Exploring the Association Between Structural Racism and Mental Health: Geospatial and Machine Learning Analysis.

BACKGROUND: Structural racism produces mental health disparities. While studies have examined the impact of individual factors such as poverty and education, the collective contribution of these elements, as manifestations of structural racism, has been less explored. Milwaukee County, Wisconsin, with its racial and socioeconomic diversity, provides a unique context for this multifactorial investigation. OBJECTIVE: This research aimed to delineate the association between structural racism and mental health disparities in Milwaukee County, using a combination of geospatial and deep learning techniques. We used secondary data sets where all data were aggregated and anonymized before being released by federal agencies. METHODS: We compiled 217 georeferenced explanatory variables across domains, initially deliberately excluding race-based factors to focus on nonracial determinants. This approach was designed to reveal the underlying patterns of risk factors contributing to poor mental health, subsequently reintegrating race to assess the effects of racism quantitatively. The variable selection combined tree-based methods (random forest) and conventional techniques, supported by variance inflation factor and Pearson correlation analysis for multicollinearity mitigation. The geographically weighted random forest model was used to investigate spatial heterogeneity and dependence. Self-organizing maps, combined with K-means clustering, were used to analyze data from Milwaukee communities, focusing on quantifying the impact of structural racism on the prevalence of poor mental health. RESULTS: While 12 influential factors collectively accounted for 95.11% of the variability in mental health across communities, the top 6 factors-smoking, poverty, insufficient sleep, lack of health insurance, employment, and age-were particularly impactful. Predominantly, African American neighborhoods were disproportionately affected, which is 2.23 times more likely to encounter high-risk clusters for poor mental health. CONCLUSIONS: The findings demonstrate that structural racism shapes mental health disparities, with Black community members disproportionately impacted. The multifaceted methodological approach underscores the value of integrating geospatial analysis and deep learning to understand complex social determinants of mental health. These insights highlight the need for targeted interventions, addressing both individual and systemic factors to mitigate mental health disparities rooted in structural racism.

Distinct Functional Connectivity Patterns for Intermittent Vs Constant Neuropathic Pain Phenotypes in Persistent Spinal Pain Syndrome Type 2 Patients.

Background: Chronic low back pain (cLBP) has been associated with alterations in brain functional connectivity (FC) but based upon heterogeneous populations and single network analyses. Our goal is to study a more homogeneous cLBP population and focus on multiple cross-network (CN) connectivity analysis. We hypothesize that within this population: 1) altered CN FC, involving emotion and reward/aversion functions are related to their pain levels and 2) altered relationships are dependent upon pain phenotype (constant neuropathic vs intermittent pain). Methods: In this case series, resting state fcMRI scans were obtained over a study duration of 60 months from 23 patients (13 constant neuropathic and 10 intermittent pain) with Persistent Spinal Pain Syndrome (PSPS Type 2) being considered for spinal cord stimulation (SCS) therapy at a single academic center. Images were acquired using a Discovery MR750 GE scanner. During the resting state acquisitions, they were asked to close their eyes and relax. The CN analysis was performed on 7 brain networks and compared to age-matched controls. Linear regression was used to test the correlation between CN connectivity and pain scores. Results: CN FC involving emotion networks (STM: striatum network index) was significantly lower than controls in all patients, regardless of pain phenotype (P < 0.003). Pain levels were positively correlated with emotional FC for intermittent pain but negatively correlated for constant pain. Conclusion: This is the first report of 1) altered CN FC involving emotion/reward brain circuitry in 2) a homogeneous population of cLBP patients with 3) two different pain phenotypes (constant vs intermittent) in PSPS Type 2 patients being considered for SCS. FC patterns were altered in cLBP patients as compared to controls and were characteristic for each pain phenotype. These data support fcMRI as a potential and objective tool in assessing pain levels in cLBP patients with different pain phenotypes.

Racial discrimination increases the risk for nonremitting posttraumatic stress disorder symptoms in traumatically injured Black individuals living in the United States.

