# A narrative review of school-based screening tools for dyslexia among students

## TL;DR

This review looks at school-based tools for identifying dyslexia in children and finds many different tools are used, but there's inconsistency in how they're applied.

## Contribution

The study provides a comprehensive overview of dyslexia screening tools in schools and highlights gaps in socio-demographic data collection.

## Key findings

- 17 different school-based dyslexia screening tools were identified across 16 studies.
- Most studies used multiple screening tools concurrently, with an average of 3.7 tools per study.
- Socio-demographic data on gender and socio-economic status were often missing in the studies reviewed.

## Abstract

Early detection and intervention of dyslexia in children and young people (CYP) can help mitigate its negative impacts. Schools play a crucial role as a key point of contact for dyslexia screening.

In this review, we examined the range of screening tools and reported sensitivities and specificities in school settings to identify CYP with dyslexia and explored variations in how tools captured the socio-demographic characteristics of screened student's groups.

Narrative review.

We searched five electronic databases: EMBASE, MEDLINE, PsychInfo, Cochrane, and Scopus (2010–2023) to identify worldwide school-based dyslexia screening studies conducted in CYP aged 4–16 years. Three independent researchers screened the papers, and data were extracted on the sensitivity and specificity of the screening tools, the informants involved, the prevalence of dyslexia among those who screened positive, and the socio-demographic characteristics of the identified CYP.

Sixteen of 6,041 articles met the eligibility criteria. The study population ranged from 95 to 9,964 participants. We identified 17 different types of school-based dyslexia screening tools. Most studies combined screening tools (mean number of 3.7, standard deviation = 2.7) concurrently to identify dyslexia. Three studies used a staged approach of two and three stages. Developmental Dyslexia and Dysorthographia and Raven Progressive Matrices were the most used tools. The percentage of cases screening positive for dyslexia ranged from 3.1 to 33.0%. Among CYP identified by screening with dyslexia, there were missing socio-demographic data on gender (50%) and socio-economic status (81%) and none on ethnicity.

A variety of screening tools are used to identify children and young people (CYP) with dyslexia in school settings. However, it is unclear whether this wide range of tools is necessary or reflects variations in definitions. Greater collaboration between researchers and front-line educators could help establish a solid evidence base for screening and reduce the inconsistencies in approach. In the meantime, a practical and beneficial approach may involve starting with a highly sensitive screening tool, followed by more specific tests to assess detailed deficits and their impact.