Mediating Mechanisms in a Program to Reduce Intentions to Use Anabolic Steroids and Improve ...

14 Pages·2001·0.11 MB·English

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PreventionScience,Vol.2,No.1,2001
Mediating Mechanisms in a Program to Reduce Intentions
to Use Anabolic Steroids and Improve Exercise Self-Efficacy
and Dietary Behavior
David P. MacKinnon,1,6 Linn Goldberg,2GregN.Clarke, 3 Diane L. Elliot,2 JeeWon Cheong,1
Angela Lapin,4 Esther L. Moe,2 and Jennifer L. Krull5
This study investigated the mediating mechanisms responsible for the effects of a program
designedtoreduceintentionstouseanabolicsteroids,improvenutrition,andincreasestrength
trainingself-efficacy.Fifteenof31highschoolfootballteams(ND1,506playersatbaseline)
inOregonandWashingtonwereassignedtoreceivetheintervention.Themulticomponent
programaddressedthesocialinfluencespromotingergogenicdruguseandengagingstudents
inhealthynutritionandstrengthtrainingalternativebehaviors.Althoughtheresultsdiffered
acrossthethreedependentvariables,theprogramappearedtoworkbychangingteamnorms.
Unlikepreventionofotherdrugs,changesinknowledgeandperceivedseverityweremediators
ofprogrameffectsinthisstudy.
KEYWORDS: adolescents;prevention;anabolicsteroids;mediationanalysis.
INTRODUCTION variable. In drug prevention research, for example,
it is useful to know if knowledge, social norms, re-
The primary focus of prevention program eval- sistance skills, or beliefs are responsible for an ob-
uations is assessing change in outcome measures, served prevention program effect (Judd & Kenny,
such as drug use (Pentz et al., 1989), exercise 1981; MacKinnon, 1994). These analyses, called me-
behavior (Marcus et al., 1998), psychological symp- diation analyses, test whether the prevention pro-
toms(Wolchiketal.,1993),ormedicalillness(Multi- gram changed the mediator, which in turn changed
ple Risk Factor Intervention Trial Research Group, thedependentvariable,therebyprovidingtestsofthe
1990). Another important task of program evalua- theoretical basis of the intervention that are crucial
tionistheinvestigationofthemediatingmechanisms for furthering the science of health behavior. Addi-
bywhichprogrameffectsareobtained.Typicallypre- tionally, these new analyses yield practical informa-
vention programs are designed to change mediating tion on the intervention’s strengths and weaknesses
variableshypothesizedtoberelatedtothedependent allowingforthedesigningofmoreeffectiveandeffi-
cientprograms.Asrecentlysummarizedinareviewof
physicalactivityinterventions,“interventionresearch
1DepartmentofPsychology,ArizonaStateUniversity,Arizona. mustmorecarefullyfocusonunderstandingmediat-
2Division of Health Promotion and Sports Medicine, Oregon
ingmechanisms”(Baranowskietal.,1998,p.294).
HealthSciencesUniversity,Oregon.
Mediation analysis has already provided an in-
3Department of Psychiatry, Oregon Health Sciences University,
Oregon. sightintothecriticalprogramingredientsfordelaying
4Department of Preventive Medicine, University of Southern orpreventingdruguse.Acrossthefewstudiesthatex-
California,California. aminedmediationalprocesses,socialinfluenceshave
5DepartmentofPsychology,UniversityofMissouri,Missouri.
emerged as mediators of beneficial drug prevention
6CorrespondenceshouldbedirectedtoDavidP.MacKinnon,
Ph.D.,DepartmentofPsychology,ArizonaStateUniversity,Box effects (Botvin et al., 1999; Donaldson et al., 1994;
871104,Tempe,Arizona85287-1104;e-mail:[email protected]
Ellickson et al., 1993; Hansen, 1992; Hansen et al.,
15
1389-4986/01/0300-0015$19.50/1(cid:176)C2001SocietyforPreventionResearch
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16 MacKinnon,Goldberg,Clarke,Elliot,Cheong,Lapin,Moe,andKrull
1988).Forexample,socialnormsamongfriendsand of intentions to use AAS, nutrition behaviors, and
beliefs about the benefits of drug use mediated pro- strengthtrainingself-efficacy.
gram effects on cigarette, alcohol, and marijuana The ATLAS program was designed to prevent
use, 1 year after a social influences-based preven- AAS use by reducing intentions to use AAS and
tionprogramwasdelivered(MacKinnonetal.,1991). teaching adolescents about two alternatives to en-
Changes in antidrug attitudes and beliefs have also hancestrengthandphysicalperformance—improved
contributed to program effects on drug use among nutrition and appropriate strength training. It is as-
minorityyouth(Botvinetal.,1994).Perceivedpreva- sumed that changes in intentions lead to less AAS
lenceandacceptabilityofdruguse,butnotresistance use as many other studies have found that inten-
skills, were mediators of an alcohol prevention pro- tions predict behavior (Fishbein & Azjen, 1975;
gram(e.g.,Donaldsonetal.,1994;Hansen&Graham, Kim&Hunter,1993).ATLASwasbasedonsuccess-
1991).Overall,thesestudiessuggestthatpassiveso- fulsocial–influences-baseddrugpreventionprograms
cial pressure, such as that conveyed through peer on gateway drug use (Glynn, 1989) and prior exper-
norms, was a primary pathway to prevent drug imentaltrialsofAASprevention(Bentsetal.,1990;
use. Knowledge, beliefs about the negative conse- Goldbergetal.,1990,1991).
