716757 POM0010.1177/0305735617716757Psychology of MusicYoo et al. research-article2017 Article Personality and world music preference of undergraduate non-music majors in South Korea and the United States Psychology of Music 1–15 © The Author(s) 2017 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav https://doi.org/10.1177/0305735617716757 DOI: 10.1177/0305735617716757 journals.sagepub.com/home/pom Hyesoo Yoo1, Sangmi Kang2 and Victor Fung3 Abstract We investigated contributors of undergraduate nonmusic majors’ preferences for world musics, specifically those from Africa, Asia, and Latin America. Drawing upon the reciprocal feedback model as a theoretical framework, we determined the extent to which predictor variables (familiarity with the music, personality, and music absorption) were related to music preference. Participants were 401 undergraduate nonmusic majors from South Korea (n = 208) and the USA (n = 183). Participants took an online survey via Qualtrics that included demographic information, the World Musics Preference Rating Scale, the Big-Five Inventory, and the Absorption in Music Scale. Results indicated that, familiarity, followed by openness to experience, was the strongest predictor of participants’ preferences for world musics. For the U.S. participants, familiarity, followed by openness to experience, was the strongest predictor of participants’ preference for musics from each continent. By contrast, for the South Korean participants, although familiarity was also the strongest predictor for African, Latin American, and Asian musics, openness to experience was not consistently the second strongest contributor. For African music, openness to experience was ranked second; for Latin American and Asian music, agreeableness and music absorption were ranked second, respectively. Keywords African, absorption, agreeableness, Asian, familiarity, Latin American, openness Affective response to music plays a crucial role in learning music. People are inclined to listen to their preferred music and show greater interest in that kind of music (Greasley, Lamont, & Sloboda, 2013). Affective response is often a stronger predictor of future music participation 1Virginia Polytechnic Institute and State University, USA of Florida, USA 3University of South Florida, USA 2University Corresponding author: Hyesoo Yoo, Virginia Polytechnic Institute and State University, 195 Alumni Mall (Squires 242 C), Blacksburg, VA 24061-0131, USA. Email: haes2000@vt.edu 2 Psychology of Music 00(0) than music ability (Demorest, Kelley, & Pfordresher, 2017). Therefore, many scholars have investigated affective responses and effective ways of promoting them (Boyle & Radocy, 1987). Among a variety of psychological constructs in affective responses, music preference has been the most frequently investigated (Brittin, 1991, 2014; LeBlanc, 1981; LeBlanc & Cote, 1983; Leblanc & McCrary, 1983). Preference refers to a degree of liking and disliking a certain object rather than cognitive or aesthetic responses to that object (Finnäs, 1989). By definition, preference is relatively immediate; this signifies a specific choice within a set of options. In contrast, taste implies a long-term value or commitment (Abeles, 1980). In light of this, preference can be altered through exposure or instruction in a relatively shorter period of time, when compared to other affective responses (Radocy & Boyle, 2012). Music educators have tried to encourage students’ music preference because it may function as a “springboard for further music learning” (Fung, 1995, p. 31). Conventionally, music familiarity has been regarded as a strong indicator of music preference (Meyer, 1956; Zajonc, 2001). The relationship between music familiarity and preference has also received great attention in world music preference. World music is defined as “musics outside the European and European-derived art music traditions” (Olsen, 1992) and it “suggests a holistic approach to music and draws attention to the need for a total world view” (Brown, 1992). According to Fung (1992, 1996), undergraduate students preferred world music pieces that are familiar to them because of their similarity to Western music in tempo and in rhythmic regularity. Demorest and Schultz (2004) also reported that children preferred arranged versions of world music recordings significantly more than original authentic versions because they sounded more like Western music. However, despite the strong relationship between music familiarity and preference, familiarity does not completely explain students’ music preferences. In one of Fung’s studies (1994), undergraduate students’ music familiarity based on music characteristics explained 13–35% of the variance in preference, and in his later study (2004), music familiarity was relatively unimportant to explaining students’ preference decisions when all music listening options were similarly unfamiliar. Personality has also been investigated as a strong indicator of individual differences in music preference (Abeles & Chung, 1996; Berlyne, 1971; Dunn, de Ruyter, & Bouwhuis, 2012; North & Hargreaves, 1999; Rawlings & Ciancarelli, 1997; Rentfrow & Gosling, 2003). Many scholars have examined the relationship between a listener’s personality and music preference according to musical styles, genres, and musical elements. Earlier personality and music preference studies were severely limited in their choice of musical materials; Western classical musical excerpts were exclusively used in these studies (Glasgow, Cartier, & Wilson, 1985; Hargreaves & Colman, 1981). As far as can be determined, Litle and Zukerman (1986) were the first to include non-Western classical categories when investigating the relationship between personality (sensation-seeking) and music preference. Out of 60 musical excerpts from their Music Preference Scale (MPS), only four pieces were categorized as folk/ethnic, which comprised mostly American folk songs; their inclusion of non-Western category thus did not cover world musics. A few years later, Rawlings and Ciancarelli (1997) adopted a modified version of MPS. One key feature in their study was the first addition of world music excerpts in preference and personality studies. However, the portion of world music samples was not large enough to compare how participants reacted differently to various types of musics outside the European and European-derived art music traditions. Afterwards, more varied world music pieces were included in music preference and personality studies. For example, Rawlings, Vidal, and Furnham (2000) adopted two world music pieces out of 15 pieces, one Nigerian and the other Spanish. Tekman