Medical Assistance in Dying in patients with advanced cancer and their caregivers: a mixed methods longitudinal study protocol
Bibliographic record
Abstract
BACKGROUND: The legal criteria for medical assistance in dying (MAiD) for adults with a grievous and irremediable medical condition were established in Canada in 2016. There has been concern that potentially reversible states of depression or demoralization may contribute to the desire for death (DD) and requests for MAiD. However, little is known about the emergence of the DD in patients, its impact on caregivers, and to what extent supportive care interventions affect the DD and requests for MAiD. The present observational study is designed to determine the prevalence, predictors, and experience of the DD, requests for MAiD and MAiD completion in patients with advanced or metastatic cancer and the impact of these outcomes on their primary caregivers. METHODS: A cohort of patients with advanced or metastatic solid tumour cancers and their primary caregivers will be recruited from a large tertiary cancer centre in Toronto, Ontario, Canada, to a longitudinal, mixed methods study. Participants will be assessed at baseline for diagnostic information, sociodemographic characteristics, medical history, quality of life, physical and psychological distress, attitudes about the DD and MAiD, communication with physicians, advance care planning, and use of psychosocial and palliative care interventions. Measures will subsequently be completed every six months and at the time of MAiD requests. Quantitative assessments will be supplemented by qualitative interviews in a subset of participants, selected using quota sampling methods. DISCUSSION: This study has the potential to add importantly to our understanding of the prevalence and determinants of the DD, MAiD requests and completions in patients with advanced or metastatic cancer and of the experience of both patients and caregivers in this circumstance. The findings from this study may also assist healthcare providers in their conversations about MAiD and the DD with patients and caregivers, inform healthcare providers to ensure appropriate access to MAiD, and guide modifications being considered to broaden MAiD legislation and policy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.042 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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".