Evidence map›Paper›PMID 36604374›Full record

ArticlePsychonomic bulletin & review2023

Social overshadowing: Revisiting cue-competition in social interactions.

Maïka Telga, José A Alcalá, Cecilia Heyes, Gonzalo P Urcelay

Abstract read
In one paragraph

Article in Psychonomic bulletin & review, 2023. 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
  2. Article
  3. Social and non-social categorisation in investment decisions and learning.Quarterly journal of experimental psychology (2006) · 2023
    Article
  4. 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

4 authors.

Maïka TelgaSchool of Management, University of St Andrews, Gateway Building, North Haugh, St Andrews, KY16 9AJ, UK. myt1@st-andrews.ac.uk.ORCID http://orcid.org/0000-0002-6792-0093
José A AlcaláComplutense University of Madrid, Madrid, Spain.
Cecilia HeyesUniversity of Oxford, Oxford, UK.
Gonzalo P UrcelaySchool of Psychology, University of Nottingham, University Park, Nottingham, NG7 2RD, UK. gonzalo.urcelay@nottingham.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In a large variety of contexts, it is essential to use the available information to extract patterns and behave accordingly. When it comes to social interactions for instance, the information gathered about interaction partners across multiple encounters (e.g., trustworthiness) is crucial in guiding one's own behavior (e.g., approach the trustworthy and avoid the untrustworthy), a process akin to trial-by-trial learning. Building on associative learning and social cognition literatures, the present research adopts a domain-general approach to learning and explores whether the principles underlying associative learning also govern learning in social contexts. In particular, we examined whether overshadowing, a well-established cue-competition phenomenon, impacts learning of the cooperative behaviors of unfamiliar interaction partners. Across three experiments using an adaptation of the iterated Trust Game, we consistently observed a 'social overshadowing' effect, that is, a better learning about the cooperative tendencies of partners presented alone compared to those presented in a pair. This robust effect was not modulated by gender stereotypes or beliefs about the internal communication dynamics within a pair of partners. Drawing on these results, we argue that examining domain-general learning processes in social contexts is a useful approach to understanding human social cognition.

Indexed as

CuesSocial InteractionCooperative BehaviorHumansLearningTrustCooperationLearningOvershadowingStereotypesTrust

Identifiers

PMID36604374
PMCPMC10482779

What OpenQuestion holds

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LicenceCC BY
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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.