UNLABELLED: Despite their widespread use in research and clinical practice, the cognitive abilities purportedly assessed by different verbal fluency task variants remain unclear and may vary across different healthy and clinical populations. The overarching aim of this study was to identify which cognitive abilities contribute to phonemic, semantic, excluded letter, and alternating verbal fluency tasks and whether these contributions differ across younger and older healthy adults. METHOD: Ninety-six younger (18-36 years) and 83 older (65-87 years) healthy participants completed measures of estimated verbal intelligence, semantic retrieval, processing speed, working memory, and inhibitory control, in addition to phonemic, semantic, excluded letter, and alternating fluency tasks. Eight hierarchical multiple regressions were conducted across the four fluency variants and two age groups to identify which cognitive variables uniquely contributed to these fluency tasks. RESULTS: In the younger group, verbal intelligence and processing speed contributed to phonemic fluency, semantic retrieval to semantic fluency, processing speed and working memory to excluded letter fluency, and semantic retrieval to alternating fluency. In contrast, in the older group, verbal intelligence contributed to phonemic fluency, no cognitive variables contributed to semantic fluency, inhibition to excluded letter fluency, and verbal intelligence to alternating fluency. CONCLUSIONS: Our findings highlight that both lower and higher order cognitive skills contribute to verbal fluency tasks; however, these contributions vary considerably across fluency variants and age groups. The heterogeneity of cognitive determinants of verbal fluency, across variants and age, may explain why older people performed less proficiently on semantic and excluded letter fluency tasks while no age effects were found for phonemic and alternating fluency. Interpretation of verbal fluency performances need to be tailored according to which verbal fluency variant and age group are used.
UNLABELLED: Despite their widespread use in research and clinical practice, the cognitive abilities purportedly assessed by different verbal fluency task variants remain unclear and may vary across different healthy and clinical populations. The overarching aim of this study was to identify which cognitive abilities contribute to phonemic, semantic, excluded letter, and alternating verbal fluency tasks and whether these contributions differ across younger and older healthy adults. METHOD: Ninety-six younger (18-36 years) and 83 older (65-87 years) healthy participants completed measures of estimated verbal intelligence, semantic retrieval, processing speed, working memory, and inhibitory control, in addition to phonemic, semantic, excluded letter, and alternating fluency tasks. Eight hierarchical multiple regressions were conducted across the four fluency variants and two age groups to identify which cognitive variables uniquely contributed to these fluency tasks. RESULTS: In the younger group, verbal intelligence and processing speed contributed to phonemic fluency, semantic retrieval to semantic fluency, processing speed and working memory to excluded letter fluency, and semantic retrieval to alternating fluency. In contrast, in the older group, verbal intelligence contributed to phonemic fluency, no cognitive variables contributed to semantic fluency, inhibition to excluded letter fluency, and verbal intelligence to alternating fluency. CONCLUSIONS: Our findings highlight that both lower and higher order cognitive skills contribute to verbal fluency tasks; however, these contributions vary considerably across fluency variants and age groups. The heterogeneity of cognitive determinants of verbal fluency, across variants and age, may explain why older people performed less proficiently on semantic and excluded letter fluency tasks while no age effects were found for phonemic and alternating fluency. Interpretation of verbal fluency performances need to be tailored according to which verbal fluency variant and age group are used.
Authors: Daniel E Gustavson; Matthew S Panizzon; Jeremy A Elman; Carol E Franz; Asad Beck; Chandra A Reynolds; Kristen C Jacobson; Hong Xian; Rosemary Toomey; Michael J Lyons; William S Kremen Journal: Behav Genet Date: 2018-06-19 Impact factor: 2.805
Authors: Rosaleena Mohanty; Lissett Gonzalez-Burgos; Lucio Diaz-Flores; J-Sebastian Muehlboeck; José Barroso; Daniel Ferreira; Eric Westman Journal: Front Aging Neurosci Date: 2021-07-05 Impact factor: 5.750