Received:15May2023Revised:19September2023Accepted:15October2023
DOI:10.1111/1745-5871.12629
AreliabilitystudyoftheParkLifepublicparticipatory geographicinformationsystemsurvey
PaulaHooper |NicoleEdwards
TheAustralianUrbanDesignResearch Centre,SchoolofDesign,TheUniversityof WesternAustralia,Perth,Australia
Correspondence
PaulaHooper,TheAustralianUrbanDesign ResearchCentre,SchoolofDesign,The UniversityofWesternAustralia,Perth, Australia.
Email: paula.hooper@uwa.edu.au
Fundinginformation
ThestudywasfundedbyaWestern AustralianNear-MissAwards(WANMA)2021 (FutureHealthResearchandInnovation Fund)andanAustralianUrbanResearch InfrastructureNetwork(AURIN)HighImpact Project(2021).
Abstract
Planningpolicyforparksistypicallyguidedbyastandardapproachthat failstoaccountforhowcommunitiesactuallyuseparks.Moreover,few researchersknowtheexactparkspeopleuse,eventhough “use” isoften hypothesisedintherelationshipsbeingtested.Publicparticipatorygeographicinformationsystems(PPGISs)presentanopportunitytocollectspecific,spatiallyreferencedinformationonparkuseandpark-basedactivities. However,thereliabilityoftheseinstrumentshasnotbeenstudied.ThePark LifePPGIScapturedresidentiallocation,parklocation,andpark-based behaviouraldatafromasampleofadultsandwastestedforreliability. Kappascoresandintra-classcorrelationsassessedthereliabilityofthe items.Recallofindividualitemsallshowedacceptablereliabilityandmostly achieved “substantial” agreementor “near-perfect” agreement.ThePark LifePPGISisareliableinstrumenttocaptureparkuseandactivities.Such informationisessentialforpublichealthandphysicalactivityresearchers, urbanplanners,andparkmanagerstodevelopinformedplanningandpublichealthpoliciesandprogramsthatpromoteparkuse.
KEYWORDS
parks,physicalactivity,publichealth,publicopenspace,publicparticipatoryGIS,urban geographyandplanning
1 | INTRODUCTION
Publicopengreenspaceisessentialforhealthy, liveable,andsustainableurbanenvironmentsanda priorityundertheUnitedNations(2016)Sustainable DevelopmentGoals.Urbangreenspacesfulfil numerousbiophysical,social,andculturalpurposes (Grose, 2009)tomanageurbanwater,protectbiodiversity,andreduceurbanheatislandeffects.Urban greenspacesalsoprovidesettingsorfacilitiesfor physicalactivity;promotementalwell-beingandsupportattentionrestoration,stressreduction,andpositive emotions;andfostersocialwell-beingthroughsocial interactionandparticipation(Bowleretal., 2010;Dinnie etal., 2013;Koohsarietal., 2015).
Ingeographical,publichealth,andphysicalactivity research, “parks” havetypicallyformedthebasisfor exploringurbangreenspaceandhealthoutcomes (Hooperetal., 2020).Researchershaveoftentakena “recreationalopportunityspectrum” approach(Clark& Stankey, 1980)focusedonphysicalandspatial aspectsofparkprovisionandmeasuresoftheavailabilityandaccessibilitytoparks(Bancroftetal., 2015; Lambetal., 2019)orofthe “quality” ofparks (Bedimo-Rungetal., 2005;Zhangetal., 2018).These methodologicalapproachestypicallyusebuffers aroundparticipants’ homesorcomputedistancesto theclosestparkfromhomesandassessassociations betweenparksandhealthoutcomes(Lamb etal., 2019).However,suchanapproachassumesthat
Thisisanopenaccessarticleunderthetermsofthe CreativeCommonsAttribution-NonCommercial-NoDerivs License,whichpermitsuseanddistributioninany medium,providedtheoriginalworkisproperlycited,theuseisnon-commercialandnomodificationsoradaptationsaremade. ©2023TheAuthors. GeographicalResearch publishedbyJohnWiley&SonsAustralia,LtdonbehalfofInstituteofAustralianGeographers.
GeographicalResearch. 2024;62:134–146. wileyonlinelibrary.com/journal/geor
participantsonlyusetheparkclosesttothemina definedresidentialcatchmentarea,eventhoughother parksareavailabletovisitoutsidedesignatedneighbourhoodbufferareas(Kaczynskietal., 2014).Few studiesidentifytheexactparksthatparticipantsuse, althoughuseisoftenhypothesisedintheaccess–use–healthrelationshipsbeingtested.Indeed, Edwardsetal.(2015)havefoundthatonly27%of adolescentsusedtheparkclosesttotheirresidence.
Internationally,planningforparksorurbangreen spacesistypicallyguidedbyastandards-based approachthatstipulatestargetsfortheprovisionofa minimalquantityofgreenspacepercapitaorthe maximumdistancesresidentsshouldhavetotravelto accessparks(Hooperetal., 2018).Thesestandards helpensureequitabledistributionofparks,including desiredfacilities,amenities,andprogrammingacrossa community,buttheyneglecttoconsiderhowmembers ofcommunitiesusethespaces(Veal, 2013).
