The impact of COVID-19 on the experiences of patients and their family caregivers with medical assistance in dying in hospital
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic and its containment measures have drastically impacted end-of-life and grief experiences globally, including those related to medical assistance in dying (MAiD). No known qualitative studies to date have examined the MAiD experience during the pandemic. This qualitative study aimed to understand how the pandemic impacted the MAiD experience in hospital of persons requesting MAiD (patients) and their loved ones (caregivers) in Canada. METHODS: Semi-structured interviews were conducted with patients who requested MAiD and their caregivers between April 2020 and May 2021. Participants were recruited during the first year of the pandemic from the University Health Network and Sunnybrook Health Sciences Centre in Toronto, Canada. Patients and caregivers were interviewed about their experience following the MAiD request. Six months following patient death, bereaved caregivers were interviewed to explore their bereavement experience. Interviews were audio-recorded, transcribed verbatim, and de-identified. Transcripts were analyzed using reflexive thematic analysis. RESULTS: Interviews were conducted with 7 patients (mean [SD] age, 73 [12] years; 5 [63%] women) and 23 caregivers (mean [SD] age, 59 [11] years; 14 [61%] women). Fourteen caregivers were interviewed at the time of MAiD request and 13 bereaved caregivers were interviewed post-MAiD. Four themes were generated with respect to the impact of COVID-19 and its containment measures on the MAiD experience in hospital: (1) accelerating the MAiD decision; (2) compromising family understanding and coping; (3) disrupting MAiD delivery; and (4) appreciating rule flexibility. CONCLUSIONS: Findings highlight the tension between respecting pandemic restrictions and prioritizing control over the dying circumstances central to MAiD, and the resulting impact on patient and family suffering. There is a need for healthcare institutions to recognize the relational dimensions of the MAiD experience, particularly in the isolating context of the pandemic. Findings may inform strategies to better support those requesting MAiD and their families during the pandemic and beyond.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".