Systematic Review and Meta‐Analysis: Examining the Psychometric Evaluations of Disordered Eating Scales in Adults Living With Gastrointestinal Conditions
Bibliographic record
Abstract
ABSTRACT Background The scales used to assess disordered eating are often not validated in adults living with gastrointestinal conditions (i.e., gastrointestinal populations). This systematic review and meta‐analysis aimed to examine the psychometric evaluations (i.e., assessments of reliability and validity) of disordered eating scales in adult gastrointestinal populations and quantify the prevalence of disordered eating in both gastrointestinal and non‐gastrointestinal populations. Methods We conducted a search of observational studies up to May 2024 that measured disordered eating using a scale in adults with a gastrointestinal condition. Psychometric evaluations of the scales were narratively reviewed. Prevalence rates of disordered eating were pooled using a random‐effects meta‐analysis, and risk of bias was assessed using an adapted Newcastle Ottawa Scale. Key Results Among 29 studies (overall medium risk of bias), 23 reported prevalences of disordered eating in gastrointestinal populations, and eight of these studies also reported prevalences in non‐gastrointestinal populations. Only one out of 10 scales was developed and psychometrically evaluated in gastrointestinal populations, and 11 studies reported internal consistency (range α = 0.63 to α = 0.95). The prevalence of disordered eating was 33.2% ( p < 0.001; 95% confidence interval: 0.25–0.41; I 2 = 97.34%) in gastrointestinal populations and 21.0% ( p < 0.001; 95% confidence interval: 0.09–0.32; I 2 = 97.41%) in non‐gastrointestinal populations. Subgroup analyses showed consistently high heterogeneity. Conclusions and Inferences The utilisation of current disordered eating scales for adults living with gastrointestinal conditions should be undertaken with caution, and there is a need for disordered eating scales to be developed and validated in this population.
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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 | 0.034 | 0.101 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".