and Hortaςsu (2002) included two world Yoo et al. 3 music styles, Arabesk and Turkish, out of six music styles. Six years later, Tekman conducted a similar study with his colleagues, and he specified the categories of Turkish music: Turkish pop, Turkish art music, Arabesk, Özgün, and Turkish folk music (Tekman, Göklü, & Saglam, 2008, as cited in Tekman, 2009). These efforts broadened the boundaries of the folk/ethnic category of MPS; however, world music excerpts in each study were still limited because, among a variety of world music pieces, only one or two styles were included in the data. More recently, Dunn et al. (2012) examined the relationships among music preference, listening behavior, and personality. They adopted the Short Test of Music Preference (STOMP) developed by Rentfrow and Gosling (2003). Although folk was included among 16 music genres in the STOMP, it was unclear whether the category included musics outside the European or European-derived art music traditions. Furthermore, no correlation was found between five personality traits and participants’ preferences for folk. Treating world musics as one subset of a category in listening examples may allow for a comparison of listeners’ responses to world and European or European-derived art musics. However, this approach could not reflect a variety of world musical styles nor could it reflect various responses to each of these musical genres sampled from different music cultures around the world. Thus, there is a need to examine the relationship between world music preference and listeners’ personalities from a broader world music perspective. We used Fung’s (1996) World Music Preference Rating Scale (WMPRS), which contained 36 musical excerpts from three different continents and nine countries: Congo, Malawi, Nigeria (Africa), China, Japan, Korea (Asia), Cuba, Mexico, and Peru (Latin America). Previous studies generally reported that music preferences were consistently related to personality characteristics; for example, extraversion (Rawlings & Ciancarelli, 1997), neuroticism (Dollinger, 1993; Dunn et al., 2012), sensationseeking (Rawlings et al., 2000), and openness to experience (Dollinger, 1993; Rawlings & Ciancarelli, 1997; Dunn et al., 2012; Rawlings et al., 2000). By adopting Fung’s WMPRS with a broader sample of non-Western world musical excerpts, we intended to compare our results with those from prior studies. The extant literature on music preference is consistent in suggesting three types of variables that contribute to a preference decision. The reciprocal feedback model of Hargreaves, Miell, and MacDonald (2005) contained three main influences on listeners’ responses to music: the “Music,” the “Situations and contexts,” and the “Listener.” The “Music” represented musical style such as complexity, familiarity, and prototypicality; the “Situations and contexts” assumed listener’s social and cultural circumstances and their effects on music preferences; and, the “Listener” described the individual’s gender, age, personality, and so forth. The model demonstrated that there was reciprocal feedback among all three types of influences because they could simultaneously influence one another bi-directionally when explaining listeners’ responses to music (North & Hargreaves, 2008). We considered all three aspects of influences in the current study, including world music as “Music,” two different countries as “Situations and contexts,” and personality and absorption as “Listeners.” For “Situations and contexts,” we compared U.S. and Korean audiences. Because traditional Korean music was reported as the least preferred music amongst U.S. audiences due to its unique musical qualities (Fung, 1996), we would be able to reveal listeners’ responses to different non-Western musical traditions, near or far and familiar or unfamiliar. For “Listeners,” we included music absorption along with personality because a possible association between music absorption and personality traits was proposed (Dollinger, 1993). The purpose of this study was to investigate factors that contribute to individuals’ music preferences for non-Western world music pieces. Music familiarity, personality, music 4 Psychology of Music 00(0) absorption, and participants’ nationality were examined to account for the listeners’ world music preferences, based on the reciprocal feedback model (Hargreaves et al., 2005). This research addressed the following questions: - - Considering undergraduate nonmusic majors’ familiarity with the music, personality, and music absorption, what predictor variable(s) contribute to their preferences for world musics, and specifically those from Africa, Asia, and Latin America based on participants’ nationality? To what extent do predictor variables (familiarity, personality, and music absorption) relate among themselves? Method Participants and procedures This study involved 401 undergraduate nonmusic majors from South Korea (n = 208) and the USA (n = 193). Participants were recruited by emailing music instructors who taught music courses for undergraduate nonmusic majors, such as music methods for elementary education majors, music appreciation, and non-auditioned choirs, at two large universities in the southeastern USA. Both institutions were categorized as “four-year, large, primarily nonresidential” universities (Indiana University Center for Postsecondary Research, n.d.). The researchers would describe the three large universities in South Korea in similar terms. All five universities enrolled more than 10,000 full-time students. After the instructors’ approval, we collected data using a standard protocol. All participants took an online survey via Qualtrics. The detailed information regarding the online survey is presented in the “Measurement Instruments” section. The age range of the U.S. participants was 17 to 26 years with a mean of 20.2 years (SD = 1.87), and the age range of the South Korean participants was 18 to 29 years with a mean of 21.8 years (SD = 2.00). The participants consisted of 38% male and 62% female in the USA, and 28.5% male and 71.5% female in South Korea. Regarding ethnicity, 100% of the Korean participants were identified as Asian. A majority of the U.S. participants (60.1%) were identified as European/White, followed by 15.1% Hispanic, 10.9% Asian, 9.8% African American, and 4.1% other. A majority of the participants in each country had previous musical experiences in learning music (South Korea, 71.2%; the USA, 76.2%). Specific to traditional nonWestern music experiences, approximately 39% of Korean participants indicated having such experiences, while nearly 42% of U.S. participants indicated the