Impact of the COVID-19 Pandemic on HIV Test Uptake Among People Who Inject Drugs in the Context of an HIV Outbreak.

Glasgow, Scotland's largest city, has been experiencing an HIV outbreak among people who inject drugs (PWID) since 2015. A key focus of the public health response has been to increase HIV testing among those at risk of infection. Our aim was to assess the impact of COVID-19 on HIV testing among PWID in Glasgow. HIV test uptake in the last 12 months was quantified among: (1) PWID recruited in six Needle Exchange Surveillance Initiative (NESI) surveys (n = 6110); linked laboratory data for (2) people prescribed opioid agonist therapy (OAT) (n = 14,527) and (3) people hospitalised for an injecting-related hospital admission (IRHA) (n = 12,621) across four time periods: pre-outbreak (2010-2014); early-outbreak (2015-2016); ongoing-outbreak (2017-2019); and COVID-19 (2020-June 21). From the pre to ongoing period, HIV testing increased: the highest among people recruited in NESI (from 28% to 56%) and on OAT (from 17% to 54%) while the lowest was among people with an IRHA (from 15% to 42%). From the ongoing to the COVID-19 period, HIV testing decreased markedly among people prescribed OAT, from 54% to 37% (aOR 0.50, 95% CI 0.48-0.53), but increased marginally among people with an IRHA from 42% to 47% (aOR 1.19, 95% CI 1.08-1.31). In conclusion, progress in increasing testing in response to the HIV outbreak has been eroded by COVID-19. Adoption of a linked data approach could be warranted in other settings to inform efforts to eliminate HIV transmission.

Polygenic risk for suicide attempt is associated with lifetime suicide attempt in US soldiers independent of parental risk.

BACKGROUND: Suicide is a leading cause of death worldwide. Whereas some studies have suggested that a direct measure of common genetic liability for suicide attempts (SA), captured by a polygenic risk score for SA (SA-PRS), explains risk independent of parental history, further confirmation would be useful. Even more unsettled is the extent to which SA-PRS is associated with lifetime non-suicidal self-injury (NSSI). METHODS: We used summary statistics from the largest available GWAS study of SA to generate SA-PRS for two non-overlapping cohorts of soldiers of European ancestry. These were tested in multivariable models that included parental major depressive disorder (MDD) and parental SA. RESULTS: In the first cohort, 417 (6.3 %) of 6573 soldiers reported lifetime SA and 1195 (18.2 %) reported lifetime NSSI. In a multivariable model that included parental history of MDD and parental history of SA, SA-PRS remained significantly associated with lifetime SA [aOR = 1.26, 95%CI:1.13-1.39, p < 0.001] per standardized unit SA-PRS]. In the second cohort, 204 (4.2 %) of 4900 soldiers reported lifetime SA, and 299 (6.1 %) reported lifetime NSSI. In a multivariable model that included parental history of MDD and parental history of SA, SA-PRS remained significantly associated with lifetime SA [aOR = 1.20, 95%CI:1.04-1.38, p = 0.014]. A combined analysis of both cohorts yielded similar results. In neither cohort or in the combined analysis was SA-PRS significantly associated with NSSI. CONCLUSIONS: PRS for SA conveys information about likelihood of lifetime SA (but not NSSI, demonstrating specificity), independent of self-reported parental history of MDD and parental history of SA. LIMITATIONS: At present, the magnitude of effects is small and would not be immediately useful for clinical decision-making or risk-stratified prevention initiatives, but this may be expected to improve with further iterations. Also critical will be the extension of these findings to more diverse populations.

Associations of active-duty mental health trajectories with post-military adjustment: Results from the STARRS Longitudinal Study.

BACKGROUND: Many servicemembers experience difficulties transitioning from military to civilian life. We examined whether changes in mental health observed during active duty were associated with indices of post-military adjustment. METHODS: Survey data from the multi-wave Army STARRS Pre/Post Deployment Study (PPDS; conducted 2012-2014) were linked to follow-up data from wave 1 of the STARRS Longitudinal Study (STARRS-LS1; conducted 2016-2018). Empirical Bayes estimates of intercepts and slopes of posttraumatic stress, problematic anger, and depressive symptoms during the PPDS were extracted from mixed-effects growth models and evaluated as predictors of life stress among 1080 participants who had separated or retired from the Army at STARRS-LS1; and of job satisfaction among 586 veterans who were employed at STARRS-LS1. RESULTS: Higher average levels and larger increases in posttraumatic stress, anger, and depression over the deployment period were each associated with increased stress and (in the case of anger and depression) reduced job satisfaction. Posttraumatic stress and anger slopes were associated with overall stress (b = 5.60, p < 0.01 and b = 15.64, p = 0.04, respectively) and relationship stress (b = 5.50, p = 0.01 and b = 22.86, p = 0.01, respectively) beyond the average levels of those symptoms. LIMITATIONS: Some transition-related difficulties may have resolved before outcome assessment; some measures were not previously validated. CONCLUSIONS: Larger increases in posttraumatic stress and anger over a deployment period were associated with increased stress after leaving the Army, even after controlling for average symptom levels during the same period. Monitoring changes in mental health during active duty may help identify personnel who need additional support to facilitate the military-to-civilian transition.

