HAL Id: hal-01314717
https://hal-amu.archives-ouvertes.fr/hal-01314717
Submitted on 5 Oct 2016
HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.
L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
French validation of the 7-item Game Addiction Scale for adolescents
Sophie Gaetan, Agnès Bonnet, Vincent Bréjard, François Cury
To cite this version:
Sophie Gaetan, Agnès Bonnet, Vincent Bréjard, François Cury. French validation of the 7-item Game
Addiction Scale for adolescents . European Review of Applied Psychology / Revue Européenne de
Psychologie Appliquée, Elsevier, 2014, 64, �10.1016/j.erap.2014.04.004�. �hal-01314717�
Original article
French validation of the 7-item Game Addiction Scale for adolescents
Validation franc¸ aise de la Game Addiction Scale à 7-items pour adolescents
S. Gaetan
a,∗, A. Bonnet
b, V. Brejard
b, F. Cury
a,caFacultédessciencesdusport,Aix-Marseilleuniversité,ISM,UMR-CNRS7287,163,avenuedeLuminy,case910,13288Marseillecedex09,France
bAix-Marseilleuniversité,LPCLS,EA3278,13331Marseille,France
cUniversitéduSudToulonVar,83130LaGarde,France
Keywords:
GameAddictionScale Psychometricproperties Adolescents
a b s t r a c t
Motsclés:
GameAddictionScale Propriétéspsychométriques Adolescents
ré s um é
Introduction.–LaGameAddictionScale(GAS:Lemmens,Valkenburg,&Peter,2008,2009)estunoutilde mesurecourt(7items)permettantd’évaluerspéciquementlapratiquevidéo-ludiquedesadolescents, quelquesoitleformatdejeuvidéoutilisé.
Objectif.–L’objectifdecetravailestd’analyserlespropriétéspsychométriquesdecetteversionfranc¸aise delaGAS.
Méthode.–Deuxétudesontétémenéesauprèsdedeuxéchantillonsd’adolescentsfranc¸ais,âgésde10à 18ans(étude1:n=159;étude2:n=306).Lesanalysesdestructurefactorielleetdelaconsistanceinterne onttoutd’abordétémenéesdanslapremièreétude.L’analysedelavaliditéconcouranteaensuiteété ajoutéedanslasecondeétudeavecl’estimationdutempsdejeuquotidien,lamesuredeladépressionet del’anxiété.
Résultats.–Auseindesdeuxétudes,lesanalysesfactoriellesontmisenavantunestructureunidimen- sionnellequidisposedebonnespropriétéspsychométriquesetquis’ajusteauxdonnées.Lesanalysesont égalementconfirméelaconsistanceinternedel’outil.Deplus,lesanalysesdecorrélationeffectuéesdans ladeuxièmeétudeontmisenavantdeslienspositifssignificatifsentrelescoredelaGASetletempsde jeuquotidien,lescorededépression,celuid’anxiétéetlefaitd’êtreungarc¸on.Cesélémentsconfirment lavaliditéconcourantedel’échelle.
∗ Correspondingauthor.
E-mailaddress:[email protected](S.Gaetan).
1. Introduction
Videogameusersrepresentapproximately40%oftheFrench population(NationalSyndicateofVideoGames,2012).Adolescents aretheprimaryusersofvideogames(Fortin,Mora,&Trémel,2005):
91%of6-to14-year-oldand95%of15-to24-year-oldarevideo game players (French Videogame Agency, 2010). Yet excessive playingofvideogameshasbecomeaprobleminmodernsociety andismanifestingitselfintreatmentcentersforadolescents.
Videogameaddictioncanbedefinedas“excessiveandcom- pulsiveuseofvideogamesthatresultsinsocialand/oremotional problems;despitetheseproblems,thegamerisunabletocontrol thisexcessiveuse”(Lemmens,Valkenburg,&Peter,2009,p.78).The definitionoftheterm“addiction”isstillunderdebate,andmany authorsprefertospeakof“excessive”or“problematic”videogame playing.Nonetheless,somestudieshavedrawnaparallelbetween pathological gamblingandplaying behavior (Griffiths &Davies, 2005;Parker,Summerfeldt,Taylor,Kloosterman,&Keefer,2013;
Parker,Taylor,Eastabrook,Schell,&Wood, 2008).Somecriteria usedtodescribevideogameaddiction,suchascognitivesalience, tolerance,andeuphoria,arerelatedtoahighlevelofinvolvement andcanberegardedas“peripheral”criteria(Wood,2008).When thesecriteriaindicatealevelofinvolvementthathasconsequences ondailylife,thenthebehaviorcanbeseenasnon-normal.Todefine addictivebehavior,othercriteria—the“core”ofaddiction(Wood, 2008)—mustbepresent:conflict,withdrawalsymptoms,relapse, andsalience.VanRooij,Schoenmakers,Vermulst,VandenEijnden, andVandeMheen(2010)madethedistinctionbetweenaddicted andnon-addicted“heavygamers”onthebasisofthepsychologi- cal,social,and/orphysicalimplicationsofthisinvolvementondaily life(King,Haagsma,Delfabbro,Gradisar,&Griffiths,2013;Tejeiro Salguero&BersabéMoran,2002).Thelossofcontroldespitenega- tiveconsequencesisasignofaddictiveuse(Lemmensetal.,2009), whichcanbeaccountedforintermsof“dysfunctionalpreoccupa- tions”(Parkeretal.,2008,2013).
Griffiths’ descriptive approach to video game addiction (Griffiths&Davies,2005)isbasedonBrown’sclinicalcriteriaof pathologicalgambling(Brown,1993).TejeiroSalgueroandBersabé Moran(2002)adaptedthesecriteriatoadolescentvideogameplay- ingasfollows:
•increasedtime spent playing or thinking about video games, schedulingnextgame,orrememberingpreviousgames;
•badmoodorirritabilitywhenit’simpossibletoplay;
•increasedtimespentplayingduringdifficulttimes;
•failedattemptstocontrolgameplayingtime;
•concealingthetimespentplayingfromparentsorfriends;
•failingtodohomework,orlyingaboutit,inordertoplayvideo games;
•sleepingin, missedmeals,and lesstime spentwithfamily or friendsinordertoplaymore.
