Evidence map›Paper›PMID 38040761›Full record

ArticleScientific reports2023

Understanding belief in political statements using a model-driven experimental approach: a registered report.

Agustín Perez Santangelo, Guillermo Solovey

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Agustín Perez SantangeloInstituto de Investigación en Ciencias de la Computación, Universidad de Buenos Aires (UBA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), C1428EGA, Buenos Aires, Argentina. asantangelo@utdt.edu.
Guillermo SoloveyInstituto de CálculoFacultad de Ciencias Exactas y Naturales, UBA-CONICET, Buenos Aires, Argentina. gsolovey@gmail.com.

Funding

Consejo Nacional de Investigaciones Científicas y Técnicas (National Scientific and Technical Research Council) 11220150100787COUniversidad de Buenos Aires (University of Buenos Aires) 20020170100330BA
6 · The paper itself

Abstract

Misinformation harms society by affecting citizens' beliefs and behaviour. Recent research has shown that partisanship and cognitive reflection (i.e. engaging in analytical thinking) play key roles in the acceptance of misinformation. However, the relative importance of these factors remains a topic of ongoing debate. In this registered study, we tested four hypotheses on the relationship between each factor and the belief in statements made by Argentine politicians. Participants (N = 1353) classified fact-checked political statements as true or false, completed a cognitive reflection test, and reported their voting preferences. Using Signal Detection Theory and Bayesian modeling, we found a reliable positive association between political concordance and overall belief in a statement (median = 0.663, CI95 = [0.640, 0.685]), a reliable positive association between cognitive reflection and scepticism (median = 0.039, CI95 = [0.006, 0.072]), a positive but unreliable association between cognitive reflection and truth discernment (median = 0.016, CI95 = [- 0.015, 0.046]) and a negative but unreliable association between cognitive reflection and partisan bias (median = - 0.016, CI95 = [- 0.037, 0.006]). Our results highlight the need to further investigate the relationship between cognitive reflection and partisanship in different contexts and formats. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 22 August 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/EBRGC .

Identifiers

PMID38040761
PMCPMC10692149

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.