Measuresofvisitationtoparksareimportantfor understandingpatternsofgreenspaceuseinurbansettings.Focusedontheimpactofpublicresources,governmentsatalllevelsarechallengedwhenitcomesto showingtheimpactorbenefitoftheserecreational spaces(Spangler&Caldwell, 2007).Hence,theevaluationofpublicspacesisbecomingincreasinglyimportant aspopulationdensitiesincreaseandcompetinginterests forlandallocationarise(Tyrväinenetal., 2007). Essential,butcurrentlylackingisabetterunderstanding offactorsthatinfluencetheuse,preferences,experiences,andvaluesofurbanparksandthebenefits gainedbymembersofthecommunityfromusingthem (Dinnieetal., 2013;Veitchetal., 2021).Addressing thosegapswillfostermorestrategic,evidence-based decision-makingrelatedtofutureparkdesign,service provision,maintenance,orinvestmentstoaccommodate communityneeds.Suchrefinementstodecision-making shouldenablelocalgovernmentstobalancecompeting demandsonlandallocationandassetsorresources (Dinnieetal., 2013).Additionally,toadvocateeffectively forimprovedparkinfrastructure,publichealthandallied professionalswithstrongspatialskillsmustunderstand anddemonstratethebenefitsthatparkshaveforhealth behavioursandoutcomes(Henderson&Fry, 2011).
Localgovernmentcommunitysurveystypically collectinformationonthedemandforparticipationin outdoorrecreation,parkuse,andattitudes.In Australia,communitysurveysareoftenadhocand primarilyusedwhenanewpublicopenspacestrategy isbeingdeveloped,whichmaybeevery5to10years. Moreover,thetypeandqualityofthedatatypicallyvary considerablyacrosslocalgovernments,withlittleorno consistencyinsurveyitemsacrossjurisdictions.
Theaccuratemeasurementofparkuseisamissing linkbetweenunderstandinginteractionsamongpeople, urbangreenspaceenvironments,andhealthbenefits, anditrequiresfurtherexploration(Chenetal., 2020).
Keyinsights
Fewstudiesmeasuretheexactparkspeople use,eventhough “use” isoftenhypothesised intheaccess–healthrelationshipsbeingtested. TheParkLifepublicparticipatorygeographic informationsystem(PPGIS)isareliableinstrumenttocapturespatiallyreferencedinformation onparkuseandactivities.Suchinformationis essentialforpublichealthandphysicalactivity researchers,urbangeographersandplanners, andparkmanagerstodevelopinformedplanningandpublichealthpoliciesandprograms thatpromotetheuseofparks.
Thisknowledgegaphindersnewapproachesto parktransformationandrenovation,urbanplanning andparkdesign,andthedevelopmentofenvironmentalchangeinterventionstoimprovepopulationphysical activityandpublichealth.However,themeasurement andsurveillanceofparkuserequireappropriate, reliable,andaccurateinstruments.
Inresponsetothesecriticalresearchgaps, Section 2 providesareviewofdifferentmethodological approachesthathavebeenusedtomeasureparkuse inthegeographicalandpublichealthfields.Section 3 presentsworkonexistingpublicparticipatorygeographicinformationsystem(PPGIS)instrumentsthat havebeendevelopedtoassesstheuseofparksor naturalenvironments.Section 4 advancesthefieldof PPGISandpresentsatest–retestreliabilitystudyofthe ParkLifePPGISinstrumentfortheidentificationof parksusedandtheactivitiesundertakeninparks.
2 | APPROACHESTOMEASURING PARKUSE
Inpopulationhealthandphysicalactivityliteratures,severalapproacheshavebeenemployedtomeasurepark use(Joseph&Maddock, 2016;Sylviaetal., 2014). Numerousstudieshaveemployedobservation approachesandmomentarytimesamplingmethodsto recordparkusersbehavioursusingtoolssuchasthe SystemforObservingPlayandRecreationinCommunities(SOPARC)(Cohenetal., 2011;McKenzie etal., 2006)andtheEnvironmentalAssessmentofPublicRecreationSpaces(EAPRS)(Saelensetal., 2006).A fewstudieshaveuseduncrewedaerialvehiclessuchas dronesandwearablevideodevicestorecordparkuse andpark-basedphysicalactivity(Park&Ewing, 2017; Suminskietal., 2021).Dataarethenretrospectivelyanalysedtocountparkusersandcodeactivities.Alimitation ofsuchapproachesisthateachobservationalprotocol onlytellsresearchersabouttheuseoftheparksbeing
studiedorobserved.Thus,onlyafewparkswithingiven regionsareassessed,makingitimpossibletoaccurately generalisefindingstodeterminetrendsintheseregions andacrossacommunityorinrelationtothemultiple parkspeoplemayuse(Joseph&Maddock, 2016). Indeed,spatiallyexplicit,perceptual,anduseinformation atcity-widescalesisscarce(Ralletal., 2019).
GlobalPositioningSystem(GPS)technologyhas alsobeenusedtoidentifytheparksthatareused (Evenson,Wen,Hillier,&Cohen, 2013;Maddison& Mhurchu, 2009;Stewartetal., 2016).However,despite theincreasingreachandcapabilitiesofsmartphone technology,whichcouldbeusedforresearchpurposes, theparticipantburdenandprivacyconcernsassociated withlocation-basedresearchmayexplainthesmallnumberofstudiesusingthetechnologytodate(Evenson, Wen,Hillier,&Cohen, 2013;Stewartetal., 2016).Moreover,GPSprovidesnoinformationaboutthereasonsor motivationsforparksusedorthetypesofactivities undertakeninthem(Chenetal., 2020).
