Purpose: Accurate identification of developmental language disorder (DLD) remains challenging, particularly for children who speak different dialects, languages, or more than 1 language. Children with DLD, on average, have shown subtle deficits on nonlinguistic cognitive processing tasks, and performance on such tasks may be minimally influenced by language experience. This study explores whether nonlinguistic cognitive processing tasks can contribute to the identification of DLD in children from diverse linguistic backgrounds. Method: Study 1 combined data from 4 U.S.-based investigations to yield a sample of 395 children, ages 6- 10 years, who spoke only English or both Spanish and English. Study 2 consisted of an international sample of 55 kindergarten children living in Vietnam. Each study included children with DLD and children with typical development. Participants completed nonlinguistic cognitive tasks of processing speed, auditory working memory, and attentional control. Data analysis compared typically developing to DLD groups by age and language background. Then, we empirically derived cut-points to report diagnostic accuracy (sensitivity, specificity, and positive and negative likelihood ratios). Results: For all 3 tasks, adequate sensitivity or specificity (but not both in most cases) was achieved in nearly all age groups. Likelihood ratios reached moderately to very informative levels in several instances. Diagnostic results were maintained when monolingual and bilingual samples were combined into a single group. Conclusions: Nonlinguistic cognitive processing tasks may contribute to accurate identification of DLD in combination with other measures. Further research is needed to refine tasks, confirm cut-points established here, and extend findings to children from additional language backgrounds.
|Original language||English (US)|
|Number of pages||13|
|Journal||American journal of speech-language pathology|
|State||Published - Aug 9 2019|
Bibliographical noteFunding Information:
Funding sources for the data analyzed in this study include National Institutes of Health Awards R01DC004437 (J. Windsor), R03DC004442 (K. Kohnert), R21HD053222 (J. Windsor), R21DC010868 (K. Kohnert), R03DC013760 (K. Ebert), and K23DC014750 (G. Pham). Portions of this database were collected with support from the University of Minnesota. We thank Kathryn Kohnert and Jennifer Windsor for access to data, and we are grateful to the many research staff and participants in the studies considered here.
© 2019 American 1000 Speech-Language-Hearing Association.