Physicians’ moral distinctions between medical assistance in dying (MAiD) and withdrawing life-sustaining treatment in Canada: a qualitative descriptive study
Bibliographic record
Abstract
BACKGROUND: Medical assistance in dying (MAiD) was legalized in Canada following the Carter v. Canada ruling of 2015. In spite of legalization, the ethics of MAiD remain contentious. The bioethical literature has attempted to differentiate MAiD from withdrawing life-sustaining treatment (WLT) in an effort to examine the nature of the moral difference between the two. However, this research has often neglected the firsthand experiences of the clinicians involved in these procedures. By asking physicians if they perceive the major bioethical accounts as clinically useful, we seek to distinguish between aspects of the contemporary bioethical landscape which are useful at the bedside and those which are divorced from the realities faced by clinicians. METHODS: We applied a qualitative descriptive approach to explore physicians' experiences and bioethical distinctions in providing MAiD and WLT. RESULTS: Semi-structured interviews were conducted with 21 physicians, and the transcripts were thematically analyzed to identify common patterns and divergences in their perspectives. Three core themes were found: (1) consensus on MAiD's moral equivalence with WLT despite differences between the practice, (2) discord regarding the use of the term 'killing', and (3) disjuncture between bioethical debates and practice. Theme 1 comprised of three sub-themes: (1.1) no moral difference between MAiD and WLT, (1.2) physician versus underlying medical condition as cause of death, and (1.3) relief of suffering. CONCLUSIONS: In order to have practical utility for clinical practice, it is essential for bioethicists to engage in dialogue with patients and their medical providers pursuing MAiD or WLT. Theoretical debates that are divorced from the realities of terminal illness do not assist physicians with navigating the ethical terrain of ending a patient's life. This research captures meaningful accounts regarding MAiD and WLT that is rooted in the lived experience of the providers of these services in order for bioethical debates to have substantive impact in clinical practice and in legislation surrounding future health policies.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.028 | 0.023 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| 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".