Bereavement after sibling death: a population‐based longitudinal case‐control study
Bibliographic record
Abstract
The objective of this study was to examine mental disorders and treatment use among bereaved siblings in the general population. Siblings (N=7243) of all deceased children in the population of Manitoba, Canada who died between 1984 and 2009 were matched 1:3 to control siblings (N=21,729) who did not have a sibling die in the study period. Generalized estimating equations were used to compare the two sibling groups in the two years before and after the index child's death on physician-diagnosed mental disorders and treatment utilization, with adjustment for confounding factors including pre-existing mental illness. Analyses were stratified by age of the bereaved (<13 vs. 13+). Results revealed that, in the two years after the death of the child, bereaved siblings had significantly higher rates of mental disorders than control siblings, even after adjusting for pre-existing mental illness. When comparing the effect of a child's death on younger versus older siblings, the rise in depression rates from pre-death to post-death was significantly higher for siblings aged under 13 (p<0.0001), increasing more than 7-fold (adjusted relative rate, ARR=7.25, 95% CI: 3.65-14.43). Bereaved siblings aged 13+ had substantial morbidity in the two years after the death: 25% were diagnosed with a mental disorder (vs. 17% of controls), and they had higher rates of almost all mental disorder outcomes compared to controls, including twice the rate of suicide attempts (ARR=2.01, 95% CI: 1.29-3.12). Siblings in the bereaved cohort had higher rates of alcohol and drug use disorders already before the death of their sibling. In conclusion, the death of a child is associated with considerable mental disorder burden among surviving siblings. Pre-existing health problems and social disadvantage do not fully account for the increase in mental disorder rates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".