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
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)