Abstract
<title>Abstract</title> <p>Background Depressive symptoms, loneliness, and social media addiction are commonly reported by medical students, yet their symptom-level interrelationships are not well understood. Objective This study employed network analysis to investigate the connections between these conditions among Chinese medical students. Method A total of 836 Chinese medical students from a university in Nantong were included in this cross-sectional study. Depressive symptoms, loneliness, and social media addiction were assessed using the Patient Health Questionnaire-9, the short-form UCLA Loneliness Scale, and the Bergen Social Media Addiction Scale, respectively. We estimated two complementary networks: a regularized partial correlation network and a Bayesian directed acyclic graph (DAG). Results For the regularized partial correlation network, we found that “Isolation” was not only the most central node but also the primary bridge symptom, with “Sad mood” and “Anhedonia” also emerging as highly central. For the DAG, “Anhedonia” was identified as a key driver of other symptoms within the network, and “Unhappy”, “Fatigue” were terminal symptoms. Conclusion As the first network analysis of depressive symptoms, loneliness, and social media addiction among Chinese medical students, the findings inform multi-level interventions by identifying central, bridge, and upstream symptoms as potential therapeutic targets, with downstream symptoms serving as key clinical indicators.</p>