Development and Validation of a Machine Learning Prediction Model of Posttraumatic Stress Disorder After Military Deployment.

Importance: Military deployment involves significant risk for life-threatening experiences that can lead to posttraumatic stress disorder (PTSD). Accurate predeployment prediction of PTSD risk may facilitate the development of targeted intervention strategies to enhance resilience. Objective: To develop and validate a machine learning (ML) model to predict postdeployment PTSD. Design, Setting, and Participants: This diagnostic/prognostic study included 4771 soldiers from 3 US Army brigade combat teams who completed assessments between January 9, 2012, and May 1, 2014. Predeployment assessments occurred 1 to 2 months before deployment to Afghanistan, and follow-up assessments occurred approximately 3 and 9 months post deployment. Machine learning models to predict postdeployment PTSD were developed in the first 2 recruited cohorts using as many as 801 predeployment predictors from comprehensive self-report assessments. In the development phase, cross-validated performance metrics and predictor parsimony were considered to select an optimal model. Next, the selected model's performance was evaluated with area under the receiver operating characteristics curve and expected calibration error in a temporally and geographically distinct cohort. Data analyses were performed from August 1 to November 30, 2022. Main Outcomes and Measures: Posttraumatic stress disorder diagnosis was assessed by clinically calibrated self-report measures. Participants were weighted in all analyses to address potential biases related to cohort selection and follow-up nonresponse. Results: This study included 4771 participants (mean [SD] age, 26.9 [6.2] years), 4440 (94.7%) of whom were men. In terms of race and ethnicity, 144 participants (2.8%) identified as American Indian or Alaska Native, 242 (4.8%) as Asian, 556 (13.3%) as Black or African American, 885 (18.3%) as Hispanic, 106 (2.1%) as Native Hawaiian or other Pacific Islander, 3474 (72.2%) as White, and 430 (8.9%) as other or unknown race or ethnicity; participants could identify as of more than 1 race or ethnicity. A total of 746 participants (15.4%) met PTSD criteria post deployment. In the development phase, models had comparable performance (log loss range, 0.372-0.375; area under the curve range, 0.75-0.76). A gradient-boosting machine with 58 core predictors was selected over an elastic net with 196 predictors and a stacked ensemble of ML models with 801 predictors. In the independent test cohort, the gradient-boosting machine had an area under the curve of 0.74 (95% CI, 0.71-0.77) and low expected calibration error of 0.032 (95% CI, 0.020-0.046). Approximately one-third of participants with the highest risk accounted for 62.4% (95% CI, 56.5%-67.9%) of the PTSD cases. Core predictors cut across 17 distinct domains: stressful experiences, social network, substance use, childhood or adolescence, unit experiences, health, injuries, irritability or anger, personality, emotional problems, resilience, treatment, anxiety, attention or concentration, family history, mood, and religion. Conclusions and Relevance: In this diagnostic/prognostic study of US Army soldiers, an ML model was developed to predict postdeployment PTSD risk with self-reported information collected before deployment. The optimal model showed good performance in a temporally and geographically distinct validation sample. These results indicate that predeployment stratification of PTSD risk is feasible and may facilitate the development of targeted prevention and early intervention strategies.

Genetic, environmental, and behavioral correlates of lifetime suicide attempt: Analysis of additive and interactive effects in two cohorts of US Army soldiers.

Recently developed measures of genetic liability to suicide attempt may convey unique information regarding an individual's risk of suicidal behavior. We calculated a polygenic risk score for suicide attempt (SA-PRS) for soldiers of European ancestry who participated in the Army STARRS New Soldier Study (NSS; n = 6573) or Pre/Post Deployment Study (PPDS; n = 4900). Multivariable logistic regression models were fit within each sample to estimate the association of SA-PRS with lifetime suicide attempt (LSA), and to examine whether SA-PRS displayed additive or interactive effects with environmental and behavioral risk/protective factors (lifetime trauma burden, childhood maltreatment, negative urgency impulsivity, social network size, perceived mattering, and dispositional optimism). Age, sex, and within-ancestry variation were included as covariates. Observed prevalence of LSA was 6.3% and 4.2% in the NSS and PPDS samples, respectively. In the NSS model, SA-PRS and environmental/behavioral factors displayed strictly additive effects on odds of LSA. Results indicated an estimated 21% increase in odds of LSA per 1 SD increase in SA-PRS [adjusted odds ratio (AOR; 95% CI) = 1.21 (1.09-1.35)]. In PPDS, the effect of SA-PRS varied by reports of optimism [AOR = 0.85 (0.74-0.98) for SA-PRS x optimism effect]. Individuals reporting low and average optimism had 37% and 16% increased odds of LSA per 1 SD increase in SA-PRS, respectively, whereas SA-PRS was not associated with LSA in those reporting high optimism. Overall, results suggested the SA-PRS had predictive value over and above several environmental and behavioral risk factors for LSA. Moreover, elevated SA-PRS may be more concerning in the presence of environmental and behavioral risk factors (e.g., high trauma burden; low optimism). Given the relatively small effect magnitudes, the cost and incremental benefits of utilizing SA-PRS for risk targeting must also be considered in future work.

