Do Large Language Models provide clinical forecasts for depression prognosis comparable to mental health professionals?
While most tested LLMs mirror expert clinical forecasts for depression prognosis, pessimistic biases in specific models highlight the need for thorough verification before clinical integration.
This study underscores the potential of AI to complement the expertise of mental health professionals and promote a collaborative paradigm in mental healthcare. The observation that three of the four LLMs closely mirrored the anticipations of mental health experts in scenarios involving treatment underscores the technology's prospective value in offering professional clinical forecasts. The pessimistic outlook presented by ChatGPT 3.5 is concerning, as it could potentially diminish patients' drive to initiate or continue depression therapy. In summary, although LLMs show potential in enhancing healthcare services, their utilisation requires thorough verification and a seamless integration with human judgement and skills.
Elyoseph et al. (Mon,) studied this question.