article review

Music Preference, Social Identity, and Self-Esteem

Author(s): Daniel Shepherd and Nicola Sigg

Source: Music Perception: An Interdisciplinary Journal , Vol. 32, No. 5 (June 2015), pp. 507-514

Published by: University of California Press

Stable URL: https://www.jstor.org/stable/10.1525/mp.2015.32.5.507

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MUS IC PREFERENCE, SO CIA L IDENTIT Y, AND SE L F-ESTEEM

DA NI E L SHEPHERD & NICOLA SIGG

Auckland University of Technology, Auckland, New Zealand.

SOCIAL IDENTITY THEORY POSITS THAT MEMBERSHIP

to social groups serves to enhance and maintain self- esteem. In young people music plays a prominent role in defining social identity, and so a relationship between music preference and self-esteem is expected, but is as yet unconfirmed by the literature. The objective of this study was to further examine the association between music preference and the self-esteem, and to apply social identity theory to differences in music prefer- ences and self-esteem. The present study measured self-esteem from university students (n ¼ 199) using Rosenberg’s (1965) self-esteem scale, and employed confirmatory factor analysis to derive a representative model of the self-esteem data. Music preference scores for clusters of music genres were found to significantly correlate with self-esteem. Furthermore, some mea- sures of group differentiation based on music prefer- ence were significantly associated with self-esteem, but the relationships differed depending on gender. Over- all, the results provided both support and challenges for social identity theory.

Received: April 11, 2014, accepted October 27, 2014.

Key words: music preference, self-esteem, music genres, social identity theory, Rosenberg self-esteem scale

M USIC PREFERENCE IS A WAY OF SIGNALING

social identity (Tarrant, North, & Hargreaves, 2001) and constitutes a window to an indivi-

dual’s identity (Steele & Brown, 1995). Self-esteem, a commonly measured construct in psychological research, can be influenced by social processes. Social identity theory (Tajfel, 1978) proposes that group mem- bership endows individuals with social identity, and that group identification (i.e., ingroup membership) strengthens and maintains self-esteem through ongoing positive evaluations of the ingroup. Furthermore, indi- viduals compare their ingroups to other groups (i.e., outgroups), and use the outcome of these comparisons to maintain positive social identity and self-esteem

through in-group favoritism, outgroup derogation, and positive distinction from the outgroup (Tarrant et al., 2001). For adolescents, and young adults especially, there is often genuine and meaningful categorization of ingroups and outgroups along the lines of music preference (North, Hargreaves, & O’Neill, 2000). Studies (e.g., Tarrant, 1999) and commentaries (e.g., Zillmann & Gan, 1997) have reinforced the notion that music pref- erence forms the dominant analysis when adolescents are making group comparisons, and hence music preference manifests a prominent dimension of adolescents’ social identity (Tarrant et al., 2001).

Though music has been coupled with well-being since ancient times, there is very little research on the topic (Laukka, 2007). This is regrettable, as many young peo- ple in modern society consider music to be essential to their well-being (Steele & Brown, 1995), and there is a growing concern that a preference for some music genres can negatively impact social behavior (Greite- meyer, 2009) and self-esteem (Baker & Bor, 2008). Some studies have touched on the association between self-esteem and music (e.g., North & Hargreaves, 1999; Tarrant et al., 2001), but few have directly examined the relationship between them. Tarrant and colleagues demonstrated that, for a sample of male adolescents, intergroup discrimination on the basis of music prefer- ence was related to self-esteem. They tested the self- esteem hypothesis (Abrams & Hogg, 1988), which was deduced from the central tenants of social identity the- ory, and suggests that intergroup discrimination and self-evaluation are intimately linked. The self-esteem hypothesis, which must be tested using a within- subjects design (Abrams & Hogg, 1988), consists of two directional hypotheses. First, that successful intergroup discrimination may lead to an increase in self-esteem and, second, low or threatened self-esteem may moti- vate increased intergroup discrimination. In support of the self-esteem hypothesis, Tarrant et al. (2001) reported that greater levels of discrimination and outgroup der- ogation were negatively associated with self-esteem, and that ingroup favoritism was positively associated with self-esteem. Furthermore, they found that ingroups were associated with positively evaluated music, and outgroups with negatively evaluated music. Therefore, social identity theory presents a useful framework for examining the relationship between self-esteem and

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Music Preference, Social Identity, and Self-Esteem 507

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music preference, the latter of which can be considered a component of an individual’s social identity (Tekman & Hortaçsu, 2002).

