Perceptions and intentions toward medical assistance in dying among Canadian medical students
Bibliographic record
Abstract
BACKGROUND: Medical assistance in dying (MAID) was legalized in Canada in 2016. As of July 2017, approximately 2149 patients have accessed MAID. There remains no national-level data on the perspectives of future physicians about MAID or its changing legal status. We provide evidence from a national survey of Canadian medical students about their opinions, intentions, and concerns about MAID. METHODS: From October 2016 to July 2017, we distributed an anonymous online survey to all students at 15 of Canada's 17 medical schools. The survey collected data on respondent socio-demographic characteristics, features of their medical education, intentions for medical practice, and perspectives on MAID. We analyzed responses using univariate descriptive and stepwise multivariate logistic regression. RESULTS: In 1210 completed surveys, 71% of respondents reported being willing to provide MAID under a legal framework that permits it. Non-religious respondents reported greater willingness to participate in MAID than respondents of any religious affiliation (p < 0.001). Frequency of religious attendance was inversely associated with willingness to provide MAID (p < 0.001). Medical students born in Québec were more willing to provide MAID than respondents from other provinces (OR 2.21; p < 0.001). Age, sex, socioeconomic status, year of medical study, previous academic major, and rural/urban city of birth were not associated with willingness to provide MAID. CONCLUSION: As the current class of medical students becomes the first cohort of new physicians to enter Canada's changing medical and legal landscape around MAID, our findings inform the public debate by examining attributes associated with support or opposition to the practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".