Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records.

Efforts to develop an individualized treatment rule (ITR) to optimize major depressive disorder (MDD) treatment with antidepressant medication (ADM), psychotherapy, or combined ADM-psychotherapy have been hampered by small samples, small predictor sets, and suboptimal analysis methods. Analyses of large administrative databases designed to approximate experiments followed iteratively by pragmatic trials hold promise for resolving these problems. The current report presents a proof-of-concept study using electronic health records (EHR) of n = 43,470 outpatients beginning MDD treatment in Veterans Health Administration Primary Care Mental Health Integration (PC-MHI) clinics, which offer access not only to ADMs but also psychotherapy and combined ADM-psychotherapy. EHR and geospatial databases were used to generate an extensive baseline predictor set (5,865 variables). The outcome was a composite measure of at least one serious negative event (suicide attempt, psychiatric emergency department visit, psychiatric hospitalization, suicide death) over the next 12 months. Best-practices methods were used to adjust for nonrandom treatment assignment and to estimate a preliminary ITR in a 70% training sample and to evaluate the ITR in the 30% test sample. Statistically significant aggregate variation was found in overall probability of the outcome related to baseline predictors (AU-ROC = 0.68, S.E. = 0.01), with test sample outcome prevalence of 32.6% among the 5% of patients having highest predicted risk compared to 7.1% in the remainder of the test sample. The ITR found that psychotherapy-only was the optimal treatment for 56.0% of patients (roughly 20% lower risk of the outcome than if receiving one of the other treatments) and that treatment type was unrelated to outcome risk among other patients. Change in aggregate treatment costs of implementing this ITR would be negligible, as 16.1% fewer patients would be prescribed ADMs and 2.9% more would receive psychotherapy. A pragmatic trial would be needed to confirm the accuracy of the ITR.

The PTSD Criterion A debate: A brief history, current status, and recommendations for moving forward.

Posttraumatic stress disorder (PTSD) Criterion A, also known as the "stressor criterion," has been a major source of debate ever since PTSD was added to the third edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM) in 1980. Since then, the traumatic stress field has held an ongoing debate about how to best define Criterion A and the events that it covers. Because of the COVID-19 pandemic and recent race-based incidents, the Criterion A debate has been reinvigorated. In this paper, we review briefly the history of Criterion A and changes in its language across different editions of the DSM. We then describe the four main positions held by scholars involved in the Criterion A debate and carefully examine the support for those positions. We conclude by offering recommendations for moving forward.

An empirical investigation of definitions of subthreshold posttraumatic stress disorder.

Subthreshold posttraumatic stress disorder (PTSD) has long been recognized as an important construct that identifies a subgroup of individuals who report significant PTSD symptoms and associated disability but do not endorse enough symptoms to meet the criteria for a full PTSD diagnosis. Different investigators have defined subthreshold PTSD in various ways, making it difficult to interpret findings across studies. To address this problem, we systematically compared individuals who met criteria for nine different subthreshold PTSD definitions with individuals diagnosed with either full PTSD or no PTSD (i.e., failed to meet the criteria for a subthreshold definition) with respect to prevalence and associated clinical outcomes of interest. Participants were 1,082 veterans enrolled in the Veterans After Discharge Longitudinal Registry. PTSD and subthreshold PTSD diagnostic status were determined using the Structured Clinical Interview for DSM-5 (SCID-5) and validated self-report instruments were used to assess clinical outcomes. Across outcomes, subthreshold definitions generally identified a group of participants that was distinguishable from participants in both the PTSD and no PTSD groups, rs = .02-.47. We discuss the benefits and drawbacks of various subthreshold definitions and highlight the need for additional work evaluating these definitions across additional outcomes and samples. In the interim, we propose a working case definition of subthreshold PTSD as meeting any three of the four DSM-5 symptom criteria (i.e., Criteria B, C, D, and E) along with Criterion A and Criteria F-H. The results suggest subthreshold PTSD is a clinically meaningful construct.

Trauma exposure and transdiagnostic distress: Examining shared and posttraumatic stress disorder-specific associations.

