Verbal fluency test

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Verbal fluency tests are a kind of psychological test in which participants have to say as many words as possible from a category in a given time (usually 60 seconds). This category can be semantic, such as animals or fruits, or phonemic, such as words that begin with letter p.[1] The semantic fluency test is sometimes described as the category fluency test or simply as 'freelisting'. The COWAT (Controlled oral word association test) is the most employed phonetic variant.[2][3] Although the most common performance measure is the total number of words, other analyses such as number of repetitions, number and length of clusters of words from the same semantic or phonetic subcategory, or number of switches to other categories can be carried out.[4][5]

Performance characteristics[edit]

Performance in verbal fluency tests show a number of consistent characteristics in both children and adults:[6][7][8]

Neural correlates[edit]

Regarding the brain areas used in this task, neuropsychological investigations implicate both frontal and temporal lobe areas, the contribution of the former being more important in the phonemic variant and of the latter in the semantic variant.[9] Accordingly different neurological pathologies affecting these areas produce impairments (typically a reduction in the number of items generated) in one or both versions of the task.[3] For this reason fluency tests are commonly included in clinical batteries,[1] they have also been widely used in cognitive psychological and neuropsychological investigations.

Exploration of semantic memory[edit]

Cluster analysis of animal semantic fluency data from British schoolchildren.[10]

Priming studies indicate that when a word or concept is activated in memory, and then spoken, it will activate other words or concepts which are associatively related or semantically similar to it. This evidence suggests that the order in which words are produced in the fluency task will provide an indirect measure of semantic distance between the items generated. Data from this semantic version of the task have therefore been the subject of many studies aimed at uncovering the structure of semantic memory, determining how this structure changes during normal development, or becomes disorganized through neurological disease or mental illness.

These studies generally make use of multiple fluency lists in order to make estimates of the semantic distance between pairs of concepts.[11] Techniques such as multidimensional scaling and hierarchical clustering can then be used to visualize the semantic organization of the conceptual space. Such studies have generally found that semantic memory, at least as reflected by this test, has a schematic, or script-based, organization.[12] whose core aspects may remain stable throughout life.[10][13] For instance, the figure on the right shows a hierarchical clustering analysis of animal semantic fluency data from 55 British schoolchildren aged 7–8.[10] The analysis reveals that children have schematic organization for this category according to which animals are grouped by where they are most commonly seen (on the farm, at home, in the ocean, at the zoo). Children, adults, and even zoology PhD candidates, all show this same tendency to cluster animals according to the environmental context in which they are observed.[14]

It has been proposed that the semantic memory organization, underlying performance in the semantic fluency test, becomes disordered as the result of some forms of neuropsychological disorder such as Alzheimer's disease[15] and schizophrenia,[16][17][18] however, the evidence for this has been queried on theoretical and methodological grounds.[11][19]

See also[edit]

References[edit]

