Introduction
Music is a highly significant and meaningful medium, particularly in adolescence. Compared to older people, adolescents and young adults attribute more importance to music, and listen to music more often and in a wider variety of contexts (Bonneville-Roussy et al.
2013). Particularly in adolescence, music is not only important for mood management, but also for identity and social identity development (North and Hargreaves
1999; North et al.
2000). Music, its lyrics and visuals on TV, and the internet can be defining elements in the development of adolescent identity and social identity, particularly among those adolescents that are highly involved in music (North et al.
2000; Ter Bogt et al.
2010). Empirical evidence confirms that music is a factor in the formation of friendships, peer groups and peer culture (Selfhout et al.
2009; Steglich et al.
2006). Not only has music preference been linked to selecting friends with a similar music taste, particular preferences for several types of music have also been linked to the development of externalizing behavior. However, the impact of friends’ externalizing behavior on the link between music preference and externalizing behavior remains understudied.
Several types of music preference have been linked to externalizing behavior. For example, a preference for rock music, such as heavy metal, has been linked to externalizing behavior (e.g., Arnett
1996, Mulder et al.
2007; North and Hargreaves
2007; Selfhout et al.
2008; Ter Bogt et al.
2012; Tanner et al.
2008, Weinstein
1991). Similarly, a preference for urban music, such as rap or hip-hop, has been associated with externalizing behavior (Miranda and Claes
2004; Mulder et al.
2007; North and Hargreaves
2007; Selfhout et al.
2008; Tanner et al.
2008; Ter Bogt et al.
2012). Moreover, in ten countries across Europe a preference for dance music emerged as the most potent musical indicator for externalizing behaviors such as substance use (Ter Bogt et al.
2012). This latter study also indicates that currently, dance music was most consistently associated with several types of externalizing behavior (Ter Bogt et al.
2012).
In their Music Marker Theory, Ter Bogt et al. (
2013) conceptualize the mechanisms through which music preferences translate into externalizing behavior. A fundamental hypothesis within Music Marker Theory states that it is not primarily the music itself or its lyrics that promote adolescent externalizing behavior. Instead, music preferences may work as a badge (Frith
1981), communicating values, attitudes and opinions. Adolescents are sensitive to the images that they themselves and their peers project and hold normative expectations about the characteristics of fans of particular musical styles (North and Hargreaves
1999; Rentfrow and Gosling
2006). Through showing their badge, adolescents identify themselves as belonging to or desiring to belong to specific peer groups and they may be drawn to other youth with similar taste. As such, peer involvement is thought to mediate between music and externalizing behavior. Through music, adolescents are drawn to specific crowds varying in externalizing behavior, which may influence their behaviors positively or negatively. In particular, listening to music types such as rock, urban, or dance music, is expected to lead to befriending others with similar music tastes. Among such friends, in turn, externalizing behavior is expected to occur more frequently and escalate more quickly (see Ter Bogt et al.
2013).
In support of the Music Marker Theory, several studies suggest that music preference plays a central role in friendship formation. From the seventies onward, a series of ethnographic studies among youth involved in sub-cultures revealed the central role of music in the structuring of peer groups or scenes (e.g., Willis
1978; Hebdige
1979; Bennett
2000,
2004). Indeed, similarity in music preferences has been shown to increase the likelihood of friendship (Frith
1981, Steglich et al.
2006). Selfhout and colleagues (
2009) have shown that, over time, among stable friends there is high similarity in liking rock (divergent types of rock music), urban (i.e., Hip hop, R&B and reggae), pop/dance (mainstream music and the most popular forms of electronic dance music) and highbrow music (classical music and jazz). Furthermore, the study indicated that future friendships were created based on similarity in music preference. Thus, preferences for specific genres seem to indicate friendship similarity selection in early adolescence.
However, a proper test of the Music Marker Theory should control for effects of friends’ externalizing behavior. Indeed, like music preference, externalizing behavior has been shown to be important for both friendship creation and further development of externalizing behavior (see Moffitt
1993; Moffitt and Caspi
2001; Veenstra et al.
2013). Moreover, externalizing behavior itself might work as a badge, portraying a mature status among peers (Moffitt
1993). Therefore, it is important to take the effects of friends’ externalizing behavior into account when studying how music preference impacts friendship selection and the development of externalizing behavior.
To study the co-development of friendship and (externalizing) behavior, Stochastic Actor-Based Modeling (SABM) has been developed. Such modeling allows to simultaneously study both friendship similarity selection and influence processes (for an overview see Veenstra et al.
