Fear of Missing Out as a Predictor of Problematic Social Media Use and Phubbing Behavior among

18 Pages·2017·0.57 MB·English

International Journal of
Environmental Research
and Public Health
Article
Fear of Missing Out as a Predictor of Problematic
Social Media Use and Phubbing Behavior among
Flemish Adolescents
VittoriaFranchina1,*,MariekVandenAbeele2,*,AntoniusJ.vanRooij3,4 ,GianlucaLoCoco1
andLievenDeMarez3
1 DepartmentofPsychologyandEducationalSciences,UniversityofPalermo,90133Palermo,Italy;
[email protected]
2 TilburgSchoolofHumanitiesandDigitalSciences,TilburgUniversity,5037ABTilburg,TheNetherlands
3 imec-mict-UGent,DepartmentofCommunicationSciences,GhentUniversity,9000Ghent,Belgium;
[email protected](A.J.v.R.);[email protected](L.D.M.)
4 DepartmentofYouth&RiskyBehavior,TrimbosInstitute,3521VSUtrecht,TheNetherlands
* Correspondence:[email protected](V.F.);
[email protected](M.V.A.)
(cid:1)(cid:2)(cid:3)(cid:1)(cid:4)(cid:5)(cid:6)(cid:7)(cid:8)(cid:1)
(cid:1)(cid:2)(cid:3)(cid:4)(cid:5)(cid:6)(cid:7)
Received:6September2018;Accepted:24September2018;Published:22October2018
Abstract: Fear-of-missing-out(FOMO)referstofeelingsofanxietythatarisefromtherealizationthat
youmaybemissingoutonrewardingexperiencesthatothersarehaving. FOMOcanbeidentifiedas
anintra-personaltraitthatdrivespeopletostayuptodateofwhatotherpeoplearedoing,among
othersonsocialmediaplatforms. Drawingfromthefindingsofalarge-scalesurveystudyamong
2663 Flemish teenagers, this study explores the relationships between FOMO, social media use,
problematicsocialmediause(PSMU)andphubbingbehavior. Inlinewithourexpectations,FOMO
wasapositivepredictorofbothhowfrequentlyteenagersuseseveralsocialmediaplatformsandof
howmanyplatformstheyactivelyuse. FOMOwasastrongerpredictoroftheuseofsocialmedia
platformsthataremoreprivate(e.g.,Facebook,Snapchat)thanplatformsthataremorepublicin
nature(e.g.,Twitter,Youtube). FOMOpredictedphubbingbehaviorbothdirectlyandindirectlyvia
itsrelationshipwithPSMU.ThesefindingssupportextantresearchthatpointstowardsFOMOasa
factorexplainingteenagers’socialmediause.
Keywords: fear of missing out (FOMO); social media; problematic social media use (PSMU);
phubbing;teenagers;adolescents;addiction
1. Introduction
Behavioraladdictionresearchersarguethatthepsychologicalprocessesthatexplainproblematic
behaviorrequiregreaterattention[1–5]. Understandingunderlyingprocessesisparticularlyrelevant
whenexaminingproblematicformsof(digital)mediause. Digitaldevices,suchasmobilephones,
canbeusedandmisusedinavarietyofdifferentways. Itislikelythatthewayinwhichproblemuse
manifestsitselfdependsontheparticularunderlyingpsychologicalmechanism[6,7].
One psychological process that may underlie problematic digital media use is the
Fear-Of-Missing-Out (FOMO). FOMO refers to the “pervasive apprehension that others might be
havingrewardingexperiencesfromwhichoneisabsent”[8]. PersonswhohaveagreaterFOMOare
assumedtohaveagreaterdesiretostaycontinuallyup-to-dateofwhatothersaredoing,forexample
viatheuseofsocialmedia. AccordingtoPrzybylskietal.[8],FOMOoriginatesfrompsychological
deficits in people’s competence and relatedness needs [9]. One way of satisfying these needs,
Int.J.Environ.Res.PublicHealth2018,15,2319;doi:10.3390/ijerph15102319 www.mdpi.com/journal/ijerph
Int.J.Environ.Res.PublicHealth2018,15,2319 2of18
theauthorsclaim,isthroughtheuseofsocialmediaapplications,becausethedynamicnatureofsocial
mediaapplicationsprovidesuserswithaconsistentstreamofsocialandinformationalrewards[10].
The purpose of the current study is to contribute to the extant body of research on FOMO in
relationtosocialmediause. Thestudyhasfouraims. First,itinvestigateswhetherteenagerswith
higherlevelsofFOMOhavemoresocialmediaaccounts(i.e.,thebreadthofsocialmediause)and
whether they access these accounts more frequently (i.e., the depth of social media use [11]) than
teenagerswithlowerlevelsofFOMO.Second,assumingthatteenagerswithhigherlevelsofFOMO
aremostlymotivatedtocheckuponpeopleintheirpersonalsocialnetworks,weexaminewhether
FOMOisastrongerpredictoroftheuseofplatformsthatconnectteenagerstotheirofflinenetworks
(e.g.,Facebook,Snapchat)thanoftheuseofplatformsthatconnecttoalargelyunknownaudience
(e.g.,Youtube,Twitter). Third,thestudyexaminesifteenagerswithgreaterFOMOreporthigherlevels
ofproblematicsocialmediause(PSMU)and,four,aremorelikelytoreportoneparticularformof
problematicsocialmediause,whichistheuseofsocialmediaduringconversationswithco-present
others(cf. “phubbing”). Theseresearchaimsareaddressedwithdatafromalarge-scalecross-sectional
surveythatwasadministeredto2663Flemishadolescents.
