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.

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.

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.

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.

Although yoga shows some promise as an intervention for post-traumatic stress disorder (PTSD), little is known about how yoga reduces PTSD symptoms. The current study hypothesised that aspects of interoceptive awareness would mediate the effect of a yoga intervention on PTSD symptoms.

We used data from our recently completed randomised controlled trial of a 16-week holistic yoga programme for veterans and civilians diagnosed with PTSD (n = 141) that offered weekly 90-minute sessions. We conducted a mediation analysis using interoceptive awareness and other variables that were associated with PTSD symptom reduction at mid-treatment and treatment end.

Although measures of anxiety, interoceptive awareness, and spirituality were identified in individual mediator models, they were no longer found to be significant mediators when examined jointly in multiple mediator models. When examining the multiple mediator models, the strongest mediator of the yoga intervention on PTSD symptoms was mental well-being at mid-treatment and stigma at the treatment end. The total effect of yoga on CAPS and PCL at the treatment end mediated by stigma was 37.1% (–1.81/–4.88) and 33.6% (–1.91/–5.68), respectively.

Investigation of mental well-being and mental illness stigma as potential mediators is warranted in future studies of yoga as a treatment for PTSD as they may prove to be important foci for yoga interventions.

Little is known about environmental factors that may influence associations between genetic liability to suicidality and suicidal behavior.

This study examined whether a suicidality polygenic risk score (PRS) derived from a large genome-wide association study (N = 122,935) was associated with suicide attempts in a population-based sample of European-American US military veterans (N = 1664; 92.5% male), and whether cumulative lifetime trauma exposure moderated this association.

Eighty-five veterans (weighted 6.3%) reported a history of suicide attempt. After adjusting for sociodemographic and psychiatric characteristics, suicidality PRS was associated with lifetime suicide attempt (odds ratio 2.65; 95% CI 1.37–5.11). A significant suicidality PRS-by-trauma exposure interaction emerged, such that veterans with higher levels of suicidality PRS and greater trauma burden had the highest probability of lifetime suicide attempt (16.6%), whereas the probability of attempts was substantially lower among those with high suicidality PRS and low trauma exposure (1.4%). The PRS-by-trauma interaction effect was enriched for genes implicated in cellular and developmental processes, and nervous system development, with variants annotated to the DAB2 and SPNS2 genes, which are implicated in inflammatory processes. Drug repurposing analyses revealed upregulation of suicide gene-sets in the context of medrysone, a drug targeting chronic inflammation, and clofibrate, a triacylglyceride level lowering agent.

Results suggest that genetic liability to suicidality is associated with increased risk of suicide attempt among veterans, particularly in the presence of high levels of cumulative trauma exposure. Additional research is warranted to investigate whether incorporation of genomic information may improve suicide prediction models.

Considerable heterogeneity exists in treatment response to first-line posttraumatic stress disorder (PTSD) treatments, such as Cognitive Processing Therapy (CPT). Relatively little is known about the timing of when during a course of care the treatment response becomes apparent. Novel machine learning methods, especially continuously updating prediction models, have the potential to address these gaps in our understanding of response and optimize PTSD treatment.

Using data from a 3-week (n = 362) CPT-based intensive PTSD treatment program (ITP), we explored three methods for generating continuously updating prediction models to predict endpoint PTSD severity. These included Mixed Effects Bayesian Additive Regression Trees (MixedBART), Mixed Effects Random Forest (MERF) machine learning models, and Linear Mixed Effects models (LMM). Models used baseline and self-reported PTSD symptom severity data collected every other day during treatment. We then validated our findings by examining model performances in a separate, equally established, 2-week CPT-based ITP (n = 108).

Results across approaches were very similar and indicated modest prediction accuracy at baseline (R2 ~ 0.18), with increasing accuracy of predictions of final PTSD severity across program timepoints (e.g. mid-program R2 ~ 0.62). Similar findings were obtained when the models were applied to the 2-week ITP. Neither the MERF nor the MixedBART machine learning approach outperformed LMM prediction, though benefits of each may differ based on the application.

