Investigating Social Interaction Patterns with Depression Severity across Different Personality Traits Using Digital Phenotyping

Depression is a prevalent mental health concern among students due to the relentless academic demands and societal pressures. This study tests the hypothesis that students with increased depression exhibit specific social interaction patterns like connecting with others both online and in-person, associated with distinct personality traits. Leveraging smartphone passive sensing data from the StudentLife dataset, we categorized students into three clusters based on their big five personality survey responses. Our key finding reveals that students with high neuroticism and increased depression exhibit greater variability in the number of social contacts. This may be because these students possess more emotional instability, self-esteem, and negative self-perception. This finding highlights the significance of focusing on interpersonal aspects of depression to identify students who may be at intense risk for psychopathology. Understanding the dynamic interplay between personality traits, social interactions, and depression can aid in developing targeted interventions to promote mental well-being among students.