How initial policy responses to COVID-19 contributed to shaping dying at home preferences and care provision: key informant perspectives from Canada
Bibliographic record
Abstract
OBJECTIVES: In response to COVID-19's first wave, provincial governments rapidly implemented several public health directives, including isolation measures and care facility visitor restrictions, which profoundly affected healthcare delivery at the end of life and dying experiences and perceptions. The objective of this study was to identify implications of early policy changes for dying at home. METHODS: Analysis of interviews with 29 key informants with expertise in the policy and practice context of dying at home and care for those dying at home was conducted as part of a larger mixed-methods study on dying at home in Canada. RESULTS: Initial pandemic policy responses, especially visitor restrictions and limitations to home care services, shaped dying at home in relation to three themes: (1) increasing preferences and demand for, yet constrained system ability to support dying at home; (2) reinforcing and illuminating systemic reliance on and need for family/friend caregivers and community organizations, while constraining their abilities to help people die at home; and (3) illuminating challenges in developing and implementing policy changes during a pandemic, including equity-related implications. CONCLUSION: This study contributes to broader understanding of the multifaceted impacts of COVID-19 policy responses in various areas within Canadian healthcare systems. Implications for healthcare delivery and policy development include (1) recognizing the role of family/friend caregivers and community organizations in end-of-life care, (2) recognizing health inequities at the end of life, and (3) considering possible changes in future end-of-life preferences and public attitudes about dying at home and responsibility for end-of-life care.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".