2013). Similarity selection takes place when adolescents select their friends based on similarities in behavior. Friendship influence processes take place when adolescents become more similar to their friends over time. It is important to disentangle these processes as they both lead to the same outcome: friends are similar to one another. Moreover, SABM controls for the increased likelihood of adolescents to reciprocate friendship, to become friends with classmates, or to become friends with their friends’ friends.
To our knowledge, only one study has simultaneously investigated the role of music preference and externalizing behavior in friendship formation and the development of externalizing behavior. Illustrating their Stochastic Actor-Based Modeling approach, Steglich et al. (
2006) studied 129 adolescents and showed that, while taking friendship selection based on alcohol use into consideration, adolescents select their friends based on a similarity in classical music preference but not based on similarity in techno or rock music preference. Controlling for friendship selection based on similarity in music preference and the positive effects of adolescents’ friends’ alcohol use, the researchers did not find any effects for techno, rock, or classical music on the development of alcohol consumption.
The Current Study
This study will investigate assumptions of the Music Marker Theory (Ter Bogt et al.
2013) that adolescents are likely to select friends based on similarity in music preference and that especially rock, urban, and dance music preferences are predictive of development of externalizing behavior. Listening to music types such as rock, urban, or dance music is expected to lead to befriending others with the same music preference and externalizing behavior is expected to occur more frequently among such friends, and as such, music preference may work as a badge, communicating values, attitudes and opinions (Frith
1981). Therefore, it was expected that adolescents who prefer rock, urban, or dance music are more likely to develop externalizing behavior. Most importantly however, since externalizing behavior is known to affect friendship selection and friends’ externalizing behavior is known to affect the development of externalizing behavior (e.g., Veenstra et al.
2013), this will be controlled for. Two hypotheses were tested. First, adolescents were expected to select friends based both on a similarity in externalizing behavior and music genre preference. Second, a preference for rock, urban, or dance, music types was expected to predict the development of externalizing behavior, even when taking friends’ influence effects on externalizing behavior into account.
Results
Descriptive Statistics
Over the whole sample, there were significant and positive correlations (p’s < 0.01) between preferences for dance (r = 0.24) and urban (r = 0.09) music, and externalizing behavior. The correlations for highbrow (r = −0.10) and popular (r = −0.09) music with externalizing behavior were negative and significant (p’s < 0.01). A preference for rock music (r = 0.03) was not correlated with engagement in externalizing behavior.
Table
2 lists descriptive statistics for each of the four networks examined in this study. Results at Time 1 suggested that all four networks did not differ in age, and that there were only some small differences in gender distribution, and externalizing behavior. Table
2 also includes network characteristics for each cohort. Per network and measurement moment, there were between 1 and 5% absent participants during the assessments. The Jaccard index indicates the relative stability of each friendship network over time. The Jaccard indices were between 0.44 and 0.48, well within the desired range for longitudinal social network analyses (Veenstra et al.
2013). This indicates that friendships are relatively stable, while some changes in friendships occur. Therefore, it is possible to study changes in both friendship connections (making and losing friends) and to study changes in behavior among stable friends.