quences of drug use, and resistance skills were not Like most modern prevention programs, the
mediators in prior studies (Donaldson et al., 1994; ATLAS program was based on theories of behav-
Hansenetal.,1988;MacKinnonetal.,1991;Sussman ior and observed empirical relationships between
etal.,1995). risk factors and anabolic steroid use, which pro-
The purpose of this paper was to identify the vide the theoretical rationale for testing the possi-
mediating mechanisms targeted by the Adolescents blemediators.ForemostwasSocialLearningTheory
Training and Learning to Avoid Steroids (ATLAS) (Bandura,1977).Accordingtothistheory,adolescent
programthatledtoreducedintentionstouseanabolic drug use is influenced by environmental influences
steroids,improvednutritionbehaviors,andincreased (Aryetal., 1993; Hawkins et al., 1992). By observ-
strengthtrainingself-efficacy.Mediationanalysiswas ing peers, coaches, and parents, adolescents learn to
usedtodeterminewhethersocialnormsmediatespro- usedrugsandestablishnormsregardingdruguse.As
gram effects on the ATLAS dependent variables as AAS are used for muscle growth and performance
found in drug prevention studies. Alternatively, the enhancement,anabolicsteroidusewasconsidereda
mediators could differ for intention to use steroids, goal-directed activity reinforced by peers, coaches,
nutritionbehavior,andstrengthtrainingself-efficacy and other adults. To change the norms about drug
as these are not measures of drug use, and nutrition use, to increase the awareness of the disapproval of
and strength training measure positive rather than druguseinthesocialenvironment,andimproveself-
negativehealthbehaviors. efficacy skills to resist drug offers, the ATLAS pro-
gram was led by the coaching staff and designated
peereducators.
THEATLASPROGRAM ATLAS was also based on the Health Belief
Model(Janz&Becker,1984).Adolescents’decision
Anabolicandrogenicsteroids(AAS)areusedto nottouseAASisdeterminedbyperceivedsuscepti-
increasemusclegrowthandimprovephysicalperfor- bilitytoandseverityoftheeffectsofAAS.Moreover,
mance (Council on Scientific Affairs, 1990). About adolescents would choose the alternative health be-
1 million individuals have used AAS in the United haviorswhentheyseethebenefitsandreducedbarri-
States (Yesalis et al., 1993). AAS use has spread to erstotheuseofalternativehealthbehaviorsthrough
adolescents with 2.4% of twelfth graders reporting teachingappropriatenutritionandstrengthtraining.
useinarecentnationalsample(Johnstonetal.,1995). AssuggestedbytheHealthBeliefModel,theATLAS
AAS use can have negative physical and emotional programemphasizedtheharmfuleffectsofAASuse
consequences,includingabnormalliverfunctionand andsusceptibilitytothesenegativeeffects.Asparal-
mood disorders (Haupt & Rovere, 1984). As a re- lel program components, the ATLAS program pro-
sult, AAS has been denounced by many national vided the participants with nutritional guidance and
andinternationalorganizations(AmericanCollegeof strengthtrainingforthemtoobtainsimilareffectsof
SportsMedicine,1987).AlthoughreducedAASuseis AASusebutinahealthyway.
the ultimate long-term outcome of the ATLAS pro- Another theoretical frame of the ATLAS pro-
gram, this report focuses on shorter-term outcomes gram was the Theory of Planned Behavior (Ajzen,
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MediatingMechanismsoftheATLASProgram 17
1991;Fishbein&Azjen,1975).Thistheorypostulates potentiallypossessmoreinfluencethanahealthclass
that behavioral intention, which is the most im- teacher,ledtheclassroomportionoftheprogramand
mediate predictor of AAS use, is determined by madeexplicitstatementsabouttheirexpectationsfor
attitudes/beliefsregardingAASuseanditsusers,sub- theplayers’behavior.
jective norms of AAS use among peers, and per- EverymediatortargetedbytheATLASprogram
ceivedbehavioralcontroltoabstainfromusingAAS. wasexpectedtocontributetothesuccessofthepro-
The ATLAS program included several components gram.However,changesinsocialnormsshouldbethe
to change norms, beliefs, and attitudes about AAS. primarymediatorofprogrameffectsifthemediating
Theexperimentalgroupstudentsdiscussedtheissue mechanismsaresimilartothosefoundinotherdrug
of substance use in sports and reasons to use AAS, preventionresearch.Significantmediationeffectsof
analyzedmediaadvertisementsonAASeffects,and knowledge and beliefs about negative consequences
developed an anti-AAS advertisement. In addition, may be expected in this study even though there is
the experimental group received classroom sessions no consistent evidence for these constructs as medi-
designed to increase their understanding of alterna- ators in previous drug prevention research. Knowl-
tives to steroid use, including nutrition and strength edge may be a mediator of ATLAS program effects
training. butnotgatewaydrugusepreventionbecausepartici-
The effects of the ATLAS program on inten- pantsmaylackknowledgeofAASeffectswhereasef-
tion to use AAS, self-reported nutrition behavior, fectsoftobaccoandalcoholarewellknown.Similarly,
andstrengthtrainingself-efficacywerereportedelse- thenegativeconsequencesofsteroidusemaybeun-
where (Goldberg et al., 1996). There were program known,perhapsmakingchangesintheperceivedvul-
effectsonseveralpotentialmediatorsaswell.Inthis nerabilitytonegativeeffectsortheseverityofthose
paper,mediatorsrefertoallconstructstargetedbythe effectssignificantmediatorsoftheATLASprogram.
