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

Rinad Bakhti^1*Nishani Fonseka²Federica Amati³Dasha Elizabeth Nicholls¹Dougal Hargreaves³Antonio Lazzarino³Lucy McCan⁴Sara-Nicole Gardner¹Krishan Narayan⁵Helen Kerslake⁶Alex Weston⁷Shamini Gnani³

• ¹Imperial College London Department of Brain Sciences, London, United Kingdom
• ²Keele University Faculty of Medicine & Health Sciences, Keele, United Kingdom
• ³Imperial College London School of Public Health, London, United Kingdom
• ⁴Queen Mary University of London Wolfson Institute of Population Health, London, United Kingdom
• ⁵King's College London, London, United Kingdom
• ⁶Royal Borough of Kensington and Chelsea, London, United Kingdom
• ⁷Listen to Act, London, United Kingdom

Abstract Background 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. Objective 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. Design Narrative review Methods We searched five electronic databases: EMBASE, MEDLINE, PsychInfo, Cochrane, and Scopus (2010 to 2023) to identify worldwide school-based dyslexia screening studies conducted in CYP aged 4 to 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. Results Sixteen of 6041 articles met the eligibility criteria. The study population ranged from 95 to 9964 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 3.1-33.0%. 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. Conclusion 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.