Frontiers in pediatrics · 2026
Development and item selection of the language and dyslexia screening questionnaire in primary care settings.
СтатьяНазвание и аннотация: Перевод в очереди
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Restrepo M Adelaida, Risueño R J, Williams Jeffrey M, Gray Shelley, Allan Carla C, Khurana Nilam Patel, Carter Jodi, Keller Rebecca, Swartz Kathleen, Stull Terrence, Seltzer Ryan, Romeo Savannah H
Аннотация
PURPOSE: The study's purpose was to develop and select items for a caregiver-completed screening tool to assess children for dyslexia and developmental language disorder (DLD).
METHOD: Participants were recruited from community centers, schools and pediatric offices. Caregivers clicked a QR code on a flyer to access the consent and questionnaire, or contacted the research assistant to access them, and completed the screening measure designed to assess the risk of DLD and dyslexia. Then, children completed a gold-standard battery that included language, reading, phonological awareness, rapid naming, and memory measures.
RESULTS: Participants included 149 children and their caregivers. We used unadjusted logistic regressions to estimate the predictive value of each individual survey question for dyslexia, DLD, and typical development (TD) to retain questions at p < 0.05. Then, three stepwise logistic regressions were run to obtain a final, restricted model using the outcomes of dyslexia, DLD, and TD vs. any other diagnosis. Analyses indicated that the best-fitting model predicting TD vs. other groups in the combined sample included 14 items. The AUC for this set was 0.84. The specificity and sensitivity were 0.69 and 0.80, respectively. For the monolingual and bilingual samples separately, AUCs and sensitivity values were all greater than 0.80, and specificity values were 0.69 or above.
CONCLUSIONS: The findings indicate that the 14-item screener may effectively identify children at risk for dyslexia and DLD. Further validation, including the development and testing of additional items in a large, representative sample, is needed to establish its validity at the population level.
METHOD: Participants were recruited from community centers, schools and pediatric offices. Caregivers clicked a QR code on a flyer to access the consent and questionnaire, or contacted the research assistant to access them, and completed the screening measure designed to assess the risk of DLD and dyslexia. Then, children completed a gold-standard battery that included language, reading, phonological awareness, rapid naming, and memory measures.
RESULTS: Participants included 149 children and their caregivers. We used unadjusted logistic regressions to estimate the predictive value of each individual survey question for dyslexia, DLD, and typical development (TD) to retain questions at p < 0.05. Then, three stepwise logistic regressions were run to obtain a final, restricted model using the outcomes of dyslexia, DLD, and TD vs. any other diagnosis. Analyses indicated that the best-fitting model predicting TD vs. other groups in the combined sample included 14 items. The AUC for this set was 0.84. The specificity and sensitivity were 0.69 and 0.80, respectively. For the monolingual and bilingual samples separately, AUCs and sensitivity values were all greater than 0.80, and specificity values were 0.69 or above.
CONCLUSIONS: The findings indicate that the 14-item screener may effectively identify children at risk for dyslexia and DLD. Further validation, including the development and testing of additional items in a large, representative sample, is needed to establish its validity at the population level.