Novel Approaches to Infant Screening for ASD in Pediatric Primary Care

儿科初级保健中婴儿自闭症谱系障碍筛查的新方法

基本信息

  • 批准号:
    10018110
  • 负责人:
  • 金额:
    $ 78.56万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-09-15 至 2024-06-30
  • 项目状态:
    已结题

项目摘要

ABSTRACT – Novel Approaches to Infant Screening for ASD in Pediatric Primary Care The overall goal of this project is to develop and validate novel tools to identify risk for autism spectrum disorder (ASD) in infants 6-12 months of age in a pediatric primary care setting. Research has confirmed that ASD is associated with changes in brain and behavior that are evident during infancy, and proof-of-concept studies suggest that early intervention during the infant period can improve early brain function and developmental outcomes. Moreover, early universal autism screening has been shown to reduce existing disparities based on socioeconomic status (SES) and ethnicity/race in access to early diagnosis and treatment. This project leverages ongoing work that is currently funded as part of the Duke NIH Autism Center of Excellence (ACE) Award (NICHD P50 HD093074; Dawson, Center Director), which is evaluating a novel digital phenotyping tool for early ASD risk assessment in toddler-age children in a pediatric primary care setting. Our novel screening tool, SenseToKnow, is based on active closed-loop sensing, where children are shown brief, developmentally-appropriate, dynamic stimuli on a smart tablet or smartphone, while the sensors in the same device capture information for automatic, objective quantification of several behavioral risk markers, based on patterns of attention, orienting, affect, vocalizations, and motor behavior. The proposed research will 1) evaluate a novel infant version of the app, SenseToKnow-Infant, in a large population of infants in the context of routine pediatric care, and 2) examine the utility of a multi- modal approach to risk assessment that combines information from SenseToKnow-I with information from infant and maternal electronic health records (EHRs). Using both direct digital behavioral measurement via SenseToKnow-I and data readily available in the EHR, we aim to develop and validate a multimodal ASD risk assessment algorithm for use in infants (6-12 months of age) that can be deployed in the general population.
摘要-在儿科初级保健中筛查婴儿ASD的新方法

项目成果

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Geraldine Dawson其他文献

Geraldine Dawson的其他文献

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{{ truncateString('Geraldine Dawson', 18)}}的其他基金

Novel Approaches to Infant Screening for ASD in Pediatric Primary Care
儿科初级保健中婴儿自闭症谱系障碍筛查的新方法
  • 批准号:
    10443752
  • 财政年份:
    2019
  • 资助金额:
    $ 78.56万
  • 项目类别:
Scalable Computational Platform For Active Closed-Loop Behavioral Coding in Autism Spectrum Disorder
用于自闭症谱系障碍主动闭环行为编码的可扩展计算平台
  • 批准号:
    10440249
  • 财政年份:
    2019
  • 资助金额:
    $ 78.56万
  • 项目类别:
Novel Approaches to Infant Screening for ASD in Pediatric Primary Care
儿科初级保健中婴儿自闭症谱系障碍筛查的新方法
  • 批准号:
    10227331
  • 财政年份:
    2019
  • 资助金额:
    $ 78.56万
  • 项目类别:
Novel Approaches to Infant Screening for ASD in Pediatric Primary Care
儿科初级保健中婴儿自闭症谱系障碍筛查的新方法
  • 批准号:
    10670242
  • 财政年份:
    2019
  • 资助金额:
    $ 78.56万
  • 项目类别:
Scalable Computational Platform For Active Closed-Loop Behavioral Coding in Autism Spectrum Disorder
用于自闭症谱系障碍主动闭环行为编码的可扩展计算平台
  • 批准号:
    9791518
  • 财政年份:
    2019
  • 资助金额:
    $ 78.56万
  • 项目类别:
Neural signatures, developmental precursors, and outcomes in young children with ASD and ADHD
患有 ASD 和 ADHD 的幼儿的神经特征、发育前兆和结果
  • 批准号:
    10227712
  • 财政年份:
    2017
  • 资助金额:
    $ 78.56万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10698185
  • 财政年份:
    2017
  • 资助金额:
    $ 78.56万
  • 项目类别:
Co-occurring ADHD in young children with ASD: Precursors, detection, neural signatures, and early treatment
患有 ASD 的幼儿同时发生 ADHD:先兆、检测、神经特征和早期治疗
  • 批准号:
    9385863
  • 财政年份:
    2017
  • 资助金额:
    $ 78.56万
  • 项目类别:
Duke Autism Center of Excellence: A translational digital health and computational approach to early identification, outcome monitoring, and biomarker discovery in autism
杜克大学自闭症卓越中心:用于自闭症早期识别、结果监测和生物标志物发现的转化数字健康和计算方法
  • 批准号:
    10523403
  • 财政年份:
    2017
  • 资助金额:
    $ 78.56万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10523404
  • 财政年份:
    2017
  • 资助金额:
    $ 78.56万
  • 项目类别:

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