Large language models (LLMs) are raging over the medical domain, and their
momentum has carried over into the mental health domain, leading to the
emergence of few mental health LLMs. Although such mental health LLMs could
provide reasonable suggestions for psychological counseling, how to develop an
authentic and effective doctor-patient relationship (DPR) through LLMs is still
an important problem. To fill this gap, we dissect DPR into two key attributes,
i.e., the psychologist's empathy and proactive guidance. We thus present
WundtGPT, an empathetic and proactive mental health large language model that
is acquired by fine-tuning it with instruction and real conversation between
psychologists and patients. It is designed to assist psychologists in diagnosis
and help patients who are reluctant to communicate face-to-face understand
their psychological conditions. Its uniqueness lies in that it could not only
pose purposeful questions to guide patients in detailing their symptoms but
also offer warm emotional reassurance. In particular, WundtGPT incorporates
Collection of Questions, Chain of Psychodiagnosis, and Empathy Constraints into
a comprehensive prompt for eliciting LLMs' questions and diagnoses.
Additionally, WundtGPT proposes a reward model to promote alignment with
empathetic mental health professionals, which encompasses two key factors:
cognitive empathy and emotional empathy. We offer a comprehensive evaluation of
our proposed model. Based on these outcomes, we further conduct the manual
evaluation based on proactivity, effectiveness, professionalism and coherence.
We notice that WundtGPT can offer professional and effective consultation. The
model is available at huggingface.

通过 fine-tuning 和真实对话，我们提出了一种具有共情和主动指导特性的心理健康大型语言模型 WundtGPT，以协助心理学家在诊断中提问和症状详述的引导以及情感上的温暖安抚。