Development of a Prospective Video-Based Measure to Identify ASD Risk in Infancy

描述（由申请人提供）：有强有力的证据表明自闭症谱系障碍（ASD）的迹象是存在的，并且在一岁晚期和第二年早期可以检测到。父母首先在孩子平均14个月大的时候发现孩子对发育的担忧。尽管如此，在美国首次诊断ASD的平均年龄在41岁半到51岁半之间（CDC, 2012）。早期强化干预对患有ASD的幼儿非常有效，但仅限于正式诊断的儿童，因此早期识别是必要的。一种可以在所有症状出现之前识别ASD风险的方法，为大脑具有最大可塑性的时候进行干预提供了机会。然而，由于测量问题，早期识别的希望仍然受到阻碍。虽然学龄儿童的家长可以可靠地报告ASD症状，但对于3岁以下儿童的家长来说，评估个体差异要困难得多。我们建议开发一种新的基于视频的早期发育评估方法。利用已经收集和编码的数千小时的ASD风险婴儿视频，我们建议创建一个视频库，描述从非常典型到明显延迟发展的社会，沟通和重复行为的连续体。我们将与一家为自闭症儿童家庭开发软件的公司合作，创建一种衡量标准，通过一个安全的网站实施，父母可以通过该网站评估与婴儿行为的相似性，并确定最能代表他们孩子的视频。这项措施将减轻家庭负担，因为它简短，可以通过互联网安全管理。第一年

DESCRIPTION (provided by applicant): There is strong evidence that signs of autism spectrum disorders (ASD) are present and detectable late in the first year and early in the second year of life. Parents first identify concerns about development at a mean age of 14 months. Despite this, the mean age of first diagnosis of ASD in the United States is between 41/2 and 51/2 years (CDC, 2012). Early intensive intervention can be highly effective for young children with ASD, but is reserved for children with a formal diagnosis, making early identification imperative. A measure that could identify ASD risk before the full set of symptoms has emerged offers the opportunity for intervention when the brain has the greatest plasticity. The promise of earlier identification remains hampered, however, by measurement issues. Although ASD symptoms can be reliably reported by parents in school-age children, individual variation is much more difficult for parents to assess in children under the age of 3 years. We propose to develop a new video-based method of assessing early development. Taking advantage of thousands of hours of already collected and coded video of infants at risk for ASD, we propose to create a video library depicting a continuum of social, communication, and repetitive behaviors, from very typical to clearly delayed development. In collaboration with a company that develops software for families of children with autism, we will create a measure, implemented through a secure website, with which parents can rate similarity to their infant's behaviors and identify video that best represents their child. This measure will be of low burden to families, as it is brief and can be administered in a secure manner via internet. The first year of funding will be used to develop this new measure (Aim 1), called the Video-Referenced Infant Rating System for Autism (VIRSA), which will extend from 6 to 18 months of age. After an initial validation process, the VIRSA will be administered three times (6, 12, and 18 months) to parents of 90 infants at familial risk for ASD and 45 infants with no family history of ASD (Aim 2) The infants will then be followed to 36 months of age, when diagnostic outcome evaluations will be performed. We will compare the psychometric properties and predictive validity of the VIRSA to other measures and identify best cutoffs for identification. We will examine agreement between parent- and expert-ratings to determine the validity of the measure in parents with and without experience of ASD. The ultimate goal of the project is to develop a low-cost, low-burden measure that can detect ASD risk in infancy. Such a measure has significant public health applications, including earlier diagnosis, longitudinal tracking of development to identify childre requiring evaluation, screening of large community-based samples, and monitoring of individual intervention progress.