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.

项目概要 低/中等收入国家 (LMIC) 的青少年因接触 早期的逆境，估计有 2.5 亿儿童面临无法发挥其发展潜力的风险。 人类潜力的这种灾难性丧失发生在 10/90 鸿沟的背景下——我们当前科学的 10% 知识是由占世界人口 90% 的中低收入国家产生的。这种扭曲的证据基础。 导致对绝大多数人大脑发育的风险和复原力模式的了解有限 世界青少年的情绪调节（ER），改变体验的内部和外部过程。 或情绪的表达，是早期逆境和结果之间的关键中介因素，然而，缺乏数据 鉴于有证据表明背景塑造了青少年的社会化，世界上大多数国家的青少年对 ER 的关注值得关注。 拟议的研究通过结合 a) 复杂的方法来解决这一重大的心理健康问题。 数据分析技术和 b) 应用于纵向多模式的社区引导/参与式研究 脑成像、高维行为评估以及环境的综合定义 来自成熟且具有深刻特征的早期出生队列的暴露（不利的和保护性的） 目前工作的目标是为南非开普敦的青少年创建一个解释模型。 保护因素对 ER 恢复力神经发育轨迹的影响的前提是： 早期的逆境是异质的、强大的事件，会显着增加 ER 不良的风险，但也 青春期早期经历的弹性因素可以减轻/改善这些风险。 预测 ER 结果需要尖端、复杂的数据分析方法。 驱动方法将 1) 更准确地定义生活在中低收入国家的青少年的 ER 行为概况，这些青少年 暴露于异质逆境，2）为复原力之间的联系提供稳健的解释模型 因素和 ER 神经行为轨迹。目标 1 亚型 525 名 12-13 岁青少年。 LMIC 出生队列基于早期环境暴露，然后测试 ER 行为的神经相关性 弹性（基于功能连接的 MRI 测量、基于任务的活动和形态测量） 对于早期逆境亚型，目标 2 确定了导致青少年改善的神经生物学变化。 ER 并开发了一个解释模型来预测 2 年 (Time2-Time1) 纵向 ER 恢复轨迹 基于并发环境暴露（保护性和不利性）的亚型，占 早期的逆境 纳入参与者性别和青春期状态将确定跨途径的潜在差异。 我们将前瞻性方法与机器学习方法结合使用，目的是 提高认识和描述社会经济、结构性、 健康和人际关系方面的逆境。