Substance abuse hinders desistance in young adults' antisocial behavior

18 Pages·2004·0.29 MB·English

DevelopmentandPsychopathology16~2004!,1029–1046
Copyright©2004CambridgeUniversityPress
PrintedintheUnitedStatesofAmerica
DOI:10.10170S095457940404012X
Substance abuse hinders desistance in young
adults’ antisocial behavior
ANDREAM.HUSSONG,a PATRICKJ.CURRAN,a TERRIEE.MOFFITT,b,c
AVSHALOMCASPI,b,c andMADELINEM.CARRIGa
aUniversityofNorthCarolinaatChapelHill; bInstituteofPsychiatry,
UniversityofLondon;and cUniversityofWisconsin–Madison
Abstract
Weexaminedtwohypothesesaboutthedevelopmentalrelationbetweensubstanceabuseandindividualdifferences
indesistancefromantisocialbehaviorduringyoungadulthood.The“snares”hypothesispositsthatsubstanceabuse
shouldresultintime-specificelevationsinantisocialbehaviorrelativetoanindividual’sowndevelopmental
trajectoryofantisocialbehavior,whereasthe“launch”hypothesispositsthatsubstanceabuseearlyinyoung
adulthoodslowsanindividual’soverallpatternofcrimedesistancerelativetothepopulationnormduringthis
developmentalperiod.Weconductedlatenttrajectoryanalysestotestthesehypothesesusinginterviewdataabout
antisocialbehaviorsandsubstanceabuseassessedatages18,21,and26inmenfromtheDunedinMultidisciplinary
HealthandDevelopmentStudy~N5461!.Wefoundsignificantindividualvariabilityininitiallevelsandratesof
changeinantisocialbehaviorovertimeaswellassupportforboththesnareshypothesisandthelaunchhypothesis
asexplanationsforthedevelopmentalrelationbetweensubstanceabuseandcrimedesistanceinyoungmen.
Demarcating one of the most striking transi- toshowthatbothprevalenceandincidenceof
tionsinnormativebehaviorovertheearlylife offending appear highest during late adoles-
course, young adulthood marks a significant cence and begin to drop off only in young or
shift from a pattern of increasing antisocial emergingadulthood~Blumstein,Cohen,&Far-
behavior in adolescence to emerging de- rington,1988;Farrington,1986!.Althoughthe
sistance.Thestudyofcrimedesistanceoffers age-related decline in antisocial behavior re-
auniqueperspectiveonthedevelopmentalin- mainstheleastunderstooddevelopmentalpro-
terplay between substance abuse and anti- cess in life-course research on crime and
socialbehaviorduringyoungadulthood.One psychopathology ~Laub & Sampson, 2001!,
of the most robust empirical observations in recentstudiessuggestthatsubstanceabuseis
the study of antisocial behavior, the age– highlyrelatedtoantisocialbehaviorduringthis
crime curve, plots rates of crime against age period of desistance ~Fergusson & Horwood,
2000;Huang,White,Kosterman,Catalano,&
Hawkins,2001;Krueger,Hicks,Patrick,Carl-
WethanktheDunedinStudymembers,DunedinUnitDi- son,Iacono,&McGue,2002!.
rector Richie Poulton, Unit research staff, and Study In the present article, our aim was to test
founderPhilSilva.Researchassistancewasprovidedby theroleofsubstanceabuseinthedevelopmen-
HonaLee Harrington. The Dunedin Multidisciplinary
tal process of desistance from antisocial be-
HealthandDevelopmentResearchUnitissupportedby
havior in young adulthood. To this end, we
theNewZealandHealthResearchCouncil.Wealsothank
AlexPiqueroforhishelpfulcomments.Thisresearchre- examinedtworelatedquestions.First,weex-
ceived support from the NIDA ~Grant DA15398 and amined the extent to which individual dif-
DA13148!,NIMH~GrantsMH45070andMH49414!,Wil- ferences characterize the process of crime
liamT.GrantFoundation,andAirNewZealand.