ATLASprogram.Thepurposeofthispaperistoin-
vestigatewhichoftheseconstructsactuallymediated METHODS
programeffects.Participantsexposedtotheprogram
hadincreasedknowledgeoftheeffectsofAAS,per- Participants
ceptionthatpeersandteamwerereliablesourcesof
information,confidenceinabilitytoresistoffers,neg- One thousand five hundred and six adolescent
ative attitudes toward AAS users, perceived sever- footballplayersfrom31highschoolsinOregonand
ityofAASeffectsandsusceptibilitytothoseeffects, Washingtonparticipatedinthisstudy.Footballplay-
reasons endorsed for using AAS as well as reasons ers were the focus of this study because they are at
against using AAS, perceived athletic competence, highriskforAAS.Theaverageagewas15yearsand
and self-esteem. Program students also became less 10 months. Of the total sample, 78.3% were White,
likely to believe that their coaches were tolerant of 5.3%wereAfricanAmerican,3.3%wereAsian,2.7%
AAS use or to believe in media advertisements for were Hispanic, 0.8% were Native American, and
allegedathletic-enhancingproducts. 9.6%hadamixedethnicheritage.Theparentsofthe
The ATLAS program differs from the earlier participants were well educated, with 69.3% of the
drug prevention programs in several ways. First, mothersand74.8%ofthefathershavingcompletedat
ATLAS focused on AAS rather than tobacco, alco- leastsomecollege.Thirty-twopercentoftheparents
hol,ormarijuana.Second,highschoolfootballplay- weredivorced.Themedianannualfamilyincome,as
ersratherthanjuniorhighandmiddleschoolstudents estimatedbytheplayers,wasabout$50,000.
were the study sample. Third, strength training and Ofthe1,506footballplayersthatinitiallypartic-
nutritioncouldbeofferedasalternativestoAAS.Typ- ipated in the study, 81.4% (nD1226) were present
icaldrugpreventionprogramscannotoffersuchclear atposttest.Fewerexperimental(75.8%)thancontrol
andcomparablealternativestotobaccoorotherdrug (86.3%)participantsremainedinthestudy,zD5:23,
use.Fourth,strengthtrainingsessionsreinforcedthe p<:001. From pretest to 1-year follow-up, 57.7%
propertrainingtechniqueslearnedintheclassroom. (nD869)ofthesamplewasretained,andtherewas
Fifth, unlike many adolescent drug prevention pro- nodifferentialattritionacrossgroupsatthismeasure-
gramsthatarepresentedinahealthclasssetting,the ment(57.5%incontrolschoolsand58.0%inprogram
ATLAS program was delivered in an athletic team schools;zD:14,ns).
setting with peers who share similar goals. Coaches, All 31 schools measured at baseline were re-
whospendconsiderabletimewiththeplayersandthus tainedoverthefollow-upperiods.Themainsources
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18 MacKinnon,Goldberg,Clarke,Elliot,Cheong,Lapin,Moe,andKrull
of student attrition were absence due to injury dur- combinedwiththeAugust1995datatocomprisethe
ing the football season, quitting or getting dropped 1-year follow-up assessment. Between pretest and
from the team, school transfer, or study withdrawal. posttest,theexperimentalschoolsreceiveda7-week,
Becausethesizeofthefootballteamchangesduring 14-session prevention program whereas the control
thefirstfewweeksofschoolduetodropouts,precise schools received only a pamphlet about steroid use.
estimates of the total participant pool are not avail- Nofurtherinterventionwasgivenpriortothe1-year
able. Coaches estimate that approximately 20% fail follow-upassessment.TheATLASprogramencom-
tocompletethefootballseason.Ofthosestudentsas- passed a 7-session strength training segment and a
sessedatthebaselinemeasure,81.4%weremeasured 7-sessionclassroomprogram(Goldbergetal.,1996).
atposttest,whichistheexpectedteamretentionrate. Theweightroomsessionsprimarilytargetedstrength
At 1-year follow-up, the retention rate was consis- trainingself-efficacy,butalsoreinforcedmanyofthe
tent with annual student retention rates in Portland lessonstaughtduringtheclassroomsessions.
publicschools,where71.6%ofstudentsareretained
fromyeartoyear.Inoursample,ofthosewhowere
assessedatposttest,70.8%weremeasuredat1-year Measures
follow-up.
Themediatorsselectedfortheanalysis,shownin
Table1,areasubsetofthetotalnumberofmediators
Design developed and measured in the ATLAS study. The
12potentialmediatorsselectedformediationanalysis
Thirty-four schools were randomized to condi- hadatleastthreeitemsformingthescale;hadacoef-
tionsaftermatchingonwin/lossrecordsandsocioeco- ficientalphaofatleast.6ateachmeasurement;were
nomicstatus.Threeschoolsintheexperimentalgroup measured at all three waves; and measured beliefs,
dropped out prior to the intervention. One control knowledge,norms,orresistanceskills,whichwerethe
school was reassigned to the program group, result- importantmediatorsaccordingtotheSocialLearning
ingin15experimentalschoolsand16controlschools.7 Theory,theHealthBeliefModel,andtheTheoryof
Twenty-eightofthefinal31schoolsrepresenttheorig- Planned Behavior. Beliefs measures were perceived
inal pairs that were matched on team records and severityofAASuse,perceivedsusceptibilitytoAAS
SESandthenrandomizedtoconditions.Asanincen- effects, beliefs in media advertisements, reasons for
tive,allparticipatingschoolsreceived$3,000worthof using AAS, and reasons for not using AAS; knowl-
weightroomequipment. edgemeasurewasknowledgeofAASeffects;norms
The players were measured in late August measureswereperceivedcoachtoleranceofAASuse,
1994, when the football season started (pretest), in perceivedpeertoleranceofAASuse,teamasanin-
November 1994 near the end of the football season formationsource,peersasaninformationsource,and
(posttest), and again in late August 1995 (1-year normativebeliefsaboutAASuse;andtheresistance
follow-up). Graduating seniors were assessed just skillsmeasurewasabilitytoturndownoffersofdrugs.
