Towards equitable early identification of autism spectrum disorders in females

实现女性自闭症谱系障碍的公平早期识别

基本信息

批准号：
10722011
负责人：
Catherine Ann Burrows
金额：
$ 12.67万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-11 至 2026-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10722011
关键词：
Age Algorithms Assessment tool Brain Child Clinical Cohort Studies Communities Computer Models Data Data Collection Decision Trees Detection Development Diagnosis Diagnostic Dimensions Early Intervention Early identification Environment Equity Evaluation Factor Analysis Family Female Funding Future General Population Goals Heterogeneity Infrastructure Intervention Interview Knowledge Life Longevity Machine Learning Measurement Measures Medical Mental disorders Mentored Clinical Scientist Development Program Mentors Mentorship Methodology Methods Minnesota Modeling National Institute of Mental Health Outcome Parents Perception Performance Phase Positioning Attribute Primary Care Provider Psychologist Quality of life Questionnaires Registries Reporting Research Risk Sampling Screening procedure Sex Differences Signs and Symptoms Site Strategic Planning Subgroup Symptoms Testing Toddler Training Training Support Universities Visit Waiting Lists Work autism spectrum disorder autistic children career development clinical translation clinically actionable clinically relevant cohort community based participatory research disorder risk dissemination science early childhood early screening gender equity gradient boosting implementation science improved information gathering lens male novel pediatric department pediatrician precision medicine professor random forest recruit repetitive behavior screening service intervention sex skills social communication training opportunity trait translational research program

项目摘要

PROJECT SUMMARY/ABSTRACT Screening tools for autism spectrum disorder (ASD) show poor predictive performance in practice, particularly for females, which may arise due to sex-related measurement bias of screening questionnaires, and lack of precision in capturing the variability in early symptom profiles of ASD. Computational approaches to characterize heterogeneity and assess and account for sex-related measurement bias in early ASD symptoms may identify ASD risk profiles that can be clinically actionable in practice. The candidate's long-term goals are to enhance goals quality of life for children with ASD and their families by lowering the age of diagnosis, especially in females missed by traditional screening methods. The research and training described in this K23 application will build on the candidate's existing expertise, adding conceptual and methodological skills needed to develop and implement a novel screening approach that will more precisely identify ASD risk in a community-based sample. Aim 1 evaluates the extent of sex-based measurement bias in measures shown to capture clinically-relevant variability in early ASD traits in a sample of 3,000 children between 17-25 months recruited from a community research registry. Aim 2 applies computational approaches to model dimensional variability in early ASD symptoms and identify subgroups of risk in the same sample that are hypothesized to vary on clinical outcomes at 36 months. Aim 3 takes a dissemination and implementation (D&I) science lens to assess parent and provider views on screening practices to identify facilitators and barriers to change via qualitative interviews (Pediatrician N=20; Parent N=40). This project is in line with NIMH Strategic Plan Goal 2 to “examining mental illness trajectories across the lifespan.” The candidate is a clinical psychologist and Assistant Professor at the University of Minnesota, with expertise in characterizing sex differences in early ASD trajectories. The proposed K23 application will provide the candidate with the training needed to develop new knowledge and skills in conducting community-based screening for ASD, computational modeling of heterogeneity, and dissemination and implementation science. Mentors Dr. Damien Fair, Jed Elison, and Timothy Beebe possess the expertise and mentoring skills to support these training and scientific aims. This will position the candidate to build an independent clinical-translational research program focused on improving the precision of early screening for ASD to enable precision medicine for early ASD concerns that are equitable by sex. Training will occur in an exceptional scientific environment in the Department of Pediatrics at the University of Minnesota and the newly established Masonic Institute of the Developing Brain.

项目摘要/摘要自闭症谱系障碍（ASD）的筛查工具在实践中表现出差的预测性能，尤其是对于女性，这可能是由于与性别相关的筛查问卷的偏差而产生的，并且缺乏捕获ASD早期症状特征的可变性的精度。计算方法表征异质性和评估，并说明与性别相关的测量偏差早期ASD症状可以识别在实践中可以在临床上可起作用的ASD风险概况。候选人的长期目标是通过降低诊断年龄，为了提高患有ASD及其家人的儿童的目标质量，特别是在传统筛查方法错过的女性中。此K23中描述的研究和培训应用程序将基于候选人的现有专业知识，增加所需的概念和方法学技能开发和实施一种新颖的筛选方法，该方法将更准确地确定一个ASD风险基于社区的样本。 AIM 1评估在显示的测量中基于性别的测量偏差的程度在17-25个月之间的3,000名儿童样本中，捕获早期ASD特征的临床差异可变性从社区研究注册表中招募。 AIM 2应用计算方法来建模维度早期ASD符号的可变性，并确定同一样本中的风险亚组在36个月时的临床结果有所不同。 AIM 3采用传播和实施（D＆I）科学镜头评估父母和提供者对筛查实践的看法，以识别通过定性访谈（儿科医生n = 20；父n = 40）。该项目符合NIMH战略计划目标2 “检查整个生命周期的精神疾病轨迹”。候选人是临床心理学家，明尼苏达大学的助理教授，在早期的性别差异方面具有专业知识 ASD轨迹。拟议的K23申请将为候选人提供开发所需的培训对ASD进行基于社区的筛查的新知识和技能，计算建模异质性，传播和实施科学。导师Damien Fair博士，Jed Elison和蒂莫西·贝贝（Timothy Beebe）具有支持这些培训和科学目标的专业知识和心理技能。这将定位候选人建立一个独立的临床翻译研究计划，旨在改善 ASD早期筛查的精确度使早期ASD关注的精确医学是性行为公平。培训将在儿科系的特殊科学环境中进行明尼苏达大学和新成立的共济会发展中心。