Baseline characteristics of people experiencing homelessness with a recent drug overdose in the PHOENIx pilot randomised controlled trial.

BACKGROUND: Drug-related deaths in Scotland are the highest in Europe. Half of all deaths in people experiencing homelessness are drug related, yet we know little about the unmet health needs of people experiencing homelessness with recent non-fatal overdose, limiting a tailored practice and policy response to a public health crisis. METHODS: People experiencing homelessness with at least one non-fatal street drug overdose in the previous 6 months were recruited from 20 venues in Glasgow, Scotland, and randomised into PHOENIx plus usual care, or usual care. PHOENIx is a collaborative assertive outreach intervention by independent prescriber NHS Pharmacists and third sector homelessness workers, offering repeated integrated, holistic physical, mental and addictions health and social care support including prescribing. We describe comprehensive baseline characteristics of randomised participants. RESULTS: One hundred and twenty-eight participants had a mean age of 42 years (SD 8.4); 71% male, homelessness for a median of 24 years (IQR 12-30). One hundred and eighteen (92%) lived in large, congregate city centre temporary accommodation. A quarter (25%) were not registered with a General Practitioner. Participants had overdosed a mean of 3.2 (SD 3.2) times in the preceding 6 months, using a median of 3 (IQR 2-4) non-prescription drugs concurrently: 112 (87.5%) street valium (benzodiazepine-type new psychoactive substances); 77 (60%) heroin; and 76 (59%) cocaine. Half (50%) were injecting, 50% into their groins. 90% were receiving care from Alcohol and Drug Recovery Services (ADRS), and in addition to using street drugs, 90% received opioid substitution therapy (OST), 10% diazepam for street valium use and one participant received heroin-assisted treatment. Participants had a mean of 2.2 (SD 1.3) mental health problems and 5.4 (SD 2.5) physical health problems; 50% received treatment for physical or mental health problems. Ninety-one per cent had at least one mental health problem; 66% had no specialist mental health support. Participants were frail (70%) or pre-frail (28%), with maximal levels of psychological distress, 44% received one or no daily meal, and 58% had previously attempted suicide. CONCLUSIONS: People at high risk of drug-related death continue to overdose repeatedly despite receiving OST. High levels of frailty, multimorbidity, unsuitable accommodation and unmet mental and physical health care needs require a reorientation of services informed by evidence of effectiveness and cost-effectiveness. Trial registration UK Clinical Trials Registry identifier: ISRCTN 10585019.

Prospective Association of Unmet Mental Health Treatment Needs With Suicidal Behavior Among Combat-Deployed Soldiers.

OBJECTIVE: Military personnel frequently report discontinuing or not pursuing psychiatric treatment despite perceiving a need for services. This study aimed to examine how unmet need for treatment or support among U.S. Army soldiers relates to future suicidal ideation (SI) or suicide attempt (SA). METHODS: Mental health treatment need and help seeking in the past 12 months were evaluated for soldiers (N=4,645) who subsequently deployed to Afghanistan. Weighted logistic regression models were used to examine the prospective association of predeployment treatment needs with SI and SA during and after deployment, with adjustment for potential confounders. RESULTS: Compared with soldiers without predeployment treatment needs, those who reported not seeking help despite needing it had increased risk for SI during deployment (adjusted OR [AOR]=1.73), past-30-day SI at 2-3 months postdeployment (AOR=2.08), past-30-day SI at 8-9 months postdeployment (AOR=2.01), and SA through 8-9 months postdeployment (AOR=3.65). Soldiers who sought help and stopped treatment without improvement had elevated SI risk at 2-3 months postdeployment (AOR=2.35). Those who sought help and stopped after improving did not have increased SI risk during or 2-3 months after deployment but had elevated risks for SI (AOR=1.71) and SA (AOR=3.43) by 8-9 months postdeployment. Risks for all suicidality outcomes were also elevated among soldiers who reported receiving ongoing treatment before deployment. CONCLUSIONS: Unmet or ongoing needs for mental health treatment or support before deployment are associated with increased risk for suicidal behavior during and after deployment. Detecting and addressing treatment needs among soldiers before deployment may help prevent suicidality during deployment and reintegration periods.

Associations of polygenic risk scores with posttraumatic stress symptom trajectories following combat deployment.

