Breaking Bad News: Impact of a Continuing Medical Education Workshop
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of an interactive continuing medical education workshop designed to help physicians in breaking bad news to their patients. METHODOLOGY: Analysis of post-workshop questionnaires from 539 physicians assessing the retention of the key concepts and the perception of the potential impact of the workshop on their practice immediately after the workshop and six months later. RESULTS: The most significant concepts retained by the respondents are: the need to take into consideration the whole patient (42.7% post-workshop and 45.6% of follow-up responses), the need to be prepared for the consultation (11.6% and 15%), the importance of better guiding the interview (18.8% and 13.6%), and the value of taking more time during the consultation (5.8% and 8.3%). Analysis of paired responses on the post-workshop and the follow-up questionnaires shows that 35% of the concepts retained are identical. CONCLUSION: The majority of physicians retained the key concepts, both immediately following the workshop and in the longer term.
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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 | 0.012 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".