Experience of Community Physicians Who Provide Medical Assistance in Dying: A Qualitative Analysis
Bibliographic record
Abstract
Aims: Since decriminalization in 2016, medical assistance in dying (MAiD) has transformed the landscape of end-of-life care in Canada. This study explored the experiences of community family physicians who provide MAiD.\nMethods: Using a qualitative study design and phenomenological approach, semi-structured interviews were conducted of twelve physician providers in Southwestern Ontario. The transcripts were coded and inductively analyzed for overarching themes.\nFindings: At the individual level, providers felt a profound sense of purpose. At the local level, participants reflected on the practical challenges encountered. At the system level, participants described the critical role of organizational support structures and the effects of legislative changes.\nConclusions: The results contribute to a deeper understanding of the MAiD experience in Canada, fostering ongoing discourse in this complex and evolving field of healthcare. The findings also hold the potential to impact decisions concerning upcoming training initiatives, policy formulation and legislative efforts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".