desistance.Theage–crimecurveisanempir-
Addresscorrespondenceandreprintrequeststo:Andrea
ical observation describing a group-level or
Hussong, CB#3270 Davie Hall, UNC-CH, Chapel Hill,
NC27599-3270. population-wide trajectory, but it ignores
1029
1030 A.M.Hussongetal.
potential for individual differences in de- have employed only two time points to test
sistance. Second, we examined two hypoth- whether various factors reduce antisocial be-
esesdescribingtheroleofsubstanceabusein havior relative to an initial assessment point
thenormativepatternofdesistancefromanti- ~Bushwayetal.,2001;Laub&Sampson,2001;
social behavior during young adulthood. We Moffitt, 1993; but also see Horney, Osgood,
examined both of these questions in the con- & Marshall, 1995; Laub, Nagin, & Sampson,
text of a longitudinal study, where we have 1998;Nagin,Farrington,&Moffitt,1995;Na-
repeatedly assessed a cohort of men over an gin & Land, 1993; Piquero, Brame, Maze-
8-year period as it made the transition from rolle,&Haapanen,2001!.However,todefine
adolescencetoadulthood. desistanceasadevelopmentalprocessorslow-
ing rate of antisocial behavior over time, we
needanalyticmethodsthattesttrajectoriesof
TheProcessofCrimeDesistance behavior assessed repeatedly within the pe-
riodwhendesistanceoccurs~i.e.,youngadult-
Several writers have posited that the pop- hood for men!. Newly introduced statistical
ulation pattern of crime desistance in young methods~e.g.,growthcurvemodels!meetthis
adulthood varies in a systematic way across criterion,butsuchmethodsrequireatleastthree
individuals,suchthatdesistanceisanindivid- repeatedmeasurestodefineindividualtrajec-
ualized process characterized by a decline in toriesofchange~Rogosa&Willett,1985!.In
antisocial behavior over time that eventually thepresentstudy,weexaminedindividualdif-
leads to termination or the end of antisocial ferencesindesistanceusingrecentlyavailable
activity ~Bushway, Piquero, Brody, Cauff- datathatincludeself-reportmeasuresofanti-
man,&Mazerolle,2001;Piquero,Blumstein, social behavior and three occasions of mea-
Brame, Haapanen, Mulvey, & Nagin, 2001!. surement in young adulthood. As such, we
Thatis,therearehypothesizedtobeinterindi- provide a timely, unique, and strong test of
vidualdifferencesinintraindividualchangein whether the population age–crime trajectory
antisocialbehaviorovertime~Laub&Samp- masks individual variability in desistance for
son,2001;Moffitt,1993!.Althoughpriorstud- men.
ies are consistent with this hypothesis, this
workhaslargelyreliedonmeasurementstrat-
TheRoleofSubstanceAbuse
egies,researchdesignsoranalytictechniques
that are suboptimal to test hypotheses about Buildingonthisinitialquestion,wetestedtwo
desistance ~Bushway et al., 2001; Laub & hypotheses concerning the role of substance
Sampson,2001;Moffitt,1993!. abuse in the process of crime desistance in
Forexample,antisocialbehaviorhasoften young adult men. Here we distinguish be-
beenassessedthroughcriminaljusticerecords tween antisocial behavior, defined as behav-
that,unlikeself-reportmeasures,introducethe iors that show a “disregard for, and violation
riskthatdecliningratesofantisocialbehavior of, the rights of others” according to the
overtimewillreflecttheimpactofincarcera- Diagnostic and Statistical Manual of Mental
tion, learning to evade detection through ex- Disorders,4thed.,Textrevision~DSM-IV-TR;
perience,changefromillegaltolegalantisocial American Psychological Association, 2000,
activities, or ongoing antisocial behavior that p. 701!, and substance abuse.1 Many studies
does not lead to arrest. Although self-report establish significant covariance between sub-
measuresmayintroducetheirownbias~Bab-
inski, Hartough, & Lambert, 2001; Huizinga
1. Althoughsometheoristsmayconsidersubstanceabuse
& Elliot, 1986!, this effect is thought to be tobemerelyaformofantisocialbehavior,researchin
constantovertime,andthusnottodistortthe thealcoholismfieldsuggeststhatthismaynotalways
longitudinalpatternofcrimedesistancethatis bethecase~asrepresentedinthevaryingsubtypesof
alcoholismthatmaynotincludeantisocialbehavior;
commonlyobserved.
Zucker,1986!.Inthecurrentmanuscript,wefocuson
Moreover,researchdesignsinpreviousstud-
thesetwoconstructsasseparable,althoughwerecog-
ies have historically been cross-sectional or nizethattheymayberelatedhierarchicallyaswell.
