Arieh Y. Shalev

The epidemiology of traumatic event exposure worldwide: results from the World Mental Health Survey Consortium

BACKGROUND Considerable research has documented that exposure to traumatic events has negative effects on physical and mental health. Much less research has examined the predictors of traumatic event exposure. Increased understanding of risk factors for exposure to traumatic events could be of considerable value in targeting preventive interventions and anticipating service needs. METHOD General population surveys in 24 countries with a combined sample of 68 894 adult respondents across six continents assessed exposure to 29 traumatic event types. Differences in prevalence were examined with cross-tabulations. Exploratory factor analysis was conducted to determine whether traumatic event types clustered into interpretable factors. Survival analysis was carried out to examine associations of sociodemographic characteristics and prior traumatic events with subsequent exposure. RESULTS Over 70% of respondents reported a traumatic event; 30.5% were exposed to four or more. Five types - witnessing death or serious injury, the unexpected death of a loved one, being mugged, being in a life-threatening automobile accident, and experiencing a life-threatening illness or injury - accounted for over half of all exposures. Exposure varied by country, sociodemographics and history of prior traumatic events. Being married was the most consistent protective factor. Exposure to interpersonal violence had the strongest associations with subsequent traumatic events. CONCLUSIONS Given the near ubiquity of exposure, limited resources may best be dedicated to those that are more likely to be further exposed such as victims of interpersonal violence. Identifying mechanisms that account for the associations of prior interpersonal violence with subsequent trauma is critical to develop interventions to prevent revictimization.

Course of Posttraumatic Stress Disorder 40 Years After the Vietnam War: Findings From the National Vietnam Veterans Longitudinal Study.

IMPORTANCE The long-term course of readjustment problems in military personnel has not been evaluated in a nationally representative sample. The National Vietnam Veterans Longitudinal Study (NVVLS) is a congressionally mandated assessment of Vietnam veterans who underwent previous assessment in the National Vietnam Veterans Readjustment Study (NVVRS). OBJECTIVE To determine the prevalence, course, and comorbidities of war-zone posttraumatic stress disorder (PTSD) across a 25-year interval. DESIGN, SETTING, AND PARTICIPANTS The NVVLS survey consisted of a self-report health questionnaire (n = 1409), a computer-assisted telephone survey health interview (n = 1279), and a telephone clinical interview (n = 400) in a representative national sample of veterans who served in the Vietnam theater of operations (theater veterans) from July 3, 2012, through May 17, 2013. Of 2348 NVVRS participants, 1920 were alive at the outset of the NVVLS, and 81 died during recruitment; 1450 of the remaining 1839 (78.8%) participated in at least 1 NVVLS study phase. Data analysis was performed from May 18, 2013, through January 9, 2015, with further analyses continued through April 13, 2015. MAIN OUTCOMES AND MEASURES Study instruments included the Mississippi Scale for Combat-Related PTSD, PTSD Checklist for DSM-IV supplemented with PTSD Checklist for DSM-5 items (PCL-5+), Clinician-Administered PTSD Scale for DSM-5 (CAPS-5), and Structured Clinical Interview for DSM-IV, Nonpatient Version. RESULTS Among male theater veterans, we estimated a prevalence (95% CI) of 4.5% (1.7%-7.3%) based on CAPS-5 criteria for a current PTSD diagnosis; 10.8% (6.5%-15.1%) based on CAPS-5 full plus subthreshold PTSD; and 11.2% (8.3%-14.2%) based on PCL-5+ criteria for current war-zone PTSD. Among female veterans, estimates were 6.1% (1.8%-10.3%), 8.7% (3.8%-13.6%), and 6.6% (3.5%-9.6%), respectively. The PCL-5+ prevalence (95% CI) of current non-war-zone PTSD was 4.6% (2.6%-6.6%) in male and 5.1% (2.3%-8.0%) in female theater veterans. Comorbid major depression occurred in 36.7% (95% CI, 6.2%-67.2%) of veterans with current war-zone PTSD. With regard to the course of PTSD, 16.0% of theater veterans reported an increase and 7.6% reported a decrease of greater than 20 points in Mississippi Scale for Combat-Related PTSD symptoms. The prevalence (95% CI) of current PCL-5+-derived PTSD in study respondents was 1.2% (0.0%-3.0%) for male and 3.9% (0.0%-8.1%) for female Vietnam veterans. CONCLUSIONS AND RELEVANCE Approximately 271,000 Vietnam theater veterans have current full PTSD plus subthreshold war-zone PTSD, one-third of whom have current major depressive disorder, 40 or more years after the war. These findings underscore the need for mental health services for many decades for veterans with PTSD symptoms.