We examined transdiagnostic and posttraumatic stress disorder (PTSD)-specific associations with multiple forms of trauma exposure within a nationwide U.S. sample (N = 1,649, 50.0% female) of military veterans overselected for PTSD. A higher-order Distress factor was estimated using PTSD, major depressive disorder (MDD), and generalized anxiety disorder (GAD) symptoms as indicators. A structural equation model spanning three assessment points over an average of 3.85 years was constructed to examine the unique roles of higher-order Distress and PTSD-specific variance in accounting for the associations between trauma exposure, measured using the Life Events Checklist (LEC) and Deployment Risk and Resiliency Inventory Combat subscale (DRRI-C), and psychosocial impairment. The results suggest the association between trauma exposure and PTSD symptoms was primarily mediated by higher-order distress (70.7% of LEC effect, 63.2% of DRRI-C effect), but PTSD severity retained a significant association with trauma exposure independent of distress, LEC: ß = .10, 95% CI [.06, .13]; DRRI-C: ß = .11, 95% CI [.07, .14]. Both higher-order distress, ß = .31, and PTSD-specific variance, ß = .36, were necessary to account for the association between trauma exposure and future impairment. Findings suggest that trauma exposure may contribute to comorbidity across a range of internalizing symptoms as well as to PTSD-specific presentations.

Longitudinal PTSD network structure: measuring PTSD symptom networks over 5 years.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Associations of vulnerability to stressful life events with suicide attempts after active duty among high-risk soldiers: results from the Study to Assess Risk and Resilience in Servicemembers-longitudinal study (STARRS-LS).

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

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.

Predicting suicide attempts among U.S. Army soldiers after leaving active duty using information available before leaving active duty: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS).

Suicide risk is elevated among military service members who recently transitioned to civilian life. Identifying high-risk service members before this transition could facilitate provision of targeted preventive interventions. We investigated the feasibility of doing this by attempting to develop a prediction model for self-reported suicide attempts (SAs) after leaving or being released from active duty in the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS). This study included two self-report panel surveys (LS1: 2016-2018, LS2: 2018-2019) administered to respondents who previously participated while on active duty in one of three Army STARRS 2011-2014 baseline self-report surveys. We focus on respondents who left active duty >12 months before their LS survey (n = 8899). An ensemble machine learning model using predictors available prior to leaving active duty was developed in a 70% training sample and validated in a 30% test sample. The 12-month self-reported SA prevalence (SE) was 1.0% (0.1). Test sample AUC (SE) was 0.74 (0.06). The 15% of respondents with highest predicted risk included nearly two-thirds of 12-month SAs and over 80% of medically serious 12-month SAs. These results show that it is possible to identify soldiers at high post-transition self-report SA risk before the transition. Future model development is needed to examine prediction of SAs assessed by administrative data and using surveys administered closer to the time of leaving active duty.

Minimal important difference metrics and test-retest reliability of the PTSD Checklist for DSM-5 with a primary care sample.

The PTSD Checklist for DSM-5 (PCL-5) is a measure of posttraumatic stress disorder (PTSD) symptom severity that is widely used for clinical and research purposes. Although previous work has examined metrics of minimal important difference (MID) of the PCL-5 in veteran samples, no work has identified PCL-5 MID metrics among adults in primary care in the United States. In this secondary analysis, data were evaluated from primary care patients (N = 971) who screened positive for PTSD and participated in a large clinical trial in federally qualified health centers in three U.S. states. Participants primarily self-identified as women (70.2%) and White (70.3%). We calculated test-retest reliability using clinic registry data and multiple distribution- and anchor-based metrics of MID using baseline and follow-up survey data. Test-retest reliability (Pearson's r, Spearman's ρ, intraclass correlation coefficient) ranged from adequate to excellent (.79-.94), with the shortest time lag demonstrating the highest reliability estimate. The MID for the PCL-5 was estimated using multiple approaches. Distribution-based approaches indicated an MID range of 8.5-12.5, and anchor-based approaches indicated an MID range of 9.8-11.7. Taken together, the MID metrics indicate that PCL-5 change scores of 9-12 likely reflect real change in PTSD symptoms and indicate at least an MID for patients, whereas PCL-5 change scores of 5 or less likely are not reliable. These findings can help inform clinicians using the PCL-5 in similar populations to track patient responses to treatment and help researchers interpret PCL-5 score changes in clinical trials.

Early predictors of chronic posttraumatic stress disorder symptom trajectories in U.S. Army soldiers deployed to the Iraq war zone.

