Multisensory Development: New Measures and a Collaborative Database

多感官发展：新措施和协作数据库

• 批准号: 10400057
• 负责人: Lorraine E Bahrick
• 金额: $ 57.57万
• 依托单位: FLORIDA INTERNATIONAL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-19 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10400057
• 关键词: 5 year old; Achievement; Address; Affect; Age; Area; Attention; Child; Childhood; Cognitive; Collaborations; Complex; Data; Data Aggregation; Data Collection; Data Pooling; Data Set; Databases; Detection; Development; Disease; Early Intervention; Education; Ensure; Equation; Event; Face; Foundations; Future; Grain; Home; Impairment; Individual; Individual Differences; Infant; Intervention; Knowledge; Language; Language Development; Learning; Libraries; Life; Link; Maintenance; Measures; Methods; Modeling; Modernization; Outcome; Participant; Pathway interactions; Protocols documentation; Public Health; Research; Research Design; Research Personnel; Resources; Risk; Role; Sampling; Schools; Science; Site; Social Development; Social Functioning; Social outcome; Speech; Speed; Standardization; Subgroup; Tablets; Testing; Time; Training; Voice; analytical method; audiovisual speech; autistic children; base; cognitive development; cost effective; data management; data mining; data quality; data standards; early childhood; indexing; infancy; language outcome; laptop; large datasets; multisensory; portability; programs; scaffold; shared database; skills; social; theories; touchscreen

Project Summary Disorders of attention, social, and communicative functioning have become a significant public health concern yet we lack a systematic data base characterizing the typical development of basic building blocks that support optimal outcomes. We developed the first two individual difference measures assessing these building blocks for infants and children. We now propose to implement the measures in 13 research labs to collectively build a well-planned, large-scale, shared database, mine the database to advance knowledge and theory in developmental science, and, at the same time, forge a new model for collaborative research. Faces, voices, and infant-directed speech are highly salient to typically developing infants and scaffold language, social, and cognitive development. In contrast, children with autism show social-orienting impairments and deficits in social-communicative functioning. These capabilities depend on early multisensory attention skills (integrating and attending to information across the senses) particularly in dynamically changing faces, voices, and audiovisual speech. Without measures to assess individual differences in these fundamental skills, the pathways by which they affect later language, social, and cognitive development remain poorly understood. Our new protocols assess individual differences in attention maintenance, disengagement, and speed, and accuracy of intersensory processing for audiovisual social and nonsocial events in preverbal children. Preliminary findings from my current R01 reveal exciting relations between these multisensory skills and language and social outcomes in 3-36-month-olds. The present proposal builds on this foundation. The Multisensory Data Network brings together 13 experts in developmental science. We will 1) integrate our new protocols into each of their research labs, and 2) implement an overall data collection plan, with each lab testing participants using both protocols along with standardized language and social outcomes. This will create a shared database of more than 1600 3-60 month old children. 3) Data will be uploaded to Databrary, an online data-sharing library. 4) We will guide and standardize data collection across sites and create a multisite aggregate dataset for easy sharing across investigators. 5) Capitalizing on advantages of large datasets, we will derive the first preliminary norms for multisensory attention skills across 3-60 months and, using cutting-edge, SEM-based analyses, develop models characterizing developmental cascades from multisensory attention skills to more complex language and social capabilities that rely on this foundation. 6) We then develop portable protocols, expanding potential applications to classroom and home settings. This project will provide the first dataset of multisensory attention skills and effects on later outcomes across the first 5 years of life, with implications for identifying atypical trajectories and infants at risk for delays and guiding interventions. This collaborative model will catalyze new research directions and is more time efficient, cost effective, and will generate a larger, more diverse dataset than possible in individual research labs.

项目摘要 关注，社会和沟通功能的疾病已成为重要的公共卫生 然而，我们缺乏系统的数据库，表征了基本构建基础的典型发展 支持最佳结果。我们制定了评估这些建筑物的前两个个体差异措施 婴儿和儿童的障碍。现在，我们建议在13个研究实验室中实施这些措施以集体 建立一个精心计划的大规模，共享数据库，开采数据库，以提高知识和理论 发展科学，同时，为合作研究奠定了新的模型。 面孔，声音和以婴儿为导向的语音对通常发展的婴儿和脚手架高度显着 语言，社会和认知发展。相比之下，自闭症儿童表现出社会为导向 社会交流功能的障碍和缺陷。这些功能取决于早期多感官 注意力技能（整合和参与感官之间的信息），特别是在动态变化中 面孔，声音和视听演讲。没有评估这些基本差异的措施 技能，影响以后的语言，社交和认知发展的途径仍然很差 理解。我们的新协议评估注意力维持，脱离接触的个体差异和 预言中有视听社会和非社交事件的速度和精度处理的准确性 孩子们。我当前R01的初步发现揭示了这些多感官技能之间的激动人心的关系 以及3-36个月大的语言和社会成果。目前的提议建立在该基金会基础上。这 多感官数据网络汇集了13位发展科学专家。我们将1）整合我们的新 每个研究实验室的协议，以及2）实施一个总体数据收集计划，每个实验室 使用这两个方案以及标准化语言和社会成果对参与者进行测试。这会 创建一个1600多个3-60个月大的孩子的共享数据库。 3）数据将上传到数据库， 在线数据共享库。 4）我们将指导和标准化跨站点的数据收集，并创建一个 多站点聚合数据集，可轻松在研究人员之间共享。 5）利用大型优势 数据集，我们将在3-60个月中得出多感觉注意力技能的第一个初步规范，并且 使用尖端的基于SEM的分析，开发了表征发育级联的模型 依赖这个基础的更复杂语言和社交能力的多感官注意力技能。 6） 然后，我们开发便携式协议，将潜在应用程序扩展到教室和家庭设置。这 项目将提供第一个多感觉注意力技能和对以后结果的影响的第一个数据集 5年的生活，对确定有延迟风险和指导风险的非典型轨迹和婴儿的影响 干预措施。这种协作模型将催化新的研究方向，并且更加效率，成本 有效，并且将产生比单个研究实验室中更大，更多样化的数据集。