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在数字评估下,儿童多动症的DSM-5-TR陈述中神经认知重叠在数字评估下

Emilio Diaz-Moreno¹, José Heredia-Jimenez^1,2

¹Human Behaviour & Motion Analysis Lab (HubemaLab), University of Granada, Ceuta, Spain.

Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence

|March 10, 2026

概括

注意缺陷/多动障碍 (ADHD) 呈现显示在数字评估上类似的神经认知表现. 数据驱动的个人资料,而不是DSM-5-TR标签,更好地描述了ADHD儿童的认知异质性.

科学领域:

神经科学是一个神经科学.
精神病学是一个精神病学.
发展心理学发展心理学

背景情况:

精神障碍的诊断和统计手册,第五版,文本修订 (DSM-5-TR) 将注意力缺陷/多动障碍 (ADHD) 分类为注意力不集中,多动/冲动和组合表现.
目前尚不清楚这些DSM-5-TR定义的表现是否与不同的神经认知特征有关.

研究的目的:

通过使用标准化的数字评估电池,调查DSM-5-TRADHD呈现的神经认知差异.
探索替代的,数据驱动的方法来表征ADHD的认知异质性.

主要方法:

193名患有多动症的儿童 (7-12岁) 经过神经认知测试 (中枢神经系统生命体征) 经过兴奋剂洗后.
陈述指标是基于母公司报告的SNAP-IV评级.
统计分析包括克鲁斯卡尔-瓦利斯测试,贝叶斯ANOVA和等效测试 (TOST) 来比较不同表现的神经认知领域.
使用无监督集群来确定数据驱动的绩效配置文件.

主要成果:

在对多次比较进行校正后,在多种ADHD表现中没有发现显著的神经认知差异 (FDR调整的p值>= .980).
贝叶斯分析偏爱没有呈现因子的模型 (BF_inclusion = .005-.011),表明呈现特异性影响的证据很少.
观察到的效应大小很小 (max d = 0.25) 和在等效范围内,这表明实际差异很小.
无监督集群确定了两个与DSM-5-TR陈述标签无关的不同性能配置文件 (平均和低),解释了显著的认知差异.

结论:

目前的DSM-5-TR ADHD表达类别似乎没有反映在标准化的数字评估条件下有意义的神经认知区别.
数据驱动的绩效档案为理解ADHD的认知异质性提供了更有信息的框架,可能有助于教育规划.
研究结果强调了考虑超越基于症状的分类之外的替代方法的重要性,以表征ADHD的个体差异.

关键词:

更多关于 ADHD ADHD 的文章贝叶斯因子是一个贝叶斯因子.中央统计系统的生命体征数字化评估是指数字化的评估.同等性测试等同性的测试.k-表示集群的平均值.

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