The role of language in autism spectrum disorder (ASD), more specifically, its function in social communication and strong predictive power on future outcomes, warrants language assessments that have good psychometric properties that capture the heterogeneity of language ability found among diagnosed individuals. Given the rapid growth in intervention and treatment research, there is an urgent need for the development and implementation of outcome measures that are easily obtained and sensitive to change. In this commentary, we argue for the use of natural language samples as measures of expressive language and communication for this purpose and review the literature on their implementation in ASD research. Conceptual and measurement issues are discussed and future developments are outlined.
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Both authors conceived of the manuscript. Mihaela Barokova carried out the systematic review guided by HTF and drafted the manuscript. Both authors worked on revising successive drafts.
This paper was supported by a research grant from the Simons Foundation Autism Research Initiative, #383660, to Dr. Helen Tager-Flusberg.
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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Barokova, M., Tager-Flusberg, H. Commentary: Measuring Language Change Through Natural Language Samples. J Autism Dev Disord 50, 2287–2306 (2020). https://doi.org/10.1007/s10803-018-3628-4
- Outcome measures
- Natural language samples