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，大约四分之一的儿童被诊断患有自闭症谱系障碍 (ASD)。许多 患有自闭症谱系障碍 (ASD) 的儿童由于一生中健康状况不佳，生活质量下降。 早期诊断和干预服务对于改善自闭症谱系障碍患者的长期结果至关重要。 然而，由于美国历史上种族隔离和歧视的做法，早期获得 诊断和干预服务不公平。识别和诊断患有 ASD 的儿童有利于 获得适当的服务，但医疗保健服务中的种族和民族差异导致许多非西班牙裔人 患有 ASD 症状的黑人和西班牙裔儿童在医疗保健中得不到诊断和治疗 系统，并且在这些临床数据库生成的研究中代表性不足。尽管这些 ASD 诊断中的种族和民族差异有据可查，许多流行病学研究都使用帐单代码 算法和医疗保健数据库来检查 ASD 的病因学问题，通常没有必要 考虑潜在的结构性偏差。因此，本论文研究将探讨 自闭症谱系障碍 (ASD) 研究的信息和选择偏差，以及硬膜外麻醉与 镇痛使用和自闭症谱系障碍 (ASD)。论文研究将解决以下具体目标：（1）评估有效性 与病历中记录的 ASD 诊断（即敏感性、预测值）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)用途 内部验证数据进行偏差分析，以检查结果错误分类对结果的影响 分娩期间使用硬膜外麻醉与自闭症谱系障碍 (ASD) 之间的关联； (3) 进行蒙特卡洛模拟来评估 选择偏差对分娩期间硬膜外使用与 ASD 之间关联的影响。数据来自 探索早期发展研究 (SEED) 是一项大型美国多中心病例对照研究，将用于开展 拟议的研究。在资助期间，奖学金申请者将实现以下目标：（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) 获得深入的培训 负责任地进行研究； (3) 培养定量偏差分析方法的分析技能 模拟研究； (4) 促进专业和个人发展； (5) 形成深刻的理解 儿童发展和自闭症谱系障碍的病因学。这些目标将使申请人能够 为自闭症谱系障碍的病因学、健康不平等和定量偏差分析方法奠定坚实的基础 通过额外的课程、研讨会、指导阅读以及与导师团队的协商。 此外，他们还将为申请人提供实现成为终身教授的目标所需的技能 教授致力于弥合流行病学研究和公共卫生实践之间的差距，以改善 少数种族和族裔的孕产妇和儿童健康状况。