early adolescent music preferences and minor delinquency · music(hip-hop,particularlygangstarap),...

Early Adolescent Music Preferences and MinorDelinquency

WHAT’S KNOWN ON THIS SUBJECT: Adolescent music preferenceshave been linked to problem behavior in cross-sectional studies.Particularly, preferences for loud, rebellious, and so-called“deviant” music predict externalizing problem behavior, such asminor delinquency and substance abuse.

WHAT THIS STUDY ADDS: There is a theoretical rationale forassociations between music preferences and minor delinquency.Preferences for rock, African American music, and electronicdance music indicate later minor delinquency. Music preferencesare better markers of later delinquency compared with earlyadolescent delinquency.

abstractOBJECTIVES: To test Music Marker Theory (MMT) positing that earlyadolescents’ preferences for nonmainstream types of popular musicindicate concurrent and later minor delinquency.

METHODS: MMT was tested in a 4-year longitudinal study (n = 309).

RESULTS: The results showed that early fans of different types of rock(eg, rock, heavy metal, gothic, punk), African American music (rhythmand blues, hip-hop), and electronic dance music (trance, techno/hardhouse) showed elevated minor delinquency concurrently andlongitudinally. Preferring conventional pop (chart pop) or highbrowmusic (classic music, jazz), in contrast, was not related to or wasnegatively related to minor delinquency.

CONCLUSIONS: Early music preferences emerged as more powerfulindicators of later delinquency rather than early delinquency, indicat-ing that music choice is a strong marker of later problem behavior. Themechanisms through which music preferences are linked to minordelinquency are discussed within the framework of MMT. Pediatrics2013;131:e380–e389

AUTHORS: Tom F.M. ter Bogt, PhD,a Loes Keijsers, PhD,b

and Wim H.J. Meeus, PhDb

aInterdisciplinary Social Studies, and bResearch CentreAdolescent Development, Utrecht University, Utrecht, Netherlands

KEY WORDSyouth, adolescence, music, risk factors, juvenile delinquency

ABBREVIATIONSMMT—Music Marker TheoryR&B—rhythm and blues

Mr ter Bogt and Ms Keijsers contributed equally to writing thismanuscript.

www.pediatrics.org/cgi/doi/10.1542/peds.2012-0708

doi:10.1542/peds.2012-0708

Accepted for publication Oct 1, 2012

Address correspondence to Tom ter Bogt, Interdisciplinary SocialSciences, Utrecht University, PO Box 80140, 3508 TC Utrecht,Netherlands. E-mail: [email protected]

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2013 by the American Academy of Pediatrics

FINANCIAL DISCLOSURE: The authors have indicated they haveno financial relationships relevant to this article to disclose.

FUNDING: No external funding.

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mailto:[email protected]

During the 1980s and 1990s, the loudestand most rebellious forms of rock (eg,heavy metal, gothic), African Americanmusic (hip-hop, particularlygangstarap),and electronic dance music (house,techno, hardhouse) were labeled byadults as “problem”music andperceivedas promoting violence, substance use,promiscuous sex, blasphemy, and de-pression.1,2 Although public claims thatengaging with “deviant” media will in-evitably lead to problem behavior arewildly exaggerated,3 social scientific re-search has uncovered associations be-tween media use, particularly musiclistening and music video watching, anda range of externalizing problem behav-iors, including minor delinquency.4–6

Until now, the music–problem behaviorlink has never been studied froma developmental perspective spanningadolescence.