same. These figures reflected how Korean participants were submerged in an environment where Western music dominated in a non-Western culture (Kang, 2005; Jang, 2004). Measurement instruments All participants took an online survey via Qualtrics consisting of demographic information and three measurement instruments: (1) the World Music Preference Rating Scale (WMPRS; Fung, 1996), (2) the Big-Five Inventory (BFI; John & Srivastava, 1999), and (3) the Absorption in Music Scale (AIMS; Sandstrom & Russo, 2011). Korean participants used Korean translations of these three measurement instruments included in the survey, while U.S. participants used the original English versions. The WMPRS contained 36 instrumental musical excerpts from three different continents and nine countries: Africa: Congo, Malawi, Yoo et al. 5 Nigeria; Asia: China, Japan, Korea; Latin America: Cuba, Mexico, and Peru. They were selected from 70 excerpts from commercial recordings (not field recordings) produced between 1972 and 1989 and collected in the Archives of Traditional Music at Indiana University, Bloomington. The selection was based on the highest inter-item correlation coefficients of preference ratings in a pilot study (Fung, 1996). Musical and stylistic variabilities were expected across excerpts from any given country, but a high level of internal consistency of the preference ratings were ensured. Four instrumental excerpts were selected from each country. Each excerpt presented the first 40 seconds of a piece with a 10-second interval between each. A full list of excerpts is presented in Supplemental Material online. For the composite preference measure of 36 items (WMPRS), reliability coefficients were consistently high: α = .96; split-halves = .93. Similarly, the composite familiarity measure displayed high reliability coefficients: α = .94; split-halves = .90 (Fung, 1996). Whereas the original WMPRS adopted a seven-point scale for preference (1 = strongly dislike, 7 = strongly like) and three-point scale for familiarity (1 = unfamiliar, 3 = familiar), the current study employed a seven-point scale for both preference and familiarity (i.e., 1 = unfamiliar, 7 = familiar) to meet the assumptions of regression analysis. The BFI is a self-report inventory designed to measure the personality traits of the Big-Five dimensions, which have been described as: - Extraversion: an individual’s propensity to be sociable, talkative, assertive, active; it indicates their preference toward stimulating and exciting environments. Agreeableness: an individual’s propensity toward being altruistic, helpful, sympathetic, and empathetic toward others. Conscientiousness: an individual’s propensity toward cleanliness, orderliness self-determination, and self-control. Neuroticism: an individual’s propensity to feel fear, sadness, embarrassment, anger, guilt, and other emotions of negative affect. Openness to Experience: an individual’s propensity toward intellectual curiosity, imagination, aesthetic and emotional sensitivity, and originality. Among the instruments measuring personality traits related to the Big-Five dimensions (the NEO Five-Factor Inventory, Costa & McCrae, 1992; the Big-Five Inventory, John & Srivastava, 1999; and Trait Descriptive Adjectives scale, Goldberg, 1992), the 44-item BFI was used in the current study for the following reasons: (a) the BFI has proven “useful for cross-language and cross-culture research” (Benet-Martínez & John, 1998, p. 20); (b) it is a simple and concise measure that is easy to administer (Nichols, Padilla, & Gomez-Maqueo, 2000); (c) the short-phrase item format is less complex than the format used by the NEO questionnaires (John & Srivastava, 1999); and, more importantly, (d) the BFI is available for researchers to use for non-commercial research purpose. The reliability coefficients of the 44-item BFI produced a consistently high α = .83, and the convergent validity correlation between the 44-item BFI and 240-item NEO-FFI was r = .73.For the convergent validity of the BFI-K (Korean translation), scores on the BFI-K correlated with the scores of the original BFI; r = .59, .69, .71, .69, and .79 for Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience, respectively (Kim et al., 2010). The BFI-K showed high internal reliabilities with the original BFI scale; Cronbach’s α = .77, .70, .78, .79, and .76 for Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience, respectively (Schmitt, Allik, McCrae, & Benet-Martínez, 2007). Furthermore, the reliability of the BFI-K was good; Guttmans’ split half = .59 - .78, Cronbach’s α = .52 - .75 (Kim 6 Psychology of Music 00(0) et al., 2010).The respondents rated their degree of agreement or disagreement with the 44 statements on a five-point scale (1 = strongly disagree, 5 = strongly agree). The AIMS, modified from the Tellegen Absorption Scale (TAS, Tellegen & Atkinson, 1974), was a self-report measure designed to measure individuals’ ability and willingness to allow music to draw them into an emotional experience (individuals’ absorption in music). A convergent validity was determined by correlating the AIMS with (a) the TAS and (b) the Musical Involvement Scale (MIS; Nagy & Szabo, 2004, as cited in Sandstrom & Russo, 2011); AIMS showed high convergence with the TAS (r = .76,) and the MIS (r = .74). Test–retest reliability also showed a strong temporal consistency (r = .91). AIMS was translated into Korean for the Korean participants by the researchers, and its content was checked by three Korean music education/psychology/therapy experts who held graduate degrees in each field and were fluent in both languages. Based on their comments, each translated item in the AIMS was revised, which was named AIMS-K (Korean translation). The AIMS-K showed high convergent validity with the original AIMS (.97) and the AIMS-K produced high reliability coefficients (.90). The respondents rated the 34-item AIMS questionnaire on a five-point scale (1 = strongly disagree, 5 = strongly agree). Results Inter-item correlations within each country category were performed for familiarity and preference. All coefficients were significant at the p < .01 level. Coefficients for familiarity ranged from .21 to .65, with most of the coefficients in the .50 range. Median coefficients within each country category for familiarity ranged from .40 to.58. All four items in each country category correlated highly with their respective composite familiarity ratings. Coefficients for preference ranged from .38 to .67, with most of the coefficients ranging from the .40s to the .50s. Median coefficients within each country category for preference ranged from .43 to .59. Furthermore, all four