An examination of mental disorders associated with spousal suicide bereavement: a longitudinal population-based study
Bibliographic record
Abstract
Suicide bereavement is a significant public health problem, with an estimated 48 to 500 million individuals bereaved by suicide every year. Accurate measurements of suicide bereavement related health is an essential component to understanding this public health problem and organizing appropriate resources for prevention and intervention. Spousal suicide bereavement is thought to be associated with poor health outcomes due to its substantial impact on the surviving partner. There are limited theoretical frameworks to better understand the relationship between suicide bereavement and associated health, therefore to address these limitations we proposed an integrative risk framework that is testable using administrative data. The overall goal of this research was to determine if spouses bereaved by suicide have greater rates of mental disorders as compared to spouses bereaved by other sudden deaths. To achieve this goal, 7 manuscripts were written in the areas of theory, methodology, policy, and four related studies using longitudinal population-based administrative data to examine rates of mental disorders among spouses bereaved by suicide, sudden natural death, and unintentional injury. These cohorts were examined both individually as compared to matched non-bereaved spousal samples and then comparatively where suicide bereaved spouses were compared to spouses bereaved by sudden natural death and unintentional injury death using advanced statistical modeling. The overall findings of this research demonstrate that while spousal bereavement seems to be a time of poor mental health, when comparing bereavement cohorts, suicide bereaved spouses appear to be doing more poorly overall. The findings from this body of research support the need for future studies in numerous areas. First, research is needed to examine the impact of the deceased’s pre-death health on the surviving spouse to determine if caregiver stress helps explain the elevated pre-bereavement rates of mental disorders found. Second, the role of guilt and stigma in suicide bereavement and its impact on help seeking is an additional area for future work to determine if reported rates are potential underestimates due to these factors. All of these factors will ultimately inform targeted interventions for spouses bereaved by suicide.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".