Traumatic, life-threatening events are experienced commonly among the general U.S. population, yet Black individuals in the United States (i.e., Black Americans) exhibit higher prevalence rates of posttraumatic stress disorder (PTSD) and more severe symptoms than other populations. Although empirical research has noted a range of symptom patterns that follow traumatic injury, minimal work has examined the role of racial discrimination in relation to PTSD symptom trajectories. The current study assessed racial discrimination and PTSD symptom trajectories at 6 months postinjury across two separate samples of traumatically injured Black Americans (i.e. emergency department (ED)-discharged and hospitalized). Identified PTSD symptom trajectories largely reflect those previously reported (i.e., ED: nonremitting, moderate, remitting, and resilient; hospitalized: nonremitting, delayed, and resilient), although the resilient trajectory was less represented than expected given past research (ED: 55.8%, n = 62; hospitalized: 46.9%, n = 38). Finally, higher racial discrimination was associated with nonremitting, ED: relative risk ratio (RR) = 1.32, hospitalized: RR = 1.23; moderate, ED: RR = 1.18; and delayed, hospitalized: RR = 1.26, PTSD symptom trajectories. Overall, the current findings not only emphasize the inimical effects of racial discrimination but also demonstrate the unique ways in which race-related negative events can impact PTSD symptom levels and recovery across time.

Sex-related disparities in vehicle crash injury and hemodynamics.

Objective: Multiple studies evaluate relative risk of female vs. male crash injury; clinical data may offer a more direct injury-specific evaluation of sex disparity in vehicle safety. This study sought to evaluate trauma injury patterns in a large trauma database to identify sex-related differences in crash injury victims. Methods: Data on lap and shoulder belt wearing patients age 16 and up with abdominal and pelvic injuries from 2018 to 2021 were extracted from the National Trauma Data Bank for descriptive analysis using injuries, vital signs, International Classification of Disease (ICD) coding, age, and injury severity using AIS (Abbreviated Injury Scale) and ISS (Injury Severity Score). Multiple linear regression was used to assess the relationship of shock index (SI) and ISS, sex, age, and sex*age interaction. Regression analysis was performed on multiple injury regions to assess patient characteristics related to increased shock index. Results: Sex, age, and ISS are strongly related to shock index for most injury regions. Women had greater overall SI than men, even in less severe injuries; women had greater numbers of pelvis and liver injuries across severity categories; men had greater numbers of injury in other abdominal/pelvis injury regions. Conclusions: Female crash injury victims' tendency for higher (AIS) severity of pelvis and liver injuries may relate to how their bodies interact with safety equipment. Females are entering shock states (SI > 1.0) with lesser injury severity (ISS) than male crash injury victims, which may suggest that female crash patients are somehow more susceptible to compromised hemodynamics than males. These findings indicate an urgent need to conduct vehicle crash injury research within a sex-equity framework; evaluating sex-related clinical data may hold the key to reducing disparities in vehicle crash injury.

Improved follow-up care for gun violence survivors in the Trauma Quality of Life Clinic.

Background: Outpatient follow-up represents a crucial opportunity to re-engage with gun violence survivors (GVS) and to facilitate positive health outcomes. Current outpatient models for firearm-related injuries and trauma care are inconsistent and unstandardized across trauma centers. This project describes the patient population served by the multidisciplinary Trauma Quality of Life (TQoL) Clinic for GVS. Also of primary interest was the outpatient follow-up services used by patients prior to their clinic appointment. Subsequent referrals placed during Clinic, as well as rate of attendance, was a secondary aim. Methods: This was a descriptive retrospective analysis of a quality improvement project of the TQoL Clinic. Data were extracted from the electronic medical record and were supplemented with information from the trauma registry and the hospital-based violence intervention program database. Descriptive statistics characterized the patient population served. A Χ2 analysis was used to compare no-show rates for the TQoL Clinic against two historical cohorts of trauma clinic attendees. Results: Most attendees were young (M=32.0, SD=1.8, range=15-88 years), Black (80.1%), and male (82.0%). Of the 306 total TQoL Clinic attendees, 82.3% attended their initial scheduled appointment. Most non-attendee patients rescheduled their appointments (92.1%), and 89.5% attended the rescheduled appointment. TQoL Clinic demonstrated a significantly lower no-show rate than the traditional trauma clinic model, including after the implementation of the hospital's inpatient violence intervention program (χ2(2)=75.52, p<0.001). Conclusion: The TQoL Clinic has demonstrated improved outpatient follow-up to address the comprehensive needs of GVS. Trauma centers with high gunshot wound volume should consider the implementation of the multidisciplinary TQoL Clinic model to increase access to care and to continue partnership with violence intervention programs to address health outcomes in those most at risk of future morbidity and mortality. Level of evidence: Therapeutic/care management, level III.

