Examining Older Adults’ Motivation for Interacting with Health-Monitoring Conversational Systems Through Field Trials (2025)

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.

## introduction in japan, the population of older adults aged 65 and above, as well as their proportion to the total population, continues to rise, and this trend is expected to persist in the future @xcite . further increases in average life expectancy are also projected (national institute of @xcite . as the gap between average life expectancy and healthy life expectancy-defined as the period during which individuals can live without limitations due to health issues-widens, the 'unhealthy period' grows. this not only prevents older adults from leading healthy and fulfilling lives but also contributes to increased social security costs, making efforts to extend healthy life expectancy crucial. the intermediate stage between a healthy state and a condition requiring care is referred to as frailty. preventing frailty is key to extending healthy life expectancy @xcite . frailty is often assessed using @xcite criteria, which include grip strength, walking speed, exhaustion, physical activity, and unintentional weight loss. recently, questionnairebased screening with 25 questions has been validated and gained popularity @xcite . however, these approaches are timeconsuming and labor-intensive. to address this issue, voice-based dialogue systems have been proposed @xcite . these systems utilize generative ai (artificial intelligence), particularly large language models. by leveraging such dialogue systems to continuously collect health information from older adults, it is possible to provide health support that considers changes in lifestyle habits and health conditions. these systems focus especially on frailty, since it has been shown to be associated with future falls @xcite , mobility impairments @xcite , difficulties in activities of daily living @xcite , hospitalization @xcite , and overall mortality @xcite . for these systems to be effective, it is essential to develop enjoyable features that encourage older adults to use them consistently. however, there is insufficient research and empirical evidence on enjoyable dialogue systems that older adults can continuously use at home. this study aims to develop a system that utilizes generative ai to obtain health information from older adults through casual conversations. through actual use of this system by older adults, the study will verify whether they can enjoy its continuous use. furthermore, we seek to identify features that motivate older adults to engage with and utilize the conversational system. ## previous research research on using voice-based interaction for supporting older adults has been conducted in various ways. first, several initiatives have utilized generative ai and dialogue systems to collect health information. in okayama city, japan, demonstration experiments have been conducted using ai avatars for frailty health checks at frailty prevention events and pharmacies (hyper cube, 2023). additionally, 'multimodal interactive care support system' (micsus), a stuffed toy-like device designed for caregiving monitoring, was tested with the aim of reducing the workload of care managers during interviews @xcite . although not voice-based, @xcite demonstrated that older adults perceive chatbot-delivered health assessments as easy to use, useful, user-friendly, and low in cognitive load. @xcite proposed a chatbot that collects and predicts health data through conversations with older adults, demonstrating its usefulness for health management tasks. furthermore, in the field of supporting older adults, there have been initiatives such as smart speaker-based support systems @xcite @xcite and schedule management systems @xcite . @xcite developed a schedule management system for older adults and demonstrated that socially cooperative dialogue plays a crucial role in its acceptability and continued use. additionally, dialogue systems for health interventions have been proposed, with @xcite demonstrating that agent behavior diversity and self-disclosure influence user engagement in systems designed for long-term health interventions. in these implementations, the system is used for specific tasks rather than free-form casual conversations. however, for the continuous collection of health information and ongoing support-which require daily voluntary use-free-form casual conversations may be more readily accepted by older adults than structured interviews due to their natural and enjoyable interaction style. on the other hand, research on free-form casual conversations has primarily focused on dialogue systems aimed at alleviating loneliness among older adults @xcite @xcite ; shitaoka et al., 2017). however, there has been limited research involving field evaluations to explore the factors that motivate continued use of such systems. since free-form casual conversation systems depend on voluntary engagement, it is important to explore what encourages users to interact with them continuously, particularly in the context of health monitoring. previous research on casual dialogue systems highlights that referencing past interactions enhances engagement @xcite and system self-disclosure fosters perceived intimacy @xcite . however, their effects on older adults remain underexplored. therefore, this study aims to enable older adults to use a voice-based conversational system for freeform casual conversations at home. it seeks to identify the features and functions that are crucial for enhancing and sustaining their motivation to use such systems. ## discussion participants were able to enjoyably incorporate the casual conversational system into their daily lives, and a sufficient number of responses regarding health indicators were collected. log data analysis revealed that participants used the system more frequently than instructed and engaged in lengthy conversations during each activation. these findings suggest that acquiring health information through generative ai-based casual conversations can be a sustainable method for monitoring older adults' health without imposing a burden on them. key conversation features that motivated participants to use the system included remembering what users talked about, addressing users by their names, and discussing the character's schedule. previous research has highlighted the importance of a system's self-disclosure in enhancing perceived intimacy among general users @xcite , and our findings suggest that the system's self-disclosure is also crucial for encouraging older adults' engagement in conversations. the frequent occurrence of topics related to "today," as revealed by the analysis of participant utterances, indicates that a conversational system that discusses the character's schedule or inquires about the user's plans can be effective when used routinely at home. thus, incorporating these features into dialogue systems for older adults is essential. additionally, starting conversations in a friendly manner, such as with greetings, can be effective. the analysis also found that participants frequently used words related to meals. for systems targeting older adults, emphasizing conversations about food could make the system more appealing and encourage usage. many participants interacted with the system after receiving line messages, indicating that personalized messages can serve as effective reminders to utilize the conversational system. previous research has shown that referencing past interactions in dialogue systems fosters a stronger sense of connection and engagement among general users @xcite . our results similarly suggest that, for older adults, sending messages related to previous conversations helps foster a sense of attachment to the character. participant feedback suggested that sending messages related to previous conversations fostered a sense of attachment to the character. analysis of log data also showed that the system was frequently used around dinner time and before bedtime, suggesting that prompts or messages from the system would be most effective if sent during the evening hours. additionally, 9 out of 11 participants reported that quizzes increased their willingness to engage in conversation, with nearly half of the participants using the quiz feature almost daily. this implies that daily quizzes could serve as an effective incentive for consistent usage. however, some participants expressed dissatisfaction with the lack of a correct/incorrect judgment in the quizzes, since the system did not engage in conversation during the quiz. consequently, when integrating such daily content into the dialogue system, it is necessary to implement features that blend seamlessly into the conversation to avoid causing discomfort for users. ## conclusion in this study, a system was developed to support the health of older adults by obtaining health-related information through casual conversations. the system was used by older adults, and an investigation was conducted to identify the factors that contribute to usage motivation. participants were able to enjoy using the conversational system, and through surveys, interviews, and analysis of usage logs, key features that encourage usage were identified. in the future, we aim to involve a larger number of participants and validate our findings through statistical analyses, including significance testing, as this study primarily focused on qualitative analysis. this approach will also enable us to quantitatively assess the final system, incorporating the improvements made based on feedback from both the preliminary and demonstration experiments conducted in this study. additionally, providing topics that are more relatable to older adults and enabling conversations with less discomfort could make the conversational system even more enjoyable for them. additionally, since opinions about the character's attributes were divided, allowing users to choose their preferred attributes could further enhance motivation.