Lemmens,Valkenburg,and Peter(2008)and Lemmenset al.
(2009) relied on these criteria to develop the 21-item and 7- itemGameAddictionScales[GAS],whicharespecificallyaimedat assessingallkindsofvideogameplayingandarewell-suitedtoado- lescents.Responsesarescoredonafive-pointLikertscale,which
affordsgreater sensitivity than dichotomous tools. Theauthors (Lemmens et al.,2009)conducted two surveyswith two inde- pendent samples of adolescents (sample 1: n=352, 67% boys;
sample 2: n=369, 68% boys). In both samples, the age varied between12and18years(sample1:M=14.80,SD=1.64;sample 2:M=15.20,SD=1.35).Confirmatoryfactoranalysis(CFA)ofthe 21-itemGAS wasperformedand revealed a good structural fit (sample1:2(182)=594.40,p<.001;CFI=0.90;RMSEA=0.08with a90%CI[0.07,0.09]).Todeterminewhethertheirmodelheldforthe secondsample,theyperformedamultigroupanalysis.Themodel exhibitedanadequatefitanditsstructurewasverysimilarinthe twosamples.Cronbach’salphaindicatedgoodinternalconsistency ineachsample(␣=0.94and␣=0.92).Exploratoryfactoranalysis (EFA)wasperformedand revealeda single-factorstructurethat accountedfor 47.40% of thevariance.Loadings ofthe21 items forthecombinedsamplewerecomputed(factorloadingsvaried between0.48and0.85).Theitemswiththehighestoverallloadings on each of the seven factors were selected in order to deter- minewhatitemstouseforthe7-itemGAS.Multigroupanalysis was performed. The model exhibited an adequate fit (uncon- strainedmodelforbothsamples:2(28)=69.90,p<.001;CFI=0.97;
RMSEA=0.05witha90%CI[0.03,0.06])anditsstructurewasvery similarinthetwosamples.The7-itemGASshowedgoodinternal consistencyineachsample(␣=0.86and␣=0.81).Finally,thesig- nificantlinkbetweentheGASscoreandthetimespentongames, loneliness,lifesatisfaction,aggression,andsocialcompetenceindi- catedtheconcurrentvalidityofbothversionsoftheGAS(7-and 21-item).
EventhoughtheGASwasnotvalidatedclinically,theauthors suggestedusingacutoffpointinlinewiththepolytheticformat appliedinDSM-4(AmericanPsychiatricAssociation,1996),thatis, atleasthalfofthecriteriaindicatethatthesubject’svideogame playingas problematic.In addition,theuseof short,fastscales hasprovennecessarywithadolescents(Maïano,Ninot,Morin,&
Bilard,2007)topreventthemfromgivinguporrespondingran- domly(Coste,Guillemin,Pouchot,&Fermanian,1997).Adolescence isknowntobetheperiodofimmediacy,action,andimpulsiveness.
Moreover,attentionalabilitiesarestillunderdevelopment,which causesadolescents tobeeasily distracted (Lacknera, Santessoa, Dywana,&Segalowitza,2013;Monketal.,2003;Steinberg,Dahl, Keating,Masten,&Pine,2006).Thus,theuseofashortscaleseems appropriate.Using shortscalescouldnotonlyreducethesocial desirabilitybiastowhichadolescentsareparticularlyprone,but alsohelppinpointtheproblematicuseofvideogamesbyreduc- ingtheriskofdrowningthisproblemintheadolescentprocess.
Shortforms arealsonecessaryinthecurrentclinicalandscien- tificcontext,where“quick,preliminaryevaluations”areneeded inhealthcarecenters,andmultivariatestudiesinvolvingabattery of questionnairesmust beconducted.Furthermore, inthe field ofaddiction, both researchersand cliniciansprefershortscales (Babor, Biddle-Higgins, Saunders, & Monteiro, 2001; Décamps, Battaglia, & Idier,2010; Etter, Le Houezecn, & Perneger, 2003;
Ewing,1984;Heatherton,Kozlowski,Freckern,&Fagerstrom,1991;
O’Loughlin,Tarasuk,Difranzan,&Paradis,2002).Moreover,there areveryfew validatedscalesin Frenchforassessingtheuseof videogamesamongadolescents(Romo,Bioulac,Kern,&Michel, 2012).Tothebestofourknowledge,thereisonlyoneexploratory studyoftheFrenchversionofProblemVideogamePlaying(Tejeiro
Salguero&BersabéMoran,2002),whichwasconductedwithADHD children(Bioulac,Arfi,Michel,&Bouvard,2010).Itisimportantfor Frenchresearchersandclinicianstohaveareliableassessmenttool foridentifyingandmeasuringtheproblematicuseofvideogames amongadolescents.Alloftheseconsiderationspromptedustouse the7-itemGAS.
2. Thepresentresearch
Theaimofthepresentresearchwastoexplorethepsychometric propertiesofaFrenchtranslationofthe7-itemGASforadolescents (Lemmens et al., 2008, 2009). We used a translation/back- translationprocedure.Tworesearchersdidthetranslation.They wereclinicalpsychologists,sotheyhadthescientificknowledge andclinicalskillslikelytobeusefulinproducingagoodtransla- tion.Eachresearchertranslatedthescaleindependently.Thenthe twoFrenchversionswereback-translatedintotheoriginallan- guagebyoutsideindividuals whowereunawareoftheoriginal version. We compared theseversions in order to reacha con- sensusonthefinalversion(theversionwesetouttovalidatein thepresentarticle).Thisprocessofscalevalidationisnecessary formakingcomparisonsbetweenstudiesconductedindifferent languages,fordevelopingscientificresearchamongFrenchspeak- ers,and,withaclinicalaim,forhavingareliabletooltocapture problematicuse(Vallerand,1989).AvalidatedFrenchversionof theGASspecifictoadolescentswouldthereforehavescientificas wellasclinicalutility,and wouldallowfor moreepidemiologi- calandempiricalresearchontheuseofvideo gameplayingby adolescents.
