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ContentslistsavailableatScienceDirect

Journal

of

Science

and

Medicine

in

Sport

j o u r n a l ho me p ag e :w w w . e l s e v i e r . c o m / l o c a t e / j s a m s

Original

research

Development

and

validation

of

a

model

of

motor

competence

in

children

and

adolescents

Carlos

Luz

a,b,∗

,

Luis

P.

Rodrigues

d,e

,

Gabriela

Almeida

c

,

Rita

Cordovil

f aLaboratoryofMotorBehavior,FaculdadedeMotricidadeHumana,UniversidadedeLisboa,Portugal

bEscolaSuperiordeEducac¸ãodeLisboa,InstitutoPolitécnicodeLisboa,Portugal cFaculdadedeCiênciasdaSaúde,UniversidadeFernandoPessoa,Portugal

dEscolaSuperiordeDesportoeLazer,InstitutoPolitécnicodeVianadoCastelo,Portugal eCIDESD,Portugal

fLaboratoryofMotorBehavior,CIPER,FaculdadedeMotricidadeHumana,UniversidadedeLisboa,Portugal

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received23December2014 Receivedinrevisedform15June2015 Accepted2July2015

Availableonline10July2015 Keywords: Motorcompetence Physicaleducation Quantitativeinstruments Locomotor Manipulative Stability

a

b

s

t

r

a

c

t

Objectives:Thisstudywasaimedatdevelopingaquantitativemodeltoevaluatemotorcompetence(MC) inchildrenandadolescents,tobeapplicableinresearch,education,andclinicalcontexts.

Design:Cross-sectional.

Methods:Atotalof584children(boysn=300)withagesbetween6and14yearswereassessedusing ninewellknownquantitativemotortasks,dividedintothreemajorcomponents(stability,locomotor andmanipulative).StructuralequationmodellingthroughEQS6.1wasusedtofindthebestmodelfor representingthestructuralandmeasurementvalidityofMC.

Results:ThefinalMCmodelwascomposedbythreelatentfactorscloselyrelatedwitheachother.Each factorwasbestrepresentedbytwooftheinitialthreemotortaskschosen.Themodelwasshowntogive averygoodoverallfit(!2=12.04,p=.061;NFI=.982;CFI=.991;RMSEA=.059).

Conclusions:MCcanbeparsimoniouslyrepresentedbysixquantitativemotortasks,groupedintothree interrelatedfactors.Thedevelopedmodelwasshowntoberobustwhenappliedtodifferentsamples, demonstratingagoodstructuralandmeasurementreliability.Theuseofaquantitativeprotocolwith few,simpletoadministerandwellknown,motortasks,isanimportantadvantageofthismodel,since itcanbeusedinseveralcontextswithdifferentobjectives.Wefinditespeciallybeneficialforphysical educationsteacherswhohavetoregularlyassesstheirstudents.

©2015SportsMedicineAustralia.PublishedbyElsevierLtd.Allrightsreserved.

1. Introduction

Inthelasttwodecadesagrowingbody ofevidencesuggests

thatearlyMotorCompetence(MC)isofparamountimportancefor

developinganactiveandhealthylifestyle.1MCisusedasaglobal

termtodescribeaperson’sabilitytobeproficientonawiderange

ofmotoractsorskills.2Thisabilityhasbeendescribedinthe

lit-eraturealsoasmotorcoordination,motorperformance,ormotor

proficiency.Intheinitialphasesofmotordevelopment,children’s

MCinvolvesthemasteryoffundamentalmotorskillsthatarethe

foundationsforthemasteryofspecializedmotorskills.Ithasbeen

reportedthatphysicalactivity,3,4cardiorespiratoryfitness,5,6

phys-icalfitness,7andperceivedphysicalcompetence,8,9havepositive

effectsandassociationswithMC,aswellasaninverseassociation

∗ Correspondingauthor.

