Measuring Sleep Problems in Children with Autism Spectrum Disorder

项目概要/摘要。 这个应用程序，写在响应PAR-18-039，将推进睡眠问题的结果测量， 自闭症谱系障碍（ASD）儿童（3-12岁）。睡眠问题（例如，睡眠障碍和 睡眠相关障碍）在ASD儿童中的范围从轻度到严重，在这方面影响多达80%。 年龄组（Katz et al，2018）。对于ASD儿童的睡眠问题，尚无公认的结局指标。 缺乏相关的、可靠的和有效的结果测量是对行为或 针对睡眠的药物治疗。使用混合方法设计，该多站点， 一个跨学科的项目将建立一个新的睡眠障碍和相关损害的父母评级， ASD儿童本研究由患者报告结局指标中描述的方法指导 （www.Fda.Gov/Cder/Guidance，2009年）。这篇专论迫使研究者将患者人群纳入 衡量发展。考虑到这项研究的年龄范围和认知或语言延迟的可能性， 自闭症儿童，我们依赖父母作为主要的信息提供者。 我们拥有一支优秀的调查人员和顾问团队，他们在测量开发方面具有专业知识， ASD的睡眠问题在第一年，多达六个焦点小组与家长将探讨发病和行为 ASD儿童睡眠问题的表现。将对焦点小组材料进行审查和编码， 生成一个项目库（Bearss et al. 2016）。这些项目将由以下人员进行审查，以确保其清晰度和阅读水平 家长和专家小组。在第二年，项目库（ASD睡眠问卷第1版; ASDSQ）将 被放置在一个安全的网站上，以收集父母报告的睡眠障碍和相关障碍的数据 在1200名自闭症儿童中。项目评分为0-3分（无、轻度、中度或重度）。因子分析和项目 本研究将应用反应理论建立因子结构，并将试题库精简至最后版本 （Scahill et al. in press）。在第3年和第4年初，对135名ASD儿童进行了现场临床评估， (age 3-12年），以收集ASDSQ最终版本的可靠性和有效性数据。一 两周后及四周后，将邀请次样本的儿童回校进行ASDSQ测试。在第四年， 来自临床评估的数据将用于评估聚合效度、发散效度和重测效度 ASDSQ的可靠性。同样在第三年和第四年初，我们将收集连续五个晚上的腕动记录 共75名ASD儿童（3至12岁）的数据，以评估睡眠效率（睡眠时间百分比 除以关灯睡觉的总时间）。活动描记术测量的睡眠效率（ASE）将用于进行 探索性分析比较ASE值受损儿童（睡眠不良者）与 具有可接受的ASE值（良好睡眠者）（Goldman等人，2009;摩尔等人，2017）。受试者工作 特征曲线将用于探索SDSQ对ASE分类的敏感性和特异性。

Project Summary / Abstract. This application, written in response to PAR-18-039, will advance outcome measurement for sleep problems in children (age 3-12 years) with Autism Spectrum Disorder (ASD). Sleep problems (e.g., sleep disturbances and sleep-related impairments) in children with ASD range from mild to severe and affect as many as 80% in this age group (Katz et al, 2018).There is no accepted outcome measure for sleep problems in children with ASD. The absence of a relevant, reliable and valid outcome measure is a barrier to rigorous testing of behavioral or pharmacological treatments targeting sleep in this population. Using a mixed method design, this multisite, transdisciplinary project will build a new parent rating for sleep disturbances and related impairments in children with ASD. The study is guided by methods described in Patient Reported Outcome Measures (www.Fda.Gov/Cder/Guidance, 2009). This monograph compels investigators to include the patient population in measure development. Given the age range of this study and likelihood of cognitive or language delays in children with ASD, we rely on parents as primary informants. We have an outstanding team of investigators and consultants with expertise in measure development and sleep problems in ASD. In Year 1, up to six focus groups with parents will explore the onset and behavioral manifestations of sleep problems in children with ASD. The focus group material will be reviewed and coded to generate a bank of items (Bearss et al. 2016). These items will be reviewed for clarity and reading level by parents and an expert panel. In Year 2, the bank of items (version 1 of ASD-Sleep Questionnaire; ASDSQ) will be placed on a secure website to collect parent-reported data on sleep disturbances and related impairments in 1200 children with ASD. Items will be scored 0-3 (none, mild, moderate or severe). Factor analysis and item response theory will be applied to establish the factor structure and prune the item pool toward the final version (Scahill et al. in press). In Year 3 and early Year 4, an in-person clinical assessment of 135 children with ASD (age 3-12 years) will be conducted to collect reliability and validity data on the final ASDSQ version. A subsample of children will be invited to return for test-retest on ASDSQ, 2 weeks and 4 weeks later. In Year 4, data from the clinical assessment will be used to evaluate convergent validity, divergent validity and test-retest reliability of the ASDSQ. Also in Year 3 and early Year 4, we will collect five consecutive nights of actigraphy data in a total of 75 children with ASD (age 3 to 12) to evaluate sleep efficiency (percentage of time sleeping divided by total time in bed with lights off). Actigraphy-measured sleep efficiency (ASE) will be used to conduct exploratory analyses comparing ASDSQ scores in children with impaired ASE values (poor sleepers) to those with acceptable ASE values (good sleepers) (Goldman et al. 2009; Moore et al. 2017). Receiver operating characteristic curves will be used to explore the sensitivity and specificity of SDSQ on ASE classifications.