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Title
Japanese: 
English:Decoding the Language of Care: A Typology of Caregiver Utterances and Their Influence on Assistive Technology Use 
Author
Japanese: 小森 丈瑠, 佐久間 大, 西條 美紀, 大橋 匠.  
English: Takeru KOMORI, Dai SAKUMA, Miki SAIJO, Takumi OHASHI.  
Language English 
Journal/Book name
Japanese: 
English:Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS 
Volume, Number, Page Vol. 3        pp. 286-293
Published date Nov. 2023 
Publisher
Japanese: 
English: 
Conference name
Japanese: 
English:15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management 
Conference site
Japanese: 
English:Rome 
Official URL https://kmis.scitevents.org/?y=2023
 
DOI https://doi.org/10.5220/0012234800003598
Abstract Amid a global caregiver shortage and a growing reliance on assistive technology, this research investigates the intricate interactions between caregivers and care recipients in elder care settings, primarily focusing on caregivers’ verbal utterances and the conditions under which these exchanges occur. Drawing on Weiner’s causal attribution theory, we developed a typology of caregiver utterances that prompt shifts in care recipients’ attributions during the use of assistive technology. This typology—comprised of ’praise’, ’affirmation /acceptance’, ’confirmation’, and ’feedback’ categories—illuminates key links between caregiver communication strategies and care recipients’ perception shifts. Notably, ’confirmation’ utterances tend to align with attributions to ’ability’, whereas ’feedback’ utterances correspond more closely with ’effort’. Our analysis of temporal fluctuations revealed significant changes in the frequency of these utterances throughout various stages of assistive technology usage. By offering a holistic understanding of these complex dynamics, this study seeks to shape the development of more effective caregiver communication strategies. Such enhancements are pivotal to optimize care recipients’ experiences and engagement with assistive technology, thus addressing the ongoing caregiver deficit. Future research endeavors will expand our dataset and examine the potential generalizability of our findings to other caregiving environments.

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