items in each country category correlated highly with preferences for their respective composites at the country level. Inter-country correlation coefficients for familiarity ranged from .16 to .82, with most of the coefficients ranging from the .50s to the .60s. Inter-country correlation coefficients for preference ranged from .39 to .83, with most of the coefficients ranging from the .50s to the .60s. To ensure that those in the U.S. group who self-identify as Asian (n = 19) did not influence the preference scores for the U.S. group as a whole, we isolated the Asian participants’ composite preference scores and compared their consistency with 19 other, randomly selected participants from the U.S. group. An independent samples t-test confirmed that no significant difference existed in composite preference mean scores between these two groups (t = .335, p > .05), indicating that the group differences did not exist and therefore the scores were not excluded from the total sample. Additionally, to show that U.S. participants’ responses were homogenous across WMPRS composite and subtests, we randomly selected 19 European/White-, 19 Hispanic-, 19 Asian-, and 19 African-American participants from the U.S. sample and conducted an ANOVA. The reason we randomly selected 19 participants from each ethnic group in the U.S. was to match the number of Asian-American participants (n = 19) in the USA. No significant differences were found in composite WMPRS mean scores (p = .28) or African, Latin, and Asian music mean scores (p = .13, p = .20, and p = .46, respectively), indicating that the U.S. students’ responses as a group were sufficiently homogenous across WMPRS composite and subtests. Research question 1: Considering undergraduate nonmusic majors’ familiarity with the music, personality, and music absorption, what contributes to their preferences for world musics, and specifically those from Africa, Asia, and Latin America based on nationality? 7 Yoo et al. Table 1. Pearson product–moment correlations among Big-Five personality factors, AIMS, familiarity, and preference for world musics (N = 401). 1. 2. 3. 4. 5. 6. 7. 8. Extraversion Agreeableness Conscientiousness Neuroticism Openness AIMS Familiarity Preference Mean (SD) 2 3 4 5 6 7 8 3.24 (.62) 3.67 (.52) 3.47 (.59) 3.02 (.64) 3.52 (.58) 3.30 (.70) 3.39 (.94) 3.98 (1.01) .22** .18** .39** –.19** –.39** –.32** .20** .25** .12* –.23** .15** .17** .02 –.04 .55** .06 .06 .01 –.05 .15** .24* .03 .13** .00 –.04 .27** .29** .63** *p < .05, **p < .01. Table 1 displays means, standard deviations, and correlations among all the variables. The relationships between each predictor and preference for world musics, from the lowest to the highest coefficients, were: Conscientiousness (r = .003, ns), Neuroticism (r = -.004, ns), Extraversion (r = .028, ns), Agreeableness (r = .132, p < .001), Openness to Experience (r = .273, p < .001), Music absorption (r = .285, p < .001), and Familiarity (r = .628, p < .001). It is important to note that the relationships between three of the Big-Five personality factors (conscientiousness, neuroticism, and extraversion) and preference for world musics were non-significant (p > .05). Among the five personality factors, the relationship with openness to experience and agreeableness reached significance (p < .001), as did the relationships between familiarity and preference for world musics and between music absorption and preference for world musics. World musics Tables 2 and 3 show the results of four stepwise multiple regression analyses. To control for Type 1 error, a Bonferroni correction was applied (p < .0125 instead of p < .05).To determine the best prediction model for participants’ preferences for world musics, we first conducted a stepwise multiple regression analysis using familiarity with the music, personality (five factors), music absorption, and nationality as the predictor variables and a composite world music preference rating scale score as the criterion variable. Preliminary analyses confirmed no violation of the assumptions of normality, linearity, multicollinearity, and homoscedasticity. The results of the first stepwise regression analysis revealed the best prediction model in which familiarity and openness to experience explained a total of 42.6% of the variance in participants’ preferences for world musics. F(2, 398) = 147.89, p < .001. Among the eight predictor variables, familiarity, β = .60, p < .001, and openness to experience, β = .18, p < .001, were the significant predictors of participants’ preferences for world musics. Familiarity was the strongest predictor, accounting for 39.3% of the variance. Openness to experience contributed an additional 3.3%. African music To test which variables significantly predicted participants’ preferences for African music in each country, we conducted another stepwise regression analysis including the same seven predictor variables we used in the first stepwise regression analysis, excluding nationality. The WMPRS scores for Africa served as the criterion variable. This stepwise multiple regression analysis 8 Psychology of Music 00(0) Table 2. Results of stepwise regression analysis for participants’ preferences for world musics (N = 401). Variables Beta r R R2 R2 Change Familiarity Openness .60 .18 .63 .27 .63 .66 .40 .43 .39 .03 Table 3. Results of stepwise regression analyses for participants’ preferences for African, Latin American, and Asian music in the USA and South Korea (N = 401). Africa USA SK Latin America USA SK Asia USA SK Variables Beta r R R2 R2 change Familiarity Openness Familiarity Openness .50 .20 .63 .16 .52 .23 .63 .15 .52 .56 .63 .65 .27 .31 .39 .42 .27 .04 .39 .03 Familiarity Openness Familiarity Agreeableness .57 .36 .66 .15 .60 .34 .66 .19 .60 .65 .66 .68 .36 .43 .44 .46 .36 .06 .44 .02 Familiarity Openness Familiarity AIMS .49 .25 .66 .13 .54 .36 .69 .30 .54 .60 .69 .71 .29 .36 .48 .50 .29 .06 .48 .02 Note: USA = United States; SK = South Korea. (Table 3) revealed that familiarity and openness to experience were also significant predictors of both South Korean and U.S. participants’ preferences for African music. In the USA, a model including these two predictors was the best prediction model, accounting for 30.8% of the variance in participants’ preferences for African music, which was significant, F(2, 190) = 42.195, p < .001. The variable of familiarity was the strongest predictor, β = .50, p < .001, contributing 27% of the variance followed by openness to experience, β = .20, p < .001, contributing an additional 3.8%. In South Korea, familiarity and openness to experience contributed 41.7% of the variance, which was significant, F(2, 