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首页> 外文期刊>Frontiers in Psychology >Two Dyscalculia Subtypes With Similar, Low Comorbidity Profiles: A Mixture Model Analysis
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Two Dyscalculia Subtypes With Similar, Low Comorbidity Profiles: A Mixture Model Analysis

机译:两种具有相似,低合并症的菌亚型:混合物模型分析

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Several studies have aimed to identify subtypes of dyscalculia. In many of these studies, either pre-defined groups (e.g., children with reading and mathematical difficulties vs. children with isolated mathematical difficulties) were analyzed regarding their cognitive profiles (top-down approach), or clusters of children with dyscalculia (CwD) were identified based on a narrow range of cognitive and mathematical skills (data-driven or bottom-up approach). However, it has remained difficult to establish robust subtypes of dyscalculia across studies. Against this background, we conducted a mixture model analysis in order to explore and identify subtypes of dyscalculia based on a broad range of variables (intelligence, reading fluency, working memory, attention, and various mathematical skills). The total sample comprised 174 elementary school CwD (IQ 70; mathematical abilities: percentile rank 10), which consisted of two subsamples. The first subsample was based on a diagnostic test focusing on calculation (HRT 1–4; n = 71; 46 girls, 25 boys; age: M = 9.28 years, SD = 0.94) whereas the second subsample was based on a diagnostic test with a strong focus on basic numerical capacities (ZAREKI-R; n = 103; 78 girls, 25 boys; age: M = 8.94 years, SD = 1.05). Results provided convincing evidence for the existence of two subtypes in CwD: A slightly impaired subtype and a strongly impaired subtype. Subtypes differed most strongly regarding mathematical abilities, but the analyses suggest that differences in attention could also be a key factor. Therefore, comorbid attention difficulties seem to be a relevant factor that needs to be considered when establishing subtypes. Substantial intelligence differences between dyscalculia subtypes could not be found. Differences in working memory and reading fluency were negligible. Overall, the results seemed to be robust regardless of the diagnostic test used for assessing dyscalculia. When planning interventions for CwD, the existence of a subtype with substantial attention problems should be kept in mind.
机译:几项研究旨在识别Dyscalculia的亚型。在许多这些研究中,关于他们的认知谱(自上而下方法)或患有麻烦(CWD)的儿童簇(CWD)的预定义的群体(例如,具有读数和数学困难的儿童与孤立的数学困难的儿童)分析。基于狭窄的认知和数学技能(数据驱动或自下而上的方法)来识别。然而,它仍然难以在研究中建立强大的紊乱亚型。在此背景下,我们进行了混合模型分析,以根据广泛的变量(智能,阅读流畅,工作记忆,关注和各种数学技能)来探索和识别Dysculculia的亚型。总样本包括174个基本学校CWD(IQ> 70;数学能力:百分位等级& 10),由两个副页组成。第一个子样本基于对计算的诊断测试(HRT 1-4; n = 71; 46个女孩,25个男孩;年龄:m = 9.28岁,SD = 0.94),而第二个子摄像机基于诊断测试强烈关注基本数量容量(Zareki-R; n = 103; 78个女孩,25个男孩;年龄:M = 8.94岁,SD = 1.05)。结果提供了令人信服的证据,以便在CWD中存在两种亚型:亚型略有受损,亚型受损。亚型在数学能力中最强烈地不同,但分析表明关注的差异也可能是一个关键因素。因此,共同注意力困难似乎是建立亚型时需要考虑的相关因素。找不到困扰亚型之间的实质性智能差异。工作记忆和阅读流畅性的差异可忽略不计。总体而言,无论用于评估Dyscalculia的诊断测试如何,结果似乎都是稳健的。当对CWD进行计划干预时,应牢记具有重要关注问题的亚型的存在。

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