Faculty Bibliography

Individuals exposed to traumatic stressors follow divergent patterns including resilience and chronic stress. However, researchers utilizing animal models that examine learned or instrumental threat responses thought to have translational relevance for Posttraumatic Stress Disorder (PTSD) and resilience typically use central tendency statistics that assume population homogeneity. This approach potentially overlooks fundamental differences that can explain human diversity in response to traumatic stressors. The current study tests this assumption by identifying and replicating common heterogeneous patterns of response to signaled active avoidance (AA) training. In this paradigm, rats are trained to prevent an aversive outcome (shock) by performing a learned instrumental behavior (shuttling between chambers) during the presentation of a conditioned threat cue (tone). We test the hypothesis that heterogeneous trajectories of threat avoidance provide more accurate model fit compared to a single mean trajectory in two separate studies. Study 1 conducted 3 days of signaled AA training (n = 81 animals) and study 2 conducted 5 days of training (n = 186 animals). We found that four trajectories in both samples provided the strongest model fit. Identified populations included animals that acquired and retained avoidance behavior on the first day (Rapid Avoiders: 22 and 25%); those who never successfully acquired avoidance (Non-Avoiders; 20 and 16%); a modal class who acquired avoidance over 3 days (Modal Avoiders; 37 and 50%); and a population who demonstrated a slow pattern of avoidance, failed to fully acquire avoidance in study 1 and did acquire avoidance on days 4 and 5 in study 2 (Slow Avoiders; 22.0 and 9%). With the exception of the Slow Avoiders in Study 1, populations that acquired demonstrated rapid step-like increases leading to asymptotic levels of avoidance. These findings indicate that avoidance responses are heterogeneous in a way that may be informative for understanding both resilience and PTSD as well as the nature of instrumental behavior acquisition. Characterizing heterogeneous populations based on their response to threat cues would increase the accuracy and translatability of such models and potentially lead to new discoveries that explain diversity in instrumental defensive responses.

BACKGROUND: Individuals experience the loss of a spouse in varied ways. There is growing recognition of major depressive disorder and complicated grief as distinct post-bereavement disorders. However, most studies focusing on these different courses of functioning have not examined pre-loss functioning. METHODS: We used data from a prospective population based study to examine depression and grief among conjugally bereaved older adults. We compared latent trajectories of grief and depression symptoms based on data from pre-loss and 6, 18, and 48 months post-loss, and examined a number of pre- and post-loss predictor variables. RESULTS: The chronic grief and chronic depression trajectories did not differ in grief symptoms at any post-loss time point. However, a number of pre- and post-loss variables uniquely differentiated these two distinct trajectories. LIMITATIONS: Measures used in the current study were based on self-report and compared only two trajectories. Additionally, the sample was restricted to older adults (M age=72) and thus our findings may not generalize to younger populations. CONCLUSIONS: These two distinct trajectories - chronic grief and chronic depression - may appear similar when examining grief symptoms alone, though it is apparent that they have different long-term courses of functioning. It is important to understand pre-loss functioning as well as variables associated with each group in order to appropriately target treatment.

Background: Predicting pathways to chronic PTSD has significant clinical and public health implications but current risk indicators are inconsistent and limited. Previously identified in a large cohort of recent trauma survivors (n=957) using Latent Growth Mixture Modeling, trajectories of PTSD symptoms from one-week to fifteenmonths, include Rapid Remission (56%), Slow Remission (27%), and Non-Remission (17%), the non-remission class comprising the majority PTSD cases at fifteen months, and not responding to cognitive behavioral therapy (CBT). Innovative approaches to forecasting membership in a nonremitting, treatment resistant class may improve our ability to identify, shortly after trauma exposure, survivors at high risk of developing PTSD. We tested the robustness of seven machine learning forecasting methods to predicting the non-remitting class from predictor variables collected during the days that followed trauma exposure. Methods: Consecutive trauma survivors admitted to a general hospital emergency department were screened and followed longitudinally and n=125 with Acute PTSD received efficient cognitive behavioral therapy within a month of the traumatic event. CBT was equally distributed among trajectory classes. Survivors were followed regardless and blindly of their participation in treatment. Markov boundary feature selection was used to identify a parsimonious set of trajectory predictors from 68 candidate variables. That set was than used to compare seven classification algorithms [two variants of linear Support Vector Machines (SVMs), polynomial SVMs, AdaBoost, Random Forests, Bayesian Logistic Regression (BBR) and Kernal Ridge Regression (KRR)] for their ability to build accurate multivariate classification models separating nonremission from other trajectories: Support Vector Machines (SVMs), two Optimized SVMs, AdaBoost, Random Forests, Bayesian Logistic Regression (BBR) and Kernel Ridge Regression (KRR). Results: Variables selected by Markov boundary method robustly predic!

In an attempt to capture the variety of symptoms that emerge following traumatic stress, the revision of posttraumatic stress disorder (PTSD) criteria in the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) has expanded to include additional symptom presentations. One consequence of this expansion is that it increases the amorphous nature of the classification. Using a binomial equation to elucidate possible symptom combinations, we demonstrate that the DSM-IV criteria listed for PTSD have a high level of symptom profile heterogeneity (79,794 combinations); the changes result in an eightfold expansion in the DSM-5, to 636,120 combinations. In this article, we use the example of PTSD to discuss the limitations of DSM-based diagnostic entities for classification in research by elucidating inherent flaws that are either specific artifacts from the history of the DSM or intrinsic to the underlying logic of the DSM's method of classification. We discuss new directions in research that can provide better information regarding both clinical and nonclinical behavioral heterogeneity in response to potentially traumatic and common stressful life events. These empirical alternatives to an a priori classification system hold promise for answering questions about why diversity occurs in response to stressors.

