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Journal of neurolinguistics, 2024-05, Vol.70, p.101189, Article 101189
2024
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Autor(en) / Beteiligte
Titel
Can we track the progression of Alzheimer's Disease via lexical-semantic variables in connected speech?
Ist Teil von
  • Journal of neurolinguistics, 2024-05, Vol.70, p.101189, Article 101189
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2024
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • Alzheimer's disease (AD) is one of the most common neurodegenerative disorders worldwide and is characterized by problems with cognition and language, especially word-finding difficulties. The present study focuses on lexical-semantic features via five discourse variables reflecting word-finding difficulties, namely indefinite terms, lexical frequency, repetitions, semantic paraphasias, and use of pronouns. Our aim is twofold: testing whether these variables can discriminate healthy aging from AD, but also mild from moderate AD. 105 participants were examined from the existing Pitt corpus (available on DementiaBank), which includes the Cookie Theft Picture Description task. 40 participants were healthy controls, 25 were mild AD participants, and 40 moderate AD participants. The moderate AD group differed significantly from healthy controls in terms of indefinite terms, repetitions, semantic paraphasias, and pronouns. For the latter variable, mild AD patients also differed significantly from healthy controls. However, none of the variables could differentiate mild from moderate AD. Four out of five discourse variables could discriminate healthy aging from moderate AD, while only one could discriminate mild AD patients. This is therefore questioning current literature on connected-speech measures in AD and calling for further research on the variables that could better distinguish mild to moderate AD. •Connected-speech measures can discriminate healthy aging from moderate AD.•Connected-speech measures cannot discriminate mild from moderate AD.•Only the proportion of pronouns can discriminate healthy aging from mild AD.
Sprache
Englisch
Identifikatoren
ISSN: 0911-6044
eISSN: 1873-8052
DOI: 10.1016/j.jneuroling.2023.101189
Titel-ID: cdi_crossref_primary_10_1016_j_jneuroling_2023_101189

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