Wang Yifan, Liu Yanru, Ren Tianyi, Li Jingguang
1School of Teacher Education, Dali University, Dali, China.
2School of Education, University of New South Wales, Kensington, NSW, Australia.
J Behav Addict. 2025 May 20;14(2):746-756. doi: 10.1556/2006.2025.00039. Print 2025 Jul 2.
As problematic internet use (PIU) becomes increasingly prevalent among university students, effective preventive measures remain scarce. This study aimed to investigate how the allocation of daily activity time influences PIU and PIU risk (PIU/PIUR) and to identify specific activities that serve as risk and protective factors along with their effect strength.
Data from 2,433 university students in 33 Chinese provinces were analyzed using compositional analysis, isotemporal substitution, and instrumental variable methods to determine causal relationships between activity allocation and PIU/PIUR and to calculate the specific effects of substituting one activity for another.
After compositional adjustment, moderate-to-vigorous physical activity (MVPA) and classroom learning statistically significantly reduced PIU/PIUR (ps < 0.001, except PIUR for classroom learning: p = 0.002), whereas short videos and gaming increased PIU/PIUR (ps < 0.001). Sleep (PIU: p = 0.023, PIUR: p = 0.009) and autonomous learning (PIU: p = 0.013, PIUR: p = 0.003) were negatively correlated with PIU/PIUR but had no significant causal effect. Light physical activity was not statistically significantly correlated with PIU/PIUR (PIU: p = 0.141, PIUR: p = 0.585). Substituting 30 min of short video time with MVPA reduced PIUR by 22.9%. Conversely, replacing MVPA with short video watching increased PIUR by 68.3%.
Findings demonstrate the significant impact of 24-hour activity allocation on PIU/PIUR and suggest that time allocation strategies, particularly increasing MVPA while reducing short videos time, effectively reduce PIUR. These insights identify potential prevention for managing PIU via reallocation of daily activities.
随着问题性网络使用(PIU)在大学生中日益普遍,有效的预防措施仍然匮乏。本研究旨在调查日常活动时间的分配如何影响PIU和PIU风险(PIU/PIUR),并确定作为风险和保护因素的具体活动及其影响强度。
运用成分分析、等时替代和工具变量法,对来自中国33个省份的2433名大学生的数据进行分析,以确定活动分配与PIU/PIUR之间的因果关系,并计算用一种活动替代另一种活动的具体效果。
经过成分调整后,中等至剧烈身体活动(MVPA)和课堂学习在统计学上显著降低了PIU/PIUR(p值均<0.001,但课堂学习对PIUR的影响:p = 0.002),而短视频和游戏则增加了PIU/PIUR(p值均<0.001)。睡眠(PIU:p = 0.023,PIUR:p = 0.009)和自主学习(PIU:p = 0.013,PIUR:p = 0.003)与PIU/PIUR呈负相关,但无显著因果效应。轻度身体活动与PIU/PIUR无统计学显著相关性(PIU:p = 0.141,PIUR:p = 0.585)。用30分钟的MVPA替代短视频时间可使PIUR降低22.9%。相反,用观看短视频替代MVPA会使PIUR增加68.3%。
研究结果表明24小时活动分配对PIU/PIUR有显著影响,并表明时间分配策略,特别是增加MVPA同时减少短视频时间,可有效降低PIUR。这些见解为通过重新分配日常活动来管理PIU确定了潜在的预防措施。