The State of Natural Language Sampling in Autism Research: A Scoping Review.

Abstract

Background and aims: 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 can use language at a single moment in time, rather than how children actually 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?

Method: 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.

Main contribution: 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.

Conclusions: This review highlights the appropriate use of NLS across development in autism and makes recommendations for NLS future research.

Implications: 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.