Cyberchondria among college students and associated factors: a latent profile analysis

Abstract

Online health research is highly prevalent among college students. Cyberchondria in this population often involves repeated health-related searches driven by anxiety, which can heighten distress and disrupt daily functioning. This study aims to explore the classes of cyberchondria among college students, and to identify the characteristics and associated factors. In this online cross-sectional study, a total of 5641 students were recruited from a comprehensive university. Latent profile analysis (LPA) was performed to determine subgroups of cyberchondria. Multinomial logistic regression was used to analyze the influencing factors of different cyberchondria classes. Four classes of cyberchondria were identified: “Low-Variable Group”, “Moderate Seeking Group”, “Moderate Affective Group”, “High-Severe Group”. Logistic regression analysis indicated that students with poorer health status and higher eHealth literacy were more likely to be in the High-Severe group. Female students and those reporting poorer health had increased odds of falling into the Moderate Seeking and Moderate Affective groups. Cyberchondria among college students showed clear categorical features. Female students, individuals with poorer self-reported health, and those with higher eHealth literacy are more prone to severe cyberchondria. Tailored interventions should be provided to address health anxiety and cyberchondria symptoms among college students.