Evidence map›Paper›PMID 41530113›Full record

ArticleNature communications2026

Feedback-induced attitudinal changes in risk preferences.

Antonios Nasioulas, Elise Potier, Fabien Cerrotti, Maël Lebreton, Stefano Palminteri

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Antonios NasioulasDépartement d'Études Cognitives, Ecole Normale Supérieure, Université de Recherche Paris Sciences et Lettres, Paris, France. nasioulas@ens.fr.ORCID http://orcid.org/0009-0002-3192-2051
Elise PotierDirection interministérielle de la transformation publique, Paris, France.
Fabien CerrottiDépartement d'Études Cognitives, Ecole Normale Supérieure, Université de Recherche Paris Sciences et Lettres, Paris, France.
Maël LebretonParis-Jourdan Sciences Économiques UMR8545, CNRS & Paris School of Economics, Paris, France.
Stefano PalminteriDépartement d'Études Cognitives, Ecole Normale Supérieure, Université de Recherche Paris Sciences et Lettres, Paris, France. stefano.palminteri@ens.fr.ORCID http://orcid.org/0000-0001-5768-6646

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Decision-making under risk is often studied with fully described lotteries, where normative theory predicts that post-choice outcome disclosure (feedback) should not influence preferences. However, previous empirical work has generally shown that feedback does affect risk-taking, yet, without reaching a consensus on the consequences of feedback or the underlying cognitive mechanisms. Here, across seven behavioral experiments, we disentangle two competing accounts: the learning hypothesis, where feedback alters subjective values through experience, and the attitudinal hypothesis, where feedback changes preferences in anticipation of outcomes. We find that feedback does not improve maximization but consistently increases risk-taking. Fine-grained temporal analyses reveal that this effect emerges before any outcomes are experienced, ruling out learning as the primary driver. Moreover, the increase of risk-taking in partial feedback seems to be driven by curiosity, while in complete feedback by anticipated regret. Our results indicate that feedback can bias decision-making primarily through attitudinal rather than learning mechanisms.

Indexed as

AttitudeChoice BehaviorDecision MakingFeedback, PsychologicalRisk-TakingFemaleHumansLearningMaleYoung Adult

Identifiers

PMID41530113
PMCPMC12847909

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.