Advancing Mental Health Pre-Screening: A New Custom GPT for Psychological Distress Assessment
This study introduces ’Psycho Analyst’, a custom GPT model based on OpenAI’s GPT-4, optimized for prescreening mental health disorders. Enhanced with DSM-5, PHQ-8, detailed data descriptions, and extensive training data, the model adeptly decodes nuanced linguistic indicators of mental health disorders. It utilizes a dual-task framework that includes binary classification and a three-stage PHQ-8 score computation involving initial assessment, detailed breakdown, and independent assessment, showcasing refined analytic capabilities. Validation with the DAIC-WOZ dataset reveals F1 and Macro-F1 scores of 0.929 and 0.949, respectively, along with the lowest MAE and RMSE of 2.89 and 3.69 in PHQ-8 scoring. These results highlight the model’s precision and transformative potential in enhancing public mental health support, improving accessibility, cost-effectiveness, and serving as a second opinion for professionals.
Authors
- Jing‐Shia Tang (ORCID: https://orcid.org/0000-0002-2518-6652)
- Yi Shang
Institutions
- University of Missouri (US)
Publication Details
- Published
- 2024-10-28
- DOI
- https://doi.org/10.1109/cogmi62246.2024.00030
- Citations
- 7
- Primary Topic
- Mental Health Treatment and Access
- Type
- article
- Field-Weighted Citation Impact
- 4.50