For an estimated 80% to 90% of ado-lescents aged12 to 18 years,music is animportant medium that enhances theirmood, helps them cope with problems,and helps them develop social identity.7

Adolescents in the United States listento music between 2 and 3 hours dailyon average.8 Adolescents listen to themusic of their choice often privatelythrough personal audio in their leisuretime that is largely unmonitored byparents.3 In Europe and North America,adolescents listen mainly to 4 or 5 dif-ferent music styles: conventional,mainstream pop music (eg, chart pop);intense and rebellious rock (eg, rock,heavy metal, emo, gothic, punk); rhyth-mic and soulful African American orAfrican Caribbean music (eg, blues,soul, hip-hop, rhythm and blues [R&B],reggae); highly energetic dance music(eg, house, trance, techno, hardhouse);and complex highbrow music (eg, clas-sical music, jazz, singer-songwriter).9–12

To a large extent, preferences for musicgenres are already in place by earlyadolescence and remain highly stableacross adolescence.5,13

Adolescence is a period for testing andinternalizing culturally defined normsand values. During adolescence, youngpeople develop a more autonomousposition in relation to their parents14,15

and becomemore dependent on friendsand peers in cliques and crowds.16 Be-cause of decreased parental monitoringand parent-child communication17,18

and strengthened peer contacts andinfluences,19 adolescent minor delin-quency (eg, shoplifting, vandalism,fighting, graffiti spraying) increasesstrongly, peaks sharply at about the ageof 17, and drops precipitously in youngadulthood.20,21

A small body of research has in-vestigated the role of music in the de-velopment of externalizing behaviorsand has proposed different mecha-nisms through which they are linked.Some researchers argue that exposureto violent lyrics or music videos canhave a direct effect on externalizingbehaviors. For example, in a series ofclassic experiments, Hansen and Han-sen22 showed that the exposure to vio-lent music makes sexist and antisocialbehavior more acceptable, at least inthe short run. Anderson et al23 reportedthat such exposure fosters hostility andaggressive thoughts and feelings. Re-cently, Lennings and Warburton24 foundthat violent music lyrics rather than vi-olent visual media are more likely toelicit violence.

Other investigators, such as JeffreyArnett25 and Keith Roe,26 stressed therole of selection, suggesting that ado-lescents consume the type of mediathat fits their personality and socialcontext, that is, those who are at oddswith their parents and teachers andare inclined to sensation seeking, dis-inhibition, and substance use, gravitatetoward media reflecting these partic-ular characteristics. Both Arnett25 andRoe26 stressed that adolescents char-acterized by disinhibition, sensationseeking, and risky behaviors are more

often alienated from school, receivelower grades, and are more likely todrop out, and, as a result, tend to havestrained relations with parents, teach-ers, and other authority figures. Es-tranged from major social institutions,they seek the company of their peersand try to compensate for their failurein school with status and respectamong these peers. Their deviant me-dia consumption adds to their socialstatus.

Additionally, other research has shownthat adolescents actively seek peerswith similar music tastes to formfriendships; therefore, music is a de-fining factor in adolescent crowd for-mation.27 For all adolescents, not onlythose at odds with parents and teach-ers, selecting deviant crowds throughmusic increases the odds of “conta-gion” by others’ externalizing behav-iors.19

A number of correlational studies haveshown that adolescents who preferloud, nonmainstream, or even devianttypesofmusic engage inmore riskyanddeviant behaviors compared with theirmusically conventional peers. Morespecifically, from the 1980s onward,young people preferring rock genres,such as heavy metal, gothic, and punk,consistently showed more risky behav-iors, such as drunk driving, speeding,alcohol and drug use, and minor de-linquencies in Canadian, Dutch, US, andSwedish studies.5,28–30 In Canadian andDutch studies, different types of hip-hopfans were more likely to be involved ingangs, minor delinquency, and alcoholand drug use.5,30,31 In a rare 2-year lon-gitudinal investigation, Selfhout andcolleagues32 reported that both heavymetal and hip-hop fans reported moreexternalizing problems. Heavy types ofrock and African American music havenot been the only types of music asso-ciated with problem behavior. In the late1980s, electronic dancemusic emerged,and fans of genres, such as house,

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trance, or techno, were more likely to

use alcohol and (hard) drugs and en-

gage in risk behavior in the United

Kingdom, Canada, and the Nether-

lands.30,33,34

Not all music indicates problems, how-ever. In Canadian, Dutch, and Swedishstudies, fans of conventional chart popmusic or highbrow music, such asclassical music and jazz, showed fewerexternalizing problems.5,29,30

Although the mapping of the effects ofmusic on different outcomes is valu-able, previous studies have an impor-tant limitation. Adolescence is a periodof life during which social relations,media use, and problem behaviors arein flux. Investigations of potentialeffects of music should account forthese changes and investigate themusic-behavior link from a develop-mental perspective.

