Development matters: Characterizing patterns of emergent ADHD risk through a neurodevelopmental framework

项目摘要 注意力缺陷/多动障碍(ADHD)是一种普遍存在的儿童早期障碍， 对规范发展提出了显著的挑战，从学龄前开始就可以可靠地确定， 在使用基于发育的评估时，早在蹒跚学步的年龄就可以捕捉到风险。鉴定 有关注意障碍的发展，在坦率障碍出现之前，可以改善负面影响。 与急性ADHD综合征和损害相关的级联反应。此外，最近的研究指出 普遍存在的、很早就引起的心理健康不平等，在新发的ADHD模式中很明显，需要 公平评估，以减少预测性风险建模中的偏差(即，考虑 除了风险之外，对具体的风险指标进行建模，而不是将种族作为其代理)。因此，当前的 该项目试图用关注模式来描述发展变化及其社会人口背景。 (DYS)整个学龄期的监管结果在学龄前。这项工作借鉴了新奇的、临床上的 可翻译的研究工具捕捉典型：神经发育和行为的非典型谱 注意指标(DYS)调节：家长调查和标准化临床观察。该项目 以社区为基础的儿童样本，在他们的第一次健康儿童年度访问中被招募，并被过度抽样 对于精神病理风险(即易怒)。对稍后时间点结果的初步检查表明， 样本具有ADHD症状的良好特征，患病率与其他社区样本相匹配。在……下面 在这个奖项中，我将培训纵向建模的创新方法(即多层次和基于组的轨迹 建模)生成在幼儿时期密集收集的数据的模型，预测发育模式 学龄前(3-5岁)的ADHD急症结局。按照公平的评估办法， 检验结构性和家族性风险以及保护因素的结构方程模型将更加丰富 描述学龄前儿童出现ADHD症状的途径。这个项目试图刻画 在发育序列的最早阶段，神经发育对ADHD的易感性，建立了 早期风险评估和概念化的基于经验的、公平的方法。

Project Summary Attention deficit/hyperactivity disorder (ADHD) is a prevalent and impairing early childhood disorder that presents notable challenges to normative development and can be reliably identified starting at preschool age, with risk captured as early as toddler age when employing developmentally based assessments. Identification of concerning attention dysregulation development, before frank disorder presents, could ameliorate negative cascades associated with emergent ADHD syndromes and impairment. Further, recent research points to pervasive, early onsetting mental health inequities, evident in patterns of emergent ADHD, and the need for equitable assessment to reduce bias in predictive risk modeling (i.e., accounting for protective factors in addition to risks, modeling specific risk indicators, rather than taking race as a proxy thereof). Thus, the current project seeks to characterize developmental change and its sociodemographic context in patterns of attention (dys)regulation across toddlerhood with outcomes at preschool age. This work draws on novel, clinically translatable research tools capturing the typical:atypical spectrum of neurodevelopmental and behavioral indicators of attention (dys)regulation: parent survey and standardized clinical observation. The project engages a community-based sample of children recruited at their first annual well-child visits and oversampled for psychopathology risk (i.e., irritability). Initial examination of outcomes at later timepoints indicates that the sample is well characterized for ADHD symptoms with prevalence matching other community samples. Under this award, I will train in innovative methods of longitudinal modeling (i.e., multilevel and group-based trajectory modeling) to generate models of data collected densely at toddler age, predicting developmental patterns to emergent ADHD outcomes at preschool age(3-5 years). In alignment with an equitable assessment approach, structural equation models examining structural and familial risks and protective factors will more richly characterize pathways to emergent ADHD symptoms at preschool age. This project seeks to characterize neurodevelopmental vulnerability to ADHD at the earliest point in the developmental sequence, establishing an empirically grounded, equitable approach to assessment and conceptualization of early risk.