@inproceedings{yoshida-etal-2025-examining,
    title = "Examining Older Adults' Motivation for Interacting with Health-Monitoring Conversational Systems Through Field Trials",
    author = "Yoshida, Mariko  and
      Hori, Ryo  and
      Zenimoto, Yuki  and
      Urata, Mayu  and
      Endo, Mamoru  and
      Yasuda, Takami  and
      Inoue, Aiko  and
      Hayashi, Takahiro  and
      Higashinaka, Ryuichiro",
    editor = "Torres, Maria Ines  and
      Matsuda, Yuki  and
      Callejas, Zoraida  and
      del Pozo, Arantza  and
      D'Haro, Luis Fernando",
    booktitle = "Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology",
    month = may,
    year = "2025",
    address = "Bilbao, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.iwsds-1.8/",
    pages = "103--114",
    ISBN = "979-8-89176-248-0",
    abstract = "When assessing the health of older adults, oral interviews and written questionnaires are commonly used. However, these methods are time-consuming in terms of both execution and data aggregation. To address this issue, systems utilizing generative AI for health information collection through conversation have been developed and implemented. Despite these advancements, the motivation of older adults to consistently engage with such systems in their daily lives has not been thoroughly explored. In this study, we developed a smart-speaker extension that uses generative AI to monitor health status through casual conversations with older adult users. The system was tested in a two-week home trial with older adult participants. We conducted post-trial questionnaires and interviews, and we analyzed conversation log data. The results revealed that older adult users enjoy interacting with such systems and can integrate their use into their daily routines. Customized notifications through text messages encouraged system use, and the system{'}s ability to refer to previous conversations and address users by name was identified as a key factor motivating continued use."
}