Acute predictors of long-term post-trauma outcomes in youth victims of violence

青年暴力受害者长期创伤后结果的急性预测因素

基本信息

批准号：
10237892
负责人：
MICHAEL N LEVAS
金额：
$ 71.45万
依托单位：
UNIVERSITY OF WISCONSIN MILWAUKEE
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-13 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10237892
关键词：
Accident and Emergency department Acute Address Adult Affect Affective Age Amygdaloid structure Anxiety Behavior Behavioral Biological Markers Brain Chronic Post Traumatic Stress Disorder Cognitive Communities Complement Data Development Dimensions Discrimination Distress Early Intervention Early-life trauma Elements Emotions Environment Event Exhibits Family Functional disorder Genetic Goals Health Hormonal Impairment Individual Intervention Knowledge Lead Life Link Longevity Machine Learning Measures Mental Depression Mental Health Mental disorders Neighborhoods Neurobiology Outcome Parents Pathology Patient Self-Report Pattern Pediatric Hospitals Performance Post-Traumatic Stress Disorders Predictive Factor Process Psychopathology Public Health Quality of life Reporting Research Risk Risk Factors Sampling Schools Signal Transduction Social Functioning Specific qualifier value Suicide attempt Symptoms System Time Trauma Victimization Violence Wisconsin Work Youth aged base brain health child and adolescent victimization clinical care cognitive control cognitive function disorder risk emotion regulation emotional functioning follow-up high risk improved injured innovation multidisciplinary neighborhood disadvantage neural circuit neurobehavioral neuroimaging physical assault post-trauma predictive marker preventive intervention programs prospective recruit reduce symptoms relating to nervous system resilience risk prediction sexual assault social socioenvironmental factor stress symptom trauma exposure trauma symptom traumatic stress violence exposure violence victimization youth violence

项目摘要

Youth violence victimization is common and increases risk for a host of negative health outcomes, most notably posttraumatic stress disorder (PTSD), which is the strongest predictor of poor quality of life following trauma, even among those injured during the event. Given the potential harmful sequelae of trauma exposure, it is crucial to identify acute post-victimization risk factors that predict chronic PTSD. At this juncture relatively little data exists to aid in prediction of youth at risk for poor long-term adjustment following victimization or other types of trauma, and there are no studies measuring relevant neural systems. Thus, our team aims to 1) characterize acute post-victimization neurobehavioral predictors of risk for chronic PTSD with a focus on prefrontal-subcortical function during processing of threat processing and frontoparietal networks for cognitive control, and 2) use machine learning to identify the most robust set of predictors of chronic PTSD drawn from a comprehensive assessment of youth neuroimaging, behavior and self-report, parent and family factors, and neighborhood and community variables. Our team is well-prepared to successfully achieve these aims, as we have relevant expertise in conducting prospective longitudinal assessment of acute neurobehavioral predictors of risk for PTSD in adults (Larson), conducting longitudinal assessment of youth victims of violence (Levas), and longitudinally characterizing neurobehavioral profiles of youth PTSD (Herringa). We will recruit youth victims of violence aged 10-16 from the Emergency Department at Children’s Hospital of Wisconsin in Milwaukee, and conduct comprehensive assessments at 2 weeks, 3 months, and 12 months following victimization. To achieve a final sample of 200 youth at 12 month follow-up, we will recruit 240 youth, oversampled for risk for PTSD based on currently available brief self-report indicators. Each assessment will include measures of neural systems instantiating threat processing, including both reactivity to threat and anticipation of unpredictable and predictable threat, and cognitive control, along with measures of PTSD and other symptoms, cognitive functioning, family environment, social and school functioning, and socioenvironmental factors (e.g. neighborhood disadvantage, discrimination). We will examine how acute post- victimization variables (2 week) and early change following victimization (from 2 weeks to 3 months) predict PTSD and other outcomes twelve months later. We will use both hypothesis-driven analyses focusing on a priori specified regions and predictors, as well as comprehensive data-driven machine learning analyses. The comprehensive assessment will allow for determination of the additional utility of neural markers for predicting risk beyond previously identified self-report indicators. We expect this project to lead to identification of predictors of risk for PTSD following victimization that are linked to underlying processes (hyper-responsivity to threat, aberrant cognitive control) that can directly inform preventive interventions, ultimately improving the quality of life for youth victims of violence.

青少年暴力受害很常见，并增加了一系列负面健康结果的风险，其中大多数值得注意的创伤后应激障碍 (PTSD)，它是创伤后应激障碍后生活质量差的最强预测因素创伤，即使是在事件中受伤的人考虑到创伤暴露可能造成有害的后遗症，在这个时刻，确定预测慢性创伤后应激障碍的急性受害后危险因素至关重要。几乎没有数据可以帮助预测青少年在受害或其他原因后长期适应不良的风险。类型的创伤，并且没有研究测量相关的神经系统，因此，我们团队的目标是 1) 描述慢性 PTSD 风险的急性受害后神经行为预测因子，重点关注处理威胁处理和认知额顶网络期间的前额皮质下功能控制，2) 使用机器学习来识别从一组最稳健的慢性 PTSD 预测因子对青少年神经影像、行为和自我报告、父母和家庭因素的综合评估，以及我们的团队已做好充分准备，可以成功实现这些目标，因为我们具有对急性神经行为预测因素进行前瞻性纵向评估的相关专业知识成人创伤后应激障碍 (PTSD) 风险 (Larson)，对青年暴力受害者进行纵向评估 (Levas)，并纵向描述青少年 PTSD 的神经行为特征（Herringa）。我们将招募青少年。威斯康星州儿童医院急诊科 10 至 16 岁的暴力受害者密尔沃基，并在随后的2周、3个月和12个月进行全面评估为了在 12 个月的随访中获得 200 名青少年的最终样本，我们将招募 240 名青少年，根据当前可用的简短自我报告指标对 PTSD 风险进行过采样。包括实例化威胁处理的神经系统的测量，包括对威胁的反应和对不可预测和可预测威胁的预期、认知控制以及创伤后应激障碍 (PTSD) 和其他症状、认知功能、家庭环境、社会和学校功能，以及我们将研究社会环境因素（例如邻里劣势、歧视）。受害变量（2 周）和受害后的早期变化（从 2 周到 3 个月）预测十二个月后，我们将使用两种假设驱动的分析，重点关注创伤后应激障碍（PTSD）和其他结果。先验指定区域和预测变量，以及全面的数据驱动机器学习分析。综合评估将允许确定神经标记在预测中的额外效用我们期望该项目能够识别出超出先前确定的自我报告指标的风险。受害后 PTSD 风险的预测因素与潜在过程（对威胁、异常认知控制），可以直接告知预防性干预措施，最终改善暴力青年受害者的生活质量。