E-mailaddress:[email protected](C.Luz).

withweightstatus10inchildrenandadolescents.Thishasprovided

emergingevidencetothetheoreticalmodelproposedbyStodden

andcolleagues.1

MCasatheoreticalconstructis consideredtobesubdivided

intolocomotor(e.g.,leaping,gallopingorverticaljump),stability

(e.g.,dynamicand staticbalance)and manipulative(e.g.,

catch-ing,throwingandkicking)11proficiency.However,thisstructure

isnotalwaysreflectedinresearchand/orclinicalsettingswhere

MCconstitutesthesubjectofinterest.Severalstandardizedtests

(e.g.,TGMD, KTK),and a number of different non-standardized

protocols,12,13foundintheliterature,aredeemedtoevaluateMC

butdonotfollowthetheoreticalMCconstruct.Forexample,the

TGMDdoesnotevaluatestabilityandtheKTKdoesnotevaluate

manipulativeproficiency.Furthermore,mostinstrumentsand

pro-tocolsarerestrictedtoaspecificage,ornarrowage-range,either

duetothedevelopmentalrestrictedagewindowofthemotortasks,

ortothenatureoftheusedscoringprocedures(quantitativeor

qualitative).

http://dx.doi.org/10.1016/j.jsams.2015.07.005

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C.Luzetal./JournalofScienceandMedicineinSport19(2016)568–572

Thisgreatdiscrepancybetweentheacceptedtheoretical

con-structofMCanditsapplicationinresearchand/orclinicalsettings

showsthelackofarobustconceptualandworkingmodelofMC

thatcouldbesuccessfullyusedindifferentsettingsand

develop-mentalages.Toourknowledge,nostudieshavebeenpresented

thatvalidatethetheoreticalMCmodelstructureusingthe

origi-nalthreecategories.Somestudieshaveusedstructuralequation

modellingorconfirmatoryfactoranalysistechniquestolookfor

thestructuralvalidityofinstruments(e.g.,M-ABC,14TGMD15)but

theinstrumentsthemselveswerenotinfullagreementwiththe

theoreticalMCmodel.

Themain objectiveof thisstudy wastoestablish aworking

developmentalmodel ofMC,based onthree domains

(locomo-tor,stability,andmanipulative)ofthetheoreticalconstructofMC.

Wehypothesizedthateachofthesethreecategoriesisrepresented

byageindependentsignificantmotortasksthatcanbeobjectively

measured(product).

Toachievethispurposewehaveassessedchildrenusingseveral

motortasksrepresentativeofeachMCcategoryintheliterature,

andworkedwiththedatatofindarepresentativeandparsimonious

modelofMCusingspecificStructuralEquationsModelling(SEM)

techniques.

2. Methods

Atotalof584children(300males),aged6to14years(M=10.60,

SD=2.40), participated in this study. Children were randomly

selectedfrompublicPortugueseschoolsandhadnoknown

learn-ing disabilitiesor pre-existing motor limitations. A localethics

committeeapprovalwasobtainedandparentsprovidedwritten

informedconsent.TwoPhysicalEducation(PE)teacherswith10

years of experiencewere trained to collectthedata in regular

scheduledclasses(eachteacheralwaysassessedthesamegroup

oftasks).

Three tests for each MC category (stability, locomotor, and

manipulative)11wereselectedfromthemostusedprotocolsand

instrumentsinthemotordevelopmentliterature.Inclusioncriteria

werebeingquantitative(product-oriented)motortestswithouta

markeddevelopmental(age)ceilingeffect,andoffeasible

execu-tion.

Stabilitytestswere:(a)balancebeams16—walkingbackwards

onthreebalancebeamswith3minlengthbutofdecreasingwidths

(6,4.5and3cm).Eachparticipanthadthreeattemptsperbeam

andeachattempthadthemaximumscoreof8points.Thetotal

scorewasgivenbythesumofpointsinthethreebalancebeams

(72totalpossiblepoints);(b)Shiftingplatforms16—moving

side-waysfor20susingtwowoodenplatforms(25cm×25cm×2cm).

Eachsuccessfultransferfromoneplatformtotheotherwasscored

withtwopoints(onepointforeachstep).Participantsweregiven

two trials and only the best score was considered; (c)

jump-inglaterally16—jumpingsidewayswithtwofeettogetherovera

woodenbeamasfastaspossiblefor15s.Eachcorrectjumpscored

1pointandthebestresultovertwotrialswasconsidered.

