Wu Lin, Liu Chang, Huang Peng, Wang Ziwei, Cai Min, Fang Peng, Liang Wei, Sun Kewei, Tang Xu, Ouyang Anping, Guo Yuanyuan, Li Kuiliang, Wei Xinyi, Li Ziyi, Wu Shengjun, Ren Lei, Liu Xufeng
Department of Military Medical Psychology, The Fourth Military Medical University, Xi'an, 710032, China.
BrainPark, School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia.
BMC Psychiatry. 2025 Jul 1;25(1):659. doi: 10.1186/s12888-025-07091-w.
Previous studies examining the relationship between obsessive-compulsive personality traits (OCPT) and intolerance of uncertainty (IU) at the latent variable level (using total score analyses) have demonstrated positive correlations between them. However, such aggregate-level analyses obscure potential differential associations among specific OCPT and IU components.
This study employed network analysis to investigate the correlation patterns between IU and OCPT at the component/trait level in a sample of 1,440 Chinese college students. The Chinese versions of the Intolerance of Uncertainty Scale-Short Form (C-IUS-12) and Compulsive Personality Assessment Scale (CPAS) were used to assess IU components and OCPT, respectively. The regularized partial correlation network was constructed and node centrality, bridge centrality and predictability were identified. Furthermore, network comparison tests (NCT) were conducted to assess potential gender differences in the IU-OCPT network structure.
In the IU-OCPT network, the strongest edges connecting IU and OCPT communities are "Unforeseen events upset me greatly" (IU1) and "Rigidity" (OCPT8), "One should always look ahead so as to avoid surprises" (IU3) and "Miserliness" (OCPT7), "It frustrates me not having all the information I need" (IU2) and "Need for control" (OCPT6), "The smallest doubt can stop me from acting" (IU11) and "Rigidity" (OCPT8). IU2 (IU community) and OCPT6 (OCPT community) have the highest expected influence (EI), IU1 (IU community) and OCPT6 (OCPT community) have the highest bridge expected influence (BEI) and "When it's time to act, uncertainty paralyses me" (IU9) has the highest predictability. Network comparison tests did not reveal any gender differences in global EI, edge invariance, node EI and BEI.
The results of the network analysis indicate that there are extensive and diverse connections between different OCPT and IU components, providing a complementary perspective for deepening existing research and reference for related prevention and intervention. Specifically, regarding the "control" in OCPT and the "frustration" in IU (OCPT6 and IU2, both of which exhibit high centrality and bridge centrality) as potential targets, interventions such as cognitive-behavioral therapy (CBT) can achieve the maximum therapeutic effect of simultaneously reducing OCPT and IU, and effectively reduce their co-occurrence.
以往在潜在变量水平上（使用总分分析）研究强迫型人格特质（OCPT）与不确定性不耐受（IU）之间关系的研究表明，它们之间存在正相关。然而，这种总体水平的分析掩盖了特定OCPT和IU成分之间潜在的差异关联。
本研究采用网络分析，在1440名中国大学生样本中，考察IU与OCPT在成分/特质水平上的相关模式。分别使用中文版不确定性不耐受量表简版（C-IUS-12）和强迫型人格评估量表（CPAS）来评估IU成分和OCPT。构建正则化偏相关网络，并确定节点中心性、桥梁中心性和可预测性。此外，进行网络比较测试（NCT）以评估IU-OCPT网络结构中潜在的性别差异。
在IU-OCPT网络中，连接IU和OCPT群落的最强边是“意外事件让我非常不安”（IU1）和“刻板性”（OCPT8）、“一个人应该总是向前看以避免惊喜”（IU3）和“吝啬”（OCPT7）、“没有我需要的所有信息让我感到沮丧”（IU2）和“控制欲”（OCPT6）、“最小的疑虑就能阻止我行动”（IU11）和“刻板性”（OCPT8）。IU2（IU群落）和OCPT6（OCPT群落）具有最高的预期影响力（EI），IU1（IU群落）和OCPT6（OCPT群落）具有最高的桥梁预期影响力（BEI），“到了行动的时候，不确定性使我瘫痪”（IU9）具有最高的可预测性。网络比较测试未发现全球EI、边不变性、节点EI和BEI存在任何性别差异。
网络分析结果表明，不同的OCPT和IU成分之间存在广泛多样的联系，为深化现有研究提供了补充视角，并为相关预防和干预提供参考。具体而言，将OCPT中的“控制”和IU中的“沮丧”（OCPT6和IU2，两者均表现出高中心性和桥梁中心性）作为潜在靶点，认知行为疗法（CBT）等干预措施可以实现同时降低OCPT和IU的最大治疗效果，并有效减少它们的共现。
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