Indirect evidence that music is related to self-esteem comes from Tekman and Hortaçsu (2002), describing a music style (‘‘Arabesk’’) whose listeners were depicted by the study’s participants as alienated, pessimistic, defeated, and ‘‘ . . . without hope or power to control their lives.’’ (p. 283). In the most direct examination of the association between music preference and self- esteem, Rentfrow and Gosling (2003) failed to uncover significant correlations, implying that perceived self- worth has no effect on music preference, or vice versa. They used the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965), a scale purporting to measure a uni- dimensional conceptualization of self-esteem con- structed from more specific facets of self-evaluation. The factor structure of the RSES has come under much scrutiny (e.g., Baranik et al., 2008; Gray-Little, Williams, & Hancock, 1997), and commonly, a two-factor struc- ture is found. Depending on the sample, the two factors might reflect either positively (e.g., I take a positive atti- tude towards myself) and negatively (e.g., I certainly feel useless at times) worded items. Others suggest that the two factors manifest a fundamental dichotomy of self- competence/self-assessment (e.g., I am able to do things as well as most other people), reflecting an objective form of self-evaluation based on instrumental value, and self- liking/self-acceptance (e.g., At times I think I am no good at all), reflecting a more subjective form of self-evaluation based on intrinsic value (Tafarodi & Milne, 2002).

In addition to using the RSES, Rentfrow and Gosling (2003) also measured self-view, and reported significant correlations between self-view and music preference. Their self-view measure assessed participant’s self- reports of athletic prowess, intelligence, and physical attractiveness, all of which can be considered a form of either self-competence or self-liking. If self-competence and self-liking are dimensions of self-esteem (Tafarodi & Swann, 2001), then one would also expect a relationship between music preference and the RSES. That Rentfrow and Gosling failed to report a significant relationship between music preference and the RSES indicates that the operationalization of self-esteem should be carefully considered, and perhaps treated as a multidimensional construct such as that uncovered by Tafarodi and Swann (2001). Additionally, the importance of gender as a deter- minant of music preference has yet to be resolved in the literature. While some have emphasized substantial gen- der differences in music preference (Schwartz & Fouts, 2003), others (e.g., Tekman & Hortaçsu, 2002) have reported no effect of gender. For example, Rentfrow and

Gosling (2003) reported no differences between males and females when originally developing their four- factor music preference scale but, when updating their scale to a five-factor model, reported significant gender differences in preferences to specific pieces of music (Rentfrow, Goldberg, & Levitin, 2011).

The objectives of the present study were to examine the structure of the RSES, and then to use the RSES to test predictions of social identity theory. To this end the RSES will be factor-analyzed in order to derive a valid representation of self-esteem, where the emergence of self-liking and self-competency factors would support the analysis of Tafarodi and colleagues (2001, 2002). The most psychometrically sound representation of the RSES will then be related to music preference, and fur- thermore, to biases towards specific music genres. Social identity theory attempts to account for the association between self-esteem and intergroup discrimination by hypothesizing that stronger intergroup discrimination increases self-esteem by strengthening one’s sense of social identity. Specifically, when social identity is strongly coupled to a preferred social category (or sub- group), individuals tend to behave in a way that mini- mizes within-group differences (i.e., converge upon the group prototype) which, by association, induces positive self-evaluation. Consistent with social identity theory, individuals preferring particular music styles over others would be expected to identify with a particular subgroup based on music preference (i.e., higher ingroup bias and outgroup discrimination), and thus evaluate themselves more positively (i.e., have higher self-esteem). Further- more, because the effects of gender on the relationship between music preference and self-esteem have yet to be sufficiently examined, the data from males and females will be scrutinized independently.