2. TheoreticalFramework
People have always had a tendency to think about what others are thinking and doing [12].
Inthe1970and1980scholarsalreadyidentifiedthatsomepeopledevelopedanxietiesaroundmissing
out,contemplatingontherewardingexperiencesthatothersmightbehaving(e.g.,inthecontextof
romanticrelationships)[13]. FOMOisthusnotanentirelynewconcept.
FOMOcanbeunderstoodassuchananxietyaroundmissingoutonrewardingexperiencesthat
results from people’s desire for interpersonal attachments [12]. This desire, which is grounded in
people’sneedtobelong,isaninnateandfundamentalmotivationwhichhumanshave[14]. People
gratifythisneedbyseekingbelongingnesstosocialgroups. Socialgroupsnowadaysexistinboth
physicalandvirtualshapesandpeoplehaveaccesstotheirsocialgroupsinbothways,onlineand
offline.Socialmedia,whichcanbedefinedas“Internet-basedapplicationsthatbuildontheideological
andtechnologicalfoundationsofWeb2.0,andthatallowthecreationandexchangeofUserGenerated
Content”[15,16],offeraplacewhereuserscankeepintouchwiththeirsocialcircles. Socialnetwork
sites(SNS)suchasFacebookorInstagram,forexample,offerusersanonlineconnectiontopersonsin
theirpersonalnetworks,facilitatingthepracticeofkeepingintouch.
Nowadays the digital world is considered an extension of the Self [17,18]. In addition to
the personal mind and physical body, the Self can be thought to include people, places, physical
possessions,aswellasaffiliationgroupstowhichapersonfeelsattached[19]. Socialmediaplatforms
areapartofthis: theyarethedigitalportalstoaffiliationgroups. Incontemporarysocietywethus
managetheaffiliationnetworkbothofflineandonline;virtualgroupsareasrealandimportantas
thephysicalones. Notbeingabletoconnectwiththoseaffiliationgroupsonsocialmediamaycause
feelingsofbeingoutoftouchwith“real”life[17]. Afterall,losingormissingapersononeisattached
to,canbringfeelingsoflossandgrievingasmuchasifapartoftheSelfwasdamaged[19].
ThefearofbeingsociallyexcludedplaysaroleinexperiencingaFOMO[12]. Socialexclusion
produces a loss of belongingness, and therefore causes anxiety. Thus, when people cannot access
their social media accounts, they might feel anxiety because of a fear that they are being socially
excluded[12].
Socialexclusionalsoelicitsfeelingsofworthlessness[12]. Thesefeelingsleadpeopletotheactof
comparingthemselvestoothersonsocialmedia[20]withthepurposeofdecidingupontheirown
personalvalue[21]. Socialnetworksofferaplacewhereconsumers,particularlyyounggenerations,
cancontinuouslykeepupwithwhatpeersaredoingandcheckingonwhattheyaremissingouton
(e.g.,socialevents,lifeexperiences,lifeopportunities,andsoonandsoforth). FOMOcanthusdrive
socialmediause,ascheckinguponotherpeoplemayleadtoatemporaryreliefofone’sanxiety.
Int.J.Environ.Res.PublicHealth2018,15,2319 3of18
2.1. FOMOandtheUseofDifferentSocialMediaPlatforms
Usersmayusedifferentmediatogratifydifferentneeds[22–24]. Thiscanexplaindifferencesin
thepopularityofcertainsocialmediaplatforms. InJanuary2015,theGlobalWebIndexsummary
showedthatthemostpopularsocialmediaplatformwasthesocialnetworksiteFacebook,immediately
followedbyYouTube,TwitterandInstagram. ThesameyearInstagram’spopularityoutperformed
Twitter. According to some, this is because pictures are more effective than words in achieving
self-presentationalobjectives,whicharecentralmotivationsforsocialmediause[25]. Giventhateach
socialmediaplatformischaracterizedbyitsownfeaturesandaffordances,itisrelevanttodifferentiate
betweensocialmediaplatformsinresearchonsocialmediause: Differentplatformsmayconnectusers
todifferentpersonsandnetworks,andgiveaccesstodifferentformsofinformationofwhichusers
maywishtostayup-to-date.
