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Comprehensive verbal fluency features predict executive function performance.

ABSTRACT: Semantic verbal fluency (sVF) tasks are commonly used in clinical diagnostic batteries as well as in a research context. When performing sVF tasks to assess executive functions (EFs) the sum of correctly produced words is the main measure. Although previous research indicates potentially better insights into EF performance by the use of finer grained sVF information, this has not yet been objectively evaluated. To investigate the potential of employing a finer grained sVF feature set to predict EF performance, healthy monolingual German speaking participants (n = 230) were tested with a comprehensive EF test battery and sVF tasks, from which features including sum scores, error types, speech breaks and semantic relatedness were extracted. A machine learning method was applied to predict EF scores from sVF features in previously unseen subjects. To investigate the predictive power of the advanced sVF feature set, we compared it to the commonly used sum score analysis. Results revealed that 8 / 14 EF tests were predicted significantly using the comprehensive sVF feature set, which outperformed sum scores particularly in predicting cognitive flexibility and inhibitory processes. These findings highlight the predictive potential of a comprehensive evaluation of sVF tasks which might be used as diagnostic screening of EFs.

SUBMITTER: Amunts J

PROVIDER: S-EPMC7994566 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveThe current study was designed to achieve 2 primary objectives: (a) determine the moderating effect of mild cognitive impairments (MCI) on intraindividual variability in semantic and letter fluency performance taking into account longitudinal annual assessments; and (b) establish predictive utility for intraindividual variability in semantic and letter fluency performance as a risk factor of incident MCI.MethodsParticipants were community-residing older adults (n = 514; M age = 75.89 ± 6.45; 55.1% female). Sixty participants were diagnosed with MCI at baseline and 50 developed incident MCI during the follow-up. We operationalized intraindividual variability as word generation slopes derived from 3 consecutive time intervals during the standard 1-min administration of both letter and semantic fluency tasks (i.e., 0-20 s, 21-40 s, and 41-60 s).ResultsLinear mixed effects models revealed significant within task slope effects for semantic (estimate = -8.350; p < .0001; 95% confidence interval [CI] = -8.604, -8.095) and letter (estimate = -5.068; p < .0001; 95% CI [-5.268, -4.869]) fluency indicating that word generation declined over the course of both tasks. The two-way interactions of MCI × Slope were significant for semantic (estimate = 1.34; p = .001; 95% CI [0.551, 2.126]) and letter (estimate = 0.733; p = .020; 95% CI [0.116, 1.350]) fluency indicating attenuated slopes among MCI participants compared to controls taking into account repeated annual assessments. Cox proportional-hazards models revealed that attenuated word generation slope, at baseline, in semantic (hazard ratio [HR] = 2.063; p = .015; 95% = 1.149 to 3.702) but not letter (HR = 0.704; p = .243; 95% CI [0.391, 1.269]) fluency was associated with increased risk of incident MCI.ConclusionIntraindividual variability in verbal fluency performance has clinical and predictive utility; it can be easily incorporated into testing batteries in clinical and research settings. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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Comprehensive verbal fluency features predict executive function performance.

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