4.7 Article

Rapid Automatized Naming and Explicit Phonological Processing in Children With Developmental Dyslexia: A Study With Portuguese-Speaking Children in Brazil

Journal

FRONTIERS IN PSYCHOLOGY
Volume 11, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fpsyg.2020.00928

Keywords

developmental dyslexia; rapid automatized naming; explicit phonological processing; Brazilian Portuguese; classification and regression tree analysis

Funding

  1. Sao Paulo Research Foundation, FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo) [N 2015/22506-9, N 2018/09654-7]
  2. Brazilian National Council for Scientific and Technological Development, CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico) [N 311479/2015-4]

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Many studies have shown that children with reading difficulties present deficits in rapid automatized naming (RAN) and phonological awareness skills. The aim of this study was to examine RAN and explicit phonological processing in Brazilian Portuguese-speaking children with developmental dyslexia and to explore the ability of RAN to discriminate between children with and without dyslexia. Participants were 30 children with a clinical diagnosis of dyslexia established by the Brazilian Dyslexia Association and 30 children with typical development. Children were aged between 7 and 12, and groups were matched for chronological age and sex. They completed a battery of tests that are commonly used in Brazil for diagnosing dyslexia, consisting of the Wechsler Intelligence Test for Children (WISC-IV) as well as tests of single word and non-word reading, RAN, and the profile of phonological abilities test. Results indicate that the cognitive profile of this group of children, with a clinical diagnosis of dyslexia, showed preserved skills in the four subscales of the WISC-IV (verbal comprehension, perceptual reasoning, working memory, and processing speed) and on the profile of phonological abilities test. Groups significantly differed on the reading tests (word and non-word) and RAN measures, with medium to large effect sizes for RAN. Classification and regression tree analysis revealed that RAN was a good predictor for dyslexia diagnosis, with an overall classification accuracy rate of 88.33%.

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