Beliefs over control and meta-worry interact with the effect of intolerance of uncertainty on worry

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Abstract

Cognitive theory conceptualizes worry as influenced by metacognitive beliefs about worry, intolerance of uncertainty, and perceptions of control over events and reactions. This study tests the hypothesis that the effect of intolerance of uncertainty would interact with meta-cognitive beliefs on worry and perceived control. One hundred eighteen individuals with generalized anxiety disorder and 54 controls completed the Meta-Cognition Questionnaire, the Intolerance of Uncertainty Scale, the Anxiety Control Scale, and the Penn State Worry Questionnaire. Models were tested measuring interactive effects in multiple regression linear analysis. The interaction model was confirmed. The effect of intolerance of uncertainty on worry was increased by its interaction with metacognitive and control beliefs. The finding emphasizes the significant role of metacognitive and control beliefs in the cognitive process that leads to the development of worry.

Highlights

► We examined the interaction effects between three predictors of worry. ► Predictors are metacognitive beliefs, intolerance of uncertainty, and anxiety control. ► Patients with generalized anxiety disorder and normal controls participated. ► Metacognitive and control beliefs increase the effect of intolerance of uncertainty. ► Anxiety control should not be overlooked in cognitive models of worry.

Introduction

In their exhaustive review Behar, DiMarco, Hekler, and Staples (2009) concluded that current cognitive models for understanding generalized anxiety disorder (GAD) fall into five types: (1) the cognitive avoidance model of Borkovec (1994); (2) the intolerance of uncertainty model (Dugas, Buhr, & Ladouceur, 2004); (3) the metacognitive model of Wells (2004); (4) the emotion dysregulation model (Mennin, 2004); and (5) the acceptance-based model of Roemer and Orsillo (2005). In addition to these five, we could add at least two other theoretical models which have been applied to anxiety disorders in general and that can be consequently linked to GAD: the mood-as-input hypothesis (Davey, 2006) and the anxiety control model (Rapee, Craske, Brown, & Barlow, 1996).

The existence of rival theoretical models suggests the exploration of possible interactions between the variables focused on by each model. This work aims to explore reciprocal influences and interactions between complementary aspects of some of the mentioned models. In order to explore clinically meaningful interactions, the current study focuses on components of three of these models: intolerance of uncertainty, metacognitive beliefs and anxiety control. We selected these models since all of them focus on mechanisms that relate to discrete cognitive constructs measurable using psychometrically sound self-report instruments tapping the central construct, given that factor analyses have shown that these questionnaires load onto a single dimension (Antony et al., 2001, Freeston et al., 1994, Wells and Cartwright-Hatton, 2004, Zebb and Moore, 1999). On the other hand we did not consider complex information processing mechanisms not measurable using single variables, like emotion dysregulation, acceptance, avoidance, and mood-as-input.

Worry is a thought activity characterized by a predominance of anxious predictions about possible future negative events (Borkovec, 1994). Worry is a good indicator of the severity of GAD for several reasons. Worry is present in other anxiety disorders, although generally less so than in GAD. In addition, worry is described as a core criterion of GAD in the DSM. The special relationship between worry as a symptom and GAD as a DSM diagnosis is further shown by the fact that the intensity of worry is able to distinguish patients with GAD from healthy controls (Brown et al., 1992, Paulesu et al., 2009) and is also able to distinguish between subjects meeting all, some, or none of the DSM criteria for GAD (Meyer, Miller, Metzger, & Borkovec, 1990). Therefore, measures of worry can be seen as a useful proxy for the presence and severity of GAD (Norton, Sexton, Walker, & Norton, 2005).

Individuals scoring high on this construct tend to evaluate any uncertain or ambiguous situation as dangerous, stressful and upsetting. For these individuals, any potential risk of a negative outcome is perceived as threatening. Given the degree of uncertainty present in everyday life, intolerance for uncertainty is thought to contribute to the chronic worry and anxiety observed in GAD (Dugas et al., 2004).

The empirical studies supporting the significant role of intolerance for uncertainty have shown that this construct is one of the more powerful predictors of worry in GAD, while other factors, such as positive beliefs about worry or cognitive avoidance, are common across anxiety disorders (Dugas et al., 2007). In conclusion, it seems that intolerance of uncertainty is a cognitive factor that is closely linked to the arousal of anxiety states in GAD.