BACKGROUND: Identification of genetic risk factors may inform the prevention and treatment of posttraumatic stress disorder (PTSD). This study evaluates the associations of polygenic risk scores (PRS) with patterns of posttraumatic stress symptoms following combat deployment. METHOD: US Army soldiers of European ancestry (n = 4900) provided genomic data and ratings of posttraumatic stress symptoms before and after deployment to Afghanistan in 2012. Latent growth mixture modeling was used to model posttraumatic stress symptom trajectories among participants who provided post-deployment data (n = 4353). Multinomial logistic regression models tested independent associations between trajectory membership and PRS for PTSD, major depressive disorder (MDD), schizophrenia, neuroticism, alcohol use disorder, and suicide attempt, controlling for age, sex, ancestry, and exposure to potentially traumatic events, and weighted to account for uncertainty in trajectory classification and missing data. RESULTS: Participants were classified into low-severity (77.2%), increasing-severity (10.5%), decreasing-severity (8.0%), and high-severity (4.3%) posttraumatic stress symptom trajectories. Standardized PTSD-PRS and MDD-PRS were associated with greater odds of membership in the high-severity v. low-severity trajectory [adjusted odds ratios and 95% confidence intervals, 1.23 (1.06-1.43) and 1.18 (1.02-1.37), respectively] and the increasing-severity v. low-severity trajectory [1.12 (1.01-1.25) and 1.16 (1.04-1.28), respectively]. Additionally, MDD-PRS was associated with greater odds of membership in the decreasing-severity v. low-severity trajectory [1.16 (1.03-1.31)]. No other associations were statistically significant. CONCLUSIONS: Higher polygenic risk for PTSD or MDD is associated with more severe posttraumatic stress symptom trajectories following combat deployment. PRS may help stratify at-risk individuals, enabling more precise targeting of treatment and prevention programs.

Exposure to Bullying or Hazing During Deployment and Mental Health Outcomes Among US Army Soldiers.

Importance: Workplace bullying is associated with mental disorders and suicidality in civilians, but few studies have examined associations of bullying with these outcomes among military personnel. Objective: To evaluate associations of being bullied or hazed during deployment with major depressive disorder (MDD), intermittent explosive disorder, posttraumatic stress disorder (PTSD), suicidal ideation, and substance use disorder (SUD). Design, Setting, and Participants: This cohort study used data from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) New Soldier Study (NSS; April 1, 2011, to November 30, 2012) and wave 1 of the STARRS Longitudinal Study (STARRS-LS1; September 1, 2016, to April 30, 2018). A computerized survey administered at 3 US Army installations (NSS) and a web/telephone survey (STARRS-LS1) were used to collect data. Data were analyzed from October 11, 2021, to October 28, 2022. The STARRS-LS1 recruited a probability sample of active-duty soldiers and veterans who had participated in Army STARRS baseline surveys while on active duty (weighted response rate, 35.6%). Respondents whose baseline was the NSS and who had deployed to a combat theater at least once were eligible for this study. Exposures: Being bullied or hazed during a combat deployment. Main Outcomes and Measures: The primary outcomes were MDD, intermittent explosive disorder, PTSD, and suicidal ideation in the 12 months before STARRS-LS1 and SUD in the 30 days before STARRS-LS1, assessed with items from the Composite International Diagnostic Interview Screening Scales, PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and Columbia-Suicide Severity Rating Scale. Logistic regression was used to estimate associations of bullying or hazing exposure with the outcomes. Results: The 1463 participants were predominantly male (weighted percentage [SE], 90.4% [0.9%]) and had a mean (SE) age of 21.1 (0.1) years at baseline. At STARRS-LS1, 188 respondents (weighted percentage [SE], 12.2% [1.1%]) reported bullying or hazing during deployment. Weighted outcome prevalences were 18.7% (1.3%) for MDD, 5.2% (0.9%) for intermittent explosive disorder, 21.8% (1.5%) for PTSD, 14.2% (1.2%) for suicidal ideation, and 8.7% (1.0%) for SUD. In models that adjusted for baseline sociodemographic and clinical characteristics and other potential traumas, exposure to bullying or hazing was significantly associated with MDD (adjusted odds ratio [aOR], 2.92; 95% CI, 1.74-4.88), intermittent explosive disorder (aOR, 2.59; 95% CI, 1.20-5.59), PTSD (aOR, 1.86; 95% CI, 1.23-2.83), suicidal ideation (aOR, 1.91; 95% CI, 1.17-3.13), and SUD (aOR, 2.06; 95% CI, 1.15-3.70). Conclusions and Relevance: In this cohort study of combat-deployed soldiers, reports of being bullied or hazed during deployment were associated with mental disorders and suicidal thoughts. Recognition of these associations may inform efforts to prevent and address mental health problems among service members.

Effects of prior deployments and perceived resilience on anger trajectories of combat-deployed soldiers.

BACKGROUND: Problematic anger is frequently reported by soldiers who have deployed to combat zones. However, evidence is lacking with respect to how anger changes over a deployment cycle, and which factors prospectively influence change in anger among combat-deployed soldiers. METHODS: Reports of problematic anger were obtained from 7298 US Army soldiers who deployed to Afghanistan in 2012. A series of mixed-effects growth models estimated linear trajectories of anger over a period of 1-2 months before deployment to 9 months post-deployment, and evaluated the effects of pre-deployment factors (prior deployments and perceived resilience) on average levels and growth of problematic anger. RESULTS: A model with random intercepts and slopes provided the best fit, indicating heterogeneity in soldiers' levels and trajectories of anger. First-time deployers reported the lowest anger overall, but the most growth in anger over time. Soldiers with multiple prior deployments displayed the highest anger overall, which remained relatively stable over time. Higher pre-deployment resilience was associated with lower reports of anger, but its protective effect diminished over time. First- and second-time deployers reporting low resilience displayed different anger trajectories (stable v. decreasing, respectively). CONCLUSIONS: Change in anger from pre- to post-deployment varies based on pre-deployment factors. The observed differences in anger trajectories suggest that efforts to detect and reduce problematic anger should be tailored for first-time v. repeat deployers. Ongoing screening is needed even for soldiers reporting high resilience before deployment, as the protective effect of pre-deployment resilience on anger erodes over time.

