Charman Tony
Behavioural & Brain Sciences Unit, Institute of Child Health, 30 Guilford Street, London WC1N 1EH, United Kingdom.
J Autism Dev Disord. 2004 Feb;34(1):59-64. doi: 10.1023/b:jadd.0000018075.77941.60.
Earlier identification of children with autism spectrum disorders (ASDs) is welcome, but presents a number of challenges to the clinical and the research enterprises (see Charman & Baird [2002] for a review). In the research enterprise, one critical methodological challenge is the use of appropriate measures on which to match groups of preschoolers with ASDs to comparison groups with other neurodevelopmental conditions. Language and communication impairments are central to the diagnosis of ASD and, therefore, critical variables to consider in group-matched research designs. In the domain of language function the challenges include the very poor language competence of many preschoolers with ASDs, the fact that some early language competencies form part of the formal diagnostic criteria of ASD and diagnostic algorithms on research diagnostic instruments, the uneven profile of language competency in children with ASDs, and the difference between performance on measures of formal language competency in the testing situation and everyday language use. The current paper will review these challenges and suggest some possible approaches to overcome them, including using more than one measure of language ability and adopting a pragmatic approach to group composition and statistical analysis.
尽早识别患有自闭症谱系障碍(ASD)的儿童是值得欢迎的,但这给临床和研究工作带来了诸多挑战(详见Charman和Baird [2002]的综述)。在研究工作中,一个关键的方法学挑战是使用适当的测量方法,以便将患有ASD的学龄前儿童组与患有其他神经发育疾病的对照组进行匹配。语言和沟通障碍是ASD诊断的核心,因此也是在组间匹配研究设计中需要考虑的关键变量。在语言功能领域,挑战包括许多患有ASD的学龄前儿童语言能力非常差,一些早期语言能力构成了ASD正式诊断标准以及研究诊断工具上诊断算法的一部分,患有ASD的儿童语言能力分布不均衡,以及在测试情境中正式语言能力测量结果与日常语言使用之间的差异。本文将综述这些挑战,并提出一些可能的应对方法,包括使用多种语言能力测量方法,以及在组群构成和统计分析方面采用务实的方法。