Review
The impact of methodological and measurement factors on transdiagnostic associations with intolerance of uncertainty: A meta-analysis

https://doi.org/10.1016/j.cpr.2019.101778Get rights and content

Highlights

  • Meta-analysed transdiagnostic associations with intolerance of uncertainty (IU)

  • Examined moderators including clinical status, age, sex, IU measure, and symptom measure.

  • Extracted 181 studies (N participants = 52,402) with 335 independent effects

  • Moderate associations between IU and symptoms were observed across all disorders.

  • Some moderating effects were observed, but these were not substantive.

Abstract

Intolerance of uncertainty is a dispositional trait associated with a range of psychological disorders, but the influence of methodological factors on theses associations remains unknown. The first aim of this meta-analysis was to quantify the strengths of the association between IU and symptoms of generalised anxiety disorder, social anxiety disorder, panic disorder, agoraphobia, obsessive compulsive disorder, depression, and eating disorders. The second aim was to assess the influence of methodological factors on these relationships, including clinical (vs. non-clinical) status, age group, sex, IU measure, and symptom measure. We extracted 181 studies (N participants = 52,402) reporting 335 independent effect sizes (Pearson's r). Overall, there was a moderate association between IU and symptoms (r = 0.51, 95% CI = 0.50–0.52), although heterogeneity was high (I2 = 83.50, p < .001). Some small but significant moderator effects emerged between and within disorders. Effect sizes were not impacted by sample size. The results indicate that IU has robust, moderate associations with a range of disorder symptoms, providing definitive evidence for the transdiagnostic nature of IU.

Section snippets

Inroduction

Intolerance of uncertainty (IU) refers to “an individual's dispositional incapacity to endure the aversive response triggered by the perceived absence of salient, key, or sufficient information, and sustained by the associated perception of uncertainty” (Carleton, 2016a, p. 31). IU is a dispositional trait that manifests as negative beliefs and reactions to unpredictable events regardless of their probability, and accounts for cognitive, affective, and behavioural responses to uncertainty (

Protocol and registration

The protocol for this study was registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 20th April 2018 (registration number CRD42018092293). Additional self-report measures of IU and of differing syndromes to those specified in the protocol were identified during the literature searches, and thus the final list of main outcome measures for analysis is more extensive than detailed in PROSPERO. The meta-analysis is reported according to the recommendations of

Effects across all studies

The random effects were first estimated across all studies, followed by estimates by syndrome (defined by symptom measure), clinical (vs. non-clinical) status, age group (child vs. adult, average sample age), sex distribution, IU measure, and symptom measure. The influence of sample size was also examined. The overall random-effects point estimate (95% CI) was 0.51 (0.50–0.52, p < .001, N = 335 independent effects). The Q-value was significant 2024.01 (p < .001) and the I2 was indicative of

The jury is in: IU is certainly transdiagnostic

The first aim of this meta-analysis was to quantify the strengths of association between IU and symptoms of depression, social anxiety disorder, panic disorder, agoraphobia, GAD, OCD, and eating disorders. The extensive body of evidence across most of these symptom domains facilitated the calculation of precise point estimates with narrow confidence intervals. There was no evidence that publication bias or study sample size influenced results. The strengths of association between IU and

Role of funding sources

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Contributors

Peter McEvoy contributed to development of the research questions, design, method, analysis, and manuscript writing. Matthew Hyett contributed to development of the research questions, design, method, data extraction, analysis, and manuscript writing. Sarah Shihata contributed to the manuscript writing. Jordan Price contributed to the development of the research questions, design, method, and data extraction. Laura Strachan contributed to the design and data extraction. All authors reviewed and

Declaration of Competing Interest

All authors declare they have no conflicts of interest.

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