To address this issue, we propose theMusic Marker Theory (MMT), whichsynthesizes theoretical and empiricalelements reviewed previously. MMTassumes that

1. In early adolescence, youths, con-fined to the parental house, school,and direct neighborhood, have rel-atively little room to move, henceto break rules.

2. In the privacy of their own room orthrough personal audio, they canlisten to the music of their choiceand develop a “mainstream” ormore “deviant” taste in music.

3. When getting older, the balance be-tween adult-monitored activitiesand unsupervised time with peersshifts to the latter, resulting in morenorm-breaking behavior, peaking atage 17.

4. Adolescents with an early andstrong taste for deviant, nonmain-stream music will see strongersimilarities with peers listeningto similar nonmainstream musiccompared with youths less inclined

to listen to energetic, noisy, and

rebellious music.

5. The concentration of youths listeningto nonmainstream music in peercrowds leads to contagion, that is,across adolescence young peoplebelonging to nonmainstream groupsimitate and stimulate each other’snorm-breaking behaviors more thando youths in mainstream crowds.

6. In addition, systematic exposure todeviant media may directly influ-ence or exacerbate norm-breakingbehaviors among youth listening tononmainstream music.

7. Although the exact balance betweenthe consequences of selection offriends through music preferencesand potential influence of direct me-dia exposure on problem behaviorshas not yet been established, it issafe to propose that: Early adoles-cent music preferences predictlater norm-breaking behavior.

Previous theorizing on the link betweenmusic preferences and problem be-havior has assumed that music tastewould reflect a problematic social po-sition (eg, lack of school commitmentand academic achievements).25,26 MMTassumes that music preferences pre-cede norm-breaking behavior (ie, evenbefore adolescent norm-breaking behav-iors have developed in full, music pref-erences function as markers of theselater behaviors).

All of the first 6 core assumptions ofMMT are based on the results fromprevious studies on adolescent peergroup selection, peer influence in thecontext of peer crowds, and media ex-posure influences; however, the last,most central inference on the link be-tween early music preferences andlater problem behavior has not beenresearchedacross adolescence. Hence,the current study aimed to testwhetherearly adolescent preferences for loud,energetic, nonmainstreammusic, such

as heavy metal, hip-hop, and techno/hardhouse, are concurrently and lon-gitudinally associated with minor de-linquency. In a 4-year longitudinal study,initial and developing preferences for11 well-known music genres weremodeled in relation to minor de-linquency.

METHOD

Participants

The current sample was drawn froma longitudinal study on the relation-ships of adolescents with parents andpeers, the Conflict and Management ofRelationships study (2001–2005), inwhich 309 2-parent families partici-pated.17 The participating adolescents,149 boys and 160 girls, came fromvarious high schools in municipalitieslocated in an urban area in the Neth-erlands. At the baseline of the currentstudy, adolescents were in their firstyear of high school and had a modalage of 12 (mean = 12.2; SD = 0.51).

Questionnaires

Music is an evolving cultural field;therefore, the Music PreferencesQuestionnaire7,12,35 is updated every 2years; however, in the course of theConflict and Management of Relation-ships study, the same measures wereused across the study. The respond-ents were asked to rate 11 well-knownand popular types of music on 5-pointLikert scales (ranging from 1 = dislikevery much to 5 = like very much). Therespondents also had the opportunityto indicate that they were unfamiliarwith specific types of music (6 = don’tknow this genre). On average, 1.1% to15.2% of the adolescents reported theywere unfamiliar with the differentgenres across the 4 waves of the study.Over time, a decreasing number of theadolescents reported not knowing thegenres in the questionnaire (averagemissing values for the 4 subsequentmeasurement waves were 13.5%, 2.7%,


2.7%, and 0.8%). These responses weretreated as missing and imputed (rela-tive mean substitution).36

