Suppr超能文献

2 岁儿童自闭症筛查:系统观察红旗在幼儿自闭症筛查工具中的应用。

Screening for Autism in 2-Year-Old Children: The Application of the Systematic Observation of Red Flags to the Screening Tool for Autism in Toddlers and Young Children.

机构信息

Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL.

Department of Special Education, The University of Texas at Austin.

出版信息

Am J Speech Lang Pathol. 2022 Nov 16;31(6):2759-2769. doi: 10.1044/2022_AJSLP-22-00132. Epub 2022 Oct 28.

Abstract

PURPOSE

A multimeasure approach was developed to capitalize on the strengths of two screening measures: the Screening Tool for Autism in Toddlers and Young Children (STAT), an observational measure of social communication, and the Systematic Observation of Red Flags (SORF), a checklist including restricted and repetitive behavior (RRB) items. This approach offers a novel method of identifying autism in toddlers.

METHOD

This was a retrospective study of data collected from a multidisciplinary diagnostic program for 24- to 36-month-olds with developmental delays. Raters with autism expertise but naïve to diagnoses applied the SORF to STAT videos. Psychometrics were derived for the SORF on STAT observations and a multiple-measure approach that used a Least Absolute Shrinkage and Selection Operator modeling framework to construct a STAT-SORF RRB Hybrid, retaining SORF RRB items based on individual predictive abilities.

RESULTS

The SORF alone correctly classified 84% of the sample (84% sensitivity and 86% specificity). The STAT-SORF RRB Hybrid model, which retained four SORF RRB items, correctly classified 90% of a validation sample (95% sensitivity and 75% specificity).

CONCLUSION

These findings highlight the potential utility of using multiple autism identification tools and regression-based scoring to establish presumptive eligibility and facilitate early access to autism interventions.

摘要

目的

开发了一种多指标方法,充分利用了两种筛查工具的优势:自闭症幼儿筛查工具(STAT),一种社交沟通的观察性评估工具,以及系统观察警示信号(SORF),一个包含受限和重复行为(RRB)项目的检查表。这种方法为幼儿自闭症的识别提供了一种新的方法。

方法

这是一项回顾性研究,数据来自一个针对 24 至 36 个月发育迟缓儿童的多学科诊断计划。具有自闭症专业知识但对诊断结果不了解的评估者将 SORF 应用于 STAT 视频。为 SORF 在 STAT 观察中的应用以及一种多指标方法推导了心理测量学,该方法使用最小绝对收缩和选择算子建模框架来构建 STAT-SORF RRB 混合模型,根据个体预测能力保留 SORF RRB 项目。

结果

单独的 SORF 正确分类了 84%的样本(84%的敏感性和 86%的特异性)。保留了四个 SORF RRB 项目的 STAT-SORF RRB 混合模型正确分类了验证样本的 90%(95%的敏感性和 75%的特异性)。

结论

这些发现强调了使用多种自闭症识别工具和基于回归的评分来确定疑似资格并促进早期获得自闭症干预的潜在效用。

相似文献

本文引用的文献

9
Caregiver Voices: Cross-Cultural Input on Improving Access to Autism Services.照顾者之声:改善自闭症服务获取途径的跨文化投入。
J Racial Ethn Health Disparities. 2019 Aug;6(4):752-773. doi: 10.1007/s40615-019-00575-y. Epub 2019 Mar 11.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验