The participants in this study included 74 Spanish-English bilingual children with (n = 36) and without (n = 38) DLD. Language samples were elicited through a story retell and story generation task using Frog wordless picture books in English and Spanish. Stories were transcribed and coded using the Systematic Analysis of Language Samples (Miller & Iglesias, 2020) to extract MLUw and PGU in both languages.
Logistic regression analyses suggested that a model that included PGU, MLUw, and age achieved the best diagnostic accuracy in predicting group membership. Both approaches, best language and total language, had fair diagnostic accuracy.
In combination, PGU and MLUw seem to be useful diagnostic tools to differentiate bilingual children with and without DLD. Clinical implications and usability are discussed.
■这项研究的参与者包括74名有(n=36)和没有(n=38)DLD的西班牙语-英语双语儿童。语言样本是通过使用英语和西班牙语的青蛙无语图画书进行故事复述和故事生成任务得出的。使用语言样本的系统分析(Miller&Iglesias,2020)以两种语言提取MLUw和PGU。
■Logistic回归分析表明,包含PGU的模型,MLUw,和年龄在预测组成员资格方面取得了最好的诊断准确性。两种方法,最好的语言和全面的语言,具有相当的诊断准确性。
■组合,PGU和MLUw似乎是区分有和没有DLD的双语儿童的有用诊断工具。讨论了临床意义和可用性。