CurrentresearchfindingsrevealthatFOMOisapredictoroftheuseofSNSwithwhichusers
connecttopeopleintheirpersonalnetworks,suchasInstagram[25]andFacebook[26]. Instagram
use,forexample,isfoundtobemotivatedbythedesiretokeepintouchwithothers[25]andto“to
keepupwithorgainknowledgeaboutwhatothers(i.e.,friends,familyandstrangers)aredoing”[27].
FOMOhasalsobeenfoundtopredictFacebookuse[28,29]andInstagramuse[30,31]. Theabovestudy
findingsthusindicatethatFOMOpredictstheuseofatleastthesesocialnetworksites,butpotentially
alsotheuseofothersocialmediaplatforms.
Withrespecttosocialmediause,adifferencecanbemadebetweenthe”depth”andthe“breadth”
ofone’suse, wherethedepthofusereferstoaspectssuchasthefrequencyanddurationofsocial
media use, and the breadth of use refers to the variety of social media platforms that are actively
used. Forteensinparticular,notonlyfrequentuse,butalsotheuseofabroadvarietyofsocialmedia
platformsmayservethepurposeofrelievinganxietieswithregardtonotknowingwhatothersare
thinkinganddoing,asthedifferencesintherelationalaffordancesofdifferentplatforms[32]mean
thattheymaygiveaccesstoatleastpartiallydifferentnetworksandcontents. Hence,forthecurrent
studyweexpectthatnotonlythedepth,operationalizedasthefrequencyofsocialmediause,but
alsothebreadth,operationalizedasthenumberofactivesocialmediaplatformsteenagersuse,are
predictedbyFOMO:
Hypothesis1. TeenswhoexperiencegreaterFOMO,usesocialmediamorefrequently(Hypothesis1a;i.e.,
thedepthofsocialmediause),andusemoredifferentsocialmediaaccounts(Hypothesis1b;i.e.,thebreadthof
socialmediause).
2.2. FOMOandtheUseofMorePrivateversusMorePublicSocialMediaPlatforms
Asmentionedabove,theuseofdifferentsocialmediaplatformsmaygratifydifferentunderlying
needs. For example, a recent study shows that users significantly differ in the gratifications they
derivefromusingFacebook,Instagram,TwitterandSnapchat[33]. Oneaffordanceinwhichplatforms
maydifferisintheextenttowhichcontentisrestrictedtoa(sub-)setofcontacts, orfullypublic—
inotherwords,whethercontentissharedwithamostlyknownversusamostlyunknownaudience.
OnplatformssuchasFacebook,InstagramorSnapchat,people’sonlinesocialnetworkusuallyoverlaps
withtheirofflineaffiliationgroup(e.g.,Facebook/Snapchatcontactsneedtoknoweachother’snames
orphonenumberstoseeeachother’spostsandprofiles). PlatformssuchasTwitterorYoutube,on
theotherhand,usuallymakecontentaccessibletoawideraudienceofmainlyunknownindividuals,
andresembleabroadcastingplatformratherthanaplatforminwhichcontentisrestrictedtopeople
whohavebeenacceptedas“contacts”,“followers”or“friends”.
Giventhisdifferenceinthepublicaccessibilityofplatformcontent,itseemslogicaltoassumethat
SNSssuchasFacebookorSnapchataremoreaptatprovidingrelieffromFOMOthan,forexample,
videosharingplatformssuchasYoutubeormicrobloggingservicessuchasTwitterbecausetheformer
providegreaterrelieffromanxietiessurroundingwhatfriendsandfamilyaredoing.
Int.J.Environ.Res.PublicHealth2018,15,2319 4of18
Indeed, platformssuchasFacebookorInstagramaremorepersonalSNSthatenableteensto
limitcontentaccessibilitytothedesiredpublic(e.g.,friendsorfriends-of-friends). Asaresult,these
SNSmaybeespeciallyattractivevenuesforteenswithahighFOMObecauseitletsthemknowwhat
people in their primary affiliative groups are thinking and doing. We explore this assumption by
askingthefollowingresearchquestion:
ResearchQuestion. IsFOMOastrongerpredictoroftheuseofmoreprivatesocialmediaplatforms(that
connectmostlytoofflinenetworks)thanmorepubliclyaccessiblesocialmediaplatforms(thatconnectmostlyto
onlinenetworks)?
2.3. FOMOandProblematicSocialMediaUse(PSMU)
Whensocialmediauseisexcessive,itcanbecomeproblematic. Severalstudieshaveaddressed
problematicsocialmediause(PSMU)[34–36].Thereisanongoingdebateintheliteraturearoundthe
differencesbetweenproblematicsocialmediauseandapossiblesocialmediabehavioraladdiction[4,37].
Anin-depthdiscussionofthisdebategoesbeyondthescopeofthiswork.Inthecurrentstudy,however,
weusethetermproblematicsocialmediause,whichwedefineasanunhealthyexcessiveformof
socialmediause,characterizedbyalackofcontroloverthebehavior,andcontinuedbehaviordespite
adverselifeconsequences.Ourfocusisonrevealingthefactorsthatpredicttoproblematicsocialmedia
useinageneralpopulationofteenagers(i.e.,theaimisnottodiagnoseoridentifypathologicalcases).
