Military Deployments, Posttraumatic Stress Disorder, and Suicide Risk in Canadian Armed Forces Personnel and Veterans
Bibliographic record
Abstract
Dear Editor: In your September 2014 issue, Dr Brunet and Dr Monson1 cite Canadian Armed Forces (CAF) data showing no association of suicide during military service with ever having deployed. We would like to clarify our interpretation of this finding. Contrary to the authors’ assertion, we do not interpret this as evidence against the suicidogenic effects of military trauma. Indeed, the professional–technical reviews done after each military suicide have identified deployment-related posttraumatic stress disorder (PTSD) as one factor among many in at least some recent suicides. Brunet and Monson attribute the lack of association of ever having deployed with suicide to the depletion of vulnerable individuals in the serving population through medical release of those who no longer meet the CAF’s stringent medical fitness standards. This is certainly an important factor, and there is, indeed, evidence of greater suicide risk after release from CAF service in modern veterans.2 No difference has been seen in suicidal ideation rates between serving personnel and civilians.3 But there are other potential explanations for the lack of association between ever having deployed and suicide while in service. First, ever having deployed is a crude marker for exposure to deployment-related trauma because the extent of exposure varies dramatically depending on deployment circumstances that vary from person to person.4 We have used this marker largely because the small number of yearly suicides precludes a more refined approach. Second, as one factor among many driving suicide, deployment may not have a strong enough contribution to be detectable at the level of the population. Indeed, no significant population attributable fraction for deployment in relation to suicidal ideation has been detected.5 This finding comes from the same CAF survey data that Brunet and Monson used to demonstrate the strong link between PTSD and suicidality. Finally, we should not dismiss out of hand the possibility that the totality of the policies, programs, and services available to CAF personnel mitigate the risk of suicide in those with a history of deployment. This may account for the lack of a striking increase in the CAF suicide rate during the past decade. This stands in stark contrast to the precipitous increases in the US military during the same period.6 We caution against assuming that US military suicide findings cited by Brunet and Monson7,8 must apply to the CAF. The finding that ever having deployed is not a significant suicide risk factor in serving personnel has not diminished our commitment to understanding and managing the adverse health effects of military service. Instead, it has informed our approach to suicide prevention as not primarily a deployment health problem, but instead as a public health problem, requiring the targeting of the full range of determinants of mental health and suicidal behaviour in our prevention efforts.9 Disproportionate emphasis on the role of deployment, PTSD, or any other single factor is not an effective approach to suicide prevention.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".