Early PTSD Symptom Trajectories: Persistence, Recovery, and Response to Treatment: Results from the Jerusalem Trauma Outreach and Prevention Study (J-TOPS)

Context Uncovering heterogeneities in the progression of early PTSD symptoms can improve our understanding of the disorders pathogenesis and prophylaxis. Objectives To describe discrete symptom trajectories and examine their relevance for preventive interventions. Design Latent Growth Mixture Modeling (LGMM) of data from a randomized controlled study of early treatment. LGMM identifies latent longitudinal trajectories by exploring discrete mixture distributions underlying observable data. Setting Hadassah Hospital unselectively receives trauma survivors from Jerusalem and vicinity. Participants Adult survivors of potentially traumatic events consecutively admitted to the hospitals emergency department (ED) were assessed ten days and one-, five-, nine- and fifteen months after ED admission. Participants with data at ten days and at least two additional assessments (n = 957) were included; 125 received cognitive behavioral therapy (CBT) between one and nine months. Approach We used LGMM to identify latent parameters of symptom progression and tested the effect of CBT on these parameters. CBT consisted of 12 weekly sessions of either cognitive therapy (n = 41) or prolonged exposure (PE, n = 49), starting 29.8±5.7 days after ED admission, or delayed PE (n = 35) starting at 151.8±42.4 days. CBT effectively reduced PTSD symptoms in the entire sample. Main Outcome Measure Latent trajectories of PTSD symptoms; effects of CBT on these trajectories. Results Three trajectories were identified: Rapid Remitting (rapid decrease in symptoms from 1- to 5-months; 56% of the sample), Slow Remitting (progressive decrease in symptoms over 15 months; 27%) and Non-Remitting (persistently elevated symptoms; 17%). CBT accelerated the recovery of the Slow Remitting class but did not affect the other classes. Conclusions The early course of PTSD symptoms is characterized by distinct and diverging response patterns that are centrally relevant to understanding the disorder and preventing its occurrence. Studies of the pathogenesis of PTSD may benefit from using clustered symptom trajectories as their dependent variables.

Spontaneous brain activity in combat related PTSD

Posttraumatic stress disorder (PTSD) is a prevalent psychiatric disorder, especially in combat veterans. Existing functional neuroimaging studies have provided important insights into the neural mechanisms of PTSD using various experimental paradigms involving trauma recollection or other forms of emotion provocation. However it is not clear whether the abnormal brain activity is specific to the mental processes related to the experimental tasks or reflects general patterns across different brain states. Thus, studying intrinsic spontaneous brain activity without the influence of external tasks may provide valuable alternative perspectives to further understand the neural characteristics of PTSD. The present study evaluated the magnitudes of spontaneous brain activity of male US veterans with or without PTSD, with the two groups matched on age, gender, and ethnicity. Amplitudes of low frequency fluctuation (ALFF), a data driven analysis method, were calculated on each voxel of the resting state fMRI data to measure the magnitudes of spontaneous brain activity. Results revealed that PTSD subjects showed increased spontaneous activity in the amygdala, ventral anterior cingulate cortex, insula, and orbital frontal cortex, as well as decreased spontaneous activity in the precuneus, dorsal lateral prefrontal cortex and thalamus. Within the PTSD group, larger magnitudes of spontaneous activity in the thalamus, precuneus and dorsal lateral prefrontal cortex were associated with lower re-experiencing symptoms. Comparing our results with previous functional neuroimaging findings, increased activity of the amygdala and anterior insula and decreased activity of the thalamus are consistent patterns across emotion provocation states and the resting state.