Asmentionedbefore,oneoftheaimsofthisstudyistoexploreifteenagerswithagreaterFOMO
reportahigherlevelsofPSMU.Previousstudiessuggestthatthisisthecase[38–43],andsuggestthat
thosewhoexperienceFOMOmaytrytorelievetheiranxietybycheckinguponotherpeopleonsocial
media. Ironically,however,themorepeoplechecktheirsocialmediaaccounts,however,themorethey
mayfindeventstheyaremissingouton. Usingsocialmediatoreducetheanxietymayenduptobe
anothersourceofFOMO.Thereforethisviciouscirclemayreinforceitself,graduallyturningsocial
mediauseintoproblematicsocialmediause. Henceweexpect:
Hypothesis2. TeenswhoexperiencegreaterFOMO,reporthigherPSMU.
2.4. FOMOandPhubbing
AfinalstudypurposeistofocusonFOMOasapredictorofoneparticularformofproblematic
social media use, which is the use of social media during conversations with co-present others.
This practice is termed “phubbing” (derived from phone + snubbing), which refers to “the act of
snubbingsomeoneinasocialsettingbyconcentratingonone’sphoneinsteadoftalkingtotheperson
directly”[44,45]. Experimentalstudiesshowthatphubbingnegativelyimpactsrelationaloutcomes
suchasimpressionformation[46].
Recentfindingsshowthatpeopleprefertousesmartphoneswhengoingonline[47].Smartphones
allowsustobeincontactwithouraffiliationgroupsonsocialmedia,everywhereweare. Therefore,
weassumethatifpeopleexperienceanxiety,theymaytemporarytrytoreduceitbyaccessingtheir
socialmediaaccountsontheirsmartphones[48]. ItislikelythatthosehighinFOMO,whousesocial
mediatoaddresstheiranxiety,mayoverusesocialmediaontheirsmartphonesinsuchawaythatit
intersectswiththeirofflinesocialinteractions,leadingthemtophubtheirofflineinteractionpartners.
Hence,thelastaimofthisstudyistoexplorewhetherteenswithagreaterFOMOreporttoengage
inphubbingbehaviormorefrequently,andwhetherthelatterrelationshipismediatedbyPSMU:
Hypothesis3a. TeenswithagreaterFOMO,aremorelikelytousesocialmediaduringconversationswith
co-presentothers(cf. “phubbing”).
Hypothesis3b. PSMUmediatestheformerrelationship.
Int.J.Environ.Res.PublicHealth2018,15,2319 5of18
3. Method
3.1. SampleandProcedure
InFlanders,aconsortiumofnon-profitorganizationscollaboratesbi-annuallyonalarge-scale
surveyprojectthatexaminesthestateofaffairsofdigitalmediaownershipanduseofFlemishyouths.
Apart from a large set of recurring questions, every edition of the survey includes a number of
questionsontopicsthatareconsideredrelevantatthetime.
Thedatagatheredforthecurrentstudywerepartofthe2016researchproject[49]. Anomnibus
surveywasadministeredtothehighschoolpupilsof11geographicallydispersedhighschoolsin
Flanders,Belgium. Usingtheinformationmadeavailablebytheministryofeducation,quotasampling
wasusedtoselectschools,and—withintheschools—yearsandclassrooms. Thisprocedureresulted
inafinalsamplethatisrepresentativeforthepopulationintermsofgender, ageandschooltrack
(seeVanWaeg,D’Hanens,Dooms&Naesens[49]forfurtherdetails).
Within each school, a local collaborator (e.g., the school’s information and communications
technologycoordinator)organizedthesurveyadministrationprocess,accordingtoasetofinstructions
providedbytheprojectleaders. Thesurveywasadministeredonline,buttoavoidself-selectionbias,
thedatacollectiontookpartduringschoolhours,inthecomputerroomsoftheschools. Unfortunately,
noresponserateswereregistered. However, thelocalcollaboratorsstatedthatfewpupilsdidnot
receivepermissiontoparticipate. Intotal,theresponsesof3291pupilsweregathered. Theproject
leaders subjected these responses to a rigorous data cleaning procedure, leading to removal of
452responsesthatwereeithersubstantiallyincomplete,eithercontainedmultipleinvalidresponses
tovalidationscreeningitems. Thisprocedureresultedinafinalsampleof2663pupils(57.1%girls;
M =14.87,SD=1.67). Thisfinaldatasetwasdistributedbytheconsortiumtothecollaborating
age
researchersforfurtheranalysis.
Informedconsentwascollectedfromboththeparticipatingteenagersandtheirparents. Giventhe
largesample-size,anopt-outprocedurewasusedforcollectingconsentfromparents. Theuniversity’s
institutionalreviewboardapprovedthestudy.
