Developing a Community-Based ASD Research Registry

开发基于社区的 ASD 研究登记处

基本信息

  • 批准号:
    7830900
  • 负责人:
  • 金额:
    $ 50万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2009
  • 资助国家:
    美国
  • 起止时间:
    2009-09-30 至 2011-08-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Developing a Community-Based ASD Research Registry This application addresses Broad Challenge Area 05 (Comparative Effectiveness Research) and Specific Challenge Topic 05-MH-104 (Building ASD Registries for Use in Comparative Effectiveness Research). Enrolling large samples in research studies is the most significant barrier to better understanding the etiology and treatment of ASD. A growing body of research portrays ASD as polygenic, phenotypically heterogeneous, and highly variable in treatment response. Large samples are therefore critical to unraveling the multiple "autisms" that comprise this puzzling disorder. At the same time, the low prevalence of ASD and the high burden of many studies make enrollment challenging. We propose a novel strategy to create an ASD research registry that complements those adopted by national registries such as IAN and AGRE. We propose to build on existing community-academic partnerships to: 1) Enroll 7500 families of individuals with ASD into a research registry through population-based recruitment. We will contact >15,000 Pennsylvania families of children diagnosed with ASD in the Medicaid system through a statewide needs assessment distributed by Pennsylvania's Bureau of Autism Services (BAS). We will also pursue alternative strategies that build on a rich array of academic-community partnerships and initiatives already in place. Caregivers will be asked to enroll in an ASD research registry and asked about specific types of studies in which they might participate. Based on response from our previous needs assessment and other research efforts, we expect to enroll at least 7500 individuals with ASD. 2) Estimate the sample bias in our respondents. We will assess sample bias with regard to geography, sex, race, ethnicity and service needs, and how bias is associated with willingness to participate in research. We will estimate bias using Medicaid claims and special education data for the population from which we are recruiting. This will be invaluable to partnering studies that make use of this registry. 3) Determine the accuracy of caregiver-reported clinical characterization. Enrolled caregivers will complete the Social Communication Questionnaire (SCQ) and the Social Responsiveness Scale (SRS). We will invite a stratified random samplee200 respondents to receive more extensive phenotyping; comparison of brief and gold standard measures will allow us to refine our strategy for efficiently identifying individuals with ASD. 4) Use bioinformatics and local community support to rapidly create and sustain the registry. The registry will use a web-based data management system that will create an electronic directory with tracking and email follow-up, and enable secure online data collection. Through a program of training and support, and involvement in an Advisory Committee, community partners will both shape and benefit from the registry. The registry will also maximize access to other researchers while maintaining scientific and ethical standards. The proposed activities will result in a large-scale, geographically proximal laboratory for the biological and behavioral characterization and treatment of individuals with ASD. We also will develop and disseminate a model for creating community registries that has the potential to result in a national network for intervention effectiveness research. PUBLIC HEALTH RELEVANCE: The difficulty of enrolling large samples in research studies is perhaps the most significant barrier to better understanding the causes and treatment of Autism Spectrum Disorder, or ASD. We propose a new approach to quickly and efficiently create an ASD research registry that includes at least 7500 individuals with ASD within the state of Pennsylvania interested in participating in research. We will establish that members of the registry are as diverse as the broader population from which they are drawn, test a cost-effective way of verifying their diagnosis, and demonstrate how to build effective partnerships between universities and local and state agencies to advance research.
描述(由申请人提供):开发基于社区的 ASD 研究登记册 该应用程序解决了广泛的挑战领域 05(比较有效性研究)和具体挑战主题 05-MH-104(建立用于比较有效性研究的 ASD 登记册)。在研究中招募大样本是更好地了解 ASD 病因和治疗的最大障碍。越来越多的研究将自闭症谱系障碍描述为多基因、表型异质性以及治疗反应的高度可变性。因此,大样本对于揭示构成这种令人费解的疾病的多种“自闭症”至关重要。与此同时,自闭症谱系障碍(ASD)患病率低,且许多研究负担重,使得入组具有挑战性。我们提出了一项新的战略来创建 ASD 研究登记处,以补充 IAN 和 AGRE 等国家登记处采用的登记处。我们建议以现有的社区学术伙伴关系为基础:1) 通过基于人群的招募,将 7500 个 ASD 患者家庭纳入研究登记册。我们将通过宾夕法尼亚州自闭症服务局 (BAS) 发布的全州需求评估,联系医疗补助系统中超过 15,000 个被诊断患有 ASD 儿童的宾夕法尼亚州家庭。我们还将寻求建立在丰富的学术界合作伙伴关系和现有举措基础上的替代战略。护理人员将被要求注册自闭症谱系障碍研究登记处,并询问他们可能参与的特定类型的研究。根据我们之前的需求评估和其他研究工作的回应,我们预计将招募至少 7500 名 ASD 患者。 2) 估计受访者的样本偏差。我们将评估地理、性别、种族、民族和服务需求方面的样本偏差,以及偏差与参与研究意愿的关系。我们将使用医疗补助索赔和我们正在招募的人群的特殊教育数据来估计偏差。这对于利用该注册表的合作研究来说是非常宝贵的。 3) 确定护理人员报告的临床特征的准确性。登记的护理人员将完成社交沟通问卷 (SCQ) 和社交反应量表 (SRS)。我们将邀请 200 名受访者进行分层随机抽样,以接受更广泛的表型分析;简单测量和黄金标准测量的比较将使我们能够完善有效识别自闭症谱系障碍患者的策略。 4) 利用生物信息学和当地社区的支持来快速创建和维护注册表。该登记处将使用基于网络的数据管理系统,该系统将创建一个带有跟踪和电子邮件后续功能的电子目录,并实现安全的在线数据收集。通过培训和支持计划以及参与咨询委员会,社区合作伙伴将塑造登记册并从中受益。该登记处还将最大限度地接触其他研究人员,同时保持科学和道德标准。拟议的活动将建立一个地理上邻近的大规模实验室,用于自闭症谱系障碍患者的生物学和行为特征分析及治疗。我们还将开发和传播一种创建社区登记处的模型,该模型有可能形成一个全国性的干预有效性研究网络。 公共卫生相关性:在研究中招募大量样本的困难可能是更好地了解自闭症谱系障碍 (ASD) 的原因和治疗的最大障碍。我们提出了一种新方法,可以快速有效地创建 ASD 研究登记册,其中包括宾夕法尼亚州内至少 7500 名有兴趣参与研究的 ASD 患者。我们将确定登记册的成员与他们所抽取的更广泛的人群一样多样化,测试一种具有成本效益的方法来验证他们的诊断,并展示如何在大学与地方和州机构之间建立有效的合作伙伴关系以推进研究。

