Canadian medical schools’ preclerkship paediatric clinical skills curricula: How can we improve?
Bibliographic record
Abstract
BACKGROUND: Little is known about how Canadian medical schools teach paediatric clinical skills (history and physical exam) to preclerkship students, or its cost to the institutions. METHODS: Clinical skills program directors from all 17 Canadian medical schools were contacted to complete a questionnaire focused on teaching methods, and barriers/strengths of their Preclerkship Paediatric Clinical Skills program. RESULTS: Seventeen schools (100% response rate) participated. Seven schools (41%) do not introduce paediatric clinical skills until the second year of medicine. Half of the schools (53%) dedicate <10 total hours to preclerkship paediatric clinical skills. Fifty-nine per cent have ≤6 total hours of hands-on paediatric patient interaction (real or simulated). Medical students were least likely to be exposed to the infant age group (age 1 to 24 months). Twelve schools (71%) used simulated parent/child dyads. The most significant barriers identified by programs were limited time for sessions and patient availability. We describe one sample medical school's simulated parent/paediatric patient program where every student has hands-on learning with paediatric patients of all ages (program cost $938/student). DISCUSSION: This study is the first to summarize Canadian preclerkship paediatric clinical skills programs, among which there is great variability and commonly experienced barriers. Many students are not being exposed to all age groups of paediatric patients before their clerkship years. Medical schools can use this information to strengthen this important and challenging aspect of the curriculum, while being mindful of its fiscal implications.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".