Substanceabuseandantisocialbehavior 1031
stanceabuseandantisocialbehaviorinyoung sistancesuchthatshort-termalterationsinthe
adulthood. Mechanisms that may account for courseofantisocialbehaviorareimpactedby
thiscovariationaremany,butincludethecausal substance abuse. Both models consider indi-
role of substance abuse in fueling antisocial vidualdifferencesincrimedesistance,butthey
behavior, the causal role of antisocial behav- suggest alternative, although not necessarily
ior in leading to substance abuse, reciprocal incompatible,mechanismsthroughwhichsub-
influencesbetweensubstanceabuseandanti- stance abuse influences trajectories of anti-
social behavior, and shared variance due to a social behavior over time.As such, although
common risk factor ~e.g., genetic liability!. bothareconsistentwithMoffitt’soriginaldef-
Moreover,theprominenceofanyonemecha- initionofsnares,herewedistinguishbetween
nism may vary over subpopulations of inter- thetwo.Togetherthetestingofthesedevelop-
est. However, our focus here is not on what mentalhypotheseshasthepotentialtoprovide
accounts for covariation between substance crucial information about individual differ-
abuseandantisocialbehaviormoregenerally, ences in the process of crime desistance that
butratherontherolethatsubstanceabusemay may help to identify factors that promote
play in understanding crime desistance as a desistanceorforestallit.
specificphenomenonofinterest.Attimeswe
considerthisrelationtobepotentiallycausal,
Thelaunchmodel
andatothersweconsiderhowsubstanceabuse
mayserveasamarkerforaprocessimpacting Perhaps the most common method for exam-
crime desistance. By focusing on the impact ining individual development over time, the
ofsubstanceabuseoncrimedesistancewerec- launch method is “analogous to a catapult, in
ognize that we imply a direction of influence which the initial forces of the contextual an-
that may reflect only part of the complexity tecedent are the major determinants of the
underlyingthemoregeneralrelationbetween shape of the curve of the outcome” ~Kinder-
these two constructs. Nonetheless, it is this man & Skinner, 1992, p. 166!. In such mod-
veryrelationthatismostlikelytoinformtheo- els,launchingfactorsserveasdistalpredictors
riesofcrimedesistancespecifically.2 ofchangeovertimeundertheassumptionthat
Inthisregard,weproposedtwohypotheses such time-lagged influences are more salient
in which substance abuse acts as a snare that predictors of course than are time-varying or
serves to entrench young adults in prolonged contextualfactors.Theroleofsuchdistalfac-
patternsofantisocialbehaviorduringaperiod tors,althoughoftendescribedincausalterms,
ofnormativedesistance.Buildingonthiscon- may also be one of early identification that
ceptualization of developmental snares as in- belies the effects of selection resulting from
troduced by Moffitt ~1993!, here we further priordevelopmentalprocesses.Ineithercase,
distinguishbetweentwomechanismsthrough whenappliedtothestudyofcrimedesistance
which such factors may act. The first, cap- andsubstanceabuseinyoungadulthood,this
tured by the “launch” hypothesis, posits that modelpositsthatearlysignsofsubstanceabuse
substanceabuseearlyinyoungadulthoodmay predictmaintenanceofelevatedantisocialbe-
both identify young men who are on a long- havioroveryoungadulthood.Thisprediction
termcourseofelevatedantisocialbehavioras is thus concerned with individual differences
wellassetmenonsuchacourse.Thesecond, intheinterceptsandslopescharacterizingthe
forwhichweretaintheterm“snares”hypoth- trajectories of antisocial behavior over time
esis, posits that substance abuse acts through ~seeFigure1!.
a series of proximal influences on crime de- Previousstudiesshowsupportforthelaunch
modelasanexplanationforantisocialbehav-
iorduringadolescence,whensuchtrajectories
2. Wealsorecognizethatignoringthecomplexityofsuch reflectariseinantisocialbehavior.Forexam-
larger sets of relations can result in biased findings
ple, Munson, McMahon, and Spieker ~2001!
withoutdueattentiontothiscontextinanalyticstrat-
showed that greater maternal depression pre-
egies.Wefurtherconsiderthisissueinthepresenta-
tionofourstatisticalmodels. dicted steeper escalations in children’s exter-
1032 A.M.Hussongetal.
Figure1. Acontrastofthesnaresversuslaunchhypotheses.
