An international survey of polypectomy training and assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background and study aims Colonic polypectomy is acknowledged to be a technically challenging part of colonoscopy. Training in polypectomy is recognized to be often inconsistent. This study aimed to ascertain worldwide practice in polypectomy training. Patients and methods An electronic survey was distributed to endoscopic trainees and trainers in 19 countries asking about their experiences of receiving and delivering training. Participants were also asked about whether formal polypectomy training guidance existed in their country. Results Data were obtained from 610 colonoscopists. Of these responses, 348 (57.0 %) were from trainers and 262 (43.0 %) from trainees; 6.6 % of trainers assessed competency once per year or less often. Just over half (53.1 %) of trainees had ever had their polypectomy technique formally assessed by any trainer. Approximately half the trainees surveyed (51.1 %) stated that the principles of polypectomy had only ever been taught to them intermittently. Of those trainees with the most colonoscopy experience, who had performed over 500 procedures, 48.2 % had had training on removing large polyps of over 10 mm; 46.2 % (121 respondents) of trainees surveyed held no record of the polypectomies they had performed. Only four of the 19 countries surveyed had specific guidelines on polypectomy training. Conclusions A significant number of competent colonoscopists have never been taught how to perform polypectomy. Training guidelines worldwide generally give little direction as to how trainees should acquire polypectomy skills. The learning curve for polypectomy needs to be defined to provide reliable guidance on how to train colonoscopists in this skill.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it