Joyner Rachel E, Wagner Richard K
Florida State University, Tallahassee, FL, USA.
Sci Stud Read. 2020;24(1):14-22. doi: 10.1080/10888438.2019.1593420. Epub 2019 Apr 3.
Despite the importance of identifying individuals with reading disabilities, existing operational definitions of reading disability do not result in reliable identification. A large part of the problem arises from measurement error when a cut-point is imposed on a continuous distribution, especially for low base-rate conditions. One way to reduce measurement error is to include additional predictors in reading disability models. The present study examined co-occurring math disability as a possible additional criterion for predicting reading disability. Meta-analysis was used to examine the probability of individuals with reading disability also having a comorbid math disability. Possible moderators including age, severity of disability, and language were examined. The main result was an average weighted odds ratio of 2.12, 95% confidence interval [1.76, 2.55], indicating that students with a math disability are just over two times more likely to also have a reading disability than those without a math disability. Implications of the results are discussed.
尽管识别有阅读障碍的个体很重要,但现有的阅读障碍操作定义并不能可靠地进行识别。很大一部分问题源于在连续分布上设置切点时的测量误差,尤其是在低基础率条件下。减少测量误差的一种方法是在阅读障碍模型中纳入额外的预测因素。本研究考察了共病的数学障碍作为预测阅读障碍的一种可能的额外标准。采用元分析来检验有阅读障碍的个体同时患有共病数学障碍的概率。研究了包括年龄、残疾严重程度和语言在内的可能调节因素。主要结果是平均加权优势比为2.12,95%置信区间为[1.76, 2.55],表明有数学障碍的学生同时患有阅读障碍的可能性是没有数学障碍学生的两倍多。讨论了结果的意义。