Adolescent delinquency was assessedwith a self-report questionnaire com-prising 14 items measuring minor de-linquency.38 Respondents indicated ona 4-point scale (1 = never, 2 = once, 3 =2 or 3 times, and 4 = 4 times or more)how many times they had committedminor offenses, such as shoplifting,petty theft, and vandalism in the pre-vious year. Reliabilities of this scalewere between a = 0.82 and a = 0.92.Previous analyses conducted in a Dutchsample of low-risk adolescents haveshown that this scale is adequatelyunidimensional.37

In the literature, both personality fac-tors and strained adolescent schoolrelations have been proposed to beimportant driving factors in the de-velopment of problem behavior; thus,this study considered these factors.Covariates in the analyses were aca-demic achievements (ie, educationallevel) and school commitment (usingUtrecht Management of Identity Com-mitments Scale [UMICS]38). Addition-ally, personality was corrected for byidentifying 3 of Block and Block’s39

personality types (ie, resilients, over-controllers, and undercontrollers). Forthis purpose, we applied cluster analy-sis to classify the ratings on Goldberg’s40

Big Five questionnaire (for proceduresee Akse et al41). Both undercontrollingpersonality characteristics41,42 and lackof school commitment43 have beenshown to be predictive of delinquencyand, hence, function as highly relevantconfounders in the analyses.

Strategy of Analyses

To examine the development of musicalpreferences among adolescents, 4 re-peated measurements of musicalpreferences were taken (at ages 12, 14,15, and 16). First, latent growth curvemodels were conducted separately for

all genres in Mplus.44 In this type ofanalysis, the development of musicpreferences is expressed by 2 or morelatent factors, namely an intercept (ie,mean initial level of music prefer-ences) and 1 or more slope factors. Alinear slope indicates linear rate ofchange of music preferences, an addi-tional quadratic slope indicates curvi-linear change. The models describinglinear and quadratic changes can becompared to obtain the best-fittingmodel (for an introduction into thistechnique, see Duncan et al45). Genderdifferences in the development of mu-sical preferences were tested by con-straining the intercept and slopefactors to be equal for boys and girls. Asignificant worsening of the fit statistic(a higher x2 value) after introducingthis constraint indicates differenceseither in mean initial levels (ie, in-tercept) or in developmental change(ie, slope factors) between boys andgirls.

Second, we tested whether the initialmean level and the development of 11musical preferences related to de-linquency at age 12 and at age 16.This model is displayed in Fig 1. Inour model, we included repeatedmeasures for the music preference,the estimated latent growth factors ofthe music preference, and observedscores of delinquency at ages 12 and 16separately for each music genre. Weexamined associations between thelatent growth factors of the musicpreference at age 12 and age 16 de-linquency while controlling for tempo-ral stability of delinquency betweenages 12 and 16. Because the distribu-tion of delinquency was positivelyskewed (skewnessAge 12 = 5.24; skew-nessAge 16 = 3.40), the normality as-sumption was violated. Therefore,robust Maximum Likelihood estimationwas used in the analyses.46 Given thatour preliminary analyses revealed nosystematic gender differences in the

association between music and de-linquency, we analyzed boys and girlstogether. Mean gender differences indelinquency and in the growth curve ofmusic genre preferences were cor-rected by regressing these variables onadolescent gender. Likewise, to correctfor school commitment, educationallevel, and adolescent personality type,growth factors of music preferencesand observed scores of delinquencywere regressed on these covariates.

Overall, 13.6% of the cases for de-linquency at age 12weremissing. Forallother variables, the percentage ofmissing responses was below 5.2%;75.4%of therespondentshadnomissingvalues across 4 measurements. More-over, the pattern of missing data wascompletely random; therefore, we in-cluded respondents with missing casesin our model estimations using Full In-formation Maximum Likelihood.

