Exploring the nature of music engagement and its relation to personality among young adults

Abstract This study examined the relationship between music preferences (MP), listening styles (LS), functions of music (FoM), perceived rasa (music) and personality traits (PT – Big Five Factors). A sample of 77 young adults (M = 39; F = 38; M = 22.7 years) completed measures of the above constructs and data were analysed via correlations, one-way ANOVA, post hoc tests, and T-tests. Significant correlations were found between LS and PT; MP and PT; FoM and PT; FoM and emotion; and LS and FoM. Findings indicated stronger preferences for genres namely Romantic songs, Soft songs and Filmy (Sad) songs. Gender difference existed in terms of MP, perceived emotions and LS. Music listening mainly served as a ‘source of pleasure and enjoyment’ and which ‘calms, motivates, or reminds of past events’. Musical genres inducing santoṣa rasa were perceived significantly higher in female participants. Based on the findings, a ‘music engagement model for Young Adults’ describing their music behaviour, have been proposed.

Music can communicate and induce a range of powerful emotions (Juslin & Sloboda, 2001). Among the most frequently felt musical emotions, according to survey studies, are: happiness, calm, nostalgia, love, sadness, interest, hope, excitement, and longing, as well various synonymous emotion terms (Juslin & Laukka, 2004;Sloboda, 1992;Wells & Hakanen, 1991;Zentner, Grandjean, & Scherer, 2008). Hunter and Schellenberg (2010) concluded considering all of the available evidences that music listening often leads to emotional responses that are more complex than simple liking and disliking. Nonetheless, music-induced affective responses may differ from common definitions of emotion, both in quality and because they are not directed at the source.
Systematic efforts to understand emotions to music are quite recent (Juslin & Sloboda, 2010). Music psychology mostly came to explore more 'basic' perceptual and cognitive processes involved in music listening (Deutsch, 1999). In reviving Leonard B. Meyer's (1956) classic theory about musical expectations, Sloboda (1991) showed that 'cognition' and 'emotion' might not be far apart as one would think. Indeed, emotional responses to music require cognition (broadly defined). Sloboda would later be one of the researchers who helped to bring 'music and emotion' to the forefront, as a primary topic in music psychology (e.g. Thompson, 2009). In his commentary on the 'Current trends in the study of music and emotion' (Juslin & Zentner, 2002), Sloboda raised a question 'to what extent the research reported in this issue points to, explicates, and encourages an understanding of diversity and complexity in musical experience' (Sloboda, 2002, p. 242).
Concept of rasa or aesthetic relish or aesthetic mood is central to this approach to understanding affective experiences as dealt in the Natyashastra of Bharathamuni (commentary by Abhinavagupta, Eleven century). Sage Bharata conceptualized the rasa theory in the context of drama and theatre, which was later, extended to all poetry and other performing art forms. In this ancient Indian text of dramatics, all three components, i.e. physiological/behavioural, cognitive, and feelings are dealt with in detail. Bharatha suggests eight aesthetic moods or rasas corresponding to eight major emotions or bhavas. Natyashastra lists 49 emotional and non-emotional states.
Like all traditional Indian approaches, distinction is made between the major or basic emotions, and the accessory ones. Major emotions are permanent emotional dispositions, sentiments, or sthayi bhava. These transform other emotions into themselves. These are also considered innate. Permanent emotions are considered as permanent mental traces (samskaras). These when accompanied with source (vibhava), transitory emotions (vyabhicari bhava), and expressions (anubhava) can give rise to rasa. Transitory emotions are not innate and they give rise to permanent emotions and disappear after the permanent emotions show up. It is also suggested that transitory emotions represent the day-to-day normal life where similar emotions are expressed and experienced in changing situations. Accessory emotions are transitory states, i.e. vyabhicari bhava and are subordinate to the permanent emotional dispositions. These theories have dealt with the causes of emotions and also provide cues for managing heightened affect.
In answer to the question, 'how does music arouse emotions?' research has revealed a number of factors in the individual that could potentially affect emotional responses to music, such as the listener's age, gender, personality, musical training, music preference, and current mood (Abeles & Chung, 1996). Similarly, Gabrielsson (2001) suggested several factors in the situation that may potentially influence emotions, such as 'physical factors' (e.g. acoustic and visual conditions, time and place), 'social factors' (e.g. listening alone vs. with others, type of audience), and 'special occasions and circumstances' (e.g. a vacation). However, most studies have focused on causal factors in the music itself. Research on music and emotion has also revealed individual differences in preferences for pieces of music that evoke emotions like happiness, joy, sadness, and anger (Chamorro-Premuzic & Furnham, 2007;Rickard, 2004;Schellenberg, Peretz, & Vieillard, 2008;Zentner et al., 2008). Positive emotions were the most frequently felt reactions to music (Laukka, 2006). Moreover, it was shown that such positive emotions are related to increased well-being (Laukka, 2006). Young adults' subsequent transition to adulthood is notoriously stressful, placing demands on young people's coping resources and putting them at greater risk of developing mental health problems (Arnett, 1995(Arnett, , 2010Laiho, 2004). There is, therefore, a need to investigate everyday strategies that young people use to support their well-being. There is a growing recognition amongst scientists that musical behaviour is central to our humanity, to what it means to be human. Not least, we engage in musical activities because doing so sweetens and structures our leisure time and thereby makes us happy and increases our well-being (Hills & Argyle, 1998;Pinker, 1997). All these assumptions, however, lack an explanation for how music can lead to such positive effects (Schafer & Sedlmeier, 2010).
Viewed against this backdrop, this study aimed to explore the dynamic interactions of variables of interest namely MP, LS, FoM, rasa represented or induced by music, and personality (Big Five Factors) of young adults. Hypotheses are as follows: (1) Personality factors relate with music preference and nature of music engagement (time spent in music listening and listening styles).
(2) Respondents would indicate the emotions perceived by them while listening to some music genre/music piece. (3) Gender differences will exist in terms of music preferences and listening styles.
(4) Functions of music relate with personality factors and listening styles. (5) Respondents would favour a particular psychosocial context in which they prefer to listen to a particular music genre.

