Language Sample Analysis in Bilingual Children: A Meta-Analysis of Diagnostic Accuracy

Area of Science:

• Speech and Language Pathology
• Developmental Psychology
• Pediatric Clinical Assessment

Background:

• Language sample analysis (LSA) is frequently used to identify developmental language disorder (DLD) in bilingual children.
• LSA is considered a less biased method, but its diagnostic accuracy requires further understanding for clinical application.
• This study addresses the need for clarity on LSA's effectiveness in bilingual DLD identification.

Purpose of the Study:

• To systematically review and meta-analyze the diagnostic accuracy of LSA for identifying DLD in bilingual children.
• To evaluate the influence of elicitation language and integrated measures on LSA's diagnostic performance.
• To assess the risk of bias in existing studies on LSA for DLD in bilingual populations.

Main Methods:

• A comprehensive literature search was conducted across electronic databases and supplementary sources.
• Eligible studies underwent abstract and full-text screening.
• Pooled estimates of sensitivity and specificity were calculated, with moderator and risk of bias analyses performed.

Main Results:

• Nine studies met the inclusion criteria, involving children aged 2–7 years.
• Pooled sensitivity for DLD identification was 70%, and pooled specificity was 83%.
• Integrated measures demonstrated the highest diagnostic accuracy, while elicitation language did not significantly impact results.

Conclusions:

• Language sample analysis (LSA) is a valuable tool for assessing bilingual children but shows variability in precision.
• Integrated assessment approaches, combining LSA with other methods, provide a more comprehensive evaluation of language ability.
• LSA should be utilized as part of a multi-method assessment battery for robust language evaluation.