205) = 73.22, p < .001. The variable of familiarity was the strongest predictor (β = .63, p < .001), contributing 39.2% of the variance. Openness to experience was the next strongest predictor, β = .16, p < .001, contributing an additional 4.2%. Latin American music In the third set of stepwise multiple repression analysis, we regressed participants’ preferences for Latin American music on the same seven predictor variables we used in the second stepwise regression analysis. The WMPRS scores for Latin America were the criterion variable. The results revealed that while familiarity and openness to experience were significant variables in the USA, familiarity and agreeableness were significant variables in South Korea. In the USA, the best prediction model is that in which familiarity and openness to experience explained a Yoo et al. 9 total of 42.7% of the variance in participants’ preferences for Latin American music, which was significant, F(2, 190) = 70.89, p < .001. Familiarity was the strongest predictor, β = .26, p < .001, contributing 36.3% of the variance followed by openness to experience, β = .57, p < .001, contributing an additional 6.4%.In South Korea, variables of familiarity and agreeableness accounted for 46.4% of the variance in participants’ preferences for Latin American music, which was significant, F(2, 205) = 88.66, p < .001. Familiarity was the strongest predictor, β = .66, p < .001, contributing 44.1% of the variance followed by agreeableness, β = .15, p < .001, contributing an additional 2.3%. Asian music In the fourth stepwise multiple repression analysis, we regressed Asian music preference on the same seven predictor variables. The WMPRS scores for Asia served as the criterion variable. The results revealed that in the USA the model including both familiarity and openness to experience significantly predicted participants’ preferences for Asian music, F(2, 190) = 50.10, p < .001. This model accounted for 35.6% of the variance in participants’ preferences for Asian music. Familiarity was the strongest predictor, β = .49, p < .001, contributing 29.4% of the variance followed by openness to experience, β = .25, p < .001, contributing an additional 6.2%. In South Korea, the model including both familiarity and music absorption accounted for 49.8% of the variance in participants’ preferences for Asian music, which was significant, F(2, 205) = 101.64, p < .001. Familiarity was the strongest predictor, β = .66, p < .001, contributing 48.2% of the variance followed by music absorption, β = .13, p < .001, contributing an additional 1.6%. Research question 2: To what extent does each predictor variable relate with one another? Pearson product–moment correlations were computed to explore the relationships across all predictor variables (Table 1). All correlations were statistically significant at the p < .01 level. Because variables of familiarity, openness to experience, agreeableness, and music absorption were significant variables in our analyses, we singled out these variables to explain their specific relationships. Dollinger (1993) predicted the association between music absorption and personality dimensions, suggesting that the relationship between these two variables should be empirically tested. In our analyses, the correlation between openness to experience and music absorption was r = .55 (p < .001). The correlation between music absorption and agreeableness was r = .17 (p < .001) and between agreeableness and openness to experience was r = .25 (p < .001). For the variable of familiarity, the relationship with openness to experience was r = .15 (p < .001) and with music absorption, r = .30 (p < .001). The relationship between familiarity and agreeableness was, however, not significant, r = .06 (p > .05). Discussion We sought to determine contributors to undergraduate nonmusic majors’ preferences for world musics, considering familiarity with the music, personality, and music absorption. We investigated these contributors to world music preference using the total WMPRS scores (sums of the three continental sub-scores) as well as the three continental scores (sub-scores of African, Asian, and Latin American musics). These investigations were undertaken based on participants’ nationalities (USA or South Korea). We further attempted to determine the relationships 10 Psychology of Music 00(0) among the contributing variables. Each of the variables in the current study were selected based on the reciprocal feedback model (Hargreaves et al., 2005) The primary results indicated that familiarity followed by openness to experience was a significant predictor of participants’ preferences for world musics. Familiarity explained nearly 40% of listeners’ preferences, but openness to experience as a personality trait explained a relatively small portion of the variance in preference (3.3%). These results are consistent with previous studies in which familiarity was found to strongly correlate with preference for world musics, and in which openness to experience was related to preferences for a wide range of world musical traditions (Dollinger, 1993; Rawlings & Ciancarelli, 1997; Rawlings et al., 2000, Vella & Mills, 2016). However, when we narrowed our scope down to the music from the three world regions (Africa, Latin America, and Asia) and analyzed the data based on the participants’ nationalities, this was not always the case. For the participants from the USA, the results were consistent with the previous findings for the WMPRS total scores. Familiarity, followed by openness to experience, was the strongest predictor of participants’ preference for each continent. By contrast, for the South Korean participants, although familiarity was also the strongest predictor for African, Latin American, and Asian music, openness to experience was not consistently the second significant contributor. For African music, openness to experience was ranked second; but for Latin American and Asian music, respectively, agreeableness and music absorption were ranked as the second contributor. As in several earlier studies in South Korea, openness to experience predicted individuals’ music preferences for classical, jazz, popular, soul, rock/metal, and blues music (Cho, 2016; Gu, 2010; Kim, 2005; Suh & Park, 2011); however, other domains of Big Five personality traits were inconsistent in explaining music preferences (Cho, 2016; Gu, 2010). These inconsistent findings may be due to differences in research participants, musical styles, types of mode and tempo, research design, or a combination of these. Several studies supported that openness to experience, extraversion, and agreeableness were