Abstract
Norms for Hebrew semantic and phonemic fluency were collected in a sample of 369 participants, ranging in age from 18 to 85. Two hundred and sixty nine persons completed both tests and the rest completed only the semantic test. Phonemic fluency was assessed with the use of three letters (bet, gimel, and shin) and semantic fluency with the use of three categories (animals, fruits and vegetables, and vehicles). Scores of individual letters and categories, sum scores, as well as the difference between the semantic and phonemic sum scores are presented for four age groups (18-30, 31-50, 51-70, and 71-85). Results show that age had the greatest effect on fluency performance, level of education was positively correlated to sum scores but contributed little to its prediction beyond the contribution of age, and gender had no significant effect.
Original language | English |
---|---|
Pages (from-to) | 690-699 |
Number of pages | 10 |
Journal | Journal of Clinical and Experimental Neuropsychology |
Volume | 27 |
Issue number | 6 |
DOIs | |
State | Published - Aug 2005 |
Externally published | Yes |
Bibliographical note
Funding Information:Several cognitive abilities underlie fluency performance. Word generation is most strongly correlated with measures of vocabulary and auditory attention (Ruff, Light, Parker, & Levin, 1997), as well as with articulation speed (Hughes & Bryan, 2002). Relatively automatic processes of clustering that rely on word storage, and relatively effortful processes of shifting that rely on strategic search and mental flexibility further influence performance (Troyer, 2000; Troyer, Moscovitch, & Winocur, 1997). The task involves Part of this work was supported by grants from the Brookdale Institute of Gerontology and Human Development, Eshel—The Association for the Planning and Development of Services for the Aged in Israel, and the Israel Foundations Trustees, which the author received while completing a doctorate degree at the Hebrew University of Jerusalem. I am grateful to Limor Assayag, Naomi Barancik, Sharon Malka, Maya Marcus, Amos Raber, Diana Tsimkin, and Daphna Tzur for their help in data collection.