Method

PARTICIPANTS

The participants were 199 New Zealand university stu- dents. The sample consisted of 199 students: 42 males (M¼ 18.7 years, SD¼ 3.16) and 157 females (M¼ 19.24 years, SD ¼ 3.61).

MEASURES

Two surveys were distributed, the RSES (Rosenberg, 1965), and the Short Test of Music Preference (STOMP: Rentfrow & Gosling, 2003). The RSES is a self-report inventory containing ten statements, each rated on a four-point Likert-type scale (0 ¼ ‘‘strongly disagree’’ to 3 ¼ ‘‘strongly agree’’). The ten ratings are then summed to provide a total score of self-esteem, ranging

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from 0 to 30, with a score of 15 or below indicating a low level of self-esteem (Rosenberg, 1965). When responding to the STOMP scale, participants were required to indicate, on a seven-point Likert-type scale, how much they enjoyed a particular music genre (1 ¼ ‘‘not at all’’ to 7 ¼ ‘‘very much’’). The genres covered by the STOMP are classical, jazz, blues, rock, heavy metal, country, pop, folk, alternative, religious, soundtracks, rap/hip-hop, soul/funk, and electric/dance.

PROCEDURE

The surveys were distributed during lecture time once the respondents were informed that participation was voluntary and anonymous, and that ethical approval had been sought and granted by the University’s Ethics Committee.

Results

Item responses were entered into SPSS, with negatively worded items being recoded in Microsoft Excel prior to analysis. All analyses were conducted in SPSS, with the exception of the confirmatory factor analyses, which were undertaken in LISREL 8.8.

SELF-ESTEEM (RSES)

The mean total RSES score was 19.38 (SD¼ 4.78, min¼ 10, max ¼ 30), and a Cronbach’s alpha (ac) of 0.86 was calculated. The average male (M ¼ 16.83, SD ¼ 4.38) and female (M¼ 17.81, SD¼ 4.24) scores did not differ significantly, t(197) ¼ �1.32, p ¼ .19. The RSES total scores for this study are not remarkable as norms typ- ically fall between 15 and 25 (Gazzaniga & Heatherton, 2006).

The dimensionality of the RSES was examined using confirmatory factor analysis (CFA). Three models were specified a priori: Model I) a one-factor model contain- ing all ten items of the RSES; Model II) a related two- factor model consisting of positively (items 1, 2, 4, 6, 7) and negatively (items 3, 5, 8, 9, 10) worded questions, and; Model III) a related two-factor model comprising self-competence (items 1, 2, 3, 4, 5) and self-liking (items 6, 7, 8, 9, 10) questions. Maximum likelihood estimation methods were employed to compare the fit of the models. Two goodness-of-fit indices, chi-square (�2) and the root-mean-square of approximation (RMSEA), are reported in Table 1 for the three models. The greater the �2 statistic and RMSEA value, the poorer the match between data and model. Of the three models, the related two-factor model dividing the RSES into self-liking and self-competence affords the best representation of factor structure, though both the

two-factor models provide a better fit than the one- factor model. A model with a greater number of para- meters may provide a superior fit over a model with fewer parameters if its functional form is representative of the process generating the empirical data or, of less utility, if the extra parameters are soaking up residual noise. If both models provide fits to the data that are not significantly different, then the simpler model should be retained in accordance with the principle of Occam’s razor. Because Model I is essentially a singly constrained version of Models II and III (Tafarodi & Milne, 2002), its goodness-of-fit can be compared to them using �2

difference tests. With an alpha level of .05, Model I provided a significantly worse fit than both Model II, �2

diff (1) ¼ 69.07, p < .001, and Model III, �2 diff (1) ¼

89.13, p < .001. Models II and III are not hierarchically related and so a �2 difference test cannot be performed to compare their fits. However, the �2 statistics and RMSEA values presented in Table 1 provide strong evi- dence that Model III better accounts for the covariation between the ten RSES items than Models I and II, and what is more, concurs with previous findings (Tafarodi & Swann, 2001) and is more theoretically interpretable.