Othermethodsforanalysingparkuseinvolve “big data” fromlocation-basedsocialmedianetworks(Martí etal., 2019).User-generatedlocation-baseddataare referredtoasvolunteeredgeographicinformation becausetheexpressedperceptions,interests,needs, andbehavioursarepublishedonline,voluntarily,by users(Martíetal., 2019).Forexample,somestudies haveexaminedparkusebasedonthecountandvisual contentofphotographsgeolocatedwithinparks (Donahueetal., 2018;Hamsteadetal., 2018;Sessions etal., 2016;Songetal., 2020).Othershaveanalysed thelanguageofsocialmediaposts(Instagram), reviewspostedofurbanparksonGoogle(Nița etal., 2021;Parketal., 2022),andTwitter[X]postsrelevanttoparkandnatureexperiencesandrecreational activities(Parketal., 2022).
However,thesedataarenotwithoutlimitation.For example,concernshavebeenraisedaboutlackof representativenessofbothparticipantsandparks.The useofsocialmediaplatformsvariesaccordingtoage groupandwillingnesstogeotagpostsorsharecontent openly(Arribas-Bel, 2014;Heikinheimoetal., 2017; Heikinheimoetal., 2020;Martíetal., 2019).Onlyasmall portionofTwitterusersactivatethegeocodedfunction whenpublishingtweets(Martíetal., 2019),anddata retrievedfromInstagramarenotgeoreferencedtothe exactlocationfromwhichtheywereposted.Instagram hasdelimitedareaswithageolocatedcentrepointto whichalldatawithintheareawillbeassociated(Martí etal., 2019);thus,identificationofanyparkusedisnot reliable.Additionally,becausenopersonaldetailsare retrievedwhenextractingdata,asamplecannotberigorouslycharacterisedintermsofuserprofilesordemographiccharacteristics(Chorleyetal., 2015;Martí etal., 2019).Whileautomatedcontentanalysisofsocial mediadatahasbeenusedtogaininsightsabout revealedactivities,interpretingphotographcontentmay
belessstraightforwardbecausetheperceptionand meaningofwhataphotographdepictscanbehighly subjective(Oteros-Rozasetal., 2018;Song etal., 2020).Moreover,reported “parkuse” behaviour maydependonthecontextofaparkvisit,whichhas implicationsforparkusedatathatrepresenttypicalpark use.Forexample,usersmaybelesslikelytotagthemselvesorshareaphotoinatypicalneighbourhoodpark regularlyusedcomparedwithavisittoalarger,unique, ordestinationpark(Zhang&Zhou, 2018).Indeed,validationagainstnationwidehouseholdsurveyshasshown thatparkphotographyreflectsresidents’ favouriteparks betterthantheirself-reportedfrequencyofvisits(Song etal., 2020).Moreover,thedataprovidenoinformation onwheretheuserhascomefrom,howoftentheyuse thepark,ortheactivitiestheyengageinatthepark.
Assuch,self-reportsurveymeasuresofparkuse remainwidelyusedforlargerscaleparkusestudies andarecrucialforunderstandingpeople’svaluesand motivationsbehindoutdoorrecreation(Tieskens etal., 2018).Inasmallnumberofrecentstudies fromAustralia(Edwardsetal., 2015;Hooper etal., 2020),Singapore(Petrunoffetal., 2021),andthe UnitedStates(Walkeretal., 2009),participantswere askedtodescribetheparkstheyused,whichwere subsequentlymapped.However,ineachcase,the mappingrequiredthatthereportedparksbematched withthoseinspatialdatabasesofparks.Thistaskis time-consuming,particularlyiftherearediscrepancies betweenparknamesreportedbyparticipantsandofficialparknames.Moreover,people’sperceptionsor usesofparksdonotalwaysalignwiththedemarcated areasidentifiedorzonedandmanagedbylocal governmentsaspublicopenspaces.Asaresult,use patternsandattitudestowardsinformalorunmanaged componentsofurbangreenspacearetypicallynot recognisedorincludedinstudiesofparkuse.
Analternativeapproachforcapturingparkusedata thatovercomesmanyofthesemethodological shortcomingsisonline-basedPPGIS.ThetermPPGIS referstodiversemethodsthatengagepeopleingeneratingspatiallyexplicitinformationforvariousplanning anddecision-makingpurposes(Tulloch, 2008).Mappingactivitiesarecommonurbanplanningcommunity engagementstrategies(Kahila-Tanietal., 2019).With thedevelopmentofspatialwebtechnologies,online geo-questionnairesandPPGISareconsideredeffectivetoolstodeepenunderstandingsofquantitativedata (Saadallah, 2020)andtouseinurbanandregional geographyandplanningpractices(Kahila-Tani etal., 2019).PPGISsurveyscanmeasureuses, experiences,andperceptionsinvarioussocialcontexts (Dinnieetal., 2013).Participantstypicallyidentify spatiallocationsonamapandprovidedataspecificto thatlocationforanalysis.Importantly,PPGISmapscan besettocollectdataatvariedscalesandenable respondentstofocusontheirchosenarea.Thus,
researcherscanexplorethehealthoutcomesassociatedwithreportedplacedatawithoutenforcingpreconceivedneighbourhoodboundaries.Anotheradvantage ofPPGISisthatitreducesdatacollectioncostsand increasestheprecisionandefficiencyofspatialdata entryandcollation(Brown&Reed, 2009).Inthecontextofstudyingparkuse,PPGISgeneratesorcaptures high-qualitydatasoresearchersandpractitionerscan understandwhoisusingparks,whatparkstheyare using,andwhytheyareusingthesespaces (Heikinheimoetal., 2020).