nalizingsymptomsovertime,especiallyamong ingyoungadulthood~Horneyetal.,1995;Laub
children with avoidant insecure attachments. et al., 1998; Quinton, Pickles, Maughan, &
However, to our knowledge, the role of sub- Rutter, 1993!. The second set may be called
stance abuse as a launching factor in young “ensnaring”factorsinthattheyinterferewith
adulthood, when the expected pattern is de- thenormativedecelerationofantisocialbehav-
sistance,hasyettobeexamined. ior that is observed in the population.As de-
fined in the current article, snares exert a
contemporaneousorshort-termeffectonanti-
Thesnareshypothesis
social behavior, such that the local effects of
In the work of developmental criminologists snaresalterthenormativecourseofantisocial
and life-course researchers ~Laub & Samp- behavior when they or their sequelae are
son, 2001; Moffitt, 1993!, two sets of factors present. Unlike protective factors, the impor-
have been implicated in desistance. The first tance of snares in the maintenance of anti-
set is often called “protective” factors in that social behavior has rarely been empirically
they hasten the process of desistance among evaluated~althoughseePiquero,Brame,etal.,
menatriskforcontinuedantisocialbehavior. 2001!.
Research focusing on protective effects has Ensnaringfactorsandprotectivefactorsare
attributedreductionsinantisocialbehaviordur- thought to play different roles in modifying
ingyoungadulthoodtotheacquisitionofadult antisocial behavior during young adulthood
roles and responsibilities that are incompati- ~Rutter,1987!.Althoughtheprotectiveinflu-
blewithanantisociallifestyleandtochanges ences offered by a good marriage or a good
in the social bonds and social controls that job may serve to actively promote desistance
accompanysuchadultroles~Laubetal.,1998; during young adulthood, snares may serve to
Sampson&Laub,1993!.Supportingtherole activelyretarddesistanceduringyoungadult-
ofprotectivefactorsincrimedesistance,sev- hood.Assuch,a“snare”ispositedtobemore
eral recent studies suggest that reduced in- than merely the opposite of a protective fac-
volvementinantisocialbehaviorcoincideswith tor. By distinguishing between these two in-
entryintogoodmarriagesandgoodjobsdur- fluences, we are able to differentiate how the
Substanceabuseandantisocialbehavior 1033
presence of various factors impacts young these pathways may result in greater anti-
adults’livesdirectly.Thisdistinctionalsohas social behavior for those who abuse sub-
importantpotentialimplicationsforinterven- stancesduringadevelopmentalperiodinwhich
tions. For example, desistance research that most individuals are curbing their involve-
focuses on protective factors in marriage and ment in deviant behavior.Across these path-
at work necessarily suggests that interven- ways, substance abuse may serve as either a
tions should focus on acquiring and promot- markervariableforaprocessinfluencingsub-
ing new adult roles and responsibilities. In stance abuse or as either a direct or indirect
contrast, research that focuses on snares sug- causal factor. Our goal here is not to dis-
geststhat,ifsnarescanbeidentified,interven- tinguish these roles of substance abuse but
tionsshouldfocusonremovingthosebarriers rather to examine whether there is support
tocrimedesistancethatarelikelytoimpedea for substance abuse to function in any one of
healthytransitiontoadulthood. these roles based on its prediction of crime
Despite their potential importance for in- desistance.
terventionstargetingantisocialbehavior,toour In contrast to the launch hypothesis, this
knowledge,littleresearchhasexaminedsuch basic prediction of the snares hypothesis is
protectivefactorsandnoresearchhasdirectly concernedwithtime-varyingdeviationsinanti-
tested the snares hypothesis. The paucity of social behavior away from the expected pat-
studies focusing on these factors is expected tern of desistance over time. Whereas snares
giventherelativelyrecentintroductionofthe are expected to alter time-specific variation
constructstotheliteratureandthelackofdata- in antisocial behavior within the course of
sets that can meet demands noted earlier for desistance, launching factors provide a more
studiesofdesistancetoincludeself-reportdata globalpredictioninwhichsubstanceabuseal-
assessed repeatedly during young adulthood. ters the actual trajectory of antisocial behav-
Nonetheless,substanceabusehasbeenhypoth- ior ~see Figure 1!. However, the launch and
esized to be a potent snare ~Moffitt, 1993!. snares hypotheses are not necessarily incom-
Several mechanisms may account for the en- patible;forexample,substanceabuseearlyin
snaringroleofsubstanceabusewithintrajec- youngadulthoodmaybothdecelerateanindi-
tories of antisocial behavior. First, substance vidual’s overall pattern of crime desistance
abuse has been associated with difficulties in relativetoothersduringthisperiod~alaunch
conventional adult roles, the same protective prediction!andincreasethelikelihoodofanti-
factors that have been found to precede socialbehaviorwithincertainpointsinyoung
desistanceinantisocialandcriminalbehavior adulthood relative to that individual’s ex-
~e.g., good marriages; Bachman,Wadsworth, pected level of antisocial behavior ~a snares
O’Malley, Schulenberg, & Johnston, 1997; prediction!. By examining these hypotheses
Leonard & Rothbard, 2000!. Second, sub- intandem,wehopetobetterelucidatethemul-
stance abuse has been associated with inter- tiple roles that substance abuse may play in
rupted education and incarceration ~Sher & crimedesistanceduringyoungadulthood.