MUSIC PREFERENCE (STOMP)

With reference to Rentfrow and Gosling’s (2003) genres, the same four factor solution was extracted using a prin- cipal components analysis. The correlation coefficient matrix for music genres was assessed for factorability by first examining the matrix for adequate associations between genres (Pearson’s r) and then by conducting a Kaiser-Meyer-Olkin (KMO) test (KMO ¼ .74) and a Bartlett’s test of sphericity, �2(153) ¼ 1389.50, p < .001. Satisfied that the matrix was factorable, a principal components analysis was performed to ascertain whether or not the 14 genres of music could be reduced into a smaller number of music domains. An initial unrotated solution indicated that four eigenvectors had eigenvalues greater than one, explaining 66.4% of the total variance. However, the extracted communality value for the ‘‘Religious’’ genre was deemed too low (¼ .13) to justify its inclusion in further analyses, and was removed. To increase the interpretably of the

TABLE 1. Goodness-of-fit Estimates for Three Models Subjected to a CFA

MODEL �2 df p-value RMSEA

Model I 219.33 35 < .001 .16 Model II 288.40 34 < .001 .16 Model III 130.20 34 < .001 .12

Music Preference, Social Identity, and Self-Esteem 509

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solution a direct oblimin rotation was undertaken and, since the correlations between the four extracted com- ponents were all less than .30, a varimax rotation was performed to achieve simple structure (see Table 2).

The four extracted factors were labelled as follows: 1) Energetic/Rhythmic (M¼ 4.03, SD ¼ 1.62, ac¼ .83); 2) Reflective/Complex (M ¼ 3.52, SD ¼ 1.34, ac ¼ .74); 3) Intense/Rebellious (M ¼ 3.76, SD ¼ 1.51, ac ¼ .81), and; 4) Upbeat/Conventional (M ¼ 4.18, SD ¼ 1.38, ac ¼ .68). A repeated-measures ANCOVA with the four music preference factors as the within-subjects factor, gender as the between-subjects factor, and age as a covariate, was performed. There were no main effects of preference, F(3, 597)¼ 1.62, p ¼ .19, or gender, F(1, 197) ¼ 0.22, p ¼ .64, no significant effect of age, F(1, 197) ¼ 2.26, p ¼ .14, but a significant interaction term between the music preference factors and gender was noted, F(3, 597) ¼ 3.65, p ¼ .013. Figure 1 displays mean preference score as a function of the music pref- erence factors for males and females. Subsequent post hoc analysis of simple effects showed significant differ- ences in mean scores across gender for both the Intense/ Rebellious (p¼ .008) and Upbeat/Conventional (p¼ .03) factors.

MUSIC PREFERENCE AND SELF-ESTEEM

Simple correlation analysis was performed to test for associations between the four STOMP music factors and summed items from the RSES: 1) all ten items; 2) five items corresponding to self-competence, and; 3) five items corresponding to self-liking. Zero-order cor- relations (Pearson’s r) were calculated for group, male and female data, and a number of small but significant

correlations were uncovered. For males, there was a neg- ative correlation between the self-liking subscale and the Reflective/Complex component, r(41) ¼ �.22, p ¼ .03. Females likewise exhibited small negative correlations with the self-liking subscale and both the Energetic/ Rhythmic component, r(156) ¼ �.20, p ¼ .01, and the Upbeat/Conventional component, r(156)¼�.19, p¼ .02. No significant correlations were noted for the group data.

