A practical risk calculator for suicidal behavior among transitioning U.S. Army soldiers: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS).

BACKGROUND: Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions. METHODS: We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011-2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016-2018, LS2: 2018-2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample. RESULTS: Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10-30% of respondents with the highest predicted risk included 44.9-92.5% of 12-month SAs. CONCLUSIONS: An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

Risk for depression and suicidal ideation among food insecure US veterans: data from the National Health and Nutrition Examination Study.

BACKGROUND: Suicide and food insecurity (i.e., lack of access to food) are two major issues that affect US Veterans. PURPOSE: Using a US-based sample, we evaluated the association between food insecurity and suicidal ideation among Veterans. Because depression often precedes suicide, we also examined the association between food insecurity and depression. METHODS: Using data from 2630 Veterans who participated in the National Health and Nutrition Examination Survey 2007-2016, we conducted an adjusted linear regression model to evaluate the association between food insecurity (measured using 18-item Household Food Security Survey) and depression (measured using PHQ-9) and an adjusted binary logistic regression model to evaluate the association between food insecurity and suicidal ideation (measured using PHQ-9 Question 9). Models were adjusted for gender, age, income-to-poverty ratio, race/ethnicity, and education level. RESULTS: Of the sample, 11.5% were food insecure, depression scores averaged 2.86 (SD = 4.28), and 3.7% endorsed suicidal ideation. Veterans with marginal (ß = 0.68, 95%CI [0.09,1.28]), low (ß = 1.38, 95%CI [0.70,2.05]) or very low food security (ß = 3.08, 95%CI [2.34, 3.83]) had significantly increased depression scores compared to food secure Veterans. Veterans with low (OR = 2.15, 95%CI [1.08, 4.27]) or very low food security (OR = 3.84, 95%CI [2.05, 7.20]) had significantly increased odds for suicidal ideation compared to food secure Veterans. CONCLUSION: Food insecurity in Veterans is associated with increased depression symptoms and suicidal ideation. This association strengthens as food insecurity worsens. Veterans with food insecurity should be screened for depression and suicidal ideation. Simultaneously, depression treatment plans and suicide prevention programs should consider basic needs like food security.

A lifeline in the dark: Breaking through the stigma of veteran mental health and treating America's combat veterans.

For generations, veterans have answered the call to service and served their country honorably and with distinction. Unfortunately, the consequences of combat cause many veterans to struggle with life after the military and with readjustment/reintegration into civilian life. Today more than ever, there are a multitude of resources, education, and treatment options for combat veterans. For mental and physical health providers, business leaders, and other professionals who work with veterans, it is of the upmost importance that they learn about programs around them that are successful in treating veterans. The current article reviews two U.S. Department of Veterans Affairs nationwide programs-the Readjustment Counseling Service/Vet Center and Veteran Cultural Competence Training-designed to decrease mental health stigma for veterans and to increase veteran engagement with mental health services. These programs highlight the importance of being aware of the culture within military systems, being aware of personal biases, and fostering an environment of genuineness, safety, and nonjudgmental empathy. In doing so, these programs are successful in reducing the unspoken power of stigmatization; they effectively reach out to veterans in need, providing a lifeline in the dark.

The modern-day Odysseus: How mental health providers can better reintegrate modern warriors and mitigate suicide risk.

During their return from combat, warriors from Greek mythology and Native American traditions received the support of "helpers" to guide the reintegration back into their communities or tribes. While the military provides our modern warriors (MWs), similar helpers, during their departure from their hometown and during their initiation into the military, there is a dearth of comparable help when MWs reintegrate back into their hometowns. We strive to assist mental health providers to serve as such helpers for MWs to shape their reintegration environment, enable MWs to meet their unique needs after exiting the military, ameliorate the MW suicide epidemic, and facilitate MWs to continue their next "mission" to serve and improve society with a newly forged MW identity, wisdom, and sense of purpose.

