Using machine learning with intensive longitudinal data to predict depression and suicidal ideation among medical interns over time

Background:¬†Use of intensive longitudinal methods (e.g. ecological momentary assessment, passive sensing) and machine learning (ML) models to predict risk for depression and suicide has increased in recent years. However, these studies often vary considerably in length, ML methods used, and sources of data. The present study examined predictive accuracy for depression and suicidal ideation (SI) […]

A prospective cohort study investigating factors associated with depression during medical internship.

Objectives To identify psychological, demographic, and residency program factors that are associated with depression among interns and to use medical internship as a model to study the moderating effects of this polymorphism. Participants Seven hundred forty interns entering participating residency programs. Main Outcome Measures Subjects were assessed for depressive symptoms using the 9-item Patient Health […]