TABLE 2. Means, Standard Deviations, and Component Loadings for the 13 Music Genres Subjected to a Principal Components Analysis

Descriptive Statistics Principal Component

Genre M SD 1 2 3 4

Dance 4.31 1.82 .90 �.12 .03 .05 Rap 3.47 1.93 .85 �.002 .09 �.11 Funk 4.31 1.86 .79 .07 �.15 .32 Blues 3.97 1.72 .13 .84 �.02 .22 Jazz 3.77 1.75 �.03 .83 �.001 .10 Classical 3.21 1.86 �.13 .59 .07 .27 Folk 4.50 1.89 .47 .49 .12 �.28 Alternative 3.66 1.92 .003 .15 .87 �.12 Metal 2.99 1.88 .06 .003 .85 �.03 Rock 4.47 1.81 �.02 �.08 .78 .23 Pop 4.41 1.64 .14 .007 .15 .76 Country 3.12 1.79 .05 .35 �.13 .71 Sound tracks 4.43 1.84 �.13 .36 .02 .59

Note. All loadings > |.40| are underlined. The highest factor loadings for each dimension are presented in bold.

FIGURE 1. Mean preference ratings as a function of music preference

factor for both males and females.

510 Daniel Shepherd & Nicola Sigg

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MUSIC PREFERENCE AND SOCIAL IDENTITY THEORY

The four music preference factors were further used to test the predictions of social identity theory, which entailed the construction of a measure of intergroup differences. To create a measure of intergroup differ- ences, six new variables were created by calculating the differences in preference ratings between each factor pairing. Table 3 displays mean difference scores, with positive and negative symbols affording further scrutiny of gender differences. Each difference variable was then correlated with the RSES and the self-liking/self- competence subscales as described in the preceding sec- tion. For example, the absolute difference between the first (i.e., Energetic/Rhythmic) and second (i.e., Reflec- tive/Complex) factors were computed and then these differences, ranging from 0 (no preference between the two factors) to 6 (a strong preference of one factor over the other) were correlated to the self-esteem measures (see Table 4). For females, negative correlations were found between the difference scores calculated from the Reflective/Complex and Energetic/Rhythmic factors and measures of self-esteem. The difference scores between these two factors correlated with both the ten-item RSES, r(198) ¼ �.15, p ¼ .03, and the self- competency subscale, r(198)¼�.21, p¼ .01. For males, positive correlations were noted between the difference

scores calculated from the Intense/Rebellious and Reflective/Complex scores and both the self-liking sub- scale, r(41) ¼ .27, p ¼ .05, and the full ten item scale, r(41)¼ .32, p¼ .04. Also for males, positive correlations were noted between the Intense/Rebellious and Upbeat/ Conventional difference scores and both the self-liking subscale, r(41) ¼ .32, p ¼ .04, and the ten-item RSES, r(41) ¼ .34, p ¼ .03. Fishers r-to-z transformations (two-tailed) revealed no significant differences in corre- lation coefficients across gender (p > .05).

Discussion

Our results reflect a number of interesting findings relating to the relationship between music preference and self-esteem, the factor structure of the RSES, and the predictions of social identity theory. Structural anal- ysis of the RSES data presented here did not extract a single self-esteem dimension. Instead, of the three competing models, the unidimensional model contain- ing all ten RSES items returned the poorest fit to the data. Thus further evidence has been marshalled in sup- port of the position that two distinct dimensions under- lie the RSES, namely, the two substantive dimensions of self-competency and self-liking proposed by Tafarodi and colleagues (2001, 2002).