Quantitative forecasting of PTSD from early trauma responses: A Machine Learning application

There is broad interest in predicting the clinical course of mental disorders from early, multimodal clinical and biological information. Current computational models, however, constitute a significant barrier to realizing this goal. The early identification of trauma survivors at risk of post-traumatic stress disorder (PTSD) is plausible given the disorders salient onset and the abundance of putative biological and clinical risk indicators. This work evaluates the ability of Machine Learning (ML) forecasting approaches to identify and integrate a panel of unique predictive characteristics and determine their accuracy in forecasting non-remitting PTSD from information collected within 10 days of a traumatic event. Data on event characteristics, emergency department observations, and early symptoms were collected in 957 trauma survivors, followed for fifteen months. An ML feature selection algorithm identified a set of predictors that rendered all others redundant. Support Vector Machines (SVMs) as well as other ML classification algorithms were used to evaluate the forecasting accuracy of i) ML selected features, ii) all available features without selection, and iii) Acute Stress Disorder (ASD) symptoms alone. SVM also compared the prediction of a) PTSD diagnostic status at 15 months to b) posterior probability of membership in an empirically derived non-remitting PTSD symptom trajectory. Results are expressed as mean Area Under Receiver Operating Characteristics Curve (AUC). The feature selection algorithm identified 16 predictors, present in ≥ 95% cross-validation trials. The accuracy of predicting non-remitting PTSD from that set (AUC = .77) did not differ from predicting from all available information (AUC = .78). Predicting from ASD symptoms was not better then chance (AUC = .60). The prediction of PTSD status was less accurate than that of membership in a non-remitting trajectory (AUC = .71). ML methods may fill a critical gap in forecasting PTSD. The ability to identify and integrate unique risk indicators makes this a promising approach for developing algorithms that infer probabilistic risk of chronic posttraumatic stress psychopathology based on complex sources of biological, psychological, and social information.

Unintended Consequences of Changing the Definition of Posttraumatic Stress Disorder in DSM-5: Critique and Call for Action

T he 2013 DSM-5, the first major revision of US psychiatric nomenclature since 1994’s DSM-IV, was coordinated by the American Psychiatric Association in a manner to ensure revisions were empirically supported and maintained continuity with previous editions.1,2 Although many important evidence-based changes resulted, core criteria and diagnostic language for most common conditions affecting adults remained unchanged, safeguarding continued use of treatments validated over decades.1,3 A notable exception was posttraumatic stress disorder (PTSD). Criteria were added and major wording changes were made to symptoms that have been foundational clinical descriptors even before DSM-IV— revisions that workgroup members themselves acknowledged were controversial.4-6 Their rationale4-6 appeared to reflect selective interpretations of evidence (eg, based on nonsystematic literature review and overlooking complex neuroscience domains); cognitive theory influenced key changes, potentially lessening the emphasis of other wellestablished neurobiological models underlying evidence-based treatments.7,8 Emerging research has demonstrated that the revised definition offers no improvement in clinical utility, identifies different individuals,andexcludesmanyindividualsmeetingpreviouscriteria.9-11 This article details problematic changes, implications, and rationale for immediate action.

Bridging a translational gap: using machine learning to improve the prediction of PTSD

BackgroundPredicting Posttraumatic Stress Disorder (PTSD) is a pre-requisite for targeted prevention. Current research has identified group-level risk-indicators, many of which (e.g., head trauma, receiving opiates) concern but a subset of survivors. Identifying interchangeable sets of risk indicators may increase the efficiency of early risk assessment. The study goal is to use supervised machine learning (ML) to uncover interchangeable, maximally predictive combinations of early risk indicators.MethodsData variables (features) reflecting event characteristics, emergency department (ED) records and early symptoms were collected in 957 trauma survivors within ten days of ED admission, and used to predict PTSD symptom trajectories during the following fifteen months. A Target Information Equivalence Algorithm (TIE*) identified all minimal sets of features (Markov Boundaries; MBs) that maximized the prediction of a non-remitting PTSD symptom trajectory when integrated in a support vector machine (SVM). The predictive accuracy of each set of predictors was evaluated in a repeated 10-fold cross-validation and expressed as average area under the Receiver Operating Characteristics curve (AUC) for all validation trials.ResultsThe average number of MBs per cross validation was 800. MBs’ mean AUC was 0.75 (95% range: 0.67-0.80). The average number of features per MB was 18 (range: 12–32) with 13 features present in over 75% of the sets.ConclusionsOur findings support the hypothesized existence of multiple and interchangeable sets of risk indicators that equally and exhaustively predict non-remitting PTSD. ML’s ability to increase prediction versatility is a promising step towards developing algorithmic, knowledge-based, personalized prediction of post-traumatic psychopathology.

