This research demonstrates how AI-assisted chatbots can efficiently collect and analyze qualitative data about depression stigma, creating actionable causal knowledge graphs.

• Innovative AI-driven chatbot engaged 1,002 participants in conversations about mental illness stigma
• Combined qualitative coding with AI assistance to analyze conversational data at scale
• Built causal knowledge graphs to visualize and understand the complex factors contributing to stigma
• Developed a more efficient methodology for gathering psychological insights that traditionally require intensive manual labor

This work matters for healthcare because understanding stigma patterns can directly improve treatment-seeking behavior and recovery outcomes for individuals with depression, potentially transforming mental healthcare delivery through data-informed interventions.

Deconstructing Depression Stigma: Integrating AI-driven Data Collection and Analysis with Causal Knowledge Graphs