Resilient Emotion Regulation Development in a South African Birth Cohort

南非出生队列的弹性情绪调节发展

• 批准号: 10656016
• 负责人: Soraya Seedat
• 金额: $ 106.51万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-02 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10656016
• 关键词: 13 year old; Accounting; Address; Adolescence; Adolescent; Age; Algorithms; Amygdaloid structure; Behavior; Behavior assessment; Behavioral; Birth; Brain; Brain imaging; Child; Childhood; Chronic; Communities; Country; Data; Data Analytics; Data Collection; Development; Emotions; Enrollment; Environment; Environmental Exposure; Event; Exposure to; Factor Analysis; Family; Goals; Grant; Health; Human; Income; Individual Differences; Inequity; Knowledge; Life; Link; Longitudinal Studies; Magnetic Resonance Imaging; Measures; Mediator; Mental Health; Mental disorders; Modeling; Neurobiology; Outcome; Parents; Participant; Pathway interactions; Patient Self-Report; Pattern; Phenotype; Play; Population; Poverty; Predictive Factor; Pregnancy; Pregnancy Trimesters; Process; Puberty; Recovery; Reporting; Research; Risk; Risk Factors; Role; Sampling; Schools; Second Pregnancy Trimester; Shapes; Social Environment; Socialization; Source; South Africa; South African; Techniques; Testing; Time; Violence; Work; Youth; analytical method; clinically significant; cohort; computerized; coping; early adolescence; early life adversity; emotion dysregulation; emotion regulation; evidence base; experience; high dimensionality; high risk; improved; low and middle-income countries; machine learning method; morphometry; multimodality; neural correlate; neurobehavioral; neuroimaging; prenatal; prenatal exposure; promote resilience; prospective; protective factors; random forest; resilience; resilience factor; retention rate; risk mitigation; sex; showing emotion; socioeconomics

Project Summary Adolescents in low-/middle-income countries (LMICs) lose substantial developmental potential from exposure to early adversities, with an estimated 250 million children at risk of not reaching their developmental potential. Such catastrophic loss of human potential occurs in the context of the 10/90 divide – 10% of our current scientific knowledge is produced in or by LMICs that comprise 90% of the world’s population. This skewed evidence base has led to a limited understanding of patterns of risk and resilience in brain development for the vast majority of the world’s adolescents. Emotion regulation (ER), the internal and external process that modifies the experience or expression of an emotion, is a key mediator between early adversity and outcomes, and yet, the lack of data on ER in youth from most of the world is of concern given evidence that context shapes the socialization of emotion. The proposed research addresses this significant mental health problem by combining a) sophisticated data analytic techniques and b) community-guided/-participatory research applied to longitudinal multimodal brain imaging, high-dimensional behavioral assessments, and comprehensive defining of environmental exposures (both adverse and protective) from a well-established and deeply-characterized birth cohort of early adolescents in Cape Town, South Africa. The goal of the present work is to create an explanatory model for the impact of protective factors on neurodevelopmental trajectories underlying ER resilience. The premise is that early adversities are heterogeneous, powerful events that significantly increase the risk of poor ER, but also that resilience factors experienced during early adolescence can mitigate/ameliorate these risks. Therefore, prediction of ER outcomes requires cutting-edge, sophisticated data analytic methods. We hypothesize that data- driven approaches will 1) more precisely define ER behavioral profiles for adolescents living in LMICs who are exposed to heterogeneous adversities, and 2) provide a robust explanatory model for links between resilience factors and ER neurobehavioral trajectories. Aim 1 subtypes 525 12-13 year-old adolescents in an established LMIC birth cohort based on early environmental exposures and then tests for neural correlates of ER behavioral resilience (based on MRI measures of functional connectivity, task-based activity, and morphometry) accounting for early adversity subtype. Aim 2 identifies changes in neurobiology that underlie improvements in adolescent ER and develops an explanatory model to predict 2-year (Time2-Time1) longitudinal ER resilience trajectory subtypes based on concurrent environmental exposures (protective and adverse), accounting for early adversity subtype. The inclusion of participant-sex and pubertal status will identify potential divergence in pathways across early adolescence. We use a prospective approach together with machine learning methods with the goal of improving precision and inclusivity in recognizing and characterizing resilience to socio-economic, structural, health, and interpersonal adversities.

项目摘要 低收入/中等收入国家的青少年因接触毒品而丧失了巨大的发展潜力。 早期逆境，估计有2.5亿儿童面临无法发挥其发展潜力的风险。 这种人类潜能的灾难性丧失发生在10/90鸿沟的背景下--我们目前的科学研究中有10%是在10/90鸿沟的背景下进行的。 知识是由占世界人口90%的中低收入国家产生的。这个扭曲的证据基础 导致对绝大多数人大脑发育中的风险和弹性模式的理解有限， 全世界的青少年。情绪调节（ER），改变经验的内部和外部过程 或情绪表达，是早期逆境和结果之间的关键调解人，然而，缺乏数据， 鉴于有证据表明，环境塑造了青年人的社会化， 情绪这项拟议中的研究通过结合以下方法来解决这一重大的心理健康问题： 数据分析技术和B）社区指导/参与式研究应用于纵向多模态 脑成像，高维行为评估，以及环境的全面定义 暴露（不利和保护）从一个完善的和深入的特点出生队列的早期 南非开普敦的青少年。本工作的目标是创建一个解释模型， 保护因素对内质网弹性神经发育轨迹的影响。前提是 早期逆境是异质的，强大的事件，显着增加了不良ER的风险，但也 在青春期早期经历的弹性因素可以减轻/改善这些风险。因此，我们认为， ER结果的预测需要尖端的、复杂的数据分析方法。我们假设数据- 驱动的方法将1）更精确地定义生活在LMIC的青少年的ER行为特征， 暴露于异质逆境，2）提供了一个强大的解释模型之间的联系弹性 因素和ER神经行为轨迹。目的1亚型525 12-13岁的青少年在一个既定的 基于早期环境暴露的LMIC出生队列，然后测试ER行为的神经相关性 弹性（基于功能连接、基于任务的活动和形态测量的MRI测量）核算 早期逆境亚型。目标2确定了神经生物学的变化，这些变化是青少年改善的基础。 ER和开发一个解释模型来预测2年（时间2-时间1）纵向ER弹性轨迹 基于并发环境暴露（保护性和不利）的亚型， 早期逆境 亚型纳入参与者性别和青春期状态将确定跨途径的潜在分歧， 青春期早期我们使用前瞻性方法和机器学习方法，目标是 提高认识和描述社会经济、结构、 健康和人际逆境。