3.2. Measures
3.2.1. BreadthofSocialMediaPlatformsUsed
Basedoninterviewswithyoungpersons,alistof25frequentlyusedsocialmediaapplications
wasconstructed. WeadheredtoKaplanandHaenlein’s[16]definitionofsocialmedia,whichincludes
allplatformsinwhichuserscangeneratecontentthatis(semi-)publiclyavailabletoothers. Thelatter
definitionexcludesplatformsthatfocusexclusivelyoninstantmessaging(e.g.,Whatsapp,Facebook
Messenger). ThelistofincludedplatformscanbeconsultedinTable1. Thebreadthofsocialmediause
wasassessedbyaskingforeachplatformwhethertheteenagerhadanactiveaccount(1=yes,0=no),
andthensummingthetotalnumberofactiveaccountsperparticipant.
Int.J.Environ.Res.PublicHealth2018,15,2319 6of18
Table1.Scaleitems,meansandstandarddeviations.
Fear-of-Missing-Out(FOMO)
Items M SD
1 Ifearmyfriendshavemorerewardingexperiencesthanme 2.33 1.11
2 ItisimportantthatIunderstandmyfriends’“insidejokes” 3.09 1.05
3 ItbothersmewhenImissanopportunitytomeetupwithfriends 4.16 0.90
4 WhenIgoonsummercamporvacation,Icontinuetokeeptabsonwhatmyfriendsaredoing 2.66 1.14
ProblematicSocialMediaUse(PSMU)
Items M SD
1 Howfrequentlydoyoufinditdifficulttoquitusingsocialmedia? 2.89 1.19
2 Howfrequentlydoothers(e.g.,yourparentsorfriends)tellyouthatyoushouldspendlesstimeonsocialmedia? 2.72 1.28
3 Howfrequentlydoyoupreferusingsocialmediaoverspendingtimewithothers(e.g.,withfriendsorfamily)? 1.89 0.97
4 Howfrequentlydoyoufeelrestless,frustratedorirritatedwhenyoucan’taccesssocialmedia? 2.33 1.16
5 Howfrequentlydoyoudoyourhomeworkpoorlybecauseyoupreferbeingonsocialmedia? 2.51 1.17
6 Howfrequentlydoyouusesocialmediabecauseyoufeelunhappy? 2.31 1.23
7 Howfrequentlydoyoulacksleepbecauseyouspentthenightusingsocialmedia? 2.44 1.35
Phubbing
Items M SD
1 Howfrequentlydoyouuseyourmobilephoneduringaconversationinabarorrestaurant? 2.39 0.99
2 Howfrequentlyareyouengagedwithyourphoneduringaconversation? 2.13 0.96
3 Howfrequentlydoyouchecksocialmediaonyourphoneduringapersonalconversation? 1.89 0.92
3.2.2. DepthofSocialMediaPlatformsUsed
Thedepthofsocialmediausewasmeasuredbyassessingforeachactiveplatformhowfrequently
itwasused(1=lessthanonceperweek,5=multipletimesperday). Questionswithrespecttothe
usagefrequencyofaplatformwereonlyansweredbyparticipantswhohadanactiveaccountforthe
platform. AsvisibleinTable2,asubstantialnumberofplatformswasusedby(very)fewparticipants.
Weoptedtoonlyincludethoseplatformswhowereusedbyatleast5%ofthesample. Theanalyses
forHypothesis1a,concerningFOMOasapredictorofplatformusagefrequency(seeTables3and4)
areperformedonthebasisofthesubsampleofusersofeachplatform.
Int.J.Environ.Res.PublicHealth2018,15,2319 7of18
Table2.Percentageofteenagerswithanaccountonvarioussocialmediaplatformsandaveragefrequencyofuseamongaccountholders(1=lessthanonce/week,
5=multipletimes/day).
