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A meta-analysis of the predictability of LENA™ automated measures for child language development
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In: Dev Rev (2020)
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Abstract:
Early language environment plays a critical role in child language development. The Language ENvironment Analysis (LENA™) system allows researchers and clinicians to collect daylong recordings and obtain automated measures to characterize a child’s language environment. This meta-analysis evaluates the predictability of LENA’s automated measures for language skills in young children. We systematically searched reports for associations between LENA’s automated measures, specifically, adult word count (AWC), conversational turn count (CTC), and child vocalization count (CVC), and language skills in children younger than 48 months. Using robust variance estimation, we calculated weighted mean effect sizes and conducted moderator analyses exploring the factors that might affect this relationship. The results revealed an overall medium effect size for the correlation between LENA’s automated measures and language skills. This relationship was largely consistent regardless of child developmental status, publication status, language assessment modality and method, or the age at which the LENA recording was taken; however, the effect was weakly moderated by the gap between LENA recordings and language measures taken. Among the three measures, there were medium associations between CTC and CVC and language, whereas there was a small-to-medium association between AWC and language. These findings extend beyond validation work conducted by the LENA Research Foundation and suggest certain predictive strength of LENA’s automated measures for child language. We discussed possible mechanisms underlying the observed associations, as well as the theoretical, methodological, and clinical implications of these findings.
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Keyword:
Article
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URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337141/
http://www.ncbi.nlm.nih.gov/pubmed/32632339
https://doi.org/10.1016/j.dr.2020.100921
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Statistical distributions of consonant variants in infant-directed speech: evidence that /t/ may be exceptional
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In: J Phon (2019)
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Novel Word Learning at 21 Months Predicts Receptive Vocabulary Outcomes in Later Childhood
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In: J Child Lang (2019)
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Attention to speech, speech perception, and referential learning
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In: Appl Psycholinguist (2018)
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Attention to speech and spoken language development in deaf children with cochlear implants: A ten-year longitudinal study
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How Does Aging Affect Recognition of Spectrally Degraded Speech?
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Hearing versus Listening: Attention to Speech and Its Role in Language Acquisition in Deaf Infants with Cochlear Implants
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Language Processing in Children with Cochlear Implants: A Preliminary Report on Lexical Access for Production and Comprehension
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The Ear Is Connected to the Brain: Some New Directions in the Study of Children with Cochlear Implants at Indiana University
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Effects of early auditory experience on word learning and speech perception in deaf children with cochlear implants: Implications for sensitive periods of language development
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Effects of congenital hearing loss and cochlear implantation on audiovisual speech perception in infants and children
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Speech perception skills of deaf infants following cochlear implantation: a first report
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Development of Pre-Word-Learning Skills in Infants with Cochlear Implants
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