Evidence map›Paper›PMID 41773660›Full record

ArticleJMIR formative research2026

The Role of Fear, Hope, Message Fatigue, and Message Shocking Value in Promoting the Public's Understanding and Support Toward COVID-19 Wastewater Monitoring: Experimental Study.

Moonsun Jeon, Youllee Kim

Abstract read
In one paragraph

Article in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

2 authors.

Moonsun JeonDepartment of Communication, Michigan State University, East Lansing, MI, United States.ORCID 0009-0009-5990-7911
Youllee KimDepartment of Communication Studies, University of Denver, 2000 E Asbury Ave, 298 Sturm Hall, Denver, CO, 80208, United States, +1 3038712385.ORCID 0000-0001-9843-5712

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although wastewater monitoring is an effective, nonintrusive public health strategy for tracking community-level COVID-19 prevalence, there has been limited research on public perceptions of this novel surveillance method. A significant gap exists in understanding how to design effective communication campaigns to gain public support for wastewater monitoring and persuade individuals to take preventive actions based on the data. objectives: This study aimed to examine the impact of emotional appeals (fear vs hope) and pronoun use (we vs you) on public support for COVID-19 wastewater monitoring, intentions to discuss the intervention, and intentions to engage in preventive behaviors. Methods: An online 2 (emotional appeal: fear vs hope) × 2 (pronoun use: you-language vs we-language) between-subjects experiment with a control condition was conducted. A total of 603 US residents were recruited via Prolific in July 2023. Participants were randomly assigned to view 1 of 5 message stimuli and then completed a survey measuring emotional responses, message judgments (fatigue and shocking value), and the primary outcome variables. Results: Fear appeals led to greater support and stronger intentions to engage in preventive behaviors than hope appeals, while pronoun use had no significant effect. Additionally, message fatigue and shock value mediated the relationship between the message-evoked emotions and the outcome variables, whereby message fatigue was negatively associated with the outcome variables, and message shock value was positively correlated with policy support and communication intention. Conclusions: The findings suggest that while fear-based messages are effective, communication strategies should also aim to mitigate message fatigue to sustain public engagement and support for long-term public health initiatives.

Indexed as

COVID-19FearHealth PromotionHopePersuasive CommunicationWastewaterAdultFemaleHumansMaleMedia ExposureMiddle AgedSARS-CoV-2Surveys and QuestionnairesWastewaterCOVID-19 preventive behaviorsemotional appealsmessage fatiguemessage shocking valuewe-language vs you-language

Identifiers

PMID41773660
PMCPMC12954702

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.