Prediction of suicidal ideation and depression in the general population with subthreshold insomnia using machine learning models

Our findings demonstrate that ML models using indirect questions can effectively screen for both suicidality and depression simultaneously. The models' robust performance in individuals with insomnia highlights their potential as feasible, ethical, and efficient tools for early detection. Given that sleep complaints are a common reason for seeking healthcare, this approach offers a critical opportunity for timely intervention in a high-risk population, potentially reducing preventable morbidity and mortality associated with suicide and depression.