LessthanOnce Onceper MultipleTimes MultipleTimes
AverageUsageFrequency Daily
SocialMediaPlatform N %ofTotalSample perWeek Week perWeek perDay
M SD % % % % %
Facebook 2360 89% 4.49 0.87 1.4 3.6 6.4 22.2 66.5
Snapchat 1937 73% 4.36 1.00 2.4 4.5 10.1 20.5 62.5
Instagram 1680 63% 4.36 0.97 1.5 4.4 15.7 31.8 46.6
YouTube 1596 60% 4.17 0.95 2.1 4.4 9.7 22.3 61.4
Google+ 925 35% 2.67 1.40 28.2 21.5 19.8 16.4 14.1
Twitter 582 22% 3.63 1.35 8.8 14.9 19.4 18.6 38.3
Swarm 510 19% 4.26 1.09 3.7 5.5 10.8 20.6 59.4
WeHeartIt 329 12% 3.42 1.34 10.6 16.4 21.9 22.2 28.9
Pinterest 324 12% 2.6 1.34 28.1 21.6 24.4 14.5 11.4
Tumblr 298 11% 3.52 1.35 9.4 16.4 21.1 18.8 34.2
Vine 232 9% 3.12 1.38 15.9 19.8 23.3 18.5 22.4
Foursquare 172 6% 3.03 1.72 34.3 8.7 9.9 13.4 33.7
Tinder 120 5% 2.52 1.51 36.7 20 15.8 9.2 18.3
Kiwi 117 4% 3 1.58 25.6 18.8 13.7 13.7 28.2
Ask.fm 92 3% 3.6 1.60 20.7 6.5 12 14.1 46.7
Runkeeper 72 3% 2.17 1.10 31.9 34.7 23.6 4.2 5.6
Reddit 60 2% 3.07 1.48 20 20 18.3 16.7 25
Happening 48 2% 2.65 1.42 29.2 20.8 20.8 14.6 14.6
Vimeo 32 1% 2.91 1.61 34.4 6.3 15.6 21.9 21.9
Strava 25 1% 2.6 1.44 28 28 16 12 16
LinkedIn 24 1% 2.08 1.38 50 16.7 20.8 12.5 /
Periscope 15 1% 3.07 1.28 13.3 20 26.7 26.7 13.3
Endomondo 11 0% 2.73 1.74 36.4 18.2 9.1 9.1 27.3
Ello 8 0% 1.5 1.41 87.5 / / / 12.5
Meerkat 6 0% 2.33 2.07 66.7 / / / 33.3
Int.J.Environ.Res.PublicHealth2018,15,2319 8of18
Table3.Gender,age,schooltrackandFear-of-Missing-Out(FOMO)aspredictorsofthefrequencyofFacebook,Snapchat,Instagram,Youtube,GooglePlusandTwitter.
Facebook Snapchat Instagram Youtube GooglePlus Twitter
PE SE Wald PE SE Wald PE SE Wald PE SE Wald PE SE Wald PE SE Wald
Gender(boy) −0.50 0.09 32.55*** −0.68 0.09 52.79*** −0.61 0.10 35.85*** 0.72 0.10 56.21*** 0.18 0.12 2.23 −0.25 0.15 2.58
Gender(girl) a
Age 0.15 0.03 28.1*** 0.02 0.03 0.30 0.12 0.03 14.36*** −0.01 0.03 0.14 −0.09 0.04 6.42* 0.02 0.05 0.15
Schooltrack(voc) 0.41 0.14 8.72** 0.40 0.14 8.00** −0.34 0.14 5.75* 0.54 0.15 13.58*** 0.51 0.17 8.79** 0.36 0.25 2.18
Schooltrack(s-voc) 0.28 0.12 5.67* 0.35 0.12 8.88** −0.01 0.12 0.00 −0.01 0.12 0.00 0.40 0.15 6.84** 0.76 0.18 19.06***
Schooltrack(ac) a
FOMO 0.48 0.07 55.09*** 0.28 0.07 16.89*** 0.34 0.07 22.48*** 0.18 0.07 7.08** 0.04 0.09 0.22 0.15 0.11 2.02
X2(1821)=1635.34, X2(1731)=1842.31, X2(1643)=1716.37, X2(1623)=1621.94, X2(1335)=1370.00, X2(1083)=1131.58,
PearsonGOF
p=1.00 p=0.031 p=0.102 p=0.503 p=0.247 p=0.148
X2(5)=150.10, X2(5)=88.07, X2(5)=79.19, X2(5)=75.47, X2(5)=17.20, X2(5)=29.41,
−2LLGOF
p<0.001 p<0.001 p<0.001 p<0.001 p=0.004 p<0.001
NagelkerkeR2 0.07 0.05 0.05 0.05 0.02 0.05
*p<0.05, **p<0.01, ***p<0.001, Note1: PE=parameterestimate, SE=standarderror, Wald=Waldteststatistic, voc=vocational, s-voc=semi-vocational, ac=academic,
GOF=goodness-of-fit,a=referencecategory.
Table4. Gender,age,schooltrackandFear-of-Missing-Out(FOMO)aspredictorsofthefrequencyofSwarm,WeHeartIt,Pinterest,Tumlbr,Vine,Foursquare
andTinder.
