StudentSense: Primary outcomes of a smartphone digital phenotyping study of university students in Australia

University students face increasing mental health challenges, yet traditional assessment methods often lack time- liness and contextual relevance. This study presents StudentSense, a digital phenotyping investigation examining associations between smartphone-sensed behavior and psychological wellbeing over a 17-week academic semester. A total of 151 students from an Australian university participated, providing continuous passive smartphone data (e.g., screen activity, app usage, location, keyboard, and on-screen text) and completing regular self-report assessments, in- cluding the Depression Anxiety Stress Scales (DASS-21), Mental Health Continuum-Short Form (MHC-SF), College Student Subjective Wellbeing Questionnaire (CSSWQ), and UCLA Loneliness Scale (ULS-8). We used Monte Carlo subsampling correlation analysis to explore relationships between behavioral and psychometric variables. Findings showed that levels of depression, anxiety, stress, and loneliness declined following the examination periods. Screen usage was positively correlated with the reported level of a loneliness item, while time spent at significant locations (e.g., university, home) was negatively correlated with depression. Students reporting higher wellbeing and extrover- sion reported more positive university experiences. • Conducted a 17-week digital phenotyping study with 151 university students. • Collected passive smartphone sensing data and regular self-report mental health assessments. • Observed declined depression, anxiety, stress, and loneliness following the examination period. • Found screen usage positively correlated with loneliness; location time negatively with depression. • Demonstrated feasibility of using smartphone data for mental health monitoring in students. • Applied bootstrapped split-sample analysis for robust behavioral correlations.