WeconductedtwostudieswithtwodifferentsamplesofFrench adolescents.Thefactorstructureandinternalconsistencyofthe scalewereevaluated.Concurrentvaliditywasassessedbylook- ingforsignificantlinkswithseveralfactors.Thefirstwasthetime spentplaying video games,consideredas aninitialbut insuffi- cientindicatorofproblematicplaying(Parkeretal.,2008,2013;
Schmit,Chauchard,Chabrol,&Sejourne,2011;TejeiroSalguero&
BersabéMoran,2002).Indeed,eventhoughthetimespentplay- ingisnotacriterionofaddiction,problematicgamersspendmore time on video games than non-problematicgamers do (Parker etal.,2008,2013;Schmitetal.,2011).Inaddition,thetimespent onvideo gamesincreaseswithinvolvement, which canleadto addiction(VanRooij et al.,2010).Thesecond andthird factors assessedweredepressionandanxiety,bothofwhichareassoci- atedwithproblematicuse(Bonnaire&Varescon,2009;Mehroof
&Griffiths,2010;Parketal.,2013;Schmitetal.,2011;Yen,Ko, Yen,Wu, &Yang, 2007).Cyberaddictionand problematic video game playingare accompaniedby depressive affectand a high level of anxiety(Bonnaire & Varescon, 2009; Yenet al., 2007).
Comparedtonon-addictedindividuals,personsaddictedtovideo games have a higher level of depression (Schmit et al., 2011) andanxiety(Mehroof&Griffiths,2010).Wethereforeexpected to find that the GAS score was positively related to the time spentonvideo games, depression, and anxiety.Theserelation- shipswouldthenbeconsideredevidenceofconcurrentvalidity.
We also analyzed thegender distribution,even thoughgender differences in video game use/abuse are underdebate. Despite currentstatisticsindicatingthatasmanygirlsasboysplayvideo games,studieshaveshownthatthemajorityof“non-players”are girls(Achabetal.,2011).Girlsaregenerallycasualplayers(TNS- Sofres,2010),whileregularandexcessiveplayersaremostlyboys (Fortin et al., 2005; Griffiths & Hunt, 1995; French Videogame Agency,2010).Finally,weconductedathirdstudythatcombined thesamplesfromstudies1 and2, inorder toconfirmthatthe factor structure wasthe samein each subgroup(i.e., boysand girls).
3. Study1:factoranalysisandreliability
Theaimofthefirststudywastoexaminethefactorstructure andinternalconsistencyofthe7-itemGAS.
3.1. Method 3.1.1. Participants
Thesampleconsistedof159Frenchadolescents(52%boys).The participants’meanagewas14years(range10–18,M=14.01,SD=2, Md=14.00).
3.1.2. Materialsandprocedure
TheFrenchtranslationofthe7-itemGASwasused.Allitems werescoredona5-pointLikertscalerangingfrom1(“never”)to 5(“veryoften”).Four“validated”items—aresponsegreaterthan orequalto3(“sometimes”)validatedtheitem—correspondedto problematicuseofvideogames(Lemmensetal.,2008,2009).
Following a briefing, a consent form was given to parents.
The adolescentswere alsoasked togive theirwritten consent.
Theexperiment tookplace ina classroomduring schoolhours.
Aresearcherwaspresentduringtestingtoanswerquestionsand ensureconfidentiality.
DataanalysiswasperformedusingtheStatisticalPackageforthe SocialSciences(SPSS16.0,SPSSInc.,Chicago)andtheAnalysisof MomentStructures(AMOS6,AMOSDevelopmentCorporation).An exploratoryfactoranalysis(EFA)wasperformedusingtheVarimax rotationmethod,inordertodeterminethedimensionalityofthe questionnaire.Confirmatoryfactoranalyses(CFA)werealsocom- putedusingthemaximumlikelihoodestimator.Wecalculatedthe Chi2value(2),whichshouldbenonsignificantinordertoconsider thefitasacceptable(Hu&Bentler,1999).Thefollowingfitindexes wereusedtoevaluatethemodel’sgoodnessoffit.TheCompar- ativeFitIndex(CFI)andtheTucker-LewisIndex(TLI)indicatea verygoodfitiftheyarecloseto1,andanacceptablefitiftheyare greaterthan0.90.TheRootMeanSquareErrorofApproximation (RMSEA)witha90%confidenceinterval(90%CI)andtheStandard- izedRootMeanSquareResidual(SRMR)indicateanacceptablefit iflessthan0.08andagoodfitiflessthan0.05(Hu&Bentler,1999;
Schermelleh-Engel,2003).Cronbach’salphawasusedtomeasure internalconsistencyasanindicatorofscalereliability;itshouldbe greaterthan0.70.
3.2. Results
TheEFArevealedafactorloadingforeveryitemthatwasgreater than0.50(Table1),andasingle-factorstructurethataccountedfor 46.50%ofthevariance.Theeigenvalueofthefirstfactorwasabove 1,whiletheotherswerebelow1(Table2).Sothescalewascon- sideredone-dimensional(Carmines&Zeller,1979).IntheCFA,we computedaone-factormodelinwhichthesevenitemsonthescale werehypothesizedtobeauniquelatentfactorrepresentingvideo gameaddiction(Table3).The2statisticoftheone-factormodel wasnonsignificant,2(14)=21.66,p=0.09,whichcorrespondsto anacceptablefit.Thecombinationofthefourfitindexesindicated anacceptablefit(CFI=0.97,TLI=0.96,RMSEA=0.06witha90%CI [0.0,0.11],and SRMR=0.04).Cronbach’salphawas0.80, which indicatesgoodinternalconsistencyofthescale.
Based on the GAS scores of the 159 adolescents, 20 were problematic videogame players(75%boys) and139werenon- problematic videogame players(48%boys).In addition,18%of theboysand7%ofthegirlswereproblematicgamers(2=4.90, p<.05). There was no significant correlation between age and problematic videogame playing, nor a significant difference
Howoftenduringthelastsixmonth... Mean(SD) Factorloading
Study1 Study2 Original Study1 Study2 Original
Item1:didyoufeeladdictedtoavideogame?
(T’es-tusentiaddictéàunjeuvidéo?)
