Back to the Basics: Limitations of Idiographic Machine Learning Forecasting In Mental Health Data

This talk evaluates machine learning methods’ performance using EMA and passive sensing data from the Brighten study. Comparing models with varied exogenous inputs, we find that simple baselines outperform sophisticated models over longer horizons. Findings highlight limits of current methods and the need to reassess symptom-level EMA features.