Implementing the Get SET Early Model in a Community Setting to Lower the Age of ASD Diagnosis

在社区环境中实施“早期干预模式”以降低自闭症谱系障碍的诊断年龄

阅读:1

Abstract

OBJECTIVE: The objective of this study was to implement a validated, university-based early detection program, the Get SET Early model, in a community-based setting. Get SET was developed to improve Screening, Evaluation, and Treatment referral practices. Specifically, its purpose was to lower the age of diagnosis and enable toddlers with autism spectrum disorder (ASD) to begin treatment by 36 months. METHODS: One hundred nine pediatric health care providers were recruited to administer the Communication and Symbolic Behavior Scales Developmental Profile Infant-Toddler Checklist at 12-month, 18-month, and 24-month well-baby visits and referred toddlers whose scores indicated the need for a developmental evaluation. Licensed psychologists were trained to provide diagnostic evaluations to toddlers as young as 12 months. Mean age of diagnosis was compared with current population rates. RESULTS: In 4 years, 45,504 screens were administered at well-baby visits, and 648 children were evaluated at least 1 time. The overall median age for ASD diagnosis was 22 months, which is significantly lower than the median age reported by the CDC (57 months). For children screened at 12 months, the age of first diagnosis was significantly lower at 15 months. Of the 350 children who completed at least 1 follow-up evaluation, 323 were diagnosed with ASD or another delay, and 239 (74%) were enrolled in a treatment program. CONCLUSION: Toddlers with ASD were diagnosed nearly 3 years earlier than the most recent CDC report, which allowed children to start a treatment program by 36 months. Overall, Get SET Early was an effective strategy for improving the current approach to screening, evaluation, and treatment. Efforts to demonstrate sustainability are underway.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。