Weight-of-Evidence Strategies to Mitigate the Influence of Messages of Science Denialism in Public Discussions.

false-balance effect forewarning multiple-source effect rebuttal science denialism vaccination weight of evidence

Journal

Journal of cognition
ISSN: 2514-4820
Titre abrégé: J Cogn
Pays: England
ID NLM: 101732790

Informations de publication

Date de publication:
01 Oct 2020
Historique:
entrez: 12 10 2020
pubmed: 13 10 2020
medline: 13 10 2020
Statut: epublish

Résumé

In mass media, the positions of science deniers and scientific-consensus advocates are repeatedly presented in a balanced manner. This false balance increases the spread of misinformation under the guise of objectivity. Weight-of-evidence strategies are an alternative, in which journalists lend weight to each position that is equivalent to the amount of evidence that supports the position. In public discussions, journalists can invite more advocates of scientific consensuses than science deniers (outnumbering) or they can employ warnings about the false-balance effect prior to the discussions (forewarning). In three pre-registered laboratory experiments, we tested the efficacy of outnumbering and forewarning as weight-of-evidence strategies to mitigate science deniers' influence on individuals' attitudes towards vaccination and their intention to vaccinate. We explored whether advocates' responses to science deniers (rebuttal) and audiences' issue involvement moderate the efficacy of these strategies. A total of

Identifiants

pubmed: 33043246
doi: 10.5334/joc.125
pmc: PMC7528676
doi:

Types de publication

Journal Article

Langues

eng

Pagination

36

Informations de copyright

Copyright: © 2020 The Author(s).

Déclaration de conflit d'intérêts

The authors have no competing interests to declare.

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Auteurs

Philipp Schmid (P)

CEREB - Center of Empirical Research in Economics and Behavioral Sciences, University of Erfurt, Erfurt, DE.
Department of Psychology, University of Erfurt, Erfurt, DE.

Marius Schwarzer (M)

Department of Media and Communication Science, University of Erfurt, Erfurt, DE.

Cornelia Betsch (C)

CEREB - Center of Empirical Research in Economics and Behavioral Sciences, University of Erfurt, Erfurt, DE.
Department of Media and Communication Science, University of Erfurt, Erfurt, DE.

Classifications MeSH