The course of posttraumatic stress disorder (PTSD) symptoms varies among veterans of war zones, but sources of variation in long-term symptom course remain poorly understood. Modeling of symptom growth trajectories facilitates the understanding of predictors of individual outcomes over time. Although growth mixture modeling (GMM) has been applied to military populations, few studies have incorporated both predeployment and follow-up measurements over an extended time. In this prospective study, 1,087 U.S. Army soldiers with varying military occupational specialties and geographic locations were assessed before and after deployment to the Iraq war zone, with long-term follow-up assessment occurring at least 5 years after return from deployment. The primary outcome variable was the PTSD Checklist-Civilian Version summary score. GMM yielded four latent profiles, characterized as primarily asymptomatic (n = 194, 17.8%); postdeployment worsening symptoms (n = 84, 7.7%); mild symptoms (n = 320, 29.4%); and preexisting, with a chronic postdeployment elevation of symptoms (n = 489, 45.0%). Regression models comparing the primarily asymptomatic class to the symptomatic classes revealed that chronic symptom classes were associated with higher degrees of stress exposure, less predeployment social support, military reservist or veteran status at the most recent assessment, and poorer predeployment visual memory, ORs = 0.98-2.90. PTSD symptom course varies considerably over time after military deployment and is associated with potentially modifiable biopsychosocial factors that occur early in its course in addition to exposures and military status.

Examining unique and prospective relationships among self-injurious thoughts and behaviors and posttraumatic stress disorder: a network analysis in two trauma-exposed samples.

BACKGROUND: As self-injurious thoughts and behaviors (SITB) remain a pressing public health concern, research continues to focus on risk factors, such as posttraumatic stress disorder (PTSD). Network analysis provides a novel approach to examining the PTSD-SITB relationship. This study utilized the network approach to elucidate how individual PTSD symptoms may drive and maintain SITB. METHODS: We estimated cross-sectional networks in two samples of trauma-exposed adults (Sample 1: N = 349 adults; Sample 2: N = 1307 Veterans) to identify PTSD symptoms that may act as bridges to SITB. Additionally, we conducted a cross-lagged panel network in Sample 2 to further clarify the temporal relationship between PTSD symptoms and SITB during a 2-year follow-up. Finally, in both samples, we conducted logistic regressions to examine the utility of PTSD symptoms in prospectively predicting SITB, over a 15-day period (Sample 1) and over a 2-year period (Sample 2), allowing us to examine both short- and long-term prediction. RESULTS: Two PTSD symptoms (i.e. negative beliefs and risky behaviors) emerged as highly influential on SITB in both cross-sectional networks. In the cross-lagged panel network, distorted blame emerged as highly influential on SITB over time. Finally, risky behaviors, unwanted memories, and psychological distress served as the strongest predictors of SITB across the two samples. CONCLUSIONS: Overall, our results suggest that treatments targeting negative beliefs and risky behaviors may prevent SITB in community and Veteran populations, whereas treatments targeting distorted blame and unwanted memories may help reduce SITB for individuals with a history of combat trauma.

Using electronic medical record diagnostic codes to identify veterans with posttraumatic stress disorder.

Researchers studying posttraumatic stress disorder (PTSD) often use diagnostic codes within electronic medical records (EMRs) to identify individuals with the disorder. This study evaluated the performance of algorithms for defining PTSD based on International Classification of Diseases (ICD) code use within EMR data. We used data from a registry of U.S. veterans for whom both structured interview data and Veterans Health Administration EMR data were available. Using interview-diagnosed PTSD as the reference criterion, we calculated diagnostic accuracy statistics for algorithms that required the presence of at least one and up to seven encounters in which a PTSD diagnosis was present in EMR data within any clinical source, mental health clinic, or specialty PTSD clinic. We evaluated algorithm accuracy in the total sample (N = 1,343; 64.1% with PTSD), within a subsample constrained to lower PTSD prevalence (n = 712; 32.3% with PTSD), and as a function of demographic characteristics. Algorithm accuracy was influenced by PTSD prevalence. Results indicated that higher thresholds for the operationalization of PTSD may be justified among samples in which PTSD prevalence is lower. Requiring three PTSD diagnoses from a mental health clinic or four diagnoses from any clinical source may be a suitable minimum standard for identifying individuals with PTSD in EMRs; however, accuracy may be optimized by requiring additional diagnoses. The performance of many algorithms differed as a function of educational attainment and age, suggesting that samples of individuals with PTSD developed based on EMR ICD codes may skew toward including older, less-educated veterans.

