Abstract
Processing uncertainty may be pathognomonic (characteristic of a disease) for some psychiatric conditions. Some people expect the world to change, even when it doesn’t. This tendency is central to paranoia, where individuals often anticipate threat or change without clear evidence. But what determines whether these beliefs translate into behavior? One possibility is that metacognitive structure – the coherence and depth with which one articulates their own thinking – acts as a buffer. An agent may endorse a belief but have sufficient accessory hypotheses to insulate it from action. To test this, we used metacognitive prompting in GPT-4 to score individual reflections on open-ended questions (e.g., did you use any particular strategy?) after completing a probabilistic reversal learning task. Individuals with higher paranoia demonstrate lower metacognitive structure (t = 5.98, p < 0.001), with metacognition attenuating the relationship between volatility belief and switching behavior (Δ = –15 pp, p < 0.001) even after controlling for reflection verbosity and general cognitive ability. These findings suggest that metacognition protects against uncertainty-driven instability, pointing to a key mechanism by which reflection protects against cognition under change. This work provides a novel framework to measure metacognition from behavioral task debrief questions.