Respondents
A total of 77 respondents (male = 39; female = 38 with mean age = 22.7 years), pursuing UG and PG programs from different schools/institutions of Amity University, completed the survey.

Demographic data sheet
The data sheet was used to gain demographic details of the respondents (e.g. age, gender, socioeconomic status, and music background).

Music preference scale
Music Preference Scale developed by the researcher was used to figure out the music preference of the respondents. The scale included 23 music genres, to be rated on a seven-point Likert rating scale by the respondents to indicate their preference for listening to a particular music genre. This scale also included one open ended item asking respondents to add, if any, to the already listed genres. Each music genre was accompanied by one open ended item asking them to respond to 'when (time, place, mood, etc.) do you prefer listening to this music genre?' Cronbach's alpha of the scale has been found to be .85.

Music engagement scale
This Likert-type rating scale was used to assess the music engagement of the participants (cf. Wöllner, Ginsborg, & Williamon, 2010). It covered items pertaining to number of hours devoted per week by each participant and their preferred ways of listening to music.

FoM Scale
This Likert type rating scale (cf. Sloboda, 1999) comprised of 10 items was used. Cronbach's alpha for this scale has been .76.

Music emotion scale
This rating scale, proposed by author, has been adopted from Koduri and Indurkhya (2010) and Misra (2014). It has 11 rasa (with clusters of emotions) to be rated on seven-point scale. The reliability coefficient (Cronbach's alpha) is .83.

Big five inventory
To ascertain the personality type of the respondents 'big five inventory' (BFI) developed by John and Srivastava (1999) was used. The BFI contains five subscales: extraversion, agreeableness, conscientiousness, neuroticism, and openness. The inventory seeks responses on a 5-point rating scale ranging from 'totally agree' to 'totally disagree' . Certain items in the inventory are reverse scored. Reliability of the BFI ranges from .79 to .88.

