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DC Field | Value | Language |
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dc.contributor.author | Winkler, Megan R | - |
dc.contributor.author | Mui, Yeeli | - |
dc.contributor.author | Hunt, Shanda L | - |
dc.contributor.author | Laska, Melissa N | - |
dc.contributor.author | Gittelsohn, Joel | - |
dc.contributor.author | Tracy, Melissa | - |
dc.date.accessioned | 2023-06-26T04:32:59Z | - |
dc.date.available | 2023-06-26T04:32:59Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/5171 | - |
dc.description.abstract | Retailfoodenvironments(RFEs)arecomplexsystemswithimportantimplicationsforpopulationhealth.StudyingthecomplexitywithinRFEscomes with challenges. Complex systems models are computational tools that can help. We performed a systematic scoping review of studies that used complex systems models to study RFEs for population health. We examined the purpose for using the model, RFE features represented, extent to which the complex systems approach was maximized, and quality and transparency of methods employed. The PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines were followed. Studies using agent-based modeling, systemdynamics,discreteeventsimulations,networks,hybrid,ormicrosimulationmodelswereidentifiedfrom7multidisciplinarydatabases.Fiftysixstudiesmettheinclusioncriteria,including23microsimulation,13agent-based,10hybrid,4systemdynamics,4network,and2discreteevent simulationmodels.Moststudies(n=45)usedmodelsforexperimentalpurposesandevaluatedeffectsofsimulatedRFEpoliciesandinterventions. RFE characteristics simulated in models were diverse, and included the features (e.g., prices) customers encounter when shopping (n=55), the settings (e.g., restaurants, supermarkets) where customers purchase food and beverages (n=30), and the actors (e.g., store managers, suppliers) whomakedecisionsthatinfluenceRFEs(n=25).Allmodelsincorporatedcharacteristicsofcomplexity(e.g.,feedbacks,conceptualrepresentation of multiple levels), but these were captured to varying degrees across model types. The quality of methods was adequate overall; however, few studies engaged stakeholders (n=10) or provided sufficient transparency to verify the model (n=12). Complex systems models are increasingly utilizedtostudyRFEsandtheircontributionstopublichealth.Opportunitiestoadvancetheuseoftheseapproachesremain,andareastoimprove futureresearcharediscussed.ThiscomprehensivereviewprovidesthefirstmarkeroftheutilityofleveragingtheseapproachestoaddressRFEsfor populationhealth. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | food environment | en_US |
dc.subject | systematic review | en_US |
dc.subject | agent-based modeling | en_US |
dc.subject | system dynamics | en_US |
dc.subject | simulation | en_US |
dc.subject | microsimulation | en_US |
dc.subject | networks | en_US |
dc.subject | healthy retail | en_US |
dc.title | ApplicationsofComplexSystemsModelsto ImproveRetailFoodEnvironmentsforPopulation Health:AScopingReview | en_US |
dc.type | Article | en_US |
Appears in Collections: | VOL 13 NO 4 2022 |
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File | Description | Size | Format | |
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1028-1043.pdf | 541.94 kB | Adobe PDF | View/Open |
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