Providing medically assisted dying in Canada: a qualitative study of emotional and moral impact
Bibliographic record
Abstract
PURPOSE: Medical assistance in dying (MAiD) in Canada places the medical provider at the centre of the process. The MAiD provider holds primary responsibility for determining eligibility and becomes acquainted with patients' inner desires and expressions of suffering. This is followed by the MAiD procedure of administering the lethal agent and being present at the death of eligible patients. We report participants' perceptions of the emotional and moral impacts of this role. METHODOLOGY: Two years after MAiD was legalised in Canada, 22 early-adopting physician providers were interviewed. Data were examined using both phenomenological analysis and a novel ChatGPT-enhanced analysis of an anonymised subset of interview excerpts. FINDINGS: Participants described MAiD as emotionally provocative with both challenges and rewards. Providers expressed a positive moral impact when helping to optimise a patient's autonomy and moral comfort with their role in relieving suffering. Providers experienced tensions around professional duty and balancing self with service to others. Personal choice and patient gratitude enhanced the provider experience, while uncertainty and conflict added difficulty. CONCLUSIONS: Participants described MAiD provision as strongly aligned with a patient-centred ethos of practice. This study suggests that, despite challenges, providing MAiD can be a meaningful and satisfying practice for physicians. Understanding the emotional and moral impact and factors that enhance or detract from the providers' experience allows future stakeholders to design and regulate assisted dying in ways congruent with the interests of patients, providers, families and society.
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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 | 0.006 | 0.015 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".