The component-to-trait relationship between intolerance of uncertainty and obsessive-compulsive personality traits: a network analysis.

Abstract

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.