Prevention of Post-Traumatic Stress Disorder After Trauma: Current Evidence and Future Directions

Post-traumatic stress disorder (PTSD) is a frequent, tenacious, and disabling consequence of traumatic events. The disorder’s identifiable onset and early symptoms provide opportunities for early detection and prevention. Empirical findings and theoretical models have outlined specific risk factors and pathogenic processes leading to PTSD. Controlled studies have shown that theory-driven preventive interventions, such as cognitive behavioral therapy (CBT), or stress hormone-targeted pharmacological interventions, are efficacious in selected samples of survivors. However, the effectiveness of early clinical interventions remains unknown, and results obtained in aggregates (large groups) overlook individual heterogeneity in PTSD pathogenesis. We review current evidence of PTSD prevention and outline the need to improve the disorder’s early detection and intervention in individual-specific paths to chronic PTSD.

Head Injury and Loss of Consciousness Raise the Likelihood of Developing and Maintaining PTSD Symptoms

Mild traumatic brain injury has been associated with higher prevalence of posttraumatic stress disorder (PTSD). The extent to which head injury or loss of consciousness predicts PTSD is unknown. To evaluate the contribution of head injury and loss of consciousness to the occurrence of PTSD, we made a longitudinal evaluation of 1,260 road accident survivors admitted to the emergency department with head injury (n = 287), head injury and loss of consciousness (n = 115), or neither (n = 858). A telephone-administered posttraumatic symptoms scale inferred PTSD and quantified PTSD symptoms at 10 days and 8 months after admission. The study groups had similar heart rate, blood pressure, and pain levels in the emergency department. Survivors with loss of consciousness and head injury had higher prevalence of PTSD and higher levels of PTSD symptoms, suggesting that patients with head injury and loss of consciousness reported in the emergency department are at higher risk for PTSD.

Social relationship satisfaction and PTSD: which is the chicken and which is the egg?

Background Impaired social relationships are linked with higher levels of posttraumatic stress disorder (PTSD), but the associations underlying dynamics are unknown. PTSD may impair social relationships, and, vice versa, poorer relationship quality may interfere with the recovery from PTSD. Objective This work longitudinally evaluates the simultaneous progression of PTSD symptoms and social relationship satisfaction (SRS) in a large cohort of recent trauma survivors. It also explores the effect of cognitive behavior therapy (CBT) on the association between the two. Method Consecutive emergency department trauma admissions with qualifying PTSD symptoms (n=501) were assessed 3 weeks and 5 months after trauma admission. The World Health Organization Quality of Life evaluated SRS and the Clinician Administered PTSD Scale evaluated PTSD symptom severity. Ninety-eight survivors received CBT between measurement sessions. We used Structural Equation Modeling to evaluate cross-lagged effects between the SRS and PTSD symptoms. Results The cross-lagged effect of SRS on PTSD was statistically significant (β=−0.12, p=0.01) among survivors who did not receive treatment whilst the effect of PTDS on SRS was nil (β=−0.02, p=0.67). Both relationships were non-significant among survivors who received CBT. Discussion SRS and PTSD are highly associated, and this study shows that changes in SRS in the early aftermath of traumatic events contribute to changes in PTSD, rather than vice versa. SRS impacts natural recovery, but not effective treatment. This study suggests that being satisfied with ones relationships might be considered as an important factor in natural recovery from trauma, as well as in intervention.