Preserved implicit metacognitive sensitivity distinguishes psychosis risk from first-episode psychosis: A cross-sectional virtual reality-based study

<jats:p>Relatively preserved insight distinguishes individuals at risk for psychosis from those with full–blown psychosis. Metacognitive processes thought to support insight and uncertainty monitoring may therefore serve as early markers of illness progression. Yet findings have been inconsistent, perhaps partly due to reliance on explicit confidence ratings that introduce reflection and response biases. To address these limitations, we used a novel implicit confidence measure derived from post–decision gaze in a virtual–reality probabilistic learning task. Gaze–based confidence quantifies the alignment between spatial predictions and gaze direction. We assessed first–order learning and gaze–based metacognition in four groups: clinical high-risk for psychosis (CHR–P), first episode psychosis (FEP), help-seeking controls (HSC), and healthy controls (HC). We tested whether implicit metacognition differentiates psychosis risk from psychosis. Learning accuracy was reduced in both CHR–P and FEP compared to control groups. At the metacognitive level, CHR–P confidence levels were approximately commensurate with their reduced first–order performance, indicating preserved confidence calibration, along with preserved metacognitive sensitivity—the ability to distinguish correct from incorrect decisions. In contrast, FEP showed impaired confidence calibration and reduced metacognitive sensitivity. Metacognitive calibration and sensitivity distinguished CHR–P from FEP and provided predictive value in distinguishing CHR–P from FEP, whereas learning accuracy did not. These findings reveal a dissociation between first-order cognitive processes and distinct aspects of implicit metacognition, including confidence calibration and metacognitive sensitivity, across the psychosis continuum. This dissociation may refine early clinical characterization and improve identification of preserved insight–related mechanisms in psychosis risk.</jats:p>