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

Area of Science:

• Child language development
• Bilingualism and language acquisition
• Clinical linguistics and audiology

Background:

• Early identification of language impairment (LI) is crucial for clinical intervention and research, yet challenging for bilingual children.
• Parental questionnaires are valuable tools for gathering developmental information, but require efficient analysis for risk assessment.
• Existing methods for identifying at-risk bilingual children may not fully capture language proficiency nuances.

Purpose of the Study:

• To develop and validate automatic risk factor indices from parental questionnaire data for identifying children at risk for LI.
• To compare the effectiveness of different indices, varying in language proficiency weighting, for predicting language impairment.
• To assess the utility of these indices in clinical triage and research sampling of bilingual children.

Main Methods:

• Derived multiple risk factor indices using the Quantifying Bilingual Language Experience (Q-BEx) online questionnaire backend.
• Applied indices to two datasets of 5- to 8-year-old children: diagnosed developmental language disorder (DLD)/typical development (TD) and a mixed monolingual/bilingual group.
• Utilized Language Impairment Testing in Multilingual Settings (LITMUS) tools to assess language outcomes and developmental status.

Main Results:

• The RF4-min index, comprising four equally weighted factors including language proficiency, effectively separated bilingual children by developmental status.
• RF4-min demonstrated significant predictive value for language outcomes, outperforming indices with different proficiency weighting.
• This composite score offered a favorable balance of separability, sensitivity, and predictive accuracy.

Conclusions:

• The RF4-min index, derived automatically from Q-BEx data, shows significant promise for the initial screening of children at risk for language impairment.
• Its balanced approach to risk factors, including language proficiency, makes it a valuable tool for first-level triage.
• This automated index can improve the efficiency and accuracy of identifying children needing further language assessment.