Social network size and personality traits independently and prospectively predict distress disorders and suicidal behavior in U.S. Army soldiers.

BACKGROUND: Personality traits (e.g. neuroticism) and the social environment predict risk for internalizing disorders and suicidal behavior. Studying these characteristics together and prospectively within a population confronted with high stressor exposure (e.g. U.S. Army soldiers) has not been done, yet could uncover unique and interactive predictive effects that may inform prevention and early intervention efforts. METHODS: Five broad personality traits and social network size were assessed via self-administered questionnaires among experienced soldiers preparing for deployment (N = 4645) and new soldiers reporting for basic training (N = 6216). Predictive models examined associations of baseline personality and social network variables with recent distress disorders or suicidal behaviors assessed 3- and 9-months post-deployment and approximately 5 years following enlistment. RESULTS: Among the personality traits, elevated neuroticism was consistently associated with increased mental health risk following deployment. Small social networks were also associated with increased mental health risk following deployment, beyond the variance accounted for by personality. Limited support was found for social network size moderating the association between personality and mental health outcomes. Small social networks also predicted distress disorders and suicidal behavior 5 years following enlistment, whereas unique effects of personality traits on these more distal outcomes were rare. CONCLUSIONS: Heightened neuroticism and small social networks predict a greater risk for negative mental health sequelae, especially following deployment. Social ties may mitigate adverse impacts of personality traits on psychopathology in some contexts. Early identification and targeted intervention for these distinct, modifiable factors may decrease the risk of distress disorders and suicidal behavior.

Pharmacist and Homeless Outreach Engagement and Non-medical Independent prescribing Rx (PHOENIx): a study protocol for a pilot randomised controlled trial.

INTRODUCTION: The number of people experiencing homelessness (PEH) is increasing worldwide. Systematic reviews show high levels of multimorbidity and mortality. Integrated health and social care outreach interventions may improve outcomes. No previous studies have targeted PEH with recent drug overdose despite high levels of drug-related deaths and few data describe their health/social care problems. Feasibility work suggests a collaborative health and social care intervention (Pharmacist and Homeless Outreach Engagement and Non-medical Independent prescribing Rx, PHOENIx) is potentially beneficial. We describe the methods of a pilot randomised controlled trial (RCT) with parallel process and economic evaluation of PEH with recent overdose. METHODS AND ANALYSIS: Detailed health and social care information will be collected before randomisation to care-as-usual plus visits from a pharmacist and a homeless outreach worker (PHOENIx) for 6-9 months or to care-as-usual. The outcomes are the rates of presentations to emergency department for overdose or other causes and whether to progress to a definitive RCT: recruitment of ≥100 participants within 4 months, ≥60% of patients remaining in the study at 6 and 9 months, ≥60% of patients receiving the intervention, and ≥80% of patients with data collected. The secondary outcomes include health-related quality of life, hospitalisations, treatment uptake and patient-reported measures. Semistructured interviews will explore the future implementation of PHOENIx, the reasons for overdose and protective factors. We will assess the feasibility of conducting a cost-effectiveness analysis. ETHICS AND DISSEMINATION: The study was approved by South East Scotland National Health Service Research Ethics Committee 01. Results will be made available to PEH, the study funders and other researchers. TRIAL REGISTRATION NUMBER: ISRCTN10585019.

Prospective relations between anxiety sensitivity and transdiagnostic anxiety following cognitive-behavioral therapy: Evidence from the Coordinated Anxiety Learning management trial.

Previous research has implicated reductions in anxiety sensitivity (AS) - the dispositional tendency to fear anxiety-related sensations - as critical to change during cognitive behavioral therapy (CBT) for anxiety. However, the relationship of AS to anxiety symptom remittance following CBT remains largely unknown. To address this gap, the current study evaluated prospective associations between AS and symptoms of various anxiety disorders following completion of the Coordinated Anxiety Learning and Management (CALM) study- a large clinical trial evaluating the efficacy of a brief, computer-facilitated CBT intervention for transdiagnostic anxiety within primary care. Participants were randomized to CALM (n = 460) or a control treatment (n = 501) and completed self-report measures of general and disorder-specific anxiety symptoms at pretreatment and at 6-month, 12-month, and 18-month follow-up. Longitudinal relations between AS and each anxiety measure across timepoints and within each treatment group were assessed using cross-lagged panel models. Results indicated that higher AS following CALM predicted greater anxiety symptoms at the subsequent timepoint for all anxiety symptoms except social anxiety symptoms. Higher anxiety following treatment also predicted later AS. These findings implicate AS as an indicator of transdiagnostic anxiety remittance and suggest that targeting AS could be useful for reducing clinical anxiety relapse following CBT.

