Background: Analyses from the Jyväskylä Longitudinal Study of Dyslexia project show that the key childhood predictors (phonological awareness, short-term memory, rapid naming, expressive vocabulary, pseudoword repetition, and letter naming) of dyslexia differentiate the group with reading disability (n ¼ 46) and the group without reading problems (n ¼ 152) at the end of the 2nd grade. These measures were employed at the ages of 3.5, 4.5 and 5.5 years and information regarding the familial risk of dyslexia was used to find the most sensitive indices of an individual child's risk for reading disability. Methods: Age-specific and across-age logistic regression models were constructed to produce the risk indices. The predictive ability of the risk indices was explored using the ROC (receiver operating curve) plot. Information from the logistic models was further utilised in illustrating the risk with probability curve presentations. Results: The logistic regression models with familial risk, letter knowledge, phonological awareness and RAN provided a prediction probability above .80 (area under ROC). Conclusions: The models including familial risk status and the three above-mentioned measures offer a rough screening procedure for estimating an individual child's risk for reading disability at the age of 3.5 years. Probability curves are presented as a method of illustrating the risk.
Lyytinen, H. (2010). Language development, literacy skills and predictive connections to reading in Finnish children with and without familial risk for dyslexia. Journal of Learning Disabilities, 43 (4), 308-321. http://dx
This study examined whether counting and rapid automatized naming (RAN) could operate as significant predictors of both later arithmetic calculation and reading fluency. The authors also took an important step to clarify the cognitive mechanisms underlying these predictive relationships by controlling for the effect of phonological awareness and verbal short-term memory. Due to rather strong covariance between verbal short-term memory and phonological awareness, short-term memory could be controlled only partially. Participants, 200 children from a longitudinal study, were followed from age 5 to 10 years. Structural equation modeling showed counting to be a strong predictor, not only of later calculation but also of reading fluency. Similarly, RAN predicted later calculation as well as reading fluency. These results indicated that counting and RAN were not skill-speciflc predictors. Phonological awareness explained part of counting and RAN. However, the predictive effects of these 2 skills on calculation and reading remained even after phonological awareness and partially for verbal short-term memory were controlled. Thus, further exploration of other cognitive processes underlying these 2 abilities is needed.
Children at risk for familial dyslexia (n = 107) and their controls (n = 93) have been followed from birth to school entry in the Jyvaskyla Longitudinal study of Dyslexia (JLD) on developmental factors linked to reading and dyslexia. At the point of school entry, the majority of the at-risk children displayed decoding ability that fell at least 1 SD below the mean of the control group. Measures of speech processing were the earliest indices to show both group differences in infancy and also significant predictive associations with reading acquisition. A number of measures of language, including phonological and morphological skill collected repeatedly from age three, revealed group differences and predictive correlations. Both the group differences and the predictive associations to later language and reading ability strengthened as a function of increasing age. The predictions, however, tend to be stronger and the spectrum of significant correlations wider in the at-risk group. These results are crucial to early identification and intervention of dyslexia in at-risk children.
The authors examined the developmental trajectories of children's early letter knowledge in relation to measures spanning and encompassing their prior language-related and cognitive measures and environmental factors and their subsequent Grade 1 reading achievement. Letter knowledge was assessed longitudinally at ages 4.5, 5.0, 5.5, and 6.5 years; earlier language skills and environmental factors were assessed at ages 3.5 and 4.5 years; and reading achievement was assessed at the beginning and end of Grade 1. The analyses were conducted on a longitudinal data set involving children with and without familial risk for dyslexia. Emerging from the trajectory analysis of letter knowledge were 3 separate clusters: delayed (n = 63), linearly growing (n = 73), and precocious (n = 51). The members of the delayed cluster were predominantly children with familial risk for dyslexia, and the members of the precocious cluster were predominantly control group children. Phonological sensitivity, phonological memory, and rapid naming skills predicted delayed letter knowledge. Environmental predictors included level of maternal education and the amount of letter name teaching. Familial risk for dyslexia made a significant contribution to the predictive relations. Membership in the delayed cluster predicted poor reading performance at Grade 1.
The authors examined second grade reading accuracy and fluency and their associations via letter knowledge to phonological and language predictors assessed at 3.5, 4.5, and 5.5 years in children in the Jyväskylä Longitudinal Study of Dyslexia. Structural equation modeling showed that a developmentally highly stable factor (early phonological and language processing [EPLP]) behind key dyslexia predictors (i.e., phonological awareness, short-term memory, rapid naming, vocabulary, and pseudoword repetition) could already be identified at 3.5 years. EPLP was significantly associated with reading and spelling accuracy and by age with letter knowledge. However, EPLP had only a minor link with reading fluency, which was additionally explained by early letter knowledge. The results show that reading accuracy is well predicted by early phonological and language skills. Variation in fluent reading skills is not well explained by early skills, suggesting factors other than phonological core skills. Future research is suggested to explore the factors behind the development of fast and accurate decoding skills.
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