Low, Alexis An Yee; (2025) Mechanisms behind Worry and their Role in Anxiety. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Worry is central to anxiety and causes key physical and psychological symptoms, including functional impairment. However, it is perceived by some to be helpful in problem-solving and avoiding aversive outcomes. To explore the hypothesis that worry occurs due to a lack of optimum stopping, becoming maladaptive when it persists beyond usefulness, a series of studies were undertaken. The overarching aim was to produce a computational model of worry as computational modelling is uniquely suited to reveal underlying mechanisms. First, a systematic scoping review revealed that evidence accumulation models are the best way to address the current lack of computational models of worry. Next, a novel experimental paradigm tested on 306 participants showed that sampling within it functions as a proxy for worry, successfully quantifying and externalising the process of worry, a process required for model-fitting. Sampling (‘re-lookings’) was predicted by both within-subject trial-to-trial state worry (p = 0.000, t-value 4.56) and between-subject trait worry (p = 0.0178) and had similar relationships with questionnaire data as worry. Notably, sampling behaviour was shown to be maladaptive in high worriers, driven by a tendency to sample even with low success probability, supporting the hypothesis that maladaptive worry occurs due to sampling persisting beyond functionality. Lastly, an evidence accumulation model in the reinforcement learning framework was proposed and was able produce synthetic data similar to collected data, suggesting a new and useful model for both adaptive and maladaptive worry.

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