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Record W4380577676 · doi:10.1186/s12904-023-01191-8

The impact of COVID-19 on the experiences of patients and their family caregivers with medical assistance in dying in hospital

2023· article· en· W4380577676 on OpenAlexafffundabout
Eryn Tong, Rinat Nissim, Debbie Selby, Sally Bean, Elie Isenberg‐Grzeda, Tharshika Thangarasa, Gary Rodin, Madeline Li, Sarah Hales

Bibliographic record

VenueBMC Palliative Care · 2023
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoPrincess Margaret Cancer CentreHealth Sciences CentreUniversity Health Network
FundersCanadian Cancer Society
KeywordsThematic analysisQualitative researchPandemicGriefMedicineCoping (psychology)Family caregiversFamily medicinePsychologyCoronavirus disease 2019 (COVID-19)NursingGerontologyPsychiatryDisease

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.089
GPT teacher head0.400
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes3
Has abstractyes

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