Veteran suicide mortality in Canada from 1976 to 2012
Bibliographic record
Abstract
Introduction: Suicide prevention for Veterans is a public health priority. However, it has been challenging to study suicide in Canadian Veterans post-release from the military. The Veteran Suicide Mortality Study (VSMS) has assembled data on the risk of death by suicide for Canadian Veterans compared to other Canadians. Methods: This was a record linkage study of Canadian cause of death data from Statistics Canada linked with a cohort of Canadian Veterans from pay data of the Canadian Armed Forces (CAF). The population-based cohort included Veterans released with Regular Force or Reserve Force Class C service for the period 1976–2012. Death by suicide was identified by International Classification of Diseases (ICD) codes. Estimates of relative risk for suicide were calculated using standardized mortality ratios (SMRs) with the Canadian general population (CGP) as the reference. Results: Male Veterans had a higher risk of suicide compared to the CGP (SMR = 1.36 [95% CI, 1.30–1.44]). Female Veterans also had a higher risk (SMR = 1.81 [95% CI, 1.40–2.31]). Suicide risk for Veterans was consistently higher than for the CGP over the 37 years of follow-up. Risk for male Veterans was highest for those under 25 years old and decreased with age, but risk for females was higher than the CGP regardless of age. Discussion: The finding of higher risk of death by suicide for both male and female Veterans compared to the CGP informs the action plans of the recently released suicide prevention strategy. Future studies will identify other characteristics of subgroups of Veterans at higher risk of suicide.
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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".