RESULTS

Mean Level Development of MusicalPreferences

Based on the observed values in Table 1,Table 2 shows the estimated values forthe intercept and slopes of the growthfunction. For each music preference,we tested whether it developed ina linear or nonlinear fashion. Non-linear models, with added quadraticslope factors in addition to interceptsand linear slope factors, had superiorfit compared with linear models (allDx2. 10.18, df = 4, all P, .03). Figure 2displays these estimated mean de-velopmental changes of music prefer-ences. The average preference for chartpop and trance declined linearly acrossadolescence, as indicated by a negativesignificant linear slope and no quadraticslope. In contrast, a significant increasein the preference for classical music,jazz, and techno/hardhouse music wasfound in middle to late adolescence, butnot in early to middle adolescence (in-dicated by significant positive quadratic

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growth). Preferences for R&B, hip-hop,rock, metal, gothic, and punk music didnot change significantly (ie, absence ofsignificant linear and quadratic growth).

Gender Differences in Developmentof Music Genre Preferences

On average, girls reported a higherinitial preference for chart pop, R&B,and jazz compared with boys. Boys,

compared with girls, reported a higherpreference for hip-hop, metal, gothic,punk, and trance. No significant genderdifferences were found in the initialpreference for rock, techno/hardhouse,and classical music. Significant genderdifferences in the development of musicpreferences were found only for gothicmusic and rock. On average, boysreported a significant decrease in their

preference for rock and gothic music,whereas girls showed no significantchange in their preference.

Music Genre Preference andAssociations With MinorDelinquency

As an initial test of MMT, we examinedbivariate correlations between musicpreferences and delinquency. Table 3shows that 12-year-old adolescentswith relatively strong preferences forhip-hop, metal, gothic, punk, trance, ortechno/hardhouse scored relativelyhigh on delinquency at age 12 (r be-tween 0.13 and 0.25), as well as ondelinquency at age 16 (r over this 4-year interval ranged from 0.16 to 0.31).Adolescents liking rock music at age 12also scored higher on delinquency atage 16 (r = 0.21). Strikingly, correlationsbetween age 12 music preferences andage 16 delinquency over a 4-year in-terval were equally strong or strongercomparedwith concurrent associations

FIGURE 1Structural equation model to test associations between growth factors that indicate initial levels and change in music style preferences and age 12/age 16delinquency, while controlling for adolescent gender, school commitment, educational level, and adolescent personality type.

TABLE 1 Descriptive Statistics of the Variables Under Study

Variable Age 12 Age 14 Age 15 Age 16

Mean SD Mean SD Mean SD Mean SD

Chart pop 4.12 0.96 3.93 1.13 3.74 1.14 3.68 1.15R&B 3.51 1.20 3.42 1.26 3.45 1.27 3.27 1.29Hip-hop 3.27 1.26 3.38 1.35 3.33 1.37 3.26 1.37Rock 2.85 1.16 2.85 1.41 2.80 1.41 2.85 1.49Metal 2.25 1.28 2.19 1.37 2.11 1.40 2.06 1.36Gothic 2.05 0.99 1.93 1.17 1.78 1.12 1.68 1.00Punk 1.90 1.05 2.08 1.27 2.00 1.30 2.05 1.33Trance 3.31 1.26 2.94 1.40 2.80 1.34 2.77 1.30Techno/Hardhouse 1.68 0.88 1.70 1.03 1.83 1.20 1.98 1.26Classic 2.06 1.07 2.06 1.01 2.22 1.08 2.38 1.12Jazz 2.65 1.15 2.34 1.12 2.49 1.18 2.54 1.18Delinquency 1.14 0.33 — — — — 1.12 0.27— , not included in the study.


between these music preferences atage 12 and delinquency at age 12 (rbetween 0.12 and 0.25), and age 16 anddelinquency at age 16 (r between –0.05and 0.26), and compared with 4-yearstability of delinquency (r = 0.17).

Althoughsomemusic preferenceswerepositively associated with delinquency,liking jazz at age 12 correlated nega-tively with delinquency (r = –0.12), butdid not relate to age 16 delinquency.Overall, earlier delinquency did not in-

dicate later music preferences; that is,levels of delinquency at age 12 did notcorrelate with music genre prefer-ences at age 16, with the exception ofpreference for classical music at age16 (r = –0.17). The overall pattern ofcorrelations thus supports MMT: earlymusic choice indicates later problembehavior and not the other way around.

