Peraita Herminia, Chacón José, Díaz-Mardomingo Carmen, Martínez-Arias Rosario
UNED (Spain).
Universidad Complutense (Spain).
Span J Psychol. 2015 Nov 20;18:E90. doi: 10.1017/sjp.2015.96.
We applied latent class analysis (LCA) to a set of neuropsychological data with the aim of corroborating the three cognitive profiles of mild cognitive impairment (MCI) described in the literature, namely: healthy, amnestic, non-amnestic, and multidomain. The ultimate purpose of the LCA was to try to find the underlying classification of MCI and related pathologies by means of the participants' response patterns, rather than on more classical psychometric criteria, such as the standard deviation of the mean. We computed 547 neuropsychological assessments derived from 223 participants who were assessed annually for three consecutive years. The battery included tests of memory, language, executive function, and praxis. The results obtained by means of LCA, with a four-group solution and using the 40th percentile as the criterion, confirm prior classifications obtained with more questionable psychometric criteria, while providing longitudinal data on the course of MCI and the stability of group assignment over time.
我们将潜在类别分析(LCA)应用于一组神经心理学数据,目的是证实文献中描述的轻度认知障碍(MCI)的三种认知概况,即:健康型、遗忘型、非遗忘型和多领域型。LCA的最终目的是通过参与者的反应模式,而非更传统的心理测量标准(如均值的标准差),试图找到MCI及相关病理的潜在分类。我们计算了来自223名参与者的547项神经心理学评估结果,这些参与者连续三年每年接受评估。测试组包括记忆、语言、执行功能和实践能力测试。通过LCA获得的结果,采用四组解决方案并以第40百分位数作为标准,证实了用更具争议性的心理测量标准获得的先前分类,同时提供了关于MCI病程以及随时间推移组分配稳定性的纵向数据。