JOURNAL ARTICLE

Conversation Analysis of Texting Exchanges in Aphasia.

  • Published In: American Journal of Speech-Language Pathology, 2023, v. 32, n. 6. P. 2512 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Azios, Jamie H.; Lee, Jaime B.; Cherney, Leora R. 3 of 3

Abstract

Purpose: Conversation analysis (CA) is an established method that has been used to understand how aphasia impacts the conversational success of individuals with aphasia (IWAs) and their conversation partners. This article demonstrates CA as a valuable analytic tool for studying text messaging in aphasia to better understand the specific co-constructed actions of IWAs and their partners as they engage in this communication modality. Method: CA was applied to transcribed text message data from eight IWAs. Conversational structures present in face-to-face interactions were identified, segmented, and explicated with a focus on how IWAs and their partners negotiate interaction in this medium. Results: Three key elements of CA, namely, sequential organization, repair, and topic negotiation, were identified within the texting exchanges of participants and their texting partners and compared with existing CA studies on electronic messaging in adults without brain injury. Conclusions: Findings suggest a multitude of strategies that IWAs and their partners used to meet both transactional and interactional goals of communication. Understanding gained from applying CA to texting in aphasia can inform the development of interventions that improve access to digital communication for IWAs. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:American Journal of Speech-Language Pathology. 2023/10, Vol. 32, Issue 6, p2512
  • Document Type:Article
  • Subject Area:Communication and Mass Media
  • Publication Date:2023
  • ISSN:1058-0360
  • DOI:10.1044/2023_AJSLP-22-00303
  • Accession Number:173108081
  • Copyright Statement:Copyright of American Journal of Speech-Language Pathology is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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