Measuring Sleep Problems in Children with Autism Spectrum Disorder

项目摘要/摘要。 此应用程序是为响应PAR-18-039而编写的，它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 睡眠相关损害)在ASD儿童中从轻度到重度不等，影响多达80% 年龄组(Katz等人，2018年)。目前还没有公认的ASD儿童睡眠问题的结果衡量标准。 缺乏相关的、可靠的和有效的结果衡量标准是严格测试行为或 针对这一人群睡眠的药物治疗。使用混合方法设计，这个多站点， 跨学科项目将为睡眠障碍和相关损害建立新的家长评级 患有自闭症的儿童。这项研究是由患者报告的结果测量中描述的方法指导的 (www.fda.gov/CDER/Guidance，2009年)。这本专著迫使调查人员将患者群体包括在内。 在衡量发展方面。考虑到这项研究的年龄范围以及认知或语言延迟的可能性 对于患有自闭症的儿童，我们依赖父母作为主要的告密者。 我们拥有一支优秀的调查人员和顾问团队，他们在测量开发和管理方面具有专业知识 自闭症患者的睡眠问题。在第一年，最多六个有父母的焦点小组将探索发病和行为 自闭症儿童睡眠问题的表现。将对焦点小组材料进行审查和编码，以 生成项目库(Bearss等人2016)。将审查这些项目的清晰度和阅读水平 家长和专家小组。在第二年，题库(ASD-睡眠问卷第一版；ASDSQ)将 放在一个安全的网站上，以收集父母报告的睡眠障碍和相关损害的数据 在1200名患有ASD的儿童中。项目将被评为0-3分(无、轻度、中度或重度)。因子分析与项目 将应用反应理论来建立因素结构，并将题库向最终版本进行修剪 (斯卡希尔等人)在新闻发布会上)。在第三年和第四年初，对135名患有自闭症的儿童进行了面对面的临床评估 (3-12岁)将收集ASDSQ最终版本的信度和效度数据。一个 在2周和4周后，将邀请部分样本的儿童返回ASDSQ进行重测。在第四年， 来自临床评估的数据将用于评估收敛效度、发散效度和重测 ASDSQ的可靠性。同样在第三年和第四年年初，我们将收集连续五个晚上的动作记录 共有75名ASD儿童(3至12岁)的数据用于评估睡眠效率(睡眠时间百分比 除以关灯时的总卧床时间)。活动测量睡眠效率(ASE)将被用来进行 ASE受损儿童(睡眠质量差)与ASDQ评分的探索性分析 具有可接受的ASE值(睡眠良好者)(Goldman等人2009年；摩尔等人。2017年)。接收器运行 将使用特征曲线来探索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.