About This Architecture

Mental health screening chatbot combining clinical assessment logic with conversational AI to deliver PHQ-9 and GAD-7 screening in a web chat interface. User messages flow through a Node.js/Express application server to parallel processing: screening logic engines calculate clinical scores while OpenAI GPT generates empathetic responses. Results and session data persist in PostgreSQL, enabling longitudinal tracking and clinical validation. Fork this architecture to customize screening instruments, swap AI providers, or integrate with EHR systems. The modular design separates clinical logic from conversational AI, supporting compliance requirements and evidence-based mental health delivery.

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How do you architect a mental health screening chatbot that combines clinical assessment logic with conversational AI?

This diagram shows a layered architecture where user messages flow through a Node.js/Express server to parallel processing: screening logic engines (PHQ-9, GAD-7) calculate clinical scores while OpenAI GPT generates responses. Results and sessions persist in PostgreSQL, enabling evidence-based mental health delivery with clinical validation and longitudinal tracking.