Table 2
Descriptive statistics of friendship networks for school 1 (cohort 1 N = 432, cohort 2 N = 390) and school 2 (cohort 1 N = 186, cohort 2 N = 136), Time 1–Time 3
Age
| | | | | | | | |
Time 1 | 12.65 | (0.43) | 12.65 | (0.43) | 12.66 | (0.48) | 12.70 | (0.68) |
% boys
| | | | | | | | |
Time 1* | 0.50a
| (0.50) | 0.48ab
| (0.50) | 0.47ab
| (0.50) | 0.61b
| (0.49) |
Externalizing behavior
| | | | | | | | |
Time 1* | 0.36a
| (0.69) | 0.47b
| (0.82) | 0.29a
| (0.60) | 0.34ab
| (0.56) |
Time 2 | 0.39 | (0.68) | 0.42 | (0.75) | 0.31 | (0.66) | 0.41 | (0.69) |
Time 3 | 0.44 | (0.78) | 0.51 | (0.81) | 0.42 | (0.71) | 0.47 | (0.76) |
Rock preference
| | | | | | | | |
Time 1* | 0.16a
| (1.07) | −0.06b
| (0.93) | −0.07b
| (1.06) | −0.27b
| (0.77) |
Dance preference
| | | | | | | | |
Time 1* | −0.16a
| (0.94) | 0.06b
| (1.02) | 0.14b
| (1.08) | 0.16b
| (0.95) |
Highbrow preference
| | | | | | | | |
Time 1 | 0.02 | (1.07) | −0.08 | (0.92) | 0.15 | (1.03) | −0.03 | (0.91) |
Popular preference
| | | | | | | | |
Time 1 | 0.02 | (1.02) | 0.00 | (1.00) | −0.04 | (1.01) | 0.00 | (0.94) |
Urban preference
| | | | | | | | |
Time 1* | −0.07a
| (0.98) | −0.07a
| (0.96) | 0.27b
| (1.10) | 0.06ab
| (0.99) |
Missing fraction
| | | | | | | | |
Time 1 | 0.01 | | 0.03 | | 0.05 | | 0.01 | |
Time 2 | 0.01 | | 0.04 | | 0.03 | | 0.01 | |
Time 3 | 0.03 | | 0.03 | | 0.02 | | 0.02 | |
Jaccard index
| | | | | | | | |
Time 1–Time 2 | 0.46 | | 0.47 | | 0.44 | | 0.45 | |
Time 2–Time 3 | 0.46 | | 0.48 | | 0.44 | | 0.45 | |
SIENA Estimates of Friends’ Influence
The outcomes of the meta-analysis of SIENA analyses of four networks are shown in Table
3 for both analyses. First, the structural network effects model the friendship network structure, and optimize the goodness of fit of the networks. It is important to model these effects as they help explain creation and maintenance of friendship. These effects were similar for both analyses and will therefore be explained once. There was a negative density effect (
1A), indicating that participants are likely to be selective in their friendship nominations. There was a positive reciprocity effect (
1B), indicating that participants are likely to reciprocate friendship nominations. There was a positive transitive triplet effect (
1C), which shows that participants are likely to be friends with the friends of their friends. Furthermore, triads were less likely to have reciprocated ties than dyads, which is an indication of hierarchy in the network, as shown by a negative transitive reciprocated triplet effect (
1D). Moreover, there was a negative three-cycle effect (
1E). In combination with the positive transitive triplet effect this indicated that there was hierarchy in the networks (within triads few participants receive many nominations, while many participants receive fewer nominations). Particularly in period 2, between Time 2 and Time 3, we found a negative indegree—popularity effect (
1F). This indicated that those with many friends were less likely to increase their number of friends. The negative effects of indegree—activity (
1G) indicated that those participants who received many friendship nominations were less likely to send out nominations themselves. The outdegree activity (
1H) was positive, indicating that those with a higher outdegree were more likely to increase the number of friends they select.
Table 3
Estimates of meta-analysis on four investigating networks similarity selection and influence effects based on music preference and externalizing behavior, in friendship networks at Time 1, 2, and 3
Network dynamics
| | | | | |
1Outdegree (density)1A
| Period 1 | −2.17** | (0.15) | −2.25** | (0.12) |
| Period 2 | 0.09 | (0.12) | 0.11 | (0.12) |
Reciprocity1B
| | 2.58** | (0.11) | 2.57** | (0.12) |
Transitive triplets1C
| | 0.52** | (0.02) | 0.51** | (0.02) |
Transitive reciprocated triplets1D
| | −0.43** | (0.04) | −0.43** | (0.04) |
3-cycles1E
| | −0.06* | (0.02) | −0.06* | (0.02) |
Indegree—popularity (sqrt)1F
| Period 1 | 0.05 | (0.06) | 0.05 | (0.06) |
| Period 2 | −0.13* | (0.04) | −0.14* | (0.04) |
Indegree—activity (sqrt)1G
| | −1.03** | (0.09) | −0.99** | (0.09) |
Outdegree—activity (sqrt)1H
| | 0.15* | (0.04) | 0.16* | (0.04) |
2Sex received2A
| | −0.05 | (0.07) | −0.05 | (0.07) |
Sex sent2B
| | −0.11 | (0.11) | −0.02 | (0.03) |
Sex similarity selection2C
| | 0.69** | (0.06) | 0.69** | (0.05) |
Class similarity selection2C
| | 0.75** | (0.06) | 0.76** | (0.06) |
Location similarity selection2C
| | 0.39 | (0.03) | 0.38 | (0.04) |
Rock received2A
| | −0.04 | (0.02) | −0.04 | (0.02) |
Rock sent2B
