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Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers

This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading) and integration of the various sub-components involved in reading (measured by Rapid Autom...

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Autores principales: Zoccolotti, Pierluigi, De Luca, Maria, Marinelli, Chiara V., Spinelli, Donatella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4235379/
https://www.ncbi.nlm.nih.gov/pubmed/25477856
http://dx.doi.org/10.3389/fpsyg.2014.01374
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author Zoccolotti, Pierluigi
De Luca, Maria
Marinelli, Chiara V.
Spinelli, Donatella
author_facet Zoccolotti, Pierluigi
De Luca, Maria
Marinelli, Chiara V.
Spinelli, Donatella
author_sort Zoccolotti, Pierluigi
collection PubMed
description This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading) and integration of the various sub-components involved in reading (measured by Rapid Automatized Naming, RAN). Subsequently, a third factor was added to the model, i.e., naming of discrete digits. In order to use homogeneous measures, all contributing variables considered the entire processing of the item, including pronunciation time. The model, which was based on commonality analysis, was applied to data from a group of 43 typically developing readers (11- to 13-year-olds) and a group of 25 chronologically matched dyslexic children. In typically developing readers, both orthographic decoding and integration of reading sub-components contributed significantly to the overall prediction of text reading fluency. The model prediction was higher (from ca. 37 to 52% of the explained variance) when we included the naming of discrete digits variable, which had a suppressive effect on pseudo-word reading. In the dyslexic readers, the variance explained by the two-factor model was high (69%) and did not change when the third factor was added. The lack of a suppression effect was likely due to the prominent individual differences in poor orthographic decoding of the dyslexic children. Analyses on data from both groups of children were replicated by using patches of colors as stimuli (both in the RAN task and in the discrete naming task) obtaining similar results. We conclude that it is possible to predict much of the variance in text-reading fluency using basic processes, such as orthographic decoding and integration of reading sub-components, even without taking into consideration higher-order linguistic factors such as lexical, semantic and contextual abilities. The approach validity of using proximal vs. distal causes to predict reading fluency is discussed.
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spelling pubmed-42353792014-12-04 Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers Zoccolotti, Pierluigi De Luca, Maria Marinelli, Chiara V. Spinelli, Donatella Front Psychol Psychology This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading) and integration of the various sub-components involved in reading (measured by Rapid Automatized Naming, RAN). Subsequently, a third factor was added to the model, i.e., naming of discrete digits. In order to use homogeneous measures, all contributing variables considered the entire processing of the item, including pronunciation time. The model, which was based on commonality analysis, was applied to data from a group of 43 typically developing readers (11- to 13-year-olds) and a group of 25 chronologically matched dyslexic children. In typically developing readers, both orthographic decoding and integration of reading sub-components contributed significantly to the overall prediction of text reading fluency. The model prediction was higher (from ca. 37 to 52% of the explained variance) when we included the naming of discrete digits variable, which had a suppressive effect on pseudo-word reading. In the dyslexic readers, the variance explained by the two-factor model was high (69%) and did not change when the third factor was added. The lack of a suppression effect was likely due to the prominent individual differences in poor orthographic decoding of the dyslexic children. Analyses on data from both groups of children were replicated by using patches of colors as stimuli (both in the RAN task and in the discrete naming task) obtaining similar results. We conclude that it is possible to predict much of the variance in text-reading fluency using basic processes, such as orthographic decoding and integration of reading sub-components, even without taking into consideration higher-order linguistic factors such as lexical, semantic and contextual abilities. The approach validity of using proximal vs. distal causes to predict reading fluency is discussed. Frontiers Media S.A. 2014-11-18 /pmc/articles/PMC4235379/ /pubmed/25477856 http://dx.doi.org/10.3389/fpsyg.2014.01374 Text en Copyright © 2014 Zoccolotti, De Luca, Marinelli and Spinelli. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Zoccolotti, Pierluigi
De Luca, Maria
Marinelli, Chiara V.
Spinelli, Donatella
Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers
title Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers
title_full Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers
title_fullStr Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers
title_full_unstemmed Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers
title_short Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers
title_sort modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4235379/
https://www.ncbi.nlm.nih.gov/pubmed/25477856
http://dx.doi.org/10.3389/fpsyg.2014.01374
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