University of Amsterdam, Faculty of Social and Behavioural Sciences, Nieuwe Achtergracht 127, 1018WS, Amsterdam, The Netherlands.
Res Dev Disabil. 2017 Dec;71:143-168. doi: 10.1016/j.ridd.2017.09.010. Epub 2017 Oct 15.
The Multiple Diagnostic Digital Dyslexia Test for Adults (MDDDT-A) consists of 12 newly developed tests and self-report questions in the Dutch language. Predictive validity and construct validity were investigated and compared with validity of a standard test battery of dyslexia (STB) in a sample of 154 students. There are three main results. First, various analyses of principal components showed that six or more factors of dyslexia can be distinguished (rapid naming, spelling, reading, short-term memory, confusion, phonology, attention, complexity). All factors are represented by the MDDDT-A. Second, various discriminant analyses showed good predictive validity for both the tests of the MDDDT-A (90%) and the STB (90%). However, predictive validity of the questionnaire was highest (97%). Third, we analysed the best predictors of dyslexia and found that predictive validity is higher when construct validity is high, that is when a set of predictors represents many characteristics of dyslexia. The main conclusion is that a digital test battery can be a reliable screening instrument for dyslexia in students, especially when it is accompanied by self-report questions. A theoretical conclusion is that dyslexia is characterized by at least six cognitive impairments in a complex way. In students, this structure may be modulated by high intelligence and good schooling through various compensation strategies. It is therefore recommended to include assessments of all characteristics of dyslexia to achieve the most reliable diagnoses in different samples and in different countries.
《成人多重诊断数字阅读障碍测试》(MDDDT-A)包含 12 项新开发的测试和荷兰语自陈式问题。我们在 154 名学生样本中调查了该测试的预测有效性和结构有效性,并与阅读障碍标准测试组合(STB)的有效性进行了比较。有三个主要结果。第一,各种主成分分析表明,可以区分六种或更多种阅读障碍因素(快速命名、拼写、阅读、短期记忆、混淆、语音、注意力、复杂性)。所有因素都由 MDDDT-A 来表示。第二,各种判别分析表明,MDDDT-A 的测试(90%)和 STB(90%)都具有良好的预测有效性。然而,问卷的预测有效性最高(97%)。第三,我们分析了阅读障碍的最佳预测因素,发现当结构有效性高时,预测有效性更高,即当一组预测因素代表阅读障碍的许多特征时。主要结论是,数字测试组合可以成为学生阅读障碍的可靠筛查工具,尤其是当它伴随着自陈式问题时。理论结论是,阅读障碍至少以六种认知障碍的复杂方式为特征。在学生中,这种结构可能会通过各种补偿策略被高智商和良好教育所调节。因此,建议在不同的样本和不同的国家中,评估阅读障碍的所有特征,以获得最可靠的诊断。