prior to graduation in Spring 1995 (N Program D
94, N Control D 146) as they would not have been
available for assessment in August. Their data were MediationAnalysis
The steps for testing mediation described in
7There was no significant difference between the experimental
thecontrolgroupsonseveralimportantdemographicvariables, BaronandKenny(1986)andMacKinnonandDwyer
whetherornotweincludedthethreeschoolsthatwereoriginally (1993)werefollowed.Mediatorswithnonsignificant
assignedtothecontrolgroups.Analysisofthedatawithoutthe program effects or nonsignificant relationships with
onereassignedschoolledtovirtuallyidenticalconclusionstothose
theoutcomemeasurewereunlikelytobesignificant
reportedhere.Also,whenweexaminedtheprogramimplemen-
mediators of program effects. There were instances,
tationdatabasedontheobservationsbytheATLASstaff,the
oneexperimentalschoolthatwasoriginallyassignedtothecon- however,wherethelackofprogrameffectsoncertain
trolgroupwasinthemiddlerangeofglobalratings(1:lowto10: mediators provided information about the program
high):Theaverageratingswere4fortheclassroomsessionsand and its theoretical basis. Two of the mediators, per-
5.5fortheweightroomsessions.Thisschoolimplementedsixout
ceived AAS norms and perceived peer tolerance of
ofsevenclassroomsessions.Thus,itisunlikelythattheoriginal
drug use, did not have clear program effects but
controlschoolreassignedtotheexperimentalgroupwasdifferent
fromtherestoftheexperimentalschools. wereincludedintheanalysisasthesewereimportant
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MediatingMechanismsoftheATLASProgram 19
Table1. Constructs,IndividualItems,andCronbach’sfiReliabilityCoefficients
Cronbach’sfi
Constructsanditems Baseline Posttest 1-yearfollow-up
IntenttouseAAS .923 .921 .918
Iintendtotrytouseanabolicsteroids.
Iwouldbewillingtousesteroidstoknowhowitfeels.
Iamcurioustotryanabolicsteroids.
Iwoulduseanabolicsteroids,ifmoreofmyteammateswouldstartusingthem.
Iwoulduseanabolicsteroids,ifmoreofmyfriendswouldstartusingthem.
Nutritionbehaviors .810 .809 .816
OverthelastfewmonthsIhavetriedtoimprovemydiet.
Ieatadietthathasnomorethan30%caloriesfromfat.
IamawareofthecaloriecontentofthefoodIeat.
Isetgoalsformynutrition.
IkeeptrackofthecaloriesIeat.
IkeeptrackoftheproteinIeat.
IchoosehealthyfoodwhenIeatatafastfoodrestaurant.
Strengthtrainingself-efficacy .879 .902 .914
Iknowhowtotrainwithweightstobecomestronger.
Iknowhowtotrainwithweightstogetmorepower.
Iknowhowtotrainwithweightstoincreasemyendurance.
Iknowthebasicsofagooddiettohelpbuildmymuscles.
InthelastfewmonthsIhaveincreasedmymaximumweightonthebenchpress.
Iknowhowtotrainwithweightstogetasstrongandquickaspossible.
KnowledgeoftheeffectsofAAS .849 .898 .915
Pleasemarkanyoftheeffectsorbenefitsthatyoubelieveanabolicsteroidscancause:
moreargumentsandfights,improvephysically,uncontrolledanger,increasedacne
onfaceandback,frequenturgetourinate,sexualproblems,nosebleeds,breast
development,testiclesshrinking.
Pleasemarkwhetherornotyouthinkthesehealthproblemscanreadilybecaused
byanabolicsteroids:liverdisease,heartdisease,cancer,stuntedgrowth,
sterility,hearingproblems,AIDSbysharingneedles,death,baldness.
PerceivedcoachtoleranceofAASuse .640 .764 .761
Ihavetalkedwithatleastoneofmycoachesaboutdifferentwaystogetstronger/
fasterinsteadofusingAAS.
Onmyteamtherearerulesagainstusinganabolicsteroids.
IfIgetcaughtusingAAS,Iwouldgetintroublewithmycoaches.
Teamasaninformationsource .758 .824 .823
Beingonthefootballteamhasimprovedmyhealth.
Beingonthefootballteamteachesplayersaboutgettingstronger.
Beingonthefootballteamteachesplayersabouteatinghealthy.
Peersasaninformationsource .844 .882 .878
Myteamleadershelpmelearnaboutdrugprevention.
Myteamleadershelpmelearnaboutsportsnutrition.
Myteamleadershelpmelearnaboutweightlifting.
Abilitytoturndowndrugoffers .875 .887 .863
Iwouldbecomfortableturningdownafriendwhoofferedmeanabolicsteroids.
Iwouldbecomfortableturningdownafriendwhoofferedmealcoholordrugs.
Iwouldbecomfortableturningdownaweightlifterwhoofferedmeanabolicsteroids.
Iwouldbecomfortableturningdownaweightlifterwhoofferedmealcoholordrugs.
Perceivedpeertoleranceofdruguse .917 .913 .895
Myteammateswouldn’tcareifIusedthefollowing:
cigarettes,alcohol,marijuana,anabolicsteroids,humangrowthhormone
NormativebeliefsaboutAASuse .813 .802 .827
Outofevery100highschoolfootballplayersatotherschools,howmanydoyou
thinkhaveeverusedanabolicsteroids,evenonce?
Outofevery100highschoolfootballplayersatyourschool,howmanydoyou
thinkhaveeverusedanabolicsteroids,evenonce?
Outofevery100averagemalestudentsatyourschool(notjustathletes,but
everyone),howmanydoyouthinkhaveusedanabolicsteroids,evenonce?
(Continued)
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20 MacKinnon,Goldberg,Clarke,Elliot,Cheong,Lapin,Moe,andKrull
Table1. (Continued)
Cronbach’sfi
Constructsanditems Baseline Posttest 1-yearfollow-up
PerceivedseverityofAASuse .820 .826 .839
Thebadeffectsofanabolicsteroidsgoawayassoonasyoustopusingthem.
Onlyafewpeoplewhouseanabolicsteroidseverhaveanyharmfulorunpleasant
sideeffects.
Anabolicsteroidsarenotdangerousifyouusethemonlyafewmonthseachyear.
PerceivedsusceptibilitytoAASeffects .704 .765 .752
IfIweretouseanabolicsteroids,Iwouldn’thaveanybadsideeffects.
