Care considerations in medical assistance in dying for persons with mental illness as the sole underlying medical condition: a qualitative study of patient and family perspectives
Bibliographic record
Abstract
BACKGROUND: Persons with mental illness as their sole underlying medical condition are eligible to access medical assistance in dying (MAiD) in a small number of countries, including Belgium, the Netherlands, Luxemburg and Switzerland. In Canada, it is anticipated that people experiencing mental illness as their sole underlying medical condition (MI-SUMC) will be eligible to request MAiD as of March 17th 2024. To date, few studies have addressed patient and family perspectives on MAiD MI-SUMC care processes. This study aimed to address this gap and qualitatively explore the perspectives of persons with lived experience of mental illness and family members on care considerations during MI-SUMC implementation. METHODS: Thirty adults with lived experience of mental illness and 25 adult family members residing in Ontario participated in this study. To facilitate participant engagement, the semi-structured interview used a persona-scenario exercise to discuss perspectives on MAiD MI-SUMC acceptability and care considerations. Framework analysis was used to inductively analyze data using NVivo 12 Pro. Steps, processes, or other care considerations suggested by the participants were charted in a framework matrix after familiarization with the narratives. Key themes were further identified. A lived-experience advisory group participated in every aspect of this study. RESULTS: Six themes were developed from the patient and family narratives: (1) Raising MAiD MI-SUMC awareness; (2) Sensitive Introduction of MAiD MI-SUMC in goals of care discussions; (3) Asking for MAiD MI-SUMC: a person-focused response; (4) A comprehensive circle of MAiD MI-SUMC care; (5) A holistic, person-centered assessment process; and (6) Need for support in the aftermath of the decision. These themes highlighted a congruence of views between patient and family members and described key desired process ingredients, including a person-centred non-judgmental stance by care providers, inter-professional holistic care, shared decision making, and the primacy of patient autonomy in healthcare decision making. CONCLUSIONS: Family and patient perspectives on the implementation of MAiD MI-SUMC offer important considerations for service planning that could complement existing and emerging professional practice standards. These stakeholders' perspectives will continue to be essential in MAiD MI-SUMC implementation efforts, to better address the needs of diverse communities and inform improvement efforts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".