Cumulative environmental risk exposure in youth at clinical high-risk for psychosis
Cumulative environmental risk exposure in youth at clinical high-risk for psychosis
批准号:
10254288
负责人:
Teresa Vargas
金额:
$3.83万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2022-06-30
关键词:
AdolescenceAffectAreaAttenuatedBehavioralBypassCensusesCharacteristicsClinicalComputer softwareConflict (Psychology)DataDevelopmentDiseaseEnvironmental Risk FactorEtiologyEvaluationExhibitsExposure toFamily ViolenceFunctional ImagingFutureHealthHealth PolicyImaging technologyIncidenceIndividualInterventionInterviewLife StyleLinkLiteratureMeasuresModelingNeighborhoodsOccupationalOnset of illnessOutcomeParticipantPharmaceutical PreparationsPopulationPreventionPsychosesPsychotic DisordersPublic HealthRegulationResearch SupportResistanceResourcesRiskRisk FactorsRoleSchoolsSeveritiesSocioeconomic StatusSourceStressStructureSubstance abuse problemSymptomsSystemTestingTimeVictimizationWorkYouthallostatic loadbasebehavioral outcomebullyingdelivery complicationsexperiencefollow up assessmenthealthy volunteerhigh riskimprovedinterestneural networkneurodevelopmentneuromechanismnovelpredictive modelingprospectiverelating to nervous systemsocialsocial observationsstressorviolent crimeyoung adult
中文摘要
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英文摘要
Project Summary
Understanding the effects of environmental risk exposure on neural and behavioral development is
essential for targeting intervention and prevention efforts in public health policy. This is especially the case for
psychotic disorders, which have a 1% incidence in the population, and are highly debilitating and treatment
resistant (1). However, current understanding of environmental influences in the clinical high-risk (CHR) period
immediately leading up to psychotic disorder onset is limited (2). Specifically, neural mechanisms underlying
the effects of cumulative environmental risk factor exposure are poorly understood. Importantly, (a) allostatic
load and aggregate dysregulation models of stress exposure suggest there are strong benefits in studying
cumulative risk, as different types of risk exposure may have similar developmental consequences (3, 4) and
(b) cumulative models have been shown to be more powerful in addition to offering an increased prospective
prediction advantage (3-5). Nonetheless, in regards to environmental risk exposure, the literature has often
focused on a single predictor. Measuring the effects of multiple types of environmental risk exposure on neural
and behavioral outcomes is essential for targeting intervention and prevention efforts, as well as for informing
future allocation of treatment and prevention resources in this population. The current proposal will measure
cumulative risk exposure in 50 CHR and 50 healthy volunteers at an individual and structural level, in addition
to predicting candidate neural mechanisms, symptoms, and social/occupational functioning longitudinally. First,
this study aims to determine whether CHR individuals experience greater exposure to cumulative
environmental risk (Aim 1). Cumulative environmental risk will be measured at an individual and structural
level with structured interviews, multiple rater systematic social observation (SSO) software (6-9) and
geocoding of Census data. Then, the proposal will seek to determine whether cumulative environmental risk
exposure differentially affects neural connectivity in regions implicated in stress and affect regulation in CHR
and typically developing individuals, using structural and functional imaging technology (Aim 2). Finally, the
proposed project will examine whether cumulative environmental risk models are associated with symptoms
and functioning, and whether they predict the course of these features longitudinally in CHR individuals (Aim
3). Notably, exploratory analyses will be conducted to analyze whether exposure during different
developmental periods differentially predicts neural connectivity in areas of interest. Exploratory analyses will
also examine exposure to individual versus structural environmental risk factors separately with regards to
group differences and neural connectivity.
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