Whatarethechancesthatanaveragehighschoolathletewouldhaveserioushealth
consequencesasaresultofregularanabolicsteroiduse?
Whatarethechancesthatyoupersonallywouldhaveserioushealthconsequences
asaresultofregularanabolicsteroiduse?
Beliefsinmediaadvertisements .746 .814 .805
Apictureofamuscularpersoninanadvertisementinamusclemagazineisproof
enoughthattheproductbeingadvertisedreallyworks.
Ifamagazinerunsanadvertisementforaproduct,theymusthavecheckeditout
andfoundthattheclaimsintheadvertisementweretrue.
Ithinkthatmostproductsadvertisedinmusclemagazinesdowhattheyclaimtodo.
ReasonsforusingAAS .865 .855 .872
Ifyouweregoingtouseanabolicsteroids,whywouldyoutakethem?Pleasemark
allthereasonsthatareorwerereasonswhyyouwouldtakesteroids:
increaseinsizeorweight(togetbigger),getstronger,becomeabetterathlete,
improvemyappearanceformuscledefinition,bemoreaggressive,increase
chancesofcollegesportscholarship,togetmorepraisefromcoachandtrainer,
playersonmyteamwereusingthem,myfriendswereusingthem.
ReasonsfornotusingAAS .842 .886 .892
Ifyoudon’tusesteroids,whynot?Markallthatapply:
concernaboutpossiblehealthrisk,afraidofbecomingaddicted,afraidof
undesirablesideeffects,afraidofbecomingaggressiveoroutofcontrol,
knowasteroiduserwhohadsideeffects,coachesdisapproveofsteroids,
parentsdisapproveofsteroids,friendsand/orteammatesdisapprove,thedrugs
costtoomuch,steroidsaretoohardtoget,afraidofbeingcaught,
friend/teammategotcaughtusingsteroids,notcompetingorworking
outanymore,becauseitischeating.
theoreticalmediators.Mediationeffectswereexam- aninformationsourceisthemediatorandintentionto
ined at the individual level of analysis because the useAASistheoutcome.Thesinglemediatormodel
numberofschools(ND31)wassmallforthecovari- shown in Fig. 1 included paths to describe the rela-
ance structure analysis (Tanaka, 1982) at the school tionshipbetweenbaselineandfollow-upvaluesofthe
level.Wealsorantheanalysis,usingmultilevelmod- mediator (b ) and between baseline and follow-up
1
els (Krull & MacKinnon, 1999), and this led to the values of the outcome measure (b ). The path from
2
sameconclusionsdescribedintheResultssection.In thebaselinemediatortothefollow-upoutcomemea-
mostcases,thestandarderrorsofthemediatedeffect sure was also included (b ). Covariances among all
3
wereslightlyhigherinthemultilevelanalysis. the exogenous variables in the model (the program
Separate multiple mediator models were es- variable,thebaselinemediator,andbaselineoutcome
timated for posttest and 1-year follow-up. The measure)werefreelyestimatedasrepresentedbythe
parametersandstandarderrorsofthemodelwerees- double-headedarrows.Thedirecteffect,ornonmedi-
timatedusingcovariancestructureanalysis(AMOS; ated effect, of the program on the outcome was b .
4
Arbuckle & Wothke, 1999). First, the mediation ef- The program effect on the mediator was b , and the
5
fect for each individual potential mediator on each regressioncoefficientrelatingthemediatortotheout-
dependentvariablewastested.Figure1showsanex- comemeasurewasb .Themediatedeffectwasequal
6
ample of the single mediator model, where peers as tob b ,andthestandarderrorofthemediatedeffect
5 6
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MediatingMechanismsoftheATLASProgram 21
dropped from the football squad. The AMOS com-
puter program was used to conduct a full informa-
tion maximum likelihood estimation under the as-
sumptionthatthemissingdataaremissingatrandom
(Arbuckle,1996).Missingatrandomassumesthatthe
reason for the missing data is either random or ran-
domafterincorporatingothervariablesmeasuredin
thestudy.Evenwhenthemissingatrandomcondition
isnotsatisfied,theparameterestimatesandstandard
errorsaregenerallybetterandneverworsethanesti-
matesbasedonpairwiseorlistwisedeletion(Graham
et al., 1994). Adjustment for missing data, using full
Fig.1. Twowavemediationmodelwithpeersasaninformation informationmaximumlikelihoodimplementedinthe
sourceasthemediatorandintentionastheoutcomevariable.Note: AMOS computer program, is currently considered
PDATLASprogram,IntentionDIntentiontouseAAS,PeersD oneofthebestmethodstoadjustformissingdataand
Peersasaninformationsource.
is now beginning to be more widely used (Hawkins
etal.,1997).
q
Thepercentageoftheprogrameffectthatwasat-
(Sobel,1982)wasequalto b52(cid:190)b26 Cb62(cid:190)b25.Simulation tributabletoeachmediationalpathwaywasassessed
studies(MacKinnonetal.,1995)suggestthatthesta- inthisstudy.Thepercentagemediatedisthepropor-
tistical test of mediation using this standard error is tion of the total effect of the program exposure on
conservative(i.e.,lowstatisticalpower).Thesample the outcome variable that is mediated by the medi-
sizeinthispaperwassufficienttodetectsmalleffects. atingvariable.Thepercentagemediatedprovidesin-
Theconservativetestofmediationisappropriatebe- formationonhowmuchofthetotalprogrameffectis
cause the number of mediation tests in this report attributable to each mediator. Following Alwin and
increasesthelikelihoodofType1errors. Hauser (1975), absolute values of effects were used
In the multiple mediator model, all 12 media- intheformula,whichmayslightlyunderestimatethe
tors were included in the analysis thereby providing percentage mediated. The numerator was the abso-
a simultaneous test of the mediators. Also, all three lute value of the mediated effect. The denominator
outcome variables were included in the model. All equaledthesumoftheabsolutevaluesofdirectand
mediators were free to correlate at each wave. The mediatedeffects.