positively related to individuals’ music preferences (Jo, 2000; Suh & Park, 2011), while others found only openness to experience and extraversion as important predictors of music preferences (Cho, 2016; Gu, 2010). Moreover, some studies have revealed a positive association for a given personality trait, whereas there were conflicting results reporting a negative relation for the same personality trait in other studies (Kim, 2005). Even though some studies have examined the relationships between personality and music preferences, none of these studies focused on the associations between personality and world music preferences among Korean participants. With the inconsistent findings and scarcity of the previous studies, it is difficult to interpret the current study’s finding that agreeableness ranked as the second significant predictor for Latin American music preference in South Korean participants. This result could be explained by the reciprocal relations between “Situation and contexts,” “Music,” and “Listener.” Given the reciprocal feedback model, the three main influences can simultaneously interact with one another bi-directionally. Thus, agreeable participants’ music preferences might be influenced by the music’s style and social and cultural context. To further investigate these relationships in South Korean participants, one should seek insights of those who rated Agreeableness as a contributing variable for world music preferences. Another interesting result is that music absorption, rather than openness to experience, was the second significant predictor of Korean participants’ preferences for Asian music. This result may also be explained by its associations with Asian philosophy in relation to the music absorption items within the reciprocal feedback model. Many Asians practice meditation under the influence of Asian philosophies, such as Confucianism, Daoism, and Buddhism, which might Yoo et al. 11 explain Korean participants’ “Situations and contexts.” Strictly speaking, the psychological concept of music absorption is not identical to meditation. Nevertheless, several items from the AIMS that we used for the current study seem to be related to meditation, for example, “When listening to music, I sometimes temporarily forget where I am”; “Sometimes when listening to music, I feel as if my mind can understand the whole world”; and “I sometimes feel like I am ‘one’ with the music.” Due to the similarity between some music absorption items and a supportive atmosphere for meditation (Situations and context), individuals who rated high in music absorption among Korean participants (Listener) might tend to prefer Asian music (Music). The possible association between absorption and meditation can be glimpsed in classic Daoist literature. Below is a quotation from a classic Daoist Zhuangzi’s “Theory of Equality,” the well-known of story of “Zhuang Zhou Dreamed of Being a Butterfly”: Once Zhuang Zhou dreamed he was a butterfly, a freely and happily fluttering butterfly. He did not know he was Zhou. Suddenly he woke up and found himself to be Zhou feeling stiff and unable to move. He did not know whether Zhou was then a man dreaming he was a butterfly, or whether he was a butterfly dreaming he was a man (Zhuangzi 2.17 in Zhuangzi & Fu, 2012, p. 52). This perspective is often explained as the theory of harmonization of object and ego (物我一體), which is congruent with the neo-Confucian view that “heaven and human are one (天人合 一)” (Zhang & Zhou, 2014) and the Daoist view of “honoring nature (崇尚自然)” (Laozi & Fu, 2012). The ancient philosophers believed that through meditation or self-reflection, a person could reach a spiritual state in which “the object and people are integrated as one.” We assume that this interaction among (a) Korean participants who tend to absorb music (Listener), (b) Asian meditation practices (Situations and contexts), and (c) Asian musical styles (Music) resulted in music absorption as the second significant predictor among Korean participants. Implications for music education The most outstanding finding in the current study is that familiarity explained the most variance (27% to 48%) in world music preference. While music teachers may not directly influence a student’s music preference, they can help students to be more familiar with various world musical styles by incorporating them in their teaching. Familiarity could be influenced by “Situations and contexts” created by teachers. Although there is limited evidence to suggest a causal relationship between familiarity and world music preference, teachers should bear a responsibility to do what they can, given the consistent familiarity–preference relationship within this study and across many other studies. If students are familiar with many world musical styles, they may make their preference decisions based on a wider range of musical styles. This study also shows that some personality variables are related to world music preference, contributing to the “Listener” factor in the reciprocal feedback model. Openness to experience for participants in both countries, as well as agreeableness and music absorption in the Korean sample, each account for a small but statistically significant amount of variance in world music preference. These personality traits are developed through long periods of acculturation. While it is far-fetched for a teacher to modify a student’s personality trait in a short period of time and it is debatable to argue whether teachers should act to change learners’ personality traits, teachers may design activities to cultivate student’s openness to a variety of experiences, including musical experiences. This recommendation parallels evidence found in the literature on personality, which identifies openness to experience and agreeableness among traits that explained undergraduate students’ learning, motivation, and academic achievement (Komarraju, Karau, 12 Psychology of Music 00(0) & Schmeck, 2009; Komarraju, Karau, Schmeck, & Avdic, 2011). Music instructional strategies may include activities that stimulate curiosity, imagination, and originality, and cultivate student’s aesthetic and emotional sensitivities. In the Korean sample, agreeableness and absorption might be working more prominently in the Korean culture than in the U.S. culture. Observing music learners’ personality traits (i.e., openness to experience, agreeableness, and absorption) may add to music teachers’ awareness of these traits found in the local culture. Music teachers may reinforce certain personality traits as each student develops into adulthood. Teachers should recognize individual differences among their students, such that