  Despite the global mental health crisis, access to screenings, professionals,
and treatments remains high. In collaboration with licensed psychotherapists,
we propose a Conversational AI Therapist with psychotherapeutic Interventions
(CaiTI), a platform that leverages large language models (LLM)s and smart
devices to enable better mental health self-care. CaiTI can screen the
day-to-day functioning using natural and psychotherapeutic conversations. CaiTI
leverages reinforcement learning to provide personalized conversation flow.
CaiTI can accurately understand and interpret user responses. When the user
needs further attention during the conversation, CaiTI can provide
conversational psychotherapeutic interventions, including cognitive behavioral
therapy (CBT) and motivational interviewing (MI). Leveraging the datasets
prepared by the licensed psychotherapists, we experiment and microbenchmark
various LLMs' performance in tasks along CaiTI's conversation flow and discuss
their strengths and weaknesses. With the psychotherapists, we implement CaiTI
and conduct 14-day and 24-week studies. The study results, validated by
therapists, demonstrate that CaiTI can converse with users naturally,
accurately understand and interpret user responses, and provide
psychotherapeutic interventions appropriately and effectively. We showcase the
potential of CaiTI LLMs to assist the mental therapy diagnosis and treatment
and improve day-to-day functioning screening and precautionary
psychotherapeutic intervention systems.