Swarm WeHeartIt Pinterest Tumblr Vine Foursquare Tinder
PE SE Wald PE SE Wald PE SE Wald PE SE Wald PE SE Wald PE SE Wald PE SE Wald
Gender(boy) −0.48 0.19 6.58** −1.41 0.58 5.87* −0.59 0.29 4.18* −0.41 0.29 2.01 0.19 0.24 0.64 −0.04 0.29 0.02 −0.11 0.34 0.11
Gender(girl) a
Age 0.21 0.06 11.25* −0.12 0.07 2.69 −0.03 0.07 0.16 −0.03 0.07 0.16 −0.13 0.08 2.48 0.03 0.11 0.10 −0.17 0.11 2.36
Schooltrack(voc) −0.58 0.25 5.34* 0.65 0.31 4.36* −0.10 0.27 0.15 −0.50 0.33 2.30 −0.21 0.36 0.33 0.25 0.37 0.46 0.75 0.48 2.45
Schooltrack(s-voc) 0.36 0.22 2.78 0.01 0.24 0.00 −0.17 0.25 0.43 0.07 0.25 0.08 0.05 0.29 0.03 0.33 0.34 0.93 0.48 0.42 1.33
Schooltrack(ac) a
FOMO 0.16 0.13 1.49 0.24 0.14 2.86 0.19 0.17 1.28 0.29 0.15 3.77* 0.37 0.18 4.22* 0.47 0.21 5.26* 0.04 0.23 0.03
X2(915)=856.28, X2(571)=607.49, X2(619)=627.27, X2(619)=620.67, X2(599)=616.26, X2(475)=488.52, X2(371)=373.34,
PearsonGOF
p=0.917 p=0.141 p=0.400 p=0.474 p=0.304 p=0.324 p=0.456
X2(5)=28.53, X2(5)=12.53, X2(5)=6.24, X2(5)=689.76, X2(5)=8.29, X2(5)=7.47, X2(5)=4.26,
−2LLGOF
p<0.001 p=0.028 p=0.283 p=0.123 p=0.141 p=0.188 p=0.513
NagelkerkeR2 0.06 0.04 0.02 0.03 0.04 0.05 0.04
*p<0.05, **p<0.01, ***p<0.001, Note1: PE=parameterestimate, SE=standarderror, Wald=Waldteststatistic, voc=vocational, s-voc=semi-vocational, ac=academic,
GOF=goodness-of-fit,a=referencecategory. Note2:TheresultsforWeHeartIt,PinterestandTinderhavetobeinterpretedwithcautionastheassumptionofproportionalodds
wasviolated.
Int.J.Environ.Res.PublicHealth2018,15,2319 9of18
3.2.3. PrivateVersusPublicAccessibilityofSocialMediaPlatformsUsed
With respect to the private versus public accessibility of platforms, we consider Facebook and
Snapchatassocialmediaplatformsonwhichcontentisgenerallylesspubliclyaccessible(i.e.,content
is oftentimes shielded off to a public of “approved” contacts), and Youtube and Twitter as social
mediaplatformsonwhichcontentisgenerallypubliclyaccessible(i.e.,contentisusuallyaccessibleto
everyonewhovisitstheplatform).
3.2.4. FearofMissingOut(FOMO)
Theomnibusformatofthesurveyimpliedaconstraintonthenumberofitemswecoulduse.
WechosetoselectfouritemsfromPrzybylskietal.’s[8]10-itemFOMO-scale,asthisscalehadbeen
pre-validated by the authors. In Przybylski et al.’s study, the ten scale items loaded on one factor,
andwereinternallyconsistent. Intheabsenceofinformationonthefactorloadingsoftheindividual
itemsintheoriginalstudy,wechosetoselectasubsetoffouritemsthatreflectthediversityofthe
original scale items well. Those items were: “It bothers me when I miss an opportunity to meet
up with friends”, “I fear my friends have more rewarding experiences than me”, “When I go on
vacationorsummercamp,Icontinuetokeeptabsonwhatmyfriendsaredoing”,and“Itisimportant
that I understand my friends “inside jokes””. The items were measured on a 5-point Likert-scale
(1=completelydisagree;5=completelyagree).
Awell-knownriskofusingadiversesetitemstoconstructashortscale,isthatinternalconsistency
maybejeopardized[50]. Indeed,althoughanexploratoryfactoranalysisrevealedthatthefouritems
loadedontoonefactor,withallfactorloadingsabove0.55,thetotalvarianceexplainedbythefactor
(42%) was below the advised 60% threshold, and the overall Kaiser-Meier-Olkin measure (0.65)
indicatedmediocresamplingadequacy. Afurtherexaminationofthescale’sreliability, confirmed
thattheinternalconsistencyofthescalewasweak(α=0.56),andrevealedthatitcouldnotbefurther
improvedviaitemselection,asthehighestinter-itemcorrelationwas0.36(p<0.001). AppendixA
showstheinter-itemcorrelationmatrix. MeansandstandarddeviationscanbeconsultedinTable1.
Asolutiontotheissueoflowinternalconsistency,istoperformanalyseswithindividualscale
items,ratherthanwithascalevariable.Forthecurrentstudy,however,suchprocedurewouldimplyan
inflationofresults—particularlywhenansweringHypothesis1a,whichreducesthecomprehensibility
ofthestudyfindings. Thealternativeistocontinuewithasub-optimalmeasure,knowingthatthe
mainriskofusingascale-measurethatsuffersfromaweakCronbachalpha,isunderestimationofthe
realrelationship[51]. Inthecontextofthecurrentstudy,weoptedforthelattersolutionforreasons
ofcomprehensibility,andthusworkwiththescalevariabletoanswerHypothesis1. Theriskofan
underestimation of the real relationship should be kept in mind, however, when interpreting the
results. ForHypotheses2,3and4,wereportboththeresultsusingtheFOMOscalevariableandthe
individualscaleitems.