Utilizing continuously updating models in PTSD treatments may be beneficial for clinicians in determining whether an individual is responding, and when this determination can be made.

The COVID-19 pandemic has threatened the mental health of individuals around the world. Ex-combatants have been repeatedly shown to be increased risk of experiencing social and psychological problems during emergencies.

To compare the severity of overall posttraumatic stress disorder (PTSD) symptoms and PTSD clusters among help-seeking veterans before and during the COVID-19 pandemic. The second aim was to identify coping strategies used and track possible changes during the timeline.

Male war veterans receiving outpatient treatment at the Referral Center for PTSD were assessed at baseline (t1=12-18 months before the COVID-19 pandemic), during the first lockdown (March-June 2020) and 12 months after the beginning of the COVID-19 pandemic (March-June 2021). A total of 132 veterans participated in all three measurements. The Life Events Checklist for DSM-5 (LEC-5), PTSD Checklist for DSM-5 (PCL-5), and The Brief COPE were used.

Exposure to COVID-19 pandemic related stressors increased over time. The great majority of participants (91.0%) followed the preventive measures. The severity of the overall PTSD symptoms significantly decreased during timeline (t1=56.9, 11.15; t2= 47.24, SD=12.87; t3= 44.1, SD=14.09). At t2, all participants still fulfilled the PTSD diagnostic criteria, and at t3, 23 participants (17.42%) did not meet all of the criteria for PTSD. The participants used adaptive coping rather than dysfunctional coping during the pandemic.

Despite the expectations of worsening the symptoms, help-seeking veterans with PTSD appeared to develop adaptive adjustment to the COVID-19 pandemic stressors, which is in line with the results of the recent longitudinal research and will be discussed.

No significant relationships.

Exposure to potentially morally injurious events (PMIEs) among combat veterans has been acknowledged as a significant stressful combat event that may lead to mental health problems, including suicide ideation (SI). Several studies have examined the risk and protective factors that can explain the conditions in which PMIEs may contribute to the development and maintenance of SI. However, the contribution of social-emotional factors has yet to be examined.

In the current study, we examined the association between PMIE-Self and SI among combat veterans and explored the mediating role of trauma-related shame and the moderation role of collective hatred in this association.

A volunteer sample of 336 Israeli combat veterans was recruited, completing self-report questionnaires in a cross-sectional study.

indicated that PMIE-Self was positively associated with SI, and trauma-related shame mediated this association. Moreover, collective hatred moderated both their direct (PMIE -SI) and indirect (PMIE-Shame-SI) association. Notably, collective hatred had an inverse role for each of the associations. Thus, collective hatred was found to comprise both a risk and a protective factor for SI following PMIE-Self.

The current findings highlight the crucial contribution of trauma-related shame and collective hatred to the association between moral injury and suicidality. Moreover, the findings demonstrate that even years after their military service release, combat veterans exposed to PMIEs may still feel consumed by painful memories and maintain premonitions of a foreshortened future. Furthermore, the findings help to better understand the dynamics of collective hatred and the challenge of modifying it.

No significant relationships.

With the application of virtual reality (VR), tailored interventions can be created that mirror the traumatic experiences of veterans with post-traumatic stress disorder (PTSD). Visual elements can be mimicked, and auditory and other senses stimulated. In doing so, the degree of immersion can be adjusted to optimize the therapeutic process. Objectively measuring the sensory immersion is key to keep subjects within their personal window of tolerance. Based on this information the therapist can decide manipulate the sensory stimulation embedded in the treatment.

The objectives of this study are to explore the different immersive design aspects of VRET that can be modified to influence the experienced presence in veterans with PTSD, and to discuss possible methods of measuring the emotional response facilitated by immersive design aspects and experienced presence.

Four design aspects are discussed: system, sensory cues, narrative and challenge. We also report on a user experiment in three veterans that informed on quality and depth of immersion.

Believability of the neutral virtual environment was important for maintaining the veterans’ presence within the VR experience. The immersive design aspects that were personalized and supportive in the narrative of the veteran such as music and self-selected images appeared to have a strong influence on recall and reliving of the traumatic events.

