Evidence map›Paper›PMID 32182247›Full record

ArticlePloS one2020

Using experimental gaming simulations to elicit risk mitigation behavioral strategies for agricultural disease management.

Eric M Clark, Scott C Merrill, Luke Trinity, Gabriela Bucini, Nicholas Cheney, Ollin Langle-Chimal, Trisha Shrum, Christopher Koliba, Asim Zia, Julia M Smith

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
5.1field-weighted citation impact, top 5% 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

9 citing papers in PubMed, 25 citations in OpenAlex.

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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

10 authors at 1 institution in 1 country.

Eric M ClarkSEGS Lab, University of Vermont, Burlington, Vermont, United States of America.ORCID 0000-0003-1512-2038
Scott C MerrillSEGS Lab, University of Vermont, Burlington, Vermont, United States of America.
Luke TrinitySEGS Lab, University of Vermont, Burlington, Vermont, United States of America.
Gabriela BuciniSEGS Lab, University of Vermont, Burlington, Vermont, United States of America.
Nicholas CheneySEGS Lab, University of Vermont, Burlington, Vermont, United States of America.
Ollin Langle-ChimalSEGS Lab, University of Vermont, Burlington, Vermont, United States of America.ORCID 0000-0002-8772-1171
Trisha ShrumSEGS Lab, University of Vermont, Burlington, Vermont, United States of America.
Christopher KolibaSEGS Lab, University of Vermont, Burlington, Vermont, United States of America.
Asim ZiaSEGS Lab, University of Vermont, Burlington, Vermont, United States of America.
Julia M SmithSEGS Lab, University of Vermont, Burlington, Vermont, United States of America.
University of Vermont · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Failing to mitigate propagation of disease spread can result in dire economic consequences for agricultural networks. Pathogens like Porcine Epidemic Diarrhea virus, can quickly spread among producers. Biosecurity is designed to prevent infection transmission. When considering biosecurity investments, management must balance the cost of protection versus the consequences of contracting an infection. Thus, an examination of the decision making processes associated with investment in biosecurity is important for enhancing system wide biosecurity. Data gathered from experimental gaming simulations can provide insights into behavioral strategies and inform the development of decision support systems. We created an online digital experiment to simulate outbreak scenarios among swine production supply chains, where participants were tasked with making biosecurity investment decisions. In Experiment One, we quantified the risk associated with each participant's decisions and delineated three dominant categories of risk attitudes: risk averse, risk tolerant, and opportunistic. Each risk class exhibited unique approaches in reaction to risk and disease information. We also tested how information uncertainty affects risk aversion, by varying the amount of visibility of the infection as well as the amount of biosecurity implemented across the system. We found evidence that more visibility in the number of infected sites increases risk averse behaviors, while more visibility in the amount of neighboring biosecurity increased risk taking behaviors. In Experiment Two, we were surprised to find no evidence for differences in behavior of livestock specialists compared to Amazon Mechanical Turk participants. Our findings provide support for using experimental gaming simulations to study how risk communication affects behavior, which can provide insights towards more effective messaging strategies.

Indexed as

AnimalsCoronavirus InfectionsDecision MakingDisease OutbreaksFood SupplyGames, ExperimentalHumansModels, TheoreticalPorcine epidemic diarrhea virusSwineSwine DiseasesVideo Games

Identifiers

PMID32182247
PMCPMC7077803
OpenAlexW2976455918

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.