Locomo-tortestswere:(a)hoppingononelegoveranobstacle16—jumping

overastackoffoamblocks5cmhighwithonefoot,reachingthe

floorwith thesame foot. Aftera successful attemptwith each

foot,the heightwas increasedby adding one foam block.

Par-ticipantsreceivedthree,twoor onepoint(s)foreachsuccessful

performanceonthefirst,secondorthirdtrial,respectively.

There-fore,eachchild hadthree attempts ateachheightand oneach

foot.Thetestingwasstoppedwhenaheighttrialwasnot

success-fullycompletedwithbothfeet.Thetotalscorewasgivenbythe

sumofpointsatalltheheights;(b)shuttlerun(SHR)17—running

atmaximalspeedtoalineplaced10mapart,pickingupablock

ofwood,runningbackand placingit onor beyondthestarting

line.Thenrunningbacktoretrievethesecondblockandcarryit

backacrossthefinishline. Thefinalscorewasthebesttimeof

thetwotrials;(c)standinglongjump(SLJ)18—jumpingwithboth

feetsimultaneouslyasfaraspossible.Thefinalscore(thebetter

of2attempts)wasthedistance(inm)betweenthestartingline

andthebackoftheheelatlandingclosesttotheline.

Manipula-tivetestswere:(a)walltosstest19—throwingatennisballwith

anoverarmactionagainstthewall(2mdistance),attemptingto

catchitwithbothhandsover30s.Thefinalscorewasgivenby

thebetterresult(numberofcatches)in2attempts;(b)throwing

velocity20—throwingabaseball(circumference:22.86cm;weight:

142g) at a maximum speed against a wall using an overarm

action.Threetrialswereperformed,andthefinalscorewasgiven

by the best result; and (c) kickingvelocity20—kicking a soccer

ballno.4 (circumference:64cm,weight: 350g) at amaximum

speedagainstawallusingakickingaction.Threetrialswere

per-formed,andthefinalscorewasgivenbythebestresult.Ballpeak

velocity wasmeasuredwitha Pro IIStalkerRadarGunin both

tests.

Participantscompletedageneralwarm-upbeforethebeginning

ofthetests.Then,groupsoffivestudentswereevaluatedinthe

sametaskorder.Participantsobservedademonstrationofthe

pro-ficienttechniqueandhadtheopportunitytoexperimentwitheach

taskonetimebeforetheirperformance.Motivationalfeedbackwas

given;howevernoverbalfeedbackonskillperformancewas

pro-vided.Inthethrowing/kickingtasks,childrenwereinstructedto

throw/kicktheballasfastastheycould.

Inordertoassesstheplausibilityandvalidityofourtheoretically

drivenMCmodel,weusedaspecialmulti-groupconfirmatory

fac-toranalysis,knownasstackmodel.21Inthefirsttwostepsofthis

procedure, thefullsample(584 subjects)wasrandomlysplitin

halfmaintainingthesexproportionality.Thefirsthalf(292

sub-jects)wasusedasacalibrationsample(tosettheinitialbestmodel

toentailMCaccordingtothetheoreticalframework),andthe

sec-ondasavalidationsample,usedtoassurethatthepreviouschosen

model (factors andloadingitems)wasable toreproduceevery

otherdata.

Onthethirdphase(crossvalidity)weformallytestedfor

mea-sureandstructuralinvariancebetweenthetwosplithalves.Totest

formeasureinvariance,theformalstructurefromthecalibration

samplewasimposedonthevalidationsamplewhileallparameters

wereleftfree.Usingamorerestrictedapproach(tightcross

vali-dation),structuralinvariancewasalsoimposedtothevalidation

sample,withallparametersconstrainedtothecalibrationmodel

values.

Theabsolutefitofthemodels(individualandmulti-group

anal-ysis)wasevaluatedusingtheSatorraandBentlerscaledchi-square

(!2)(1994)withcorrectionfornon-normality,whiletherelativefit

wasassessedusingthecomparativefitindex(CFI),thenormedfit

index(NFI),andthegoodnessoffitindex(GFI).Fortheseindices,

valuesover.95andupto1.0aredeemedindicativeofagoodfit.

