Comparing random forest and elastic net models to predict substance use disorder transitions in participants with cannabis and stimulant use: Evidence from the All of Us cohort

EN and RF models achieved moderate prediction of SUD transitions. Incorporating SDoH and wearable-derived data enhanced interpretability and risk stratification, particularly in linear models, underscoring substance-specific pathways and the utility of multimodal frameworks for developing precision prevention strategies.