modelfitofthemultiplemediatormodelwasevalu-
atedusing´2statistics,therootmeansquareerrorof
approximation(RMSEA;Browne&Cudeck,1993), RESULTS
thenormedfitindex(NFI;Bentler&Bonnett,1980),
and the comparative fit index (CFI; Bentler,1990). SingleMediatorModel
Single and multiple mediator models results are
both presented to provide a more complete pic- The mediated effect of each mediator for each
ture of mediational processes. A significant effect dependent variable was tested first. For intention to
in the single mediator model but not in the multi- use AAS, the significant mediators at posttest were
ple mediator model is important because it suggests knowledge of the effects of AAS, perceived coach
that the mediator’s mechanism was present but was toleranceofAASuse,teamasaninformationsource,
not statistically significant when adjusted for other abilitytoturndowndrugoffers,perceivedseverityof
mediators. AASeffects,perceivedsusceptibilitytothenegative
The estimates of parameters in the model were effectsofAAS,beliefsinmediaadvertisements,rea-
adjusted for attrition. All school-based prevention sonsforusingAAS,andreasonsfornotusingAAS.
studies experience attrition when following partici- At the 1-year follow-up, these constructs remained
pants over time (Hansen et al., 1990). Attrition may significant mediators, except perceived coach toler-
begreaterintheATLASstudybecauseretentionin ance of AAS use, ability to turn down drug offers,
thestudywascontingentonremainingonthefootball and reasons for not using AAS. Also, peers as an
teambetweenmeasurements.Overall,approximately information source emerged as a significant media-
15%–20% of the players on each team quit or are torforintenttouseAASatthe1-yearfollow-up.
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22 MacKinnon,Goldberg,Clarke,Elliot,Cheong,Lapin,Moe,andKrull
For nutrition behavior, knowledge of AAS ef- meaning that the increase in reasons for using AAS
fects,perceivedcoachtoleranceofAASuse,peersas actually led to greater intention to use AAS. At the
aninformationsource,teamasaninformationsource, 1-year follow-up, perceived severity of AAS effects
and reasons for not using AAS were the significant (25%mediated)andreasonsforusingAAS(15%me-
mediatorsatposttest.Amongthese,peersandteam diated)weresignificantmediatorswiththemediated
as information sources and perceived severity were effectofreasonsforusingAASacounterproductive
significantmediatorsatthe1-yearfollow-up. effect.
Inthesinglemediatormodelforstrengthtrain-
ingself-efficacy,knowledgeofAASeffects,perceived
coach tolerance, peers and team as information NutritionBehaviors
sources, ability to turn down drug offers, perceived
severity, perceived susceptibility, belief in media ad- At both posttest and 1-year follow-up, peers
vertisements, and reasons for not using AAS sig- as an information source (22% and 31% medi-
nificantly mediated the program effects at posttest. ated at posttest and 1-year follow-up, respectively),
Atthe1-yearfollow-up,alltheseconstructsremain- team as an information source (14% and 8% medi-
ed significant mediators except reasons for not us- ated at posttest and 1-year follow-up, respectively),
ingAAS. andbeliefsinmediaadvertisements(9%and14%me-
diatedatposttestand1-yearfollow-up,respectively)
significantly mediated the program effects on nutri-
MultipleMediatorandMultipleOutcomeModel tionbehaviors.Themediatedeffectofbeliefsinmedia
advertisementswasacounterproductiveeffect.
The final models, which included all the 12 me-
diators and all three outcomes simultaneously, fit
the data well both at posttest (´2(36)D79:054, pD StrengthTrainingSelf-Efficacy
:000; RMSEA D .028; NFI D .99; CFI D .99) and
at the 1-year follow-up (´2(36)D59:817, pD:008; At posttest, team (23% mediated) and peers
RMSEAD.021;NFID.99;CFID1.00).Thesquared (23% mediated) as information sources, perceived
multiple correlation measure of explained variance coachtolerance(8%mediated),perceivedseverityof
was substantial at posttest and 1-year follow-up for AAS effects (8% mediated), knowledge of AAS ef-
intentions (.482 and .428), nutrition behavior (.399 fects (7% mediated), ability to turn down the drug
and.307),andstrengthtrainingself-efficacy(.458and offers (3% mediated), and perceived susceptibility
.477).Theestimatesofprogrameffectsonthemedi- tonegativeeffectsofAAS(2%mediated)weresig-
ator,mediatoreffectsontheoutcome,andmediated nificant mediators. At the 1-year follow-up, the me-
effectsarereportedinTable2fortheintentionout- diated effects of peers (21% mediated) and team
come,Table3fornutritionoutcome,andTable4for (20%mediated)asinformationsourcesandperceived
thestrengthtrainingself-efficacyoutcome. severityofAASeffects(10%mediated)remainedsig-
nificant.Anotherconstruct,beliefinmediaadvertise-
ments(10%mediated)wasasignificantmediatorat
IntentiontoUseAnabolicSteroids the1-yearfollow-up.
Atposttest,theprogrameffectsonintenttouse
AASweresignificantlymediatedbyperceivedsever-
DISCUSSION
ity of AAS effects (22% mediated), knowledge of
the effects of AAS (15% mediated), ability to turn
The ATLAS prevention program was designed
downoffersofdrugs(14%mediated),reasonsforus-
toreduceintentionstouseAASandtoimprovediet
ingAAS(12%mediated),perceivedsusceptibilityto
AASeffects(6%mediated),andreasonsfornotus-
ingAAS(5%mediated).8Themediatedeffectofrea- ofperceivedseverityofAASeffectsonAASintentionwas.074at
sons for using AAS was a counterproductive effect, posttestasinTable2.ThetotalprogrameffectonAASintention
wascalculatedbyaddingalltheabsolutevaluesofmediatedeffects
of12potentialmediatorsandthedirecteffect,.015,whichsummed
8Thepercentagemediatedisthemediatedeffectdividedbythe up to .341. The percentage mediated by the perceived severity
totaleffect.Forexample,theabsolutevalueofthemediatedeffect mediatorwas22%(.074dividedby.341).
