Is the bereavement grief intensity of survivors linked with their perception of death quality?
Bibliographic record
Abstract
BACKGROUND: Some people experience exceptionally severe bereavement grief, and this level of post-death grief could potentially be the result of a low quality dying process. AIMS: A pilot study was conducted to determine if a relationship exists between perceived death quality and bereavement grief intensity. METHODS: A questionnaire was developed and posted online for data on bereavement grief intensity, perceived death quality, and decedent and bereaved person characteristics. Data from 151 Canadian volunteers were analysed using bi-variate and multiple linear regression tests. FINDINGS: Half had high levels of grief, and over half rated the death as more bad than good. Perceived death quality and post-death grief intensity were close to being negatively correlated. CONCLUSION: These findings indicate research is needed to explore possible connections between bereavement grief and the survivor's perceptions of whether a good or bad death took place. In the meantime, it is important for palliative care nurses to think of the quality of the dying process as being potentially very impactful on the people who will be left to grieve that death.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".