Identification of treatment parameters that maximize language treatment efficacy for children.

NIH RePORTER · NIH · R01 · $641,329 · view on reporter.nih.gov ↗

Abstract

Abstract Poor language skills are associated with numerous negative outcomes ranging from higher rates of tantrums and difficulty developing friendships to school failure, contact with the justice system, and increased victimization. Although language deficits may be noticed as early as toddlerhood, effective treatment may not begin this early and there is relatively little time to close the language gap before these children are faced with the increased language demands of formal education and the cumulative effects of academic struggle. For the 7-13% of children with impaired language skills, language treatments that are faster and more effective are urgently needed. This competing renewal addresses this need with a series of studies that translate basic research in statistical learning to treatment contexts. The Statistical Learning Framework posits learners extract word meaning and grammatical structure from the language input they receive, and the statistical structure of the input accounts for rapid, implicit language learning. Six proposed studies translate statistical learning principles to a treatment context. Theoretically-motivated treatment factors are tested in two groups of children with poor language skills. “Late Talkers” are children (ages 2-3 years) who are identified by the very limited number of vocabulary words that they understand and use. Preschool children with Developmental Language Disorder (ages 4-5 years) show marked deficits in the use of grammatical morphemes. Parallel studies targeting vocabulary treatment (for Late Talkers) and morphosyntax treatment (for children with DLD) will test whether leveraging prior learning can improve treatment methods by making learning faster and more effective. We will also directly address the issue of non-responders (i.e., children who make limited improvement despite treatment that is effective for others), an unaddressed problem inherent to all treatment research. We leverage our previous findings to predict which children are highly likely to be non-responders and propose alternative treatment methods that might assist this subset of children. These studies represent the necessary work for principled language treatment that is supported by evidence, and can provide insights into the nature of learning in a range of children with poor language skills.

Key facts

NIH application ID
10584512
Project number
5R01DC015642-07
Recipient
UNIVERSITY OF ARIZONA
Principal Investigator
MARY ALT
Activity code
R01
Funding institute
NIH
Fiscal year
2023
Award amount
$641,329
Award type
5
Project period
2016-07-01 → 2027-08-31