1.88(1.05) 2.48(1.24) 1.59(0.95) .79 .78 .70
Item2:didyouspendmoreandmoretimeonvideogames?
(As-tuaugmentétontempspasséàjouerauxjeuxvidéo?)
1.55(0.86) 1.84(1.04) 1.64(0.95) .51 .55 .79
Item3:didyouplayvideogamestoescapereality?
(As-tujouéauxjeuxvidéopourfuir/oublierlaréalité?)
1.47(0.94) 1.90(1.20) 1.52(0.86) .55 .51 .76
Item4:othershaveunsuccessfullytriedtoreduceyourplayingtime?
(D’autresont-ilsessayésanssuccèsderéduiretontempsdejeu?)
1.75(1.07) 2.27(1.28) 1.66(1.07) .65 .61 .61
Item5:didyoufeelbadwhenunabletoplay?
(T’es-tusentimalquandtunepouvaispasjouer?)
1.45(0.83) 1.87(1.10) 1.32(0.72) .80 .79 .85
Item6:didyouhavehardargumentswithothersonyourtimespent ongames?
(As-tueudesconflitsaveclesautresausujetdetontempspasséàjouer auxjeuxvidéo?)
1.81(1.03) 2.24(1.28) 1.29(0.65) .64 .70 .74
Item7:yourplayingtimecausedsleepdeprivation?
(Tontempsdejeua-t-ilcausédesmanquesdesommeil?)
1.74(1.02) 2.19(1.18) 1.50(0.91) .78 .72 .67
Nomissingdata.
Table2 Eigenvalues.
Eigenvalues
Study1 Study2
Factor1 3.3 3.2
Factor2 0.9 0.9
Factor3 0.8 0.7
Factor4 0.7 0.6
Factor5 0.5 0.5
Factor6 0.4 0.5
Factor7 0.3 0.4
Nomissingdata.
between the average ages of problematic gamers (M=13.49, SD=2.5)andnon-problematicgamers(M=14.18,SD=2)(t=−1.38, p>.05). We divided the sample into two age groups at the median(Md=14,so[10–13]and[14–18]);nosignificantdifference betweenthetwogroupswasfoundconcerningtheproblematicuse ofvideogames(t=1.47,p>.05).
Theresultsindicatedthattheone-factormodelofthe7-item GAShadgoodpsychometricpropertiesandfitthedatawell.These resultsaresimilartothoseobtainedbyLemmensetal.(2009)in theiroriginalstudy.However,thenumberofparticipantswasrel- ativelysmall,barelyabovethegenerallyacceptedvalueofatleast
10subjectsperitemneededtovalidateascale(Tabachnik&Fidell, 2007).Oursamplesizemaythereforelimitthegeneralityofour resultsregardingtheprevalenceofaddiction.
4. Study2:factoranalysis,reliability,andconcurrent validity
Theaimofthesecondstudywastoconfirmthefactorstruc- tureandinternalconsistencyofthe7-itemGAS,andtoexamineits concurrentvaliditywithalargersampleofadolescents.
4.1. Method 4.1.1. Participants
Thesampleconsistedof306Frenchadolescents(65%boys).The participants’meanagewas14years9months(range10–18years, M=14.75,SD=2.4,Md=14.40).
4.1.2. Materialsandprocedure
TheFrenchtranslationofthe7-itemGASwasused.TheFrench version(Moor&Mack,1982)oftheChildDepressionInventoryor CDI(Kovacs&Beck,1977)wasusedtoassessdepression(␣=0.86).
TheCDI contains 27items, each consistingof three statements.
For each item, the adolescent is asked to selectthe statement
Table3
Confirmatoryfactoranalysis:fitindexes.
Model 2 CFI TLI RMSEA SRMR
Study1 21.66
p=0.086
.97 .96 .06(90%CI:.0;.11) .04
Study2 41.88
p<.05
.95 .92 .08(90%CI:.05;.11) .05
Study3
Totalsample 32.74
p<.05
.98 .97 .05(90%CI:.03;.08) .04
Boys 32.30
p<.01
.96 .94 .06(90%CI:.04;.09) .04
Girls 17.13
p=.25
.99 .98 .04(90%CI:.0;.08) .04
Under14years 23.02
p=.06
.98 .97 .06(90%CI:.0;.09) .04
14orolder 24.57
p<.01
.98 .96 .06(90%CI:.01;.09) .04
Original 69.90
p<.01
.97 / .05(90%CI:.03;.06) /
Nomissingdata.CFI:ComparativeFitIndex;TLI:Tucker-LewisIndex;RMSEA:StandardizedRootMeanSquareResidual;SRMR:StandardizedRootMeanSquareResidual.
thatbestdescribeshis/herfeelings.TheFrenchversion(Turgeon&
Chartrand,2003)oftheRevisedChildren’sManifestAnxietyScale orRCMAS(Reynolds&Richmond,1979)wasusedtoassessanx- iety.The RCMASconsistsof37yes/noitems thatrate thelevel ofanxiety(totalanxietyscore),andthenatureoftheanxietyon threedimensions:physiologicalanxiety,worry,andsocialanxiety (␣=0.78,0.57,0.82,and0.70,respectively).Anotherdimensionof thisscalecorrespondstodefensiveness.Itassessesthetendencyto denycommonnegativebehaviors.Highscoresonthisdimension reflectidealbehavior(whichisnotcharacteristicofanyone),and maybeindicativeofsocialdesirability(desirabilityscale,␣=0.73).
Theparticipantswereaskedtoassessthetimespentdailyonvideo gamesduringweekdays,weekends,andholidays.Theywerealso askedabouttheirweeklyfrequency ofvideogameplaying(less thanonceperweek,1–3timesperweek,morethanthreetimesa week,andeveryday).
Participants were recruited through advertising in their schools and on social network sites.An information leaflet for adolescents and their parents containing the link to the pro- tocol wascirculated. Measureswere performedwithan online questionnaire containing a consent form (Google documents:
https://www.docs.google.com).