Beyond stigma: Understanding the "inclined abstainers" in military behavioral health-care utilization.

Low treatment utilization in Soldiers with combat-related Posttraumatic Stress Disorder (PTSD) is an ongoing issue. The critical concern is to better understand factors which prohibit a Soldier with PTSD who wants help from seeking treatment (an "inclined abstainer"). A total of 537 Active Duty Soldiers on a US Army post completed a brief survey comprising psychometrically validated measures of stigma, behavioral health treatment beliefs, resilience, PTSD symptoms, and treatment intentions. Health-care records were prospectively tracked for 12 months to determine the relation between survey answers and treatment utilization. Sixty-three percent of those who acknowledged having a mental health-related problem did not seek help within a one-year period. Greater severity of PTSD symptoms was associated with an increased likelihood of behavioral health engagement. Soldiers that were classified as "inclined abstainers" were also more likely to endorse negative beliefs about psychotherapy and report higher levels of resilience as compared to "inclined actors." These results suggest that a treatment model of PTSD emphasizing self-efficacy and self-reliance, while addressing negative beliefs about psychotherapy, may help promote engagement of behavioral health services among Active Duty Soldiers.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort.

BACKGROUND: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. METHODS: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. DISCUSSION: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.

Exploring high dimensional data with Butterfly: a novel classification algorithm based on discrete dynamical systems.

MOTIVATION: We introduce a novel method for visualizing high dimensional data via a discrete dynamical system. This method provides a 2D representation of the relationship between subjects according to a set of variables without geometric projections, transformed axes or principal components. The algorithm exploits a memory-type mechanism inherent in a certain class of discrete dynamical systems collectively referred to as the chaos game that are closely related to iterative function systems. The goal of the algorithm was to create a human readable representation of high dimensional patient data that was capable of detecting unrevealed subclusters of patients from within anticipated classifications. This provides a mechanism to further pursue a more personalized exploration of pathology when used with medical data. For clustering and classification protocols, the dynamical system portion of the algorithm is designed to come after some feature selection filter and before some model evaluation (e.g. clustering accuracy) protocol. In the version given here, a univariate features selection step is performed (in practice more complex feature selection methods are used), a discrete dynamical system is driven by this reduced set of variables (which results in a set of 2D cluster models), these models are evaluated for their accuracy (according to a user-defined binary classification) and finally a visual representation of the top classification models are returned. Thus, in addition to the visualization component, this methodology can be used for both supervised and unsupervised machine learning as the top performing models are returned in the protocol we describe here. RESULTS: Butterfly, the algorithm we introduce and provide working code for, uses a discrete dynamical system to classify high dimensional data and provide a 2D representation of the relationship between subjects. We report results on three datasets (two in the article; one in the appendix) including a public lung cancer dataset that comes along with the included Butterfly R package. In the included R script, a univariate feature selection method is used for the dimension reduction step, but in the future we wish to use a more powerful multivariate feature reduction method based on neural networks (Kriesel, 2007). AVAILABILITY AND IMPLEMENTATION: A script written in R (designed to run on R studio) accompanies this article that implements this algorithm and is available at http://butterflygeraci.codeplex.com/. For details on the R package or for help installing the software refer to the accompanying document, Supporting Material and Appendix.

Veteran Cultural Competence Training: Initial Effectiveness and National-Level Implementation.

