Large language models outperform mental and medical health care...
Despite the promising capacity of large language model (LLM)-powered chatbots to diagnose diseases, they have not been tested for obsessive-compulsive disorder (OCD). We assessed the diagnostic accuracy of LLMs in OCD using vignettes and found that LLMs outperformed medical and mental health professionals. This highlights the potential benefit of LLMs in assisting in the timely and accurate diagnosis of OCD, which usually entails a long delay in diagnosis and treatment.
Professional-level Knowledge
Large language model (LLM)-powered artificial intelligence (AI) chatbots exhibit professional-level knowledge across multiple medical specialty areas. They have been evaluated for disease detection, treatment suggestions, medical education, and triage assistance. Moreover, their ability in advanced clinical reasoning holds promise in assisting in a physician’s diagnosis and treatment planning.
In a statement from the American Psychiatric Association (APA), caution was urged in the use of LLM tools in clinical decision-making. Yet a recent survey revealed that many psychiatrists use LLMs in answering clinical questions and documenting notes, believing that LLMs would improve diagnostic accuracy in psychiatry. Given the interest and current usage, rigorous study of these tools is urgently needed.
Obsessive-Compulsive Disorder (OCD)
Obsessive-compulsive disorder (OCD) is a common mental health condition where individuals perform repetitive behaviors (compulsions) to avoid unwanted thoughts or sensations (obsessions), significantly disrupting daily lives. It affects approximately 1 in 40 adults in the United States, with nearly one-half experiencing serious disability among adults with OCD. Unfortunately, there is a significant delay between the onset of symptoms and treatment initiation, impacting the long-term outcome of patients with OCD.
Efforts to detect mental disorders through social media and online languages have been made, but exploration of LLMs in OCD identification has been limited. Recent studies have employed clinical vignettes for LLM assessments due to patient data safety concerns around deploying LLMs in care.
