Objective: To explore the relationship of social anxiety and emotion regulation strategy with short video addiction among college students, so as to provide reference for alleviating social anxiety, improving the level of emotion regulation and preventing short video addiction. Methods: From May to June 2024, 2 172 college students from a university in Guangzhou were selected by multistage random cluster sampling method. The Interaction Anxiousness Scale, Emotion Regulation Questionnaire and Short Video Addiction Scale were used as the measurement tools. The potential profile was used to analyze the potential categories of social anxiety and emotion regulation strategy. The Chi square test was used to analyze the characteristics of the distribution of potential profile categories of college students with different demographic characteristics. Multiple linear regression analysis was used to analyze the relationship between social anxiety, emotion regulation strategy and short video addiction. Results: The potential categories of social anxiety and emotion regulation strategy in college students were divided into adaptive regulation type (784 cases, 36.10 %), low anxiety-expression type (623 cases, 28.68%), inhibition-anxiety type (478 cases, 22.01%), high anxiety-disorder type (287 cases, 13.21%). There were statistically significant differences in the distribution of various potential categories of social anxiety and emotion regulation strategy among cadres of different gender, family residence, class cadres or not ( χ 2=42.55, 17.86 , 39.05, all P <0.01). Multiple linear regression analysis showed that after controlling the confounding factors such as demographic variables, the potential categories of social anxiety and emotion regulation strategy of college students (low anxiety-expression type, inhibition-anxiety type, high anxiety-disorder type) were the important related factors of short video addiction ( β =0.15,0.25,0.35, all P <0.05). Conclusions Social anxiety and emotion regulation strategy of college students exhibit distinct categorical characteristics, and its varying latent categories are associated with short video addiction. Schools should implement targeted intervention measures for different categories of college students to promote their comprehensive mental health development.

Objective: To explore the causal relationship between academic procrastination, negative emotions, self control, and smartphone addiction among college students, so as to provide theoretical reference for promoting their mental health and academic achievement. Methods: A multi stage cluster random sampling method was used to select 452 first year students from a university in Guangzhou as the research subjects. Procrastination Assessment Scale- Student (PASS), The Depression Anxiety Stress Scale (DASS-21), Self Control Scale, and Short Version of the Smartphone Addiction Scale (SAS-SV) were used as measurement tools. Three questionnaire surveys were completed in October 2024 (T1), February 2025 (T2), and May 2025 (T3). Coss lagged models were utilized to analyze the causal relationship between academic procrastination, negative emotions, self control, and smartphone addiction. Results: The SAS-SV scale for college students showed an average score of (40.52±1.96), with 43.1% of freshmen exhibiting smartphone addiction.Positive correlations were observed between academic procrastination, negative emotions, and smartphone addiction across different time points, while self control exhibited negative correlations with these three variables ( r = 0.30 -0.62, -0.72 to -0.34, all P <0.05). Cross lagged model results indicated that academic procrastination and negative emotions at T1 and T2 positively predicted smartphone addiction at T2 and T3 (T1→T2, β =0.22, 0.35; T2→T3, β =0.21, 0.24; all P < 0.05 ). Self control negatively predicted smartphone addiction (T1→T2, β =-0.32; T2→T3, β =-0.26; both P <0.05). In reverse causality regression models, smartphone addiction at T1 and T2 positively predicted academic procrastination and negative emotions at T2 and T3 (T1→T2, β =0.09, 0.24; T2→T3, β =0.10, 0.35; all P <0.05), but no statistically significant predictions were found for self control (T1→T2, β =-0.04; T2→T3, β =-0.03; both P >0.05). Conclusion Academic procrastination and negative emotions exhibit bidirectional causality with smartphone addiction among college students, while self control unidirectionally predicts smartphone addiction.