Validation of the test for finding word retrieval deficits (WoFi) in detecting Alzheimer's disease in a naturalistic clinical setting

Eleni-Zacharoula Georgiou, Maria Skondra, Marina Charalampopoulou, Panagiotis Felemegkas, Asimina Pachi, Georgia Stafylidou, Dimitrios Papazachariou, Robert Perneczky, Vasileios Thomopoulos, Antonios Politis, Iracema Leroi, Polychronis Economou and Panagiotis Alexopoulos ()
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Eleni-Zacharoula Georgiou: University of Patras
Maria Skondra: University of Patras
Marina Charalampopoulou: University of Patras
Panagiotis Felemegkas: University of Patras
Asimina Pachi: University of Patras
Georgia Stafylidou: University of Patras
Dimitrios Papazachariou: University of Patras
Robert Perneczky: Ludwig-Maximilians-Universität Munich
Vasileios Thomopoulos: University of Patras
Antonios Politis: National and Kapodistrian University of Athens
Iracema Leroi: The University of Dublin
Polychronis Economou: University of Patras
Panagiotis Alexopoulos: University of Patras

European Journal of Ageing, 2023, vol. 20, issue 1, No 29, 10 pages

Abstract: Abstract Background Detecting impaired naming capacity contributes to the detection of mild (MildND) and major (MajorND) neurocognitive disorder due to Alzheimer’s disease (AD). The Test for Finding Word retrieval deficits (WoFi) is a new, 50-item, auditory stimuli-based instrument. Objective The study aimed to adapt WoFi to the Greek language, to develop a short version of WoFi (WoFi-brief), to compare the item frequency and the utility of both instruments with the naming subtest of the widely used Addenbrooke’s cognitive examination III (ACEIIINaming) in detecting MildND and MajorND due to AD. Methods This cross-sectional, validation study included 99 individuals without neurocognitive disorder, as well as 114 and 49 patients with MildND and MajorND due to AD, respectively. The analyses included categorical principal components analysis using Cramer’s V, assessment of the frequency of test items based on corpora of television subtitles, comparison analyses, Kernel Fisher discriminant analysis models, proportional odds logistic regression (POLR) models and stratified repeated random subsampling used to recursive partitioning to training and validation set (70/30 ratio). Results WoFi and WoFi-brief, which consists of 16 items, have comparable item frequency and utility and outperform ACEIIINaming. According to the results of the discriminant analysis, the misclassification error was 30.9%, 33.6% and 42.4% for WoFi, WoFi-brief and ACEIIINaming, respectively. In the validation regression model including WoFi the mean misclassification error was 33%, while in those including WoFi-brief and ACEIIINaming it was 31% and 34%, respectively. Conclusions WoFi and WoFi-brief are more effective in detecting MildND and MajorND due to AD than ACEIIINaming.

Keywords: Dysnomia; Auditory stimuli-based naming test; Mild and major neurocognitive disorder (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10433-023-00772-z

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