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

患有自闭症谱系障碍的学龄前儿童的亲子互动和情绪调节

• 批准号: 10597223
• 负责人: Jessie B Northrup
• 金额: $ 17.46万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10597223
• 关键词: 4 year old; Arousal; Behavior; Behavioral; Biological; Caregivers; Child; Child Development; Clinical; Code; Collection; Communication; Complex; Cues; Data; Development; Diagnosis; Distress; Drug Prescriptions; Early identification; Emotional; Emotions; Environment; Expressed Emotion; Face; Family; Foundations; Fright; Goals; Home; Hospitalization; Impairment; Individual Differences; Infant; Inpatients; Intervention; Knowledge; Link; Machine Learning; Measurement; Measures; Mentors; Methodology; Modality; Monitor; Nursery Schools; Parent-Child Relations; Parents; Peripheral; Physiological; Physiology; Play; Population; Positioning Attribute; Problem behavior; Process; Psychiatry; Psychologist; Qualifying; Reporting; Research; Risk Assessment; Risk Factors; Role; Sampling; School-Age Population; Series; Signal Transduction; Social Processes; Stress; Techniques; Testing; Time; Training; Universities; Videotape; autism spectrum disorder; autistic children; behavioral response; biobehavior; emotion regulation; emotional distress; experience; high risk; indexing; individuals with autism spectrum disorder; innovation; machine learning method; multimodality; non-verbal; peer; positive emotional state; primary caregiver; programs; prospective; response; scaffold; showing emotion; skills; social; social communication; verbal

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.

项目总结 自闭症谱系障碍(ASD)儿童情绪调节(ER)障碍加剧社交 困难，增加父母的压力，限制功能。学龄前几年是典型的 在这个过程中，亲子互动起着至关重要的作用。这也是ASD通常 诊断并开始干预。此K23应用程序中描述的研究和培训将建立在 应聘者的现有专业知识，增加了研究复杂、多学科和多学科的概念和方法技能 对ER发展很重要的情态和二元社会过程。具体地说，这项创新研究将 考察儿童对困境的生理和行为反应的动态以及父母的调控 对子女的反应可作为学龄前儿童内质网损害的潜在早期标志物 没有自闭症。目的1检验ASD儿童与非ASD儿童在沟通方面的不同假设 消极情绪以及生理唤醒预测观察到的情绪的程度。《目标2》拍摄 二元发展观考察儿童情绪沟通中的个体差异如何与儿童情绪沟通 父母的适应性协同调节反应。这些目标将通过整合流动电话来实现 儿童情绪交流的外周生理测量和详细的微分析编码(例如 情绪信号的清晰度、显着性、指导性)和父母的反应。机器学习技术将 提供数据驱动的方法，在检查预测关系时集成多模式、二元数据 在生理和行为之间(目标1)以及在儿童交流和父母反应之间(目标2)。目标 3将利用儿童ER的纵向测量来考察儿童情绪沟通和父母如何 反应性与较晚的ER有关。应聘者是一位在微分析编码方面有专长的临床心理学家， 亲子互动中的双向影响与婴幼儿早期社交能力的发展 ASD的风险很高。拟议的K23应用程序将为应聘者提供开发所需的培训 新的知识和技能；(1)生理数据的收集、分析和解释；(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) 学龄前阶段与ER发展有关的概念/理论和方法问题。有了这些 新的专业知识，候选人将处于有利地位，建立一个创新的研究计划，专注于 发现ASD儿童社交情绪发育受阻的生物行为标记物 干预措施的具体目标侧重于亲子互动。培训将在特殊情况下进行 匹兹堡大学精神病学系的科学环境和一个 由非常合格的导师(马泽夫斯基博士、古德温博士、阿卡卡亚博士和希普韦尔博士)和顾问组成的团队 (摩根博士和伦肯海默博士)，他们的互补专业知识非常适合K23的目标 提案和候选人的长期目标。