Eating disorder symptoms, including avoidant/restrictive food intake disorder, in patients with disorders of gut‐brain interaction
Bibliographic record
Abstract
Abstract Background Previous studies show some patients with functional gastrointestinal disorders (disorders of gut‐brain interaction) may be at risk for or already have an eating disorder (ED). Avoidant/restrictive food intake disorder (ARFID) (ED not primarily motivated by body shape/weight concerns) may be particularly relevant but previous studies have been unable to fully apply diagnostic criteria. This study aimed to determine the frequency and nature of the full spectrum of ED symptoms, among adults with disorders of gut‐brain interaction. Methods Adults with disorders of gut‐brain interaction (n = 99, 77.1% female, ages 18–82 years) from academic medical center gastroenterology clinics completed a modified ARFID Canadian Paediatric Surveillance Program Questionnaire, the ED Examination Questionnaire (EDE‐Q), and other self‐report measures of depression, generalized anxiety, and pain interference. Key Results Of the 93 participants who completed the measures, 37 (39.8%) had ARFID symptoms and 12 (12.9%) had clinically significant shape/weight‐motivated ED symptoms (EDE‐Q‐Global ≥4.0). Exploratory comparisons among ARFID, shape/weight‐motivated ED, and no‐ED groups revealed that ARFID symptom presence was associated with lower body mass index (BMI), and shape/weight‐motivated ED presence was associated with higher depression, anxiety, and pain interference. However, the majority (86%) of patients with ARFID symptoms had a BMI >18.5 kg/m2. Conclusions & Inferences The full spectrum of ED symptoms was frequent among patients with disorders of gut‐brain interaction, particularly ARFID symptoms. Further research is needed to understand risk and maintenance factors to inform prevention and intervention efforts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".