Military Deployments, Posttraumatic Stress Disorder, and Suicide Risk in Canadian Armed Forces Personnel and Veterans
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».