项目成果

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ROBERT Thomas SCHULTZ其他文献

ROBERT Thomas SCHULTZ的其他文献

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{{ truncateString('ROBERT Thomas SCHULTZ', 18)}}的其他基金

Clinical Translational Core
临床转化核心
  • 批准号:
    10678894
  • 财政年份:
    2021
  • 资助金额:
    $ 50万
  • 项目类别:
Clinical Translational Core
临床转化核心
  • 批准号:
    10240000
  • 财政年份:
    2021
  • 资助金额:
    $ 50万
  • 项目类别:
Predicting Autism and Social Functioning from Computer Vision Analyses of Motor Synchrony During Dyadic Interactions
通过计算机视觉对二元交互过程中运动同步的分析来预测自闭症和社交功能
  • 批准号:
    10057391
  • 财政年份:
    2019
  • 资助金额:
    $ 50万
  • 项目类别:
Predicting Autism and Social Functioning from Computer Vision Analyses of Motor Synchrony During Dyadic Interactions
通过计算机视觉对二元交互过程中运动同步的分析来预测自闭症和社交功能
  • 批准号:
    10540333
  • 财政年份:
    2019
  • 资助金额:
    $ 50万
  • 项目类别:
Novel computer vision-based assessment of infant-caregiver synchrony as an early level II screening tool for autism
基于计算机视觉的婴儿-看护者同步性评估作为自闭症早期 II 级筛查工具
  • 批准号:
    10023938
  • 财政年份:
    2019
  • 资助金额:
    $ 50万
  • 项目类别:
Predicting Autism and Social Functioning from Computer Vision Analyses of Motor Synchrony During Dyadic Interactions
通过计算机视觉对二元交互过程中运动同步的分析来预测自闭症和社交功能
  • 批准号:
    10308068
  • 财政年份:
    2019
  • 资助金额:
    $ 50万
  • 项目类别:
Testing the hyperspecificity hypothesis: a neural theory of autism
检验超特异性假说:自闭症的神经理论
  • 批准号:
    8514729
  • 财政年份:
    2012
  • 资助金额:
    $ 50万
  • 项目类别:
Testing the hyperspecificity hypothesis: a neural theory of autism
检验超特异性假说:自闭症的神经理论
  • 批准号:
    8359473
  • 财政年份:
    2012
  • 资助金额:
    $ 50万
  • 项目类别:
NEUROIMAGING OF AUTISM SPECTRUM DISORDERS
自闭症谱系障碍的神经影像学
  • 批准号:
    8171148
  • 财政年份:
    2010
  • 资助金额:
    $ 50万
  • 项目类别:
NEUROIMAGING OF AUTISM SPECTRUM DISORDERS
自闭症谱系障碍的神经影像学
  • 批准号:
    7955782
  • 财政年份:
    2009
  • 资助金额:
    $ 50万
  • 项目类别:

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