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Objectives. To examine associations of administratively recorded sexual assault victimization during military service with subsequent mental health and negative career outcomes among US Army women controlling for nonrandom victimization exposure. Methods. We used data from the Army Study to Assess Risk and Resilience in Servicemembers to apply propensity score methods to match all 4238 female Regular Army soldiers with administratively recorded sexual assault victimization during 2004 to 2009 to 5 controls per case with similar composite victimization risk. We examined associations of this victimization measure with administratively recorded mental health treatment, suicide attempt, and Army career outcomes over the subsequent 12 months by using survival analysis for dichotomous outcomes and conditional generalized linear models for continuous outcomes. Results. Women with administratively recorded sexual assault had significantly elevated odds ratios (ORs) of subsequent mental health treatment (any, OR= 2.5; 95% confidence interval [CI] = 2.4,2.6; specialty, OR= 3.1;95%CI = 2.9,3.3; inpatient, OR= 2.8;95%CI = 2.5,3.1), posttraumatic stress disorder treatment (any, OR= 6.3; 95% CI = 5.7, 6.9; specialty, OR= 7.7; 95% CI = 6.8, 8.6; inpatient, OR= 6.8; 95% CI = 5.4, 8.6), suicide attempt (OR= 3.0; 95% CI = 2.5, 3.6), demotion (OR= 2.1; 95% CI = 1.9, 2.3), and attrition (OR= 1.2; 95% CI = 1.1, 1.2). Conclusions. Sexual assault victimization is associated with considerable suffering and likely decreased force readiness. [ABSTRACT FROM AUTHOR]

Objective: Prior research has shown that a substantial portion of suicide decedents access health care in the weeks and months before their death. We examined whether this is true among soldiers. Method: The sample included the 569 Regular Army soldiers in the U.S. Army who died by suicide on active duty between 2004 and 2009 compared to 5,690 matched controls. Analyses examined the prevalence and frequency of health care contacts and documentation of suicide risk (i.e., the presence of prior suicidal thoughts and behaviors) over the year preceding suicide death. Predictors of health care contact and suicide risk documentation were also examined. Results: Approximately 50% of suicide decedents accessed health care in the month prior to their death, and over 25% of suicide decedents accessed health care in the week prior to their death. Mental health encounters were significantly more prevalent among suicide decedents (4 weeks: 27.9% vs. 7.9%, χ2 = 96.2, p < .001; 52 weeks: 59.4% vs. 33.7%, χ2 = 120.2, p < .001). Despite this, risk documentation was rare among suicide decedents (4 weeks: 13.8%; 52 weeks: 24.5%). Suicide decedents who were male, never married, and non-Hispanic Black were less likely to access care prior to death. Number of mental health encounters was the only predictor of suicide risk documentation among decedents at 4 weeks (OR = 1.14) and 52 weeks (OR = 1.05) prior to their death. Conclusions: Many soldiers who die by suicide access health care shortly before death, presenting an opportunity for suicide prevention. However, in most cases, there was no documentation of prior suicidal thoughts or behaviors, highlighting the need for improvements in risk detection and prediction. Increasing the frequency, scope, and accuracy of risk assessments, especially in mental health care settings, may be particularly useful. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: The Department of Defense uses a universal prevention framework for sexual assault prevention, with each branch implementing its own branch-wide programs. Intensive interventions exist, but would be cost effective only if targeted at high-risk personnel. This study developed actuarial models to identify male U.S. Army soldiers at high risk of administratively recorded sexual assault perpetration.Methods: This study investigated administratively recorded sexual assault perpetration among the 821,807 male Army soldiers serving 2004-2009. Administrative data were also used to operationalize the predictors. Penalized discrete-time (person-month) survival analysis (conducted in 2016) was used to select the smallest possible number of stable predictors to maximize number of sexual assaults among the 5% of soldiers with highest predicted risk of perpetration (top-ventile concentration of risk). Separate models were developed for assaults against non-family and intra-family adults and minors.Results: There were 4,640 male soldiers found to be perpetrators against non-family adults, 1,384 against non-family minors, 380 against intra-family adults, and 335 against intra-family minors. Top-ventile concentration of risk was 16.2%-20.2% predicting perpetration against non-family adults and minors and 34.2%-65.1% against intra-family adults and minors. Final predictors consisted largely of measures of prior crime involvement and the presence and treatment of mental disorders.Conclusions: Administrative data can be used to develop actuarial models that identify a high proportion of sexual assault perpetrators. If a system is developed to consolidate administrative predictors routinely, then predictions could be generated periodically to identify those in need of preventive intervention. Whether this would be cost effective, though, would depend on intervention costs, effectiveness, and competing risks. [ABSTRACT FROM AUTHOR]