Advancing Mental Health Pre-Screening: A New Custom GPT for Psychological Distress Assessment

Jinwen Tang, Yi Shang
8/3/2024
cs.CYcs.AI

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Abstract

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.

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Cite this paper

@article{tang2024advancing,
  title  = {Advancing Mental Health Pre-Screening: A New Custom GPT for Psychological Distress Assessment},
  author = {Jinwen Tang and Yi Shang},
  year   = {2024},
  eprint = {2408.01614},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2408.01614v2}
}

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