DataanalysiswasperformedusingSPSS16.0(SPSSInc.,Chicago) andAMOS6(AMOSDevelopmentCorporation).Exploratoryand confirmatoryfactoranalyseswerecomputed(usingVarimaxrota- tionmethod for theEFA). For theCFA,we used themaximum likelihoodestimatorand computedfivefitindexes (2,CFI,TLI, RMSEAwitha90%CI,andSRMR).Internalconsistency(␣)wasused toassess reliability. Correlation analysis(Bravais-Pearson’s cor- relationcoefficientr)wasperformedtodeterminateconcurrent validity.WelookedathowtheGASscorewasrelatedtothetime spentonvideogames,depression,anxiety,andgender(boyswere labeled+1andgirls−1).AstrongcorrelationbetweentheGASand thesevariableswasconsideredasevidenceofitsconcurrentvalid- ity.Wealsoanalyzedthedistributionofsubjectsbygender(2)to checkforconsistencywiththeliterature.
4.2. Resultsanddiscussion
TheEFArevealedafactorloadinggreaterthan0.50oneveryitem (Table1)andasingle-factorstructurethataccountedfor44.90%of thevariance.Theeigenvalueofthefirstfactorwasabove1,while theotherswerebelow1(Table2).Sothescalewasconsideredone- dimensional(Carmines&Zeller,1979).IntheCFA,wecomputeda one-factormodel(Table3).TheChi2 valuewassignificant.How- ever,itisknownthat2increaseswithsamplesizeandthatitis unusualtoobtainanonsignificant2whenperformingCFAonself- reportquestionnaires(Byrne,2010).Moreover,thecombinationof thefourindexesindicatedanacceptablefit(CFI=0.95,TLI=0.92, RMSEA=0.08witha 90%CI[0.05,0.11],andSRMR=0.05).Cron- bach’salphawas0.79,whichconfirmsthegoodinternalreliability ofthescale.
Based on the GAS scores of the 306 adolescents, 86 were problematic video game players (82.50% boys) and 220 were non-problematicvideogame players(58.50% boys).Inaddition, 35.50%oftheboysand15%ofthegirlswereproblematicgamers (2=15.63,p<.05).Asin Study1,there wasnosignificantcor- relationbetween ageand problematic video game playing and nosignificantdifferencebetweentheaverageageofproblematic gamers(M=14.94,SD=2.3)andnon-problematicones(M=14.67, SD=2.4)(t=0.90,p>.05).Nosignificantdifferencebetweenthetwo agegroupsintheproblematicuseofvideogameswasfound(under 14and14orover;t=0.58,p>.05).
Duringweekdays,adolescentsclassifiedasproblematicgamers didnot play more than the others (M=2.6hours,SD=2.1, and M=2.2hours, SD=2, respectively, p>.05). However, 53.40% of
Table4
Concurrentvalidity:correlationanalysis.
GAS Timespentdailyonvideogamesduring
Weekdays .22**
Weekends .40**
Holidays .28**
Depression .31**
Anxiety
Total .15*
Physiological .07
Worry .12
Social-anxiety .20**
Gender(boy=+1;girl=−1) .30**
Nomissingdata.*p<.05;**p<.01.GAS:GameAddictionScale.
the problematic gamers played every day vs. 21.70% for non- problematic ones, and 19.80% played less than once a week vs.43.80% fornon-problematicgamers(2=33.49,p<.05).Dur- ing weekends and holidays, problematic gamers played more (M=5.4, SD=3.1, and M=5.9, SD=3.3, respectively) than did non-problematic ones (M=3.8, SD=3.1, and M=4.3, SD=3.5, respectively)(t=3.43,p<.05,andt=3.18,p<.05).
Correlationanalyses(Table4)showedthattheGASscorewas significantlyandpositivelycorrelatedwiththetimespentonvideo gamesdaily,onweekdays,onweekends,andonholidays,andalso withdepression,anxiety(especiallysocialanxiety),andthefactof beingaboy.
Thissecondstudywasconductedtoconfirmtheresultsofthe firstwithalargersample,andtoassesstheconcurrentvalidityof the7-itemGAS.Thefactoranalysisindicatedaone-factormodel withgoodpsychometricpropertiesthatfitthedatawell.Internal reliabilitywasgood.Theseelementsconfirmtheconstructvalidity ofthisscaleandareconsistentwiththoseobtainedbyLemmens etal.(2009)intheoriginalstudy.
Furthermore,in line withtheliterature (Parker et al., 2008, 2013; Schmitetal., 2011), there wasa significantpositive cor- relationbetweentheGASscoreandtimespentonvideogames, andadolescentsclassifiedasproblematicgamersplayedmorefre- quentlyandlongerthandidnon-problematicgamers.Ourresults confirmedthatproblematicuseofvideogamesismoreprevalent amongboys.Thegeneralpopulation,aswellastheplayersthem- selves,considervideogamesasamaleactivity(Fox&Tang,2014).
Theyareplayedmoreoftenbymaleadolescents(Bioulac&Michel, 2012)andthemajorityofregularandproblematicplayersareboys (FrenchVideogameAgency,2010;Fortinetal.,2005;Griffiths&
Hunt,1995).Inaddition,wefoundsignificantpositivecorrelations betweenthe GAS score and depression, anxiety,and especially social anxiety.These results are consistent with the literature, insofarasdepressionandanxietyareconsideredcomorbiditiesof cyberaddiction(Bonnaire&Varescon,2009)andInternetaddiction (Yenetal.,2007).Inthecaseofonlinevideogameaddiction,ado- lescentsandyoungadultshavebeenshowntohaveadepressive symptomatology(Schmitetal.,2011).Finally,asignificantrela- tionshipbetweenanxiety(traitandstate)andonlinevideogame addictionwasfound,suggestingthatanxietypromotesexcessive onlineplaying(Mehroof&Griffiths,2010).Thus,theconcurrent validityofthisFrenchversionofthe7-itemGASseemssatisfactory.
5. Study3:multigroupfactoranalysis
Theaimofthethirdstudywastoconfirmtheinvariantfactorial structureofthe7-itemGASineachoffouradolescentsubgroups:
boys,girls,under14yearsofage,and14orolder.Wetestedthe equalityofthefactorloadingsforeachgroup,inordertodetermine whetherthesamemodelwasapplicableacrossgroups.
