  This study introduces 'Psycho Analyst', a custom GPT model based on OpenAI's
GPT-4, optimized for pre-screening 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.
