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Objectives To develop a composite score for differential resilience to effects of combat‐related stressors (CRS) on persistent DSM‐IV post‐traumatic stress disorder (PTSD) among US Army combat arms soldiers using survey data collected before deployment. Methods A sample of n = 2542 US Army combat arms soldiers completed a survey shortly before deployment to Afghanistan and then again two to three and 8–9 months after redeployment. Retrospective self‐reports were obtained about CRS. Precision treatment methods were used to determine whether differential resilience to persistent PTSD in the follow‐up surveys could be developed from pre‐deployment survey data in a 60% training sample and validated in a 40% test sample. Results 40.8% of respondents experienced high CRS and 5.4% developed persistent PTSD. Significant test sample heterogeneity was found in resilience (t = 2.1, p = 0.032), with average treatment effect (ATE) of high CRS in the 20% least resilient soldiers of 17.1% (SE = 5.5%) compared to ATE = 3.8% (SE = 1.2%) in the remaining 80%. The most important predictors involved recent and lifetime pre‐deployment distress disorders. Conclusions A reliable pre‐deployment resilience score can be constructed to predict variation in the effects of high CRS on persistent PTSD among combat arms soldiers. Such a score could be used to target preventive interventions to reduce PTSD or other resilience‐related outcomes.

Suicide is a leading cause of death. A substantial proportion of the people who die by suicide come into contact with the health care system in the year before their death. This observation has resulted in the development of numerous suicide prediction tools to help target patients for preventive interventions. However, low sensitivity and low positive predictive value have led critics to argue that these tools have no clinical value. We review these tools and critiques here. We conclude that existing tools are suboptimal and that improvements, if they can be made, will require developers to work with more comprehensive predictor sets, staged screening designs, and advanced statistical analysis methods. We also conclude that although existing suicide prediction tools currently have little clinical value, and in some cases might do more harm than good, an even-handed assessment of the potential value of refined tools of this sort cannot currently be made because such an assessment would depend on evidence that currently does not exist about the effectiveness of preventive interventions. We argue that the only way to resolve this uncertainty is to link future efforts to develop or evaluate suicide prediction tools with concrete questions about specific clinical decisions aimed at reducing suicides and to evaluate the clinical value of these tools in terms of net benefit rather than sensitivity or positive predictive value. We also argue for a focus on the development of individualized treatment rules to help select the right suicide-focused treatments for the right patients at the right times. Challenges will exist in doing this because of the rarity of suicide even among patients considered high-risk, but we offer practical suggestions for how these challenges can be addressed.

Evidence has suggested increased risk for homelessness and suicide among US veterans, but little is known about the associations between housing instability and psychological distress (including suicidal ideation). We examined frequent mental distress (FMD) and suicidal ideation among a probability-based sample of 1767 Nebraska veterans who participated in the 2010 Behavioral Risk Factor Surveillance Survey who had and had not experienced housing instability in the past 12 months. Veterans experiencing housing instability had increased odds of FMD and suicidal ideation.

BackgroundHealth care systems struggle to identify risk factors for suicide. Adverse social determinants of health (SDH) are strong predictors of suicide risk, but most electronic health records (EHR) do not include SDH data.ObjectiveTo determine the prevalence of SDH documentation in the EHR and how SDH are associated with suicide ideation and attempt.DesignThis cross-sectional analysis included EHR data spanning October 1, 2015–September 30, 2016, from the Veterans Integrated Service Network Region 4.ParticipantsThe study included all patients with at least one inpatient or outpatient visit (n = 293,872).Main MeasurementsAdverse SDH, operationalized using Veterans Health Administration (VHA) coding for services and International Statistical Classification of Diseases and Related Health Problems (ICD)-10 codes, encompassed seven types (violence, housing instability, financial/employment problems, legal problems, familial/social problems, lack of access to care/transportation, and nonspecific psychosocial needs). We defined suicide morbidity by ICD-10 codes and data from the VHA’s Suicide Prevention Applications Network. Logistic regression assessed associations of SDH with suicide morbidity, adjusting for socio-demographics and mental health diagnoses (e.g., major depression). Statistical significance was assessed with p < .01.Key ResultsOverall, 16.4% of patients had at least one adverse SDH indicator. Adverse SDH exhibited dose-response-like associations with suicidal ideation and suicide attempt: each additional adverse SDH increased odds of suicidal ideation by 67% (AOR = 1.67, 99%CI = 1.60–1.75; p < .01) and suicide attempt by 49% (AOR = 1.49, 99%CI = 1.33–1.68; p < .01). Independently, each adverse SDH had strong effect sizes, ranging from 1.86 (99%CI = 1.58–2.19; p < .01) for legal issues to 3.10 (99%CI = 2.74–3.50; p < .01) for non-specific psychosocial needs in models assessing suicidal ideation and from 1.58 (99%CI = 1.10–2.27; p < .01) for employment/financial problems to 2.90 (99%CI = 2.30–4.16; p < .01) for violence in models assessing suicide attempt.ConclusionsSDH were strongly associated with suicidal ideation and suicide attempt even after adjusting for mental health diagnoses. Integration of SDH data in EHR could improve suicide prevention.

