Medical assistance in dying for people living with mental disorders: a qualitative thematic review
Bibliographic record
Abstract
BACKGROUND: Medical assistance in dying (MAiD) sparks debate in several countries, some of which allow or plan to allow MAiD where a mental disorder is the sole underlying medical condition (MAiD-MD). Since MAiD-MD is becoming permissible in a growing number of jurisdictions, there is a need to better understand the moral concerns related to this option. Gaining a better understanding of the moral concerns at stake is a first step towards identifying ways of addressing them so that MAiD-MD can be successfully introduced and implemented, where legislations allow it. METHODS: Thus, this article aims (1) to better understand the moral concerns regarding MAiD-MD, and (2) to identify potential solutions to promote stakeholders' well-being. A qualitative thematic review was undertaken, which used systematic keyword-driven search and thematic analysis of content. Seventy-four publications met the inclusion criteria. RESULTS: Various moral concerns and proposed solutions were identified and are related to how MAiD-MD is introduced in 5 contexts: (1) Societal context, (2) Healthcare system, (3) Continuum of care, (4) Discussions on the option of MAiD-MD, (5) MAiD-MD practices. We propose this classification of the identified moral concerns because it helps to better understand the various facets of discomfort experienced with MAiD-MD. In so doing, it also directs the various actions to be taken to alleviate these discomforts and promote the well-being of stakeholders. CONCLUSION: The assessment of MAiD-MD applications, which is part of the context of MAiD-MD practices, emerges as the most widespread source of concern. Addressing the moral concerns arising in the five contexts identified could help ease concerns regarding the assessment of MAiD-MD.
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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 | 0.031 | 0.228 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".