Bereavement outcomes in family members of those who died in acute care hospitals before and during the first wave of COVID-19: A cohort study
Bibliographic record
Abstract
Background: The COVID-19 pandemic has caused millions of deaths worldwide, leading to symptoms of grief among the bereaved. Neither the burden of severe grief nor its predictors are fully known within the context of the pandemic. Aim: To determine the prevalence and predictors of severe grief in family members who were bereaved early in the COVID-19 pandemic. Design: Prospective, matched cohort study. Setting/Participants: Family members of people who died in an acute hospital in Ottawa, Canada between November 1, 2019 and August 31, 2020. We matched relatives of patients who died of COVID (COVID +ve) with those who died of non-COVID illness either during wave 1 of the pandemic (COVID −ve) or immediately prior to its onset (pre-COVID). We abstracted decedents’ medical records, contacted family members >6 months post loss, and assessed grief symptoms using the Inventory of Complicated Grief-revised. Results: We abstracted data for 425 decedents (85 COVID +ve, 170 COVID −ve, and 170 pre-COVID), and 110 of 165 contacted family members (67%) consented to participate. Pre-COVID family members were physically present more in the last 48 h of life; the COVID +ve cohort were more present virtually. Overall, 35 family members (28.9%) had severe grief symptoms, and the prevalence was similar among the cohorts ( p = 0.91). Grief severity was not correlated with demographic factors, physical presence in the final 48 h of life, intubation, or relationship with the deceased. Conclusion: Severe grief is common among family members bereaved during the COVID-19 pandemic, regardless of the cause or circumstances of death, and even if their loss took place before the onset of the pandemic. This suggests that aspects of the pandemic itself contribute to severe grief, and factors that normally mitigate grief may not be as effective.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".