In a more stringent test of MMT, weexamined whether early preferencesfor loud, rebellious music, but not in-creasing tendencies to listen to thesetypes of music, would be associatedwith higher levels of delinquency. Thatis, we tested whether an individual’slevel of delinquency at age 12 and age16 would be associated with initiallevels (reflected in intercept) but notwith mean-level change (reflected inlinear and quadratic slope) of musicpreferences. In this model, we also cor-rected for gender differences, potentialconfounding variables, including edu-cational levels and school commitment,

TABLE 2 Development of Musical Preferences

Music Style Mean Growth Factors

Intercept Linear Slope Quadratic Slope

Chart pop 4.12a –0.12* 0.00R&B 3.50a 0.03 –0.02Hip-hop 3.27b 0.10 –0.03Rock 2.86 –0.04a 0.01a

Metal 2.26b –0.04 0.00Gothic 2.06b –0.06a –0.01b

Punk 1.90b 0.09 –0.01Trance 3.31b –0.25** 0.03Techno/Hardhouse 1.68 –0.04 0.03*Classic 2.06 –0.06 0.04**Jazz 2.65a –0.22** 0.05**

Development of music style preference is expressed in 3 growth factors: Intercept (ie, mean initial level), Linear Slope (ie,linear increase or decrease), and Quadratic Slope (ie, curvature). All 9 models had adequate model fit: x2 (2) , 4.83;Comparative Fit Index . 0.99; Tucker-Lewis Index . 0.97; Root Mean Square Error of Approximation , 0.07.a Girls score significantly higher than boys on this growth factor.b Boys score significantly higher than girls on this growth factor. These developmental changes are graphically displayed inFig1.* P , .05.** P , .001.

FIGURE 2Estimated mean development of 11 music style preferences between ages 12 and 16 for the whole sample of adolescents.

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and adolescent personality type. Theresults of these final structural equa-tion models are displayed in Table 4.(The results of models in which thesecovariates were omitted showed iden-tical results and can be obtained fromthe authors.)

Consistent with correlational analysis,and in support of MMT, the initial meanlevels of music genre preferencesclearly related to themean levels of age12 and age 16 delinquency in thestructural equation model. More spe-cifically, the results indicated positiveassociations of initial preference forhip-hop, metal, gothic, and trance withage 12 and age 16 delinquencies.Preferences for R&B, rock, punk, andtechno were not associated with age 12delinquency, but they indicated higherlevels of age 16 delinquency. Again,mean initial levels of music prefer-ences were equally strong or morestrongly associated with age 16 de-linquency rather than with age 12 de-linquency. Interestingly, and furthersupporting MMT, the associations be-tween music preference at age 12 andage 16 delinquency ranged from 0.20 to0.46, indicating stronger relations thanthe bivariate association (ie, 4-yearstability) between age 12 delinquencyand age 16 delinquency (b = 0.04, P.

.05). This suggests that music prefer-ence is a better predictor of later de-linquency than early delinquency.

Initial preference for jazz or chart popdid not predict engagement in de-linquency concurrently (age 12) orprospectively (age 16), andpreferencesfor classicalmusic related negatively todelinquency at age 12.

Consistent with MMT, developmentalchanges in music genre preferencesdid not relate to delinquency at age 16,except for a weak but significant link(–0.20) between smaller linear increasesin R&B preferences and lower levels ofdelinquency at age 16. Thus, individualsshowing stronger increases in loud,rebellious music were not more de-linquent at age 16, as indicated by thenonsignificant associations betweenmusic-slope coefficients and age 16 de-linquency in Table 4. Finally, associationswere found between lower schoolcommitment and higher levels of de-linquency at age 16. Resilient adoles-cents tended to show lower levels ofdelinquency at age 12 compared withother personality types. Boys, comparedwith girls, scored higher on delinquencyat both ages and had stronger prefer-ences for louder music (not shown inTable 4). It is important to note that evenwhen considering the potential con-

founders, associations between musicpreferences and minor delinquencyremained.