Weidentified13studiesthatusedPPGISmethods thatfocusedonurbangreenspaces(Bijker& Sijtsma, 2017;Brownetal., 2014, 2018;deVries etal., 2013;Heikinheimoetal., 2020;Hughey etal., 2021;Korpiloetal., 2021;Latinopoulos, 2022; Pietrzyk-Kaszynskaetal., 2017;Ralletal., 2019; RamírezArandaetal., 2021;Raymondetal., 2016; Schrammeijeretal., 2022).Ninestudiesexplicitly askedparticipantstoidentifyandmapthegreen spacestheyused.However,thespecificinstructions andrecallperiodsdifferedacrossallstudies(forexample, “visitmost” [Schrammeijeretal., 2022], “spendthe mosttimein” [Latinopoulos, 2022], “usedinthepast 30days” [Hugheyetal., 2021], “frequentlyvisit” [Korpiloetal., 2021], “usedforactivitiesinthepasttwo weeks,”“placeswhereyouspendtimewithingreen spaces” [Pietrzyk-Kaszynskaetal., 2017],and “areas youenjoyusing” [Raymondetal., 2016]).Theremainingfourstudieswerelessexplicitintheirinstructions, askingparticipantstomapgreenspacesthatweretheir “favourite ” (Raymondetal., 2016), “meaningful” (Rall etal., 2019),or “attractive,valuableorimportant” (Bijker&Sijtsma, 2017;deVriesetal., 2013).
However,peoplemayvalueparks,greenspaces,or naturalenvironmentswithoutvisitingorusingthem. Therewasalsosomeambiguityaboutwhatismeasured inthesestudies.Phrasesaboutthe “activities” engaged inwithinthespaces,the “motivations” foruse,orreasonstheparkswere “attractive” forusealsodiffered acrossthestudiesfromaskingabout “activities” (Brown etal., 2014, 2018;Raymondetal., 2016), “benefits” (Brownetal., 2014, 2018), “culturalpractices” (Ramírez Arandaetal., 2021), “culturalecosystemservices” (Ralletal., 2019),or “qualities” (Bijker&Sijtsma, 2017; deVriesetal., 2013).Thesedifferencesmake comparisonacrossstudiesdifficult.Exceptforarecent studybyHugheyetal.(2021),theuseofPPGISto measureparkuseandphysicalactivityhas,todate,not beendeployedinpublichealth-focusedresearch.
Furthermore,participatorymappingreliesonindividuals’ abilitiestorecalltheirexperiencesinplacesor landscapesandlocatethepotentialaffordancesof thesespacesonadigitalmap(Brown&Kyttä, 2014).It isessentialtounderstandwhetherpeoplecanreliably recalldetailsoftheirparkuseandassociatedactivities andconfirmifPPGISinstrumentsaresuitablefor
collectingthesedatainpopulationmonitoringandsurveillancestudiesofparkuseandhealthoutcomes.To date,studiestestingthevalidityandreliabilityofPPGIS technologiesandmethods,includingthosetocapture parkuse,havenotbeenconducted(Chenetal., 2020). Thislackofreliabilitydataremainsasignificantgapin thefieldandapplicationsofPPGIS.
3 | METHODS
Followingethicsapprovals,the “ParkLife” PPGISwas developedasanonlinegeo-questionnaireinwhichparticipantsindividuallyansweredaseriesofquestions thatwereaccompaniedbyinteractivemapsthatprovidedgeographicalcontextabouttheirparkuse.There werenoconstraintsonthelocationorspatialextentof parksthatcouldbeidentifiedoronthenumberofparks thatcouldbemapped.Thespatialcaptureofdata allowedtheresearchteamtoeasilyintegrateingeographicinformationsystem,thespatiallylinkedpark data,andindividualparticipantinformationandcharacteristics.ThesurveywasbuilttocapturedataAustraliawide,butforthistest–reteststudy,datacollectionwas focusedonPerth,thecapitalcityofWesternAustralia. Thesurveyquestionsandprotocolareoutlinedin Figure 1.Allquestionswereinformedbypreviously implementedlocalgovernmentsurveys,parkliterature, andapanelofexpertscomprisinglocalgovernment parksandplanningmanagers,urbanplanningofficers, andplanningconsultants.
Socialdemographicvariablesoftenmoderatethe builtenvironmentandhumanhealthrelationships.As such,demographicdatatypicallyusedforstudiesthat examineassociationsbetweentheuseofgreenspace andhealthoutcomeswerecollected.Demographic questionscapturedinformationonparticipants’ gender, age,education,income,employmentsituation,living arrangement,dogownership,andsportsclub/team membership.
Participantswererecruitedbyamarketresearch companythatmaintainsadatabaseofpanellistsand randomisesparticipantstospecificsurveysdepending onthedemographicrequirementsofthestudyandthat providesparticipantswithmodestcompensation. PanellistswholivedinthePerthmetropolitanareain WesternAustraliawereinvitedtoparticipate.Toassess test–retestreliability,theParkLifePPGISparticipants (n = 150)weresentthesurveylinkforasecondtime 1weekaftercompletionofthefirstsurvey.Onboth occasions,participantswereemailedalinktothePark LifePPGIS,whichwasconductedonline.
