Medical Assistance in Dying for Mental Illness as a Sole Underlying Medical Condition and Its Relationship to Suicide: A Qualitative Lived Experience-Engaged Study: Aide Médicale à Mourir Pour Maladie Mentale Comme Seule Condition Médicale Sous-Jacente et Son Lien Avec le Suicide: Une Etude Qualitative Engagée Dans l’Expérience Vécue
Bibliographic record
Abstract
OBJECTIVE: This lived experience-engaged study aims to understand patient and family perspectives on the relationship between suicidality and medical assistance in dying when the sole underlying medical condition is mental illness (MAiD MI-SUMC). METHOD: = 16.0) participated in qualitative interviews examining perspectives on MAiD MI-SUMC and its relationship with suicide. Audio recordings were transcribed and analysed using reflexive thematic analysis. People with lived experience were engaged in the research process as team members. RESULTS: Four main themes were developed, which were consistent across individuals with mental illness and family members: (a) deciding to die is an individual choice to end the ongoing intolerable suffering of people with mental illness; (b) MAiD MI-SUMC is the same as suicide because the end result is death, although suicide can be more impulsive; (c) MAiD MI-SUMC is a humane, dignified, safe, nonstigmatized alternative to suicide; and (4) suicidality should be considered when MAiD MI-SUMC is requested, but suicidality's role is multifaceted given its diverse manifestations. CONCLUSION: For patient-oriented mental health policy and treatment, it is critical that the voices of people with lived experience be heard on the issue of MAiD MI-SUMC. Given the important intersections between MAiD MI-SUMC and suicidality and the context of suicide prevention, the role that suicidality should play in MAiD MI-SUMC is multifaceted. Future research and policy development are required to ensure that patient and family perspectives guide the development and implementation of MAiD MI-SUMC policy and practice.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".