some musical preference indicators might be explained, utilized, and integrated into their teaching. Suggestions for further research We suggest a few directions for further research. Revisiting the reciprocal feedback model, explaining musical response involves numerous factors surrounding the music itself, listeners’ characteristics, and the social and cultural contexts to which the listeners belong. Continued endeavors should be made to explain this multi-dimensional process from psychological and socio-cultural perspectives. In the scope of the current study, the two countries’ differences in general openness and tolerance toward foreign cultures, foreign lifestyles, and foreign cultural values would also explain world music preference. World music preference should be further investigated using various factors and their interactions represented in the reciprocal model. There could be other personality variables not included in the BFI but worthy of exploring, such as those measured by the Myers-Briggs Type Indicator (MBTI, Myers, McCaulley, Quenk, & Hammer, 2003), the Minnesota Multiphasic Personality Inventory (MMPI-2RF; Tellegen & Ben-Porath, 2008), or the 16 Personality Factor Questionnaire (16PF, Cattell, Cattell, Cattell, Russell, & Bedwell, 2003). There is a potential to map out a series of personality traits in explaining world music preference, so teachers may use the information in making informed curricular and instructional decisions. While we speculate a cultural explanation for the Korean participants’ agreeableness and music absorption, researchers might carry out an in-depth qualitative investigation regarding the impact of cultural differences in explaining world music preference. The prominent role of imported music in the broader society, such as Latin American music in South Korea, and how the importation explains preference warrant further studies. Finally, the WMPRS contains some of the widest selection of world musical excerpts used in preference studies. Thirty-six excerpts from nine countries in three continents cover a lot, but this is still limited compared to the 195 nation states in the world. There is a need to develop a more varied pool of musical excerpts that could be used in world music preference studies. The more researchers understand world music preference, the more specific information music teachers have to make instructional decisions. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article. References Abeles, H. F. (1980). Responses to music. In D. A. Hodges (Ed.), Handbook of music psychology (pp. 105– 140). Lawrence, KS: National Association for Music Therapy. Abeles, H. F., & Chung, J. W. (1996). Responses to music. In D. A. Hodges (Ed.), Handbook of music psychology (2nd ed.; pp. 285–342). San Antonio, TX: IMR Press. Yoo et al. 13 Berlyne, D. E. (1971). Aesthetics and psychobiology. New York: Appleton-Century-Crofts. Benet-Martínez, V., & John, O. P. (1998). Across cultures and ethnic groups: Multitrait-multimethod analyses of the Big Five in Spanish and English. Journal of Personality and Social Psychology, 75, 729– 750. Brown, R. E. (1992). World music—past, present, and future. College Music Symposium, 32. Retrieved from https://symposium.music.org/index.php?option=com_k2&view=item&id=9510:world-music-pastpresent-and-future Boyle, J. D., & Radocy, R. E. (1987). Measurement and evaluation of musical experiences. New York: Schirmer. Brittin, R. V. (1991). The effect of overtly categorizing music on preference for popular music styles. Journal of Research in Music Education, 39, 143–151. doi:10.2307/3344694 Brittin, R. V. (2014). Young listeners’ music style preferences patterns related to cultural identification and language use. Journal of Research in Music Education, 61, 415–430. doi:10.1177/0022429413509108 Cattell, R. B., Cattell, A. K., Cattell, H. E. P., Russell, M. T., & Bedwell, S. (2003). The PsychEval Personality Questionnaire. Champaign, IL: Institute for Personality and Ability Testing. Cho, E. H. (2016). 음악 선호도와 성격, 행동 유형간의 상관관계 연구 [A study on the correlations between musical preference, personality, and behavioral patterns]. Sukmyeong University, Seoul South Korea. Costa, P. T., & McCrae, R. R. (1992). NEO PI-R professional manual. Odessa, FL: Psychological Assessment Resources. Demorest, S. M., Kelley, J., & Pfordresher, P. Q. (2017). Singing ability, musical self-concept, and future music participation. Journal of Research in Music Education, 64(4), 405–420. doi:10.1177/0022429416680096 Demorest, S. M., & Schultz, S. J. (2004). Children’s preference for authentic versus arranged versions of world music recordings. Journal of Research in Music Education, 52, 300–313. doi:10.1177/002242940405200403. Dollinger, S. J. (1993). Research note: Personality and music preference: Extraversion and excitement seeking or openness to experience? Psychology of Music, 21, 73–77. doi:10.1177/030573569302100105 Dunn, P. G., de Ruyter, B., & Bouwhuis, D. G. (2012). Toward a better understanding of the relation between music preference, listening behavior, and personality. Psychology of Music, 40, 411–428. doi:10.1177/0305735610388897 Finnäs, L. (1989). How can musical preferences be modified? Bulletin of the Council for Research in Music Education, 120, 1–58. Fung, C. V. (1992). Musicians’ preference and perception for world music. Southeastern Journal of Music Education, 4, 178–190. Fung, C. V. (1994). Undergraduate non-music majors’ world music preference and multicultural attitudes. Journal of Research in Music Education, 42, 45–57. doi:10.2307/3345336 Fung, C. V. (1995). Music preference as a function of musical characteristics. The Quarterly Journal of Music Teaching and Learning, 6(3), 30–45. Fung, C. V. (1996). Musicians’ and nonmusicians’ preferences for world musics: Relation to musical characteristics and familiarity. Journal of Research in Music Education, 44, 60–83. doi:10.2307/3345414. Fung, C. V. (2004). Pre-service music educators’ perceived reasons for preferring three foreign and distinctive Asian pieces. International Journal of Music Education, 22, 35–43. doi:10.1177/0255761404042373 Glasgow, M. R., Cartier, A. M., & Wilson, G. D. (1985). Conservatism, sensation seeking, and music preferences. Personality and Individual Differences, 3, 395–396. Goldberg, L. R. (1992). The development of markers for the Big-Five factor structure. Psychological Assessment, 4, 26–42. Greasley, A., Lamont, A., & Sloboda, J. (2013). Exploring musical preferences: An in-depth qualitative study of adults’ liking for music in their personal collections. Qualitative Research in Psychology, 10(4), 402–427. Gu, O. H. (2010). 