Evidence map›Paper›PMID 33837148›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Emotion and humor as misinformation antidotes.

Sara K Yeo, Meaghan McKasy

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
18.2field-weighted citation impact, top 1% of its field
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

12 citing papers in PubMed, 62 citations in OpenAlex.

  1. Review
  2. Our changing information ecosystem for science and why it matters for effective science communication.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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  9. "Human vaccines & immunotherapeutics · 2022
    Article
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  12. Misinformation about science in the public sphere.Proceedings of the National Academy of Sciences of the United States of America · 2021
    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

2 authors at 2 institutions in 1 country.

Sara K YeoDepartment of Communication, University of Utah, Salt Lake City, UT 84112-0491; sara.yeo@utah.edu.ORCID 0000-0002-2043-8400
Meaghan McKasyDepartment of Communication, Utah Valley University, Orem, UT 84058-6703.ORCID 0000-0002-3489-612X
University of Utah · USUtah Valley University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many visible public debates over scientific issues are clouded in accusations of falsehood, which place increasing demands on citizens to distinguish fact from fiction. Yet, constraints on our ability to detect misinformation coupled with our inadvertent motivations to believe false science result in a high likelihood that we will form misperceptions. As science falsehoods are often presented with emotional appeals, we focus our perspective on the roles of emotion and humor in the formation of science attitudes, perceptions, and behaviors. Recent research sheds light on how funny science and emotions can help explain and potentially overcome our inability or lack of motivation to recognize and challenge misinformation. We identify some lessons learned from these related and growing areas of research and conclude with a brief discussion of the ethical considerations of using persuasive strategies, calling for more dialogue among members of the science communication community.

Indexed as

EmotionsDeceptionHealth CommunicationHumansemotionhumormisinformationscience communication

Identifiers

PMID33837148
PMCPMC8054012
OpenAlexW3144680086

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.