Data Management and Analysis Core

数据管理与分析核心

• 批准号: 10523406
• 负责人: SCOTT N COMPTON
• 金额: $ 28.25万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-07 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10523406
• 关键词: Adaptive Behaviors; Address; Advisory Committees; Behavioral; Biological Markers; Caregivers; Caring; Child; Clinical Trials; Collaborations; Communication; Computer Vision Systems; Computing Methodologies; Consent; Data; Data Analyses; Data Collection; Data Reporting; Data Set; Data Storage and Retrieval; Databases; Detection; Development; Devices; Diagnostic; Doctor of Philosophy; Early identification; Electroencephalography; Ensure; Equipment; Faculty; Family; Goals; Health Insurance Portability and Accountability Act; Individual; Knowledge; Language; Leadership; Manuals; Measurement; Measures; Methodology; Methods; Monitor; Neurocognitive; Outcome; Outcome Measure; Participant; Patient Recruitments; Pattern; Phase; Phenotype; Play; Policies; Preparation; Procedures; Process; Protocols documentation; Publications; Quality Control; Quickset; Reporting; Reproducibility of Results; Research; Research Methodology; Research Personnel; Role; Science; Scientist; Screening procedure; Secure; Security; Standardization; Statistical Data Interpretation; Structure; Surveys; Testing; Time; Training; Work; adult with autism spectrum disorder; autism spectrum disorder; autistic children; behavioral outcome; biomarker discovery; brain based; data acquisition; data cleaning; data integrity; data management; data quality; data sharing; data submission; demographics; design; digital; digital health; experience; file format; improved; individuals with autism spectrum disorder; informatics infrastructure; innovation; novel; outreach; participant retention; programs; quality assurance; recruit; screening; social communication; timeline; tool; virtual

ABSTRACT – Data Management and Analysis Core The overall goal of the Duke Autism Center of Excellence (ACE) is to use a translational digital health and computational approach to address the critical need for more effective autism screening tools, objective outcome measures, and brain-based biomarkers that can be used in clinical trials with young autistic children. The Data Management and Analysis Core (DMAC) will support coordination of high-quality data collection, management, and analysis across the Duke ACE Projects and Cores. These Projects and Cores aim to apply shared, cutting- edge computational research methods to develop effective digital health tools for early autism detection and outcome monitoring and discover novel brain-based autism biomarkers. DMAC will play a key role in the Center’s ability to achieve its goals by overseeing consistent application of scientific standards and methodological rigor. DMAC will ensure clear, replicable acquisition protocols, post-processing analytic approaches, and data management and storage across a wide range of measurement domains, including electroencephalography, computer vision analytic measures, neurocognitive ability, language/social communication, adaptive behaviors, patterns of caregiver-child interaction, and diagnostic assessments. DMAC will employ well-justified data acquisition standards and innovative analytics within a secure informatics infrastructure designed to facilitate collaboration among the synergistic ACE Projects and Cores. The primary aims of DMAC are to (1) oversee the design and implementation of experimental protocols for acquisition of all study-related measures; (2) provide data acquisition and management support across all Projects and Cores; and (3) provide support and assistance with analyses of Center Projects, and in collaboration with investigators, conduct statistical analyses to address the specific aims of Projects and Cores. DMAC also will provide timely submissions of data to the National Database for Autism Research. This Core will also provide regular reports to the Center leadership, Executive Committee, External Advisory Committee, and individual investigators related to participant recruitment and retention, timelines, deliverables, protocol deviations, quality control indicators, scientific data, and outreach and dissemination activities. By providing these essential data management and analysis functions for all Projects and Cores, DMAC will ensure that the Duke ACE reaches its goals.

摘要 - 数据管理和分析核心 杜克自闭症卓越中心（ACE）的总体目标是使用翻译的数字健康和 计算方法以满足对更有效自闭症筛查工具的关键需求，客观结果 措施和基于大脑的生物标志物，可用于与年轻攻击性儿童的临床试验中。数据 管理和分析核心（DMAC）将支持高质量数据收集，管理， 以及杜克王牌项目和核心的分析。这些项目和核心旨在应用共同的，削减 - 边缘计算研究方法开发有效的数字保健工具，用于早期自闭症检测和 结果监测并发现新型的基于大脑的自闭症生物标志物。 DMAC将在该中心的关键角色 通过海外一致地应用科学标准和方法论严格的应用来实现其目标的能力。 DMAC将确保清晰，可复制的采集协议，后处理分析方法和数据 在包括脑电图，包括脑电图的各种测量领域的管理和存储 计算机视觉分析测量，神经认知能力，语言/社会交流，适应性行为， 照料者 - 儿童互动和诊断评估的模式。 DMAC将采用良好的数据 旨在促进的安全信息基础设施中的获取标准和创新分析 协同ACE项目和核心之间的合作。 DMAC的主要目的是（1）监督 设计和实施实验方案，以获取所有与研究相关的措施； （2）提供 所有项目和核心的数据获取和管理支持； （3）提供支持和帮助 通过对中心项目的分析，并与调查人员合作进行统计分析以解决 项目和核心的具体目的。 DMAC还将及时向国家提供数据提交 自闭症研究数据库。该核心还将为中心领导，高管提供定期报告 委员会，外部咨询委员会以及与参与招聘有关的个人调查人员 保留，时间表，可交付成果，协议出发，质量控制指标，科学数据和外展 传播活动。通过为所有项目提供这些基本数据管理和分析功能 核心，DMAC将确保公爵王牌实现其目标。