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.

Background: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods: Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n= 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated. Results: rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group. Conclusions: Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.

Experiences of racial discrimination and adverse gene expression among black individuals in a level 1 trauma center sample.

Up to 40 % of individuals who sustain traumatic injuries are at risk for posttraumatic stress disorder (PTSD) and the conditional risk for developing PTSD is even higher for Black individuals. Exposure to racial discrimination, including at both interpersonal and structural levels, helps explain this health inequity. Yet, the relationship between racial discrimination and biological processes in the context of traumatic injury has yet to be fully explored. The current study examined whether racial discrimination is associated with a cumulative measure of biological stress, the gene expression profile conserved transcriptional response to adversity (CTRA), in Black trauma survivors. Two-weeks (T1) and six-months (T2) post-injury, Black participants (N = 94) provided a blood specimen and completed assessments of lifetime racial discrimination and PTSD symptoms. Mixed effect linear models evaluated the relationship between change in CTRA gene expression and racial discrimination while adjusting for age, gender, body mass index (BMI), smoking history, heavy alcohol use history, and trauma-related variables (mechanism of injury, lifetime trauma). Results revealed that for individuals exposed to higher levels of lifetime racial discrimination, CTRA significantly increased between T1 and T2. Conversely, CTRA did not increase significantly over time in individuals exposed to lower levels of lifetime racial discrimination. Thus, racial discrimination appeared to lead to a more sensitized biological profile which was further amplified by the effects of a recent traumatic injury. These findings replicate and extend previous research elucidating the processes by which racial discrimination targets biological systems.

Relationship between heart rate variability and differential patterns of cortisol response to acute stressors in mid-life adults: A data-driven investigation.

Cortisol and heart rate variability (HRV) are well-established biomarkers of the human stress response system. While a relationship between cortisol and HRV is assumed, few studies have found evidence of their correlation within single study designs. One complication for isolating such a relationship may lie in individual variability in the cortisol response to stress such that atypical cortisol responding (i.e., elevated or blunted) occurs. To-date, studies on the cortisol response have employed traditional mean-difference-based approaches to examine average magnitude change in cortisol over time. Alternatively, data-driven trajectory modelling, such as latent growth mixture modelling, may be advantageous for quantifying cortisol based on patterns of response over time. Latent growth mixture modelling was used in N = 386 adults to identify subgroups based on trajectories of cortisol responses to stress. The relationship between cortisol and HRV was tested within subgroups. Results revealed a 'prototypical' subgroup characterised by expected rise and fall in cortisol response to stress (n = 309), a 'decline' subgroup (n = 28) that declined in cortisol after stress, and a 'rise' subgroup (n = 49) that increased in cortisol after stress. Within the 'prototypical' subgroup, greater HRV during stress was associated with decline in cortisol after stress from its maximum (r (306) = 0.19, p < 0.001). This relationship failed to emerge in the 'decline' and 'rise' subgroups (p > 0.271). Results document different patterns of cortisol response to stress; among those who exhibit a 'prototypical' response, changes in HRV during stress are related to changes in cortisol after stress.

Neural processes of emotional conflict detection and prediction of posttraumatic stress disorder symptom clusters in traumatic injury survivors.