| | −0.03 | (0.02) | −0.02 | (0.02) |
Rock similarity selection2C
| | −0.20 | (0.11) | −0.23 | (0.11) |
Dance received2A
| | −0.02 | (0.03) | −0.02 | (0.03) |
Dance sent2B
| | 0.05 | (0.04) | 0.03 | (0.03) |
Dance similarity selection2C
| | 0.25 | (0.14) | 0.25 | (0.13) |
Highbrow received2A
| | 0.05 | (0.02) | 0.05 | (0.02) |
Highbrow sent2B
| | 0.03 | (0.05) | 0.04 | (0.05) |
Highbrow similarity selection2C
| | 0.48* | (0.15) | 0.52* | (0.14) |
Popular received2A
| | −0.01 | (0.02) | 0.00 | (0.02) |
Popular sent2B
| | 0.00 | (0.03) | 0.01 | (0.03) |
Popular similarity selection2C
| | 0.00 | (0.05) | −0.02 | (0.05) |
Urban received2A
| | 0.00 | (0.02) | 0.00 | (0.02) |
Urban sent2B
| | 0.07* | (0.01) | 0.07* | (0.01) |
Urban similarity selection2C
| | 0.34* | (0.11) | 0.34 | (0.11) |
Externalizing behavior received 2A
| | | | 0.12 | (0.04) |
Externalizing behavior sent2B
| | | | 0.21* | (0.05) |
Externalizing behavior similarity selection2C
| | | | 0.68* | (0.18) |
Behavior dynamics
|
3Externalizing behavior change period 13A
| | 1.38** | (0.13) | 1.43** | (0.12) |
Externalizing behavior change period 23A
| | 1.51** | (0.14) | 1.54** | (0.15) |
Externalizing behavior change linear3A
| | −1.27** | (0.07) | −1.26** | (0.07) |
Externalizing behavior change quadratic3A
| | 0.32** | (0.04) | 0.21* | (0.05) |
Effect from r\k on externalizing behavior3B
| | 0.02 | (0.04) | 0.03 | (0.05) |
Effect from dance on externalizing behavior3B
| | 0.19* | (0.04) | 0.16* | (0.05) |
Effect from highbrow on externalizing behavior3B
| | −0.12 | (0.05) | −0.13 | (0.06) |
Effect from popular on externalizing behavior3B
| | −0.11 | (0.05) | −0.09 | (0.05) |
Effect from urban on externalizing behavior3B
| | 0.11 | (0.04) | 0.13 | (0.05) |
Externalizing behavior influence average alter3C
| | | | 1.00* | (0.18) |
Second, to examine the first hypotheses that adolescents select their friends both on music preference and on externalizing behavior, the similarity selection effects were estimated for both analyses (Table
3). These effects indicate how adolescents create and maintain friendship, based on several characteristics such as gender or physical proximity (i.e., being in the same classroom). It is important to take such selection effects into account, as they help explain why friends are similar to one another. Three types of effects are important for this part of the model. First, received (or alter) effects (
2A); which model whether participants are nominated as friends more frequently based on certain characteristics. Second, sent (or ego) effects (
2B); which model whether participants with certain characteristics are more likely to nominate friends. Third, similarity selection effects (
2C); which model whether participants are likely to select friends based on similarity in certain characteristics. The main effects of the control variables were generally consistent with prior research. While controlling for the number of friends adolescents select (sent effects) and the number of times they are selected as friends (received effects), participants’ selection of friends was significantly associated with similarity in gender and class. Therefore, participants were more likely to befriend peers with the same gender, and those who were part of the same class in school.
Partial support was found for the first hypothesis that friendship selection is based on music preferences. These effects indicate whether participants were more likely to befriend others who are similar to them in music preference or externalizing behavior. In the first analysis, without taking effects of friends’ externalizing behavior into account, participants were likely to select their friends based on a similarity in both highbrow and urban music preference (positive highbrow and urban similarity selection). Therefore, adolescents who had a preference for highbrow or urban music were more likely to select friends who also had a preference for highbrow or urban music, respectively. The second analysis also took friendship selection based on externalizing behavior into account. Participants were likely to select friends based on a similarity in externalizing behavior. While controlling for this friendship selection based on externalizing behavior (positive externalizing behavior similarity effect), similarity selection based on urban music became non-significant (p = 0.06), but the effect of friendship selection based on similarity in preferences of highbrow music remained significant (positive highbrow similarity selection effect). There was no selection based on similarity in other types of music.