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MediatingMechanismsoftheATLASProgram 23
Table 2. Program Effects on Mediators, Mediator Effects on Intention to Use AAS, Mediated Effects, and Standard
ErrorsofEstimatesintheMultipleMediatorandMultipleOutcomeModel
Posttest 1-yearfollow-up
Program Mediator Program Mediator
effecton effecton Mediated effecton effecton Mediated
mediatora intentionb effectc mediatora intentionb effectc
Mediator (SE) (SE) (SE) (SE) (SE) (SE)
Knowledgeoftheeffects 2.437 ¡.021 ¡.051 1.534 .012 .018
ofAAS (.231)⁄⁄⁄⁄ (.006)⁄⁄⁄⁄ (.015)⁄⁄⁄⁄ (.306)⁄⁄⁄⁄ (.007) (.011)
Perceivedcoachtolerance ¡.374 ¡.024 .009 ¡.161 .046 ¡.007
ofAASuse (.068)⁄⁄⁄⁄ (.023) (.009) (.086)⁄ (.028) (.006)
Teamasaninformation .559 ¡.025 ¡.014 .229 ¡.017 ¡.004
source (.058)⁄⁄⁄⁄ (.027) (.015) (.072)⁄⁄⁄ (.034) (.008)
Peersasaninformation 1.084 .027 .029 .648 ¡.006 ¡.004
source (.081)⁄⁄⁄⁄ (.018) (.020) (.102)⁄⁄⁄⁄ (.023) (.015)
Abilitytoturndown .283 ¡.168 ¡.048 .144 ¡.176 ¡.025
offersofdrugs (.068)⁄⁄⁄⁄ (.023)⁄⁄⁄⁄ (.013)⁄⁄⁄⁄ (.084)⁄ (.027)⁄⁄⁄⁄ (.015)⁄
Perceivedpeertolerance ¡.169 .030 ¡.005 .048 .042 .002
ofdruguse (.095)⁄ (.016)⁄ (.004) (.121) (.018)⁄⁄ (.005)
Normativebeliefsabout ¡.122 .029 ¡.004 ¡.007 .069 ¡.0005
AASuse (.079) (.018) (.003) (.100) (.022)⁄⁄⁄ (.007)
Perceivedseverityof .471 ¡.157 ¡.074 .269 ¡.259 ¡.070
AASuse (.063)⁄⁄⁄⁄ (.026)⁄⁄⁄⁄ (.016)⁄⁄⁄⁄ (.079)⁄⁄⁄⁄ (.032)⁄⁄⁄⁄ (.022)⁄⁄⁄
Perceivedsusceptibility .435 ¡.050 ¡.022 .278 ¡.054 ¡.015
totheeffectsofAAS (.109)⁄⁄⁄⁄ (.014)⁄⁄⁄⁄ (.008)⁄⁄⁄ (.131)⁄⁄ (.019)⁄⁄⁄ (.009)⁄
Beliefsinmedia ¡.588 .021 ¡.012 ¡.425 .007 ¡.003
advertisements (.065)⁄⁄⁄⁄ (.024) (.014) (.081)⁄⁄⁄⁄ (.029) (.012)
ReasonsforusingAAS .543 .078 .042 .480 .089 .043
(.106)⁄⁄⁄⁄ (.013)⁄⁄⁄⁄ (.011)⁄⁄⁄⁄ (.123)⁄⁄⁄⁄ (.018)⁄⁄⁄⁄ (.014)⁄⁄⁄
Reasonsfornotusing .979 ¡.016 ¡.016 ¡.001 ¡.031 .00003
AAS (.204)⁄⁄⁄⁄ (.007)⁄⁄ (.008)⁄⁄ (.262) (.008)⁄⁄⁄⁄ (.008)
Note.Thedirecteffectsofprogramexposureonintentionoutcomewere.015(.057)atposttestand¡:093(.067)at1-year
follow-up.Thedirecteffectistheeffectoftheprogramontheoutcomevariableafteradjustingforallmediators(b4in
Fig.1).
aTheprogrameffectonmediatoristhepathcoefficientofthemediatorontheprogramattheposttest(b5inFig.1).
bThemediatoreffectonoutcomeisthepathcoefficientoftheoutcomeonthemediatorattheposttest(b6inFig.1).
cThemediatedeffectistheproductoftheprogrameffectonmediatorandthemediatoreffectonoutcome.
⁄p<:10.⁄⁄p<:05.⁄⁄⁄p<:01.⁄⁄⁄⁄p<:001,two-tailed.
andstrengthtrainingself-efficacybychangingspecific metricproperties,theresultssuggestthattheATLAS
mediatingvariablesincludingknowledge,norms,re- program was not successful in changing these norm
sistance skills, and beliefs. There was evidence that measures.
the program successfully changed many but not all Therewasevidencethatfourconstructswereme-
of the mediators targeted by the ATLAS program. diators of all three outcomes in the single mediator
There were no significant program or mediated ef- modelsatposttest.Increasedperceptionoftheteam
fectsonpeertoleranceofdrugsandperceivedpreva- as an information source and perceptions of coach’s
lencenormssuggestingthattheprogramdidnotaffect tolerance of AAS use suggest that changes in team
thesemediators.Chen(1990)callsthislackofapro- andcoachnormswereimportantmechanismsinob-
gram effect on the mediator a failure of the action- taining program effects on the outcomes. The other
theory,thetheorythatlinkstheprogramcomponents mediators of all three outcomes were knowledge of
tochangesinthemediators.Mostothervariablesthat the effects of AAS and reasons against using AAS.
were not mediators in this report reflect a failure Only three mediators, team and peers as informa-
of the conceptual theory, the theory that links the tion sources and perceived severity, were significant
mediators to the outcome measure. Given that peer mediators for all three dependent variables at the
toleranceandperceivednormshadsufficientpsycho- 1-yearfollow-up.
