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

> **NIH NIH R56** · UNIVERSITY OF ARIZONA · 2021 · $634,465

## 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 children extract word
meaning and grammatical structure from the distributional information contained in the language input they
receive and accounts for rapid implicit language learning. The proposed studies take an experimental approach
in which 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 their very limited number of vocabulary words
that they know and use. Preschool children with Developmental Language Disorder (ages 4-5 years) show
marked deficits in the use of grammatical morphemes. We will directly address the issue of non-responders (i.e.,
children who make limited improvement despite treatment that is effective for others), a problem inherent to all
treatment research. We leverage our previous findings to predict early in the treatment process which children
are highly likely to be non-responders and propose an alternative treatment method that might be better suited
to 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:** 10412433
- **Project number:** 2R56DC015642-06
- **Recipient organization:** UNIVERSITY OF ARIZONA
- **Principal Investigator:** MARY ALT
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $634,465
- **Award type:** 2
- **Project period:** 2016-07-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10412433

## Citation

> US National Institutes of Health, RePORTER application 10412433, Identification of treatment parameters that maximize language treatment efficacy for children. (2R56DC015642-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10412433. Licensed CC0.

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