Evidence map›Paper›PMID 36713316›Full record

ArticlePNAS nexus2022

Minimal effects from injunctive norm and contentiousness treatments on COVID-19 vaccine intentions: evidence from 3 countries.

John M Carey, Tracy Keirns, Peter John Loewen, Eric Merkley, Brendan Nyhan, Joseph B Phillips, Judy R Rees, Jason Reifler

Erratum issuedAbstract read
In one paragraph

Article in PNAS nexus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

John M CareyDepartment of Government, Dartmouth College, Hanover, NH 03755, USA.ORCID https://orcid.org/0000-0002-1426-1565
Tracy KeirnsUNH Survey Center, University of New Hampshire, Durham, NH 03823, USA.ORCID https://orcid.org/0000-0002-2227-0971
Peter John LoewenDepartment of Political Science, University of Toronto, Toronto, ONT M5S 3G3, Canada.
Eric MerkleyDepartment of Political Science, University of Toronto, Toronto, ONT M5S 3G3, Canada.ORCID https://orcid.org/0000-0001-7647-9650
Brendan NyhanDepartment of Government, Dartmouth College, Hanover, NH 03755, USA.ORCID https://orcid.org/0000-0001-7497-1799
Joseph B PhillipsSchool of Psychology, University of Kent, Canterbury CT2 7NP, UK.
Judy R ReesGeisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA.
Jason ReiflerDepartment of Politics, University of Exeter, Amory Building, Exeter EX4 4RJ, UK.ORCID https://orcid.org/0000-0002-1116-7346

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Does information about how other people feel about COVID-19 vaccination affect immunization intentions? We conducted preregistered survey experiments in Great Britain (5,456 respondents across 3 survey waves from September 2020 to February 2021), Canada (1,315 respondents in February 2021), and the state of New Hampshire in the United States (1,315 respondents in January 2021). The experiments examine the effects of providing accurate public opinion information to people about either public support for COVID-19 vaccination (an injunctive norm) or public beliefs that the issue is contentious. Across all 3 countries, exposure to this information had minimal effects on vaccination intentions even among people who previously held inaccurate beliefs about support for COVID-19 vaccination or its perceived contentiousness. These results suggest that providing information on public opinion about COVID vaccination has limited additional effect on people's behavioral intentions when public discussion of vaccine uptake and intentions is highly salient.

Identifiers

PMID36713316
PMCPMC9802041

What OpenQuestion holds

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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.