With the lifetime prevalence ranging from 4.3–5.9%, generalized anxiety disorder (GAD) is one of the most common mental health problems all over the world [1]. Characterized by excessive and uncontrollable worry about a series of events or activities lasting for at least 6 months, GAD often accompanies with other nonspecific psychological and physical symptoms [2]. Individuals with GAD have considerable role impairment and a high comorbidity with depression [3]. If GAD is not treated promptly, the prognosis is poor [4]. Therefore, it is important to identify the developing and maintaining factors for GAD to improve existing intervention strategies.
Intolerance of uncertainty (IU), “a dispositional characteristic that reflects a set of negative beliefs about uncertainty and its connotations and consequences” [5], is considered to be a specific risk factor or cognitive vulnerability in the development and maintenance of anxiety disorders [6, 7]. To better explain the relationship between IU and the psychopathology of anxiety, the most comprehensive conceptual model was developed, which was designed primarily to explain the symptoms of generalized anxiety disorder [8]. According to research on the relationship between IU and GAD [9], IU may develop and maintain symptoms of GAD by increasing repetitive negative thought (i.e., worry) [10]. Moreover, individuals with higher level of IU are more likely to treat ambiguous phenomena as unacceptable and threatening, which may lead to a negative problem orientation and an avoidance response style [11, 12]. Thus, they will be more prone to enter the process of worry. Under such model, increasing the patient’s tolerance and acceptance of uncertainty are the center of GAD therapy [13]. This strategy is supported by some randomized clinical trials with moderate to large effects [14, 15, 16].
To date, the pathways through how IU is related to individual symptoms of GAD still need to be further explored. Prior researches have generally studied IU at the disorder level or the core symptom level (i.e., worry) [17, 18, 19, 20, 21, 22]. Studies have compared the IU across different diagnostic groups or examined IU in relation to total scores on self-report measures of GAD symptoms (such as Beck Anxiety Inventory [18], Trait-Anxiety Scale of State-Trait Anxiety Inventory [19], Hamilton Rating Scale for Anxiety [20], and Generalized Anxiety Disorder Questionnaire for the Diagnostic and Statistical Manual of Mental Disorders 4th edition [21]) or worry (such as Penn State Worry Questionnaire [17, 18, 19, 20, 22]). However, as GAD is a heterogeneous syndrome characterized by worry and various cognitive, affective, and physical symptoms, the conclusions drew from these mentioned studies might be problematic. In addition, pathological worry also has different dimensions, such as generality, excessiveness and uncontrollability dimensions [23].
Neglecting the symptomatic heterogeneity of GAD and different dimensions of worry (e.g., excessiveness and uncontrollability dimensions) are serious limitations because it may mask differential associations between different clinical symptoms and different dimensions of worry and IU. In order to further understanding the relationship between IU and GAD, a symptom-level approach should be adopted considering worry and other cognitive, affective, and physical symptoms of GAD. Moreover, there is increasingly robust evidence that IU can be represented as having two factors, including prospective anxiety which involves fear and anxiety based on future events and inhibitory anxiety involves uncertainty inhibiting action or experience [24, 25]. These two factors may play different roles in the development and maintenance of GAD. Understanding the relations between different factors of IU and symptoms of GAD may increase our insights into the specific contribution of IU to GAD.
A promising approach revealing complex relations among individual symptoms of mental disorders and their risk factor is the network approach. According to network approach, mental disorders arise from complex reciprocal influences between their constituting symptoms, instead of a latent common cause [26, 27]. Recently, research has expanded symptom networks [28, 29, 30]. The researchers integrate cognitive and biological factors that are considered as the causal roles in mental disorders, in order to find out the causality of risk factor and symptoms in mental disorders. A systematic review article has also demonstrated that adding non-symptom (e.g., risk factor) should enhance the understanding of important aspects of psychopathology [31]. In addition, this approach can give several centralities (e.g., strength and bridge strength) and predictability indicators for each node to quantify their importance and controllability in the entire network [31, 32].
By expanding depression and anxiety symptom networks to integrate emotion regulation difficulties, repetitive negative thinking and positive reappraisal were found to be differentially related to affective, cognitive, and somatic symptoms of depression and anxiety [33]. These differences cast light on potential pathways through which repetitive negative thinking and positive reappraisal may operate within depression and anxiety [33]. By incorporating genetic risk scores into symptom networks of psychosis, research has showed that the polygenic risk score is directly connected to the spectrum of positive and depressive symptoms and allowed for a novel outlook on the investigation of the relations between genome-wide association study-based polygenic risk scores and symptoms of mental disorders [34]. These studies supported that adding important and meaningful non-symptom components as nodes in related symptom networks is both empirically feasible and theoretically enriching [28, 31].
In the present study, we tend to uncover pathways between prospective anxiety and inhibitory anxiety of IU and various symptoms of GAD. We adopted an expanded network approach to model two factors of IU within symptoms networks of GAD. There were three aims in the present study. First, we want to specify differential relations among two factors of IU and different symptoms of GAD. Second, using strength centrality to determine the relative importance of two factors of IU and different symptoms of GAD in the present network. Third, using bridge strength centrality to examine which factor of IU has the stronger connections with symptoms of GAD and which symptom of GAD has the stronger connections with IU. In addressing these objectives, we sought to keep with the Research Domain Criteria [35] by considering varying degrees of two factors of IU (i.e., prospective anxiety and inhibitory anxiety) along the continuum of severity of different GAD symptoms. In this way, we attempted to improve the understanding of complex relations between individual differences in prospective anxiety, inhibitory anxiety, as well as severity of generalized anxiety symptoms.