Social difficulties have become an increasingly serious issue among older adults. For older adults, regular self-disclosure is essential for maintaining mental health and building close relationships. Leveraging conversational agents to encourage self-disclosure in older adults has shown increasing potential. Understanding how LLM-based agents can influence and stimulate self-disclosure across different topics is crucial for designing future agents tailored to older users. This study introduces Disclosure-Agent, an LLM-based conversational agent, and examines its impact on self-disclosure in older adults through a user study involving 20 participants, 8 topics, and two interactive interfaces equipped with Disclosure-Agent. The findings provide valuable insights into how LLM-based agents can promote self-disclosure in older adults and offer design recommendations for future elderly-oriented conversational agents.
https://dl.acm.org/doi/10.1145/3706598.3713639
As the global population ages, there is increasing need for accessible technologies that promote cognitive health and detect early signs of cognitive decline. This research demonstrates the potential for in-residence monitoring and assessment of cognitive health using large language model (LLM)-powered socially assistive robots (SARs). We conducted a 5-week within-subjects study involving 22 older adults in retirement homes to investigate the feasibility of LLM-powered SARs for promoting and assessing cognitive health. We designed tasks that involved verbal dialogue based on clinically validated cognitive tools. Our findings reveal improved task performance after three robot-administered sessions, with significantly more detailed picture descriptions, fewer word repetitions in semantic fluency, and reduced need for hints. We found that older adults were more socially engaged in robot-administered tasks compared to those administered by a human, and they accepted and were willing to engage with SARs in this context, which had not been tested before.
As the global aging population grows and technology advances rapidly, integrating technology into community-based initiatives for older adults has become an increasingly important topic among HCI researchers. This research explores the role of Information and Communication Technology (ICT) tools in the co-creation and maintenance of a community gardening program involving researchers, older adult residents, and supporting organizations. A follow-up study, conducted eight months after the program’s initiation assessed its sustainability, revealing how stakeholders navigated diverse ICT preferences and challenges by employing a hybrid communication system that integrated both digital and face-to-face methods to foster collaboration and sustain the initiative. This research contributes to the understanding of community preferences and needs, and the importance of contextualizing technology use within Japanese local community for collaborative community development.
https://dl.acm.org/doi/10.1145/3706598.3714158
Despite recent advances in cancer treatments that prolong patients' lives, treatment-induced cardiotoxicity (i.e., the various heart damages caused by cancer treatments) emerges as one major side effect. The clinical decision-making process of cardiotoxicity is challenging, as early symptoms may happen in non-clinical settings and are too subtle to be noticed until life-threatening events occur at a later stage; clinicians already have a high workload focusing on the cancer treatment, no additional effort to spare on the cardiotoxicity side effect. Our project starts with a participatory design study with 11 clinicians to understand their decision-making practices and their feedback on an initial design of an AI-based decision-support system. Based on their feedback, we then propose a multimodal AI system, CardioAI, that can integrate wearables data and voice assistant data to model a patient's cardiotoxicity risk to support clinicians' decision-making. We conclude our paper with a small-scale heuristic evaluation with four experts and the discussion of future design considerations.
https://dl.acm.org/doi/10.1145/3706598.3714272
Polycystic ovary syndrome (PCOS) is a common hormonal disorder affecting 11-13% of women of reproductive age, characterized by a wide range of symptoms (e.g., menstrual irregularity, acne, and obesity) that varies among individuals. While self-tracking tools help PCOS patients to monitor their symptoms and find personalized treatment, they often focus on regular periods of healthy women with inadequate support for the 1) personalization and 2) long-term holistic tracking necessary for managing complex chronic conditions like PCOS. To bridge this gap, the first author (who has PCOS) conducted an autoethnographic study of holistic self-tracking over a period of ten months in an effort to manage her condition. Our results highlight the challenges of personalized, holistic, long-term tracking in medical, socio-cultural, temporal, technical, and spatial contexts. Based on these insights, we provide design implications for tracking tools that are more inclusive and sustainable.
Social Virtual Reality (VR) presents a promising avenue for older adults to connect with others and engage in collaborative activities remotely. However, many social VR experiences focus on individual tasks, reducing opportunities for meaningful social interaction. To investigate the potential of VR to enhance engagement with other participants, this paper explores two modes of coupling: (i) loosely coupled, where participants focus on their individual tasks within a collaborative setting, and (ii) tightly coupled, where participants need to rely on each other’s assistance to complete their tasks. We conducted a user study with 20 older adults to evaluate how these modes affect task performance and engagement. Results show that the tightly coupled mode, focused on collaboration, increases engagement, while the loosely coupled mode, centers on individual tasks, improves performance in time and attempts. We provide guidelines for collaborative VR applications to enhance social engagement and interaction among older adults.
https://dl.acm.org/doi/10.1145/3706598.3713345
Wearable augmented reality (AR) systems have significant potential to enhance surgical outcomes through in-situ visualization of patient-specific data. Yet, efforts to develop AR-based systems for open surgery have been limited, lacking comprehensive interdisciplinary research and actual clinical evaluations in real surgical environments. Our research addresses this gap by presenting a user-centered design and development process of ARAS, an AR assistance for open pancreatic surgery. ARAS provides in-situ visualization of critical structures, such as the vascular system and the tumor, while offering a robust dual-layer registration method ensuring accurate registration during relevant phases of the surgery. We evaluated ARAS in clinical trials of 20 patients with pancreatic tumors. Accuracy validation and postoperative surgeon interviews confirmed its successful deployment, supporting surgeons in vascular localization and critical decision-making. Our work showcases AR's potential to fundamentally transform procedures for complex surgical operations, advocating a research shift toward ecological validation in open surgery.
https://dl.acm.org/doi/10.1145/3706598.3713458