Posttraumatic stress disorder-related anhedonia as a predictor of psychosocial functional impairment among United States veterans.

Prior research suggests that anhedonia symptoms related to posttraumatic stress disorder (PTSD; i.e., diminished interest, detachment from others, and difficulty experiencing positive emotions) are consistently associated with a higher degree of impairment in psychosocial functioning beyond that associated with other PTSD symptoms. Unfortunately, much of this research has used cross-sectional study designs; relied upon outdated DSM diagnostic criteria; and failed to control for potentially confounding variables, such as the presence of co-occurring depression. This study used data from Waves 2 and 4 (n = 1,649) of the Veterans' After-Discharge Longitudinal Registry (Project VALOR), a longitudinal dataset of U.S. Army and Marine veterans. As measured using the Inventory of Psychosocial Functioning, Wave 4 psychosocial functioning was regressed on seven PTSD symptom factors at Wave 2 (i.e., intrusions, avoidance, negative affect, anhedonia, externalizing behaviors, anxious arousal, and dysphoric arousal) and potential Wave 2 confounds. The Anhedonia factor, ß = .123, most strongly predicted later psychosocial functional impairment beyond the impact of other PTSD symptom factors, ßs = -.076-.046. Clinical implications of these findings are also discussed.

A prospective examination of health care costs associated with posttraumatic stress disorder diagnostic status and symptom severity among veterans.

Posttraumatic stress disorder (PTSD) is associated with increased health care costs; however, most studies exploring this association use PTSD diagnostic data in administrative records, which can contain inaccurate diagnostic information and be confounded by the quantity of service use. We used a diagnostic interview to determine PTSD diagnostic status and examined associations between PTSD symptom severity and health care costs and utilization, extracted from Veteran Health Administration (VHA) administrative databases. Using a nationwide longitudinal sample of U.S. veterans with and without PTSD (N = 1,377) enrolled in VHA health care, we determined the costs and utilization of mental health and non-mental health outpatient, pharmacy, and inpatient services for 1 year following cohort enrollment. Relative to veterans without PTSD, those with PTSD had higher total health care, B = 0.47; mental health clinic care, B = 0.72; non-mental health clinic care, B = 0.30; and pharmacy costs, B = 0.72, ps < .001. More severe PTSD symptoms were associated with mental health clinic care costs, B = 0.12; non-mental health clinic care costs, B = 0.27; and higher odds of inpatient, B = 0.63, and emergency service use, B = 0.39, p < .001-p = .012. These findings indicate that veterans' PTSD status, determined by a clinician-administered semistructured diagnostic interview, was associated with higher health care costs and increased use of mental health and non-mental health clinic services. The findings also suggest that more severe PTSD is associated with increased costs and utilization, including costly emergency and inpatient utilization.

Network analysis of mild traumatic brain injury, persistent neurobehavioral and psychiatric symptoms, and functional disability among recent-era United States veterans.

Recent-era U.S. veterans are clinically complex, with a high prevalence of co-occurring mild traumatic brain injury (mTBI), psychiatric conditions, and behavioral dysfunction. The current study examined the direct and indirect associations between mTBI and persistent neurobehavioral, psychiatric, and functional disability symptoms among recent-era U.S. veterans and service members (n = 648). We evaluated the postconcussive syndrome (PCS) potential causal model with two network analysis modeling approaches. Separate analyses were conducted for military mTBI and lifetime mTBI. An exploratory factor analysis was conducted to limit topological overlap in the network analysis. The most influential symptoms (i.e., the unique variables most strongly associated with the rest of the network) in the military mTBI network were behavioral disengagement, expected influence (EI) = 1.10; cognitive difficulties, EI = 1.08; agitation/irritability, EI = 1.05; and PTSD-related reexperiencing and avoidance symptoms, EI = 0.98. After accounting for other symptoms, mTBI was only minimally informative, EI = 0.34. Additionally, military mTBI did not moderate the association between symptoms or the overall connectivity of the network. The results for lifetime mTBI were consistent with those for military mTBI. The present analyses identified a variety of behavioral, cognitive, and emotional symptoms that play an important role in understanding comorbidity and daily functioning among recent-era U.S. veterans. Associations between cumulative mTBI that occurred in civilian or military settings were indirect and relatively small in magnitude. The current results add to a growing literature raising doubts about the PCS model.

Development and validation of the Durham Risk Score for estimating suicide attempt risk: A prospective cohort analysis.

