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: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10677370
• 关键词: Accidental Injury; Accounting; Algorithms; Birth Certificates; Black race; Caregivers; Case/Control Studies; Child; Child Development; Childbirth; Classification; Clinical assessments; Code; Consultations; Country; Data; Databases; Development; Diagnosis; Early Diagnosis; Early Intervention; Epidemiologic Methods; Epidural Analgesia; Equity; Ethnic Origin; Etiology; Evaluation; Fellowship; Foundations; Future; Goals; Grant; Health; Healthcare; Healthcare Systems; Hispanic; Information Dissemination; Interview; Life Cycle Stages; Literature; Maternal and Child Health; Medical Records; Mental disorders; Mentorship; Metabolic syndrome; Methods; Monte Carlo Method; Mothers; Not Hispanic or Latino; Outcome; Predictive Value; Public Health Practice; Quality of life; Race; Racial Segregation; Registries; Reporting; Research; Risk; Risk Factors; Selection Bias; Services; Site; Sleep Disorders; Solid; Structural Racism; Training; United States; Validation; Work; Writing; administrative database; anti-racism; autism spectrum disorder; autistic children; barrier to care; clinical database; clinical diagnosis; design; epidemiology study; ethnic disparity; ethnic health disparity; ethnic minority; experience; hazard; health care availability; health care disparity; health care service; health care service utilization; health inequalities; improved; individuals with autism spectrum disorder; multidisciplinary; novel; professor; racial discrimination; racial disparity; racial minority; research study; responsible research conduct; service intervention; simulation; skills; systemic barrier; tenure track

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.

项目摘要 在美国，大约每44名儿童中就有1名被诊断患有自闭症谱系障碍（ASD）。许多 患有ASD的儿童由于在整个生命过程中的不利健康结果而经历降低的生活质量。 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，由于美国种族隔离和歧视的历史做法， 诊断和干预服务不公平。识别和诊断ASD儿童有助于 获得适当的服务，但在医疗保健服务的种族和民族差异造成许多非西班牙裔 患有ASD神经病学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 系统中，并在从这些临床数据库生成的研究中代表不足。即使这些 ASD诊断中的种族和民族差异是有据可查的，许多流行病学研究使用计费代码 算法和医疗保健数据库来检查关于ASD的病因学问题，通常不需要 考虑潜在的结构性偏差。因此，本论文的研究将探讨 ASD研究中的信息和选择偏差，以及硬膜外麻醉与 镇痛药使用和ASD。本论文的研究将致力于以下几个方面：（1）评估有效性 (i.e.,敏感性，预测值）的ASD诊断记录在医疗记录相比， 根据金标准临床评估得出的诊断（按儿童的种族和民族分层）;（2）使用 内部验证数据进行偏倚分析，以检查结果错误分类对 分娩期间硬膜外使用与ASD之间的关联;（3）进行Monte Carlo模拟，以评估 选择偏差对分娩期间使用硬膜外麻醉与ASD之间关联的影响。的数据 探索早期发育研究（SEED）是一项大型美国多中心病例对照研究，将用于进行 拟议的研究。在资助期内，奖学金申请人将实现以下目标：（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）获得以下方面的深入培训： 负责任的研究行为;（3）发展定量偏差分析方法的分析技能， 模拟研究;（4）增强专业和个人发展;以及（5）加深理解 儿童发展和自闭症谱系障碍的病因学。这些目标将允许申请人 在ASD的病因学，健康不公平和定量偏倚分析方法方面建立坚实的基础 通过额外的课程，研讨会，指导阅读，并与导师团队咨询。 此外，他们将为申请人提供实现终身教职目标所需的技能 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，以提高 少数种族和族裔的孕产妇和儿童健康结果。