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：
10441367
负责人：
MICHAEL N LEVAS
金额：
$ 70.22万
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/10441367
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.

青年暴力胜利很普遍，增加了许多负面健康结果的风险，大多数值得注意的是创伤后应激障碍（PTSD），这是效果不佳的强大预测指标创伤，即使在活动期间受伤的人中。考虑到创伤暴露的潜在有害后遗症，至关重要的是鉴定预测慢性PTSD的急性恶化后风险因素。在这个关头相对很少有数据可以帮助预测胜利后长期调整不佳的年轻人或其他数据创伤的类型，并且没有研究测量相关神经系统的研究。那，我们的团队的目标是1）表征急性恶化后神经行为的慢性PTSD风险预测指标，重点是在处理威胁处理和认知额叶网络的过程中，前额叶和皮质功能控制，以及2）使用机器学习来识别从A 全面评估青年神经影像，行为和自我报告，父母和家庭因素以及邻里和社区变量。我们的团队已经准备好以成功地实现这些目标，就像我们一样拥有相关专家在进行急性神经行为预测指标的前瞻性纵向评估成人（拉尔森）有PTSD的风险，对青年虐待暴力（LEVAS）进行纵向评估，并纵向描述了青年PTSD（Herringa）的神经行为特征。我们将招募青年威斯康星州儿童医院的急诊科的暴力受害者10-16岁密尔沃基并在2周，3个月和12个月内进行全面评估受害。为了在12个月的随访中获得200名青年的最终样本，我们将招募240名青年，基于当前可用的简短自我报告指标，对PTSD的风险进行了过采样。每个评估都会包括神经元系统实例化威胁处理的措施，包括对威胁的反应性和期待不可预测和可预测的威胁以及认知控制，以及PTSD和PTSD的措施其他症状，认知功能，家庭环境，社会和学校功能以及社会环境因素（例如邻里障碍，歧视）。我们将研究急性后受害变量（2周）和受害后的早期变化（从2周到3个月）预测 PTSD和其他成果十二个月后。我们将使用两个假设驱动的分析，重点是先验指定的区域和预测因素以及全面的数据驱动机器学习分析。全面的评估将允许确定神经标记的额外效用以预测超越先前确定的自我报告指标的风险。我们希望这个项目能够确定胜利后PTSD风险的预测因素与基本过程有关威胁，异常认知控制），可以直接告知预防性干预措施，最终改善青年虐待暴力的生活质量。