A Multimedia Screening System for Early ASD Identification in Diverse Populations

用于不同人群早期 ASD 识别的多媒体筛查系统

• 批准号: 8893574
• 负责人: KATARZYNA CHAWARSKA
• 金额: $ 24.98万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-17 至 2017-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8893574
• 关键词: 8 year old; Administrator; Age; Age of Onset; Agreement; Algorithms; Attention; Autistic Disorder; Behavior; Caring; Child; Childhood; Clinic; Clinical; Collaborations; Collection; Communities; Complex; Data; Detection; Development; Developmental Delay Disorders; Developmental Disabilities; Devices; Diagnosis; Diagnostic; Differential Diagnosis; Early Intervention; Early identification; Early treatment; Electronics; Evaluation; Failure; Feedback; Focus Groups; Future; Generations; Goals; Guidelines; Hand; Hospitals; Human Resources; Language; Life; Measures; Medical; Modeling; Multimedia; Nature; Outcome; Paper; Parents; Participant; Phenotype; Physicians; Population; Population Heterogeneity; Predictive Value; Preparation; Primary Care Physician; Primary Health Care; Process; Property; Provider; Psychometrics; Questionnaires; Recommendation; Records; Recruitment Activity; Research; Resources; Risk; Sampling; Services; Solutions; Specificity; Statistical Models; Surveys; Symptoms; Syndrome; System; Systems Integration; Tablets; Technology; Testing; Text; Time; Toddler; Translating; Validation; Visit; Visual; Work; autism spectrum disorder; base; clinical care; clinical phenotype; collaborative environment; cost; data exchange; digital; early awareness; follow-up; health record; high risk; indexing; information gathering; instrument; literacy; novel; population based; primary care setting; public health relevance; response; screening; socioeconomics; tool; usability

 DESCRIPTION (provided by applicant): Although we now have the tools and expertise to diagnose autism spectrum disorders (ASD) reliably in the 2nd year of life, most children are still diagnosed after their 4th birthday and, in under-resourced, ethnically diverse communities, as late as 8 years of age. These gaps highlight our failure to translate state-of-the art screening and diagnostic practices into practical solutions for identifying the most vulnerable children across socioeconomic strata. This disconnect is highly concerning given that early implementation of treatment leads to more positive outcomes. Factors contributing to the gaps include the limited awareness of early signs of ASD amongst parents and professionals, limited feasibility of deploying traditional paper-and-pencil screeners in primary care centers, and difficulties accessing appropriate services. In low-resource communities, these problems are further compounded by lack of supportive environments and language and literacy issues. This study aims to pilot a solution to surmount some of these challenges through the development of a new generation, tablet-based screening system comprised of two parts: (1) A novel video-based screener (Yale Adaptive Multimedia Screener, YAMS) based on early syndrome expression data collected over a decade at the Yale Toddler Developmental Disabilities Clinic (YTDDC) (Aim 1). By using simple spoken language, this screener will circumvent literacy-related issues. By providing visual examples, it will add clarity to concepts that may be complex for new parents. The screener will be adaptive, with questions contingent on prior responses, thus maintaining diagnostic precision within a time-efficient system highly acceptable by parents and staff; (2) Digital implementation of the M-CHAT-R/F, with automatic scoring for increased efficiency and with high-level interpretations and recommendations to increase physician utility. This adaptation will provide an established measure to augment our research goals and to serve as a comparison system for the YAMS (Aim 3). To gauge the utility and feasibility of our approach (Aim 2), we will test YAMS through collaborations with community primary care centers serving low-resource and ethnically diverse populations. 200 parents will be recruited to participate at their child's 18- or 24-month well-care visit. All who screen positive on the M-CHAT- R/F and/or our YAMS (N~20) will be invited for expert follow-up assessment at the YTDDC. Data from this community screening sample will be augmented by a clinic-based sample of 18-24 month-old toddlers with diagnoses of ASD (N=70), developmental delay (DD, N=20), or typical development (N=70). The combination of these two samples will provide preliminary validation of the usability, utility, and potential of our screener. Our study represens a cohesive, unified approach that leverages the full capabilities of modern, low-cost, hand-held technologies to move us towards the goal of early universal screening for ASD. Our unique focus combines attention to not just the development of the screening system itself, but also the usability of the system in diverse settings and the integration of the screener as a facilitating agent of the clinical care process.

 描述（由适用提供）：尽管我们现在拥有在生命第二年可靠地可靠地诊断自闭症谱系障碍（ASD）的工具和专业知识，但大多数儿童在4岁生日后仍被诊断出，并且在8岁以后，在资源不足，种族差异不足的社区中。这些差距突出了我们未能将最先进的筛查和诊断实践转化为实用解决方案，以识别社会经济阶层中最脆弱的儿童。这种脱节高度关注的是，早期的治疗实施会导致更积极的结果。导致差距的因素包括父母和专业人士对ASD早期迹象的认识有限，在初级保健中心部署传统的纸笔筛选器的可行性有限，以及难以获得适当服务的困难。在低资源社区中，由于缺乏支持的环境，语言和文学问题，这些问题进一步加剧了这些问题。这项研究旨在通过开发新一代，基于平板电脑的筛查系统的发展解决方案，包括两个部分：（1）基于早期综合征表达数据的新型基于视频的筛查器（Yale自适应多媒体筛选器，YAMS），该数据在耶鲁大学的十年中收集了耶鲁大学的幼儿发展企业固定型诊所（YTDC）（YTDC）（YTDC）。通过使用简单的口语，该筛选器将规避与扫盲有关的问题。通过提供视觉示例，它将为新父母可能很复杂的概念增添清晰度。筛选器将具有自适应，并取决于先前的答复，从而在父母和员工高度可接受的时间效率系统中保持诊断精度； （2）M-CHAT-R/F的数字实施，具有提高效率的自动评分，并提出了高级解释和建议，以增加物理效用。这种适应将提供既定的测量，以增强我们的研究目标并作为山药的比较系统（AIM 3）。为了衡量我们的方法的效用和可行性（AIM 2），我们将通过与服务低资源和种族多样性人群的社区初级保健中心的合作进行测试。将招募200个父母参加孩子的18个或24个月的良好护理访问。所有在M-Chat-R/F和/或我们的YAM（n〜20）上呈阳性的人将邀请在YTDDC进行专家后续评估。该社区筛查样本的数据将通过18-24个月大的幼儿的基于诊所的样本来增加ASD诊断（n = 70），发育延迟（DD，n = 20）或典型发育（n = 70）。这两个样本的组合将提供我们的研究，代表了一种凝聚力，统一的方法，它利用了现代，低成本，手持技术的全部能力，使我们朝着早期通用ASD筛选ASD的目标。我们独特的焦点组合不仅是筛选系统本身的开发，而且还可以在潜水员环境中的可用性以及筛选器作为临床护理过程的支持剂的整合。