Finally, in order to increase the therapeutic effect in veterans with PTSD, the highlighted design aspects should be recognized and tailored to maximize immersion in virtual reality exposure therapy.

No significant relationships.

Cognitive processing therapy (CPT) and prolonged exposure (PE) delivered in an individual setting are efficacious and effective treatments for veterans with posttraumatic stress disorder (PTSD). Group CPT has been shown to be less efficacious than individual CPT, however, evidence regarding real-world effectiveness is limited.

We conducted a retrospective, observational, comparative effectiveness study including veterans that received at least eight sessions of group CPT, individual CPT, or individual PE, and were discharged from PTSD residential treatment at the Department of Veterans Affairs between 1 October 2015, and 30 September 2020. PTSD symptom severity was assessed with the PTSD Checklist for DSM-5 (PCL-5) and treatments delivered in a group (CPT) or individual (CPT or PE) setting were compared at discharge and 4-month post-discharge follow-up.

Of 6735 veterans, 3888 [653 women (17%), median (IQR) age 45 (35–55) years] received individual and 2847 [206 women (7.2%), median (IQR) age 42 (34–54)] received group therapy. At discharge, improvement in PTSD severity was statistically greater among those treated individually (mean difference on the PCL-5, 2.55 (95% CI 1.61–3.49); p = <0.001]. However, the difference was smaller than the minimal clinically important difference of 7.9 points. The groups did not differ significantly at 4-month follow-up [mean difference on the PCL-5, 0.37 (95% CI −0.86 to 1.60); p = 0.551].

Group CPT was associated with a slightly smaller reduction of PTSD symptom severity than individual CPT or PE in veterans at the end of residential treatment. There were no differences at 4-month follow-up.

The transition from military service to civilian life is a high-risk period for suicide attempts (SAs). Although stressful life events (SLEs) faced by transitioning soldiers are thought to be implicated, systematic prospective evidence is lacking.

Participants in the Army Study to Assess Risk and Resilience in Servicemembers (STARRS) completed baseline self-report surveys while on active duty in 2011–2014. Two self-report follow-up Longitudinal Surveys (LS1: 2016–2018; LS2: 2018–2019) were subsequently administered to probability subsamples of these baseline respondents. As detailed in a previous report, a SA risk index based on survey, administrative, and geospatial data collected before separation/deactivation identified 15% of the LS respondents who had separated/deactivated as being high-risk for self-reported post-separation/deactivation SAs. The current report presents an investigation of the extent to which self-reported SLEs occurring in the 12 months before each LS survey might have mediated/modified the association between this SA risk index and post-separation/deactivation SAs.

The 15% of respondents identified as high-risk had a significantly elevated prevalence of some post-separation/deactivation SLEs. In addition, the associations of some SLEs with SAs were significantly stronger among predicted high-risk than lower-risk respondents. Demographic rate decomposition showed that 59.5% (s.e. = 10.2) of the overall association between the predicted high-risk index and subsequent SAs was linked to these SLEs.

It might be possible to prevent a substantial proportion of post-separation/deactivation SAs by providing high-risk soldiers with targeted preventive interventions for exposure/vulnerability to commonly occurring SLEs.

Patients with end stage kidney disease (ESKD) are at higher risk for increased mortality and morbidity due to disaster-related disruptions to care. We examine effects of Hurricanes Irma and Maria on access to dialysis care for US Department of Veterans Affairs (VA) ESKD patients in Puerto Rico.

A retrospective, longitudinal cohort study was conducted among VA patients with at least 1 dialysis-related encounter between September 6, 2016, and September 5, 2018. The annual number of dialysis encounters, visits to an emergency department (ED), and the number of deaths pre- and post-hurricanes were compared. A random effects logistic regression model for correlated binary outcomes was fitted for predictors of mortality. Chi-square tests were for differences between pre- and post-hurricane visits.

The number of ED visits increased in post-hurricane period (1172 [5.7%] to 1195 [6.6%]; P < 0.001). ESKD-related ED visits increased from 200 (0.9%) to 227 (1.3%) (P < 0.05). Increase in mortality was associated with age (OR = 1.66; CI: 1.23-2.17), heart failure (OR = 2.07; CI: 1.26-3.40), chronic pulmonary disease (OR = 3.26; CI: 1.28-8.28), and sepsis (OR = 3.16; CI: 1.89-5.29).

