Evidence map›Paper›PMID 42853899›Full record

ArticlePLoS computational biology2026

How does explicit reliability guide choices? Effect of trustworthiness on choice and metacognition.

Keiji Ota, Anthony Ciston, Patrick Haggard, Thibault Gajdos Preuss, Lucie Charles

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In one paragraph

Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Keiji OtaInstitute of Cognitive Neuroscience, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-3982-7534
Anthony CistonMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Patrick HaggardInstitute of Cognitive Neuroscience, University College London, London, United Kingdom.
Thibault Gajdos PreussAix Marseille Univ, CNRS, CRPN, Marseille, France.ORCID https://orcid.org/0000-0001-6906-4836
Lucie CharlesInstitute of Cognitive Neuroscience, University College London, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A key challenge in today's fast-paced digital world is to integrate information from various sources, which differ in their reliability. Yet, little is known about how explicit probabilistic information about the likelihood that a source provides correct information is used in decision-making. Here, we investigated how such explicit reliability markers are integrated into decisions and the extent to which individuals have metacognitive insight into this process. We developed a novel paradigm where participants viewed predictions from sources of varying explicit reliability to help them make a choice between two options. After each decision, they rated how much they felt a given source influenced their choice. Using computational modelling, we estimated the effective reliability that participants assigned to each source. Overall, we found that participants did not take source reliability at face value, inappropriately using the stated probabilities of source correctness to make a choice. Interestingly, even sources that were explicitly labelled as unreliable biased choices, as if these were treated as moderately reliable. Additionally, the presence of sources flagged as lying ones and known to be reliably predicting the incorrect answer impaired performance by increasing leakiness in evidence accumulation. Despite these biases, participants showed some metacognitive awareness of what influenced their choices: they were aware of the impact unreliable sources had on their decisions and could evaluate how much a given source had increased the likelihood of their response. These results suggest that people distort explicit source reliability but have some awareness of this process.

Indexed as

Choice BehaviorMetacognitionTrustAdultComputational BiologyDecision MakingFemaleHumansMaleProbabilityReproducibility of ResultsYoung Adult

Identifiers

PMID42853899
PMCPMC13652329

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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.