TABLE 3. Mean Difference Scores (M) and Standard Deviations (SD) for Group, Male, and Female Data

Group (n ¼ 199) Males (n ¼ 42) Women (n ¼ 157)

Difference Scores M SD M SD M SD

Intense/Rebellious vs. Energetic/Rhythmic 1.66 1.43 – 1.88 1.44 þ 1.61 1.43 – Intense/Rebellious vs. Reflective/Complex 1.58 1.29 þ 1.64 1.21 þ 1.56 1.31 þ Intense/Rebellious vs. Upbeat/Conventional 1.55 1.28 – 1.43 1.26 þ 1.59 1.29 – Energetic/Rhythmic vs. Reflective/Complex 1.67 1.30 þ 1.71 1.23 þ 1.65 1.32 þ Energetic/Rhythmic vs. Upbeat/Conventional 1.66 1.18 – 1.59 1.15 þ 1.68 1.20 – Reflective/Complex vs. Upbeat/Conventional 1.23 0.89 – 0.96 0.78 – 1.31 0.91 –

Note: Positive and negative symbols indicate the direction of the difference.

TABLE 4. Correlation Coefficients (Pearson’s r) Estimating the Association Between Difference Scores and Self-esteem Measures for Group, Male, and Female Data

Group (n ¼ 199) Males (n ¼ 42) Women (n ¼ 157)

Difference Scores RSES Compt. Liking RSES Compt. Liking RSES Compt. Liking

Intense/Rebellious vs. Energetic/Rhythmic .04 .05 .02 .15 .13 .17 .02 .03 �.007 Intense/Rebellious vs. Reflective/Complex .02 .01 .02 .17 .01 .27* -.15* -.21* �.04 Intense/Rebellious vs. Upbeat/Conventional .06 .03 .08 .34* .23 .32* �.02 �.02 .001 Energetic/Rhythmic vs. Reflective/Complex �.11 �.10 �.10 �.06 �.08 �.02 �.11 �.10 �.12 Energetic/Rhythmic vs. Upbeat/Conventional .03 �.02 .08 .05 .06 .01 .02 �.04 .09 Reflective/Complex vs. Upbeat/Conventional .04 �.02 .12 �.03 �.76 .12 .04 �.03 .10

Note. All tests were two-tailed. * p < .05. RSES ¼ 10-item RSES. Compt. ¼ 5-item self-competence scale. Liking ¼ 5-item self-liking scale.

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The research reported here found no evidence sup- porting a relationship between the ten-item RSES and any of the four music preference dimensions derived from the STOMP. This result concurs with the findings reported by Rentfrow and Gosling (2003), who also found no significant correlations between the ten-item RSES and the four factors of music preference extracted from their music preference scale. However, when we divided the RSES scale into subscales based on self- competence and self-liking items, then small but signif- icant correlations emerged between three of the four music-preference dimensions and RSES items tapping into self-liking. Specifically, negative correlations were found between self-liking and the following two factors: Reflective/Complex (males only) and for females Ener- getic/Rhythmic and Upbeat/Conventional. Here, the implications of the findings are two-fold. First, it is the self-liking component of self-esteem that may be asso- ciated with music preference, and second, gender mod- erates the relationship between music preference and self-esteem.

Social identity theory predicts an association between group identification and self-esteem, which our results partially supported. Using measures of group differ- ences based on music preference, we uncovered small correlations (�.14 to .34), consistent in size with those reported in the literature (e.g., Tarrant et al., 2001). The small magnitude of the statistical relationships between group differences and music preference dimensions may be explained by a number of considerations. First, it may be that certain musical genres lend themselves to greater attachment and hence will be more strongly associated with social identity (Tekman & Hortaçsu, 2002). For example, those enjoying classical music may not feel motivated to wear clothes and regalia expressing their preference, nor play the music loudly in public, while those who identify with the rock or rap genres may do. Second, tolerance of different genres peak at different times across the lifespan (North & Hargreaves, 1999), and so the sample of young adults we tested may no longer invest their identities into a single genre while debasing others.

