Individual prediction of dyslexia by single versus multiple deficit models.
Individual prediction of dyslexia by single versus multiple deficit models.
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DOI：
10.1037/a0025823
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发表时间：
2012-02
影响因子：
4.6
通讯作者：
Olson, Richard K.
中科院分区：
文献类型：
--
作者：
Pennington, Bruce F.;Lemmon, Laura Santerre;Rosenberg, Jennifer;MacDonald, Beatriz;Boada, Richard;Friend, Angela;Leopold, Daniel R.;Samuelsson, Stefan;Byrne, Brian;Willcutt, Erik G.;Olson, Richard K.
本研究的总体目标是在个体病例水平上测试阅读障碍（阅读障碍）的单一与多重认知缺陷模型，并确定这些模型用于预测和诊断阅读障碍的临床效用。为了实现这些目标，我们测试了五个认知模型的阅读障碍：两个单赤字模型，两个多赤字模型，和一个混合模型在两个大的人口为基础的样本，一个横截面（科罗拉多学习障碍研究中心-CLDRC）和一个纵向（国际纵向双胞胎研究-ILTS）。这些认知模型中的认知缺陷包括语音意识、语言技能、加工速度和/或命名速度。为了确定个体病例是否符合这些模型之一，我们使用了两种方法：1）存在或不存在预测的认知缺陷，以及2）个体的阅读技能水平是否最适合回归方程与相关的认知预测因素（即他们的阅读技能是否与这些认知预测因素成比例）。我们发现，大致相同比例的病例符合多重缺陷模型（30-36%）和单一缺陷模型（24-28%）的模型拟合检验;因此，混合模型提供了对数据的最佳总体拟合。每个样本中剩余的大约40%的病例缺乏与其最佳拟合回归模型相对应的缺陷或缺陷。我们讨论了这些结果对学龄儿童的诊断和学龄前儿童阅读障碍风险预测的临床意义。
The overall goals of this study were to test single vs. multiple cognitive deficit models of dyslexia (reading disability) at the level of individual cases and to determine the clinical utility of these models for prediction and diagnosis of dyslexia. To accomplish these goals, we tested five cognitive models of dyslexia: two single-deficit models, two multiple-deficit models, and one hybrid model in two large population-based samples, one cross-sectional (Colorado Learning Disability Research Center—CLDRC) and one longitudinal (International longitudinal Twin Study—ILTS). The cognitive deficits included in these cognitive models were in phonological awareness, language skill, and processing speed and/ or naming speed. To determine whether an individual case fit one of these models, we used two methods: 1) the presence or absence of the predicted cognitive deficits, and 2) whether the individual’s level of reading skill best fit the regression equation with the relevant cognitive predictors (i.e. whether their reading skill was proportional to those cognitive predictors.) We found that roughly equal proportions of cases met both tests of model fit for the multiple deficit models (30–36%) and single deficit models (24–28%); hence, the hybrid model provided the best overall fit to the data. The remaining roughly 40% of cases in each sample lacked the deficit or deficits that corresponded with their best fitting regression model. We discuss the clinical implications of these results for both diagnosis of school age children and preschool prediction of children at risk for dyslexia.
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影响因子：
10.6
作者：
Nigg, JT;Willcutt, EG;Sonuga-Barke, EJS
通讯作者：
Sonuga-Barke, EJS
影响因子：
2.2
作者：
Furnes, Bjarte;Samuelsson, Stefan
通讯作者：
Samuelsson, Stefan
DOI：
10.1044/1092-4388(2009/08-0024
发表时间：
2009-10-01
影响因子：
2.6
作者：
Peterson, Robin L.;Pennington, Bruce F.;Boada, Richard
通讯作者：
Boada, Richard
影响因子：
4.6
作者：
Pennington, BF;Lefly, DL
通讯作者：
Lefly, DL
影响因子：
56.9
作者：
DAWES, RM;FAUST, D;MEEHL, PE
通讯作者：
MEEHL, PE