Yu Liping, Li Yanlin, Wang Xianbin, Cui Yonghua
Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission (NHC) Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Front Psychiatry. 2025 Jun 3;16:1530911. doi: 10.3389/fpsyt.2025.1530911. eCollection 2025.
Tic disorders are neurodevelopmental disorders. Current research suggests that premonitory urges (PU) may be the cause and basis of tic disorders. The study used network analysis to investigate the detailed associations between PUs and tic symptoms the and internal relationships of PUs.
We included 1021 outpatient tic disorders. We used R 4.1.3 to perform network analysis. The "qgraph" package constructed the Premonitory Urge for Tics Scale (PUTS) and Yale Global Tic Severity Scale (YGTSS)networks for low-age and high-age group, and calculated the centrality measures for the four networks. We used the "bootnet" package to test the accuracy of the four network models and used the "NetworkComparisonTest" package to compare the networks for different age groups.
The network structures were stable (above 0.5). The node with the highest intensity was the 8th entry. The "connection" node was identified as the "all defects caused by motion or vocal tics" entry in the YGTSS. The strength and weight of the network structures did not significantly differ between the different groups. The node strength substitution test revealed that the 9th item had a significantly stronger intensity in lower age group (0.75) than in the higher age group (0.53) with a -value of 0.03. The strength in the network was also significantly greater in the younger age group (1.34) than in the older age group (1.02) with a -value of 0.04.
This study validates the internal structure of the PUTS scale across different age groups from a network perspective. It provides theoretical guidance and practical basis for targeted behavioral therapy.
抽动障碍是神经发育障碍。目前的研究表明，先兆冲动（PU）可能是抽动障碍的病因和基础。本研究采用网络分析方法，探讨先兆冲动与抽动症状之间的详细关联以及先兆冲动的内部关系。
我们纳入了1021例抽动障碍门诊患者。我们使用R 4.1.3进行网络分析。“qgraph”软件包构建了低年龄组和高年龄组的抽动先兆冲动量表（PUTS）和耶鲁全球抽动严重程度量表（YGTSS）网络，并计算了这四个网络的中心性指标。我们使用“bootnet”软件包测试这四个网络模型的准确性，并使用“NetworkComparisonTest”软件包比较不同年龄组的网络。
网络结构稳定（大于0.5）。强度最高的节点是第8项。“关联”节点被确定为YGTSS中“所有由运动或发声抽动引起的缺陷”项。不同组之间网络结构的强度和权重没有显著差异。节点强度替代测试显示，第9项在低年龄组（0.75）中的强度显著高于高年龄组（0.53），P值为0.03。网络中的强度在低年龄组（1.34）也显著高于高年龄组（1.02），P值为0.04。
本研究从网络角度验证了PUTS量表在不同年龄组中的内部结构。它为针对性行为治疗提供了理论指导和实践依据。