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24 MacKinnon,Goldberg,Clarke,Elliot,Cheong,Lapin,Moe,andKrull
Table3.ProgramEffectsonMediators,MediatorEffectsonNutrition,MediatedEffects,andStandardErrorsofEstimates
intheMultipleMediatorandMultipleOutcomeModel
Posttest 1-yearfollow-up
Program Mediator Program Mediator
effecton effecton Mediated effecton effecton Mediated
mediatora Nutritionb effectc mediatora Nutritionb effectc
Mediator (SE) (SE) (SE) (SE) (SE) (SE)
Knowledgeoftheeffects 2.437 .007 .017 1.534 ¡.006 ¡.009
ofAAS (.231)⁄⁄⁄⁄ (.006) (.015) (.306)⁄⁄⁄⁄ (.008) (.012)
Perceivedcoachtolerance ¡.374 .012 ¡.004 ¡.161 .002 ¡.0003
ofAASuse (.068)⁄⁄⁄⁄ (.024) (.009) (.086)⁄ (.030) (.005)
Teamasaninformation .559 .143 .080 .229 .090 .021
source (.058)⁄⁄⁄⁄ (.027)⁄⁄⁄⁄ (.017)⁄⁄⁄⁄ (.072)⁄⁄⁄ (.036)⁄⁄ (.010)⁄⁄
Peersasaninformation 1.084 .119 .129 .648 .130 .084
source (.081)⁄⁄⁄⁄ (.019)⁄⁄⁄⁄ (.023)⁄⁄⁄⁄ (.102)⁄⁄⁄⁄ (.024)⁄⁄⁄⁄ (.020)⁄⁄⁄⁄
Abilitytoturndown .283 .014 .004 .144 .018 .003
offersofdrugs (.068)⁄⁄⁄⁄ (.023) (.007) (.084)⁄ (.029) (.004)
Perceivedpeertolerance ¡.169 .021 ¡.004 .048 ¡.009 ¡.0004
ofdruguse (.095)⁄ (.016) (.003) (.121) (.019) (.001)
Normativebeliefsabout ¡.122 ¡.012 .001 ¡.007 .024 ¡.0002
AASuse (.079) (.019) (.003) (.100) (.023) (.002)
Perceivedseverityof .471 .007 .003 .269 .072 .019
AASuse (.063)⁄⁄⁄⁄ (.026) (.012) (.079)⁄⁄⁄⁄ (.034)⁄⁄ (.011)⁄
Perceivedsusceptibility .435 ¡.006 ¡.003 .278 ¡.029 ¡.008
totheeffectsofAAS (.109)⁄⁄⁄⁄ (.014) (.006) (.131)⁄⁄ (.019) (.007)
Beliefsinmedia ¡.588 .089 ¡.052 ¡.425 .091 ¡.039
advertisements (.065)⁄⁄⁄⁄ (.024)⁄⁄⁄⁄ (.015)⁄⁄⁄⁄ (.081)⁄⁄⁄⁄ (.030)⁄⁄⁄ (.015)⁄⁄⁄
ReasonsforusingAAS .543 .016 .009 .480 ¡.018 ¡.009
(.106)⁄⁄⁄⁄ (.014) (.008) (.123)⁄⁄⁄⁄ (.018) (.009)
Reasonsfornotusing .979 .010 .010 ¡.001 ¡.010 .00001
AAS (.204)⁄⁄⁄⁄ (.007) (.007) (.262) (.009) (.003)
Note.Thedirecteffectsofprogramexposureonnutritionoutcomewere.267(.058)⁄⁄⁄⁄atposttestand.079(.070)at1-year
follow-up.Thedirecteffectistheeffectoftheprogramontheoutcomevariableafteradjustingforallmediators(b4in
Fig.1).
aTheprogrameffectonmediatoristhepathcoefficientofthemediatorontheprogramattheposttest(b5inFig.1).
bThemediatoreffectonoutcomeisthepathcoefficientoftheoutcomeonthemediatorattheposttest(b6inFig.1).
cThemediatedeffectistheproductoftheprogrameffectonmediatorandthemediatoreffectonoutcome.
⁄p<:10.⁄⁄p<:05.⁄⁄⁄p<:01.⁄⁄⁄⁄p<:001,two-tailed.
Althoughthereweremanysignificantmediators sion of effective strength training and thus changed
inthesinglemediationmodelsforbothintenttouse teamnormsaboutAASuse,whichinturnledtoim-
AAS and strength training self-efficacy, there were provedstrengthtrainingself-efficacy.Perceivedsever-
fewermediatorsforthesedependentvariableswhen ityofAASeffectswasalsoasignificantmediatorof
all12mediatorsandallthreeoutcomeswereincluded strength training self-efficacy, suggesting that the in-
simultaneouslyinthemodels.Perceivedseveritywas creased awareness of the severe negative effects of
the most powerful mediator for program effects on AAS led to improved strength training, an alterna-
intentionstouseAAS.TheATLASprogramsuccess- tivewaytoenhanceathleticperformance.
fullyincreasedtheawarenessofthenegativeeffectsof There were fewer mediators of program effects
AASuseandthisappearstohavereducedintention onnutritionbehaviors.Threeoutof12possibleme-
to use AAS. The team and peers as an information diators were significant at posttest and at the 1-year
sourcemeasuresweretheprimarymediatorsforpro- follow-up. At both posttest assessments and in both
gram effects on strength training self-efficacy. These thesinglemediatorandthemultiplemediatormodels,
resultsaresensiblebecausesuccessfullearningabout perceptionsofteamandpeersasinformationsources
strengthtrainingincludesconsiderablepeerandteam were significant mediators. The reduced number of
interaction.Thepreventionprogramfostereddiscus- significant mediators for the nutrition dependent