A Survey of Medical Ethics Education at U.S. and Canadian Medical Schools
Bibliographic record
Abstract
PURPOSE: To assess the format, content, method, and placement of medical ethics education in medical schools; the faculty and curricular resources and institutional structure and support of medical ethics; and the perceptions of ethics education among deans of medical education and medical ethics course directors at U.S. and Canadian medical schools. METHOD: Two questionnaires were mailed to 125 U.S. medical schools and 16 Canadian schools: one to be completed by the deans of medical education and one to be completed by the medical ethics course director. Descriptive statistics were used to compare responses. RESULTS: In all, 123 (87%) deans and 91 (64%) course directors responded, providing information about 91 schools (six Canadian). All responding institutions offered some formal instruction in medical ethics, and among these, 71 (78%) incorporated ethics into required preclinical courses. The primary pedagogic course structure was small-group discussion and the primary pedagogic method was case discussions. One-fifth of schools provided no funding for ethics teaching, and 47 (52%) did not fund curricular development in ethics. Institutions with a dedicated ethics faculty member were twice as likely to have a mandatory introductory ethics course (64% versus 32%, p <.05). The primary obstacles to ethics education were thought to be a lack of time in the curriculum, a lack of qualified teachers, and a lack of time in faculty schedules. CONCLUSIONS: Within a few decades the number of U.S. and Canadian medical schools requiring medical ethics has increased. Nevertheless, significant variation in the content, method, and timing of ethics education suggests consensus about curricular content and pedagogic methods remains lacking. Further progress in ethics education may depend on institutions' willingness to devote more curricular time and funding to medical ethics.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".