BACKGROUND: Worldwide, nearly 800,000 individuals die by suicide each year; however, longitudinal prediction of suicide attempts remains a major challenge within the field of psychiatry. The objective of the present research was to develop and evaluate an evidence-based suicide attempt risk checklist [i.e., the Durham Risk Score (DRS)] to aid clinicians in the identification of individuals at risk for attempting suicide in the future. METHODS AND FINDINGS: Three prospective cohort studies, including a population-based study from the United States [i.e., the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) study] as well as 2 smaller US veteran cohorts [i.e., the Assessing and Reducing Post-Deployment Violence Risk (REHAB) and the Veterans After-Discharge Longitudinal Registry (VALOR) studies], were used to develop and validate the DRS. From a total sample size of 35,654 participants, 17,630 participants were selected to develop the checklist, whereas the remaining participants (N = 18,024) were used to validate it. The main outcome measure was future suicide attempts (i.e., actual suicide attempts that occurred after the baseline assessment during the 1- to 3-year follow-up period). Measure development began with a review of the extant literature to identify potential variables that had substantial empirical support as longitudinal predictors of suicide attempts and deaths. Next, receiver operating characteristic (ROC) curve analysis was utilized to identify variables from the literature review that uniquely contributed to the longitudinal prediction of suicide attempts in the development cohorts. We observed that the DRS was a robust prospective predictor of future suicide attempts in both the combined development (area under the curve [AUC] = 0.91) and validation (AUC = 0.92) cohorts. A concentration of risk analysis found that across all 35,654 participants, 82% of prospective suicide attempts occurred among individuals in the top 15% of DRS scores, whereas 27% occurred in the top 1%. The DRS also performed well among important subgroups, including women (AUC = 0.91), men (AUC = 0.93), Black (AUC = 0.92), White (AUC = 0.93), Hispanic (AUC = 0.89), veterans (AUC = 0.91), lower-income individuals (AUC = 0.90), younger adults (AUC = 0.88), and lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ) individuals (AUC = 0.88). The primary limitation of the present study was its its reliance on secondary data analyses to develop and validate the risk score. CONCLUSIONS: In this study, we observed that the DRS was a strong predictor of future suicide attempts in both the combined development (AUC = 0.91) and validation (AUC = 0.92) cohorts. It also demonstrated good utility in many important subgroups, including women, men, Black, White, Hispanic, veterans, lower-income individuals, younger adults, and LGBTQ individuals. We further observed that 82% of prospective suicide attempts occurred among individuals in the top 15% of DRS scores, whereas 27% occurred in the top 1%. Taken together, these findings suggest that the DRS represents a significant advancement in suicide risk prediction over traditional clinical assessment approaches. While more work is needed to independently validate the DRS in prospective studies and to identify the optimal methods to assess the constructs used to calculate the score, our findings suggest that the DRS is a promising new tool that has the potential to significantly enhance clinicians' ability to identify individuals at risk for attempting suicide in the future.

Seeking to Understand the Conditions Under Which Exposure-Based Writing Therapy for Posttraumatic Stress Disorder is an Effective Approach: A Commentary on Dawson et al. (2020).

Exposure-based writing interventions for posttraumatic stress disorder (PTSD) have shown promise when compared with waitlist conditions, placebo writing control conditions, and evidence-based, trauma-focused treatments. Recently, Dawson et al. (2020) conducted a systematic review and meta-analysis to examine existing published randomized controlled trials investigating exposure-based writing interventions. The findings were encouraging; however, the studies included in the meta-analysis had a high degree of methodological heterogeneity. Our own work examining exposure-based writing as an intervention for PTSD has demonstrated that methodological differences in the structure of exposure-based writing can have a meaningful impact on treatment outcome. Accordingly, we urge caution in interpreting the meta-analysis findings reported by Dawson and colleagues and encourage investigation into better understanding the mechanisms underlying exposure-based writing interventions to further propel this important area of work.

The Role of Negative Affect in Differentiating Posttraumatic Stress Disorder, Depression, and Their Comorbidity Among United States Veterans.