Unit cohesion during deployment and post-deployment mental health: is cohesion an individual- or unit-level buffer for combat-exposed soldiers?

BACKGROUND: Unit cohesion may protect service member mental health by mitigating effects of combat exposure; however, questions remain about the origins of potential stress-buffering effects. We examined buffering effects associated with two forms of unit cohesion (peer-oriented horizontal cohesion and subordinate-leader vertical cohesion) defined as either individual-level or aggregated unit-level variables. METHODS: Longitudinal survey data from US Army soldiers who deployed to Afghanistan in 2012 were analyzed using mixed-effects regression. Models evaluated individual- and unit-level interaction effects of combat exposure and cohesion during deployment on symptoms of post-traumatic stress disorder (PTSD), depression, and suicidal ideation reported at 3 months post-deployment (model n's = 6684 to 6826). Given the small effective sample size (k = 89), the significance of unit-level interactions was evaluated at a 90% confidence level. RESULTS: At the individual-level, buffering effects of horizontal cohesion were found for PTSD symptoms [B = -0.11, 95% CI (-0.18 to -0.04), p < 0.01] and depressive symptoms [B = -0.06, 95% CI (-0.10 to -0.01), p < 0.05]; while a buffering effect of vertical cohesion was observed for PTSD symptoms only [B = -0.03, 95% CI (-0.06 to -0.0001), p < 0.05]. At the unit-level, buffering effects of horizontal (but not vertical) cohesion were observed for PTSD symptoms [B = -0.91, 90% CI (-1.70 to -0.11), p = 0.06], depressive symptoms [B = -0.83, 90% CI (-1.24 to -0.41), p < 0.01], and suicidal ideation [B = -0.32, 90% CI (-0.62 to -0.01), p = 0.08]. CONCLUSIONS: Policies and interventions that enhance horizontal cohesion may protect combat-exposed units against post-deployment mental health problems. Efforts to support individual soldiers who report low levels of horizontal or vertical cohesion may also yield mental health benefits.

Association between neurocognitive functioning and suicide attempts in U.S. Army Soldiers.

BACKGROUND: Suicide is a serious public health problem, including among U.S. Army personnel. There is great interest in discovering objective predictors of suicide and non-fatal suicidal behaviors. The current study examined the association between neurocognitive functioning and pre-military history of suicide attempts (SA) and post-enlistment onset of SA. METHODS: New Soldiers reporting for Basic Combat Training (N = 38,507) completed a comprehensive computerized neurocognitive assessment battery and self-report questionnaires. A subset of Soldiers (n = 6216) completed a follow-up survey, including assessment of lifetime SA, 3-7 years later. RESULTS: Six hundred eighty-nine Soldiers indicated lifetime SA at baseline and 210 Soldiers indicated new-onset SA at follow-up. Regression analyses, adjusted for demographic variables, revealed significant bivariate associations between neurocognitive performance on measures of sustained attention, impulsivity, working memory, and emotion recognition and lifetime SA at baseline. In a multivariable model including each of these measures as predictors, poorer impulse control and quicker response times on an emotion recognition measure were significantly and independently associated with increased odds of lifetime SA. A second model predicted new-onset SA at follow-up for Soldiers who did not indicate a history of SA at baseline. Poorer impulse control on a measure of sustained attention was predictive of new-onset SA. LIMITATIONS: Effect sizes are small and of unlikely clinical predictive utility. CONCLUSIONS: We simultaneously examined multiple neurocognitive domains as predictors of SA in a large, representative sample of new Army Soldiers. Impulsivity most strongly predicted past and future SA over and beyond other implicated cognitive-emotional domains.

Association Between Responsibility for the Death of Others and Postdeployment Mental Health and Functioning in US Soldiers.

