Research Component: Multimodal Approach to Word Learning in Children with Autism

研究内容：自闭症儿童词汇学习的多模式方法

• 批准号: 10005937
• 负责人: NANCY CAROLINE BRADY
• 金额: $ 20.69万
• 依托单位: UNIVERSITY OF KANSAS LAWRENCE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10005937
• 关键词: 5 year old; Adaptive Behaviors; Address; Age; Area; Augmentative and Alternative Communication; Books; Characteristics; Child; Clinic; Clinical Trials; Combined Modality Therapy; Communication; Communication impairment; Comprehension; Computer software; Custom; Development; Devices; Educational process of instructing; Effectiveness; Effectiveness of Interventions; English Language; Environment; Family; Future; Home environment; Hour; Image; Impairment; Individual; Individual Differences; Instruction; Intellectual and Developmental Disabilities Research Centers; Intellectual functioning disability; Intervention; Investigation; Joints; Kansas; Language; Language Development; Learning; Life; Link; Longitudinal Studies; Measures; Neighborhoods; Nonverbal Communication; Outcome; Outcome Measure; Parents; Participant; Pilot Projects; Prediction of Response to Therapy; Principal Investigator; Probability; Production; Prognostic Marker; Publishing; Reading; Research; School-Age Population; Schools; Sequential Multiple Assignment Randomized Trial; Severities; Speech; Speech Sound; Students; Teaching Method; Technology; Time; Visual; Vocabulary; autism spectrum disorder; autistic children; automated speech recognition; base; computerized; density; follow-up; improved; innovation; learning outcome; multi-component intervention; multimodality; novel; personalized intervention; primary outcome; response; skills; sound; sound frequency; success; teacher; therapy design; treatment as usual; trial design; virtual vocal tract; word learning

Our project highlights one of the primary areas of research within the Kansas Intellectual and Developmental Research Center— language and communication. Specifically, we focus on language and communication in children with autism and minimal verbal skills (less than 20 spoken words). Remaining nonverbal past the age of 5 years has been considered a poor prognostic indicator for future language developments (Picket et al., 2009), yet few interventions have been developed to address this problem. The Specific Aims for this project are (1) to further investigate a multimodal intervention for school-age children with minimal verbal skills— defined as less than 20 words spontaneously spoken, signed, or selected via graphic symbol selection—and (2) to identify significant covariates associated with differential responding to the intervention. The research addresses an unmet need to promote spoken word production in children who remain essentially nonverbal well past the ages associated with speech acquisition. The project is also innovative because: a) it investigates a multimodal intervention based on principles of phonotactic probability and neighborhood density in combination with augmentative and alternative communication (AAC), and b) it investigates novel predictors of treatment response that are obtained through cutting-edge technologies. We propose that this intervention will have better success than past interventions because we will provide increased input through speech, digitized speech and visual images and additional speech sound practice for words that are comprised of high frequency sounds in the child’s repertoire. Extant speech sounds in each participant’s repertoire will be identified using LENA digitized recordings. Vocabulary words will then be selected based on a child’s speech sound repertoire and principles of word learning—words with high probability speech sound sequences will be selected and taught with either our multimodal intervention or a treatment as usual condition. Responses to these interventions will be evaluated using a Sequential Multiple Assignment Randomized Trials (SMART) design. We propose that different outcomes will be associated with individual and environmental predictors identified in our previous research. Individual predictors include verbal comprehension, imitation skills, adaptive behavior, nonverbal speech sound repertoire, and communication complexity. Communication complexity will be measured with the Communication Complexity Scale (CCS), developed by the Principal Investigator. Environmental predictors include language input to the child as measured with LENA recording devices. Results will determine if our multimodal intervention is more successful than treatment as usual for teaching word productions, but will also identify the individual and environmental profiles associated with differential outcomes. Our discoveries will lead to more focused clinical trial research and will inform customized intervention practices in schools and clinics. Ultimately this line of research aims to improve the lives of children with autism and their families through enhanced communication skills.

我们的项目突出了堪萨斯智力和发展研究中心的主要研究领域之一 研究中心——语言与交流。具体来说，我们专注于语言与交流。 患有自闭症且语言能力极差的儿童（超过年龄后仍保持非语言能力的单词少于 20 个）。 5 年被认为是未来语言发展的不良预后指标（Picket 等人， 2009），但很少有干预措施来解决这个问题。 (1) 进一步研究针对语言能力最低的学龄儿童的多模式干预—— 定义为自发说出、签名或通过图形符号选择选择的少于 20 个单词，并且 (2) 识别与干预措施的差异反应相关的显着协变量。 解决促进本质上仍不具备语言能力的儿童口语表达的未满足需求 该项目也具有创新性，因为：a）它进行了研究。 基于语音趋向概率和邻域密度原理的多模式干预 与增强性和替代性沟通（AAC）相结合，b）它研究了新的预测因素 我们建议这种干预措施将通过尖端技术获得治疗反应。 比过去的干预措施取得了更好的成功，因为我们将通过语音、数字化提供更多的输入 语音和视觉图像以及由高音组成的单词的附加语音练习 孩子的曲目中现有的语音将是每个参与者的曲目中的频率声音。 然后根据孩子的语音选择使用 LENA 数字化录音识别的词汇。 声音库和单词学习原理——具有高概率语音序列的单词将被 通过我们的多模式干预或对通常情况的治疗进行选择和教学。 这些干预措施将使用序贯多重分配随机试验 (SMART) 进行评估 我们建议不同的结果将与个人和环境预测因素相关。 我们之前的研究中确定的个人预测因素包括言语理解力、模仿能力、 适应性行为、非语言语音库和沟通复杂性。 复杂性将通过委托人开发的通信复杂性量表（CCS）来衡量 调查员。环境预测因素包括通过 LENA 记录测量的儿童语言输入。 结果将决定我们的多模式干预是否比常规治疗更成功。 教授文字作品，但也会识别与相关的个人和环境概况 我们的发现将带来更有针对性的临床试验研究，并提供信息。 最终，这一系列研究旨在改善学校和诊所的定制干预实践。 通过增强沟通技巧，改善自闭症儿童及其家人的生活。