Meta-analysis on language sample analysis for developmental language disorder in bilingual children

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American journal of speech-language pathology Published May 11, 2026 Medically reviewed May 11, 2026 Study authors: Ortiz José A, Chow Jason C, Nolasco Jessica M, Huang Yi Ting PubMed ↗ DOI ↗ By Dr. Sofia Müller, MD · Lifespan & Whole-Person Care

Key Takeaway

Consider language sample analysis as part of a broader assessment battery for developmental language disorder in bilingual children.

This is a meta-analysis examining the diagnostic accuracy of language sample analysis for identifying developmental language disorder in bilingual children. The authors synthesized findings on pooled sensitivity, which was 70%, and pooled specificity, which was 83%. The diagnostic accuracy range was described as poor to good. The analysis found that the elicitation language was not associated with variation in diagnostic accuracy, and integrated measures showed the highest diagnostic accuracy.

The authors note limitations, including variability in diagnostic accuracy across different language sample analysis metrics and that not all metrics perform with the same degree of precision. They emphasize that language sample analysis is best used as part of an assessment battery that includes multiple methods of measurement.

Practice relevance is restrained, with the authors advising against inferring that language sample analysis is a standalone diagnostic tool and against overstating the precision of any single metric. The evidence base has notable gaps, and the findings should be interpreted with caution.

Study Details

Study typeMeta analysis

EvidenceLevel 1

Follow-up84.0 mo

PublishedMay 2026

PMID41842702

View Original Abstract ↓

PURPOSE: Language sample analysis (LSA) is a common approach in the identification of developmental language disorder (DLD) in bilingual children. Because LSA is often recommended as a less biased assessment method, a better understanding of its diagnostic accuracy is needed to ensure appropriate decision making in clinical applications. This systematic review and meta-analysis synthesized the existing literature on the diagnostic accuracy of LSA in DLD identification for bilingual children. METHOD: We conducted a comprehensive literature search of electronic databases along with supplementary strategies and applied abstract and full-text screening procedures to identify eligible studies. We extracted relevant metrics from all studies to derive pooled estimates of sensitivity and specificity. We then conducted moderator analyses to examine the effect of elicitation language (first or second language) and the performance of integrated measures that included LSA with other methods as well as a risk of bias evaluation for each study. RESULTS: The search yielded nine articles that met the inclusion criteria. Studies included participants ranging from 2 to 7 years of age. Across studies, diagnostic accuracy in DLD identification ranged from poor to good. The pooled sensitivity was 70%, and the pooled specificity was 83%. Several LSA measures exhibited fair sensitivity and specificity, most of which consisted of combinations of multiple LSA metrics. Language of elicitation was not associated with variation in diagnostic accuracy. Integrated measures exhibited the highest diagnostic accuracy. DISCUSSION: LSA is a useful approach in the assessment of language for bilingual children, but the variability in diagnostic accuracy suggests that not all metrics may perform with the same degree of precision. Integrated measures, which include LSA along with other assessment methods, likely provide the most representative characterization of language ability. These results indicate that LSA is best used as part of an assessment battery that includes multiple methods of measurement. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.31592305.