Following trauma exposure, two frequently co-occurring forms of psychopathology include posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). Although these diagnoses have been identified as distinct constructs, the proper classification of these disorders remains a challenge due to overlapping symptoms. Instead, systematically establishing higher- and lower-order personality traits associated with each diagnosis may avoid this confound and improve differential diagnosis. In the present study, we examined how higher-order negative affect and its lower-order facets (i.e., anxiousness, emotional lability, and separation insecurity) may be associated with a diagnosis of PTSD only, MDD only, both diagnoses, or neither diagnosis. Participants were 1,175 veterans enrolled in the Veterans After Discharge Longitudinal Registry. Higher- and lower-order negative affect were assessed using the Personality Inventory for DSM-5 (PID-5), and PTSD and MDD diagnoses were based on the Structured Clinical Interview for DSM-5 (SCID-5). Multinomial logistic regressions were used to model the association between higher- and lower-order negative affect and diagnostic status, after controlling for potential covariates. Diagnostic utility analyses were conducted to examine the degree to which higher- and lower-order negative affect classified participants across groups. Higher-order negative affect and lower-order anxiousness differentiated diagnostic groups, ORs = 1.76-4.66, and had strong specificity and negative predictive value for individuals with PTSD and MDD and those with MDD only. These findings help explain the role of higher-order negative affect and lower-order anxiousness in differentiating PTSD from MDD and comorbid PTSD and MDD and may have implications for assessment, differential diagnosis, and treatment planning.

A Comparison of Dimensional and Categorical Approaches to Characterizing the Association Between Posttraumatic Stress Disorder and Future Suicide Attempts.

The present study compared the utility of categorical (i.e., diagnostic status) and dimensional (i.e., symptom severity) approaches to measuring posttraumatic stress disorder (PTSD) in predicting future suicide attempts among participants in a nationwide, longitudinal study of U.S. military veterans who were deployed in support of operations in Iraq or Afghanistan after the September 11, 2001, terrorist attacks (9/11) and were enrolled in Veterans Health Administration services (N = 1,649). Following an initial assessment of PTSD symptoms, we assessed for suicide attempts at two subsequent time points (M = 28.74 months, SD = 8.72 and M = 55.11 months, SD = 6.89 following the initial assessment). Between the initial and final assessments, 125 participants (7.58%) made at least one suicide attempt. All categorical and dimensional indicators of PTSD predicted suicide attempts at both time points except the categorical indicator for reexperiencing symptoms. Categorical indicators predicting suicide attempts demonstrated excellent sensitivity but poor specificity and overall accuracy. The point along the continuum at which PTSD symptom severity was most accurate regarding the prediction of future suicide attempts was well above the threshold previously established as indicating a probable diagnosis. Although this score was less sensitive than diagnostic indicators, it demonstrated greater specificity and overall accuracy in predicting future suicide attempts. The present results indicate that veterans whose PTSD symptoms satisfy the diagnostic criteria have a higher risk of future suicide attempts, but this risk appears to be even higher for veterans with symptom levels above the diagnostic threshold.

Associations Among Increases in Posttraumatic Stress Symptoms, Neurocognitive Performance, and Long-Term Functional Outcomes in U.S. Iraq War Veterans.

Cross-sectional research suggests that posttraumatic stress symptoms (PTSS) among war zone veterans are associated with functional impairment and poor quality of life. Less is known about the long-term functional repercussions of PTSS. This study of Iraq War veterans examined the associations between increases in PTSS and long-term functional outcomes, including the potential contributions of neurocognitive decrements. Service members and veterans (N = 594) completed self-report measures of functioning and PTSS severity before Iraq War deployment and again after their return (M = 9.3 years postdeployment). Some participants (n = 278) also completed neurocognitive testing at both times. Multiple regression analyses with the full sample-adjusted for TBI, demographic characteristics, military variables, and predeployment PTSS and functioning-revealed that increased PTSS severity over time was significantly associated with unemployment, aOR = 1.04, 95% CI [1.03, 1.06]; poorer work performance; and poorer physical, emotional, and cognitive health-related functioning at long-term follow-up, f2 s = 0.37-1.79. Among participants who completed neurocognitive testing, a decline in select neurocognitive measures was associated with poorer functioning; however, neurocognitive decrements did not account for associations between increased PTSS and unemployment, aOR = 1.04, 95% CI [1.02, 1.07], with the size and direction upheld after adding neurocognitive variables, or poorer functional outcomes, with small increases after adding neurocognitive measures to the models, f2 s = 0.03-0.10. War zone veterans experiencing long-term increased PTSS and/or neurocognitive decrements may be at elevated risk for higher-level functional impairment over time, suggesting that early PTSS management may enhance long-term functioning.