Self-reported experience and competence in core procedures among Canadian pediatric emergency medicine fellowship trainees.
Bibliographic record
Abstract
OBJECTIVE: We sought to determine the frequency with which fellows in accredited Canadian pediatric emergency medicine (PEM) fellowships perform specific procedures, the level of confidence fellows have in their abilities and whether there are differences in self-perceived success between first- and second-year fellows. METHODS: A national survey was developed that focused on 24 PEM procedural skills. The survey asked respondents how many times they had performed these procedures within the past 12 months and within the past 3 years. Respondents were then asked to rate their confidence in successfully performing each of the 24 procedures. RESULTS: Of the 46 surveys sent to PEM fellows, 32 (70%) were returned. Most respondents were in their second year of training and the vast majority had previous training in pediatrics. In order of frequency, the most common procedures performed were closed reduction of fractures, peripheral intravenous insertion, complex laceration repair and endotracheal intubation. Of the surveyed skills, oropharyngeal/nasopharyngeal airway insertion was deemed the most successful (100% success rate for second-year fellows v. 92.5% success rate for first-year fellows, p=0.01). Similarly, second-year fellows had a higher self-perceived success rate for intraosseous line insertion than did first-year fellows (95.0% v. 80.0% for second- and first-year fellows, respectively, p>0.001). CONCLUSION: In surveying PEM trainees across Canada, we have described the frequency and self-perceived success rate for 24 important procedures. This information may be helpful for program directors in evaluating future directions and opportunities for training of their PEM trainees.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".