What Drives Task Performance During Animal Fluency in People With Alzheimer’s Disease?
dc.creator | Rofes, A | |
dc.creator | de Aguiar, V | |
dc.creator | Jonkers, R | |
dc.creator | Oh, SJ | |
dc.creator | DeDe, G | |
dc.creator | Sung, JE | |
dc.date.accessioned | 2020-12-15T20:21:24Z | |
dc.date.available | 2020-12-15T20:21:24Z | |
dc.date.issued | 2020-07-21 | |
dc.identifier.issn | 1664-1078 | |
dc.identifier.issn | 1664-1078 | |
dc.identifier.doi | http://dx.doi.org/10.34944/dspace/4448 | |
dc.identifier.other | NA8LP (isidoc) | |
dc.identifier.other | 32774312 (pubmed) | |
dc.identifier.uri | http://hdl.handle.net/20.500.12613/4466 | |
dc.description.abstract | © Copyright © 2020 Rofes, de Aguiar, Jonkers, Oh, DeDe and Sung. Background: Animal fluency is a widely used task to assess people with Alzheimer’s disease (AD) and other neurological disorders. The mechanisms that drive performance in this task are argued to rely on language and executive functions. However, there is little information regarding what specific aspects of these cognitive processes drive performance on this task. Objective: To understand which aspects of language (i.e., semantics, phonological output lexicon, phonological assembly) and executive function (i.e., mental set shifting; information updating and monitoring; inhibition of possible responses) are involved in the performance of animal fluency in people with AD. Methods: Animal fluency data from 58 people with probable AD from the DementiaBank Pittsburgh Corpus were analyzed. Number of clusters and switches were measured and nine word properties (e.g., frequency, familiarity) for each of the correct words (i.e., each word counting toward the total score, disregarding non-animals and repetitions) were determined. Random forests were used to understand which variables predicted the total number of correct words, and conditional inference trees were used to search for interactions between the variables. Finally, Wilcoxon tests were implemented to cross-validate the results, by comparing the performance of participants with scores below the norm in animal fluency against participants with scores within the norm based on a large normative sample. Results: Switches and age of acquisition emerged as the most important variables to predict total number of correct words in animal fluency in people with AD. Cross-validating the results, people with AD whose animal fluency scores fell below the norm produced fewer switches and words with lower age of acquisition than people with AD with scores in the normal range. Conclusion: The results indicate that people with AD rely on executive functioning (information updating and monitoring) and language (phonological output lexicon, not necessarily semantics) to produce words on animal fluency. | |
dc.format.extent | 1485- | |
dc.language.iso | eng | |
dc.relation.haspart | Frontiers in Psychology | |
dc.relation.isreferencedby | Frontiers Media SA | |
dc.rights | CC BY | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | fluency | |
dc.subject | category | |
dc.subject | animal | |
dc.subject | switches | |
dc.subject | clusters | |
dc.subject | age of acquisition | |
dc.title | What Drives Task Performance During Animal Fluency in People With Alzheimer’s Disease? | |
dc.type | Article | |
dc.type.genre | Journal Article | |
dc.relation.doi | 10.3389/fpsyg.2020.01485 | |
dc.ada.note | For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu | |
dc.date.updated | 2020-12-15T20:21:21Z | |
refterms.dateFOA | 2020-12-15T20:21:25Z |