청소년의성격유형과음악선호도간의상관관계연구 [Study of the relationship between adolescents’ personality and musical preference]. Sungsin University, Pusan South Korea. Hargreaves, D. J., & Colman, A. M. (1981). The dimension of aesthetic reactions to music. Psychology of Music, 9, 15–20. doi:10.1177/03057356810090010301 14 Psychology of Music 00(0) Hargreaves, D. J., Miell, D. E., & MacDonald, R. A. R. (2005). How do people communicate using music? In D. E. Miell, R. A. R. MacDonald, & D. J. Hargreaves (Eds.), Musical communication (pp. 1–25). Oxford: Oxford University Press. Indiana University Center for Postsecondary Research (n.d.). The Carnegie Classification of Institutions of Higher Education, 2015 edition. Bloomington, IN: Author. Jang, S. H. (2004). 중고등학생및대학생의음악양식에대한선호도 [Music style preferences of secondary school and college students in Korea]. 음악교육연구 [Journal of Research in Curriculum and Instruction], 8(2), 247–271. Jo, H. S. (2000). 고등학생의선호음악장르에따른성격특성비교 [Study of the relationship between personality and musical preference]. Pusan, South Korea: Kyungpook University. John, O. P., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. In L. A. Pervin, & O. P. John (Eds.), Handbook of personality: theory and research (pp. 102–138). New York: Guilford Press. Kang, Y. H. (2005). 청소년의음악선호도와감성지능과의관계연구 [Study of the relationship between musical preference and emotional intelligence of the youth]. Pusan, South Korea: Dong-a University. Kim, E. S. (2005). 성격유형과 음악선호간의상관성 연구 [The research of the correlation between the types of characteristics and the preferences of Muisc ]. Sukmyeong University, Seoul South Korea. Kim, S. Y., Kim, J. M., Yoo, J. A., Bae, K. Y., Kim, S. W., Yang, S. J., … & Yoon, J. S. (2010). Standardization and validation of big five inventory-Korean version (BFI-K) in elders. Korean Journal of Biological Psychiatry, 17, 15–25. Komarraju, M., Karau, S. J., & Schmeck, R. R. (2009). Role of the Big Five personality traits in predicting college students’ academic motivation and achievement. Learning and Individual Differences, 19, 47–52. Komarraju, M., Karau, S. J., Schmeck, R. R., & Avdic, A. (2011). The Big Five personality traits, learning styles, and academic achievement. Personality and Individual Differences, 51, 472–477. Laozi老子, & Fu, P-R. 傅佩榮 (2012). 《老子》解讀 [Laozi reader]. Taipei: New Century Publishing. LeBlanc, A. (1981). Effects of style, tempo, and performing medium on children’s music preference. Journal of Research in Music Education, 29, 143–156. doi:10.2307/3345023 LeBlanc, A., & Cote, R. (1983). Effects of tempo and performing medium on children’s music preference. Journal of Research in Music Education, 31, 57–66. doi:10.2307/3345110 LeBlanc, A., & McCrary, J. (1983). Effect of tempo on children’s music preference. Journal of Research in Music Education, 31, 283–294. doi:10.2307/3344631 Litle, P., & Zukerman, M. (1986). Sensation seeking and music preferences. Personality and Individual Differences, 7, 575–577. Meyer, L. B. (1956). Emotion and meaning in music. Chicago: University of Chicago Press. Myers, L. B., McCaulley, M. H., Quenk, N. L., & Hammer, A. L. (2003). MBTI® manual: A guide to the development and use of the Myers-Briggs Type Indicator® (3rd ed.). Mountain View, CA: CPP. Nichols, D. S., Padilla, J., & Gomez-Maqueo, E. L. (2000). Issues in the cross-cultural adaptation and use of the MMPI-2. In J. H. Dana (Ed.), Handbook of cross-cultural and multicultural assessment (pp. 247– 266). Mahwah, NJ: Lawrence Erlbaum. North, A. C., & Hargreaves, D. J. (1999). Music and adolescent identity. Music Education Research, 1, 75– 92. doi:10.1080/1461380990010107 North, A. C., & Hargreaves, D. J. (2008). The social and applied psychology of music. Oxford: Oxford University Press. Olsen, D. A. (1992). World music and ethnomusicology—understanding the differences. College Music Symposium, 32. Retrieved from https://symposium.music.org/index.php?option=com_ k2&view=item&id=3237:world-music-and-ethnomusicology-understanding-the-differences Radocy, E. R., & Boyle, J. D. (2012). Psychological foundations of musical behavior (5th ed.). Springfield, IL: Charles C Thomas Publisher. Rawlings, D., & Ciancarelli, V. (1997). Music preference and the five-factor model of the NEO Personality Inventory. Psychology of Music, 25, 120–132. Yoo et al. 15 Rawlings, D., Vidal, N., & Furnham, A. (2000). Personality and aesthetic preference in Spain and England: Two studies relating sensation seeking and openness to experience to liking for paintings and music. European Journal of Personality, 14(6), 553–576. Rentfrow, P. J., & Gosling, S. D. (2003). The do re mi’s of everyday life: The structure and personality correlates of music preferences. Journal of Personality and Social Psychology, 84(6), 12–36. Sandstrom, G. M., & Russo, F. A. (2011). Absorption in music: Development of a scale to identify individuals with strong emotional responses to music. Psychology of Music, 41, 216–228. doi:10.1177/0305735611422508 Schmitt, D. P., Allik, J., McCrae, R. R., & Benet-Martínez, V. (2007). The geographic distribution of Big Five personality traits patterns and profiles of human self-description across 56 nations. Journal of Cross-Cultural Psychology, 38, 173–212. Suh, K. H., & Park, J. Y. (2011). 음악선호와 성격의 관계 [Music preference and its relationship with personality traits], 한국 심리학회 [Korean Journal of Psychology], 30(1), 185–203. Tekman, H. G. (2009, August). Music preferences as signs of who we are: Personality and social factors. Paper presented at the 7th Triennial Conference of European Society for the Cognitive Sciences of Music, Jyväskylä, Finland. Tekman, H. G., & Hortaςsu, N. (2002). Music and social identity: Stylistic identification as a response to musical style. International Journal of Psychology, 37, 277–285. doi:10.1080/00207590244000043 Tellegen, A., & Atkinson, G. (1974). Openness to absorbing and self-altering experiences (‘absorption’), a trait related to hypnotic susceptibility. Journal of Abnormal Psychology,83, 268–277. Tellegen, A., & Ben-Porath, Y. S. (2008). MMPI-2-RF, Minnesota multiphasic personality inventory-2 restructured form: Technical manual. Minneapolis, MN: University of Minnesota Press. Vella, E. J., & Mills, G. (2016). Personality, uses of music, and music preference: The influence of openness to experience and extraversion. Psychology of Music, doi:10.1177/0305735616658957 Zajonc, R. B. (2001). Mere exposal: A gateway to subliminal. Current Directions in Psychological Science,10, 224–228. Zhang, Z. 張載, & Zhou, Y. 周贇. (2014). 《正蒙》詮譯 [Zhengmeng interpretation]. Beijing: Intellectual Property Publishing House. Zhuangzi, 莊子, & Fu, P-R. 傅佩榮. (2012). 《莊子》解讀 [Zhuangzi reader]. Taipei: New Century Publishing.