Two previous studies have examined social identity theory and music preference (Tarrant et al., 2001; Tek- man & Hortaçsu, 2002), though recruited predomi- nantly young males. Their findings are extended here by the inclusion of a greater proportion of females in the sample. Coley (2008) reported gender differences in relation to music preference, and gender differences in self-esteem are well documented (Baranik et al., 2008), though did not reach significance in the current study. For females we noted a negative association between

self-competency and the difference scores calculated from the Reflective/Complex and the Energetic/Rhyth- mic factors. Thus a high preference score on one of the two factors and a low score on the other is associated with lower self-esteem. This finding is not immediately explained by social identity theory, and the study design does not afford analyses testing the self-esteem hypoth- esis, which argues that increased intergroup discrimina- tion may be predicted by low or threatened self-esteem. For males, positive associations were noted between self-liking and difference scores calculated using the Intense/Rebellious factor and either of the Reflective/ Complex or Upbeat/Conventional factors. The male data provides some support for the predictions of social identity theory, namely that increased intergroup dis- crimination leads to increased self-esteem. Thus the data once again indicate the importance of gender as a moderating factor. However, while the magnitudes of the significant correlations were greater for males than females, they were not significantly so.

These gender differences are difficult to reconcile on the basis of current theory, though conjecture can be formed around gender differentials in music preference and use. For males, we note that intergroup discrimina- tion, according to social identity theory, is a strategy for achieving self-esteem via social competition aimed at increasing the positive distinctiveness of one’s own group (Lemyre & Smith, 1985). Thus, it may be the more competitive nature of males that produced both stronger and positive correlations relative to females. For males, outgroup discrimination along music dimen- sions were between aggressive styles of music, reflecting dominance, and ‘‘lighter’’ music types manifesting socialization themes of emotional expressiveness and relationships (Schwartz & Fouts, 2003). For females, the negative correlation involving the Reflective/Complex (blues, folk, jazz, classical) and Energetic/Rhythmic (dance, rap, funk) difference scores is more problematic. The lack of positive correlations could be because females do not use music socially like males, and instead use music emotionally (North et al., 2000). Within- group processes might also explain the differences between the genders, as to some extent the processes occurring within one’s group, such as acceptance from other members, will determine group identification and hence the ability to maximize between-group differences (Tekman & Hortaçsu, 2002). Because individuals also make ingroup comparisons (i.e., relatively privileged or deprived), the degree of group membership and sense of belonging may vary, and with it social identity. It maybe that the negative correlation found with the female data arose because while intergroup discrimination was high,

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within group processes were serving to attenuate self- esteem.

There were several limitations to this exploratory study, all of which motivate further research. First, the sample was fairly homogenous, as all participants were university students. Second, grouping the music into discrete, unidimensional genres constitutes an addi- tional limitation, since many musicians fit into several genres. Third, the indirect measure of intergroup differ- ences represents the differences between the preferences for various music domains, but further research is required to elucidate the psychological meaning of these differences. Lastly, the modest sample size precluded the use of multivariate techniques that better guard again an increase in the Type I error rate, and for the small male sample, avoid potential Type II errors. Future research in this area is needed to address these limitations, and to advance more comprehensive models that include the determinants of music preference.

In summary, previous research has failed to convinc- ingly uncover a relationship between music preference and self-esteem (Rentfrow & Gosling, 2003), though methodological considerations may partly explain the null finding. This study demonstrated that measures of self-esteem need to be employed with care, and when so used can uncover an association between music pref- erence and self-esteem, and can test theories of social processes. Furthermore, the moderating effect of gender should be estimated when reporting music preference data.

Author Note

Correspondence concerning this article should be addressed to Daniel Shepherd, Department of Psychol- ogy, P. O. Box 92006, Auckland University of Technol- ogy, Auckland, New Zealand. E-mail: daniel.shepherd@ aut.ac.nz

References

ABRAMS D., & HOGG, M.A. (1988). Comments on the motiva- tional status of self-esteem in social identity and intergroup discrimination. European Journal of Social Psychology, 18, 317-338.

BAKER, F., & BOR, W. (2008). Can music preference indicate mental health status in young people? Australasian Psychiatry, 16, 284-288.

