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Developing a Community-Based ASD Research Registry

Developing a Community-Based ASD Research Registry
开发基于社区的 ASD 研究登记处
批准号:
7830900
负责人:
ROBERT Thomas SCHULTZ
金额:
$50.0万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2011-08-31

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中文摘要
翻译
描述(由申请人提供):开发基于社区的ASD研究登记本申请涉及广泛挑战领域05(比较有效性研究)和特定挑战主题05-MH-104(构建ASD登记用于比较有效性研究)。在研究中招募大样本是更好地了解ASD病因和治疗的最重要障碍。越来越多的研究将ASD描述为多基因、表型异质性和治疗反应高度可变。因此,大样本对于解开构成这种令人困惑的疾病的多种“自闭症”至关重要。与此同时,ASD的低患病率和许多研究的高负担使招募具有挑战性。我们提出了一种新的策略,以创建一个ASD研究注册,补充那些通过国家注册,如IAN和AGRE。我们建议在现有的社区-学术合作伙伴关系的基础上:1)通过基于人口的招募,将7500个ASD患者家庭纳入研究登记。我们将通过宾夕法尼亚州自闭症服务局(BAS)分发的全州需求评估,联系超过15,000个宾夕法尼亚州被诊断患有ASD的儿童家庭。我们还将寻求替代战略,建立在一系列丰富的学术社区伙伴关系和倡议已经到位。护理人员将被要求参加ASD研究登记,并询问他们可能参加的特定类型的研究。根据我们以前的需求评估和其他研究工作的反应,我们预计将招募至少7500名ASD患者。2)估计我们受访者的样本偏差。我们将评估地理、性别、种族、民族和服务需求方面的样本偏倚,以及偏倚如何与参与研究的意愿相关联。我们将使用我们招募的人群的医疗补助索赔和特殊教育数据来估计偏差。这对于利用该登记系统的合作研究将是非常宝贵的。3)确定所有者报告的临床表征的准确性。入组的护理人员将完成社会沟通问卷(SCQ)和社会反应量表(SRS)。我们将邀请分层随机抽样200名受访者接受更广泛的表型分析;简单和金标准措施的比较将使我们能够完善我们的策略,有效地识别ASD患者。4)利用生物信息学和当地社区的支持,快速创建和维护登记册。登记册将使用一个基于网络的数据管理系统,该系统将创建一个电子目录,可进行跟踪和电子邮件跟踪,并能够安全地收集在线数据。通过培训和支持计划,并参与咨询委员会,社区合作伙伴将塑造并受益于登记册。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。拟议的活动将导致一个大规模的,地理上接近实验室的生物和行为特征和治疗的个人与ASD。我们还将开发和传播一个创建社区登记处的模型,该模型有可能形成一个干预有效性研究的国家网络。 公共卫生相关性:在研究中招募大样本的困难可能是更好地理解自闭症谱系障碍(ASD)的原因和治疗的最重要障碍。我们提出了一种新的方法来快速有效地创建一个ASD研究注册表,其中包括至少7500名有兴趣参与研究的宾夕法尼亚州ASD患者。我们将建立登记处的成员是从他们被画的更广泛的人口一样多样化,测试验证他们的诊断的成本效益的方式,并展示如何建立大学和地方和国家机构之间的有效合作伙伴关系,以推进研究。
英文摘要
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.
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Clinical Translational Core
  • 批准号:
    10678894
  • 项目类别:
  • 资助金额:
    $16.48万
  • 财政年份:
    2021
  • 负责人:
    ROBERT Thomas SCHULTZ
  • 依托单位:
Clinical Translational Core
  • 批准号:
    10240000
  • 项目类别:
  • 资助金额:
    $18.91万
  • 财政年份:
    2021
  • 负责人:
    ROBERT Thomas SCHULTZ
  • 依托单位:
Predicting Autism and Social Functioning from Computer Vision Analyses of Motor Synchrony During Dyadic Interactions
  • 批准号:
    10057391
  • 项目类别:
  • 资助金额:
    $72.09万
  • 财政年份:
    2019
  • 负责人:
    ROBERT Thomas SCHULTZ
  • 依托单位:
Predicting Autism and Social Functioning from Computer Vision Analyses of Motor Synchrony During Dyadic Interactions
  • 批准号:
    10540333
  • 项目类别:
  • 资助金额:
    $64.6万
  • 财政年份:
    2019
  • 负责人:
    ROBERT Thomas SCHULTZ
  • 依托单位:
海外基金