3.2.5. ProblematicSocialMediaUse(PSMU)
ProblematicsocialmediausewasassessedusinganadaptedversionoftheC-VATinstrument[52],
whichisascalebasedontheCIUS-scalethatwasdevelopedandvalidatedbyMeerkerk,Vanden
Eijndenetal.[53]andMeerkerk[54]. Theadaptedversionaddressessocialmediauseratherthan
videogaming. Theitemsweremeasuredona5pointLikert-scale(α =0.82). Thescaleitems, their
meansandstandarddeviations,andtheirfactorloadingscanbeconsultedinTable1.
3.2.6. PhubbingBehavior
Atthetimeofconstructingthequestionnaire,wewereunawareofscalesmeasuringphubbing
behavior. Hence,wemeasuredphubbingbehaviorwiththreeself-constructeditems: “Howfrequently
doyouuseyourmobilephoneduringaconversationinabarorrestaurant?”,“Howfrequentlyareyou
engagedwithyourphoneduringaconversation?”,and“Howfrequentlydoyouchecksocialmedia
Int.J.Environ.Res.PublicHealth2018,15,2319 10of18
onyourphoneduringapersonalconversation?”. Theitemsweremeasuredona5-pointLikertscale,
rangingfrom1(never)to5(almostallthetime;α=0.77). Thescaleitems,theirmeansandstandard
deviationscanbeconsultedinTable1.
3.2.7. Controlvariables
Gender(1=boy,2=girl),ageandschooltrack(1=vocational,2=semi-vocational,3=academic)
wereincludedascontrolvariablesinthelinearregressionanalyses.
3.3. Analyses
Hypothesis 1a states that teens who have a greater FOMO use social media platforms more
frequently. Weusedordinalregressionanalysisintotestthishypothesisbecausethefrequencyof
use-measureshaveordinalresponsescales. IntheanalyseswiththefrequencyofuseofSnapchat,
WeHeartit,PinterestandTinderasthedependentvariables,theassumptionofproportionalodds
wasviolated;thisoccursmorefrequentlyinlargesamples,becauseminorviolationsoftheparallel
linestestmayalreadybestatisticallysignificant[55]. Nonetheless,weadvisetointerprettheseresults
withcaution.
Hypothesis1bstatesthatFOMOpositivelypredictsthebreadthofsocialmediause. The“breadth
of social media use” variable was operationalized by counting the number of active social media
accountsthatteenshave(min=0,max=25). Weusedmultiplelinearregressionanalysistotestthe
hypothesis,afterassessingthatthestandardizedresidualsofthevariablewerenormallydistributed
(andthusthattheassumptionofnormalitywasnotviolated: becausemeasurementsgatheredinlarge
samplestypicallyhaveverysmallstandarderrors,itisadvisedtoassessnormalityonthebasisofthe
absolutevaluesofskewnessandkurtosisratherthanonZ-scoresofskewnessandkurtoses. Advised
criticalvaluesforskewness,respectivelykurtosisinlargesamplesare2,respectively7[56]. Using
these guidelines, the skewness (1.22) and kurtosis (5.95) values of the residuals indicated that the
assumptionofnormalityforregressionanalysiswassufficientlymet).
ToexploreourresearchquestiononthecomparativestrengthofthecorrelationsbetweenFOMO
andprivateplatformsontheonehand,andbetweenFOMOandpublicplatformsontheother,we
firstcalculatedthecorrelations,andnextcomparedthestrengthofthesecorrelationsusingSteiger’s
Z-test[57]inLeeandPreacher’s[58]web-basedsoftware. TheSteigerZ-testoperatesonthebasis
ofPearsoncorrelationsbetweentwodependentcorrelationswithonevariableincommon. Because
thecorrelationshavetobedrawnfromthesamesample,wefirstrecodedthe‘frequencyofplatform
use’variablessothatpersonswithoutanactiveaccountreceivedthelowestusagescore(ratherthan
amissingvalue). Thisrecodingprocedureensuredthattherewere2663responsesforeachvariable.
Next,wecalculatedthePearsoncorrelationcoefficients,whichformtheinputfortheSteiger’sZ-test.
ThereadermaynoticethatthePearsoncorrelationtestisaparametrictest,whereasthe“frequencyof
platformuse”variablesareordinal. However,thevariablesmetthestandardguidelinesforskewness
and kurtosis in large samples [56], and the Pearson correlation coefficients and the Spearman rho
correlation coefficients were highly similar (i.e., for only two out of ten correlations the difference
betweenthePearsonandtheSpearmancorrelationcoefficientexceededavalueof0.03).
Insocialscienceresearch,scalevariablesareoftentimestreatedasintervalvariables,basedon
theideathatthesetsofitemsthatcompriseeachscaleformanindexthatrepresentsanunderlying
latent factor [59]. The required assumptions for parametric testing were met. Hence, to examine
Hypotheses2and3,wefittedamediationmodelusingmodel4ofHayes’[60]. Processmacrofor
SPSS with FOMO as the independent variable, PSMU as the mediator and phubbing behavior as
the dependent variable. The indirect effect was estimated for 5000 bootstrap samples with a 95%
bias-correctedconfidenceinterval.