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Exploring the phonological profiles of children with reading difficulties: A multiple case study
Dyslexia ( IF 2.066 ) Pub Date : 2020-08-18 , DOI: 10.1002/dys.1667
Ian R. Mundy 1 , Penelope Hannant 2
Affiliation  

Studies of group differences have established that the phonological profiles of people with reading difficulties contain both strengths and weaknesses. The current study extends this work by exploring individual differences in phonological ability using a multiple case study approach. A heterogeneous sample of 56 children (M age = 9 years) with reading difficulties completed a battery of tasks measuring literacy, phonological processing, expressive vocabulary and general ability. The phonological tasks included measures of phonological awareness (PA), phonological memory (PM), and rapid naming (RAN). A majority—although not all—of the children had phonological processing impairments. However, there was also substantial variability in the nature of children's phonological difficulties. While multiple impairments encompassing two or more phonological domains were most common, impairments that were specific to PA, PM or RAN also occurred frequently. Even within the domain of PA, where children completed three well‐matched tasks, individual children were rarely impaired across all three measures and a number of different profiles were observed. Additional, group‐level analyses indicated that PA was a significant predictor of decoding while RAN was a significant predictor of automatic word recognition and comprehension. Findings are discussed with reference to conceptual models of phonological processing and implications for assessment.

中文翻译:

探索阅读困难儿童的语音特征:一个多案例研究

对群体差异的研究已经确定,阅读困难者的语音特征既有优点也有缺点。当前的研究通过使用多案例研究方法探索语音能力的个体差异来扩展这项工作。异质样本的56个儿童(M年龄= 9岁),有阅读困难,完成了一系列的任务,这些任务测量读写能力,语音处理,表达性词汇和一般能力。语音任务包括语音意识测量(PA),语音记忆(PM)和快速命名(RAN)。大多数(尽管不是全部)儿童都有语音处理障碍。但是,儿童的语音困难的性质也存在很大的差异。虽然涵盖两个或多个音域的多重损伤最为常见,但针对PA,PM或RAN的损伤也经常发生。即使在儿童完成了三项非常匹配的任务的PA领域内,在这三项措施中个别儿童也很少受到损害,并且观察到许多不同的情况。额外,小组分析表明,PA是解码的重要预测指标,而RAN是自动单词识别和理解的重要预测指标。研究结果参考语音处理的概念模型及其对评估的影响进行了讨论。
更新日期:2020-08-18
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