Statistical invisibility of Developmental Language Disorder in Castilla-La Mancha (2006-2024): A descriptive-analytical study
DOI:
https://doi.org/10.55040/k01w7q33Keywords:
Developmental Language Disorder, Language Impairments, Educational Statistics, Early Childhood Education, Primary EducationAbstract
Developmental Language Disorder is a common neurodevelopmental condition that affects learning and emotional well-being. Its educational response requires comparable information and consistent administrative criteria.
The aim of this study is to document the statistical visibility of Developmental Language Disorder in Castilla-La Mancha between the 2006/07 and 2023/24 school years, analyzing how records of special educational support needs in Early Childhood and Primary Education count students with profiles compatible with this disorder, delineating the statistical space they occupy, and contrasting these figures with expected prevalence rates.
A descriptive–analytical time-series study was conducted using reports from the Regional Ministry of Education, harmonizing language-related labels and analyzing the evolution of the administrative category by school year, educational stage, sex, and province when the annual report provided such disaggregations.
The results show that the label Developmental Language Disorder does not appear in any school year; students with compatible profiles are grouped under generic categories of language disorders. These categories remain quantitatively substantial, but clearly below expected prevalence rates, with male overrepresentation, identification mainly at the start of Primary Education, and significant territorial gradients across provinces.
Finally, the absence of the explicit Developmental Language Disorder label in Castilla-La Mancha’s records creates a structural statistical invisibility that limits support planning, policy evaluation, and comparison with other education systems. We propose explicitly incorporating the Developmental Language Disorder label into the regional classification, standardizing recording criteria, and linking data to resource decisions such as early screening, language support interventions, and longitudinal follow-up.
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