Results
Results revealed that majority of 55.90% respondents actively listened to music up to 6 h, 27.3% listened between 6 and 10 h, and 13% listened more than 10 h per week. Active listening was defined as 'listening carefully or on purpose, instead of doing other things as well' . Only 3.90% respondents did not actively listen to music. Passive listening was defined as 'listening in the background, while you do other things' . 53.3% respondents listened up to 6 h, 19.5% between 6 and 10 h, and 24.5% listened more than 10 h per week in the background. 2.6% indicated 'not (listening) at all' in the background. The male respondents (M = 4.33, SD = 1.91), in comparison to female respondents (M = 3.55, SD = 1.69) were more engaged in active listening.
Respondents' responses to the open-ended question 'when do you prefer listening to particular music genre' were put in three categories: time, context and mood. Respondents indicated that they listened to Bollywood sad (slow) songs anytime (50%) being alone (100%) and when they were in bad (low) mood (60%) or felt gloomy/sad (40%). On the other hand, most of the respondents (87.5%) enjoyed listening to romantic (love) songs being alone but when they were in happy mood (90%). Genres namely rock songs (66.67%), hip-hop (85.71%), remix (57.14%) and rap (57.14%) were preferred in clubs/parties. Bhajan (88.89%) was preferred in morning whereas patriotic songs (100%) on special occasions. Respondents also showed preferences for particular genres in terms of actions they are involved in while listening to them. While driving respondents generally preferred romantic (love) songs, melodious film songs, English songs, sufi and rock songs; when felt like dancing, indicated for rap, hiphop, pop, remix, new age, Punjabi and rock songs; and to relax they preferred listening to genres like trance, instrumental, sufi, classic, jazz and ghazal.
The Table 1 below exhibits the preference for listening to selected music genres. Table 1 lists ratings for different music genres (7 = 'very much enjoyable'). Results of a one-sample test against the centre of the scale (test value = 4) indicate whether ratings were higher or lower from 'somewhat enjoyable' . A one-way ANOVA revealed a significant effect of music genre on preference ratings, F(22, 1748) = 17.43, p < .001, ƞ 2 = .18. Post-hoc tests (Bonferroni) revealed that Ghazal was rated higher at p < .005 than all other genres (difference to Sufi p < .021).
Romantic/love songs as well as film songs were generally favoured over other genres. On seven-point scales, mean ratings of 'romantic/love songs' were significantly higher in female respondents (M = 6.00, SD = 1.21) than male respondents (M = 5.33, SD = 1.61). Whereas, mean ratings of 'rock song' , 'pop' , 'blues' , 'trance' , 'jazz' , and 'instrumental music' were significantly higher in male respondents than female respondents.
Music genres were correlated with personality factors. Genres namely rock song, ghazal, patriotic songs, sufi, classic, hip-hop, English songs, blues, jazz, trance and instrumental music were significantly correlated with 'openness' . 'Extraversion' was correlated with genres namely patriotic songs, melodious film songs and folk; whereas 'neuroticism' was negatively correlated with rock and rap music genres and 'conscientiousness' with English songs (Table 3). Correlation coefficients were also calculated between LS and personality factors. The results are shown in Table 4. Significant correlations with LS were found for two personality factors. (Table 4) 'Neuroticism' was correlated with 'emotional listening' , r (77) = .28, p < .05, and 'openness' with 'analytical listening' , r (77) = .27, p < .05.
Respondents were asked what functions active or passive music listening have for them. Results are presented in Table 5. Results indicated that music mainly serves as a 'source of pleasure and enjoyment' , 'calms/releases stress/relaxes' , 'motivates' or 'reminds of past events' . Significant correlations were found between hours spend in active listening and music that 'motivates' , r (77) = .25, p < .05, and between passive listening and music that 'reminds of past events' , r (77) = .38, p < .01. Table 6 reveals results pertaining to the perceived rasa while listening to different music genres. Respondents rated their experienced rasa while listening to music ( Table 6). The highest ratings were yielded for Śṛṅgāra rasa (represents emotions like arousal, longing, desire, naughty, romance and love, M = 5.16, SD = 1.79), followed by Santoṣa rasa (represents emotions like joy, pleasure, excitement, and contentment, M = 4.58, SD = 2.10), and Śānta rasa (represents emotions like steady, rest, and peace, M = 4.25, SD = 2.07). Significant difference in rating of Santoṣa rasa were found between female respondents (M = 4.05, SD = 2.43) and male respondents (M = 5.10, SD = 1.59), t (77) = 2.25, p < .05.  Listening style 'visual and other associations' was found significantly correlated with five functions served by music listening, which were as follows: It reminds me of past events, r (77) = .33, p < .01; It evokes visual images, r (77) = .42, p < .01; It moves to tears/chills/other bodily reactions, r (77) = .24, p < .05; It functions as catharsis, r (77) = .44, p < .01; and It motivates, r (77) = .34, p < .01. This listening style was also found significantly correlated with four rasa namely Śṛṅgāra (r = .34, p < .01), Bhayānaka (r = .25, p < .05), Adbhuta (r = .27, p < .05), and Santoṣa (r = .25, p < .05) evoked by music listening. It indicates that respondents of this listening style could be more engaged and affected by the music they listen to.
Significant correlations with 'openness' personality factor were found with five functions served by music listening, indicating that music listening served maximum functions on respondents who are open to new experiences (Table 7).