DISCUSSION

This study is the first to provide evi-dence that an early preference fordifferent types of noisy, rebellious,nonmainstream music genres is astrong predictor of concurrent andlater minor delinquency. Early pref-erences are more important pre-dictors of later delinquency comparedwith developing preferences for de-viant music (ie, increases in liking ofnonmainstream music across ado-lescence did not indicate more de-linquency at age 16). Specifically,adolescents with a strong early pref-erence for music types that have beenlabeled as deviant (hip-hop, heavymetal, gothic, punk, and techno/hardhouse) were more engaged inminor delinquency in late adolescence.Moreover, preferences for music typesthat have been labeled as mainstream(R&B, rock, and trance), also predicteddeviant behavior. Two highly intriguingresults emerged. Longitudinal associa-tions betweenmusic preferences at age12 and minor delinquencies at age 16were generally stronger compared withconcurrent associations betweenmusic

TABLE 3 Bivariate Correlations Between Study Variables

1 2 3 4 5 6 7 8 9 10 11 12 13

1. Chart pop 0.55** 0.47** –0.28** –0.54** –0.29** –0.34** 0.23** 0.06 –0.13* 0.01 –0.05 –0.112. R&B 0.44** 0.67** –0.26** –0.39** –0.21** –0.27** 0.15* 0.01 –0.13* 0.24** –0.05 0.003. Hip-hop 0.28** 0.55** –0.29** –0.34** –0.27** –0.15* 0.31** 0.27** –0.24** 0.14* 0.03 0.15*4. Rock 0.00 0.21** 0.21** 0.61** 0.43** 0.42** –0.18** –0.07 0.33** 0.20** 0.00 –0.055. Metal 0.00 0.23** 0.42** 0.59** 0.60** 0.64** –0.12* 0.12* 0.22** 0.10 0.06 0.16**6. Gothic –0.01 0.23** 0.26** 0.56** 0.69** 0.48** –0.16** 0.05 0.18** 0.10 0.01 0.067. Punk –0.04 0.09 0.25** 0.52** 0.68** 0.70** 0.09 0.32** 0.13* 0.05 0.06 0.14*8. Trance 0.21** 0.38** 0.31** 0.14* 0.34** 0.25** 0.24** 0.52** –0.16** –0.02 0.08 0.20**9. Techno/Hardhouse 0.17** 0.19** 0.26** 0.34** 0.44** 0.33** 0.50** 0.33** –0.15** –0.09 0.10 0.26**10. Classic –0.17** –0.19** –0.22** 0.01 –0.12* –0.09 –0.05 –0.26** –0.12* 0.40** –0.17** –0.17**11. Jazz 0.10 0.13* 0.11 0.18** 0.10 0.16** 0.14* 0.00 0.14* 0.32** –0.10 0.0312. Delinquency age 12 –0.03 0.01 0.16* 0.12 0.25** 0.19** 0.16** 0.19** 0.13* –0.11 –0.12* 0.17**13. Delinquency age 16 –0.07 0.09 0.16** 0.21** 0.29** 0.31** 0.27** 0.18** 0.20** –0.04 –0.06 0.17**

Below the diagonal, are presented the correlations between age 12 music preferences and delinquency at ages 12 and 16. Above the diagonal, are presented the correlations between age 16music preferences and delinquency at ages 12 and 16. Correlations with age 14 and age 15 music preferences can be obtained from the first author on request.* P , .05.** P , .01.


and minor delinquencies at both age 12and age 16. Next, the predictive value ofinitial music genre preferences in laterminor delinquency was stronger com-pared with the predictive value of de-linquency at age 12 in similar behaviorat age 16; hence, early adolescentmusicpreferences emerged as highly sensi-tive indicators of later problem behav-ior. Therefore, the results confirmed 1crucial element of MMT, which proposesthat early music preferencesmark laterproblem behavior.

