Leveraging Swipe Gesture Interactions From Mobile Games as Indicators of Anxiety and Depression: Exploratory Study

Abstract

Background: Anxiety and depression are serious mental health conditions affecting millions of people worldwide; however, they are often underdiagnosed due to limited health care resources. Mobile games, with their widespread popularity and availability, offer a unique opportunity to use user-game interaction data for mental health screening. Objective: This study aimed to explore whether swipe gesture interactions from mobile games can serve as indicators of anxiety and depression symptoms. Methods: A total of 82 participants played 3 casual mobile games (puzzle, infinite runner, and object slicing games) for 15 minutes each and completed validated measures of anxiety (Generalized Anxiety Disorder-7; GAD-7) and depression (Patient Health Questionnaire-8; PHQ-8). Data were logged for each swipe event, and metrics were computed using statistical measures, yielding roughly 150 metrics per game. Spearman rank correlations were calculated between each metric and GAD-7 and PHQ-8 scores. Results: Multiple swipe gesture metrics showed significant associations with both anxiety and depression scores. For the puzzle game, mean swipe speed correlated with PHQ-8 (ρ=−0.405; P