To make a long story short: A descriptive study of formulaic language use in post-stroke fluent aphasia

ABSTRACTBackground Language sample analysis is a common tool for inventorying an individual’s linguistic strengths and weaknesses. Although most research has focused on quantifying propositional or novel language production, studies suggest that individuals with aphasia, specifically nonfluent aphasia, produce high percentages of formulaic language relative to healthy controls. To date, little is known about how individuals with fluent aphasia subtypes use formulaic language and how the elicitation task influences their production.Aims The purpose of this research was to comprehensively describe patterns of formulaic language use in various discourse tasks in language samples of individuals with fluent aphasia.Methods & Procedures The retrospective analysis included discourse samples from Aphasiabank from 142 individuals with anomic, conduction, and Wernicke’s aphasia across four monologic discourse tasks. After identifying and classifying formulaic items into nine types, percentages of formulaic language were calculated for each participant and discourse task. Non-parametric statistics and Pearson’s correlations were used to compare production patterns and explore relationships between language severity and formulaic item types.Outcomes & Results Unique patterns of formulaic language were observed across groups including lower proportions of fillers in individuals with Wernicke’s aphasia and higher proportions of yes/no variants and speech formulas in individuals with conduction aphasia. Production patterns were most influenced by discourse task in individuals with anomic aphasia. Formulaic language use did not correlate with aphasia severity as measured by aphasia quotient.Conclusions Findings add to the evidence base describing formulaic language usage in individuals with post-stroke aphasia, which serves as a necessary foundation for eventual clinical application.KEYWORDS: Formulaic languageaphasiaspontaneous speech AcknowledgementsWe wish to thank Melanie Smith, Emily Lafitte, and the members of the San Antonio Network for Aphasia (SANA) Lab for their endless hours spent coding transcripts. Thanks also to Brian MacWhinney, Davida Fromm, contributing researchers, and willing participants for their invaluable support and contributions to Aphasiabank.Disclosure statementThe authors report there are no competing interests to declare.