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用于威斯康星卡片分类任务的序列学习模型:评估物质依赖个体的过程。

Sequential Learning Models for the Wisconsin Card Sort Task: Assessing Processes in Substance Dependent Individuals.

作者信息

Bishara Anthony J, Kruschke John K, Stout Julie C, Bechara Antoine, McCabe David P, Busemeyer Jerome R

机构信息

Department of Psychology, College of Charleston.

出版信息

J Math Psychol. 2010 Feb 1;54(1):5-13. doi: 10.1016/j.jmp.2008.10.002.

Abstract

The Wisconsin Card Sort Task (WCST) is a commonly used neuropsychological test of executive or frontal lobe functioning. Traditional behavioral measures from the task (e.g., perseverative errors) distinguish healthy controls from clinical populations, but such measures can be difficult to interpret. In an attempt to supplement traditional measures, we developed and tested a family of sequential learning models that allowed for estimation of processes at the individual subject level in the WCST. Testing the model with substance dependent individuals and healthy controls, the model parameters significantly predicted group membership even when controlling for traditional behavioral measures from the task. Substance dependence was associated with a) slower attention shifting following punished trials and b) reduced decision consistency. Results suggest that model parameters may offer both incremental content validity and incremental predictive validity.

摘要

威斯康星卡片分类任务(WCST)是一种常用的用于测试执行功能或额叶功能的神经心理学测试。该任务的传统行为测量指标(例如,持续性错误)可区分健康对照组和临床人群,但这些指标可能难以解释。为了补充传统测量方法,我们开发并测试了一系列序列学习模型,这些模型能够在个体水平上估计WCST中的各种过程。在对物质依赖个体和健康对照组进行模型测试时,即使在控制了该任务的传统行为测量指标的情况下,模型参数仍能显著预测组别归属。物质依赖与以下两点相关:a)在受惩罚试验后注意力转移较慢;b)决策一致性降低。结果表明,模型参数可能同时具有增量内容效度和增量预测效度。

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