Long-term 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: Severe grief is highly distressing and prevalent up to 1 year post-death among people bereaved during the first wave of COVID-19, but no study has assessed changes in grief severity beyond this timeframe. AIM: Understand the trajectory of grief during the pandemic by reassessing grief symptoms in our original cohort 12-18 months post-death. DESIGN: Prospective matched cohort study. SETTINGS/PARTICIPANTS: Family members of decedents who died in an acute care hospital between November 1, 2019 and August 31, 2020 in Ottawa, Canada. Family members of patients who died of COVID (COVID +ve) were matched 2:1 with those who died of non-COVID illness (COVID -ve) during pandemic wave 1 or immediately prior to its onset (pre-COVID). Grief was assessed using the Inventory of Complicated Grief (ICG). RESULTS: Follow-up assessment was completed by 92% (111/121) of family members in the initial cohort. Mean ICG score on the 12-18-month assessment was 19.9 (SD = 11.8), and severe grief (ICG > 25) was present in 28.8% of participants. One-third (33.3%) had either a persistently high (>25) or worsening ICG score (⩾4-point increase between assessments). Using a modified Poisson regression analysis, persistently high or worsening ICG scores were associated with endotracheal intubation in the deceased, but not cause of death (COVID +ve, COVID -ve, pre-COVID) or physical presence of the family member in the final 48 h of life. CONCLUSIONS: Severe grief is a substantial source of psychological morbidity in the wake of the COVID-19 pandemic, persisting more than a year post-death. Our findings highlight an acute need for effective and scalable means of addressing severe grief.
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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".