2 df CFI RMSEA Base CMIN -CFI -RMSEA Boys/girls
Modela:unconstrained-Configuralinvariance 34.49 28 0.949 0.02 – – – –
Modelb:measurementweights-Metricinvariance 46.44 34 0.931 0.03 ma 11.96 0.018 0.01
Modelc:measurementintercepts-Stronginvariance 97.27 41 0.627 0.06 mb 50.83* 0.322 0.03
Modelc2:partialstronginvariance(i1,i4,i6&i7free) 48.78 36 0.915 0.03 mb 2.34 0.016 0.00
Modeld:structuralmeans(i1,i4,i6&i7free) 51.59 37 0.903 0.03 mc2 2.81 0.012 0.00
Modele:structuralcovariance 52.85 38 0.902 0.03 md 1.26 0.001 0.00
Modelf:measurementresiduals-Partialstrictinvariance(e1,e4,e6&e7free) 64.75 41 0.843 0.04 me 11.90* 0.059 0.01 Modelf2:partialstrictinvariance(e1,e4,e5,e6&e7free) 53.40 40 0.911 0.03 me 0.55 0.009 0.00 Under14years/14yearsorolder
Modela:unconstrainedConfiguralinvariance 47.57 28 0.978 0.03 – – – –
Modelb:measurementweightsmetricinvariance 51.35 34 0.980 0.03 ma 3.78 0.002 0.00
Modelc:measurementintercepts-Stronginvariance 63.38 40 0.973 0.03 mb 12.07 0.007 0.00
Modeld:structuralmeans 63.43 41 0.974 0.03 mc 0.05 0.001 0.00
Modele:structuralcovariance 64.69 42 0.974 0.03 md 1.26 0.000 0.00
Modelf:measurementresiduals-Strictinvariance 73.23 49 0.972 0.03 me 8.54 0.002 0.00
Nomissingdata.*p<.05.CFI:ComparativeFitIndex;RMSEA:StandardizedRootMeanSquareResidual.
5.1. Method
Wecombinedthesamplesfromstudies1and2(n=465;60%
boysand40%girls;47%underage14,and53%14orolder).First,we performedaconfirmatoryfactoranalysis(CFA)forthetotalsam- pleandforeachsubgroup.Beforetestingmeasurementinvariance acrossgroups,thepropertiesofthemodelwereassessedusingthe wholesample.Wecalculatedfivefitindexes:2,CFI,TLI,RMSEA, andSRMR.Ifthemodelappearedtofitthedatareasonablewellfor theindividualsubsamples,assessmentofinvariancebetweenthe groupscontinuedbysequentiallytestingaseriesofprogressively restrictiveandnestedmodelsinthefollowingorder:
•modela:unconstrained–configuralinvariance;
•modelb:measurementweights(equalfactorloadings)–metric invariance;
•model c: measurement intercepts (equal indicator inter- cepts)–stronginvariance;
•modeld:structuralmeans(equallatentmeans);
•modele:structuralcovariance(equalfactorco-variances);
•modelf:measurementresiduals(equalfactorvariances)–strict invariance.
Our rationale for the model testing sequence was that the modelsa,bandcspecificallyassessconfigural,metricandscalar measurementinvariancerespectively.Themodelsd,eandfcom- pare subgroup distributional properties of the constructs. We calculatedtheChi2 and theCFIandRMSEA differencestatistics measuringthedifferencebetween theoriginal andconstrained models.Anon-significantChi2difference(CMIN,p>.05)indicates thatthe model exhibitsmeasurement invarianceacross groups (Byrne, 2010).Adelta-CFIvalueless thanorequalto0.01indi- catesthatthenullhypothesisofinvarianceshouldnotberejected (Cheung&Rensvold,2002);avaluebetween0.01and0.02means thatdifferencesmayexist;avalueabove0.02indicatesthenon- invarianceofthemodel(Vandenberg&Lance,2000).Averysmall delta-RMSEArepresentssubstantivelyinsignificantvariations in themodel’sfit(Marsh,Ellis,Parada,Richards,&Heubeck,2005).
DataanalysiswasperformedusingAMOS6software(AMOSDevel- opmentCorporation).
5.2. Resultsanddiscussion
CFAwasperformedforthewholesampleandforeachsubgroup.
Wecomputedaone-factormodel(Table3).Forthewholesample, forboys,andforadolescentsunder14yearsofage,theChi2value
wassignificant.However,itisknownthat2increaseswithsam- plesize,andthatitisunusualtoobtainanonsignificant2when performingCFAonself-reportquestionnaires(Byrne,2010).The combinationofthefourindexesindicatedagoodfitforthetotal sampleandforeachsubgroup(Table3).
MultigroupCFAwasperformedonthegenderandagegroups (Table5).
Genderinvariance:Thetwofirstmodelsfitsuggestedaccept- able evidences for configural and metric invariances (Model a: 2(28)=34.49, p>.05; CFI=0.95, RMSEA=0.02; Model b:
CMIN=11.96, p>.05; -CFI<0.02, -RMSEA=0.01). The third model (Modelc: Measurement intercepts) testing strongfacto- rial invariancewas rejected(CMIN=50.83,p<.05; -CFI>0.02, -RMSEA=0.03).Modificationindices suggestedthatthecross- groupequalityconstraintontheintercept foritems1,4,6 and 7contributedmoststronglytothelackoffit.Thefourthmodel freelyestimatedtheseparameters inboth groupsand provided evidenceof partialstrongfactorial invariance(Gregorich, 2006) (model c2: CMIN=2.34, p>.05; -CFI<0.02, -RMSEA=0.00).
Thefifthandsixthmodelsfitsuggestedacceptableevidencesfor structuralmeansandstructuralcovarianceinvariances(modeld:
CMIN=2.81,p>.05;-CFI<0.02, -RMSEA=0.00;andmodele:
CMIN=1.26, p>.05;-CFI<0.01, -RMSEA=0.00).The seventh modeltestedpartialstrictfactorialinvariancebyimposingaddi- tionalcross-groupequalityconstraintsonallcorrespondingitem residualvariancesexceptthoseforitems1,4,6and7.Thismodel wasrejected(CMIN=11.90,p<.05;-CFI>0.02,-RMSEA=0.01).
