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Accounting for selection and information bias in studies of Autism Spectrum Disorder

Accounting for selection and information bias in studies of Autism Spectrum Disorder
自闭症谱系障碍研究中的选择和信息偏差的解释
批准号:
10677370
负责人:
Taniqua Ingol
金额:
$3.97万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-05-01 至 2025-04-30

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中文摘要
翻译
项目摘要 在美国,大约每44名儿童中就有一名被诊断出患有自闭症谱系障碍(ASD)。许多 患有自闭症的儿童由于整个生命过程中的不利健康后果,生活质量下降。 早期诊断和干预服务对于改善ASD患者的长期预后至关重要。 然而,由于美国历史上种族隔离和歧视的做法,早期获得 诊断和干预服务是不公平的。识别和诊断患有ASD的儿童有助于 获得适当的服务,但保健服务中的种族和民族差异导致许多非西班牙裔 患有自闭症症状的黑人和西班牙裔儿童在医疗保健中未被诊断和治疗不足 在这些临床数据库产生的研究研究中没有得到充分的体现。即使这些 种族和民族差异在ASD诊断中有很好的记录,许多流行病学研究使用帐单代码 算法和医疗保健数据库来检查有关ASD的病因学问题,通常不需要 考虑潜在的结构性偏差。因此,这项拟议的论文研究将探索 关于ASD研究的信息和选择偏差,以及在硬膜外麻醉之间的关联的应用 止痛用法和房间隔缺损。本论文的研究内容包括以下几个方面:(1)效度评价 (即敏感度、预测值)病历中记录的ASD诊断与 根据黄金标准临床评估得出的诊断(按儿童种族和民族分层);(2)使用 内部验证数据,以进行偏差分析,以检查结果错误分类对 分娩期间硬膜外使用与自闭症之间的关系;以及(3)进行蒙特卡罗模拟以评估 选择偏向对分娩期间硬膜外使用与ASD之间的关联的影响。数据来自 探索早期发展研究(SEED)是一项大型的美国多点病例对照研究,将用于进行 建议的研究。在授予期间,奖学金申请者将达到以下目标:(1)获得 在科学写作和成果传播活动方面有更深入的经验;(2)在以下方面获得深入培训 负责任地进行研究;(3)发展定量偏差分析方法的分析技能和 模拟研究;(4)促进职业和个人发展;以及(5)发展强烈的理解 儿童发展和自闭症谱系障碍病因学的研究。这些目标将允许申请者 在自闭症病因学、健康不平等和定量偏差分析方法方面建立坚实的基础 通过额外的课程作业、研讨会、指导性阅读材料和与导师团队的咨询。 此外,他们将为申请者提供所需的技能,以实现他们成为终身教职的目标 教授专注于弥合流行病学研究和公共卫生实践之间的差距,以改进 在种族和族裔少数群体中的孕产妇和儿童健康结果。
英文摘要
PROJECT ABSTRACT In the United States, approximately 1 in 44 children are diagnosed with Autism Spectrum Disorder (ASD). Many children with ASD experience a reduced quality of life due to adverse health outcomes across the life course. Early diagnosis and intervention services are critical for improving long-term outcomes for individuals with ASD. However, because of historical practices of racial segregation and discrimination in the US, access to an early diagnosis and intervention services are not equitable. Identifying and diagnosing children with ASD facilitates access to appropriate services, but racial and ethnic disparities in healthcare services cause many Non-Hispanic Black and Hispanic children with ASD symptomology to be undiagnosed and under-treated in the healthcare system and under-represented in research studies generated from those clinical databases. Even though these racial and ethnic disparities in ASD diagnosis are well documented, many epidemiologic studies use billing code algorithms and healthcare databases to examine etiologic questions about ASD, often without necessary consideration of potential structural biases. Thus, this proposed dissertation research will explore the impact of information and selection bias on ASD research, with an application to the association between epidural analgesia use and ASD. The dissertation research will address the following specific aims: (1) Assess the validity (i.e., sensitivity, predictive values) of an ASD diagnosis documented in the medical record compared to a diagnosis derived from gold standard clinical assessments (stratified by child's race and ethnicity); (2) Use internal validation data to conduct a bias analysis to examine the impact of outcome misclassification on the association between epidural use during childbirth and ASD; and (3) Conduct Monte Carlo simulations to assess the impact of selection bias on the association between epidural use during childbirth and ASD. Data from the Study to Explore Early Development (SEED), a large US multi-site case control study, will be used to conduct the proposed research. During the grant period, the fellowship applicant will achieve the following goals: (1) gain more in-depth experience in scientific writing and results dissemination activities; (2) obtain in-depth training in responsible conduct of research; (3) develop analytical skills in methods for quantitative bias analysis and simulation studies; (4) enhance professional and personal development; and (5) develop a strong understanding of child development and the etiology of Autism Spectrum Disorders. These goals would allow the applicant to establish a solid foundation in the etiology of ASD, health inequities, and quantitative bias analysis approaches through additional coursework, seminars, guided readings, and consultation with the mentorship team. Furthermore, they will give the applicant the skillset needed to achieve their goal of becoming a tenure-track professor focused on bridging the gap between epidemiologic research and public health practice to improve maternal and child health outcomes among racial and ethnic minorities.
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