Gotham,1999;Vaillant,1995!,bothofwhich
havebeenproposedasadditionalsnaresfore-
TheCurrentStudy
stalling normative desistance. Third, sub-
stance abuse may reflect a physiological In sum, we examined two hypotheses about
dependencethatmotivatesantisocialbehavior theeffectofsubstanceabuseondesistancein
necessary to purchase, obtain, and use sub- antisocial behavior during young adulthood.
stances.Fourth,thesocialnatureofsubstance First, we tested whether the pattern of de-
abuse during young adulthood may serve to sistancethattypifiesthepopulationtrajectory
maintain common activities and ties with a ofantisocialbehavioramongmalesoveryoung
deviant peer context. Fifth, the disinhibiting adulthood masks significant individual vari-
propertiesofalcoholandotherdrugsmayin- ability.Second,wetestedwhethertheroleof
creasetheoddsthatpoorjudgmentandimpul- alcoholandmarijuanaabuseinyoungadults’
sivitywillleadtoantisocialactivities.Eachof antisocialbehaviorcouldbeexplainedthrough
1034 A.M.Hussongetal.
eitherasnaresoralaunchhypothesis.Accord- theDunedincohorttoothersettings,seeMof-
ingtothesnareshypothesis,alcoholandmar- fitt,Caspi,Rutter,andSilva~2001!.
ijuanaabuseaccountforheterogeneityinyoung Forthecurrentstudy,menwithincomplete
adults’antisocialbehaviorbyactingassnares, data at age 18 ~n564! or who were missing
increasingtheoddsthatyoungadultswillshow data at both ages 21 and 26 ~n 5 10! were
time-specificelevationsinantisocialbehavior omitted from analyses ~final n5461 of 535
above their underlying propensity for anti- malerespondentsatage18,including438with
socialbehaviorovertime.Thelaunchhypoth- completed data and 23 with partially missing
esis examines whether substance abuse early data!.Thettestsshowednosignificantdiffer-
in young adulthood marks a distinct overall ences between retained and omitted cases,
courseofantisocialbehaviorthatfollows.By whereavailable,onantisocialbehavior,alco-
testingthesehypotheses,weexamineassump- holsymptoms,ormarijuanasymptomsatages
tionsaboutcrimedesistanceandmaintenance 18, 21, or 26. Detailed analyses comparing
and offer a more refined specification of the groups of study members who did not take
associationbetweensubstanceabuseandanti- partinassessmentsversusthosewhodidona
socialbehaviorovertime. variety of family and individual characteris-
ticshaverevealednogroupdifferencesasre-
portedinMoffittetal.~2001!.