  1. ^ a b Lezak, Muriel Deutsch (1995). Neuropsychological assessment. Oxford [Oxfordshire]: Oxford University Press. ISBN 0-19-509031-4. 
  2. ^ Loonstra AS, Tarlow AR, Sellers AH (2001). "COWAT metanorms across age, education, and gender". Appl Neuropsychol 8 (3): 161–6. doi:10.1207/S15324826AN0803_5. PMID 11686651. 
  3. ^ a b Ardila, A.; Ostrosky-solís, F.; Bernal, B. (2006). "Cognitive testing toward the future: The example of Semantic Verbal Fluency (ANIMALS)" (– Scholar search). International Journal of Psychology 41 (5): 324–332. doi:10.1080/00207590500345542. Retrieved 2011-10-19. 
  4. ^ Troyer AK, Moscovitch M, Winocur G (January 1997). "Clustering and switching as two components of verbal fluency: evidence from younger and older healthy adults". Neuropsychology 11 (1): 138–46. doi:10.1037/0894-4105.11.1.138. PMID 9055277. 
  5. ^ Troyer AK, Moscovitch M, Winocur G, Leach L, Freedman M (March 1998). "Clustering and switching on verbal fluency tests in Alzheimer's and Parkinson's disease". J Int Neuropsychol Soc 4 (2): 137–43. doi:10.1017/S1355617798001374. PMID 9529823. 
  6. ^ Henley NM (1969). "A psychological study of the semantics of animal terms". J Verbal Learning and Verbal Behav 8 (2): 176–184. doi:10.1016/S0022-5371(69)80058-7. 
  7. ^ Gruenewald PJ, Lockhead GR (1980). "The free recall of category examples". J Exp Psych: Human Learning and Memory 6 (3): 225–241. doi:10.1037/0278-7393.6.3.225. 
  8. ^ Kail R, Nippold MA (1984). "Unconstrained retrieval from semantic memory". Child Development (Child Development, Vol. 55, No. 3) 55 (3): 944–951. doi:10.2307/1130146. JSTOR 1130146. PMID 6734329. 
  9. ^ Baldo JV, Schwartz S, Wilkins D, Dronkers NF (November 2006). "Role of frontal versus temporal cortex in verbal fluency as revealed by voxel-based lesion symptom mapping". J Int Neuropsychol Soc 12 (6): 896–900. doi:10.1017/S1355617706061078. PMID 17064451. 
  10. ^ a b c Crowe SJ, Prescott TJ (2003). "Continuity and change in the development of category structure: Insights from the semantic fluency task". Int J Behav Dev 27 (5): 467–479. doi:10.1080/01650250344000091. 
  11. ^ a b Prescott TJ, Newton LD, Mir NU, Woodruff P, Parks RW (2006). "A new dissimilarity measure for finding semantic structure in category fluency data with implications for understanding memory organization in schizophrenia". Neuropsychology 20 (5): 685–699. doi:10.1037/0894-4105.20.6.685. PMID 17100513. 
  12. ^ Lucariello J, Kyratzis A, Nelson K (1992). "Taxonomic knowledge - what kind and when". Child Development (Child Development, Vol. 63, No. 4) 63 (4): 978–998. doi:10.2307/1131248. JSTOR 1131248. 
  13. ^ Mandler JM. "Representation". In Flavell JH, Markman EM. Cognitive development 3. New York: Wiley. 
  14. ^ Storm C (1980). "The semantic structure of animal terms - a developmental-study". Int J Behav Dev 3 (4): 381–407. doi:10.1177/016502548000300403. 
  15. ^ Chan AS, Butters N, Salmon DP, Johnson SA, Paulsen JS, Swenson MR (1995). "Comparison of the semantic networks in patients with dementia and amnesia". Neuropsychology 9 (2): 177–186. doi:10.1037/0894-4105.9.2.177. 
  16. ^ Aloia AS, Gourovitch ML, Weinberger DR, Goldberg TE (1996). "An investigation of semantic space in patients with schizophrenia". J Int Neuropsychological Society 2 (04): 267–273. doi:10.1017/S1355617700001272. 
  17. ^ Paulsen JS, Romero R, Chan AS, Davis AV, Heaton R.K, Jeste DV (1996). "Impairment of the semantic network in schizophrenia". Psychiatry Research 63 (2–3): 109–121. doi:10.1016/0165-1781(96)02901-0. PMID 8878307. 
  18. ^ Sumiyoshi C, Matsui M, Sumiyoshi T, Yamashita I, Sumiyoshi S, Kurachi M (2001). "Semantic structure in schizophrenia as assessed by the category fluency test: Effect of verbal intelligence and age of onset". Psychiatry Research 105 (3): 187–199. doi:10.1016/S0165-1781(01)00345-6. PMID 11814538. 
  19. ^ Storms G, Dirikx T, Saerens J, Verstraeten S, De Deyn PP (2003). "On the use of scaling and clustering in the study of semantic deficits". Neuropsychology 17 (2): 289–301. doi:10.1037/0894-4105.17.2.289. PMID 12803435. 

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