PURPOSE: Children with language impairment (LI) often perform below the level of typically developing peers on measures of both processing speed and working memory. This study examined the relationship between these 2 types of measures and attempted to determine whether such measures can account for the LI itself. METHOD: Fourteen-year-old children with LI and their typically developing peers participated in a wide range of processing speed and working memory tasks and were administered a comprehensive language test battery. Confirmatory factor analyses were used to compare 3 nested models designed to examine the dimensionality of the speed and working memory measures. A model that included a general speed factor was also evaluated. RESULTS: The models meeting our evaluation criteria treated speed and working memory as separable factors. Furthermore, nonverbal as well as verbal processing factors emerged from these analyses. Latent variable regression analyses showed that each of the appropriate models accounted for 62% of the variance in the children's concurrent composite language test scores, with verbal working memory making the largest contribution. CONCLUSIONS: These findings shed light on the relationship among different types of processing and suggest that processing factors can contribute to the understanding of language disorders.
PURPOSE:Children with language impairment (LI) often perform below the level of typically developing peers on measures of both processing speed and working memory. This study examined the relationship between these 2 types of measures and attempted to determine whether such measures can account for the LI itself. METHOD: Fourteen-year-old children with LI and their typically developing peers participated in a wide range of processing speed and working memory tasks and were administered a comprehensive language test battery. Confirmatory factor analyses were used to compare 3 nested models designed to examine the dimensionality of the speed and working memory measures. A model that included a general speed factor was also evaluated. RESULTS: The models meeting our evaluation criteria treated speed and working memory as separable factors. Furthermore, nonverbal as well as verbal processing factors emerged from these analyses. Latent variable regression analyses showed that each of the appropriate models accounted for 62% of the variance in the children's concurrent composite language test scores, with verbal working memory making the largest contribution. CONCLUSIONS: These findings shed light on the relationship among different types of processing and suggest that processing factors can contribute to the understanding of language disorders.
Authors: Paola Colozzo; Ronald B Gillam; Megan Wood; Rebecca D Schnell; Judith R Johnston Journal: J Speech Lang Hear Res Date: 2011-09-19 Impact factor: 2.297
Authors: Anita M-Y Wong; Thomas Klee; Stephanie F Stokes; Paul Fletcher; Laurence B Leonard Journal: J Speech Lang Hear Res Date: 2010-06 Impact factor: 2.297
Authors: Natalya Kaganovich; Jennifer Schumaker; Laurence B Leonard; Dana Gustafson; Danielle Macias Journal: J Speech Lang Hear Res Date: 2014-08 Impact factor: 2.297