Are Canadian Soldiers More Likely to Have Suicidal Ideation and Suicide Attempts Than Canadian Civilians?
Bibliographic record
Abstract
Significant controversy exists as to whether soldiers are at increased risk for suicide and suicidal behaviors compared with civilians. Furthermore, little is known about whether risk factors for suicidal behaviors in civilian populations are generalizable to soldiers. The aim of the current study is to determine whether the prevalence and correlates of past-year suicidal ideation and suicide attempts differ in Canadian soldiers when compared with Canadian civilians. The current study utilized data from the Canadian Community Health Survey Cycle 1.2-Canadian Forces Supplement in conjunction with the 2001-2002 Canadian Community Health Survey Cycle 1.2. Logistic regression interaction models were used to explore differences between correlates of suicidal ideation and suicide attempts comparing Canadian soldiers with civilians. Although there was no significant difference between the 2 samples on prevalence of past-year suicidal ideation, the prevalence of past-year suicide attempts was significantly lower in the Canadian forces sample compared with the civilian population (odds ratio = 0.41, 95% confidence interval: 0.25, 0.67). Findings suggest that suicide attempts are less common in Canadian active military personnel than in the civilian population. Possible mechanisms for these differences are discussed.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".