Method
Participants Measures
ParticipantsaremembersoftheDunedinMulti- Alcohol abuse and marijuana abuse were as-
disciplinaryHealthandDevelopmentStudy,a sessed by symptoms from the Diagnostic In-
longitudinalinvestigationofhealthandbehav- terviewSchedule~DIS;Robins,Helzer,Cottler,
ior in a complete birth cohort ~Silva & Stan- & Goldring, 1989!. The DIS was adminis-
ton, 1996!. The study members were born in tered to participants at ages 18 ~DIS-III-R!,
Dunedin, New Zealand, between April 1972 21 ~DIS-III-R!, and 26 ~DIS-IV!. Antisocial
andMarch1973.Ofthese,1,037children~91% behaviorswereassessedviatheself-reportof-
of eligible births, 52% males! participated in fendinginterview,whichascertainsillegalbe-
the first follow-up assessment at age 3, and haviorsandconductproblems~Moffitt,Silva,
theyconstitutethebasesamplefortheremain- Lynam,&Henry,1994!.Antisocialbehaviors
derofthestudy.Cohortfamiliesrepresentthe and substance abuse symptoms were ascer-
fullrangeofsocioeconomicstatusinthegen- tainedonthesamedaybutinseparate,coun-
eral population of New Zealand’s South Is- terbalancedsessionsconductedbyinterviewers
land and are primarily White; fewer than 7% who were blind to the other assessment. Be-
self-identified at age 18 as Maori or Pacific causewewereinterestedinexaminingchanges
Islanders. Assessments have been conducted inboththemeanandvarianceofbehaviorover
at ages 3 ~n 51,037!, 5 ~n 5 991!, 7 ~n 5 time,continuityinitemcontentforeachscale
954!,9~n5955!,11~n5925!,13~n5850!, was very important. For this reason, parallel
15~n5976!,18~n5993!,21~n5961!,and itemswereselectedfromeachassessmentage
most recently at age 26~n5980, 499 males, tomeasureantisocialbehavior,alcoholabuse,
96% of living cohort members!. The current andmarijuanaabuse.3
studyfocusedonself-reportdatagatheredfrom
men at ages 18, 21, and 26. Rates of diag-
nosed conduct disorder, substance depen- 3. AlthoughtheDunedinstudyhasaricharrayofmea-
dence,andself-reporteddelinquentoffending suresextendingdowntoage3,ourconstraintforpar-
in New Zealand were similar to those ob- allel measurement and our focus on the desistance
characterizingantisocialbehaviorinyoungadulthood
tained for surveys of same-age epidemi-
guidedustofocusonages18–26inthecurrentstudy.
ological samples in the United States; for
Thisalsoallowedforaspecificempiricaltestofour
documentationsupportinggeneralizationfrom theoreticalquestionsofinterest.
Substanceabuseandantisocialbehavior 1035
Table1.Correlationmatrix
Variable 1 2 3 4 5 6 7 8 9
1.Antisocialbehaviorat18 —
2.Antisocialbehaviorat21 .56 —
3.Antisocialbehaviorat26 .51 .53 —
4.Marijuanasymptomsat18 .55 .37 .36 —
5.Marijuanasymptomsat21 .50 .54 .46 .55 —
6.Marijuanasymptomsat26 .42 .40 .49 .42 .57 —
7.Alcoholsymptomsat18 .53 .37 .35 .46 .42 .31 —
8.Alcoholsymptomsat21 .44 .48 .34 .34 .53 .36 .52 —
9.Alcoholsymptomsat26 .34 .32 .40 .20 .30 .48 .34 .46 —
M 1.95 1.57 1.50 0.63 1.07 1.08 2.32 3.54 2.78
SD 1.59 1.71 1.46 1.61 2.02 1.98 2.85 3.68 3.23
Reliability .67 .74 .67 .86 .86 .85 .82 .86 .84
n 461 451 455 461 446 456 461 451 456
Note:Becauseofmissingdata,n5440–461acrosscorrelationsreportedabove;allcorrelationsaresignificantat
p,.000.
Antisocial behavior. We used eight parallel marijuana abuse and dependence across the
items assessing conduct disorder ~DSM-IV- threeassessments.Thesesymptomslargelyre-
TR;American PsychiatricAssociation, 2000! flect those for substance abuse and depen-
to create a variety score for antisocial behav- denceasstatedintheDSM-IV-TR~e.g.,unable
ior within each period. Variety scores index tostopusing,tolerance,continuedusedespite
the total number of different forms of anti- healthorsocialproblems;AmericanPsychiat-
socialbehaviorinwhichaparticipanthasen- ric Association, 2000!. Each symptom was
gaged as opposed to, for example, the total codedaspresentorabsentwithintheprevious
frequency of antisocial acts. Previous studies year.Thetotalnumberofsymptomsendorsed
suggest that variety scores may better reflect foreachscaleservedasthealcoholabuseand
the extent or severity of antisocial involve- marijuana abuse scores, respectively, for the
ment and these scores are consistent with a current study. Table 1 contains psychometric
diagnosticapproachtoassessingconductprob- propertiesforthesevariables.
