Think twice: Re-assessing confidence improves visual metacognition

• Published in: Attention, perception & psychophysics Vol. 86; no. 2; pp. 373 - 380
• Main Authors: Elosegi, Patxi, Rahnev, Dobromir, Soto, David
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2024; Springer Nature B.V
• Subjects: Behavioral Science and Psychology; Cognitive Psychology; Confidence; Decision making; Discrimination Learning; Evidence; Experiments; Feedback (Response); Hypotheses; Mental disorders; Metacognition; Mnemonics; Psychiatry; Psychology; Replication (Evaluation); Research Methodology; Sample Size; Short Report; Stimuli; Teaching Methods; Visual Impairments; Visual Perception; Change-of-mind; Confidence calibration; Sensitivity; Perceptual decision-making; Metacognition
• ISSN: 1943-3921; 1943-393X; 1943-393X
• DOI: 10.3758/s13414-023-02823-0

Metacognition is a fundamental feature of human behavior that has adaptive functional value. Current understanding of the factors that influence metacognition remains incomplete, and we lack protocols to improve metacognition. Here, we introduce a two-step confidence choice paradigm to test whether metacognitive performance may improve by asking subjects to reassess their initial confidence. Previous work on perceptual and mnemonic decision-making has shown that (type 1) perceptual sensitivity benefits from reassessing the primary choice, however, it is not clear whether such an effect occurs for type 2 confidence choices. To test this hypothesis, we ran two separate online experiments, in which participants completed a type 1 task followed by two consecutive confidence choices. The results of the two experiments indicated that metacognitive sensitivity improved after re-evaluation. Since post-decisional evidence accumulation following the first confidence choice is likely to be minimal, this metacognitive improvement is better accounted for by an attenuation of metacognitive noise during the process of confidence generation. Thus, here we argue that metacognitive noise may be filtered out by additional post-decisional processing, thereby improving metacognitive sensitivity. We discuss the ramifications of these findings for models of metacognition and for developing protocols to train and manipulate metacognitive processes.