Evaluating LLM Biases when Applied to Psychiatric Risk Scores

This project evaluates how medically irrelevant (nonsensical or morally coded) variables affect predictive uncertainty in large language models used for mood-disorder risk assessment. We're using a controlled within-subjects perturbation design with synthetic patient configurations; the study measures resulting instability in LLM-generated risk scores.