AllanalyseswereperformedusingSPSSVersion 26.0.Kappascores(κ)wereusedtoassessthereliabilityofthecategoricalsurveyitems.Intra-classcorrelations(ICCs,two-waymixed-effectsmodelwith95% confidenceintervals)wereusedtoassessthereliability
ofcontinuoussurveyitems.Interpretationofthecoefficientsreliedonagreement-levelratingsassuggested byLandisandKoch(1977):0–0.2 = poor agreement; 0.21–0.40 = fair agreement;0.41–0.60 = moderate/ acceptable agreement;0.61–0.80 = substantial agreement;and0.81–1.0 = near-perfecttoperfect agreement.
4 | RESULTS
Ninety-oneparticipantscompletedtheParkLifePPGIS twice.Thedemographiccharacteristicsofthestudy samplearepresentedusingdatafromTest1andare
FIGURE1 TheParkLifepublic participatorygeographicinformation system(PPGIS)protocolandquestions.
outlinedinTable 1.Sixty-twopercentofthestudyparticipantswerefemale,50%wereinfullorpart-time employment,28%hadchildrenlivingathome,almost 30%hadadog,27%wereasportsclubmember,and themajority(82%)wereborninAustralia.
4.1 | Test–retestreliabilityofthePark LifePPGIS
Table 2 presentstheKapparesultsoftheParkLife PPGIStestandretest.Themediantimebetweenthe twoParkLifesurveyswas8.7days(range6.5
21.1days).Onaverage,30%ofparticipantsreported
usingaparkmonthly(32%Test1and29%Test2), 45%usedaparkonaweeklybasis(45%Test1and 44%Test2),andabout25%reportedusingapark daily(23%Test1and26%Test2)(Table 2).The “parkuse” screeningquestionthatdeterminedthelevel
ofusualparkuseshowed substantial agreement (kappa = 0.706, p <0.001).
Theparkidentifiedasusedmostoftenshowed near-perfect agreement(kappa = 0.900, p <0.001). Threeparticipantsmappedgreenspacelocationsoutsidetheparkpolygonsdisplayedinthemappinginterface.Assessmentofthesepinnedlocationsrevealed thattwowereschoolplayingfieldsaccessibletothe publicandoneparticipanthadmappedanareaof bushlandthatincludedinformalwalkingtracksthroughoutthatwereaccessibletothepublic.Allthreeparticipantsmappedthesesamelocationsontheirrespective testandretestsurveys.
Onaverage,participantsselectedthreeactivities (range1–6)relatingtotheparkusedmostoften.Ofthe 16parkactivityvariables(Table 2),twoshowed nearperfect agreement,three substantial agreement,three moderate/acceptable agreement,andfour fair agreement.Walkingwasthemostfrequentlyreportedactivity (81%Test1and77%Test2)followedbyexperiencing natureorwildlife,scenery,orviews(37%Test1and 43%Test2),sitting,resting,andrelaxing(37%Test 1and29%Test2),andwalking/exercisingadog(23% Test1and27%Test2).Thepercentagreementofthe 16parkactivityvariablesintheparksused “mostoften” washigh,withallabove75%.Fourteenvariableshad percentagreementsof>80%,with10having>90% (Table 2).
Recalloftheparkvisitationshowedgoodreliability: Frequencyofvisitationtothemappedparksshowed near-perfectagreement(ICC = 0.965,resultnot shown).Timespentattheparkshowed substantial agreement(kappa = 0.706, p <0.005);thosewith whomparticipantsvisitedtheparkshowed near-perfect agreement(kappa = 0.965,0.816, p <0.001,respectively);andthedaysofparkvisitsshowed substantial agreement(kappa = 0.753, p <0.001).Theusual modeoftransportitemshowed near-perfect agreement (kappa = 0.913, p <0.001),andthree-quartersofparticipants(76%Test1and77%Test2)walkedtotheir park.Mostparticipants(99%Test1and97%Test2) indicatedthattheirjourneytotheparkstartedfrom home,andtheseitemsachieved “near-perfect” agreement(kappa = 0.795, p <0.001).
Twenty-two(24%)participantsmappedasecond parkthattheyregularlyused,andfive(6%)mappeda thirdparkthattheyregularlyused.Whereasecondor thirdparkwasmapped,therewas near-perfect agreementfortheparksmapped(kappa = 0.896,0.886, p <0.001,respectively).Justfivedifferentactivities wereidentifiedwhereasecondregularlyusedpark wasmapped(Table 2).Again,themostfrequently reportedactivitywaswalking(81%Test1and77% Test2).Recallaboutsitting,resting,relaxing,and experiencingnatureorscenerywas moderate/acceptable (kappa = 0.625, p = 0.005;kappa = 0.667, p = 0.002),socialisingormeetingfriendsorfamily,and
Parkusedmostoften
Howoftenyouusuallyvisitparks?
Daily23.126.40.706<0.001Substantial Monthly31.929.2 Weekly45.144.4
Mappedpark(s)
Parkusedmostoften--0.922<0.001Near-perfect Park2usedregularly--0.896<0.001Near-perfect Park3usedregularly--0.886<0.001Near-perfect Numberofparksmapped1.31.20.713<0.001Substantial Parkactivities
Whatactivitiesdoyouusuallydoat[mappedparkname]?
