ArticleEuropean journal of ageing2023
Validation of the test for finding word retrieval deficits (WoFi) in detecting Alzheimer's disease in a naturalistic clinical setting.
Article in European journal of ageing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The potential of depressive symptoms to identify cognitive impairment in ageing.European journal of ageing · 2025Article
- Pragmatic questionnaire-based evaluation of auditory function in individuals with major neurocognitive disorders and hearing loss in diverse contexts.Frontiers in aging neuroscience · 2025Article
- Telehealth memory clinics in primary healthcare: real-world experiences from low-resource settings in Greece.Frontiers in dementia · 2024Article
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13 authors.
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Abstract
backgroundDetecting 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.
objectiveThe 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.
methodsThis 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).
resultsWoFi 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.
conclusionsWoFi and WoFi-brief are more effective in detecting MildND and MajorND due to AD than ACEIIINaming.
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