Cultural Perspectives on the Efficacy and Adoption of the Crohn’s Disease Exclusion Diet across Diverse Ethnicities: A Case-Based Overview
Bibliographic record
Abstract
BACKGROUND: The Crohn's Disease Exclusion Diet (CDED) is a whole-foods regimen that has demonstrated efficacy in inducing remission among children and adults with mild-to-moderate disease. While initial studies predominantly originated from Israel, recent years have witnessed the expansion of experiences to diverse cultures, culminating in the recognition of CDED in the latest ESPEN guidelines. However, implementing dietary therapy poses significant challenges across various cultures, necessitating adaptations. AIM AND METHODS: This case-based study aims to present the collective experience from different cultures, shedding light on the encountered challenges and the corresponding solutions devised to surmount them by convening healthcare providers (dietitians and physicians across six countries and eight cultural settings) with extensive experience in utilizing the CDED. RESULTS AND CONCLUSIONS: Our findings underscore the efficacy of CDED across diverse cultural contexts and emphasize the pivotal role of dietitians in tailoring the diet to accommodate patients' cultural behaviors and traditions. We highlight challenges encountered and delineate strategies for overcoming them by customizing the diet and offering tailored guidance. Additionally, we provide insights into implementing CDED in various regions through adjusted recipes and personalized counseling from dietitians. This study contributes to the growing body of literature on CDED, and offers practical guidance for its effective adoption in diverse cultural 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".