OBJECTIVE: Because service professionals often lack cultural competence in working with veterans, veterans often perceive such professionals as "not understanding." The authors developed, evaluated, and implemented Veteran Cultural Competence Training (VCCT), combining educational and experiential components in an in-person training focused on building awareness, knowledge, and skills to better work with veterans. METHODS: Study 1 was a type 1 effectiveness-implementation hybrid trial examining VCCT effectiveness in a sample of social service professionals (N=41) compared with a matched comparison group (N=41) via the Multicultural Counseling Self-Efficacy Scale-Veteran Form (MCSE-V) instrument. In study 2, the authors used the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework to conduct a type 2 effectiveness-implementation hybrid trial and implemented VCCT with an expanded population (N=312) during eight training sessions in three U.S. states. RESULTS: Results from study 1 indicated that VCCT significantly increased self-efficacy of trainees in veteran cultural competence compared with the matched group (p<0.001). In study 2, the RE-AIM framework highlighted the importance of building coalitions and utilizing implementation facilitation to maintain fidelity. The within-group effectiveness of VCCT was statistically significant and maintained across settings and professions (p<0.001), and trainees were satisfied with VCCT. Maintenance analysis revealed expansion of VCCT after implementation in terms of the number of training sessions (N=9), regions hosting the training (N=5), staff hired (N=13), and trainee applications (N=1,018). CONCLUSIONS: VCCT effectively increases self-efficacy in veteran cultural competence. Gains appeared across different professions, demographic characteristics, and locations. Participation in VCCT may increase professionals' competence in understanding veteran culture, thereby potentially improving veteran services.

Partnership building for scale-up in the Veteran Sponsorship Initiative: Strategies for harnessing collaboration to accelerate impact in suicide prevention.

OBJECTIVE: To evaluate the implementation and trust-building strategies associated with successful partnership formation in scale-up of the Veteran Sponsorship Initiative (VSI), an evidence-based suicide prevention intervention enhancing connection to U.S. Department of Veterans Affairs (VA) and other resources during the military-to-civilian transition period. DATA SOURCES AND STUDY SETTING: Scaling VSI nationally required establishing partnerships across VA, the U.S. Department of Defense (DoD), and diverse public and private Veteran-serving organizations. We assessed partnerships formalized with a signed memorandum during pre- and early implementation periods (October 2020-October 2022). To capture implementation activities, we conducted 39 periodic reflections with implementation team members over the same period. STUDY DESIGN: We conducted a qualitative case study evaluating the number of formalized VSI partnerships alongside directed qualitative content analysis of periodic reflections data using Atlas.ti 22.0. DATA COLLECTION/EXTRACTION METHODS: We first independently coded reflections for implementation strategies, following the Expert Recommendations for Implementing Change (ERIC) taxonomy, and for trust-building strategies, following the Theoretical Model for Trusting Relationships and Implementation; a second round of inductive coding explored emergent themes associated with partnership formation. PRINCIPAL FINDINGS: During this period, VSI established 12 active partnerships with public and non-profit agencies. The VSI team reported using 35 ERIC implementation strategies, including building a coalition and developing educational and procedural documents, and trust-building strategies including demonstrating competence and credibility, frequent interactions, and responsiveness. Cultural competence in navigating DoD and VA and accepting and persisting through conflict also appeared to support scale-up. CONCLUSIONS: VSI's partnership-formation efforts leveraged a variety of implementation strategies, particularly around strengthening stakeholder interrelationships and refining procedures for coordination and communication. VSI implementation activities were further characterized by an intentional focus on trust-building over time. VSI's rapid scale-up highlights the value of partnership formation for achieving coordinated interventions to address complex problems.

Technical and clinical considerations for electroencephalography-based biomarkers for major depressive disorder.

Major depressive disorder (MDD) is a prevalent and debilitating psychiatric disease that leads to substantial loss of quality of life. There has been little progress in developing new MDD therapeutics due to a poor understanding of disease heterogeneity and individuals' responses to treatments. Electroencephalography (EEG) is poised to improve this, owing to the ease of large-scale data collection and the advancement of computational methods to address artifacts. This review summarizes the viability of EEG for developing brain-based biomarkers in MDD. We examine the properties of well-established EEG preprocessing pipelines and consider factors leading to the discovery of sensitive and reliable biomarkers.

Machine learning hypothesis-generation for patient stratification and target discovery in rare disease: our experience with Open Science in ALS.