The root mean square error of approximation (RMSEA) and

respective confidence intervals (CI) were used for evaluating

howwellthemodel-impliedreproducedthevariance-covariance

matrixofthedata,keepinginmindthatRMSEAvaluesaslowas

.06representagoodfittothemodel.21–23EQSLagrangeMultiplier

Tests(LMT)foraddinganddeletingparameterswereinterpreted

withinthetheoreticalframeworkforeachmodeltestedinthe

cal-ibrationphase,andalterationsmadeaccordingly.Variableswere

considered for deletion when LMT suggested that such

proce-dureresultedinasignificantimprovementofthemodelfit.Each

consecutivemodelwascomparedwiththeprevioususingthe

chi-squareanddegreesoffreedomchange,andwasonlyretainedwhen

thiscomparisonshowedstatisticalsignificance.Allanalyseswere

conductedusingtheEQS6.1computerprogram(Multivariate

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C.Luzetal./JournalofScienceandMedicineinSport19(2016)568–572 Table1

Indicesforevaluatinggoodnessoffitofmodelsindifferentphases.

!2 p NFI CFI RMSEA

Phase1—Calibrationsample(n=292)

Model1(9variables) 159.39(24df) .000 .881 .896 .139

Model2(8variables) 134.31(18df) .000 .880 .894 .149

Model3(7variables) 96.69(11df) .000 .897 .907 .164

Model4(6variables) 12.04(6df) .061 .982 .991 .059

Phase2—Validationsample(n=292)

Model4(6variables) 12.15(6df) .058 .986 .993 .059

Phase3—Multi-groupanalysis(n=584)

Measurementinvariance 24.20(12df) .019 .984 .992 .042

Structuralinvariance 30.44(15df) .010 .980 .990 .042

3. Results

Inthecalibrationphase(phase1)theinitialformulationofthe

MCmodelwassetaccordingtothetheoreticalformulationwith

threefactors(stability,locomotor,and manipulative),and three

possibleitems (motorskill tasks)accounting (loading)oneach

factor.Departingfromthis theoreticalmodel,weexaminedthe

solutionaccordingtothesignificanceoftheloadingcoefficients,

R2valuesofthevariablesequations,andindicesofoveralland

rel-ativefit(!2,CFI,NFIandRMSEA).EQSLagrangeMultipliertestsfor

addinganddeletingparameterswereusedtoimprovethemodel

fit,accordingtotheoreticalinterpretation.Asaresultofthis

proce-dure,threevariables(hoppingononelegoveranobstacle,walking

onabalancebeam,andtossingandcatchingaball)were

consecu-tivelydroppedfromtheoriginalmodel,resultinginafinalmodelof

MCwithsixmotortasks(jumpinglaterally,shiftingplatforms,SHR,

SLJ,throwingvelocity,kickingvelocity)andthreecorrelated

fac-torsshowingaverygoodoverallfit(!2=12.04,p=.061;NFI=.982;

CFI=.991;RMSEA=.059;CI(RMSEA)=(000–.106).Thisfinal

stan-dardizedsolutionisshowninFig.1,andthefitindexesvaluesfor

thefourconsecutivemodelstestedcanbeseeninTable1.

Inthesecondstep(validationphase),datafromthesecondhalf

ofthesamplewastestedusingthefinalspecifiedmodelfromthe

calibrationsample.Overallindicesshowedaverygoodadjustment

ofthismodeltothedata(seeTable1),similartotheonefoundin

thevalidationsample.