Importance: Rates of suicidal thoughts and behaviors (STBs) in US soldiers have increased sharply since the terrorist attacks on September 11, 2001, and postdeployment posttraumatic stress disorder (PTSD) remains a concern. Studies show that soldiers with greater combat exposure are at an increased risk for adverse mental health outcomes, but little research has been conducted on the specific exposure of responsibility for the death of others. Objective: To examine the association between responsibility for the death of others in combat and mental health outcomes among active-duty US Army personnel at 2 to 3 months and 8 to 9 months postdeployment. Design, Setting, and Participants: This cohort study obtained data from a prospective 4-wave survey study of 3 US Army brigade combat teams that deployed to Afghanistan in 2012. The sample was restricted to soldiers with data at all 4 waves (1-2 months predeployment, and 2-3 weeks, 2-3 months, and 8-9 months postdeployment). Data analysis was performed from December 12, 2020, to April 23, 2021. Main Outcomes and Measures: Primary outcomes were past-30-day PTSD, major depressive episode, STBs, and functional impairment at 2 to 3 vs 8 to 9 months postdeployment. Combat exposures were assessed using a combat stress scale. The association of responsibility for the death of others during combat was tested using separate multivariable logistic regression models per outcome adjusted for age, sex, race and ethnicity, marital status, brigade combat team, predeployment lifetime internalizing and externalizing disorders, and combat stress severity. Results: A total of 4645 US soldiers (mean [SD] age, 26.27 [6.07] years; 4358 men [94.0%]) were included in this study. After returning from Afghanistan, 22.8% of soldiers (n = 1057) reported responsibility for the death of others in combat. This responsibility was not associated with any outcome at 2 to 3 months postdeployment (PTSD odds ratio [OR]: 1.23 [95% CI, 0.93-1.63]; P = .14; STB OR: 1.19 [95% CI, 0.84-1.68]; P = .33; major depressive episode OR: 1.03 [95% CI, 0.73-1.45]; P = .87; and functional impairment OR: 1.12 [95% CI, 0.94-1.34]; P = .19). However, responsibility was associated with increased risk for PTSD (OR, 1.42; 95% CI, 1.09-1.86; P = .01) and STBs (OR, 1.55; 95% CI, 1.03-2.33; P = .04) at 8 to 9 months postdeployment. Responsibility was not associated with major depressive episode (OR, 1.30; 95% CI, 0.93-1.81; P = .13) or functional impairment (OR, 1.13; 95% CI, 0.94-1.36; P = .19). When examining enemy combatant death only, the pattern of results was unchanged for PTSD (OR, 1.44; 95 CI%, 1.10-1.90; P = .009) and attenuated for STBs (OR, 1.46; 95 CI%, 0.97- 2.20; P = .07). Conclusions and Relevance: This cohort study found an association between being responsible for the death of others in combat and PTSD and STB at 8 to 9 months, but not 2 to 3 months, postdeployment in active-duty soldiers. The results suggest that delivering early intervention to those who report such responsibility may mitigate the subsequent occurrence of PTSD and STBs.

Pre-enlistment Anger Attacks and Postenlistment Mental Disorders and Suicidality Among US Army Soldiers.

Importance: Anger is linked to adverse outcomes in military populations; however, whether pre-enlistment anger attacks are associated with postenlistment mental disorders and suicidality is unknown. Objective: To explore the associations of pre-enlistment anger attacks with postenlistment mental health. Design, Setting, and Participants: In this observational cohort study, the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) New Soldier Study (NSS) surveyed soldiers entering basic training from April 2011 to November 2012, with a subsample recruited for wave 1 of the STARRS Longitudinal Study (STARRS-LS) (conducted September 2016 to April 2018). Participants were recruited from 3 US Army installations for the NSS survey. Those who were subsequently contacted for STARRS-LS completed the follow-up survey via web or telephone. Prospective analyses were based on a weighted NSS subsample included in wave 1 of STARRS-LS. Data were analyzed from May 22, 2020, to March 17, 2021. Exposures: History of anger attacks at baseline (NSS). Survey responses were used to classify new soldiers as having nonimpairing anger attacks (>2 attacks without interference in work or personal life), impairing anger attacks (>2 attacks with interference in work or personal life), or no significant history of anger attacks. Main Outcomes and Measures: Baseline analyses examined sociodemographic and clinical correlates of a history of anger attacks. Prospective logistic regression models estimated associations of baseline history of anger attacks with new onset and persistence of posttraumatic stress disorder, major depressive disorder (MDD), generalized anxiety disorder (GAD), panic disorder, mania/hypomania, substance use disorder, suicidal ideation, and suicide attempt at wave 1 of STARRS-LS. Results: Of the 38 507 baseline participants (83.0% male and 17.0% female; mean [SD] age, 20.97 [3.57] years), 6216 were selected for and completed wave 1 of the STARRS-LS. Baseline prevalence (SE) of nonimpairing and impairing anger attacks was 8.83% (0.16%) and 5.75% (0.15%), respectively. Prospective models showed that impairing anger attacks were associated with new onset of MDD (adjusted odds ratio [AOR], 1.98; 95% CI, 1.31-2.99), GAD (AOR, 2.39; 95% CI, 1.66-3.45), panic disorder (AOR, 2.02; 95% CI, 1.34-3.05), and suicidal ideation (AOR, 2.11; 95% CI, 1.45-3.07). When baseline psychiatric comorbidity was controlled for, impairing attacks remained associated with onset of GAD (AOR, 1.75; 95% CI, 1.19-2.58) and suicidal ideation (AOR, 1.62; 95% CI, 1.09-2.42). Anger attacks were not significantly associated with persistence of pre-enlistment mental disorders. Conclusions and Relevance: The findings of this study suggest that a pre-enlistment history of impairing anger attacks may be associated with elevated risk of developing GAD, MDD, and suicidality after enlistment. Detection of impairing anger attacks could aid in assessing psychiatric risk in new soldiers.

Polygenic risk for major depression is associated with lifetime suicide attempt in US soldiers independent of personal and parental history of major depression.

