Competency‐Based Assessment Tool for Pediatric Tracheotomy: International Modified Delphi Consensus
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Create a competency-based assessment tool for pediatric tracheotomy. STUDY DESIGN: Blinded, modified, Delphi consensus process. METHODS: Using the REDCap database, a list of 31 potential items was circulated to 65 expert surgeons who perform pediatric tracheotomy. In the first round, items were rated as "keep" or "remove," and comments were incorporated. In the second round, experts were asked to rate the importance of each item on a seven-point Likert scale. Consensus criteria were determined a priori with a goal of 7 to 25 final items. RESULTS: The first round achieved a response rate of 39/65 (60.0%), and returned questionnaires were 99.5% complete. All items were rated as "keep," and 137 comments were incorporated. In the second round, 30 task-specific and seven previously validated global rating items were distributed, and the response rate was 44/65 (67.7%), with returned questionnaires being 99.3% complete. Of the Task-Specific Items, 13 reached consensus, 10 were near consensus, and 7 did not achieve consensus. For the 7 previously validated global rating items, 5 reached consensus and two were near consensus. CONCLUSIONS: It is feasible to reach consensus on the important steps involved in pediatric tracheotomy using a modified Delphi consensus process. These items can now be considered to create a competency-based assessment tool for pediatric tracheotomy. Such a tool will hopefully allow trainees to focus on the important aspects of this procedure and help teaching programs standardize how they evaluate trainees during this procedure. LEVEL OF EVIDENCE: 5 Laryngoscope, 130:2700-2707, 2020.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".