lems ~Gottfredson & Hirschi, 1995; Robins,
1978!.Ourvarietyscoreswerethetotalnum-
Results
ber of forms of antisocial behavior in which
each participant had engaged over the past
Analyticstrategy
twelve months. Eight forms of antisocial be-
haviorwereassessed,includingbreakingand
To test our hypotheses, we examined a series
entering, destroying property ~illegal acts of oflatenttrajectorymodels~LTMs!.LTMs,also
vandalism!, fighting ~simple assault, aggra- referredtoasgrowthcurveanalysesorrandom-
vated assault, or gang fighting!, setting fires effectsmodeling,extendslatentvariableanaly-
~arson!, lying ~criminal fraud!, stealing with ses within the structural equation modeling
confrontation~robbery!,stealingwithoutcon- framework to provide a flexible tool for test-
frontation ~criminal theft!, and carrying or ing hypotheses of change over time and pre-
using a weapon. Psychometric properties of
dictors of such change ~McArdle, 1988;
theresultingvariablesarereportedinTable1.
Meredith & Tisak, 1984, 1990!. First, we es-
timatedanunconditionallineargrowthmodel
Substanceabuse. NineteenitemsfromtheDIS to examine whether the characteristics of in-
assessed symptoms of alcohol abuse and de- dividualtrajectoriesofantisocialbehaviorvar-
pendenceand10itemsassessedsymptomsof iedacrossmen.Second,wetestedthelaunch
1036 A.M.Hussongetal.
hypothesisthroughaconditionalLTMinwhich 18, 21, and 26. Two latent factors were esti-
substance abuse at age 18 served as an exog- mated: one to define the intercept of the de-
enous predictor of change over time in anti- velopmental trajectory of antisocial behavior
social behavior. Third, we tested the snares ~withallfactorloadingsfixedto1.0!,andone
hypothesis through a time-varying covariate todefinethelinearslopeofthetrajectory~with
LTM that considers the repeated measures of factor loadings set to 0, 3, and 8 to define an
substanceabuseastime-varyingcovariatesto annual metric of time!. This model is pre-
testtheirtime-specificinfluencesonantisocial sentedinFigure2.Ameanwasestimatedfor
behavioraboveandbeyondtheinfluenceofeach theinterceptandslopefactors,andtheseval-
individual’sunderlyingtrajectoryofantisocial ues represented the mean model-implied
behavior.Thetime-varyingcovariateLTMal- developmentaltrajectorypooledoverallindi-
lows for a direct test of our hypothesis about viduals.Avariancewasalsoestimatedforthe
developmental snares given the simultaneous intercept and slope factors, representing the
estimationof~a!variabilityacrossmeninin- degreeofindividualvariabilityintrajectories
dividualtrajectoriesofantisocialbehaviorand around the group mean values. The covari-
~b!theassociationofsubstanceabusewithtime- ance between the two factors represented
specificdeviationsawayfromthispredictedtra- the covariation between initial level and rate
jectoryforeachman’santisocialbehaviorwithin of change. Larger variance estimates imply
time ~see, e.g., Bryk & Raudenbush, 1992, greater individual variability in the starting
p. 151; Curran & Hussong, 2002; Curran, point and the rate of change over time. Fi-
Muthén,&Harford,1998!. nally, residual variances were estimated for
Toavoidbiasduetothelimitedattritionin each repeated measure, and these values rep-
thesample,weestimatedallmodelsusingthe resented variability in the time-specific mea-
direct maximum likelihood procedure avail- sures not accounted for by the underlying
ableinMplus~Muthén&Muthén,1998!and randomtrajectories.
thusincludedallcaseswhohadcompletedata The unconditional LTM presented in Fig-
at age 18 and at least one subsequent time ure 2 was estimated and found to fit the ob-
point~finaln5461!.4Theadequacyofmodel serveddatawell,x2~1!59.31,p5.002,IFI5
fitwasevaluatedusingthelikelihoodratiotest .98,CFI5.98.Themeansofthelatentfactors
~i.e.,modelchisquare!andassociatedpvalue. showedthatthemodel-impliedtrajectoryforthe
Given that our large sample size may lead to groupwascharacterizedbyasignificantinter-
excessive power of the chi-square test to de- ceptof1.90differenttypesofantisocialbehav-
tect even small misspecifications ~MacCal- ioratthefirsttimeperiod~t526.33,p,.001!,
lum, 1990!, we also used two incremental fit andasignificantlydecreasingslopeof.05units
indicesthatarelessdependentonsamplesize: peryear~t525.84,p,.001;seeFigure3!.