Inthethirdstep(crossvalidationphase),inordertotestfor

thecrossvalidityofthemodelweformallytestedformeasureand

structuralinvariancebetweenthetwosplithalves.Totestfor

mea-sureinvariance,theformalstructurefromthecalibrationmodel4

samplewasimposedonthevalidationsamplewhileallparameters

wereleftfree.Indices(!2=24.20,p=.019;NFI=.984;CFI=.993;

RMSEA=.059)fortheoverallfitofthis multi-groupmodelwere

good(seeTable1).Usingamorerestrictedapproach(tightcross

validation),structural invariance wasalsoimposed to the

vali-dationsample,withallparametersconstrainedtothecalibration

model4loadingvalues.Finalresultscontinuedtoshowagood

over-allfit(!2=30.44,p=.010;NFI=.980;CFI=.990;RMSEA=.042),and

theformaltestingfordifferencesbetweentheimposed

parame-ter’svaluesshowednosignificantvalues.So,thesolutionfoundfor

thecalibrationsample(model4)showedaverygoodadjustment

totheotherhalfofthedata,provingitsvalidityforinterpretingthe

MCmodel.

4. Discussion

TheaimofthisstudywastoestablishamodelofMC,based

onatheoreticallystructuredividedintolocomotor,stability,and

manipulative domains. In this endeavor, quantitative

(product-oriented) motor test protocols without a developmental (age)

ceilingeffect,andoffeasibleexecution,wereused.Ourpurpose

when selecting only product-oriented tests was to ensure an

objectiveevaluationandagoodsensitivitytodiscriminateamong

competencelevelsacrossages.20

TheuseofSEMfortestingthisspecificmodelisofgreatutility

sinceitallowstoworkfromthedataforreachingafinalsolutionfor

aMCstructurethatrepresentswellthecommunality(represented

bythecovariance)andtheuniquecharacteristics(non-explained

covariance)oftests(items) andcategories (factors).Theoverall

adjustmentindices,alongwiththeindividualcoefficientsforthe

pathsinvolved(factor-item;factor–factor)providesarationalefor

includingorexcludingeachitem(test),orfactor(category),orpath

(representativenessoftheteststomarka category),toa better

representationofthefullmodel.

Inthevalidationphaseourresultsconfirmedtheexistenceof

three latentfactorsrepresentingthe stability(shifting platform

andjumpinglaterally),locomotor(SHRandSLJ),and

manipula-tive(moving platformand jumping laterally)categories of MC,

eachonebestrepresentedbytwooftheinitialthreemotortasks

chosen.Thesethreefactorsshowtoreproduceverywellthree

dis-tinctiveaspectsofMC,asprovedbytheinexistenceofanychange

JUMP.

Stabil

ity

SHIFT. SLJ

Locomotor

SHR KICK

Man

ipu

lative

THROW .86 .84 .65 .88 .91 .86 .83 .94 .64

Fig.1.Pathdiagramofthemodelformotorcompetencewithcompletely standard-izedvaluesforcoefficientsandcovariances.

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C.Luzetal./JournalofScienceandMedicineinSport19(2016)568–572

suggestedinthefactor-itemstructurebythemodificationindices.

In addition,and in accordance withthetheoretical framework,

thesethreecategories(factors)provedtobecloselyrelatedwith

eachother.Overall,this modelpresenteda verygoodfit tothe

data,21–23suggestingthatitcanbeusedtorepresent(andassess)

MC.

Inthesecondphase,thereplicationoftheinitiallyfoundmodel

structureresultedalsoinaverygoodfittotheotherhalfsample

data(calibrationsample),indicatingagoodreliabilityofthemodel

toreproduceMCdata.Inthelaststepweformallytestedfor

mea-sureandstructuralinvariancebetweenthetwohalf-splitsamples,

inordertocross-validateformeasurementandstructural

invari-ance.Inbothcases,thetestedmodelshowedaveryadequatefit,

concludingforitsoverallvalidityforinterpretingMCinchildren

andadolescents.

Therefore,ourresultspostulatethatMCcanbeadvantageously

representedbylocomotor(SHRandSLJ),stability(movingplatform

andjumpinglaterally),andmanipulative(kickandthrowvelocity)

categoriesofmovementskills,andthatthelatentessenceofeachof

thesecategoriescanbeobjectivelymeasuredbytwoquantitative

motortasks.Thismodelpresentsseveraladvantagesforresearch,

education,andclinicalsettings.

Thefirstadvantageistheuseofasetofmotortaskswidelyused

inpastresearchsettingsasrepresentativeofMCcategories.11,16,20

Thesecondadvantageistheparsimonyofthemodel.Unlikeother

models’protocolsthatuseseveralmotortasks,suchastheTGMD24

orM-ABC25orevensomenon-standardizedprotocols,13ourfinal

modelisonlycomprisedbysixfeasibletests.Thethirdadvantage

isthatthismodelusesobjective(quantitative)measures.