Discussion
This study provides an overview of the nature of young adult's musical engagement in relation to their personality and gender. It has been hypothesized that personality factors relate with young adults' MP, and their nature of music engagement (time spent in music listening and LS); gender differences exist Table 5. functions of music listening for respondents (cf. sloboda, 1999), and correlation with listening hours per week (n = 77). * p < .05; ** p < .01. in terms of their MP and LS; they would indicate the rasa perceived by them while listening to some music genre/music piece; functions served by music relate with personality factors and LS; and listening to a particular music genre occurs in a particular psychosocial context. In previous research, listeners are characterized by variables that can have an influence on their music preference, such as age, gender, music experience, and personality (Schafer & Sedlmeier, 2010) to name a few. Results of this study too, indicated differences in terms of gender and relations in terms of personality factors on young adults' MP, LS, and rasa perceived. Males are more engaged in active music listening and listen to music 'analytically' whereas females consume more time in passive listening and listen to music 'emotionally' and use to 'move their body or parts of the body. ' In general, the highest ratings were yielded for Śṛṅgāra rasa (represents emotions like arousal, longing, desire, naughty, romance and love, followed by Santoṣa rasa (represents emotions like joy, pleasure, excitement, and contentment), and Śānta rasa (represents emotions like steady, rest, and peace). Difference in rating of Santoṣa rasa was found significant between female respondents and male respondents.