Introduction: Advances in machine learning (ML) methodologies, combined with multidisciplinary collaborations across biological and physical sciences, has the potential to propel drug discovery and development. Open Science fosters this collaboration by releasing datasets and methods into the public space; however, further education and widespread acceptance and adoption of Open Science approaches are necessary to tackle the plethora of known disease states. Motivation: In addition to providing much needed insights into potential therapeutic protein targets, we also aim to demonstrate that small patient datasets have the potential to provide insights that usually require many samples (>5,000). There are many such datasets available and novel advancements in ML can provide valuable insights from these patient datasets. Problem statement: Using a public dataset made available by patient advocacy group AnswerALS and a multidisciplinary Open Science approach with a systems biology augmented ML technology, we aim to validate previously reported drug targets in ALS and provide novel insights about ALS subpopulations and potential drug targets using a unique combination of ML methods and graph theory. Methodology: We use NetraAI to generate hypotheses about specific patient subpopulations, which were then refined and validated through a combination of ML techniques, systems biology methods, and expert input. Results: We extracted 8 target classes, each comprising of several genes that shed light into ALS pathophysiology and represent new avenues for treatment. These target classes are broadly categorized as inflammation, epigenetic, heat shock, neuromuscular junction, autophagy, apoptosis, axonal transport, and excitotoxicity. These findings are not mutually exclusive, and instead represent a systematic view of ALS pathophysiology. Based on these findings, we suggest that simultaneous targeting of ALS has the potential to mitigate ALS progression, with the plausibility of maintaining and sustaining an improved quality of life (QoL) for ALS patients. Even further, we identified subpopulations based on disease onset. Conclusion: In the spirit of Open Science, this work aims to bridge the knowledge gap in ALS pathophysiology to aid in diagnostic, prognostic, and therapeutic strategies and pave the way for the development of personalized treatments tailored to the individual's needs.

Situational stress and suicide attempt behavior in Army soldiers and veterans: Insights from the Army Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study.

INTRODUCTION: Prevention of suicide-related behaviors is considered a top clinical priority within the Departments of Veterans Affairs and Defense. Despite previous literature attesting to the likely importance of situational stress as a key correlate of acute changes in suicide risk, longitudinal research into associations between situational stress and suicide-related outcomes among military personnel has been relatively limited. METHODS: The current study examined associations between situational stress, recent suicide attempt, and future suicide attempt using data from 14,508 Army soldiers and recently discharged veterans enrolled in the Army Study to Assess Risk and Resilience in Servicemembers-Longitudinal Studies (STARRS-LS). RESULTS: Recent situational stress was more common among recently discharged veterans (vs. soldiers), those with a recent suicide attempt (vs. those without), and those with a subsequent suicide attempt (vs. those without). Job loss was more closely associated with suicide attempts among soldiers, whereas financial crisis, police contact, and death, illness, or injury of close others were more closely associated with suicide attempts among recently discharged veterans. CONCLUSION: Findings further highlight situational stress as a salient risk factor for suicide-related outcomes among military personnel, particularly among recently discharged veterans. Implications for screening and treatment of at-risk military personnel are discussed.

Supporting servicemembers and veterans during their transition to civilian life using certified sponsors: A three-arm randomized controlled trial.

