Liu Dayi, Liu Xiaoxuan, Long Yicheng, Xiang Zhibiao, Wu Zhipeng, Liu Zhening, Bian Dujun, Tang Shixiong
Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, China.
Front Neurosci. 2022 Oct 21;16:1010488. doi: 10.3389/fnins.2022.1010488. eCollection 2022.
This study aimed to investigate the possible associations between problematic smartphone use and brain functions in terms of both static and dynamic functional connectivity patterns.
Resting-state functional magnetic resonance imaging data were scanned from 53 young healthy adults, all of whom completed the Short Version of the Smartphone Addiction Scale (SAS-SV) to assess their problematic smartphone use severity. Both static and dynamic functional brain network measures were evaluated for each participant. The brain network measures were correlated the SAS-SV scores, and compared between participants with and without a problematic smartphone use after adjusting for sex, age, education, and head motion.
Two participants were excluded because of excessive head motion, and 56.9% (29/51) of the final analyzed participants were found to have a problematic smartphone use (SAS-SV scores ≥ 31 for males and ≥ 33 for females, as proposed in prior research). At the global network level, the SAS-SV score was found to be significantly positively correlated with the global efficiency and local efficiency of static brain networks, and negatively correlated with the temporal variability using the dynamic brain network model. Large-scale subnetwork analyses indicated that a higher SAS-SV score was significantly associated with higher strengths of static functional connectivity within the frontoparietal and cinguloopercular subnetworks, as well as a lower temporal variability of dynamic functional connectivity patterns within the attention subnetwork. However, no significant differences were found when directly comparing between the groups of participants with and without a problematic smartphone use.
Our results suggested that problematic smartphone use is associated with differences in both the static and dynamic brain network organizations in young adults. These findings may help to identify at-risk population for smartphone addiction and guide targeted interventions for further research. Nevertheless, it might be necessary to confirm our findings in a larger sample, and to investigate if a more applicable SAS-SV cutoff point is required for defining problematic smartphone use in young Chinese adults nowadays.
本研究旨在从静态和动态功能连接模式方面，探讨问题性智能手机使用与脑功能之间可能存在的关联。
对53名年轻健康成年人进行静息态功能磁共振成像数据扫描，他们均完成了智能手机成瘾量表简版（SAS-SV）以评估其问题性智能手机使用的严重程度。对每位参与者的静态和动态脑功能网络指标进行评估。将脑网络指标与SAS-SV评分进行相关性分析，并在调整性别、年龄、教育程度和头部运动后，对有和没有问题性智能手机使用的参与者进行比较。
两名参与者因头部运动过度被排除，最终分析的参与者中有56.9%（29/51）被发现存在问题性智能手机使用（如先前研究所建议，男性SAS-SV评分≥31，女性≥33）。在全局网络水平上，发现SAS-SV评分与静态脑网络的全局效率和局部效率显著正相关，而使用动态脑网络模型时与时间变异性负相关。大规模子网分析表明，较高的SAS-SV评分与额顶叶和扣带回-脑岛叶子网内静态功能连接的较高强度显著相关，以及与注意力子网内动态功能连接模式的较低时间变异性显著相关。然而，在直接比较有和没有问题性智能手机使用的参与者组时，未发现显著差异。
我们的结果表明，问题性智能手机使用与年轻人的静态和动态脑网络组织差异有关。这些发现可能有助于识别智能手机成瘾的高危人群，并为进一步研究指导有针对性的干预措施。然而，可能有必要在更大的样本中证实我们的发现，并研究对于当今中国年轻成年人定义问题性智能手机使用是否需要更适用的SAS-SV临界值。
