Investigating intolerance of uncertainty as a moderator of threat expectancies in a virtual reality conditioning paradigm using non-linear Bayesian regression modelling

Autor: Haberkamp, Anke, Grill, Markus, Kloft, Matthias
Rok vydání: 2023
Předmět:
DOI: 10.17605/osf.io/6gjyp
Popis: Exposure therapy for anxiety disorders is highly effective and considered as the gold standard treatment for these disorders (Carpenter et al., 2018). One recent large clinical study investigating the treatment mechanism of exposure therapies found that one crucial aspect of success is how well patients are able to adjust their expectancies of threat in their feared situation (Pittig et al., 2022). Those patients who successfully learned that feared situations were less threatening than assumed in advance profited most from exposure therapy (i.e. who were most successful at extinction; Craske et al., 2018). However, Pittig et al. also found high interindividual differences in those exposure related learning rates. Thus, it seems important to experimentally determine potential moderators influencing this learning rate. As one such potential moderator, intolerance of uncertainty (IU, Carleton et al., 2012) has been identified in previous studies to negatively impact extinction processes, and thus the learning rate, although mainly in the domain of skin conductance responses (see Morriss et al., 2021 for a meta-analysis). Differences in subjective ratings related to the learning rate, such as US expectancy, have been more difficult to find, especially in healty samples (Wroblewski et al., 2022). Importantly, if a moderator influences subjective ratings only in the middle part of extinction phases but not at the beginning or end, linear statistical models are unable to capture such an influence, which is why it may be more appropriate to use non-linear models in these contexts. Therefore, the goal of the present study is to investigate intolerance of uncertainty (IU; Carleton et al., 2012) as a moderator influencing subjective US expectancy ratings in a virtual-reality conditioning experiment using spider-fearful individuals via non-linear Bayesian regression modelling. Additionally, we want to investigate whether one sub-factor of IU, inhibitory IU (I-IU), may be the specific component of general IU that influences US expectancy (as it has been previously referred to as a “paralysis of cognition and action in the face of uncertainty”; Morriss, Zuj, et al., 2021) and to control for trait anxiety (Morriss, Wake, et al., 2021). Importantly, we seek to improve on the translational aspects of experimental conditioning studies by employing a paradigm specifically designed to take such aspects into account (see Hollandt et al., 2020 for details) and by further increasing immersion via a virtual-reality (VR) design (Mertens et al., 2019). Our study will furthermore sample spider fearful-individuals, enabling us to use fear-relevant unconditioned stimuli (US; i.e. spiders) in our design.
Databáze: OpenAIRE