Person:

Petukhova, Maria

Background: Motor vehicle collisions (MVCs) are a substantial contributor to the global burden of disease and lead to subsequent post-traumatic stress disorder (PTSD). However, the relevant literature originates in only a few countries, and much remains unknown about MVC-related PTSD prevalence and predictors. Methods: Data come from the World Mental Health Survey Initiative, a coordinated series of community epidemiological surveys of mental disorders throughout the world. The subset of 13 surveys (5 in high income countries, 8 in middle or low income countries) with respondents reporting PTSD after life-threatening MVCs are considered here. Six classes of predictors were assessed: socio-demographics, characteristics of the MVC, childhood family adversities, MVCs, other traumatic experiences, and respondent history of prior mental disorders. Logistic regression was used to examine predictors of PTSD. Mental disorders were assessed with the fully-structured Composite International Diagnostic Interview using DSM-IV criteria. Results: Prevalence of PTSD associated with MVCs perceived to be life-threatening was 2.5 % overall and did not vary significantly across countries. PTSD was significantly associated with low respondent education, someone dying in the MVC, the respondent or someone else being seriously injured, childhood family adversities, prior MVCs (but not other traumatic experiences), and number of prior anxiety disorders. The final model was significantly predictive of PTSD, with 32 % of all PTSD occurring among the 5 % of respondents classified by the model as having highest PTSD risk. Conclusion: Although PTSD is a relatively rare outcome of life-threatening MVCs, a substantial minority of PTSD cases occur among the relatively small proportion of people with highest predicted risk. This raises the question whether MVC-related PTSD could be reduced with preventive interventions targeted to high-risk survivors using models based on predictors assessed in the immediate aftermath of the MVCs. Electronic supplementary material The online version of this article (doi:10.1186/s12888-016-0957-8) contains supplementary material, which is available to authorized users.

Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. While efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine learning (ML) models developed from self-reports about incident episode characteristics and comorbidities among respondents with lifetime MDD in the World Health Organization World Mental Health (WMH) Surveys predicted MDD persistence, chronicity, and severity with good accuracy. We report results of model validation in an independent prospective national household sample of 1,056 respondents with lifetime MDD at baseline. The WMH ML models were applied to these baseline data to generate predicted outcome scores that were compared to observed scores assessed 10–12 years after baseline. ML model prediction accuracy was also compared to that of conventional logistic regression models. Area under the receiver operating characteristic curve (AUC) based on ML (.63 for high chronicity and .71–.76 for the other prospective outcomes) was consistently higher than for the logistic models (.62–.70) despite the latter models including more predictors. 34.6–38.1% of respondents with subsequent high persistence-chronicity and 40.8–55.8% with the severity indicators were in the top 20% of the baseline ML predicted risk distribution, while only 0.9% of respondents with subsequent hospitalizations and 1.5% with suicide attempts were in the lowest 20% of the ML predicted risk distribution. These results confirm that clinically useful MDD risk stratification models can be generated from baseline patient self-reports and that ML methods improve on conventional methods in developing such models.

IMPORTANCE: The US Army experienced a sharp increase in soldier suicides beginning in 2004. Administrative data reveal that among those at highest risk are soldiers in the 12 months after inpatient treatment of a psychiatric disorder. OBJECTIVE: To develop an actuarial risk algorithm predicting suicide in the 12 months after US Army soldier inpatient treatment of a psychiatric disorder to target expanded posthospitalization care. DESIGN, SETTING, AND PARTICIPANTS: There were 53,769 hospitalizations of active duty soldiers from January 1, 2004, through December 31, 2009, with International Classification of Diseases, Ninth Revision, Clinical Modification psychiatric admission diagnoses. Administrative data available before hospital discharge abstracted from a wide range of data systems (sociodemographic, US Army career, criminal justice, and medical or pharmacy) were used to predict suicides in the subsequent 12 months using machine learning methods (regression trees and penalized regressions) designed to evaluate cross-validated linear, nonlinear, and interactive predictive associations. MAIN OUTCOMES AND MEASURES: Suicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge. RESULTS: Sixty-eight soldiers died by suicide within 12 months of hospital discharge (12.0% of all US Army suicides), equivalent to 263.9 suicides per 100,000 person-years compared with 18.5 suicides per 100,000 person-years in the total US Army. The strongest predictors included sociodemographics (male sex [odds ratio (OR), 7.9; 95% CI, 1.9-32.6] and late age of enlistment [OR, 1.9; 95% CI, 1.0-3.5]), criminal offenses (verbal violence [OR, 2.2; 95% CI, 1.2-4.0] and weapons possession [OR, 5.6; 95% CI, 1.7-18.3]), prior suicidality [OR, 2.9; 95% CI, 1.7-4.9], aspects of prior psychiatric inpatient and outpatient treatment (eg, number of antidepressant prescriptions filled in the past 12 months [OR, 1.3; 95% CI, 1.1-1.7]), and disorders diagnosed during the focal hospitalizations (eg, nonaffective psychosis [OR, 2.9; 95% CI, 1.2-7.0]). A total of 52.9% of posthospitalization suicides occurred after the 5% of hospitalizations with highest predicted suicide risk (3824.1 suicides per 100,000 person-years). These highest-risk hospitalizations also accounted for significantly elevated proportions of several other adverse posthospitalization outcomes (unintentional injury deaths, suicide attempts, and subsequent hospitalizations). CONCLUSIONS AND RELEVANCE: The high concentration of risk of suicide and other adverse outcomes might justify targeting expanded posthospitalization interventions to soldiers classified as having highest posthospitalization suicide risk, although final determination requires careful consideration of intervention costs, comparative effectiveness, and possible adverse effects.

