Predicting states of elevated negative affect in adolescents from smartphone sensors: a novel personalized machine learning approach

Abstract

To the extent that smartphone data could provide reasonably accurate real-time predictions of states of high negative affect in teens, brief 'just-in-time' interventions could be immediately deployed via smartphone notifications or mental health apps to alleviate these states.