Themodificationindicessuggestedfreelyestimatingtheresidual varianceforitem5,resultinginawell-fittingpartialstrictfactorial invariancemodel(Gregorich,2006)(modelf2:CMIN=0.55p>.05;
-CFI<0.01,-RMSEA=0.00).Theseresultsallowustoconsider thepartial factorial invarianceacross gender,which implies to avoidorrestrictgroupcomparisontothoseitemswithappropriate invariantparameters(Gregorich,2006).
Ageinvariance(under14vs. 14orolder):thesixmodelsfit suggestedacceptableevidencesforconfigural,metric,strong,strict andstructuralinvariances(Table5:modela:2(28)=47.57,p>.05;
CFI=0.98,RMSEA=0.03;modelb:CMIN=3.78,p>.05;-CFI<0.01, -RMSEA=0.00; model c: CMIN=12.07, p>.05; -CFI<0.01, -RMSEA=0.00; model d: CMIN=0.05, p>.05; -CFI<0.01, -RMSEA=0.00; model e: CMIN=1.26, p>.05; -CFI<0.01, -RMSEA=0.00; model f:CMIN=8.54, p>.05; -CFI<0.01, - RMSEA=0.00). These results allow us to consider the factorial invarianceacrossagegroups.
Thus,thehypothesisoftheinconsistencyofthemodelbetween boysandgirls,ontheonehand,andbetweenadolescentsunder
14and14orolder,ontheother,canberejected.Study’s3results confirmthatthefactorstructureofthescaledidnotvaryacrosssub- groups(boysvs.girls,under14vs.14orolder),therebyconfirming thevalidityoftheresultsobtainedinstudies1and2.
6. Generaldiscussion
Over the past decade, excessive/problematic use of video games has received much empirical and theoretical attention.
Thereisincreasinginterestinthisissue,particularlyforadoles- cents.However,muchmoreresearchisneededtobetterdetect andunderstandthisproblem,andtoallowforthedevelopment oftargetedtreatmentprograms(Collins,Freeman,&Chamarro- Premuzic,2012).TheGASwasintroducedasaself-reportmeasure of the problematic use of video games (Lemmens et al., 2008, 2009). The main aim of the current research was to examine the psychometric properties of the 7-item GAS in two French samples.
Duetotheabsenceofaconsensusontheconceptofaddiction tovideogames(Wood,2008),andaccordingtorecentstudies,the prevalenceofproblematicusevariesbetween3%and12%(Bonnaire
&Varescon,2009;Gentile,2009).Inthepresentstudieswherewe appliedthepolytheticformat,12.60%(study1)and28.10%(study 2)oftheadolescentswereclassifiedasproblematicvideogame players.Withamonotheticformat(validationofallcriteria)only 0.6and1%ofadolescentswereclassifiedasproblematicvideogame players,whichcouldbeanunderestimation(VanRooijetal.,2010).
However,wenotedtwoitemsthathadverylowfactorloadings inboth samples:Item2(“Howoftenduringthelast sixmonth didyouspend moreandmore timeonvideo games?”),a mea- sureof tolerance(.51 and .55,in studies1 and 2,respectively) andItem3(“Howoftenduringthelast sixmonthdidyou play videogamestoescapereality?”),ameasureofmoodchanges(.55 and.51,respectively).Itshouldbenotedthatintheoriginalstudy (Lemmensetal.,2008,2009)thesampleswerecomposedonlyof adolescentswhohadplayedvideogameswithinthelastmonth.In ourstudies,thesampleswerenotselectiveforvideogameplay- ing.Thiscouldexplaindifferencesinthefactorloadings.Invideo gameplaying,thesetwoitemscorrespondto“peripheralcriteria”
foraddiction(Wood,2008).Assuch,theyarerelatedtoahighlevel ofinvolvementandnotnecessarilytotheproblematicuseofvideo games.Duetotheinteractiveandimmersionqualitiesofanyvideo game,itisnotnecessarytospendalotoftimeplayingtoreachthe desiredstate;simplyplayingmightbeenough.Sointhiscontext, onecannotassumethatplayinglongerisaquestionoftolerance.
Wecanassume,however,thattheseitemscorrespondtoahigh levelofinvolvement,butarenotenoughtoconsiderthebehavior problematic.
Finally,theseconsiderationsmayraisethequestionofthecutoff pointstoapplyonthe7-itemGAS.Thepolytheticformatapplied byDSM-4couldbesupplementedbyarecommendation,suchas havingtovalidateatleasttwoorthreeitemsreferringtothecore criteriaofaddiction,outoftherequiredfour.
Toconclude,this Frenchversion of the7-itemGAS exhibits acceptablepsychometricpropertiesthatconfirmitstheoreticaland concurrentvalidity.Althoughagreatmanystudiesareneededto assesstheclinicalvalidityofanyscale,theFrenchversionofthe 7-itemGASseemstobeareliableassessmenttoolforidentifying andcapturingtheproblematicuseofvideogamesandshouldbe usefulinfutureresearch.
Disclosureofinterest
Theauthorsdeclarethattheyhavenoconflictsofinterestcon- cerningthisarticle.
References
Achab,S.,Nicolier,M.,Mauny,F.,Monnin,J.,Trojak,B.,Vandel,P.,etal.(2011).
Massivelymultiplayeronlinerole-playinggames:comparingcharacteristicsof addictvs.non-addictonlinerecruitedgamersinaFrenchadultpopulation.BMC Psychiatry,11(144),1–12.http://dx.doi.org/10.1186/1471-244X-11-144 AmericanPsychiatricAssociation.(1996).DSMIV.Critèresdiagnostiques[DSMIV.
diagnosticcriteria](J.D.Guelfi,etal.,Trad.).Paris:Masson(Originalworkpub- lishedin1994)
Babor,T.F.,Biddle-Higgins,J.C.,Saunders,J.B.,&Monteiro,M.G.(2001).AUDIT:The AlcoholUseDisordersIdentificationTest:guidelinesforuseinprimaryhealthcare.
Geneva,Switzerland:WorldHealthOrganization.
