Review of methods for conducting speech research with minimally verbal individuals with autism spectrum disorder.
Karen V Chenausky, Marc Maffei, Helen Tager-Flusberg and 1 others
PMID 36345836WHAT IT FOUND
This review outlines how to collect and analyze speech data from minimally verbal children with autism.
It compares natural language samples, repetition tasks, and acoustic measures, offering practical guidance on choosing methods that yield reliable data for clinical or research use.
Key findings
01Natural language samples offer high ecological validity but may produce insufficient data for children with extremely limited vocal output.
02Speech and nonspeech repetition tasks are viable alternatives that can yield useful information for children who do not produce much spontaneous speech.
03Perceptual analyses are more common in clinical settings but are subject to bias, whereas acoustic analyses are more fine-grained and likely more useful for research purposes.
STILL TO COME
How it was doneWhat they foundWhat it means for SLPs
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What it does not show
This is a narrative review, not a systematic review or meta-analysis, so it does not provide a comprehensive or unbiased survey of all available evidence. The paper focuses on methods for research and clinical assessment but does not report efficacy data for any specific intervention. Guidance is based on existing literature and author expertise; it does not present new empirical validation of the recommended protocols.
Declared interests
No potential conflict of interest was reported by the author(s).
The easy way to misread this
Do not interpret this paper as evidence that any specific assessment tool or analysis method is superior for all clinical situations. The authors explicitly state that the choice of method depends on the specific research or clinical question, and no single approach is universally recommended.