Walking83.574.70.669<0.001Substantial Running/jogging9.911.00.861<0.001Near-perfect Walking/exercisingadog23.127.50.839<0.001Near-perfect Socialising/meetingfriendsorfamily19.822.00.684<0.001Substantial Organisedsportscompetitionsortraining0.00.0--Organisedactivities,fitnessclasses,bootcamps, personaltrainingsessions 2.61.9---
Supervisechildrenonplayequipment17.219.80.604<0.001Moderate Sitting,resting,relaxing37.428.60.523<0.001Moderate Cycling3.35.50.479<0.001Moderate Experiencenatureorwildlife,scenery,orviews41.842.90.537<0.001Moderate BBQorpicnicking11.06.60.588<0.001Moderate Watchingsport4.45.50.737<0.001Substantial Usefitnessequipment/outdoorgym2.23.40.795<0.001Substantial SkatePark/BMXorpumptrack0.00.0--Attendcommunityactivities,special/major events,markets,concerts,festivals
13.215.70.520<0.001Moderate Parkvisitation
Howmuchtimedoyouusuallyspendat[mappedpark]oneachvisit?
30minorless44.044.00.705<0.005Substantial 30minto1h41.844.9 1to2h13.212.1
Morethan2h1.10.0
Whodoyounormallyvisit[mappedpark]with?
Adog16.514.30.816<0.001Near-perfect Alone40.742.9
Children16.517.6
Exercisegroup/trainer0.01.1
Sportsteamorrecreationalclub0.00.0 Friends/family26.424.2
Whatmodeoftransportdoyouusuallytaketogetto[mappedpark]?
Cycle5.54.40.913<0.001Near-perfect Motorvehicle18.718.7 Walk75.876.9
ParkLifePPGISitems
Whatdaysoftheweekdoyouusuallyvisit[mappedpark]?
Weekday22.017.40.753<0.001Substantial Weekend20.917.3
Both57.165.3
Whenyouvisit[park],wheredoesyourjourneyusuallystartfrom?
Home98.897.30.9130.795Near-perfect
Work1.21.6
Other0.0%1.1%
Otherparksregularlyused Parkactivities
Whatactivitiesdoyouusuallydoat[mappedparkname]?
Walking81.076.70.6400.002Substantial Walking/exercisingadog19.018.31.000<0.001Perfect Socialising/meetingfriendsorfamily28.619.00.741<0.001Substantial Sitting,resting,relaxing28.623.80.6250.005Moderate Experiencenatureorwildlife,scenery,orviews33.328.60.6670.002Moderate Park2regularlyusedvisitation
Howmuchtimedoyouusuallyspendat[mappedpark]oneachvisit?
30minorless33.333.30.656<0.001Substantial 30minto1h42.937.6 1to2h19.019.0 Morethan2h4.80.0
Whodoyounormallyvisit[mappedpark]with?
Whatmodeoftransportdoyouusuallytaketogetto[mappedpark]? Cycle4.84.80.625<0.001Substantial
Abbreviation:PPGIS,publicparticipatorygeographicinformationsystem.
walkingshowed substantial agreement (kappa = 0.741, p <0.001),andwalkingorexercising thedogshowed “perfect” agreement(kappa = 1.000, p <0.001).Recallofthesecondparkmapped
(regularlyused)againalsoshowedexcellentreliability: Timeusuallyspentattheparkshowedsubstantial agreement(kappa = 0.656, p <0.001);frequencyof visitationandwhotheynormallyvisittheparkwith
showed near-perfect agreement(kappa = 0.806, 0.865, p <0.001,respectively).Theusualmodeof transporttothepark,usualdaysoftheweekvisiting thepark,andusualplaceoforiginallshowed substantial agreement(kappa = 0.625,0.777,0.644, p <0.001,respectively).Moreparticipantsvisitedthe secondparkfromanoriginotherthanhome(5%Test 1and10%Test2).
5 | DISCUSSION
Thoseinpublichealthandparksandrecreational planningareinvestedinpromotingparkuse.Public healthadvocates includingurbangeographersand planners haveastakeinfosteringpeople’svisitsto parkstopromotehealth-enhancingbehaviourssuchas physicalactivity.Geographersandplannershavea stakeinfosteringvisitsaspartoftheirmissiontostudy and/orprovidequalityrecreationalandleisureexperiences(Krugeretal., 2007).Assuch,themeasurement ofcontext-specificbehavioursisvitaltoimprovingthe predictivecapacityforstudiesthatmeasureenvironmentalcorrelatesofhealthbehavioursandoutcomes. However,abetterunderstandingofthecommunity’s useofparksisrequired,whichinturnnecessitatesthe needforreliableinstrumentstomeasureparkuse. PPGIShasgrowninpopularityasatooltocapture spatiallycontextualiseddataforuseinurbanand regionalplanningpracticeandacademicresearchin planning-relatedandbuiltenvironmentfields(KahilaTanietal., 2019).
PublishedevaluationsoftheeffectivenessofPPGIS havefocusedonparticipationratesand spatialdata quality andaccuracy(Kahila-Tanietal., 2019).Inthis paper,wehaveexaminedthetest–retestreliabilityof theParkLifePPGISforcapturingparkuseandactivities.Toourknowledge,thisstudyisthefirsttoundertakeatest–retestreliabilityanalysisonaPPGIS designedtocaptureurbanparkuse.Thetest–retest resultsindicatethatindividualswereabletoreliably recalltheparkstheyusemostoftenversusthosethey useregularlyandcouldmapthesespacesona digitalmap.
