4.3 Article

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

Journal

CLINICAL NEUROPSYCHOLOGIST
Volume 24, Issue 1, Pages 70-79

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/13854040903002232

Keywords

Learning; Memory; Neuropsychology; CVLT

Funding

  1. NATIONAL INSTITUTE ON AGING [K24AG026431, R01AG012674] Funding Source: NIH RePORTER
  2. NIA NIH HHS [K24 AG026431, K24 AG026431-03, R01 AG012674, R01 AG012674-12] Funding Source: Medline

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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on a method for computing semantic clustering on list-learning tasks (recall-based formula) that was derived from an outdated assumption about how learning occurs.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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