This study aimed to identify latent profiles of Biological Rhythm Disorders (BRDs) among university students and to examine their associations with Problematic Digital Behaviors (PDBs). A total of 2,660 students from four universities in Hunan Province were surveyed. Biological rhythm disturbances were assessed using the Questionnaire of BRDs for Adolescents, while PDBs were evaluated using the Problematic Short-Form Video Media Use Scale, Problematic Social Network Use Tendency Scale, and Internet Game Addiction Scale. Latent profile analysis (LPA) was conducted with Mplus 8.3 to classify participants into distinct biological rhythm profiles. One-way ANOVA and multinomial logistic regression in SPSS 27.0 were used to examine demographic and behavioral predictors of profile membership. LPA identified four profiles of BRDs: Stable Rhythm (n = 774, 29.1%), Mild Disturbance (n = 956, 35.9%), Overall Disturbance (n = 500, 18.8%), and Sleep-Activity Disturbance (n = 430, 16.2%). Multinomial logistic regression showed that higher levels of Internet Gaming Addiction were associated with a greater likelihood of belonging to the Overall Disturbance profile (OR = 1.09, 95% CI: 1.07–1.12), whereas Problematic Short-Form Video Use (OR = 1.10, 95% CI: 1.08–1.12) and Problematic Social Network Use (OR = 1.08, 95% CI: 1.05–1.11) was notably associated with the Sleep-Activity Disturbance profile. BRDs among university students exhibit notable heterogeneity. The influence of PDBs differs across rhythm disturbance profiles. Interventions promoting biological rhythm health should consider students’ sex, academic year, and digital behavior patterns to develop personalized preventive strategies.
Chen et al. (Thu,) studied this question.