Search results

To identify trajectories of posttraumatic stress (PTS) and depression symptom groups after deployment and determine the effect of alcohol use disorder on these trajectories, PTS symptoms were modeled using the PTSD Checklist in 472 Ohio National Guard members, and depression symptoms were modeled using the 9-item Patient Health Questionnaire in 727 Ohio National Guard members. There were 42% of participants who were resistant to PTS symptoms across the 4 years of study and 55.9% were resistant to depression symptoms. There were 19% and 42.2% of participants who showed resilience (experiencing slightly elevated symptoms followed by a decline, according to Bonanno et al., 2004) to depression and PTS symptoms, respectively. Mild and chronic dysfunction constituted the smallest trajectory groups across disorders. Marital status, deployment to an area of conflict, and number of lifetime stressors were associated with membership into different latent groups for depression (unstandardized beta estimates range: 0.69 to 1.37). Deployment to an area of conflict, number of lifetime potentially traumatic events and education predicted membership into different latent groups for PTS (unstandardized beta estimate range: 0.83 to 3.17). Alcohol use disorder was associated with an increase in both symptom outcomes (unstandardized beta estimate range: 0.20 to 9.45). These results suggest that alcohol use disorder may have contributed substantially to trajectories of psychopathology in this population.

BACKGROUND: Prevention of PTSD requires identification of subpopulations contributing most to the population burden of PTSD. This study examined the relative contribution of subthreshold PTSD and probable PTSD on future PTSD in a representative military cohort. METHODS: We analyzed data on 3,457 US National Guard members from the state of Ohio, assessed by telephone annually from 2008–2014. At each wave, participants were classified into one of three groups based on the PTSD Checklist: probable PTSD (DSM-IV-TR criteria), subthreshold PTSD (Criterion A1, at least one symptom in each cluster, symptom lasting longer than 30 days, and functional impairment), and no PTSD. We calculated the exposure rate, risk ratio (RR), and population attributable fraction (PAF) to determine the burden of future probable PTSD attributable to subthreshold PTSD compared to probable PTSD. RESULTS: The annualized prevalence of subthreshold PTSD and probable PTSD was respectively 11.9% and 5.0%. The RR for probable PTSD was twice as great among respondents with probable PTSD the prior interview than that of those with subthreshold PTSD (7.0 vs. 3.4); however, the PAF was considerably greater in participants with subthreshold PTSD the prior interview (PAF=35%; 95% CI=26.0–42.9%) than in those with probable PTSD (PAF=28.0%; 95% CI=21.8–33.8%). Results were robust to changes in subthreshold PTSD definition. CONCLUSIONS: Subthreshold PTSD accounted for a substantial proportion of this population's future PTSD burden. Population-based preventive interventions, compared to an approach focused exclusively on cases of diagnosable PTSD, is likely to affect the greatest reduction in this population's future PTSD burden.

OBJECTIVE: Depression is one of the most common mental disorders in the United States in both civilian and military populations, but few prospective studies assess a wide range of predictors across multiple domains for new-onset (incident) depression in adulthood. Supervised machine learning methods can identify predictors of incident depression out of many different candidate variables, without some of the assumptions and constraints that underlie traditional regression analyses. The objectives of this study were to identify predictors of incident depression across 5 years of follow-up using machine learning, and to assess prediction accuracy of the algorithms. METHODS: Data were from a cohort of Army National Guard members free of history of depression at baseline (n = 1951 men and 298 women), interviewed once per year for probable depression. Classification trees and random forests were constructed and cross-validated, using 84 candidate predictors from the baseline interviews. RESULTS: Stressors and traumas such as emotional mistreatment and adverse childhood experiences, demographics such as being a parent or student, and military characteristics including paygrade and deployment location were predictive of probable depression. Cross-validated random forest algorithms were moderately accurate (68% for women and 73% for men). CONCLUSIONS: Events and characteristics throughout the life course, both in and outside of deployment, predict incident depression in adulthood among military personnel. Although replication studies are needed, these results may help inform potential intervention targets to reduce depression incidence among military personnel. Future research should further refine and explore interactions between identified variables.