OBJECTIVE: A growing body of literature suggests that college students display alarming rates of psychological distress. However, studies of responses to significant life stressors in other contexts have found that people respond in heterogeneous ways and that attachment style and ego-resiliency mitigate the effects of stressors on mental health. METHOD: Individual differences in distress among a cohort of students (N = 157; Mean age = 18.8 years, 62.6% female) across the four years of college were analyzed using latent class growth analysis. Trajectories were then regressed on levels of anxious and avoidant attachment and ego-resiliency. RESULTS: Four discrete patterns emerged characterized by healthy and maladaptive patterns of stress response, indicating that students respond to college in heterogeneous ways. Several patterns showed significant variability in distress by semester. Low levels of anxious but not avoidant attachment predicted membership in the stable-low distress or resilient class while ego-resiliency predicted membership in both the resilient and moderate distress classes. CONCLUSIONS: Findings indicate that low levels of anxious attachment and the ability to flexibly cope with adversity may be associated with better mental health throughout college. Implications from stress response and developmental perspectives are discussed.

Responses to both potentially traumatic events and other significant life stressors have been shown to conform to discrete patterns of response such as resilience, anticipatory stress, initial distress with gradual recovery, and chronic distress. The etiology of these trajectories is still unclear. Individual differences in levels of negative and positive emotion are believed to play a role in determining risk and resilience following traumatic exposure. In the current investigation, we followed police officers prospectively from academy training through 48 months of active duty, assessing levels of distress every 12 months. Using latent class growth analysis, we identified 4 trajectories closely conforming to prototypical patterns. Furthermore, we found that lower levels of self-reported negative emotion during academy training prospectively predicted membership in the resilient trajectory compared with the more symptomatic trajectories following the initiation of active duty, whereas higher levels of positive emotion during academy training differentiated resilience from a trajectory that was equivalently low on distress during academy training but consistently grew in distress through 4 years of active duty. These findings emerging from a prospective longitudinal design provide evidence that resilience is predicted by both lower levels of negative emotion and higher levels of positive emotion prior to active duty stressor exposure. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

BACKGROUND: Posttraumatic stress disorder (PTSD) is associated with high rates of psychiatric comorbidity, most notably substance use disorders, major depression, and other anxiety disorders. However, little is known about how these disorders cluster together among people with PTSD, if disorder clusters have distinct etiologies in terms of trauma type, and if they confer greater burden over and above PTSD alone. METHOD: Utilizing Latent Class Analysis, we tested for discrete patterns of lifetime comorbidity with PTSD following trauma exposure (n = 409). Diagnoses were based on the Structured Clinical Interview for DSM-IV (SCID). Next, we examined if gender, trauma type, symptom frequency, severity, and interference with everyday life were associated with the latent classes. RESULTS: Three patterns of lifetime comorbidity with PTSD emerged: a class characterized by predominantly comorbid mood and anxiety disorders; a class characterized by predominantly comorbid mood, anxiety, and substance dependence; and a relatively pure low-comorbidity PTSD class. Individuals in both high comorbid classes had nearly two and a half times the rates of suicidal ideation, endorsed more PTSD symptom severity, and demonstrated a greater likelihood of intimate partner abuse compared to the low comorbidity class. Men were most likely to fall into the substance dependent class. CONCLUSION: PTSD comorbidity clusters into a small number of common patterns. These patterns may represent an important area of study, as they confer distinct differences in risk and possibly etiology. Implications for research and treatment are discussed.

BACKGROUND: Our goal was to better understand distinct PTSD symptom presentations in Iraq and Afghanistan Veterans (N=227) and to determine whether those who killed in war were at risk for being in the most symptomatic class. METHODS: We used latent class analysis of responses to the PTSD checklist and logistic regression of most symptomatic class. RESULTS: We found that a four-class solution best fit the data, with the following profiles emerging: High Symptom (34% of participants), Intermediate Symptom (41%), Intermediate Symptom with Low Emotional Numbing (10%), and Low Symptom (15%). The largest group of individuals who reported killing (45%) was in the High Symptom class, and those who killed had twice the odds of being in the most symptomatic PTSD class, compared to those who did not kill. Those who endorsed killing a non-combatant (OR=4.56, 95% CI [1.77, 11.7], p<0.01) or killing in the context of anger or revenge (OR=4.63, 95% CI=[1.89, 11.4], p<0.001) were more likely to belong to the most symptomatic PTSD class, compared to those who did not kill. LIMITATIONS: The study was retrospective and cross-sectional. The results may not generalize to veterans of other wars. CONCLUSIONS: Killing in war may be an important indicator of risk for developing frequent and severe PTSD symptoms. This has implications for the mental healthcare of veterans, providing evidence that a comprehensive evaluation of returning veterans should include an assessment of killing experiences and reactions to killing.

CONTEXT: Uncovering heterogeneities in the progression of early PTSD symptoms can improve our understanding of the disorder's 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 hospital's 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.