Importance Although high rates of current mental disorder are known to exist in the US Army, little is known about the proportions of these disorders that had onsets prior to enlistment.

Objective To estimate the proportions of 30-day DSM-IV mental disorders among nondeployed US Army personnel with first onsets prior to enlistment and the extent which role impairments associated with 30-day disorders differ depending on whether the disorders had pre- vs post-enlistment onsets.

Design, Setting, and Participants A representative sample of 5428 soldiers participating in the Army Study to Assess Risk and Resilience in Servicemembers completed self-administered questionnaires and consented to linkage of questionnaire responses with administrative records.

Main Outcomes and Measures Thirty-day DSM-IV internalizing (major depressive, bipolar, generalized anxiety, panic, and posttraumatic stress) and externalizing (attention-deficit/hyperactivity, intermittent explosive, alcohol/drug) disorders were assessed with validated self-report scales. Age at onset was assessed retrospectively. Role impairment was assessed with a modified Sheehan Disability Scale.

Results A total of 25.1% of respondents met criteria for any 30-day disorder (15.0% internalizing; 18.4% externalizing) and 11.1% for multiple disorders. A total of 76.6% of cases reported pre-enlistment age at onset of at least one 30-day disorder (49.6% internalizing; 81.7% externalizing). Also, 12.8% of respondents reported severe role impairment. Controlling for sociodemographic and Army career correlates, which were broadly consistent with other studies, 30-day disorders with pre-enlistment (χ28 = 131.8, P < .001) and post-enlistment (χ27 = 123.8, P < .001) ages at onset both significantly predicted severe role impairment, although pre-enlistment disorders were more consistent powerful predictors (7 of 8 disorders significant; odds ratios, 1.6-11.4) than post-enlistment disorders (5 of 7 disorders significant; odds ratios, 1.5-7.7). Population-attributable risk proportions of severe role impairment were 21.7% for pre-enlistment disorders, 24.3% for post-enlistment disorders, and 43.4% for all disorders.

Conclusions and Relevance Interventions to limit accession or increase resilience of new soldiers with pre-enlistment mental disorders might reduce prevalence and impairments of mental disorders in the US Army.

The US Army suicide rate has increased sharply in recent years. Identifying significant predictors of Army suicides in Army and Department of Defense (DoD) administrative records might help focus prevention efforts and guide intervention content. Previous studies of administrative data, although documenting significant predictors, were based on limited samples and models. A career history perspective is used here to develop more textured models. The analysis was carried out as part of the Historical Administrative Data Study (HADS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). De-identified data were combined across numerous Army and DoD administrative data systems for all Regular Army soldiers on active duty in 2004–2009. Multivariate associations of sociodemographics and Army career variables with suicide were examined in subgroups defined by time in service, rank and deployment history. Several novel results were found that could have intervention implications. The most notable of these were significantly elevated suicide rates (69.6–80.0 suicides per 100 000 person-years compared with 18.5 suicides per 100 000 person-years in the total Army) among enlisted soldiers deployed either during their first year of service or with less than expected (based on time in service) junior enlisted rank; a substantially greater rise in suicide among women than men during deployment; and a protective effect of marriage against suicide only during deployment. A career history approach produces several actionable insights missed in less textured analyses of administrative data predictors. Expansion of analyses to a richer set of predictors might help refine understanding of intervention implications.

