What Are the Most Challenging Aspects of Inflammatory Bowel Disease? An International Survey of Gastroenterologists Comparing Developed and Developing Countries
Bibliographic record
Abstract
Background and Aims: As inflammatory bowel disease (IBD) becomes more prevalent, the challenges that gastroenterologists face in managing these patients evolve. We aimed to describe the most important challenges facing gastroenterologists from around the world and compare these between those working in developed and developing countries. Methods: An online questionnaire was developed, and a link distributed to gastroenterologists. Data were analyzed descriptively using Friedman and Wilcoxon matched-pair signed rank tests to compare rankings for responses. Mann-Whitney U tests were used to compare rankings between responses from gastroenterologists from developed and developing countries. Lower scores reflected greater challenges. Results: Of 872 who started, 397 gastroenterologists (45.5%) completed the survey. Respondents represented 65 countries (226 [56.9%] from developed countries). Overall, the challenge ranked most important (smallest number) was increasing IBD prevalence (13.6%). There were significant differences in mean ranking scores for many simple aspects of care for those from developing countries compared to providers from developed countries, such as access to simple IBD treatments (5.52 vs. 6.02, p = 0.01), access to anti-TNF drugs including dose escalation (3.33 vs. 3.93, p < 0.01), access to good stoma care (2.57 vs. 3.03, p < 0.001), access to therapeutic drug monitoring (1.47 vs. 1.84, p < 0.001), and access to care for people from low socioeconomic status (2.77 vs. 3.37, p < 0.001). Conclusions: Increasing IBD prevalence is seen by gastroenterologists as the greatest challenge facing them. There are significant differences between the IBD challenges facing gastroenterologists from developed and developing countries that reflect inequities in access to health care.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".