Quali-tativemethodsarefocusedontheprocess,providinginsightinto

theformorcharacteristicsofthemovement;therefore,requiring

agreater knowledgeofthemovementcomponentsand usually

requirealotoftimetoanalyzethedata.Quantitativeapproaches

arefocusedonlyonthefinalproductandenableafaster

assess-mentoftheperformanceoutcomewithahighlevelofreliability

over time.26 Thesemethodsare sensitivediscriminatorsamong

competencelevelsacrosschildhoodandearlyadolescence,20and

arecorrelatedwithqualitativeprocess-orientedassessmentsofthe

skills.27–29Moreover,quantitativemethodsalsodonotrequirea

highlevelofexpertiseandtrainingoftheevaluators,asusually

recommendedinqualitativemethods,13sincethelackof

subjec-tivityinherenttothequantitativeapproachespermitsthateven

lessexperiencedobserverscanapplyit.Theentireprotocoltakes

about10minperparticipant;howeverchildrencanbegroupedin

smallgroups,reducing theaveragetimeneededforassessment.

Furthermore,the resultsinformation can beimmediatelyused,

makingitahugeadvantagefortheuseinPEclasses,andsports’

environments.Thefourthadvantageisthatthemotortasksused

donothaveaceilingeffectoverdevelopmentalyears,andsothe

samemodel and protocolcan beusedfrom childhoodtoadult

years. Thefifth advantageis thatthe model,giving the

magni-tudeofthecorrelationsbetweenfactors,suggeststhepossibilityto

obtainaglobalcompositescoreofMC,inadditiontothecategories’

scores.

This model is representative of MC and can be used by

researchers,PEteachers, andhealth and sports training

profes-sionals,inordertoobjectivelymonitormotordevelopment.This

MCmodelseemspromising,butfurtherresearchiswarrantedto

replicatethecurrentresults.

This study has some limitations. The results confirmed the

agreementofsixofthemwiththetestedmodel,nevertheless,and

inordertoachieveamoreaccuraterepresentationofMC,abroader

rangeofmotortestscouldbewarrantedinnextstudies.In

addi-tion,inordertobeconsistentwiththenumberoftrialsforeach

skill,theuseofthreetrialscouldbemoreappropriatetoselectthe

bestscore.

Itisalsoimportanttonotethatoursamplehadchildrenfrom6

to14yearsoldandtheresultsmightevenhaveabetteradjustment

forseparategroupsofageandgender.Futureinvestigationsshould

takeintoconsiderationageandgender.

5. Conclusion

OurresultssupporttheideathatMCcanbeevaluatedthrougha

protocolwithsixmotortasksthatrepresentthethreemajorlatent

variables ofMC(i.e.,stability,locomotorandmanipulative). We

suggestthattheuseofa quantitativeapproachwithfewmotor

taskswithoutacellingeffect,whicharerepresentativeofthemajor

MCcomponents,isagoodalternativetotheexistingtesting

proto-cols.Becausethetestedmotortasksareeasytoassess,PEteachers

oreventrainedclassroomteacherscanusethismodelregularlyin

theirpracticesandevaluations.

Practicalimplications

• Briefandeasytoadministerevaluationmodelrepresentativeof

MC,whichcanbeusedbyseveralprofessionalstoobjectively

monitorMCinseveralcontexts.

• TheteachingofmotorskillsshouldbeintegratedintothePE

cur-riculumactivities,andteacherscouldusethismodelprotocolto

assesschildren’sMC.

• Thisregularassessment canhelpteacherstodevelopthebest

approachandexercisestoimprovetheirstudent’sMC.

Acknowledgments

Wewouldliketothanktheschools,childrenandparentsfor

their participation in this study. We also thank everyone who

helpedwiththedatacollection.

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Imagem

Fig. 1. Path diagram of the model for motor competence with completely standard- standard-ized values for coefficients and covariances.

Referências

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