Empowering trainee fellows today will ensure that we build tomorrow’s leaders in gastroenterology
Bibliographic record
Abstract
Dear Editor, We read with great interest the article by Gardezi et al. exploring the experiences of gastroenterology (GI) fellows across Saudi Arabia.[1] The authors are to be commended for undertaking one of the first national, multiregional surveys of fellowship training, highlighting both progress and persisting gaps in education and mentorship. This work provides valuable insights into a rapidly evolving training landscape. The authors employed a cross-sectional online survey distributed nationwide. The questionnaire was thoughtfully developed and pilot-tested, with responses analyzed using descriptive statistics and thematic analysis. Such methodology offers an efficient way to capture fellows’ perceptions, though reliance on self-reported data introduces subjectivity and recall bias. Importantly, the sample size (n = 54) represents a reasonable proportion of this subspecialty cohort but may not fully reflect the heterogeneity of all training centers, particularly with no representation from the northern region, similar to previous limitations in assessment of Inflammatory bowel disease training.[2] Fellows reported overall moderate to high satisfaction (mean 3.96/5), with strengths including diverse case exposure, structured rotations, and strong endoscopic training. However, significant deficiencies were noted in mentorship (2.78/5), access to advanced therapeutic endoscopy, structured teaching sessions (40.7%), and leadership or research training (≈50%). These findings mirror concerns raised in international surveys, such as variability in advanced endoscopy exposure in the UK[3] and Canada.[4] This study represents the first multiregional survey of GI fellows in Saudi Arabia, capturing both quantitative and qualitative data. The mixed-methods design provides a nuanced picture of training strengths and challenges. By aligning results with the Saudi Commission for Health Specialties (SCFHS) competency framework, the study highlights important areas for national program alignment. As the authors acknowledge, self-perception may not correlate with objective measures of competence. Cross-sectional design precludes assessment of longitudinal training outcomes. Further, anonymity—while ethically sound—prevents center-specific benchmarking that could guide targeted interventions. Finally, the absence of objective procedural logs, simulation exposure data, or faculty perspectives limits triangulation of findings. The findings underscore the urgent need for standardized curricula, structured mentorship frameworks, and equitable access to simulation-based endoscopy training. International models, such as the British Society of Gastroenterology’s national mentorship initiatives and the American Society for Gastrointestinal Endoscopy’s fellows’ programs, could provide adaptable templates. Moreover, embedding leadership and research as mandatory fellowship components would better prepare graduates for academic and administrative roles. We encourage future research to incorporate: Longitudinal assessment of fellows’ outcomes post-graduation (e.g., independent practice readiness, academic productivity). Faculty perspectives to balance trainee-reported data. Objective procedural and competency metrics, potentially integrated into the SCFHS e-portal for real-time monitoring. National benchmarking to ensure consistency across low- and high-volume centers. Gardezi et al. provide a timely contribution to the discourse on gastroenterology training reform in Saudi Arabia. Their findings resonate with global challenges in GI education and should prompt stakeholders to prioritize structured mentorship, simulation, and leadership training. By addressing these gaps, the Kingdom can ensure the next generation of gastroenterologists is both globally competent and locally responsive to healthcare needs. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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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 | 0.007 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.019 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".