Dataset Information

Post-Deployment Screening In The Military Health System: An Opportunity To Intervene For Possible Alcohol Use Disorder.

ABSTRACT: Unhealthy alcohol use in the military remains a serious threat to health and military readiness and raises the question of how to improve detection that facilitates diagnosis and treatment. Army active duty soldiers are routinely screened for possible alcohol use disorder in pre- and post-deployment health surveillance surveys. We examined the likelihood of having a follow-up behavioral health visit or receiving an alcohol use disorder diagnosis among soldiers returning from deployments associated with the Afghanistan or Iraq operations in fiscal years 2008-13, based on their post-deployment screening results. After we controlled for demographic and military treatment facility characteristics, military history, and comorbidities, we found that people who screened positive for possible alcohol use disorder were significantly more likely to have such a visit and receive such a diagnosis. Routine post-deployment alcohol screening represents an opportunity for timely intervention by the Military Health System for military members whose results indicate elevated risk for alcohol use disorder.

SUBMITTER: Adams RS

PROVIDER: S-EPMC7357622 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Post-Deployment Screening In The Military Health System: An Opportunity To Intervene For Possible Alcohol Use Disorder.

Adams Rachel Sayko RS Dietrich Erich J EJ Gray Joshua C JC Milliken Charles S CS Moresco Natalie N Larson Mary Jo MJ

Health affairs (Project Hope) 20190801 8

Unhealthy alcohol use in the military remains a serious threat to health and military readiness and raises the question of how to improve detection that facilitates diagnosis and treatment. Army active duty soldiers are routinely screened for possible alcohol use disorder in pre- and post-deployment health surveillance surveys. We examined the likelihood of having a follow-up behavioral health visit or receiving an alcohol use disorder diagnosis among soldiers returning from deployments associat ...[more]

PMID: 31381410

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Project description:ImportanceMilitary deployment involves significant risk for life-threatening experiences that can lead to posttraumatic stress disorder (PTSD). Accurate predeployment prediction of PTSD risk may facilitate the development of targeted intervention strategies to enhance resilience.ObjectiveTo develop and validate a machine learning (ML) model to predict postdeployment PTSD.Design, setting, and participantsThis diagnostic/prognostic study included 4771 soldiers from 3 US Army brigade combat teams who completed assessments between January 9, 2012, and May 1, 2014. Predeployment assessments occurred 1 to 2 months before deployment to Afghanistan, and follow-up assessments occurred approximately 3 and 9 months post deployment. Machine learning models to predict postdeployment PTSD were developed in the first 2 recruited cohorts using as many as 801 predeployment predictors from comprehensive self-report assessments. In the development phase, cross-validated performance metrics and predictor parsimony were considered to select an optimal model. Next, the selected model's performance was evaluated with area under the receiver operating characteristics curve and expected calibration error in a temporally and geographically distinct cohort. Data analyses were performed from August 1 to November 30, 2022.Main outcomes and measuresPosttraumatic stress disorder diagnosis was assessed by clinically calibrated self-report measures. Participants were weighted in all analyses to address potential biases related to cohort selection and follow-up nonresponse.ResultsThis study included 4771 participants (mean [SD] age, 26.9 [6.2] years), 4440 (94.7%) of whom were men. In terms of race and ethnicity, 144 participants (2.8%) identified as American Indian or Alaska Native, 242 (4.8%) as Asian, 556 (13.3%) as Black or African American, 885 (18.3%) as Hispanic, 106 (2.1%) as Native Hawaiian or other Pacific Islander, 3474 (72.2%) as White, and 430 (8.9%) as other or unknown race or ethnicity; participants could identify as of more than 1 race or ethnicity. A total of 746 participants (15.4%) met PTSD criteria post deployment. In the development phase, models had comparable performance (log loss range, 0.372-0.375; area under the curve range, 0.75-0.76). A gradient-boosting machine with 58 core predictors was selected over an elastic net with 196 predictors and a stacked ensemble of ML models with 801 predictors. In the independent test cohort, the gradient-boosting machine had an area under the curve of 0.74 (95% CI, 0.71-0.77) and low expected calibration error of 0.032 (95% CI, 0.020-0.046). Approximately one-third of participants with the highest risk accounted for 62.4% (95% CI, 56.5%-67.9%) of the PTSD cases. Core predictors cut across 17 distinct domains: stressful experiences, social network, substance use, childhood or adolescence, unit experiences, health, injuries, irritability or anger, personality, emotional problems, resilience, treatment, anxiety, attention or concentration, family history, mood, and religion.Conclusions and relevanceIn this diagnostic/prognostic study of US Army soldiers, an ML model was developed to predict postdeployment PTSD risk with self-reported information collected before deployment. The optimal model showed good performance in a temporally and geographically distinct validation sample. These results indicate that predeployment stratification of PTSD risk is feasible and may facilitate the development of targeted prevention and early intervention strategies.

Dataset Information

Post-Deployment Screening In The Military Health System: An Opportunity To Intervene For Possible Alcohol Use Disorder.

Publications

Post-Deployment Screening In The Military Health System: An Opportunity To Intervene For Possible Alcohol Use Disorder.

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