Purpose This study investigated methodological and theoretical aspects of using mean length of utterance (MLU) and its alternatives in cross-linguistic research and, in particular, its applicability to Russian—a language with a rich system of grammatical and derivational morphemes. Method We collected audio recordings of spontaneous speech samples from 27 Russian-speaking children aged between 2;9 and 5;7 (years;months) over individual play sessions. For each participant, we transcribed the first 100 complete utterances and coded them for several types of utterance length measurements, including length in morphemes (grammatical and derivational), words, and syllables. At a sample level, we calculated the average number of produced unique grammatical forms, getting an alternative quantitative estimate of children's morphosyntactic abilities. Results A combination of Pearson correlation analysis and Bland–Altman difference plots established that MLU can be reliably used in Russian-speaking children aged around 3;0. The average number of unique grammatical forms remains a sensitive measurement of language capabilities even in older children aged over 3;6. Two quantitative measurements, MLU in syllables and morphemes, show good agreement, suggesting that these measurements can be used interchangeably across studies. Sample size analysis revealed that samples under 75 utterances do not provide sufficient reliability for estimating a child's MLU. Conclusions This article demonstrated that MLU can be used in young Russian-speaking children under 3;0–3;6. Also, we showed that the classical morpheme calculation approach can be substituted with counting syllables, which is more time efficient in the absence of automated parsers and is potentially more appropriate for some (e.g., polysynthetic) languages. Our proposed alternative to MLU—the average number of grammatical forms in a sample—appears to be a more sensitive measurement of language capabilities even in older children.
Background: The important role of phonological processing for reading has been demonstrated by many studies. The purpose of this research was to investigate the role of phonological processing for reading in Russian. Specifically, we tested whether the overall complexity of a phonological task predicts reading fluency and reading comprehension. Method: We used seven phonological tests ranked according to the number of linguistic processes involved in each task. We examined the relative difficulty of the tests and the relationship between phonological processing and reading skills (reading fluency and comprehension of simpler and more difficult texts) in 90 typically developing 7 to 11 years-of-age Russian-speaking children.
Purpose: The main purpose of this study was to investigate whether the performance on each of seven phonological processing (PP) tests from the Russian Test of Phonological Processing (RuToPP), with their varying levels of linguistic complexity and composite phonological indices, are significant predictors of developmental dyslexia (DD) and can reliably differentiate children with and without reading impairment. Additionally, we examined the general contribution of phonological skills to text reading fluency in children with various levels of reading performance. Method: A total of 173 Russian-speaking 7- to 11-year-old children participated in this study: 124 who were typically developing (TD) and 49 who had been diagnosed with DD. We assessed reading fluency with a standardized reading test and PP with the RuToPP. We investigated the potential of phonological skills to predict the presence or absence of a dyslexia diagnosis using multinomial logistic regression, receiver operating characteristic (ROC) curve analysis, and calculations of the sensitivity and specificity of each test and index. The contribution of phonological skills to reading fluency was also assessed in a mixed group of children. Results: Six of seven RuToPP tests were significant predictors of dyslexia. However, while the RuToPP correctly identified 93%–99% of TD children, for children with dyslexia, it ranged from 4% to 47% depending on the test. In a mixed group of children with and without dyslexia, performance in the more complex phonological tests was a stronger predictor of reading fluency. Conclusions: Our findings are consistent with the literature on predictors of literacy skills and dyslexia while uniquely demonstrating the impact of the complexity level of the phonological tests on the classification outcome. PP is a significant and necessary predictor of reading skills, but it is not sufficient for diagnostic purposes. Supplemental Material: https://doi.org/10.23641/asha.20779294
This work is a comprehensive cross-methodological experimental study of phonological processing disorders in dyslexic Russian-speaking children. We developed and standardized a Russian-language test battery to assess phonological processing skills (The Russian Test of Phonological Processing), wich we then used to assess the features of phonological deficits in children with dyslexia and conduct an analysis of reading difficulties and their structural brain correlates using modern methods of videooculography and neuroimaging. The first phase’s findings revealed that more complex phonological tests were also more difficult, whereas children’s performance in these tests was found to be a significant predictor of reading speed. The project’s second phase identified five common patterns of eye movements during reading in children with and without dyslexia. We discovered that children with dyslexia exhibit the same patterns as their typically developing peers, albeit with a three-year delay. Finally, the third phase revealed significant differences in gray matter volume in the cerebellum, insula, and parietal lobule between group of children with dyslexia and control group of typically developing children. These findings have significant implications for clinical practice, interdisciplinary research on dyslexia, and possibly the educational system.
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