Designing an Empathetic Conversational Agent for Student Mental Health: A Pilot Study

This study presents the design and evaluation of a conversational agent aimed at supporting university students' mental health. We implemented two variants of a chatbot, referred to as A1 and A2, using large language models (LLMs). A1 employed a baseline prompt reflecting a structured yet neutral counseling style, while A2 was an enhanced version incorporating feedback from psychiatrists and findings from a preliminary study. Emotionally rich expressions, conversational variation, and mild self-disclosure are introduced in A2. A mixed-method user study with 18 participants was conducted to compare A1, A2, and human interactions. Results indicated that A2 significantly improved users’ perception of empathy and engagement compared to A1, though human-level rapport was not fully achieved. These findings highlight the role of prompt design in creating emotionally responsive AI companions for mental health support.

@article{Minami2025,
  title     = {Designing an Empathetic Conversational Agent for Student Mental Health: A Pilot Study},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {7},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Kaichi Minami and Choi Dongeun and Panote Siriaraya and Noriaki Kuwahara},
  doi       = {10.14569/IJACSA.2025.0160702},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160702}
}