Wells’ metacognitive model of GAD (2004) describes five metacognitive beliefs that include different domains of beliefs about anxious states, worry, and perceived threats and danger. Of these five dimensions, two are conceptually related to worry and statistically correlated with proneness to develop worry and GAD: positive beliefs about worry and negative beliefs about worry concerning uncontrollability and danger (from now on: negative beliefs about worry). Positive beliefs about worry would encourage individuals with GAD to be involved in the execution of prolonged worry sequences about possible danger-related questions. Wells (2004) calls this process Type 1 worrying. On the other hand negative beliefs about worry are related to a negative appraisal of worry, and the fear that continuous worrying is an uncontrollable and potentially harmful mental condition. Wells calls this process meta-worry and reports that it is more specific for GAD than Type 1 worry. Due to this specificity, we focused on negative beliefs about worry in our set of predictors of worry.

Another cognitive factor that has been related more broadly to a range of anxiety disorders is the perception of low control over external threats and internal emotional reactions. The perception of control over a threat (a construct and variable called ‘anxiety control’) involves both the perception of being able to both master the threatening event itself (control of events) and also being able to control and master emotional reactions of fear (control of reactions) in a way that enhances the sense of personal competence and self-efficacy (Rapee et al., 1996, Shapiro and Astin, 1998, pp. 23). Given that one of the key diagnostic criteria for GAD is that worry is uncontrollable (American Psychiatric Association, 2000), low perceived control is a construct that is relevant to GAD. Considered within a control framework, the chronic worry and behavioural avoidance associated with GAD can be conceptualised as reflecting persistent (and futile) efforts to gain control over future threat.

As described above, the scientific literature suggests that intolerance of uncertainty, and negative beliefs on worry are powerful predictors of worry, while anxiety control is significantly linked to anxiety disorders and anxiety states, states which include worry and GAD. However, little is known about their possible interactive effects on worry. A significant interaction between AC, intolerance of uncertainty, and negative beliefs on worry would mean that these variables have a reciprocally reinforcing effect on the severity of worry and that their combined effect on worry is higher than the sum (Baron & Kenny, 1986).

This work seeks to test the hypothesis that these interactive effects exist and significantly influence the severity of worry. In particular, negative beliefs on worry and the reactions subscale of anxiety control are cognitive beliefs which influence the severity of worry via the appraisal of other internal mental states. This suggests that their mechanism of action may be intrinsically interactive, in that they exacerbate the severity of worry and GAD initiated via other cognitive processes.

Section snippets

Participants

Two groups of participants were recruited to the study. The clinical group were 119 participants meeting diagnostic criteria for GAD (Diagnostic and Statistical Manual of Mental Disorders, 4th ed., text rev.; American Psychiatric Association, 2000). Additional criteria for inclusion to the study were a minimum age of 18 years, and adequate written language abilities. This study included a mixed sample combining 90 Italian individuals and 29 Australian with GAD (Italian sample: 64 females and 26

Preliminary analyses

The independent variables explored in this study were correlated with each other (ACQ – NBWCD-MQ, r = −.77; IUS – ACQ, r = −.77; IUS – NBWCD-MQ, r = .68; all p’s < .001). This may result, particularly for small sample sizes, in multicollinearity, which can produce computational lack of precision in moderated regression (Aiken & West, 1991). To quantify multicollinearity we measured the variance inflation factor (VIF). There is no formal cut off value for VIF for determining the impact of

Summing up the results

The results support the relevance of intolerance of uncertainty and negative beliefs on worry for understanding cognitive mechanisms underlying worry and GAD and suggest that anxiety control is an equally relevant factor and should not be overlooked in cognitive models of this disorder. In addition, results support an original model of interaction in which negative beliefs on worry and anxiety control interact with and strengthen the effect of intolerance of uncertainty on worry.

The role of intolerance of uncertainty

From a clinical

References (30)

  • L.S. Aiken et al.

    Multiple regression: Testing and interpreting interactions

    (1991)
  • American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (DSM IV) (4th ed.),...
  • M.M. Antony et al.

    Practitioner’s guide to empirically based measures of anxiety

    (2001)
  • R.M. Baron et al.

    The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations

    Journal of Personality and Social Psychology

    (1986)
  • T.D. Borkovec

    The nature, functions, and origins of worry

  • Cited by (0)

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