Searching for relief from suffering: A patient-oriented qualitative study on medical assistance in dying for mental illness as the sole underlying medical condition
Bibliographic record
Abstract
Medical assistance in dying (MAiD) was introduced into Canadian legislation in 2016. Mental illness as the sole underlying medical condition (MI-SUMC) is excluded from eligibility; this is expected to change in 2024. Incurability, intolerable suffering, capacity to make healthcare decisions, and suicidality have been publicly debated in connection with mental illness. Few studies have explored the views of persons with mental illness on the introduction and acceptability of MAiD MI-SUMC; this study aimed to fill this gap. Thirty adults, residing in Ontario, Canada, who self-identified as living with mental illness participated. A semi-structured interview including a persona-scenario exercise was designed to discuss participants' views on MAiD MI-SUMC and when it could be acceptable or not. Reflexive thematic analysis was used to inductively analyze data. Codes and themes were developed after extensive familiarization with the dataset. A lived-experience advisory group was engaged throughout the study. We identified six themes: The certainty of suffering; Is there a suffering threshold to be met? The uncertainty of mental illness; My own limits, values, and decisions; MAiD MI-SUMCas acceptable when therapeutic means, and othersupports, have been tried to alleviate long-term suffering; and Between relief and rejection. These themes underline how the participants' lived experience comprised negative impacts caused by long-term mental illness, stigma, and in some cases, socioeconomic factors. The need for therapeutic and non-therapeutic supports was highlighted, along with unresolved tensions about the links between mental illness, capacity, and suicidality. Although not all participants viewed MAiD MI-SUMC as acceptable for mental illness, they autonomously embraced limits, values, and decisions of their own along their search for relief. Identifying individual and contextual elements in each person's experience of illness and suffering is necessary to understand diverse perspectives on MAiD MI-SUMC.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".