Autism and Hierarchical Models of Intelligence.
Autism and Hierarchical Models of Intelligence.
复制标题
自闭症和智力的层次模型。
DOI：
10.1007/s10803-023-05984-x
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发表时间：
2023
影响因子：
3.9
通讯作者：
Ewen,JoshuaB
中科院分区：
文献类型：
--
作者：
Levine,MichaelA;Chen,Huan;Wodka,ErickaL;Caffo,BrianS;Ewen,JoshuaB
背景韦克斯勒儿童智力量表（WISC）采用一般智力的分层模型，其中指数评分区分了智力的不同临床相关方面;该测试的设计使得指数评分在标准样本中在统计上相互独立。现有的指数分数是否符合所需的心理测量学属性是统计独立的自闭症samples.MethodWe进行了因素分析WISC第五版（WISC-V）（N = 83）和WISC第四版（WISC-IV）（N = 131）的子测试数据在自闭症儿童。我们比较了数据驱动的探索性因素分析与手动导出的指数得分，包括在一个典型的发展中（TD）WISC-IV队列（N = 209）。ResultsThe WISC-IV TD队列显示了预期的1：1关系之间的经验得出的因素和手动导出的指数得分。我们在两个ASD样本（WISC-IV和WISC-V）中观察到我们的数据驱动因素和手动IQ指数得分之间的独特相关性较低。特别是，在这两个WISC-IV和-V，工作记忆（WM）的影响指数分数在自闭症个体不加载WM在normal samples.ConclusionsWISC指数分数不显示所需的统计独立性自闭症样本内，判断对一个judically-derived探索性因素分析。特别是，在目前使用的WISC-V版本中，WM影响多个指标得分。
BackgroundThe Wechsler Intelligence Scale for Children (WISC) employs a hierarchical model of general intelligence in which index scores separate out different clinically-relevant aspects of intelligence; the test is designed such that index scores are statistically independent from one another within the normative sample. Whether or not the existing index scores meet the desired psychometric property of being statistically independent within autistic samples is unknown.MethodWe conducted a factor analysis on WISC fifth edition (WISC-V) (N = 83) and WISC fourth edition (WISC-IV) (N = 131) subtest data in children with autism. We compared the data-driven exploratory factor analysis with the manual-derived index scores, including in a typically developing (TD) WISC-IV cohort (N = 209).ResultsThe WISC-IV TD cohort showed the expected 1:1 relationship between empirically derived factors and manual-derived index scores. We observed less unique correlations between our data-driven factors and manualized IQ index scores in both ASD samples (WISC-IV and WISC-V). In particular, in both WISC-IV and -V, working memory (WM) influenced index scores in autistic individuals that do not load on WM in the normative sample.ConclusionsWISC index scores do not show the desired statistical independence within autistic samples, as judged against an empirically-derived exploratory factor analysis. In particular, within the currently used WISC-V version, WM influences multiple index scores.