Prevalence and correlates of positive and negative psychological effects of bereavement due to COVID-19: A living systematic review
Bibliographic record
Abstract
Background: The coronavirus disease 2019 (COVID-19) pandemic is associated with an increase in mortality rates globally. Given the high numbers of deaths and the potentially traumatic characteristics of COVID-19 deaths, it is expected that grief-related distress levels are higher in COVID-19 bereaved (compared to non-COVID-19 bereaved) people. This living systematic review (LSR) investigates the empirical evidence regarding this claim. More specifically, this LSR summarizes studies evaluating prevalence and correlates of positive and negative psychological effects of COVID-19 bereavement. This iteration synthesizes evidence up to July 2022. Methods: Systematic searches were conducted in PsychInfo, Web of Science, and Medline by two independent reviewers. Eligible studies included quantitative peer-reviewed articles reporting on positive and/or negative psychological outcomes, using validated measures, in COVID-19 bereaved adults. The primary outcome was prolonged grief symptoms (PG). Results: Searches identified 9871 articles, whereof 12 studies met the inclusion criteria. All studies included prevalence rates and/or symptom-levels of psychological outcomes after COVID-19 losses. Prevalence rates of psychological outcomes were primarily reported in terms of (acute) PG, pandemic grief, depression, anxiety, and functional impairment, and varied widely between studies (e.g., ranged between 29% and 49% for acute PG). No studies reported on prevalence rates of positive psychological outcomes. Closer kinship to the deceased, death unexpectedness, and COVID-19 stressors were identified as correlates of increased psychological symptoms. Conclusions: Due to the small number and heterogeneity of studies, knowledge about psychological effects of COVID-19 bereavement is limited. This LSR offers a regular synthesis of up-to-date research evidence to guide clinicians, policy makers, public health professionals, and future research on the psychological effects of COVID-19 bereavement.
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".