Cross‐Cultural Validation of the Binge Eating Disorder Screener‐7 (BEDS‐7) Across 42 Countries
Bibliographic record
Abstract
Objective: This study aimed to evaluate the reliability and validity of the Binge Eating Disorder Screener-7 (BEDS-7) across 42 countries and 26 languages, assessing its reliability and validity as a screening tool for binge-eating disorder (BED) in diverse cultural contexts. Specifically, it sought to enhance early recognition of BED symptoms in primary care settings globally, contributing to a standardized framework for assessing BED. Method: The International Sex Survey, a cross-sectional online study, was conducted in 42 countries and 26 languages. A diverse community sample of 82,243 participants, aged 18 years or older, completed the BEDS-7 and measures of sexuality, mental health, substance use, and sociodemographic characteristics. Confirmatory factor analyses and tests of measurement invariance were employed to evaluate the reliability and validity of the BEDS-7 across languages, countries, genders, and sexual orientations. Results: The BEDS-7 demonstrated scalar factorial invariance across languages and countries, indicating consistent factor loadings and item intercepts. In contrast, the screener showed residual invariance across gender and sexual orientation groups, supporting its robustness across these demographics. Kruskal–Wallis tests revealed significant differences in BED symptoms across languages, countries, genders, and sexual orientations, with the highest BED scores observed among queer, pansexual, and gender-diverse individuals. The BEDS-7 also demonstrated adequate reliability (Cronbach's alpha > 0.80) and moderate criterion validity. Discussion: The findings provide further evidence of the reliability and validity of the BEDS-7 as a potential screening tool for identifying probable cases of BED globally, facilitating early intervention in primary care settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".