BARANIK, L. E., MEADE, A., LAKEY, C. E., LANCE, C. E., HU, C., HUA, W., & MICHALOS, A. (2008). Examining differential item functioning of the Rosenberg Self-Esteem Scale across eight countries. Journal of Applied Social Psychology, 38, 1867-1904.

COLEY, A. (2008). Young people’s musical taste, Relationship with gender and gender-related traits. Journal of Applied Social Psychology, 38, 2039-2055.

GAZZANIGA, M. S., & HEATHERTON, T. F. (2006). Psychological science, mind, brain, and behaviour. New York: W.W. Norton & Co.

GRAY-LITTLE, B., WILLAIMS, V. S. L., & HANCOCK, T. D. (1997). An item response theory analysis of the Rosenberg self-esteem scale. Personality and Social Psychology Bulletin, 23, 443-451.

GREITEMEYER, T. (2009). Effects of songs with prosocial lyrics on prosocial behavior: Further evidence and a mediating mecha- nism. Personality and Social Psychology Bulletin, 35, 1500-1511.

LAUKKA, P. (2007). Uses of music and psychological well-being among the elderly. Journal of Happiness Studies, 8, 215-241.

LEMYRE, L., & SMITH, P. M. (1985). Intergroup discrimination and self-esteem in the minimal group paradigm. Journal of Personality and Social Psychology, 49, 660-670.

NORTH, A. C., & HARGREAVES, D. J. (1999). Music and adoles- cent identity. Music Education Research, 1, 75-92.

NORTH, A. C., HARGREAVES, D. J., & O’NEILL, S. A. (2000). The importance of music to adolescents. British Journal of Educational Psychology, 70, 255-272.

RENTFROW, P. J., & GOSLING, S. D. (2003). The do re mi’s of everyday life: Examing the structure and personality correlates of music preferences. Journal of Personality and Social Psychology, 84, 1236-1256.

RENTFROW, P. J., GOLDBERG, L. R., & LEVITIN, D. J. (2011). The structure of musical preferences: A five-factor model. Journal of Personality and Social Psychology, 100, 1139-1157.

ROSENBERG, M. (1965). Society and the adolescent self-image. Princeton, NJ: Princeton University Press.

SCHWARTZ, K. D., & FOUTS, G. T. (2003). Music preferences, personality style, and developmental issues of adolescents. Journal of Youth and Adolescence, 32, 205–213.

STEELE, J. R., & BROWN, J. D. (1995). Adolescent room culture: Studying media in the context of everyday life. Journal of Youth and Adolescence, 24, 551-576.

TAFARODI, R. W., & MILNE, A. B. (2002). Decomposing self- esteem. Journal of Personality, 70, 443-483.

TAFARODI, R. W., & SWANN, W. B. (2001). Two-dimensional self- esteem: Theory and measurement. Personality and Individual Differences, 31, 653-673.

TAJFEL, H. (1978). Differentiation between social groups. London, UK: Academic Press.

Music Preference, Social Identity, and Self-Esteem 513

This content downloaded from �����������68.230.212.70 on Wed, 31 May 2023 01:01:32 +00:00������������

All use subject to https://about.jstor.org/terms

TARRANT, M. (1999). Musical and social development in adoles- cence (Unpublished doctoral dissertation). University of Leicester, Leicester, United Kingdom.

TARRANT, M., NORTH, A. C., & HARGREAVES, D. J. (2001). Social categorization, self-esteem, and the estimated musical prefer- ence of male adolescents. The Journal of Social Psychology, 141, 565-581.

TEKMAN, H. G., & HORTAÇSU, N. (2002). Music and social identity: Stylistic identification as a response to musical style. International Journal of Psychology, 37, 277-285.

ZILLMANN, D., & GAN, S. (1997). Musical taste in adolescence. In D. J. Hargreaves & A. C. North (Eds.), The social psychology of music (pp. 161-187). Oxford, UK: Oxford University Press.

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