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早期识别自闭症谱系障碍(ASD):在当地社区使用的策略。

Early Identification of Autism Spectrum Disorder (ASD): Strategies for Use in Local Communities.

机构信息

Autism Spectrum Center, Department of Neurology, Boston Children's Hospital, 2 Brookline Place, Brookline, MA, 02445, USA.

Division of Developmental and Behavioral Pediatrics, University of Massachusetts Chan Medical School, Worcester, MA, USA.

出版信息

Indian J Pediatr. 2023 Apr;90(4):377-386. doi: 10.1007/s12098-022-04172-6. Epub 2022 May 23.

Abstract

Early diagnosis of autism spectrum disorder (ASD) is essential for improved outcomes. There is a paucity of data on the prevalence of ASD in low- and middle-income countries (LMIC), but early identification may be further delayed in those communities. In this paper, recent studies on strategies for the early detection of ASD, and the prevalence of ASD in LMIC are reviewed. The limitations that can arise in the early identification of ASD in LMIC communities are discussed, and screening tools and strategies that can be helpful are identified. The goal is to recommend models that are culturally appropriate and scientifically valid, easily integrated within community settings while strengthening community systems and reducing disparities in the early identification of ASD. Starting locally by simplifying and demystifying the ASD identification process and building community connections will inform global researchers and policymakers while making a difference in the lives of the children and families affected by ASD.

摘要

自闭症谱系障碍(ASD)的早期诊断至关重要,可以改善预后。在中低收入国家(LMIC),ASD 的患病率数据很少,但在这些社区,早期识别可能会进一步延迟。本文回顾了最近关于 ASD 早期检测策略和 LMIC 中 ASD 患病率的研究。讨论了在 LMIC 社区中早期识别 ASD 可能出现的局限性,并确定了可能有帮助的筛查工具和策略。目标是推荐在文化上合适且科学上有效的模型,这些模型可以方便地整合到社区环境中,同时加强社区系统并减少 ASD 早期识别方面的差异。从简化和揭开 ASD 识别过程的神秘面纱并建立社区联系开始,从当地做起,将为全球研究人员和政策制定者提供信息,并改善受 ASD 影响的儿童和家庭的生活。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ccdb/10017576/baf581730fcb/12098_2022_4172_Fig1_HTML.jpg

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