Daily Affect Fluctuations in Phone Screen Content Predict Anxiety and Depressive Symptoms
This research addresses the need for targeted measurement and intervention in mental health by revealing the dynamic relationship between digital media use and symptoms, though it is incremental in linking specific content types to outcomes.
The study tracked smartphone interactions over one year to investigate how daily fluctuations in screen content affect mental health, finding that exposure to low-arousal negative content predicted higher depression and anxiety symptoms.
The relationship between digital media use and mental health remains poorly understood, in part because real-world digital behavior is rarely captured at scale. This intensive longitudinal study tracked participants' complete natural smartphone interactions over one year. We collected screenshots every 5 seconds from 145 adults (yielding 111 million screenshots), alongside biweekly assessments of anxiety and depression (mean = 24 surveys). The valence and arousal of each screenshot were assessed using a deep learning affect model. Individuals showed highly idiosyncratic media patterns, with substantially more variance in anxiety and depression accounted for within-person than between-person. Day-to-day fluctuations in the valence and arousal of a person's screen content predicted subsequent changes in depression and anxiety, whereas between-person differences did not. Specifically, greater exposure to low-arousal negative content was associated with higher depression and anxiety. These findings underscore the dynamic, idiosyncratic nature of digital consumption and the need for targeted measurement and intervention.