Objective: To understand the dynamic temporal evolution pathways of Internet addiction among university students and to identify the core driving nodes, so as to provide theoretical evidences for the precise implementation of targeted interventions. Methods: Using a convenient cluster sampling method, a total of 1 066 full time freshmen and sophomores were recruited from three universities in Guizhou, Jiangxi, and Guangdong Provinces for a follow up survey (T1:January-March 2024; T2:January-March 2025). The Revised Chen Internet Addiction Scale (CIAS-R) was employed to assess the status of Internet addiction among university students, and cross sectional as well as cross lagged panel network models were constructed to analyze Internet addiction and its multidimensional influencing factors. Results: The T1 network comprised 19 nodes and 114 non zero edges, while the T2 network comprised 19 nodes and 126 non zero edges. Cross sectional network analysis revealed the strongest association between "insufficient sleep" and "daytime fatigue"; the core nodes were "first thought upon waking for going online" and "feeling low after disconnection" (characteristics of psychological dependence) at T1, while the core nodes shifted to "impaired health" and "excitement when online" (characteristics of functional impairment and addictive psychodynamic features) at T2. Cross lagged network analysis further indicated that "reduced leisure" directly predicted "sleep compression", and a bidirectional relationship was observed between "needing more time to achieve satisfaction" and "academic decline". Conclusions Internet addiction among university students exhibits dynamic evolutionary characteristics. Stage specific targeted interventions focusing on core driving nodes are needed, integrating behavioral regulation and academic support to break the vicious cycle and enhancing the ability to cope with real life demands.

Objective: To explore the longitudinal relationship between regulatory emotional self-efficacy and the persistence of exercise, so as to provide a reference for promoting the development of exercise habits among college students. Methods: Using a cluster random sampling method, one undergraduate institution was selected from each of Jiangxi, Hunan, Guizhou, Yunnan, Guangdong, Anhui, and Fujian provinces. A total of 2 576 college students were recruited. The Regulatory Emotional Self-efficacy Scale and Exercise Persistence Scale were distributed to college students through the questionnaire star platform. Three rounds of questionnaire surveys were completed in September 2023 (T1), December 2023 (T2), and March 2024 (T3). Crosslagged analysis was employed to explore the relationship between regulatory emotional selfefficacy and the persistence of college students exercise. Results: Repeated measures analysis of variance indicated that the main effects of regulatory emotional self-efficacy on time and gender were statistically significant ( F =102.15, η 2=0.07; F =34.80, η 2=0.01), and the interaction effects between time and gender, as well as between time and academic stage, were also statistically significant ( F =3.81, η 2=0.00; F = 25.54 , η 2=0.02)( P ＜ 0.05). The main effect of exercise persistence on time was statistically significant ( F =111.28, η 2=0.05) and the interaction effect between time and academic stage was statistically significant ( F =27.13, η 2=0.02)( P <0.01). Cross lagged analysis revealed that regulatory emotional self-efficacy at T1 positively predicted exercise persistence at T2 ( β =0.068), and regulatory emotional self-efficacy at T2 positively predicted exercise persistence at T3 ( β =0.368)( P ＜0.01). Prior exercise persistence positively predicted subsequent exercise persistence, with path coefficients of 0.298 and 0.240 ( P <0.01). Exercise persistence at T1 negatively predicted regulatory emotional self-efficacy at T2 ( β =-0.068), and exercise persistence at T2 positively predicted regulatory emotional self-efficacy at T3 ( β =0.061) ( P <0.01). Prior regulatory emotional self-efficacy positively predicted subsequent regulatory emotional self-efficacy, with path coefficients of 0.271 and 0.639 ( P <0.01). Conclusions There is a longitudinal causal relationship between regulatory emotional self-efficacy and college students exercise persistence. In daily physical activities, the significant role of emotional factors in sports practices should be emphasized to promote exercise behaviors among college students.