Plate Samantha N
Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
Autism Dev Lang Impair. 2025 May 23;10:23969415251341247. doi: 10.1177/23969415251341247. eCollection 2025 Jan-Dec.
Caregiver reports and standardized assessments have been the primary methods used to study language development in autism. However, these forms of measurement are often coarse, complicated by floor effects and reporter bias, and limited by the fact that they only capture how children use language at a single moment in time, rather than how children use language during everyday interactions. These limitations have led to recent calls for the use of natural language sampling (NLS) as a fine-grained, developmentally appropriate, and contextually relevant measure of everyday communication. The number of studies using NLS to study language in autism has increased substantially in the last 15 years, resulting in a wide array of sampling methods and measures. Given both the increasing prevalence of NLS methods in the autism literature and the variability in sampling approaches and measures, this scoping review addresses the following questions: 1. What populations have been studied using NLS?2. Which data collection methods are most prevalent in NLS research?3. How are measures of language derived from NLS?
Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a search for studies published in the last 15 years across three databases was conducted. After removing duplicates, 4,671 titles and abstracts were screened and 59 papers met inclusion criteria. Sample characteristics, natural language collection methods, and derived measures were extracted and tabled for each study. The most prevalent NLS methods and measures in autism language research are reviewed and the benefits and drawbacks of various methods are discussed.
This scoping review highlights subgroups of the autistic population that have been underrepresented in NLS studies-in particular, minimally/nonspeaking school-aged autistic children. This article also examines means to collect a "naturalistic" sample of language. Notably, studies did not address whether autistic children exhibit different social communication skills when talking to different types of social partners. Broadly, research has underreported key methodological details, making comparisons across studies difficult.
This review highlights the appropriate use of NLS across development in autism and makes recommendations for NLS future research.
Additional work is needed to address the gaps described in this article and replicate previous findings to identify patterns of natural language across the literature.
照顾者报告和标准化评估一直是研究自闭症语言发展的主要方法。然而，这些测量形式往往较为粗略，受到地板效应和报告者偏差的影响，并且由于它们仅能捕捉儿童在某一时刻的语言使用情况，而非日常互动中的语言使用方式，因而存在局限性。这些局限性促使近期有人呼吁使用自然语言抽样（NLS）作为一种针对日常交流的精细、符合发展阶段且与情境相关的测量方法。在过去15年中，使用NLS研究自闭症语言的研究数量大幅增加，产生了各种各样的抽样方法和测量手段。鉴于NLS方法在自闭症文献中的使用日益普遍，且抽样方法和测量手段存在差异，本综述探讨以下问题：1. 哪些人群使用NLS进行了研究？2. NLS研究中最普遍的数据收集方法有哪些？3. 如何从NLS中得出语言测量结果？
按照系统评价和荟萃分析的首选报告项目指南，对过去15年在三个数据库中发表的研究进行检索。去除重复项后，筛选了4671篇标题和摘要，59篇论文符合纳入标准。提取每项研究的样本特征、自然语言收集方法和派生测量指标，并制成表格。对自闭症语言研究中最普遍的NLS方法和测量指标进行综述，并讨论各种方法的优缺点。
本综述强调了NLS研究中代表性不足的自闭症亚群体——特别是极少/不说话的学龄自闭症儿童。本文还研究了收集“自然主义”语言样本的方法。值得注意的是，研究未涉及自闭症儿童与不同类型社交伙伴交谈时是否表现出不同的社交沟通技巧。总体而言，研究对关键方法细节的报道不足，使得跨研究比较变得困难。
本综述强调了NLS在自闭症各发展阶段的恰当应用，并为NLS未来研究提出建议。
需要开展更多工作来填补本文所述的空白，并重复先前的研究结果，以确定整个文献中的自然语言模式。
