An Analysis of Public Attitudes toward Medical Assistance in Dying (MAID) and the Associated Safeguards in Canada: A Systematic Review
Bibliographic record
Abstract
Medical Assistance in Dying (MAID) has become a significant topic of public and ethical discourse in Canada since its legalization in 2015 following the Carter v. Canada Supreme Court decision.This systematic review examines public attitudes toward MAID, focusing on the influence of demographic, cultural, and socio-economic factors, as well as perceptions of the safeguards designed to protect vulnerable populations.The review, adhering to PRISMA guidelines, analyzed 13 studies published between 2015 and 2025, including public opinion polls, policy analyses, and qualitative research.Findings indicate strong public support for MAID, driven by principles of autonomy and dignity, with higher approval among younger, secular, and more educated individuals.However, opposition persists, particularly among older, religious, and conservative groups, who cite concerns about the sanctity of life and potential coercion of vulnerable populations.Safeguards, such as independent assessments and waiting periods, are generally viewed positively, though recent legislative changes, including the expansion of eligibility to individuals with mental illness and the removal of the 10-day reflection period, have raised concerns about their adequacy.The review highlights the need for ongoing public engagement, equitable access to healthcare, and transparent policymaking to address ethical dilemmas and ensure MAID aligns with societal values while protecting vulnerable individuals such as the older population, Individuals considering MAID,
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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 | 0.015 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".