OBJECTIVE: Given the prevalence and significant burden of posttraumatic stress disorder (PTSD), identifying early predictors of symptom development following trauma is critical. PTSD is a heterogeneous disorder comprised of distinct symptom clusters-reexperiencing, avoidance, negative mood, and hyperarousal-that contribute to the broad range of possible symptom profiles. Affective and attentional regulation processes, such as emotional conflict detection, are impaired in individuals with PTSD; however, the neural mechanisms underlying these alterations and their predictive utility for the development of PTSD symptoms remain unclear. METHOD: Traumatic injury survivors (N = 49) without traumatic brain injury were recruited from the emergency department of an urban, Level-1 trauma center. Within 1 month of trauma exposure, participants completed a well-characterized emotional conflict task during a functional magnetic resonance imaging scan. Participants returned 6-month later for a clinical assessment of PTSD symptoms. Using a region-of-interest mask derived from whole-brain voxelwise analyses during emotional conflict detection (vs. no emotional conflict detection) we examined whether differential neural activity predicted 6-month PTSD symptom cluster severity. RESULTS: Greater activation of the right middle frontal gyrus during emotional conflict detection prospectively predicted lower PTSD avoidance symptom severity 6 months later (above and beyond the effects of self-reported baseline PTSD and depressive symptoms, previous traumatic life events, racial discrimination, age, sex, and injury severity). CONCLUSIONS: Neural processes of emotion conflict detection measured in the early aftermath of a potentially traumatic event are useful as predictors for the development of PTSD symptoms. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Trends in Adult Suicide Rates in Milwaukee County, Wisconsin, 2002 through 2020.

BACKGROUND: Monitoring suicide rates is an important public health strategy to inform prevention efforts. We describe rates of adult suicide in Milwaukee County, Wisconsin, over a 19-year period. METHODS: Data on all adult suicides from 2002 through 2020 (n = 981) were obtained from the Milwaukee County Medical Examiner's Office. Subpopulation rates were identified using the Wisconsin Interactive Statistics on Health System. RESULTS: Suicide rates increased significantly over the study period, with disproportionate increases among Black and Latinx residents. DISCUSSION: Expanded prevention efforts are needed to reverse this concerning trend. Further research should guide development of culturally relevant interventions, provide data for the equitable allocation of limited resources.

Attributional negativity bias and acute stress disorder symptoms mediate the association between trauma history and future posttraumatic stress disorder.

Individuals who have experienced more trauma throughout their life have a heightened risk of developing posttraumatic stress disorder (PTSD) following injury. Although trauma history cannot be retroactively modified, identifying the mechanism(s) by which preinjury life events influence future PTSD symptoms may help clinicians mitigate the detrimental effects of past adversity. The current study proposed attributional negativity bias, the tendency to perceive stimuli/events as negative, as a potential intermediary in PTSD development. We hypothesized an association between trauma history and PTSD symptom severity following a new index trauma via heightened negativity bias and acute stress disorder (ASD) symptoms. Recent trauma survivors (N =189, 55.5% women, 58.7% African American/Black) completed assessments of ASD, negativity bias, and lifetime trauma 2-weeks postinjury; PTSD symptoms were assessed 6 months later. A parallel mediation model was tested with bootstrapping (10,000 resamples). Both negativity bias, Path b1 : ß = -.24, t(187) = -2.88, p = .004, and ASD symptoms, Path b2 : ß = .30, t(187) = 3.71, p < .001, fully mediated the association between trauma history and 6-month PTSD symptoms, full model: F(6, 182) = 10.95, p < .001, R 2 = .27; Path c': ß = .04, t(187) = 0.54, p = .587. These results suggest that negativity bias may reflect an individual cognitive difference that can be further activated by acute trauma. Moreover, negativity bias may be an important, modifiable treatment target, and interventions addressing both acute symptoms and negativity bias in the early posttrauma period may weaken the link between trauma history and new-onset PTSD.

Mechanisms of traumatic injury by demographic characteristics: an 8-year review of temporal trends from the National Trauma Data Bank.

