Comparing the attitudes of four groups of stakeholders from Quebec, Canada, toward extending medical aid in dying to incompetent patients with dementia
Bibliographic record
Abstract
OBJECTIVE: The Canadian province of Quebec has recently legalized medical aid in dying (MAID) for competent patients who satisfy strictly defined criteria. The province is considering extending the practice to incompetent patients. We compared the attitudes of four groups of stakeholders toward extending MAID to incompetent patients with dementia. METHODS: We conducted a province-wide postal survey in random samples of older adults, informal caregivers of persons with dementia, nurses, and physicians caring for patients with dementia. Clinical vignettes featuring a patient with Alzheimer's disease were used to measure the acceptability of extending MAID to incompetent patients with dementia. Vignettes varied according to the stage of the disease (advanced or terminal) and type of request (written or oral only). We used the generalized estimating equation (GEE) approach to compare attitudes across groups and vignettes. RESULTS: Response rates ranged from 25% for physicians to 69% for informal caregivers. In all four groups, the proportion of respondents who felt it was acceptable to extend MAID to an incompetent patient with dementia was highest when the patient was at the terminal stage, showed signs of distress, and had written a MAID request prior to losing capacity. In those circumstances, this proportion ranged from 71% among physicians to 91% among informal caregivers. CONCLUSION: We found high support in Quebec for extending the current MAID legislation to incompetent patients with dementia who have reached the terminal stage, appear to be suffering, and had requested MAID in writing while still competent.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 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) | 0.002 | 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".