PDF(Pubmed)
Abstract：
UNASSIGNED: This study aims to investigate the impact of physical activity and self-control on college students\' mobile phone addiction through cross-lagged longitudinal surveys, addressing the limitations of previous cross-sectional studies.
UNASSIGNED: A total of 414 college students were tracked three times during a 12-month period using the Physical Activity Rating Scale-3 (PARS-3), the Mobile Phone Addiction Tendency Scale (MPATS), and the Brief Self-Control Scale (BSCS). AMOS25.0 software was used to construct the cross-lagged relationship model, and the maximum likelihood approach was employed to investigate the model fitting. The asynchronous correlation between variables was investigated from the time series through the cross-lagged path coefficient.
UNASSIGNED: The fitting indexes of the cross-lagged model showed x 2/df = 5.098, GFI = 0.977, NFI = 0.969, IFI = 0.975, CFI = 0.974; RMSEA = 0.100, and SRMR = 0.030. The calculation conducted by combining the path coefficient of the model shows that PA and SC are the antecedent variables of MPA, and PA is the antecedent variable of SC. In addition, SC serves as a mediator in the path of PA, affecting MPA.
UNASSIGNED: (1) physical activity can positively affect subsequent self-control; (2) physical activity can negatively influence subsequent mobile phone addiction; (3) self-control can negatively affect subsequent mobile phone addiction; and (4) physical activity can indirectly influence subsequent mobile phone addiction through self-control.
UNASSIGNED: A total of 414 college students were tracked three times during a 12-month period using the Physical Activity Rating Scale-3 (PARS-3), the Mobile Phone Addiction Tendency Scale (MPATS), and the Brief Self-Control Scale (BSCS). AMOS25.0 software was used to construct the cross-lagged relationship model, and the maximum likelihood approach was employed to investigate the model fitting. The asynchronous correlation between variables was investigated from the time series through the cross-lagged path coefficient.
UNASSIGNED: The fitting indexes of the cross-lagged model showed x 2/df = 5.098, GFI = 0.977, NFI = 0.969, IFI = 0.975, CFI = 0.974; RMSEA = 0.100, and SRMR = 0.030. The calculation conducted by combining the path coefficient of the model shows that PA and SC are the antecedent variables of MPA, and PA is the antecedent variable of SC. In addition, SC serves as a mediator in the path of PA, affecting MPA.
UNASSIGNED: (1) physical activity can positively affect subsequent self-control; (2) physical activity can negatively influence subsequent mobile phone addiction; (3) self-control can negatively affect subsequent mobile phone addiction; and (4) physical activity can indirectly influence subsequent mobile phone addiction through self-control.
摘要：
■本研究旨在通过交叉滞后的纵向调查来调查身体活动和自我控制对大学生手机成瘾的影响，解决了以往横断面研究的局限性。
■在12个月的时间内，使用身体活动评定量表-3（PARS-3）对总共414名大学生进行了3次跟踪，手机成瘾倾向量表(MPATS)，和简要自我控制量表(BSCS)。采用AMOS25.0软件构建交叉滞后关系模型,并采用最大似然方法对模型拟合进行了研究。通过交叉滞后路径系数从时间序列中考察了变量之间的异步相关性。
■交叉滞后模型的拟合指数为x2/df=5.098，GFI=0.977，NFI=0.969，FI=0.975，CFI=0.974；RMSEA=0.100，SRMR=0.030。结合模型的路径系数进行的计算表明，PA和SC是MPA的前因变量，PA是SC的前因变量。此外,SC充当PA路径中的调解人，影响MPA。
■（1）身体活动可以积极影响随后的自我控制；（2）身体活动可以负面影响随后的手机成瘾；（3）自我控制可以负面影响随后的手机成瘾；（4）身体活动可以通过自我控制间接影响随后的手机成瘾。
■在12个月的时间内，使用身体活动评定量表-3（PARS-3）对总共414名大学生进行了3次跟踪，手机成瘾倾向量表(MPATS)，和简要自我控制量表(BSCS)。采用AMOS25.0软件构建交叉滞后关系模型,并采用最大似然方法对模型拟合进行了研究。通过交叉滞后路径系数从时间序列中考察了变量之间的异步相关性。
■交叉滞后模型的拟合指数为x2/df=5.098，GFI=0.977，NFI=0.969，FI=0.975，CFI=0.974；RMSEA=0.100，SRMR=0.030。结合模型的路径系数进行的计算表明，PA和SC是MPA的前因变量，PA是SC的前因变量。此外,SC充当PA路径中的调解人，影响MPA。
■（1）身体活动可以积极影响随后的自我控制；（2）身体活动可以负面影响随后的手机成瘾；（3）自我控制可以负面影响随后的手机成瘾；（4）身体活动可以通过自我控制间接影响随后的手机成瘾。
