Dataset Information

Predeployment predictors of psychiatric disorder-symptoms and interpersonal violence during combat deployment.

ABSTRACT: BACKGROUND:Preventing suicides, mental disorders, and noncombat-related interpersonal violence during deployment are priorities of the US Army. We used predeployment survey and administrative data to develop actuarial models to identify soldiers at high risk of these outcomes during combat deployment. METHODS:The models were developed in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) Pre-Post Deployment Study, a panel study of soldiers deployed to Afghanistan in 2012-2013. Soldiers completed self-administered questionnaires before deployment and one (T1), three (T2), and nine months (T3) after deployment, and consented to administrative data linkage. Seven during-deployment outcomes were operationalized using the postdeployment surveys. Two overlapping samples were used because some outcomes were assessed at T1 (n = 7,048) and others at T2-T3 (n = 7,081). Ensemble machine learning was used to develop a model for each outcome from 273 predeployment predictors, which were compared to simple logistic regression models. RESULTS:The relative improvement in area under the receiver operating characteristic curve (AUC) obtained by machine learning compared to the logistic models ranged from 1.11 (major depression) to 1.83 (suicidality).The best-performing machine learning models were for major depression (AUC = 0.88), suicidality (0.86), and generalized anxiety disorder (0.85). Roughly 40% of these outcomes occurred among the 5% of soldiers with highest predicted risk. CONCLUSIONS:Actuarial models could be used to identify high risk soldiers either for exclusion from deployment or preventive interventions. However, the ultimate value of this approach depends on the associated costs, competing risks (e.g. stigma), and the effectiveness to-be-determined interventions.

SUBMITTER: Rosellini AJ

PROVIDER: S-EPMC6212319 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Predeployment predictors of psychiatric disorder-symptoms and interpersonal violence during combat deployment.

Rosellini Anthony J AJ Stein Murray B MB Benedek David M DM Bliese Paul D PD Chiu Wai Tat WT Hwang Irving I Monahan John J Nock Matthew K MK Sampson Nancy A NA Street Amy E AE Zaslavsky Alan M AM Ursano Robert J RJ Kessler Ronald C RC

Depression and anxiety 20180813 11

<h4>Background</h4>Preventing suicides, mental disorders, and noncombat-related interpersonal violence during deployment are priorities of the US Army. We used predeployment survey and administrative data to develop actuarial models to identify soldiers at high risk of these outcomes during combat deployment.<h4>Methods</h4>The models were developed in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) Pre-Post Deployment Study, a panel study of soldiers deployed to Afg ...[more]

PMID: 30102442

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Project description:The potential stressors associated with military deployment are related to an increased risk of adverse mental health outcomes. Perceived exposure to combat has been found to be proportional to the severity of post-deployment posttraumatic stress disorder (PTSD). However, other perceived adversities during deployment, such as witnessing danger, distress, and hardship in the war zone, have been less systematically studied, but might play an equally substantial role for post-deployment mental health. The development and validation of scales that assess these related constructs are needed to distinguish their contribution to post-deployment risk of PTSD. We evaluated the validity of 10 items measuring perceived danger distributed to all deployed personnel with the Danish Defense since 1998. We hypothesize two scales: Exposure to Danger and Combat (EDC) and Witnessing Consequences of War (WCW). Two military cohorts deployed to Afghanistan in 2009 (Cohort 1, N = 276) and 2013 (Cohort 2, N = 273) were included. Questionnaire data was collected six months after homecoming, including deployment experiences and post-deployment reactions. We tested the construct validity of the 10 items of perceived danger with Rasch models (RM), focusing specifically on presence of subscales, and differential item functioning (DIF) across cohorts. We confirmed the existence of two separate subscales, EDCS and WCWS, both with adequate reliability. None of the subscales fitted a pure RM, but adequate fit was found for graphical log-linear RMs with evidence of DIF for the ECDS. However, adjusting the score to account for DIF had practically no effect, suggesting that the total non-adjusted mean score can be used in future cohort comparisons. Perceived exposure to combat and danger and witnessing consequences of war are related, but essentially distinct, concepts, each providing unique information about deployment adversities. Future studies should evaluate their shared and unique contribution to the risk of post-deployment PTSD.

Dataset Information

Predeployment predictors of psychiatric disorder-symptoms and interpersonal violence during combat deployment.

Publications

Predeployment predictors of psychiatric disorder-symptoms and interpersonal violence during combat deployment.

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