Externalizing outcomes in high risk youth
Externalizing outcomes in high risk youth
批准号:
10153459
负责人:
KENT A KIEHL
金额:
$69.21万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-05 至 2022-04-30
关键词:
AcademiaAdolescenceAdolescentAdultAge of OnsetAggressive behaviorAlcoholsAnteriorAreaAttentionBehaviorBehavioralBiologicalBrainBrain imagingCollaborationsCollectionComplexConsentCrimeCriminologyDangerousnessDataData SetDevelopmentDisciplineDrug usageEvaluationEventExpenditureFamilyFirearmsFollow-Up StudiesForensic MedicineFundingFutureGenderHealthHealth StatusHealthcareImageImpairmentImprisonmentIndividualInterventionInterviewInvestigationKnowledgeLateralLeadLifeLife Cycle StagesMRI ScansMachine LearningMagnetic Resonance ImagingMapsMeasuresMedialMental HealthMethodsModelingNeurocognitiveNeuropsychological TestsNew MexicoOutcomeParticipantPathologicPatternPharmaceutical PreparationsPropertyPsychological FactorsPsychosocial FactorRelapseResearchRestRiskSamplingScanningSecuritySociologyStatistical ModelsStructureSubstance abuse problemSumTechniquesTimeUnited StatesUnited States National Institutes of HealthViolenceWorkYouthanti socialantisocial behaviorbehavioral outcomecallous unemotional traitcognitive controlcognitive neurosciencecohortconvictcorrectional systemcostdevelopmental psychologyefficacious treatmentexternalizing behaviorfollow-uphigh dimensionalityhigh riskindexingmultidimensional datamultimodal dataneural circuitneurodevelopmentneuroimagingneuromechanismnoveloutcome predictionpediatric traumapredictive modelingpreventprospectiveprotective factorspsychologicpsychosocialrelating to nervous systemrepeat offendersocialsocial factorssubstance usetrait impulsivitytreatment strategyyoung adult
中文摘要
项目概要/摘要
公众的注意力往往被吸引到暴力与心理健康问题之间的关系,
暴力行为是一种非常复杂的现象,受到无数社会、心理、环境
和生物影响。本项目旨在调查这些影响中的一个大样本,
对以前被监禁的青年进行跟踪,并收集宝贵的纵向数据。我们的团队
我与这些年轻人和他们的家人一起收集了详细的心理、行为和神经成像
作为以前NIH资助的调查的一部分。目前的项目旨在重新评估这些
个体(现在是年轻的成年人)检查长程阳性(即,停止吸毒/反社会
行为)和负面(药物复发,反社会行为)结果。我们会收集新的神经成像
扫描,结合先前的MRI数据,将有助于量化的变化轨迹,映射到
坚持和停止将结果外化。先进的机器学习方法将是
与结构、功能、网络和动态网络脑测量结合使用,
行为和心理测量。机器学习方法能够识别
高维数据,并描绘出最能预测特定
结果变量。使用这些方法,我们打算定义预测结果的神经机制。我们
还旨在确定变量的组合,赋予更大的风险,持续的反社会行为,
暴力这项工作的翻译价值将是澄清数据的信息模式,
可预防的结果。此外,指示特定脆弱性的神经测量将被确定为
具体的治疗目标和新的干预战略。通过识别特定的漏洞,
伴随积极成果的变化,我们将更接近于理解认识和
防止代价高昂的暴力行为
英文摘要
Project Summary/abstract
Public attention has often been drawn to the relationship between violence and mental health issues, but
violent behavior is a very complex phenomenon undergirded by myriad social, psychological, environmental,
and biological influences. This project intends to investigate these influences among a large sample of
previously incarcerated youth, following up with them and collecting valuable longitudinal data. Our team
worked with these youth and their families collecting detailed psychological, behavioral, and neuroimaging
measures as part of a previous NIH-funded investigation. The current project aims to re-assess these
individuals (now young adults) to examine long-range positive (i.e., desistance from drug use/antisocial
behavior) and negative (relapse to drugs, antisocial behavior) outcomes. We will collect new neuroimaging
scans, which combined with prior MRI data, will be useful for quantifying trajectories of change that map to
persistence and desistence from externalizing outcomes. Advanced machine-learning approaches will be
utilized in conjunction with structural, functional, network, and dynamic network brain measures in addition
to behavioral and psychological measures. Machine learning approaches are capable of identifying patterns in
high-dimensional data and delineating the unique combinations of variables that are most predictive of specific
outcome variables. Using these methods, we intend to define neural mechanisms that predict outcomes. We
also aim to identify combinations of variables that confer greater risk for persistent antisocial behavior and
violence. The translational value of this work will be to clarify informative patterns of data that may indicate
preventable outcomes. Furthermore, neural measures indicative of specific vulnerability will be identified as
specific targets for treatment and novel intervention strategies. By identifying specific vulnerabilities and the
changes that accompany positive outcomes, we will be closer to understanding the best way to recognize and
prevent costly violent behavior.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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海外基金