The relations between different components of intolerance of uncertainty and symptoms of generalized anxiety disorder: a network analysis

Abstract

Background Intolerance of uncertainty (IU) is considered as a specific risk factor in the development and maintenance of generalized anxiety disorder (GAD). Yet, researches have investigated the relations between IU and GAD (or worry) using total scores on self-report measures. This ignores that there are different components exist in IU and the heterogeneity of GAD symptoms. In the present study, we explored the relations among different components of IU and symptoms of GAD. Methods A dimensional approach which take individual differences into consideration in different components of IU along a full range of normal to abnormal symptom severity levels of GAD were used in this study. Components of IU were measured by 12-item Intolerance of Uncertainty Scale and symptoms of GAD were measured by Generalized Anxiety Disorder 7-Item Questionnaire. Regularized partial-correlation network was estimated using cross-sectional data from 624 university students. Results Four strongest edges are between components of IU, like “Unforeseen events upset me greatly” and “It frustrates me not having all the information I need”. Two strongest edges are between symptoms of GAD, like “Being so restless that it is hard to sit still” and “Feeling afraid as if something awful might happen”. Symptom “Worrying too much about different things” and component “It frustrates me not having all the information I need” have the highest expected influences in the present network. In the community of IU, component “It frustrates me not having all the information I need” has the highest bridge expected influence. And in the community of GAD, symptoms “Worrying too much about different things” and “Not being able to stop or control worrying” have the highest bridge expected influence. Conclusions This study reveals potential pathways between different components of IU and various symptoms of GAD. Understanding how putative risk factors such as different components of IU are related to symptoms of GAD may provide some references for related preventions and interventions, such as targeting component “It frustrates me not having all the information I need” may be more effective at reducing symptoms of GAD than targeting other components of IU.

Understanding the Association Between Intolerance of Uncertainty and Problematic Smartphone Use: A Network Analysis

“…The strongest edges within the IU cluster were between IU 1 (“Unforeseen events upset me greatly”) and IU 2 (“It frustrates me not having all the information I need”). These results are consistent with previous research on the network structure of IU ( 19 , 24 ). For the PSU cluster, we found PSU 2 (“Do you feel more irritability, anxiety or even sadness when you try to either reduce or stop your smartphone use”) has a strong connection to PSU 3 (“Do you feel the need to spend increasing amount of time engaged smartphone use in order to achieve satisfaction or pleasure?”).…”

“…It is worth mentioning the crucial role of IU 2 (i.e. as both a central node and a bridge node) was also reported in a network study that examined the relationship between IU components and generalized anxiety disorder symptoms ( 24 ). This indicates that IU 2 may be a target for research and interventions across different mental health conditions, in line with current transdiagnostic models of psychopathology (e.g., RDOC) ( 53 ).…”

“…For instance, individual PSU symptoms have shown different associations with self-control ( 21 ), problematic internet use ( 22 ) and neuroticism ( 23 ). Meanwhile, different components of IU were found to have distinct effects on generalized anxiety disorder ( 24 ). In viewing this drawback, it has been proposed that psychopathology research may benefit from moving beyond disorder-level analysis to a more fine-grained symptom-level analysis ( 25 , 26 ).…”

The roles of behavioral inhibition/activation systems and impulsivity in problematic smartphone use: A network analysis

“…This study revealed that the strongest edges appeared within the communities rather than connecting different communities. This is consistent with prior studies that have shown that the strongest edges exist within each community when detecting relationships between variables in a network consisting of two or more communities (24,53,63,(90)(91)(92)(93). For the PSU community, the two strongest positive edges were between PSU1 "salience" and PSU3 "mood modification" and between PSU4 "tolerance" and PSU6 "relapse"; this has also been found in a prior network research (24).…”

The relations between mental well-being and burnout in medical staff during the COVID-19 pandemic: A network analysis

“…Within the current network, node bridge centrality may help to understand the relative importance of each MW component in relation to burnout ( 56 – 58 ). Addressing the bridge node could deactivate the propagation path and reduce co-occurrence ( 33 ).…”