Evidence map›Paper›PMID 38135781›Full record

ArticleAttention, perception & psychophysics2024

Think twice: Re-assessing confidence improves visual metacognition.

Patxi Elosegi, Dobromir Rahnev, David Soto

Abstract read
In one paragraph

Article in Attention, perception & psychophysics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Patxi ElosegiBasque Center on Cognition, Brain and Language, San Sebastian, Spain. pelosegi001@ikasle.ehu.eus.ORCID http://orcid.org/0000-0002-3412-8390
Dobromir RahnevSchool of Psychology, Georgia Institute of Technology, Atlanta, USA.
David SotoBasque Center on Cognition, Brain and Language, San Sebastian, Spain.

Funding

Eusko Jaurlaritza BERC 2022-2025 programEusko Jaurlaritza Predoc grantMinisterio de Economìa y Competitividad EX2020-001010-SMinisterio de Economìa y Competitividad PID2019-105494GB-I0
6 · The paper itself

Abstract

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.

Indexed as

MetacognitionDecision MakingHumansMemoryChange-of-mindConfidence calibrationMetacognitionPerceptual decision-makingSensitivity

Identifiers

PMID38135781
PMCPMC10805928

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.