BACKGROUND/PURPOSE: This 8-year retrospective study of the National Trauma Data Bank describes temporal trends of traumatic injury by mechanism of injury (MOI) by demographic characteristics from 2012 to 2019 for adult patients 18 years and older. METHODS: Overall, 5 630 461 records were included after excluding those with missing demographic information and International Classification of Disease codes. MOIs were calculated as proportions of total injury by year. Temporal trends of MOI were evaluated using two-sided non-parametric Mann-Kendall trend tests for (1) all patients and (2) within racial and ethnic groups (ie, Asian, 2% of total patient sample; Black, 14%; Hispanic or Latino, 10%; Multiracial, 3%; Native American, <1%; Pacific Islander, <1%; White, 69%) and stratified by age and sex. RESULTS/OUTCOMES: For all patients, falls increased over time (p=0.001), whereas burn (p<0.01), cut/pierce (p<0.01), cyclist (p=0.01), machinery (p<0.001), motor vehicle transport (MVT) motorcyclist (p<0.001), MVT occupant (p<0.001) and other blunt trauma (p=0.03) injuries decreased over time. The proportion of falls increased across all racial and ethnic groups and significantly for those aged 65 and older. There were further differences in decreasing trends of MOI by racial and ethnic categories and by age groups. CONCLUSIONS: These results suggest that falls are an important injury prevention target with an ageing US population across all racial and ethnic groups. Differing injury profiles by racial and ethnic identity indicate that injury prevention efforts be designed accordingly and targeted specifically to individuals most at risk for specific MOIs. STUDY TYPE: Level I, prognostic/epidemiological.

Harmonizing PTSD severity scales across instruments and sites.

OBJECTIVE: The variety of instruments used to assess posttraumatic stress disorder (PTSD) allows for flexibility, but also creates challenges for data synthesis. The objective of this work was to use a multisite mega analysis to derive quantitative recommendations for equating scores across measures of PTSD severity. METHOD: Empirical Bayes harmonization and linear models were used to describe and mitigate site and covariate effects. Quadratic models for converting scores across PTSD assessments were constructed using bootstrapping and tested on hold out data. RESULTS: We aggregated 17 data sources and compiled an n = 5,634 sample of individuals who were assessed for PTSD symptoms. We confirmed our hypothesis that harmonization and covariate adjustments would significantly improve inference of scores across instruments. Harmonization significantly reduced cross-dataset variance (28%, p < .001), and models for converting scores across instruments were well fit (median R² = 0.985) with an average root mean squared error of 1.46 on sum scores. CONCLUSIONS: These methods allow PTSD symptom severity to be placed on multiple scales and offers interesting empirical perspectives on the role of harmonization in the behavioral sciences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Milwaukee Syndemic? Penetrative Injury and COVID-19.

INTRODUCTION: This study sought to evaluate injury frequency of penetrative trauma before and after stay-at-home orders were implemented due to COVID-19 in Wisconsin. METHODS: Patients who presented to a level I trauma center from January 2018 through December 2021 with a mechanism of injury of firearm or stab wound were included. The study was split into pre-COVID (January 2018-February 2020) and COVID (March 2020-December 2021) periods. Statistical analysis included chi-square tests and interrupted time series analysis. RESULTS: A total of 1702 patients met inclusion criteria. The COVID group had a statistically significantly higher proportion of firearm injuries (83.2%) and a significantly lower proportion of stab injuries (16.8%) compared to the pre-COVID period group (70% and 30%, respectively, P < 0.001). There was no change from pre-COVID to COVID periods in in-hospital mortality or length of hospital stays. There was an increase in firearm incidents in the COVID period in 72% of Milwaukee County ZIP codes and a decrease in stab incidents in 48% of ZIP codes. Interrupted time series analysis indicated a significant increase from the pre-COVID to COVID periods in monthly firearm and stab injuries. Firearm injury significantly increased from pre-COVID to COVID for Black or African American patients but no other racial group. CONCLUSIONS: These findings are consistent with other state and national trends suggesting increasing penetrative injury during the COVID-19 pandemic. The intersection of the COVID-19 pandemic and violence pandemic may yield a "syndemic," imposing a significant burden on trauma systems. Evidenced-based public health interventions are needed to mitigate the surge of firearm injuries.

Event centrality and posttraumatic stress symptoms after traumatic injury: A longitudinal investigation.

