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支持自闭症谱系障碍早期筛查的信息通信技术:一项系统综述。

Information and Communication Technologies to Support Early Screening of Autism Spectrum Disorder: A Systematic Review.

作者信息

Desideri Lorenzo, Pérez-Fuster Patricia, Herrera Gerardo

机构信息

AIAS Bologna Onlus, 40134 Bologna, Italy.

Autism and Technologies Laboratory, University Research Institute on Robotics and Information and Communication Technologies (IRTIC), Universitat de València, 46010 València, Spain.

出版信息

Children (Basel). 2021 Feb 1;8(2):93. doi: 10.3390/children8020093.

Abstract

 The aim of this systematic review is to identify recent digital technologies used to detect early signs of autism spectrum disorder (ASD) in preschool children (i.e., up to six years of age). A systematic literature search was performed for English language articles and conference papers indexed in Pubmed, PsycInfo, ERIC, CINAHL, WoS, IEEE, and ACM digital libraries up until January 2020. A follow-up search was conducted to cover the literature published until December 2020 for the usefulness and interest in this area of research during the Covid-19 emergency. In total, 2427 articles were initially retrieved from databases search. Additional 481 articles were retrieved from follow-up search. Finally, 28 articles met the inclusion criteria and were included in the review. The studies included involved four main interface modalities: Natural User Interface (e.g., eye trackers), PC or mobile, Wearable, and Robotics. Most of the papers included (n = 20) involved the use of Level 1 screening tools. Notwithstanding the variability of the solutions identified, psychometric information points to considering available technologies as promising supports in clinical practice to detect early sign of ASD in young children. Further research is needed to understand the acceptability and increase use rates of technology-based screenings in clinical settings.&nbsp.

摘要

本系统综述的目的是确定近期用于检测学龄前儿童(即六岁及以下)自闭症谱系障碍(ASD)早期迹象的数字技术。对截至2020年1月在Pubmed、PsycInfo、ERIC、CINAHL、WoS、IEEE和ACM数字图书馆中索引的英文文章和会议论文进行了系统的文献检索。进行了一次后续检索,以涵盖在2020年12月之前发表的关于新冠疫情期间该研究领域的实用性和关注度的文献。最初从数据库检索中总共获取了2427篇文章。从后续检索中又获取了481篇文章。最后,28篇文章符合纳入标准并被纳入综述。纳入的研究涉及四种主要的界面模式:自然用户界面(如眼动仪)、个人电脑或移动设备、可穿戴设备和机器人技术。大多数纳入的论文(n = 20)涉及使用一级筛查工具。尽管所确定的解决方案存在差异,但心理测量信息表明,可将现有技术视为临床实践中检测幼儿ASD早期迹象的有前景的支持手段。需要进一步研究以了解基于技术的筛查在临床环境中的可接受性并提高其使用率。

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