Background

Civilian suicide rates vary by occupation in ways related to occupational stress exposure. Comparable military research finds suicide rates elevated in combat arms occupations. However, no research has evaluated variation in this pattern by deployment history, the indicator of occupation stress widely considered responsible for the recent rise in the military suicide rate.

Method

The joint associations of Army occupation and deployment history in predicting suicides were analysed in an administrative dataset for the 729 337 male enlisted Regular Army soldiers in the US Army between 2004 and 2009.

Results

There were 496 suicides over the study period (22.4/100 000 person-years). Only two occupational categories, both in combat arms, had significantly elevated suicide rates: infantrymen (37.2/100 000 person-years) and combat engineers (38.2/100 000 person-years). However, the suicide rates in these two categories were significantly lower when currently deployed (30.6/100 000 person-years) than never deployed or previously deployed (41.2–39.1/100 000 person-years), whereas the suicide rate of other soldiers was significantly higher when currently deployed and previously deployed (20.2–22.4/100 000 person-years) than never deployed (14.5/100 000 person-years), resulting in the adjusted suicide rate of infantrymen and combat engineers being most elevated when never deployed [odds ratio (OR) 2.9, 95% confidence interval (CI) 2.1–4.1], less so when previously deployed (OR 1.6, 95% CI 1.1–2.1), and not at all when currently deployed (OR 1.2, 95% CI 0.8–1.8). Adjustment for a differential ‘healthy warrior effect’ cannot explain this variation in the relative suicide rates of never-deployed infantrymen and combat engineers by deployment status.

Conclusions

Efforts are needed to elucidate the causal mechanisms underlying this interaction to guide preventive interventions for soldiers at high suicide risk.

Background

The prevalence of 30-day mental disorders with retrospectively-reported early onsets is significantly higher in the U.S. Army than among socio-demographically matched civilians. This difference could reflect high prevalence of pre-enlistment disorders and/or high persistence of these disorders in the context of the stresses associated with military service. These alternatives can to some extent be distinguished by estimating lifetime disorder prevalence among new Army recruits.

Methods

The New Soldier Study (NSS) in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) used fully-structured measures to estimate lifetime prevalence of 10 DSM-IV disorders in new soldiers reporting for Basic Combat Training in 2011-2012 (n=38,507). Prevalence was compared to estimates from a matched civilian sample. Multivariate regression models examined socio-demographic correlates of disorder prevalence and persistence among new soldiers.

Results

Lifetime prevalence of having at least one internalizing, externalizing, or either type of disorder did not differ significantly between new soldiers and civilians, although three specific disorders (generalized anxiety, posttraumatic stress, and conduct disorders) and multi-morbidity were significantly more common among new soldiers than civilians. Although several socio-demographic characteristics were significantly associated with disorder prevalence and persistence, these associations were uniformly weak.

Conclusions

New soldiers differ somewhat, but not consistently, from civilians in lifetime pre-enlistment mental disorders. This suggests that prior findings of higher prevalence of current disorders with pre-enlistment onsets among soldiers than civilians are likely due primarily to a more persistent course of early-onset disorders in the context of the special stresses experienced by Army personnel.

Although earlier trauma exposure is known to predict post-traumatic stress disorder (PTSD) after subsequent traumas, it is unclear if this association is limited to cases where the earlier trauma led to PTSD. Resolution of this uncertainty has important implications for research on pre-trauma vulnerability to PTSD. We examined this issue in the WHO World Mental Health (WMH) Surveys with 34,676 respondents who reported lifetime trauma exposure. One lifetime trauma was selected randomly for each respondent. DSM-IV PTSD due to that trauma was assessed. We reported in a previous paper that four earlier traumas involving interpersonal violence significantly predicted PTSD after subsequent random traumas (OR=1.3–2.5). We also assessed 14 lifetime DSM-IV mood, anxiety, disruptive behavior, and substance disorders prior to random traumas. We show in the current report that only prior anxiety disorders significantly predicted PTSD in a multivariate model (OR=1.5–4.3) and that these disorders interacted significantly with three of the earlier traumas (witnessing atrocities, physical violence victimization, rape). History of witnessing atrocities significantly predicted PTSD after subsequent random traumas only among respondents with prior PTSD (OR=5.6). Histories of physical violence victimization (OR=1.5) and rape after age 17 (OR=17.6) significantly predicted only among respondents with no history of prior anxiety disorders. Although only preliminary due to reliance on retrospective reports, these results suggest that history of anxiety disorders and history of a limited number of earlier traumas might usefully be targeted in future prospective studies as distinct foci of research on individual differences in vulnerability to PTSD after subsequent traumas.