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.
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on a method for computing semantic clustering on list-learning tasks (recall-based formula) that was derived from an outdated assumption about how learning occurs.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.
Delis
Dean C
DC
Psychology Service, Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA. ddelis@ucsd.edu
Fine
Eric M
EM
Stricker
John L
JL
Houston
Wes S
WS
Wetter
Spencer R
SR
Cobell
Krystal
K
Jacobson
Mark W
MW
Salmon
David P
DP
Bondi
Mark W
MW
D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000503:physiopathology*; D016022:Case-Control Studies; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D008297:Male; D011939:Mental Recall / Q000502:physiology*; D008875:Middle Aged; D009483:Neuropsychological Tests; D009716:Numerical Analysis, Computer-Assisted; D012660:Semantics; D014706:Verbal Learning / Q000502:physiology*