TheParkLifePPGISassesses “usual” parkuse behaviourratherthanadefinedrecallperiodsuchas thelastweekor7days.Therepeatabilityofthe “usual parkuse” questionwas substantial,indicatingthatparticipantswereabletounderstandtheconstructofthe questionandreliablyindicatetheirusuallevelofpark use.Theuseofa “usualframe” inphysicalactivity measurementquestionnaires(Giles-Cortietal., 2006) hasbeenfoundtohaveminimaldifferencesinpsychometricqualitycomparedwiththepastweek’squestions andminimiseinherentweeklyvariationinphysical activity(Domaetal., 2017).Conversely,aprevious parkusestudyfoundhigherreliabilitycoefficientsfor
parkvisitfrequencyanddurationofusewitha “usual week” framethana “pastweek” recall(Evenson,Wen, Golinelli,etal., 2013).Ausualstructurealsoprovidesa morestablemeasureforuseinlongitudinalorexperimentalstudiesseekingtomonitorchangesinparkuse behaviourinthesameindividualovertime(Giles-Corti etal., 2006).Thisdetailisalsoimportantfordetectinga changeinparkuseformonitoringorsurveillance applications.
Recallandmappingoftheparkusedmostoften, andadditionalparksusedregularly,wasveryhigh,with kappacoefficientvaluesinthe near-perfect range. Importantly,thissuggeststhatparticipantscouldreliablydifferentiatebetweenparksusedmostoftenand thoseparksusedregularly.Furthermore,participants wereabletolocatetheirparksonthedigitalmap.The useofGoogle® basemapswaschosentoincrease thefamiliaritywiththeuserexperiencewhenmapping theparks.ArecurringquestionforthoseusingPPGIS asaresearchmethodordatacollectioninstrumenthas beenthespatialaccuracyofthedatacollectedwitha presumptionofPPGISmarkerplacementvalidity (Brownetal., 2015).Inthisstudy,spatialaccuracywas lessofaconcern,giventhatmarkerswereintendedto beassociatedwithapark.Thepotentialforspatialerror wasalsomanagedbydisplayingpolygonsrepresenting parklocationsinthemapwindowtohelpguidethe participant.TheGoogle® searchbaralsoallowed participantstosearchquicklyfortheparktheywanted tolocate.Moreover,toimprovespatialaccuracy, participantswhoselectedalargepark(>10ha)were askedtomovethepintotheareaoftheparkthey typicallyused.
Theparkspeopleuseandtheactivitiestheyundertakeareshapedbyacomplexinteractionbetweentheir individualneeds,preferencesforcharacteristicsof specificlocations,andperceivedaccessibilityand suitabilityoftheparklocations(Chenetal., 2019). Consideringarangeofdifferentrecreationalactivities undertakeninparksisthereforeessentialtounderstandthevariousbenefitsprovidedbyurbanparks (Chenetal., 2019;Krellenbergetal., 2021),better informplanningdecisionsandpublichealthinterventions,andfacilitatethedevelopmentofliveableurban areasthatpromoteparkuse,andhealthandwell-being benefits(Hansenetal., 2019).Allparkactivityitems showed moderate/acceptable orhigherreliability,with fiveactivitiesshowingsubstantialor near-perfect agreement,indicatingthatpeoplecouldreliablyrecall theirparkactivities.Thehighkappavaluesoftheactivitiesreportedinmultipleparksusedindicatethatparticipantswereabletoreliablyandaccuratelyrecall differentactivitiesundertakeninmultipleparks.
ThedetaileddataelicitedfromPPGISsituatethe ParkLifePPGISasaviablemethodthatcouldbeused tocreatepark “quality” scoresbasedonreported amenitiesusedinparks,ratherthansimplyassigning
scoresbasedonthenumberoffeaturesoramenities present.Previousparkqualityscoreshavereliedon objectivedataprimarilyrelatedtofacilityprovision,which failstoaccountforsubjectiveelementsofqualityorecological,cultural,spiritual,orsocialvaluationofthe spaces(DeVreeseetal., 2016).Capturingparkusers’ activitiesandexperiencesallowsforamorebalanced approachtoparksplanning(Ralletal., 2019).Thelistof parkactivitiesusedinthisstudyisapplicabletoother parksinAustralia.However,whenappliedinothercountriesorsettings,theactivitiesmayrequiremodification.
Twodistinctlydifferentmappingapproacheshave beenemployedinearlierapplicationsofPPGISof urbangreenspaceuse.Thefirstapproachaskedparticipantstoidentifyandmapgreenspacesusedorvaluedandthenelicitedinformationonactivities,values, ormotivationsforuseassociatedwiththatgreenspace, fromeitheralistofoptionsoropen-endedresponses. Thesecondapproachprovidedaseriesofpinsrepresentingdifferentactivitiesorvaluesthatparticipants markedonthemaptodefinethegreenspacesinwhich theyengagedinthoserespectiveactivitiesorwere associatedwiththeindividualvalues.TheParkLife PPGISemployedthefirstmethod,becausethealternativeapproachresultsinamultiplicativeeffectofthe responseburdenwiththeplacementofeachmarker (Brownetal., 2015).Moreover,identifyingabehaviouralcontextorsettingmayassistwiththerecall, whichmayaccountforthehighkappacoefficients.
