Incorporating CanMEDS and subspecialty training into paediatric residency programs: Why are we still deficient?
Bibliographic record
Abstract
BACKGROUND: The Royal College of Physician and Surgeons of Canada mandates that paediatric training programs in Canada incorporate subspecialty training and the teaching and evaluation of the seven CanMEDS roles into their curriculum. The literature suggests that newly practicing paediatricians feel inadequately prepared in many subspecialties and CanMEDS roles. HYPOTHESIS: That either current training programs underestimate the importance of these areas for future practice, or that residents themselves feel that these areas are less important. METHOD: An online survey of Canadian paediatric residents and paediatric residency program directors was conducted to determine their views on various subspecialty areas and CanMEDS roles. RESULTS: Fourteen of 16 Canadian paediatric programs participated, and 127 of 486 (26%) paediatric residents completed the survey. Overall, trainees were satisfied with their current training (86%), and 90% believed they would be adequately prepared for independent practice. Forty-six residents (40%) believed training programs place less importance on 10 of the subspecialties that newly practicing paediatricians felt less comfortable with (from a previous study conducted in 2006). However, at least 25% of residents themselves placed less importance on nine of these 10 areas. Residents also place less importance on two CanMEDS competencies which practicing paediatricians felt less comfortable with, including the medical aspects of palliative care (medical expert) and managing an efficient office practice (manager). CONCLUSIONS: Residents and programs place less importance on specific areas of paediatric training, thus creating potential deficiencies in graduating paediatricians. Promotion of these topics during training may better prepare residents for future practice.
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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 | 0.014 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".