ChatGPT Demonstrates Potential for Identifying Psychiatric Disorders: Application to Childbirth-Related Post-Traumatic Stress Disorder

Free-text analysis using Machine Learning (ML)-based Natural Language Processing (NLP) shows promise for diagnosing psychiatric conditions. Chat Generative Pre-trained Transformer (ChatGPT) has demonstrated initial feasibility for this purpose; however, this work remains preliminary, and whether it can accurately assess mental illness remains to be determined. This study examines ChatGPT’s utility to identify post-traumatic stress disorder following childbirth (CB-PTSD), a maternal postpartum mental illness affecting millions of women annually, with no standard screening protocol. We explore ChatGPT’s potential to screen for CB-PTSD by analyzing maternal childbirth narratives as the sole data source. By developing an ML model that utilizes ChatGPT’s knowledge, we identify CB-PTSD via narrative classification. Our model outperformed (F1 score: 0.82) ChatGPT and six previously published large language models (LLMs) trained on mental health or clinical domains data, suggesting that ChatGPT can be harnessed to identify CB-PTSD. Our modeling approach can be generalized to assess other mental health disorders.