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.

项目概要/摘要自闭症谱系障碍 (ASD) 的筛查工具在实践中表现出较差的预测性能，特别是对于女性，这可能是由于筛查问卷的性别相关测量偏差以及缺乏精确捕获 ASD 早期症状特征的计算方法。描述早期 ASD 症状的异质性并评估和解释与性别相关的测量偏差可以确定在实践中可以临床操作的 ASD 风险概况候选人的长期目标是。通过降低诊断年龄来提高自闭症谱系障碍儿童及其家人的生活质量，尤其是在传统筛查方法遗漏的女性中。本 K23 中描述的研究和培训。申请将建立在候选人现有的专业知识的基础上，增加所需的概念和方法技能开发和实施一种新颖的筛查方法，该方法将更准确地识别 ASD 风险目标 1 评估基于性别的测量偏差的程度捕获 3,000 名 17-25 个月内儿童样本中早期 ASD 特征的临床相关变异目标 2 将计算方法应用于模型维度。早期 ASD 症状的变异性，并确定同一样本中的风险亚组目标 3 采用传播和实施 (D&I) 科学视角来实现 36 个月时临床结果的变化。评估家长和提供者对筛查实践的看法，以确定变革的促进因素和障碍定性访谈（儿科医生 N=20；家长 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。”候选人是一名临床心理学家，并且明尼苏达大学助理教授，擅长描述早期性别差异拟议的 K23 应用程序将为候选人提供发展所需的培训。进行基于社区的 ASD 筛查、计算模型的新知识和技能异质性、传播和实施科学导师Damien Fair、Jed Elison 和。蒂莫西·毕比 (Timothy Beebe) 拥有支持这些培训和科学目标的专业知识和指导技能。将使候选人建立一个独立的临床转化研究项目，重点是改善自闭症谱系障碍 (ASD) 早期筛查的准确性，使精准医疗能够解决早期自闭症谱系障碍 (ASD) 问题培训将在儿科的特殊科学环境中进行，性别平等。明尼苏达大学和新成立的共济会大脑发育研究所。