Evidence map›Paper›PMID 42745644›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2026

Can Knowledge Counteract Conflict? A Partial Replication Study of PFAS Science Communication.

Laura N Rickard, Janet Z Yang, Carter Emerson, Gulsen Brennan-Buyukaydin

Abstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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.

Laura N RickardDepartment of Communication and Journalism, University of Maine, Orono, Maine, USA.ORCID https://orcid.org/0000-0002-5668-7580
Janet Z YangDepartment of Communication, University at Buffalo, SUNY, Buffalo, New York, USA.ORCID https://orcid.org/0000-0002-5989-5254
Carter EmersonSchool of Communication, The Ohio State University, Columbus, Ohio, USA.ORCID https://orcid.org/0009-0002-9586-5893
Gulsen Brennan-BuyukaydinDepartment of Communication and Journalism, University of Maine, Orono, Maine, USA.ORCID https://orcid.org/0009-0006-6915-2477

Funding

U.S.D.A. Agricultural Research Service Agreement 58-8030-4-015
6 · The paper itself

Abstract

On the basis of two surveys embedded with a 3 × 2 full-factorial experiment, we examine whether exposing participants to a message about the process of scientific inquiry prepares them to deal with conflicting risk information more effectively. Study 1 suggests initial evidence that, as compared to a testimonial, analogical and inoculation appeals increased trust in science when followed by consistent information. Conflicting information, conversely, was detrimental to risk perception, especially when paired with an inoculation appeal. These findings were not replicated in Study 2. Nevertheless, across both studies, trust in science, message credibility, risk perception, and self-efficacy were related to policy support and behavioral intention, whereas fatalism exercised an indirect effect through risk perception and self-efficacy. Findings highlight the importance of consistent messaging when communicating an emergent environmental health risk-here, per- and polyfluoroalkyl substances (PFAS)-while suggesting challenges in fostering a scientific mindset.

Indexed as

CommunicationFluorocarbonsKnowledgeHumansRisk AssessmentScienceSelf EfficacyTrustFluorocarbonsconflicting informationpolyfluoroalkyl substances (PFAS)risk perceptionscientific processself‐efficacy

Identifiers

PMID42745644
PMCPMC13579205

What OpenQuestion holds

Textmetadata
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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.