PDF(Pubmed)
Abstract：
UNASSIGNED: The high prevalence of internet addiction (IA) has become a worldwide problem that profoundly affects people\'s mental health and executive function. Empirical studies have suggested trait anxiety (TA) as one of the most robust predictors of addictive behaviors. The present study investigated the neural and socio-psychological mechanisms underlying the association between TA and IA.
UNASSIGNED: Firstly, we tested the correlation between TA and IA. Then we investigated the longitudinal influence of TA on IA using a linear mixed effect (LME) model. Secondly, connectome-based predictive modeling (CPM) was employed to explore neuromarkers of TA, and we tested whether the identified neuromarkers of TA can predict IA. Lastly, stressful life events and default mode network (DMN) were considered as mediating variables to explore the relationship between TA and IA.
UNASSIGNED: A significant positive correlation between TA and IA was found and the high TA group demonstrated higher IA across time. CPM results revealed that the functional connectivity of cognitive control and emotion-regulation circuits and DMN were significantly correlated with TA. Furthermore, a significant association was found between the neuromarkers of TA and IA. Notably, the CPM results were all validated in an independent sample. The results of mediation demonstrated that stressful life events and correlated functional connectivity mediated the association between TA and IA.
UNASSIGNED: Findings of the present study facilitate a deeper understanding of the neural and socio-psychological mechanisms linking TA and IA and provide new directions for developing neural and psychological interventions.
UNASSIGNED: Firstly, we tested the correlation between TA and IA. Then we investigated the longitudinal influence of TA on IA using a linear mixed effect (LME) model. Secondly, connectome-based predictive modeling (CPM) was employed to explore neuromarkers of TA, and we tested whether the identified neuromarkers of TA can predict IA. Lastly, stressful life events and default mode network (DMN) were considered as mediating variables to explore the relationship between TA and IA.
UNASSIGNED: A significant positive correlation between TA and IA was found and the high TA group demonstrated higher IA across time. CPM results revealed that the functional connectivity of cognitive control and emotion-regulation circuits and DMN were significantly correlated with TA. Furthermore, a significant association was found between the neuromarkers of TA and IA. Notably, the CPM results were all validated in an independent sample. The results of mediation demonstrated that stressful life events and correlated functional connectivity mediated the association between TA and IA.
UNASSIGNED: Findings of the present study facilitate a deeper understanding of the neural and socio-psychological mechanisms linking TA and IA and provide new directions for developing neural and psychological interventions.
摘要：
■网络成瘾（IA）的高患病率已成为一个全球性问题，深刻地影响着人们的心理健康和执行功能。实证研究表明，特质焦虑（TA）是成瘾行为的最有力预测因素之一。本研究调查了TA和IA之间关联的神经和社会心理机制。
■首先，我们测试了TA和IA之间的相关性。然后，我们使用线性混合效应（LME）模型研究了TA对IA的纵向影响。其次,基于连接体的预测模型(CPM)用于探索TA的神经标志物，我们测试了确定的TA神经标志物是否可以预测IA。最后,应激性生活事件和默认模式网络（DMN）被认为是中介变量，以探讨TA和IA之间的关系。
■发现TA和IA之间存在显着正相关，高TA组显示出随时间的较高IA。CPM结果表明，认知控制和情绪调节回路以及DMN的功能连通性与TA显着相关。此外，发现TA和IA的神经标志物之间存在显著关联.值得注意的是,CPM结果均在独立样本中得到验证.调解结果表明，紧张的生活事件和相关的功能连接介导了TA和IA之间的关联。
■本研究的发现有助于更深入地理解连接TA和IA的神经和社会心理机制，并为发展神经和心理干预提供新的方向。
■首先，我们测试了TA和IA之间的相关性。然后，我们使用线性混合效应（LME）模型研究了TA对IA的纵向影响。其次,基于连接体的预测模型(CPM)用于探索TA的神经标志物，我们测试了确定的TA神经标志物是否可以预测IA。最后,应激性生活事件和默认模式网络（DMN）被认为是中介变量，以探讨TA和IA之间的关系。
■发现TA和IA之间存在显着正相关，高TA组显示出随时间的较高IA。CPM结果表明，认知控制和情绪调节回路以及DMN的功能连通性与TA显着相关。此外，发现TA和IA的神经标志物之间存在显著关联.值得注意的是,CPM结果均在独立样本中得到验证.调解结果表明，紧张的生活事件和相关的功能连接介导了TA和IA之间的关联。
■本研究的发现有助于更深入地理解连接TA和IA的神经和社会心理机制，并为发展神经和心理干预提供新的方向。