Transitioning servicemembers and veterans (TSMVs) face difficulties throughout their reintegration to civilian life, including challenges with employment, poor social connection, and elevated risk for suicide. To meet the needs of this high-risk population, national initiatives have leveraged community-based interventions. Authors conducted a three-arm randomized controlled trial (n = 200) to evaluate two community-based interventions. The first, Team Red, White, and Blue (RWB), connects TSMVs to their community through physical/social activities. The second, Expiration Term of Service Sponsorship Program (ETS-SP) provides one-on-one certified sponsors to TSMVs who provide support during the reintegration process. TSMVs were assessed at baseline, 3, 6, and 12 months. The primary hypothesis was not supported as reintegration difficulties and social support were not significantly different for participants randomly assigned to the two community-based interventions (Arm-2/RWB and Arm-3/RWB + ETS-SP), when the data from the separate arms were collapsed and combined, compared to the waitlist. The results did support the secondary hypothesis as Arm-3/RWB + ETS-SP had less reintegration difficulties over 12 months and initially had more social support compared to Arm-2/RWB, which suggest that augmenting interventions with sponsors outperforms participation in community-based interventions alone. Overall, the results show some limitations of the studied community-based interventions, as implemented and researched within this study. The authors identified factors that may have contributed to the null findings for the primary hypothesis, which can be addressed in future studies, such as addressing the unique needs of TSMVs, enrolling TSMVs into interventions prior to military discharge, measuring and improving participation levels, and providing stepped-care interventions based on risk levels. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Supporting the nation's transitioning veterans: Narrative review of practices and recommendations for psychotherapy and counseling of veterans separating from military service.

Each year, approximately 200,000 service members transition out of military service and return to civilian life. For many, the stresses of this military-to-civilian transition are vast and include instabilities in mental health, relationships, employment, education, and housing. Given their unique training, mental health professionals often find themselves on the front lines of efforts to support this population. However, to date, literature to guide work with this population has been scant and disorganized. This narrative review provides practitioners both within and outside the Veterans Health Administration with an overview of relevant literature in this area and offers concrete, practical recommendations for how to best support transitioning Veterans through psychotherapy and counseling. Three major themes are reviewed: (a) Engagement strategies, including clinical style, mitigation of privacy concerns, and consideration of broader psychosocial issues; (b) contextual considerations, including challenges of the "Thank You for Your Service" phenomenon, identity considerations, and circumstances of discharge; and (c) information about available services. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

EMT transcription factors snail and slug directly contribute to cisplatin resistance in ovarian cancer.

BACKGROUND: The epithelial to mesenchymal transition (EMT) is a molecular process through which an epithelial cell undergoes transdifferentiation into a mesenchymal phenotype. The role of EMT in embryogenesis is well-characterized and increasing evidence suggests that elements of the transition may be important in other processes, including metastasis and drug resistance in various different cancers. METHODS: Agilent 4 × 44 K whole human genome arrays and selected reaction monitoring mass spectrometry were used to investigate mRNA and protein expression in A2780 cisplatin sensitive and resistant cell lines. Invasion and migration were assessed using Boyden chamber assays. Gene knockdown of snail and slug was done using targeted siRNA. Clinical relevance of the EMT pathway was assessed in a cohort of primary ovarian tumours using data from Affymetrix GeneChip Human Genome U133 plus 2.0 arrays. RESULTS: Morphological and phenotypic hallmarks of EMT were identified in the chemoresistant cells. Subsequent gene expression profiling revealed upregulation of EMT-related transcription factors including snail, slug, twist2 and zeb2. Proteomic analysis demonstrated up regulation of Snail and Slug as well as the mesenchymal marker Vimentin, and down regulation of E-cadherin, an epithelial marker. By reducing expression of snail and slug, the mesenchymal phenotype was largely reversed and cells were resensitized to cisplatin. Finally, gene expression data from primary tumours mirrored the finding that an EMT-like pathway is activated in resistant tumours relative to sensitive tumours, suggesting that the involvement of this transition may not be limited to in vitro drug effects. CONCLUSIONS: This work strongly suggests that genes associated with EMT may play a significant role in cisplatin resistance in ovarian cancer, therefore potentially leading to the development of predictive biomarkers of drug response or novel therapeutic strategies for overcoming drug resistance.

Demographic and socioeconomic correlates of suicide deaths and nonfatal self-injury related hospital visits: An analysis of counties in New York State.

