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COMPARISON OF THE TRADITIONAL RECALL-BASED VERSUS A NEW LIST-BASED METHOD FOR COMPUTING SEMANTIC CLUSTERING ON THE CALIFORNIA VERBAL LEARNING TEST: EVIDENCE FROM ALZHEIMER’S DISEASE

机译:基于传统的召回与基于新列表的基于列表的方法的比较用于计算加州语言学习测试的语义聚类:来自阿尔茨海默病的证据

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摘要

For over 50 years, cognitive psychologists and neuropsychologists have relied almost exclusively on a method for computing semantic clustering on list-learning tasks (recall-based formula) that was derived from an outdated assumption about how learning occurs. A new procedure for computing semantic clustering (list-based formula) was developed for the CVLT-II to correct the shortcomings of the traditional method. In the present study we compared the clinical utility of the traditional recall-based method versus the new list-based method using results from the original CVLT administered to 87 patients with Alzheimer’s disease and 86 matched normal control participants. Logistic regression and score distribution analyses indicated that the new list-based method enhances the detection of differences in semantic-clustering ability between the groups.

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