was developed and survey logic was developed. Results: Through the review of existing literature, self-report measures, and clinical interviews, that assess BE clinical categories of LOC and base vignettes were developed. After reviewing EDE audios, the vignettes were revised to more accurately depict the experience of those with BE. Vignettes were further added and refined to accurately depict LOC+ and LOC- eating through interviewing trained EDE assessors. Next, these preliminary vignettes were validated through interviewing those with and without BE. Through qualitative coding, we identified themes of eating episodes that were endorsed by those with and without BE. Vignettes with themes that were not endorsed by at least one-third of participants were removed to ease participant burden and themes that were not captured by previously developed vignettes were added (e.g., eating due to boredom, feeling physically exhausted after the eating episode). Conclusion: The current study successfully accomplished its aim of developing a new method for assessing the presence and severity of BE. The BEAM is the first self-report measure for BE to utilize vignettes, survey logic, and an automated version of the EDE's binge size assessment. This measure holds the potential to be a valuable tool to clinical and research groups who need to assess for BE but do not possess the staffing hours to reliable administer a clinical interview like the EDE. While the BEAM was developed using a rigorous iterative methodology and holds the potential to be a reliable and valid method for assessing BE, the measure requires additional psychometric assessment before it can be disseminated. Future research should complete this psychometric assessment to determine the reliability and validity of the measure.

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