Themappingapproachusedinthestudypresented severaladvantagesovertheuseofsocialmediagenerateddataopportunisticallyextractedbyresearchers. Forexample,ParkLifePPGISpinpointstheparksand openspacesused,avoidingthepitfallsassociatedwith thespatialinaccuracyofphoto-sharingplatforms (Muñozetal., 2020).TheParkLifePPGISapproach enablesgreenspaceplannerstoconsiderthequantity anddistributionofparkswherepeoplecanpursue variousactivities,aswellasmeettheneedsand expectationsofdifferentkindsofusers(Bertram& Rehdanz, 2015).Thisapproachmayalsoinclude assessingthevaluesandusesofinformalgreen spaces,whichoftendonotreceiveattentionin greenspaceplanning(Ralletal., 2019).
Althoughthisstudymakesauniquecontributionto theevidence,ithassomelimitations.First,the participantswererecruitedthroughamarketresearch companyandfinanciallycompensatedfortheirparticipation,whichmayhaveimplicationsfortheaccurate depictionofparkusebehaviour.Byusinganexternal marketresearchcompany,wedonothaveinformation ofthedemographiccharacteristicsofparticipantswho didnotcompleteboththetestandretestsurveys. However,thesample’sdemographiccharacteristics indicateddemographicdiversityinthepopulationand thesamplesizeinthisstudyiscomparablewithother physicalactivitytest–reteststudies(Brownetal., 2004;
Frehlichetal., 2018;Giles-Cortietal., 2006).Second, justunderaquarterofparticipants(24.2%)reported andmappedusingtwoparks.Evenfewer(5.5%)identifiedthreeparkstheyregularlyused.However,among theseparticipants,therewasnoattritionbetweenthe testandretestsurveyinthenumberofparksmapped, suggestingthattherewerenoproblemsassociated withuserwillingnessoracceptancetomapthese. Third,therewaslimitedvariabilityintheactivitieslisted forthesecondmappedparkregularlyused.Thisfactis likelyduetothesmallnumberofparticipantsidentifying asecondpark.Again,thekappacoefficientsforthese activitiesshowed “moderate/acceptable” orhigherreliability.Theslightlylowerkappacoefficientsforthesecondparkactivities(comparedwiththeparkusedmost often)mightindicategreatervariabilityintheactivities undertakenintheseparksand/orthelessregularuse.
TheuseofPPGIStocaptureparkusecouldbeeasilyintegratedintolocalgovernmentpublicopenspace communityconsultationsurveystoprovidebenchmarks ofcommunityparkuseandbenefitsandevaluateany parkupgradesorinterventions.Itshouldbecoupledwith instrumentstoquantifythecontributionsofpark-based physicalactivitytototalphysicalactivitylevels,suchas theParkPhysicalActivityQuestionnaire(Park-PAQ)that hasbeenshowntohaveacceptablereliabilityinprovidingatotalmeasureofphysicalactivityanddetermining theproportionofanindividual’stotalphysicalactivity undertakenwithinparks(Edwards&Hooper, 2023).
Insummary,theParkLifePPGISwasfoundtobea reliableinstrumenttocaptureparkuseandactivities. TheParkLifePPGISadvancesthemeasurementof parkusebehavioursbyexplicitlyaddressingthemissing “exactparklocation” datainpublichealthresearch andpublicopenspaceplanningpolicyandpractice. Thisstudyconfirmsthatpeoplecanreliablyrecall detailsoftheirparkuseandassociatedactivitiesand locatethespacestheyuseonadigitalmap.Further, thecollationofexactparklocationdata,coupledwith park-basedactivitydata,providesaccuratedata neededtoenablebetterpublicopenspaceplanning.
Moreover,thisreliabilitystudyadvancesthefieldof publicparticipatorymappingmethodsandprovides evidenceonthereliabilityofPPGISinstrumentsthat waspreviouslylacking.TheParkLifePPGISelicits informationonparkusethatisessentialforpublic healthandphysicalactivityresearchers,urbanplanners,andparkmanagerstodevelopinformedplanning andpublichealthpoliciesandprogramsthatpromote theuseofparks.
ACKNOWLEDGEMENTS
WeacknowledgethecontributionsofDrRamPandit (UWA)andProfessorMichaelBurton(UWA)fortheir contributionstoprojectconceptualisationandsurvey developmentandDrJulianBolleter(UWA)andDr SarahFoster(RMIT)forreviewingearlyversionsofthe
surveycontent.Openaccesspublishingfacilitatedby TheUniversityofWesternAustralia,aspartofthe Wiley-TheUniversityofWesternAustraliaagreement viatheCouncilofAustralianUniversityLibrarians.
CONFLICTOFINTERESTSTATEMENT
Theauthorsdeclarenocompetinginterests.
DATAAVAILABILITYSTATEMENT
Dataareavailableonrequestfromtheauthors.
ETHICSSTATEMENT
TheUniversityofWesternAustralia’sHumanEthics Committeeprovidedethicsapproval(2019/RA/4/1/8734).
ORCID
PaulaHooper https://orcid.org/0000-0003-4459-2901
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Howtocitethisarticle: Hooper,P.,&Edwards, N.(2024).AreliabilitystudyoftheParkLife publicparticipatorygeographicinformation systemsurvey. GeographicalResearch, 62(1), 134–146. https://doi.org/10.1111/1745-5871. 12629