Suicide is a major public health problem. The contribution of common genetic variants for major depressive disorder (MDD) independent of personal and parental history of MDD has not been established. Polygenic risk score (using PRS-CS) for MDD was calculated for US Army soldiers of European ancestry. Associations between polygenic risk for MDD and lifetime suicide attempt (SA) were tested in models that also included parental or personal history of MDD. Models were adjusted for age, sex, tranche (where applicable), and 10 principal components reflecting ancestry. In the first cohort, 417 (6.3%) of 6,573 soldiers reported a lifetime history of SA. In a multivariable model that included personal [OR = 3.83, 95% CI:3.09-4.75] and parental history of MDD [OR = 1.43, 95% CI:1.13-1.82 for one parent and OR = 1.64, 95% CI:1.20-2.26 for both parents), MDD PRS was significantly associated with SA (OR = 1.22 [95% CI:1.10-1.36]). In the second cohort, 204 (4.2%) of 4,900 soldiers reported a lifetime history of SA. In a multivariable model that included personal [OR = 3.82, 95% CI:2.77-5.26] and parental history of MDD [OR = 1.42, 95% CI:0.996-2.03 for one parent and OR = 2.21, 95% CI:1.33-3.69 for both parents) MDD PRS continued to be associated (at p = .0601) with SA (OR = 1.15 [95% CI:0.994-1.33]). A soldier's PRS for MDD conveys information about likelihood of a lifetime SA beyond that conveyed by two predictors readily obtainable by interview: personal or parental history of MDD. Results remain to be extended to prospective prediction of incident SA. These findings portend a role for PRS in risk stratification for suicide attempts.

Dissecting the heterogeneity of posttraumatic stress disorder: differences in polygenic risk, stress exposures, and course of PTSD subtypes.

BACKGROUND: Definition of disorder subtypes may facilitate precision treatment for posttraumatic stress disorder (PTSD). We aimed to identify PTSD subtypes and evaluate their associations with genetic risk factors, types of stress exposures, comorbidity, and course of PTSD. METHODS: Data came from a prospective study of three U.S. Army Brigade Combat Teams that deployed to Afghanistan in 2012. Soldiers with probable PTSD (PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition ≥31) at three months postdeployment comprised the sample (N = 423) for latent profile analysis using Gaussian mixture modeling and PTSD symptom ratings as indicators. PTSD profiles were compared on polygenic risk scores (derived from external genomewide association study summary statistics), experiences during deployment, comorbidity at three months postdeployment, and persistence of PTSD at nine months postdeployment. RESULTS: Latent profile analysis revealed profiles characterized by prominent intrusions, avoidance, and hyperarousal (threat-reactivity profile; n = 129), anhedonia and negative affect (dysphoric profile; n = 195), and high levels of all PTSD symptoms (high-symptom profile; n = 99). The threat-reactivity profile had the most combat exposure and the least comorbidity. The dysphoric profile had the highest polygenic risk for major depression, and more personal life stress and co-occurring major depression than the threat-reactivity profile. The high-symptom profile had the highest rates of concurrent mental disorders and persistence of PTSD. CONCLUSIONS: Genetic and trauma-related factors likely contribute to PTSD heterogeneity, which can be parsed into subtypes that differ in symptom expression, comorbidity, and course. Future studies should evaluate whether PTSD typology modifies treatment response and should clarify distinctions between the dysphoric profile and depressive disorders.

Prevalence of Frailty in Patients Referred to the Kidney Transplant Waitlist.

Background: Comparisons between frailty assessment tools for waitlist candidates are a recognized priority area for kidney transplantation. We compared the prevalence of frailty using three established tools in a cohort of waitlist candidates. Methods: Waitlist candidates were prospectively enrolled from 2016 to 2020 across five centers. Frailty was measured using the Frailty Phenotype (FP), a 37-variable frailty index (FI), and the Clinical Frailty Scale (CFS). The FI and CFS were dichotomized using established cutoffs. Agreement was compared using κ coefficients. Area under the receiver operating characteristic (ROC) curves were generated to compare the FI and CFS (treated as continuous measures) with the FP. Unadjusted associations between each frailty measure and time to death or waitlist withdrawal were determined using an unadjusted Cox proportional hazards model. Results: Of 542 enrolled patients, 64% were male, 80% were White, and the mean age was 54±14 years. The prevalence of frailty by the FP was 16%. The mean FI score was 0.23±0.14, and the prevalence of frailty was 38% (score of ≥0.25). The median CFS score was three (IQR, 2-3), and the prevalence was 15% (score of ≥4). The κ values comparing the FP with the FI (0.44) and CFS (0.27) showed fair to moderate agreement. The area under the ROC curves for the FP and FI/CFS were 0.86 (good) and 0.69 (poor), respectively. Frailty by the CFS (HR, 2.10; 95% CI, 1.04 to 4.24) and FI (HR, 1.79; 95% CI, 1.00 to 3.21) was associated with death or permanent withdrawal. The association between frailty by the FP and death/withdrawal was not statistically significant (HR, 1.78; 95% CI, 0.79 to 3.71). Conclusion: Frailty prevalence varies by the measurement tool used, and agreement between these measurements is fair to moderate. This has implications for determining the optimal frailty screening tool for use in those being evaluated for kidney transplant.