Can Pediatric Endoscopists Accurately Assess Their Clinical Competency? A Comparison Across Skill Levels
Bibliographic record
Abstract
BACKGROUND: Assessment is critical to support pediatric endoscopy training. Although trainee engagement in assessment is encouraged, the use of self-assessment and its accuracy among pediatric endoscopists is not well described. We aimed to determine the self-assessment accuracy of novice, intermediate, and experienced pediatric endoscopists. METHODS: Novice (performed <50 previous colonoscopies), intermediate (50-500), and experienced (>1000) pediatric endoscopists from 3 North American academic teaching hospitals each performed a clinical colonoscopy. Endoscopists were assessed in real-time by 2 experienced endoscopists using the Gastrointestinal Endoscopy Competency Assessment Tool for Pediatric Colonoscopy (GiECATKIDS). In addition, participants self-assessed their performance using the same instrument. Self-assessment accuracy between the externally assessed and self-assessed scores was evaluated using absolute difference scores, intraclass correlation coefficients, and Bland-Altman analyses. RESULTS: Forty-seven endoscopists participated (21 novices, 16 intermediates, and 10 experienced). Overall, there was moderate agreement of externally assessed and self-assessed GiECATKIDS total scores with an intraclass correlation coefficient of 0.72 (95% confidence interval, 0.55-0.83). The absolute difference scores among the 3 groups were significantly different (P = 0.005), with experienced endoscopists demonstrating a more accurate self-assessment compared to novices (P = 0.003). Bland-Altman plots revealed that novice endoscopists' self-assessed scores tended to be higher than their externally assessed scores, indicating they overestimated their performance. CONCLUSIONS: We found that endoscopic experience was positively associated with self-assessment accuracy among pediatric endoscopists. Novices were inaccurate in assessing their endoscopic competence and were prone to overestimation of their performances. Our findings suggest novices may benefit from targeted interventions aimed at improving their insight and self-awareness.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".