Addressing the competency of breaking bad news: What are Canadian general paediatric residency programs currently doing
Bibliographic record
Abstract
OBJECTIVE: To describe how breaking bad news (BBN) is currently taught in Canadian general paediatric residency programs and the confidence level of fourth year paediatric residents (Ped-PGY4) in BBN and managing end-of-life-care (EOLC). METHODS: A prospective, cross-sectional survey of General Paediatric Residency Program Directors (PDs) and Ped-PGY4s was conducted. RESULTS: When learning to BBN, residents state faculty observation (22/23) and interactive workshops (14/23) are the most helpful, while PDs state interactive workshops (9/16) and deliberate practice (5/16) are ideal. Residents identified a knowledge gap and discomfort with providing anticipatory guidance, and symptom management, including prescribing opioids. CONCLUSIONS: In the era of competency-based medical education, there is an opportunity to create a standardized national curriculum addressing universal competencies related to BBN and EOLC.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".