The development of posttraumatic stress symptoms (PTSS) can occur following a traumatic injury, which may include an increase in negative cognitions. One cognitive construct shown to be associated with the development of PTSS is event centrality, or the degree to which an individual views a traumatic experience as central to their life story. Although cross-sectional work has demonstrated a robust connection between event centrality and PTSS, the directionality of this association remains unclear. Most previous work has investigated centrality as a predictor of PTSS, although one recent study suggests that PTSS may, in fact, predict event centrality. The current longitudinal study enrolled adult civilian participants (N = 191) from a Level 1 trauma center following a traumatic injury and assessed both event centrality and PTSS at three points posttrauma (3, 12, and 18 months). A time-constrained random intercept cross-lagged panel analysis showed that PTSS predicted event centrality over the 18-month follow-up period, B = 0.16, p = .021, but event centrality did not predict PTSS, B = -0.27, p = .340. These findings suggest that the development of PTSS following trauma exposure may lead to the perception of the traumatic event as central to an individual's story over time. Further longitudinal research is necessary to determine what variables may influence the connection between PTSS and event centrality.

Machine learning prediction of posttraumatic stress disorder trajectories following traumatic injury: Identification and validation in two independent samples.

Due to its heterogeneity, the prediction of posttraumatic stress disorder (PTSD) development after traumtic injury is difficult. Recent machine learning approaches have yielded insight into predicting PTSD symptom trajectories. Using data collected within 1 month of traumatic injury, we applied eXtreme Gradient Boosting (XGB) to classify admitted and discharged patients (hospitalized, n = 192; nonhospitalized, n = 214), recruited from a Level 1 trauma center, according to PTSD symptom trajectories. Trajectories were identified using latent class mixed models on PCL-5 scores collected at baseline, 1-3 months posttrauma, and 6 months posttrauma. In both samples, nonremitting, remitting, and resilient PTSD symptom trajectories were identified. In the admitted patient sample, a unique delayed trajectory emerged. Machine learning classifiers (i.e., XGB) were developed and tested on the admitted patient sample and externally validated on the discharged sample with biological and clinical self-report baseline variables as predictors. For external validation sets, prediction was fair for nonremitting versus other trajectories, areas under the curve (AUC = .70); good for nonremitting versus resilient trajectories, AUCs = .73-.76; and prediction failed for nonremitting versus remitting trajectories, AUCs = .46-.48. However, poor precision (< .57) across all models suggests limited generalizability of nonremitting symptom trajectory prediction from admitted to discharged patient samples. Consistency in symptom trajectory identification across samples supports prior studies on the stability of PTSD symptom trajectories following trauma exposure; however, continued work and replication with larger samples are warranted to understand overlapping and unique predictive features of PTSD in different traumatic injury populations.

Neighborhood Socioeconomic Disadvantage and the Neurobiology of Uncertainty in Traumatically Injured Adults.

BACKGROUND: Individuals residing in more socioeconomically disadvantaged neighborhoods experience greater uncertainty through insecurity of basic needs such as food, employment, and housing, compared with more advantaged neighborhoods. Although the neurobiology of uncertainty has been less frequently examined in relation to neighborhood disadvantage, there is evidence that neighborhood disadvantage is associated with widespread neural alterations. METHODS: Recently traumatically injured participants (n = 90) completed a picture anticipation task in the magnetic resonance imaging scanner, in which they viewed images presented in a temporally predictable or unpredictable manner. We investigated how neighborhood disadvantage (via area deprivation index [ADI]) was related to neural activation during anticipation and presentation of negative and neutral images after accounting for individual factors (i.e., age, gender, income, acute posttraumatic stress symptoms). RESULTS: There was a significant interaction during the anticipation period such that higher ADI rankings were related to greater activation of the right anterior cingulate cortex to predictable versus unpredictable neutral stimuli. Although no other robust interactions emerged related to ADI, we note several novel simple effects of ADI during anticipation and presentation periods in the hippocampus and prefrontal, cingulate, and occipital cortices. CONCLUSIONS: Together, these results may represent an adaptive response to predictable and/or negative stimuli, stemming from chronic exposure to socioeconomic-based uncertainties. Although effects were modest, future work should continue to examine pretrauma context on posttrauma outcomes. To better understand trauma outcomes, it is imperative that researchers consider the broader context in which trauma survivors reside.