Third, to enable a test of the second hypothesis, the change in externalizing behavior was estimated (Table
3). Behavior dynamics (i.e., changes in behavior) model the change in externalizing behavior. The first effects (
3A) estimate the change of participants’ externalizing behavior. There was a negative linear effect, and a positive quadratic effect for the development of externalizing behavior. The combination of a negative linear effect and a positive quadratic effect indicates that externalizing behavior has a tendency to escalate once it develops: participants were likely to either engage in no externalizing behavior, or to engage in multiple externalizing behaviors.
To test the second hypothesis that rock, urban, and dance music preference would be associated with an increased likelihood to develop externalizing behavior (3B), effects from music preference on the development of externalizing behavior were tested. In the first analysis, without taking effects of friends’ externalizing behavior into account, music preference in rock, highbrow, popular, or urban music did not affect the development of externalizing behavior (non-significant effects from these types of music preference on externalizing behavior). However, preference for dance music was positively associated with the development of externalizing behavior. Thus, participants who had a preference for dance music were more likely to increase their externalizing behavior. In the second analysis, taking effects of friends’ externalizing behavior into account, participants were likely to be influenced by their friends’ externalizing behavior in the development of externalizing behavior (positive externalizing behavior average alter (3C)), and a preference for dance music still predicted an increase in externalizing behavior. This indicates that participants were likely to adapt their engagement in externalizing behavior to become more similar to their friends, and that there is an additional likelihood for participants who listen to dance music to develop externalizing behavior.
In sum, in partial support of the first hypothesis, adolescents were likely to select friends based both on music preference and on externalizing behavior. However, the selection of music preference was limited to a similarity in highbrow music, when taking selection based on externalizing behavior into account. Furthermore, partially supporting the second hypotheses, above and beyond the effects of friends’ externalizing behavior, adolescents who listen to dance music were likely to develop externalizing behavior. No friendship influence effects were found for preferences for rock or urban music.
Discussion
Externalizing behavior is expected to occur more frequently and escalate more quickly among adolescents who prefer rock, urban, or dance music. According to the Music Marker Theory (Ter Bogt et al.
2013), such music preferences might work as a badge, communicating values, attitudes, and opinions (Frith
1981). Peer involvement is expected to mediate between music preference and externalizing behavior. Although similarity in music preference has been associated with friendship (e.g., Selfhout et al.
2009; Steglich et al.
2006), a proper test of the Music Marker Theory should control for the effects of friends’ externalizing behavior. Moreover, effects of friendship selection (adolescents befriend similar others) and influence (adolescents become similar to their friends) have to be disentangled. Therefore, this study set out to investigate whether (1) adolescents select friends based on music preference and/or on a similarity in externalizing behavior, and whether (2) adolescents’ preference for rock, urban, or dance music adds to the development of externalizing behavior beyond the influence effects of friends’ externalizing behavior. The results were based on two analyses, one excluding and one including the effects of externalizing behavior on friendship selection and on the development of externalizing behavior. The results provide partial support for both hypotheses. Adolescents were likely to select friends based on similarity in music preference, both on a preference for urban and on preference for highbrow music in the model excluding effects of friendship selection based on externalizing behavior. However, in the model taking similarity selection based on externalizing behavior into account, friendships selection was only based on a similarity in highbrow music preference. Moreover, irrespective of friends’ externalizing behavior, dance music was indicative for a faster increase in externalizing behavior. This study provides some support for claims by the Music Marker Theory (Ter Bogt et al.
2013) that music preference for certain music styles is an important indicator for externalizing behavior development, but this was limited to dance music only. Both a preference for dance music and friends who engage in externalizing behavior may influence adolescents’ engagement in externalizing behavior.
Although it was expected that a preference for rock, urban, and dance music would all be associated with externalizing behavior development, only dance music significantly predicted the development of externalizing behavior. Interestingly, dance music has recently also been specifically identified as most consistently associated with several types of externalizing behavior in Europe (Ter Bogt et al.
2012). Therefore, our findings support the idea that dance music, rather than rock or urban music, is currently the music type most associated with externalizing behavior. Moreover, the finding that dance music predicts future externalizing behavior also adds to the claim that music preference works through a badge rather than directly through the music itself or the lyrics. Dance music’s lyrics and visuals on TV are much less associated with externalizing behavior, compared to for example, rock or urban music. Thus, the values, attitudes, and opinions transmitted through dance music might be important especially to adolescents.
