ArticlePloS one2016
Computerized Analysis of Verbal Fluency: Normative Data and the Effects of Repeated Testing, Simulated Malingering, and Traumatic Brain Injury.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04800588 (Computerized Tests of Cognitive Decline in Presymptomatic Alzheimer's Disease), which is not on this map. Cited by 22 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Computerized Tests of Cognitive Decline in Presymptomatic Alzheimer's Disease
Who cites it
22 citing papers in PubMed.
- Preliminary Evaluation of the Circle Sequencing Task (CST) as a Cognitive-Motor Tool for Concussion Assessment.Sports (Basel, Switzerland) · 2026Article
- The contribution of verbal delayed recall to phonemic but not semantic fluency in aging individuals.Oxford open neuroscience · 2026Article
- Automated remote longitudinal neuropsychological testing with the California Cognitive Assessment Battery.The Clinical neuropsychologist · 2025Article
- A Japanese LDA model for automatic clustering analysis of semantic verbal fluency tests.Behavior research methods · 2025Article
- After cochlear implantation in older adults, enhanced working memory does not fully mediate the relationship between CI and improved semantic fluency.Frontiers in aging neuroscience · 2025Article
- The association of sociodemographic factors with total and item-level semantic fluency metrics.Neuropsychology · 2024Article
- A semantic strength and neural correlates in developmental dyslexia.Frontiers in psychology · 2024Review
- The California Cognitive Assessment Battery (CCAB).Frontiers in human neuroscience · 2023Article
- Remote data collection speech analysis in people at risk for Alzheimer's disease dementia: usability and acceptability results.Frontiers in dementia · 2023Article
- Selecting the Most Important Features for Predicting Mild Cognitive Impairment from Thai Verbal Fluency Assessments.Sensors (Basel, Switzerland) · 2022Article
- Verbal fluency as a quick and simple tool to help in deciding when to refer patients with a possible brain tumour.BMC neurology · 2022Article
- Dopamine-Related Reduction of Semantic Spreading Activation in Patients With Parkinson's Disease.Frontiers in human neuroscience · 2022Article
- Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis.Brain imaging and behavior · 2021Article
- Dual-Task Training Program for Older Adults: Blending Gait, Visuomotor and Cognitive Training.Frontiers in network physiology · 2021Article
- Serial Recall Order and Semantic Features of Category Fluency Words to Study Semantic Memory in Normal Ageing.Frontiers in aging neuroscience · 2021Article
- The Dual-Task Cost Is Due to Neural Interferences Disrupting the Optimal Spatio-Temporal Dynamics of the Competing Tasks.Frontiers in behavioral neuroscience · 2021Article
- SNAFU: The Semantic Network and Fluency Utility.Behavior research methods · 2020Article
- Improving the Assessment of Mild Cognitive Impairment in Advanced Age With a Novel Multi-Feature Automated Speech and Language Analysis of Verbal Fluency.Frontiers in psychology · 2020Article
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4 authors.
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Abstract
In verbal fluency (VF) tests, subjects articulate words in a specified category during a short test period (typically 60 s). Verbal fluency tests are widely used to study language development and to evaluate memory retrieval in neuropsychiatric disorders. Performance is usually measured as the total number of correct words retrieved. Here, we describe the properties of a computerized VF (C-VF) test that tallies correct words and repetitions while providing additional lexical measures of word frequency, syllable count, and typicality. In addition, the C-VF permits (1) the analysis of the rate of responding over time, and (2) the analysis of the semantic relationships between words using a new method, Explicit Semantic Analysis (ESA), as well as the established semantic clustering and switching measures developed by Troyer et al. (1997). In Experiment 1, we gathered normative data from 180 subjects ranging in age from 18 to 82 years in semantic ("animals") and phonemic (letter "F") conditions. The number of words retrieved in 90 s correlated with education and daily hours of computer-use. The rate of word production declined sharply over time during both tests. In semantic conditions, correct-word scores correlated strongly with the number of ESA and Troyer-defined semantic switches as well as with an ESA-defined semantic organization index (SOI). In phonemic conditions, ESA revealed significant semantic influences in the sequence of words retrieved. In Experiment 2, we examined the test-retest reliability of different measures across three weekly tests in 40 young subjects. Different categories were used for each semantic ("animals", "parts of the body", and "foods") and phonemic (letters "F", "A", and "S") condition. After regressing out the influences of education and computer-use, we found that correct-word z-scores in the first session did not differ from those of the subjects in Experiment 1. Word production was uniformly greater in semantic than phonemic conditions. Intraclass correlation coefficients (ICCs) of correct-word z-scores were higher for phonemic (0.91) than semantic (0.77) tests. In semantic conditions, good reliability was also seen for the SOI (ICC = 0.68) and ESA-defined switches in semantic categories (ICC = 0.62). In Experiment 3, we examined the performance of subjects from Experiment 2 when instructed to malinger: 38% showed abnormal (p< 0.05) performance in semantic conditions. Simulated malingerers with abnormal scores could be distinguished with 80% sensitivity and 89% specificity from subjects with abnormal scores in Experiment 1 using lexical, temporal, and semantic measures. In Experiment 4, we tested patients with mild and severe traumatic brain injury (mTBI and sTBI). Patients with mTBI performed within the normal range, while patients with sTBI showed significant impairments in correct-word z-scores and category shifts. The lexical, temporal, and semantic measures of the C-VF provide an automated and comprehensive description of verbal fluency performance.
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