There was an increase in dialysis services at the San Juan VA Medical Center post-Irma/Maria, and access to dialysis care at the non-VA clinics was limited. The role of VA dialysis centers in providing care during disasters warrants further investigation.

Network modeling has been applied in a range of trauma-exposed samples, yet results are limited by an over reliance on cross-sectional data. The current analyses used posttraumatic stress disorder (PTSD) symptom data collected over a 5-year period to estimate a more robust between-subject network and an associated symptom change network.

A PTSD symptom network is measured in a sample of military veterans across four time points (Ns = 1254, 1231, 1106, 925). The repeated measures permit isolating between-subject associations by limiting the effects of within-subject variability. The result is a highly reliable PTSD symptom network. A symptom slope network depicting covariation of symptom change over time is also estimated.

Negative trauma-related emotions had particularly strong associations with the network. Trauma-related amnesia, sleep disturbance, and self-destructive behavior had weaker overall associations with other PTSD symptoms.

PTSD's network structure appears stable over time. There is no single ‘most important’ node or node cluster. The relevance of self-destructive behavior, sleep disturbance, and trauma-related amnesia to the PTSD construct may deserve additional consideration.

Homelessness is a major public health problem among U.S. military veterans. However, contemporary, population-based data on the prevalence, correlates, and mental health burden of homelessness among veterans are lacking.

Data were analyzed from the 2019–2020 National Health and Resilience in Veterans Study, a nationally representative survey of veterans (n = 4069). Analyses examined the prevalence and correlates of homelessness, as well as the independent associations between homelessness and current probable psychiatric conditions, suicidality, and functioning.

The lifetime prevalence of homelessness was 10.2% (95% confidence interval 9.3–11.2). More than 8-of-10 veterans reported experiencing their first episode of homelessness following military service, with a mean of 10.6 years post-discharge until onset (s.d. = 12.6). Adverse childhood experiences (ACEs), cumulative trauma burden, current household income, younger age, and drug use disorder emerged as the strongest correlates of homelessness (49% of total explained variance). Veterans with a history of homelessness had elevated odds of lifetime suicide attempt, attempting suicide two or more times, and past-year suicide ideation [odd ratios (ORs) 1.3–3.1]. They also had higher rates of current probable posttraumatic stress disorder, major depressive, generalized anxiety, and drug use disorders (ORs 1.7–2.4); and scored lower on measures of mental, physical, cognitive, psychosocial functioning (d = 0.11–0.15).

One in ten U.S. veterans has experienced homelessness, and these veterans represent a subpopulation at substantially heightened risk for poor mental health and suicide. ACEs were the strongest factor associated with homelessness, thus underscoring the importance of targeting early childhood adversities and their mental health consequences in prevention efforts for homelessness in this population.

To examine socioeconomic disparities in use of electroconvulsive therapy (ECT) among homeless or unstably housed (HUH) veterans with mental illness.

National data from medical records in years 2000 to 2019 on 4 to 6 million veterans with mental illness, including 140 000 to 370 000 homeless veterans served annually from the U.S. Department of Veterans Affairs (VA) healthcare system, were analyzed to examine ECT utilization and changes in utilization over time.

ECT utilization was higher among HUH veterans (58–104 per 1000) than domiciled veterans with mental illness (9–15 per 1000) across years with a trend toward increasing use of ECT use among HUH veterans over time. Among HUH and domiciled veterans who received ECT, veterans received an average of 5 to 9 sessions of ECT. There were great regional differences in rates of ECT utilization among HUH and domiciled veterans with the highest overall rates of ECT use at VA facilities in the Northeast and Northwest regions of the country.

ECT is commonly and safely used in HUH veterans in a comprehensive healthcare system, but geographic and local factors may impede access to ECT for veterans who may benefit from this treatment. Efforts should be made to reduce barriers to ECT in the HUH population.