Functions of music listening
Generally, romantic (love) songs, and melodious film songs were favoured the most by the respondents, however, females rated 'romantic (love) songs' more important, whereas, males rated high on contradicting genres namely 'rock songs ' , 'pop' , in one side and 'blues' , 'trance' , 'jazz' , and 'instrumental music' on the other. Studies on the influence of gender on music preference revealed that males tend to prefer louder music (Staum & Brotons, 2000) and music with an exaggerated bass (McCown, Keiser, Mulhearn, & Williamson, 1997) more than females; females prefer softer, more romantic, and dance-oriented types of music such as pop or rhythm and blues (Christenson & Peterson, 1988;Maidlow & Bruce, 1999). The results of this study contradict the researches done by Christenson and Peterson (1988) and Maidlow and Bruce (1999) in which it was found that males tend to prefer music which is louder and is with amplified bass; and females prefer dance-oriented types of music such as pop or rhythm and blues. Moreover, preference in listening to the particular music genre varies according to the time, context, purpose and one's mood.
As far as the personality factors of young adults are concerned, results indicated its relation with variables MP, LS, and FoM. Young adults high in facet 'openness to experience' have wide preferences for music genres (12 out of 23 genres) in comparison to others. They tend to listen to music 'analytically' and music served maximum functions to them. Young adults high on 'neuroticism' listen to music more emotionally.
It has been found that people high in facet -openness to feelings -experience a broader range of emotions, accept their emotions, and experience complex emotions more often (Terracciano, McCrae, Hagemann, & Costa, 2003). Likewise, for extraversion (Wilt & Revelle, 2009), the tendency to experience activated positive states is probably more fundamental than features like gregariousness and social  (Watson, 2000). Extraversion is particularly notable for our purposes because extraverted people are much more likely to experience intense positive states, such as excitement, joy, and enthusiasm (Fleeson, Malanos, & Achille, 2002;Lucas, Le, & Dyrenforth, 2008;Shiota, Keltner, & John, 2006). As a result, extraversion is a credible alternative trait for understanding profound states like awe, which are experienced as both intense and rewarding (Bonner & Friedman, 2011). Results suggest that 'openness to experience' was positively related to Karuṇa and Adbhuta rasas, whereas 'extraversion' was positively related to Śṛṅgāra. Both factors were positively correlated with two common rasa namely Bibhatsa, and Santoṣa. Conscientiousness was negatively correlated with Karuṇa, Bhayānaka, Adbhuta and Vira.
Music mainly serves as a 'source of pleasure and enjoyment' , 'calms/releases stress/relaxes' , 'motivates' and 'reminds of past events' . Significant correlations were found between active listening and music that 'motivates' and between passive listening and music that 'reminds of past events' . Listening style 'visual and other associations' was found significantly correlated with five functions served by and four rasa evoked by music listening. It indicates that respondents of this listening style could be more engaged and affected by the music they listen to.
Previous researches argue that after exercise, music is the second most commonly used mood regulation strategy in young people (Thayer, Newman, & McClain, 1994). Various forms of musical engagement were related to well-being through emotion regulation strategies (Rickard, 2012). Although, this study didn't investigate correlations between young adults' musical engagement and their psychological well-being. However, it can be hypothesized that young adults' day-to-day musical engagements may predict their psychological well-being.
This study proposes a tentative Music Engagement Model for Young Adults (see Figure 1), which indicates gender differences in terms of MP, LS, types of listening, FoM and rasa perceived. MP and LS are correlated with the rasa perceived. Functions served by music listening are correlated with type of listening, LS and the rasa perceived. Personality factors are correlated with the rasa perceived, MP, FoM, LS and type of listening (active/passive). Moreover, music listening occur in a specific psychosocial context (e.g. place, time, mood etc.). Proposed model assumes that variables like types of rasa, preferences for music genres, LS and functions served by music listening may predict psychological well-being. The proposed model and its assumption are subject to verification. In conclusion, investigating young adults' musical engagement, their background, and their personality enhances our understanding of their musical behaviour. This study puts forth several questions to be answered. For example, how do they develop preference for music genres? How do they use music strategically to regulate their moods/emotions or to deal with their sufferings? When do they prefer listening to a particular music? How many hours they spend listening to particular music genre in a day or in a week? Future research could explore the musical experiences of young adults of both music and non-music background through in-depth interviews. Answers to these questions may help researchers to explain the musical behaviour of young adults that support their well-being.

Disclosure statement
No potential conflict of interest was reported by the authors.

Notes on contributors
Durgesh K. Upadhyay is an assistant professor of Music Education and Music Psychology.

Viveka Nand Tripathi is an assistant professor of Emotion and Cognition.
Manju Agrawal is a professor of Gender Issues, Adolescent Issues, Personality and Emotions.