Extending Medical Aid in Dying to Incompetent Patients: A Qualitative Descriptive Study of the Attitudes of People Living with Alzheimer’s Disease in Quebec
Bibliographic record
Abstract
Background: In Quebec, medical aid in dying (MAiD) is legal under certain conditions. Access is currently restricted to patients who are able to consent at the time of the act, which excludes most people with dementia at an advanced stage. However, recent legislative and political developments have opened the door to an extension of the legislation that could give them access to MAiD. Our study aimed to explore the attitudes of people with early-stage dementia toward MAiD should it become accessible to them. Methods: We used a qualitative descriptive design consisting of eight face-to-face semi-structured interviews with persons living with early-stage Alzheimer’s disease, followed by a thematic analysis of the contents of the interviews. Results and Interpretations: Analysis revealed three main themes: 1) favourable to MAiD; 2) avoiding advanced dementia; and 3) disposition to request MAiD. Most participants anticipated dementia to be a painful experience. The main reasons for supporting MAiD were to avoid cognitive loss, dependence on others for their basic needs, and suffering for both themselves and their loved ones. Every participant said that they would ask for MAiD at some point should it become available to incompetent patients and most wished that it would be legal to access it through a request written before losing capacity. Conclusion: The reasons for which persons with Alzheimer’s disease want MAiD are related to the particular trajectory of the disease. Any policy to extend MAiD to incompetent patients should take their perspective into account.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".