Previous research has establisheda link between media preferences andexternalizing behaviors. In the seminalwork of Keith Roe26 and Jeffrey Arnett,25

media delinquency reflects actualalienation from social institutions,such as family and school, and heavyreliance on deviant peers as company.In addition, experimental work hasshown that exposure to deviant mediacan affect deviant behaviors. MMT isbuilt on these assumptions and moreprecisely pins down the temporal link

between music taste and problem be-havior. It furthermore provides a de-scription of a progression in whichearly adolescents with a propensity tolisten to loud, nonmainstream musiccongregate with peers with a similartaste. Music is the medium that sepa-rates mainstream youth from youngpeople who may more easily adoptnorm-breaking behaviors. In peergroups characterized by their deviantmusic taste, norm-breaking youth may“infect” their friends with their behav-iors. Individually heavy exposure todeviant media and deviant models mayaffect delinquent behavior directly. Fu-ture research should investigate indetail the exact set of mechanismsthrough which music preferences in-fluence problem behavior and estab-lish their relative strength.

Adolescent minor delinquency hasbeen characterized as an attempt toexplore personal and social normsand rules, and for most young people,this problem behavior is limited toadolescence.20 Future investigationsshould also discriminate betweendifferent youths. First, researchshould consider those who expresstheir liking of deviant media as part ofa longer chain of problem behaviorsthat persist throughout individuals’lifetimes. These include, for example,exhibiting oppositional or defiantbehavior in childhood, listening to“problem” music in early adoles-cence, or engaging in minor de-linquency in middle and lateadolescence that extends into per-sistent adult problem behavior. Sec-ond, research needs to considerother young people for whom listen-ing to music, which is often annoyingto grown-ups, is energizing, comfort-ing or simply fun, and functions sim-ilarly as adolescent-limited problembehavior; that is, as a test of personaland social limits.

TABLE 4 Associations Between Development of Music Style Preferences and AdolescentDelinquency at Age 12 and Age 16

Model Correlations Between Music and Delinquency

Growth Factors Age 12 Delinquency Age 16 Delinquency

Chart Intercept –0.01 –0.03Linear Slope –0.13** –0.09

Quadratic Slope 0.16** 0.08R&B Intercept 0.09 0.21*

Linear Slope –0.04 –0.20*Quadratic Slope 0.01 0.18

Hip-hop Intercept 0.21** 0.20*Linear Slope –0.10 0.03

Quadratic Slope 0.06 –0.01Rock Intercept 0.23 0.37**

Linear Slope 0.08 –0.09Quadratic Slope –0.15 –0.03

Metal Intercept 0.35** 0.36***Linear Slope –0.06 –0.15

Quadratic Slope –0.04 0.13Gothic Intercept 0.31* 0.46***

Linear Slope –0.10 –0.21Quadratic Slope 0.03 0.19

Punk Intercept 0.22 0.37**Linear Slope 0.16 0.01

Quadratic Slope –0.20* –0.04Trance Intercept 0.25*** 0.21**

Linear Slope –0.11* –0.10Quadratic Slope 0.06 0.10

Techno/Hardhouse Intercept 0.14 0.29**Linear Slope 0.09 –0.12

Quadratic Slope –0.11 0.16Classic Intercept –0.11* –0.01

Linear Slope –0.02 –0.26Quadratic Slope –0.02 0.15

Jazz Intercept –0.15 –0.00Linear Slope 0.12 –0.02

Quadratic Slope –0.09 0.07

Development of music style preference is expressed in 3 growth factors: Intercept (ie, mean initial level), Linear Slope (ie,linear increase or decrease), or Quadratic Slope (ie, curvature). A separate growth model per music genre was estimated.Values in the table are standardized bs, while controlling for adolescent gender, school commitment, educational level, andadolescent personality type. All models had adequate model fit: x2 (9) # 15.96; CFI $ 0.98; TLI $ 0.91; RMSEA # 0.05. Theassociation between age 12 and age 16 delinquency in these models was b = 0.04, P . .05.* P , .05.** P , .01.*** P , .001.

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