Evidence map›Paper›PMID 38807103›Full record

ArticleBMC public health2024

The effect of information provision on consumers' risk perceptions of, support for a ban, and behavioral intention towards the preventive use of antibiotics in food animals.

Yingnan Zhou, Airong Zhang, Rieks Dekker van Klinken, Junxiu Wang

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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
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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.

Yingnan ZhouHealth and Biosecurity, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Brisbane, QLD, 4102, Australia.
Airong ZhangHealth and Biosecurity, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Brisbane, QLD, 4102, Australia.
Rieks Dekker van KlinkenHealth and Biosecurity, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Brisbane, QLD, 4102, Australia.
Junxiu WangSchool of Mental Health, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China. nmwjx@sina.com.

Funding

China Scholarship Council 202004920045Key Projects of Philosophy and Social Sciences Research, Ministry of Education of the People's Republic of China 21JZD038
6 · The paper itself

Abstract

backgroundAntibiotics have been widely used in feed and drinking water for food animals to prevent them from getting sick. Such preventive use of antibiotics has become a contributor to increasing antibiotic resistance and thus poses threats to human health. However, consumers have little knowledge about this practice and the associated health risks of increasing transmission of antibiotic residues and antibiotic resistant bacteria. This study aimed to examine the effect of information provision on consumers' risk perceptions, support for a ban, and behavioral intention regarding the preventive use of antibiotics in food animals. Especially, the study sought to test two competing hypotheses which were informed by two theoretical perspectives of fear appeal theory - the linear model and the plateau effect model. The former suggested that providing information on the health risks of both antibiotic residues and antibiotic resistant bacteria would have a stronger effect compared to providing information on only one of them, while the latter posited that providing information on both risks might not have additional influence, as the effect of information on either risk could reach the plateau.

methodsAn experimental study with four conditions was conducted where participants read different information on the health risks associated with the preventive use first and then answered questions regarding consumers' risk perceptions, support for a ban, and behavioral intention regarding the preventive use. Condition 1 was the control condition, where basic information about antibiotics, antibiotic resistance, and the preventive use was provided. Condition 2 and Condition 3 further added information on the health risk of antibiotic residues (Condition 2) and antibiotic resistant bacteria (Condition 3) due to the preventive use, respectively. Condition 4 provided all information contained in the first three conditions.

resultsThe results showed that compared to participants in the control condition, participants in Conditions 2-4 reported higher risk perceptions, stronger support for a ban on the preventive use, and a higher intention to buy meat produced without the preventive use of antibiotics. However, there were no significant differences in these factors between Conditions 2-4, indicating that providing information on the health risk of either antibiotic residues, or antibiotic resistant bacteria, or both, has similar effect on these variables. That is, the hypothesis based on the plateau effect model was supported.

conclusionsThe findings suggested that informing the public with the health risk of either antibiotic residues or antibiotic resistant bacteria associated with the preventive use is effective enough to reach plateau effect in increasing risk perceptions, support for a ban, and behavioral intention, which has important implications for policymakers and livestock industries to develop effective communication strategies to promote responsible antibiotic use in food animals.

Indexed as

Anti-Bacterial AgentsHealth Knowledge, Attitudes, PracticeIntentionAdolescentAdultAnimalsConsumer BehaviorFemaleHumansMaleMiddle AgedRisk AssessmentSurveys and QuestionnairesYoung AdultAnti-Bacterial AgentsBehavioral intentionFood animalsInformation provisionRisk perceptionSupport for a banThe preventive use of antibiotics

Identifiers

PMID38807103
PMCPMC11134945

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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.