Using the Quantifying Bilingual Language Experience Questionnaire to Identify Risk for Language Impairment in...

Clinical triage, but also inclusive population sampling in research, requires efficient detection of children likely to be at risk for language impairment (LI), a significant challenge in the case of bilingual children. Our goal was to derive automatic risk factor indices from a parental questionnaire and compare their usefulness in initial identification of children at risk for LI.

Alternative risk factor indices were derived from the Quantifying Bilingual Language Experience (Q-BEx) online questionnaire backend calculator, differing in the weight and detail given to language proficiency. Each index was applied to two data sets composed of 5- to 8-year-old children: one with independent diagnosis of developmental language disorder (DLD)/typical development (TD; 109 bilingual children tested in France) and one of largely all-comer children (278 bilingual and monolingual children tested in France, the Netherlands, and the United Kingdom). We compared how these alternative indices predicted (likely) DLD/TD status and structural language outcomes, assessed with Language Impairment Testing in Multilingual Settings tools, designed for bilingual children.

RF4-min, a risk factor index composed of four equally weighted components (age of first word, age of first sentence, early development concerns, and strongest speaking skills between the home/heritage language and the societal language), satisfactorily separated bilingual children according to developmental status and was a significant predictor of language outcomes. This composite score showed the best balance between separability, sensitivity, and predictive value compared to indices without a proficiency component or with a more heavily weighted/detailed proficiency component.

RF4-min, a Q-BEx automatically derived composite risk factor index, yielded promising results, indicating usefulness as part of first-level triage for LI.

https://doi.org/10.23641/asha.32080185.