Bioulac,S.,Arfi,L.,Michel,G.,&Bouvard,M.P.(2010).Intérêtdel’utilisationduques- tionnairedesproblèmesassociésauxjeuxvidéodeTejeiro(ProblemVideogame Playing:PVP),ÉtudeexploratoirechezdesenfantspresentantunTDA/H[Inter- estoftheuseoftheProblemVideogamePlaying(PVP)questionnairefrom Tejeiro:exploratorystudyinADHDchildren].AnnalesMédicoPsychologiques, 168,632–635.
Bioulac,S.,&Michel,G.(2012).Addiction:définitionetpsychopathologie[Addic- tion:definitionandpsychopathology].InL.Romo,S.Bioulac,L.Kern,&G.Michel (Eds.),LadépendanceauxjeuxvidéoetàInternet[Dependancetovideogamesand toInternet](pp.15–30).Paris:Dunod.
Bonnaire,C.,&Varescon,I.(2009).Lacyberdépendance[Cyberdependance].In I. Varescon(Ed.),Lesaddictions comportementales.Aspects cliniqueset psy- chopathologiques[Behavioraladdictions.Clinicalandpsychopathologicalaspects]
(pp.107–132).Paris:Mardaga.
Brown,R.I.(1993).PlanningdeficienciesinaddictionsfromthePerspectiveofRever- salTheory.InJ.H.Kerr,S.Murgatroyd,&M.J.Apter(Eds.),AdvancesinReversal Theory(pp.205–223).Amsterdam:Swets&Zeitlinger.
Byrne,B.M.(2010).StructuralequationmodelingwithAMOS:basicconcepts,applica- tionsandprogramming(2nded.).NewYork:Taylor&FrancisGroup.
Carmines,E.G.,&Zeller,R.A.(1979).Reliabilityandvalidityassessment.London:
Sage.
Cheung,G.W.,&Rensvold,R.B.(2002).Evaluatinggoodness-of-fitindexesfor testing measurementinvariance.StructuralEquation Modeling, 9, 233–255, doi:10.1207/S15328007SEM0902 5.
Collins,E.,Freeman,J.,&Chamarro-Premuzic,T.(2012).Personalitytraitsasso- ciatedwithproblematic andnon-problematicmassivelymultiplayeronline roleplaying gameuse.PersonalityandIndividual Differences, 52, 133–138.
http://dx.doi.org/10.1016/j.paid.2011.09.015
Coste,J.,Guillemin,F.,Pouchot,J.,&Fermanian,J.(1997).Methodologicalapproaches toshorteningcompositemeasurementscales.JournalofClinicalEpidemiology, 50(3),247–252.
Décamps,G.,Battaglia,N.,&Idier,L.(2010).ÉlaborationduQuestionnairedeMesure del’IntensitédesConduitesAddictives[QMICA]:évaluationdesaddictions etco-addictionsavecetsanssubstances[DevelopmentoftheQuestionnaire forMeasuringIntensityofAddictiveBehaviors[QMICA]:assessmentofaddic- tionsandco-addictionswithandwithoutsubstance].PsychologieFranc¸aise,55, 279–294.http://dx.doi.org/10.1016/j.psfr.2010.06.001
Etter,J.F.,LeHouezec,J.,&Perneger,T.V.(2003).Aself-administeredquestion- nairetomeasuredependenceoncigarettes:thecigarettedependencescale.
Neuropsychopharmacology,28(2),359–370.
Ewing,J.A.(1984).Detectingalcoholism:theCAGEquestionnaire.JournalofAmeri- canMedicalAssociation,252(14),1905–1907.
Fortin,T.,Mora,P.,&Trémel,L.(2005).Lesjeuxvidéo:pratiques,contenusetenjeux sociaux[Videogames:practices,contentsandsocialissues].Paris:L’Harmattan.
Fox,J.,&Tang,W.Y.(2014).Sexisminonlinevideogames:theroleofconfor- mitytomasculinenormsandsocialdominanceorientation.ComputersinHuman Behavior,33,314–320.http://dx.doi.org/10.1016/j.chb.2013.07.014
FrenchVideogameAgency.(2010).Médiamétrie:observatoiredesjeuxvidéo[Medi- ametrie: video games’ observatory]. http://www.afjv.com/press1007/100708
observatoirejeuxvideojoueuses.php
Gentile,D.A.(2009).Pathologicalvideo-gameuseamongyouthages8–18.Psycho- logicalScience,20,594–602.
Gregorich,S.E.(2006).Doself-reportinstrumentsallowmeaningfulcomparisons acrossdiversepopulationgroups?Testingmeasurementinvarianceusingthe confirmatoryfactoranalysisframework.MedicalCare,44(11Suppl.3),S78–S94.
Griffiths,M.D.,&Davies,M.N.(2005).Videogameaddiction:doesitexist?InJ.
Goldstein,&J.Raessens(Eds.),Handbookofcomputergamestudies(pp.359–368).
Boston:MIT-Press.
Griffiths,M.D.,&Hunt,N.(1995).Computergamesplayinginadolescence:preva- lenceanddemographicindicators.JournalofCommunityandAppliedSocial Psychology,5,189–193.
Heatherton,T.F.,Kozlowski,L.T.,Frecker,R.C.,&Fagerstrom,K.O.(1991).TheFager- stromTestforNicotineDependence:arevisionoftheFagerstromTolerance Questionnaire.BritishJournalofAddiction,86,1119–1127.
Hu,L.,&Bentler,P.M.(1999).Cutoffcriteriaforfitindexesincovariancestruc- tureanalysis:conventionalcriteriaversusnewalternatives.StructuralEquation Modeling,6,1–55.
King,D.,Haagsma,M.,Delfabbro,P.,Gradisar,M.,&Griffiths,M.(2013).Toward a consensusdefinition ofpathological video-gaming: asystematic review ofpsychometricassessment tools.ClinicalPsychology Review,33, 331–342.
http://dx.doi.org/10.1016/j.cpr.2013.01.002
Kovacs,M.,&Beck,A.T.(1977).Anempirical-clinicalapproachtowardadefinition ofchildhooddepression.InJ.G.Schulterbrandt,&A.Raskin(Eds.),Depressionin