This study took into account that adolescents are likely to befriend peers who are similar in music preference and in externalizing behavior and controlled for the effect of friends’ externalizing behavior on participants’ own externalizing behavior. Even while controlling for these alternative explanations of the development of externalizing behavior, music preference predicted future externalizing behavior. This is in line with the findings of Ter Bogt and colleagues (
2013). However, this is in contrast to the study of Steglich et al. (
2006) who did not find such influence effects from music preference while investigating alcohol use among 129 adolescents of the age of 13 year, using three yearly assessments. This may possibly be because Steglich et al. (
2006) focused on alcohol use rather than a more global construct of externalizing behavior. Furthermore, there may have been too few participants, other music preferences such as hip-hop or RnB could have been more important at the time of the study (data was collected starting 1995), or measurement moments could have been too far apart. During secondary school, friends may change their classrooms from one year to another.
Friendship selection was not based on similarity in rock, dance, popular, or urban music preferences when taking friendship selection based on externalizing behavior into account. Urban music, however, was associated with friendship selection if friendship selection on externalizing behavior was not taken into account. Thus, friendship selection based on externalizing behavior partially explains friendship selection based on a preference for urban music. In both models with and without externalizing behavior, friendship similarity selection was based on externalizing behavior and on a preference for highbrow music. The selection effect based on highbrow music is in line with the finding of Steglich and colleagues (
2006) and might indicate that there is a strong basis for early adolescents to select one another on a similarity in preference for highbrow music. When looking at these findings from the perspective of music and externalizing behavior working as badges (Frith
1981), it is possible that externalizing behavior takes over the role of badge that urban music would otherwise have. Possibly the badge of engagement in externalizing behavior, which Moffitt (
1993) expects to signal social maturity, is more prominent than the musical badge in early adolescence. This would help explain why similarity selection based on a preference for urban music lost its significance when taking friendship selection based on externalizing behavior into account, as urban music preference was positively associated with externalizing behavior. Highbrow music was negatively associated with externalizing behavior, which may help explain why, next to externalizing behavior, adolescents select friends with a similar preference for highbrow music.
It would be interesting to further investigate these friendship similarity selection processes, and their underlying motivations. For example, comparing which roles group formation based on music preference and externalizing behavior fulfill would allow a better understanding of these underlying motivations. Both externalizing behavior and urban music might serve to signal friendship selection based on a more mature status or badge, but there might also be different reasons for such friendship selection. For example, in the case of highbrow music preference, music preference might help adolescents obtain a different social goal. Future studies could further investigate these mechanisms.
The main strength of this longitudinal network study is that both music preference and externalizing behavior were estimated while taking friendship, embeddedness of friendship in networks, and changes of friendship and externalizing behavior into account. This was done every 3 months after adolescents entered a new network of friends; thus the effects found in this study are likely based on current music preference and externalizing behavior rather than pre-existing friendships. Therefore, this provides a stringent test of the assumption that music preference plays an important role explaining both friendship selection and the development of externalizing behavior during adolescence. Moreover, these analyses were done in two models: one with and one without the effects of externalizing behavior. A second strength of the current study is that we identified profiles of music preference, using principal component analyses. This allowed adolescents to have a profile of music preference, which is more informative compared to basing music preference solely on some exemplary items.
As any study, this study also has some limitations. One important limitation is that changes in music preference were not accounted for. It would be interesting to investigate how externalizing behavior and friendship affect changes in music preferences, and how these changes in turn impact externalizing behavior and friendship. Secondly, although friendship similarity selection was modeled, the Music Marker Theory might even better explain effects based on friendship groups or cliques, rather than individual friendships. Thirdly, this study focused on the occurrence of adolescents’ externalizing behaviors rather than the frequency with which adolescents engage in such behaviors. Future studies should investigate this frequency, perhaps during later years in adolescence when there is more engagement in externalizing behavior. In such a sample of late adolescents, it might also be possible to compare friendship influence processes with regard to different kinds of externalizing behaviors. Moreover, the current study focused on music preference and the influence of friends. Future studies should take other important aspects for the development of externalizing behavior into account, such as self-control (see Gottfredson and Hirschi
1990) or pubertal development (Dijkstra et al.
2015). With the complexity of these findings, future studies should aim to study the impact of musical preference on externalizing behavior in alternative ways. Comparing more detailed differences in music preference, for example differentiating between different types of dance music, might build on these findings and be a good start to further study how music is associated with externalizing problems.
Acknowledgements
We are grateful to all adolescents, their parents and teachers who participated in this research and to everyone who worked on this project and made it possible.