Objectives. The Veterans Health Administration (VHA) evaluated the use of predictive modeling to identify patients at risk for suicide and to supplement ongoing care with risk-stratified interventions. Methods. Suicide data came from the National Death Index. Predictors were measures from VHA clinical records incorporating patient-months from October 1, 2008, to September 30, 2011, for all suicide decedents and 1% of living patients, divided randomly into development and validation samples. We used data on all patients alive on September 30, 2010, to evaluate predictions of suicide risk over 1 year. Results. Modeling demonstrated that suicide rates were 82 and 60 times greater than the rate in the overall sample in the highest 0.01% stratum for calculated risk for the development and validation samples, respectively; 39 and 30 times greater in the highest 0.10%; 14 and 12 times greater in the highest 1.00%; and 6.3 and 5.7 times greater in the highest 5.00%. Conclusions. Predictive modeling can identify high-risk patients who were not identified on clinical grounds. VHA is developing modeling to enhance clinical care and to guide the delivery of preventive interventions.

Objectives: The US Department of Veterans Affairs’ Suicide Prevention Applications Network (SPAN) is a national system for suicide event tracking and case management. The objective of this study was to assess data on suicide attempts among people using Veterans Health Administration (VHA) services. Methods: We assessed the degree of data overlap on suicide attempters reported in SPAN and the VHA’s medical records from October 1, 2010, to September 30, 2014—overall, by year, and by region. Data on suicide attempters in the VHA’s medical records consisted of diagnoses documented with E95 codes from the International Classification of Diseases, Ninth Revision. Results: Of 50 518 VHA patients who attempted suicide during the 4-year study period, data on fewer than half (41%) were reported in both SPAN and the medical records; nearly 65% of patients whose suicide attempt was recorded in SPAN had no data on attempted suicide in the VHA’s medical records. Conclusion: Evaluation of administrative data suggests that use of SPAN substantially increases the collection of data on suicide attempters as compared with the use of medical records alone, but neither SPAN nor the VHA’s medical records identify all suicide attempters. Further research is needed to better understand the strengths and limitations of both systems and how to best combine information across systems.

Sexual violence is a serious public health problem that has been associated with negative mental and physical health outcomes. Few existing studies have examined the prevalence and patterns of adverse mental health among victims of sexual violence using data from nationally representative samples of U.S. adults. The main objectives of this study were to identify patterns in the associations between sexual violence victimization and depression and anxiety (DA) symptoms using data from the sexual violence and DA Behavioral Risk Factor Surveillance System (BRFSS) modules. Stratified multivariate logistic regression models were conducted to test the associations between sexual violence victimization and DA controlling for demographic characteristics. Multiple stratified MANOVA models were used to detect the effect of sexual violence victimization on DA symptoms while controlling for key demographic characteristics. Among all 61,187 participants, more than 5% (n = 3,240) were victims of sexual violence, out of which 18.82% reported being diagnosed with depression, 8.37% reported an anxiety disorder, and 28.28% reported being diagnosed with DA disorder. Victims of sexual violence reported significantly higher number of days when they had trouble concentrating, sleep difficulties, poor appetite, little interest or pleasure in activities, blamed themselves for personal failure, felt depressed, and had little energy. The present study highlights the importance of collecting nationally representative data from victims of sexual violence and extends previous findings from clinically based studies. This study also serves as an example of an analytic approach that addresses a public health priority area by drawing on data from multiple topic-specific BRFSS modules.

Objectives. We estimated the prevalence and incidence of gender identity disorder (GID) diagnoses among veterans in the Veterans Health Administration (VHA) health care system and examined suicide risk among veterans with a GID diagnosis. Methods. We examined VHA electronic medical records from 2000 through 2011 for 2 official ICD-9 diagnosis codes that indicate transgender status. We generated annual period prevalence estimates and calculated incidence using the prevalence of GID at 2000 as the baseline year. We cross-referenced GID cases with available data (2009–2011) of suicide-related events among all VHA users to examine suicide risk. Results. GID prevalence in the VHA is higher (22.9/100 000 persons) than are previous estimates of GID in the general US population (4.3/100 000 persons). The rate of suicide-related events among GID-diagnosed VHA veterans was more than 20 times higher than were rates for the general VHA population. Conclusions. The prevalence of GID diagnosis nearly doubled over 10 years among VHA veterans. Research is needed to examine suicide risk among transgender veterans and how their VHA utilization may be enhanced by new VA initiatives on transgender care.

The aim of the study was to report the mental and physical health of a population-based cohort of Gulf War and Gulf Era veterans 20 years after the war. A multimode (mail, Web, or computer-assisted telephone interviewing) heath survey of 14,252 Gulf War and Gulf Era veterans. The survey consisted of questions about general, physical, mental, reproductive, and functional health. Gulf War veterans report a higher prevalence of almost all queried physical and mental health conditions. The population as a whole, however, has a significant burden of disease including high body mass index and multiple comorbid conditions. Gulf War veterans continue to report poorer heath than Gulf Era veterans, 20 years after the war. Chronic disease management and interventions to improve health and wellness among both Gulf War and Gulf Era veterans are necessary.

The World Health Organization has identified intimate partner violence (IPV) as a public health issue affecting both men and women, though significantly more information is available regarding female victimization. This study examines IPV through the lens of male victimization, focusing on a comparison of physical and mental health consequences among men who are and are not military veterans. Results from a secondary analysis of data from the Behavior Risk Factor Survey taken by 13,765 males indicated that all males, regardless of veteran status, should be screened for IPV victimization given the prevalence reported in this sample (9.5% to 12.5%). Furthermore, it was found that veteran status did affect prevalence of particular health consequences, such as depression, smoking, and binge drinking. Based on the specific comparisons examined in this study, implications for Veteran’s Administration Health Services are discussed, as is the need for more research on IPV victimization rates for men and the particular health consequences that they suffer.