Language ENvironment Analysis (LENA) in Phelan-McDermid Syndrome: Validity and Suggestions for Use in Minimally Verbal Children with Autism Spectrum Disorder View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-06

AUTHORS

Jacquelin Rankine, Erin Li, Stacey Lurie, Hillary Rieger, Emily Fourie, Paige M. Siper, A. Ting Wang, Joseph D. Buxbaum, Alexander Kolevzon

ABSTRACT

Phelan-McDermid syndrome (PMS) is a single-locus cause of developmental delay, autism spectrum disorder, and minimal verbal abilities. There is an urgent need to identify objective outcome measures of expressive language for use in this and other minimally verbal populations. One potential tool is an automated language processor called Language ENvironment Analysis (LENA). LENA was used to obtain over 542 h of audio in 18 children with PMS. LENA performance was adequate in a subset of children with PMS, specifically younger children and those with fewer stereotypic vocalizations. One LENA-derived language measure, Vocalization Ratio, had improved accuracy in this sample and may represent a novel expressive language measure for use in severely affected populations. More... »

PAGES

1605-1617

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10803-017-3082-8

    DOI

    http://dx.doi.org/10.1007/s10803-017-3082-8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1084026961

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28255759


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