Toward Digital Assessment of Developmental Dyslexia in Mainland China: Establishing Nationwide Norms With a GAMLSS Approach

Existing diagnosis instruments for developmental dyslexia (DD) in mainland China are limited in generalizability and typically rely on traditional norming approaches, which require large sample sizes to achieve precision. This study aims to develop and validate the Beijing Normal University Diagnostic Tool for Chinese Mandarin Developmental Dyslexia (BNU-DTCMDD), a DD diagnostic tool with regression-based norms for elementary school students in mainland China. A nationally representative sample of 3,782 first-to-sixth-grade students and a clinical sample of 84 first-to-sixth-grade students diagnosed with specific learning disabilities (SLD) were administered the BNU-DTCMDD, comprising six tasks that measure reading abilities and related cognitive skills. The tool demonstrated high internal consistency (Cronbach’s α .73–.99), good test–retest reliability (Pearson’s r .68–.99), good structural validity, and reasonable criterion validity (Cohen’s d 0.27–0.63). Norms were established using generalized additive models for location, scale, and shape (GAMLSS), yielding percentile curves and Z-scores. Based on the norms, the prevalence of DD was 6.08% in the normative sample and 73.81% in the clinical sample with SLD. The BNU-DTCMDD can diagnose DD in elementary school students in mainland China with good reliability and validity, and its regression-based norms overcome the statistical constraints of traditional norming and support timely diagnosis and intervention for DD.