Parent-Child Interaction and Emotion Regulation in Preschoolers with Autism Spectrum Disorder

项目摘要 自闭症谱系障碍（ASD）儿童的情绪调节（ER）障碍加剧了社交障碍。 困难，增加父母的压力，并限制功能。学龄前是一个重要的时期， ER发育过程中，亲子互动起着至关重要的作用。这也是ASD通常 诊断和干预开始。本K23应用程序中描述的研究和培训将建立在 候选人现有的专业知识，增加研究复杂，多， 模态和二元社会过程对ER的发展很重要。具体而言，这项创新研究将 研究儿童对痛苦的生理和行为反应以及父母的调节动力学 作为学龄前儿童ER损伤的潜在早期标志物， 没有ASD。目的1检验ASD儿童与非ASD同龄人在沟通方面存在差异的假设， 消极情绪和他们的生理唤醒预测观察到的情绪的程度。目标2采取 发展的二元观点，以研究儿童情感沟通中的个体差异如何与 父母的适应性协同调节反应。这些目标将通过整合门诊 周边生理测量和详细的儿童情绪沟通的微分析编码（例如， 情绪信号的清晰度、显著性、直接性）和父母的反应。机器学习技术将 提供一种数据驱动的方法，在检查预测关系时整合多模态、二元数据 生理和行为之间的关系（目标1）和儿童沟通和父母的反应（目标2）。目的 3.利用儿童情绪反应的纵向测量，考察儿童情绪沟通与父母的关系 反应性与后期ER有关。候选人是一位临床心理学家，擅长微分析编码， 父母-婴儿互动的双向影响，以及婴儿早期社会交往的发展。 ASD的高风险。拟议的K23应用程序将为候选人提供开发所需的培训 新的知识和技能;（1）收集，分析和解释生理数据;（2）机器学习 用于分析来自多个模态的变量之间的预测关系的方法;以及（3） 概念/理论和方法问题有关的ER发展在学龄前。与这些 新的专业知识，候选人将有能力建立一个创新的研究计划，重点是 揭示ASD儿童社会情感发育障碍的生物行为标志物， 干预措施的具体目标侧重于父母与子女的互动。培训将在特殊的 匹兹堡大学精神病学系的科学环境，并得到了 一个由非常优秀的导师（Mazefsky、Goodwin、Akcakaya和Hipwell博士）和顾问组成的团队 (Drs. Morgan和Lunkenheimer），其互补的专业知识非常适合K23的目标 候选人的长期目标和目标。

PROJECT SUMMARY Emotion regulation (ER) impairments in children with autism spectrum disorder (ASD) exacerbate social difficulties, increase parental stress, and limit functioning. The preschool years mark a significant period in typical ER development during which parent-child interactions play a critical role. This is also when ASD is typically diagnosed and intervention begins. The research and training described in this K23 application will build on the candidate’s existing expertise, adding conceptual and methodological skills needed to study complex, multi- modal, and dyadic social processes important to ER development. Specifically, this innovative research will examine dynamics of children’s physiological and behavioral responses to distress and parents’ regulatory responses to their children as potential early markers of ER impairment in preschool-age children with and without ASD. Aim 1 tests the hypothesis that children with ASD differ from non-ASD peers in communication of negative emotion and in the degree to which their physiological arousal predicts observed emotion. Aim 2 takes a dyadic view of development to examine how individual differences in child emotion communication relate to parents’ adaptive co-regulatory responses. These aims will be achieved through integration of ambulatory peripheral physiological measurement and detailed microanalytic coding of child emotion communication (e.g. clarity, salience, directedness of emotional signals) and parent response. Machine learning techniques will provide a data-driven approach to integrate multi-modal, dyadic data in examining predictive relationships between physiology and behavior (Aim 1) and between child communication and parent response (Aim 2). Aim 3 will make use of longitudinal measures of child ER to examine how child emotion communication and parental responsiveness relate to later ER. The candidate is a clinical psychologist with expertise in microanalytic coding, bidirectional influences in parent-infant interactions, and early social-communication development in infants at high risk for ASD. The proposed K23 application will provide the candidate with the training needed to develop new knowledge and skills in; (1) collection, analysis, and interpretation of physiological data; (2) machine learning methods for analyzing predictive relations between variables from multiple modalities; and (3) conceptual/theoretical and methodological issues related to ER development in the preschool years. With these new expertise, the candidate will be well-positioned to build an innovative program of research focused on uncovering biobehavioral markers of disrupted social emotional development in children with ASD to act as specific targets for interventions focused on parent-child interactions. Training will occur within the exceptional scientific environment in the Department of Psychiatry at the University of Pittsburgh and with the support of a team of extremely well-qualified mentors (Drs. Mazefsky, Goodwin, Akcakaya, and Hipwell) and consultants (Drs. Morgan and Lunkenheimer) whose complementary expertise is ideally suited to the goals of this K23 proposal and the candidate’s long-term goals.