Leveraging social circles and algorithmic processes in digital mental health tools for college students' stress management

Abstract

Introduction. College students frequently face stress from academic pressures, social demands, and the challenges of daily life. Digital mental health (DMH) interventions have shown promise in helping manage these stressors. However, many students quickly abandon DMH tools, which limits their effectiveness. Previous research has identified social interaction as a key factor in improving user engagement with DMH tools. Still, most existing DMH tools have not been designed with these sharing practices in mind. Moreover, research on recommender systems (RSs) has mainly focused on single-user interactions, leaving a gap in the development of RSs for group settings, particularly in the health domain.

Method. To address this gap, we developed a technological probe that integrates social features with algorithmic processes to provide recommendations for both individuals and groups, aimed at supporting students' stress management efforts. We conducted a user study with 15 college students and their social circles, who interacted with the probe over the course of a day.

Results. Our findings revealed that students appreciated the opportunity to share daily activities with friends and felt motivated to engage in well-being-enhancing behaviours. Participants also gave valuable feedback on the stress management recommendations. We discuss and provide recommendations for future research.