Perceptions of interprofessional collaboration among University of Montreal’s pediatric residents rotating through the Pediatric Intensive Care Unit: Mixed-method analysis of the current situation and recommendations for future innovative teaching-learning activities
Bibliographic record
Abstract
Background Interprofessional collaboration is essential for healthcare workers in intensive care units. To collaborate effectively, doctors must be trained in medical schools. Unfortunately, training is uneven across residency programs. The objectives of this project were to explore the collaborative training needs of pediatric residents at the University of Montreal program and then make recommendations for the development of future training activities. Methods This was a mixed-methods study. Results Our study explored perceptions of collaboration between residents and their colleagues (doctors, nurses, respiratory therapists, pharmacists), and the barriers and facilitators to training, particularly during the pediatric intensive care rotation. Conclusions This study provides helpful and insightful suggestions for fostering interprofessional education among pediatric trainees. Interventions must be implemented locally to better clarify the role of the resident within the team, provide more support to physician teachers, and integrate the rest of the professional team into training and assessment.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".