Patient insights into empathy, compassion and self-disclosure in medical large language models: results from the IPALLM III study - Carl, Nicolas; Haggenmüller, Sarah; Winterstein, Jana Therés; Nguyen, Lisa; Wies, Christoph; Hetz, Martin Joachim; Mangold, Maurin Helen; Grüne, Britta; Michel, Maurice Stephan; Brinker, Titus Josef; Wessels, Frederik (World journal of urology, 2025)
Large language models (LLMs) offer promising applications in healthcare communication, including the provision of medical information and simulation of empathetic responses. However, the extent to which patients perceive such interactions as empathetic remains unclear. This study explores urological patients’ perceptions of empathy and compassion in interactions with an LLM-powered chatbot, as well as their willingness to disclose personal information.