For many years, suicide rates in U.S. general and veteran populations have steadily increased, stimulating research into suicide and nonfatal self-injury (NFSI). However, little research has examined community correlates of suicide and NFSI. This study used county data from New York State to identify community correlates of veteran and general population suicide deaths and general population NFSI-related hospitalization. In bivariate analyses, both suicide and NFSI-related hospitalization were associated with measures of social disintegration (i.e., smaller population size, larger male and/or White population) and socioeconomic disadvantage (i.e., higher disability rates disability, lower household incomes, more limited-English speaking households). In regression analyses, general-population suicide was independently associated with higher disability and veteran-suicide rates, whereas NFSI-related hospitalization was independently associated with lower household income. Findings attest the importance of low-cost, accessible, outpatient services and highlight social disintegration and socioeconomic disadvantage as salient, community risk factors for suicide and NFSI.

Respondents of health survey powered by the innovative NURO app exhibit correlations between exercise frequencies and diet habits, and between stress levels and sleep wellness.

Nurosene's NURO app (nurosene.com) is an innovative smartphone application that gathers and analyzes active self-report metrics from users, empowering them with data-driven health machine intelligence. We present the data collected and analyzed from the initial round of participants who responded to a 12-question survey on their life-style and health status. Exploratory results using a variational autoencoder (VAE) suggested that much of the variability of the 12 dimensional data could be accounted for by two approximately uncorrelated latent variables: one pertaining to stress and sleep, and the other pertaining to exercise and diet. Subsequent modeling of the data using exploratory and confirmatory factor analyses (EFAs and CFAs) found that optimal data fits consisted of four factors, namely exercise, diet, stress, and sleep. Covariance values were high between exercise and diet, and between stress and sleep, but much lower between other pairings of non-identical factors. Both EFAs and CFAs provided extra contexts to and quantified the more preliminary VAE observations. Overall, our results significantly reduce the apparent complexity of the response data. This reduction allows for more efficient future stratification and analyses of participants based on simpler latent variables. Our discovery of novel relationships between stress and sleep, and between exercise and diet suggests the possibility of applying predictive analytics in future efforts.

Prevalence of Personality Disorders Across Veteran Samples: A Meta-Analysis.

Despite priorities around mental health, Veteran health care organizations have historically considered personality disorders to be preexisting conditions ineligible for disability benefits. However, growing evidence suggests potentially elevated prevalence of these disorders among military and Veteran samples and attests to implications of risk. The current study provides a meta-analytic review of literature on the prevalence of personality disorders in Veteran samples. Analysis of 27 unique samples, comprising 7,161 Veterans, suggests alarmingly high rates of Veteran personality disorders. Prevalence was highest for paranoid (23%) and borderline (21%) personality disorders and lowest for histrionic (0.8%) personality disorder. Rates were generally highest among Veterans experiencing substance use or elevated suicide risk and among studies establishing diagnoses through clinical interview (versus official medical record review). Results attest to the need for Veteran health care organizations to acknowledge personality disorders in this population, through both research and treatment, and to consider reclassifying personality disorders as potential "service-connected conditions."

Arrest history and psychopathology among veterans at risk for suicide.

While preliminary evidence suggests an association between legal involvement and suicide risk among veterans, no research to date has explored the prevalence and/or correlates of legal involvement among veterans at high risk for suicide. The current study examined the relation of suicide attempt, suicidal ideation, and psychopathology to history of criminal arrest in a sample of 286 veterans at risk for suicide. Results indicated approximately half (47%) of at-risk veterans had a history of arrest. Inconsistent with hypotheses, arrest history was not associated with history of suicide attempt, current suicidal ideation, or severity of psychopathological symptoms. Arrest history was, however, associated with diagnoses of substance use disorder and antisocial personality disorder in this high-suicide risk sample. Further, likelihood of an antisocial personality disorder diagnosis was associated with higher frequency of past arrests. Taken together, results indicate that many veterans at risk for suicide have a history of arrest, and at-risk veterans with such history likely have a specific pattern of psychopathology, including antisocial personality traits and substance use. As such, legal status and history of justice involvement may be important considerations when assessing suicide risk and management of this high-risk population. (PsycInfo Database Record (c) 2022 APA, all rights reserved).