thecomparativefitindex~CFI;Bentler,1990! Thus, the model-implied mean rate of anti-
andtheincrementalFI~IFI;Bollen,1989!. social behavior significantly decreased from
1.90to1.50typesofbehaviorovertheperiod
ofstudy.Further,significantvarianceestimates
Trajectoriesofantisocialbehavior forboththeintercept~cZ 51.77,t58.96,p,
inyoungadulthood .001!andslope~cZ 50.02,t52.69,p,.01!
factorsindicatedsubstantialinterindividualvari-
Toexaminethefixedandrandomcomponents
abilityinintraindividualdevelopmentaltrajec-
ofgrowthinantisocialbehavior,weestimated
tories of antisocial behavior. Finally, the
an unconditional LTM for the repeated mea-
negativecorrelationbetweentheinterceptand
sures of antisocial behavior reported at ages slope factors ~r52.44, t523.20, p , .01!
indicatedthathigherinitialvalueswereasso-
4. Comparisonsweremadeforallanalyseswhentheef- ciatedwithsteeperdecreasesovertime.
fectsofmissingdatawereestimatedusingmaximum
Overall,theseresultsindicatethatthemean
likelihoodinMplusversuswithresultsusinglistwise
developmental trajectory of antisocial behav-
deletion.Parameterschangedonlyslightlyandnosub-
stantivedifferenceswerefoundacrossapproaches. ior for the sample is significantly decreasing
Substanceabuseandantisocialbehavior 1037
Figure2. Theunconditionalgrowthmodelforantisocialbehavior.
over time, consistent with previous findings greater than 0!, 13% showed no change and
on the age–crime curve. However, we also 34% showed increasing slopes. These results
foundthattherearesubstantialindividualdif- furtherunderscorethenotablevariationinin-
ferences in both the initial level and rate of dividualtrajectories.Althoughthegrowthtra-
changeovertime.5Figure4depictssuchvari- jectories explained 70, 49, and 78% of the
ation by plotting the intercept and slope val- varianceinthetime-specificindicatorsofanti-
uesforeachparticipant’sestimatedtrajectory socialbehavioratages18,21,and26,respec-
against one another.6 These trajectories were tively,significantresidualvariancesremained
estimated by conducting separate regression at each age. Thus, the underlying trajectory
models within each case with complete data. processisaccountingforonlyaportionofthe
Asindicated,53%ofparticipantsshowedde- observed variability in antisocial behavior
creasing trajectories over time ~i.e., slopes withineachtimeperiod.
5. Toexaminewhethermenwhowereincarcerateddur-
ingthe12-monthperiodsbeforeassessmentsatages Testofthelaunchhypothesis
21 and 26 accounted for this pattern of desistance
~Piquero,Blumstein,etal.,2001!,wereestimatedthese We next estimated a conditional LTM that
modelsdroppingthe14menwhohadbeenincarcer- tested the hypothesis that substance abuse at
atedformorethan1monthpriortoeitherassessment
age18predictsaslowedordampenedpattern
point. No meaningful changes in the findings oc-
ofdesistanceintheoveralldevelopmentaltra-
curred.We also reestimated these models to explore
whethercasesthatshowedanotabledropinantisocial jectoryofantisocialbehavioroveryoungadult-
behavioratage21relativetoages18and26servedas hood.Inotherwords,thismodeltestedwhether
influentialoutliers.Again,nomeaningfulchangesin themagnitudeofinterceptsandslopesunder-
thefindingsoccurred.
lying antisocial behavior varied as a function
6. Notethattheseindividualcasebycaseestimatesare
ofage18substanceabuse.Bothmarijuanaand
for descriptive visualization purposes only. See Car-
rig,Wirth,andCurran~inpress!forfurtherdetails. alcohol abuse at age 18 were included as ex-
1038 A.M.Hussongetal.
Figure3. Thegroup-averagedtrajectoryofantisocialbehavior.
Figure4. Thepatternoftrajectoryparametersbasedonregressionanalyseswithinindividuals.
ogenous predictors of the intercept and slope fittothedata,x2 ~3!511.33,p5.01,CFI5
factors defining the trajectories of antisocial .99,IFI5.99.Greateralcoholandmarijuana
behavior over ages 18, 21, and 26 ~see Fig- abuse at age 18 both significantly predicted
ure 5!. The resulting model provided a good higher intercepts of the trajectories of anti-