Understanding verbal fluency in healthy aging, Alzheimer’s disease, and Parkinson’s disease

Abstract

This is the author's accepted manuscript. This article may not exactly replicate the final version published in the APA journal. It is not the copy of record.• Objective: Verbal fluency measures are frequently part of batteries designed to assess executive function, but are also used to assess semantic processing ability or word knowledge. The goal of the present study was to identify the cognitive components underlying fluency performance. • Method: Healthy young and older adults, adults with Parkinson’s disease, and adults with Alzheimer’s disease performed letter, category, and action fluency tests. Performance was assessed in terms of number of items generated, clustering, and the time course of output. A series of neuropsychological assessments were also administered to index verbal ability, working memory, executive function, and processing speed as correlates of fluency performance. • Results: Findings indicated that regardless of the particular performance measure, young adults performed the best and adults with Alzheimer’s disease performed most poorly, with healthy older adults and adults with Parkinson’s disease performing at intermediate levels. The exception was the action fluency task, where adults with Parkinson’s disease performed most poorly. The time course of fluency performance was characterized in terms of slope and intercept parameters and related to neuropsychological constructs. Speed of processing was found to be the best predictor of performance, rather than the efficiency of executive function or semantic knowledge. • Conclusions: Together, these findings demonstrate that the pattern of fluency performance looks generally the same regardless of how performance is measured. In addition, the primary role of processing speed in performance suggests that the use of fluency tasks as measures of executive function or verbal ability warrants reexamination.This work was conducted with grant support from the Kansas City Life Sciences Institute. Additional support was provided by the Digital Electronics Core of the Center for Biobehavioral Neurosciences in Communication Disorders, grant number P30 DC-005803, for assistance with the development of the digital ink assessment

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