Adaptation and Validation of Short Test of Music Preference Scale for Students With Music and Non-Music Majors

Music is a universal phenomenon however, despite its unified properties, the taste and preference of music may still vary as a function of ethnicity and culture. So, the present study aimed to adapt and validate the short test of music preference scale for music and non-music Pakistani students. In Phase I, the cultural adaption of the scale was carried out while the content validity index (Lawshe, 1975) was also established. However, in phase II, the Short test of Music Scale (STOMP) was validated, yielding confirmatory factor analysis. For the empirical evaluation, a sample of 561 students, including both 286 music and 275 non-music students of undergraduate level with the age range of 18-26 years were recruited. The psychometric evolution of STOMP turned into excellent validity and reliability estimates for first-order constructs. Moreover, strict measurement invariance was established for STOMP across music and non-music students. The validation of this scale would be a little effort to pave the way for music psychology to make research available to measure the construct indigenously.

Music Preference Dimensions and Personality Traits Among University Students

The present study explored the relationship between music reference dimensions and personality trait. This study comprised of three stages. In Stage-I, adaptation of Short Test of Music Preference Scale (STOMP; Rentfrow & Gosling, 2003) was done. In Stage-II the psychometric properties of adapted STOMP Scale and NEO-PI-R (Costa & McCrea, 1992) were determined on a sample of 60 students (20-25 years). Stage-III involved measuring the relationship between music preference dimensions and personality traits on sample of 250 students age range of 20-25 years. Results revealed that extraversion, openness to experience, and agreeableness showed positive association with intense and rebellious music, upbeat and conventional music, and reflective and complex music. Whereas extraversion and openness to experience was negatively associated with energetic and rhythmic music. Additionally, neuroticism was negatively related with reflective and complex music, and agreeableness has negative relation with intense and rebellious music. Conscientiousness has negative relationship with reflective and complex, intense and rebellious, and upbeat and conventional; while exhibited positive relationship with energetic and rhythmic music. Future implications of the study were also discussed.

THE EFFECT OF MUSIC GENRE AND MUSIC-PREFERENCE DIMENSION ON ACCEPTABLE NOISE LEVELS IN LISTENERS WITH NORMAL HEARING

ABSTRACT Background: The acceptable noise level (ANL) is the maximum level of background noise that an individual is willing to accept while listening to speech. The type of background noise does not affect ANL results except for music (Gordon-Hickey & Moore, 2007; Nàbĕlek et al, 1991). Purpose: The purpose of this study was to determine if ANL differed due to music genre or music genre preference. Research Design: A repeated-measures experimental design was employed. Study Sample: Thirty-three young adults with normal hearing served as listeners. Data Collection and Analysis: MCL and BNL were measured to twelve-talker babble and 5 music samples from different genres: blues, classical, country, jazz, and rock. Additionally, music preference was evaluated via rank ordering of genre and by completion of the STOMP questionnaire. Results: Results indicated that ANL for music differed based on music genre; however, the difference was unrelated to music genre preference. Also, those with low ANLs tended to prefer the Intense and Rebellious music-preference dimension compared to those with high ANLs. Conclusions: For instrumental music, ANL was lower for blues and rock music compared to classical, country, and jazz. The differences identified were not related to music genre preference; however, this finding may be related to the music preference dimension of Intense and Rebellious music. Future work should evaluate the psychological variables that make up music-preference dimension to determine if these relate to our ANL.

Relationship Between Personality and Music Preferences Among University Students

This study analysed the relationship between Big Five personality traits and music preferences among university students. Big Five Inventory (BFI) and Short Test of Music Preferences (STOMP) was used to assess personality traits and music preferences. Questionnaires were distributed through social media platforms to college and university students aged 19 to 26. A total number of 145 respondents participated in this study. The results showed Agreeableness, Conscientiousness, and Openness were the most prevalent personality traits among respondents and Energetic-Rhythmic (ER) was the most preferred music. The correlation analysis showed that there is a significant correlation between Openness and energetic-rhythmic (ER) music. On the other hand, there was no significant correlation between other traits (Conscientiousness, Extraversion, Agreeableness, and Neuroticism) with music preference dimensions such as Intense-Rebellious (IR) and Energetic-Rhythmic (ER). The inconsistencies in the literature and our findings suggested more studies are needed to understand the influence of personality on music preferences.

Students' music preferences towards classical music

Music preferences can be related to many groups of factors, as LeBlanc’s Interactive theory of music preference suggests. In this research four factors from the model were explored in relation to students’ preference towards classical music: students' age, their gender, their attendance of extracurricular music activities and familiarity of music pieces. Fifteen excerpts of classical music pieces from different musical-historical periods were presented to a sample of 516 students, 7 to 18 years old. Results reveal moderate negative correlation between age and preference towards classical music. Higher preference was found in female students and for familiar pieces. Students that attended extracurricular music activities preferred only some excerpts more. Findings provide strong support to LeBlanc’s model. Implications for teaching are proposed.

What to Expect When the Unexpected Becomes Expected: Harmonic Surprise and Preference Over Time in Popular Music

Previous work demonstrates that music with more surprising chords tends to be perceived as more enjoyable than music with more conventional harmonic structures. In that work, harmonic surprise was computed based upon a static distribution of chords. This would assume that harmonic surprise is constant over time, and the effect of harmonic surprise on music preference is similarly static. In this study we assess that assumption and establish that the relationship between harmonic surprise (as measured according to a specific time period) and music preference is not constant as time goes on. Analyses of harmonic surprise and preference from 1958 to 1991 showed increased harmonic surprise over time, and that this increase was significantly more pronounced in preferred songs. Separate analyses showed similar increases over the years from 2000 to 2019. As such, these findings provide evidence that the human perception of tonality is influenced by exposure. Baseline harmonic expectations that were developed through listening to the music of “yesterday” are violated in the music of “today,” leading to preference. Then, once the music of “today” provides the baseline expectations for the music of “tomorrow,” more pronounced violations—and with them, higher harmonic surprise values—become associated with preference formation. We call this phenomenon the “Inflationary-Surprise Hypothesis.” Support for this hypothesis could impact the understanding of how the perception of tonality, and other statistical regularities, are developed in the human brain.

The Influence of Music Preference on Exercise Responses and Performance: A Review

Listening to music has been repeatedly shown to have ergogenic benefits during various modes of exercise, including endurance, sprint, and resistance-based activities. Music is commonly incorporated into training regimens by recreational exercisers and competitive athletes alike. While specific modalities of exercise elicit varying physiological responses, listening to music has been shown to modulate many of these responses (i.e., heart rate, catecholamines, muscle activation) often leading to improved performance. Furthermore, listening to music during exercise may positively impact psychological (i.e., mood, motivation) and psychophysiological (i.e., rate of perceived exertion, arousal) changes, which may allow for favorable responses during an exercise challenge. However, there is mixed evidence regarding music’s efficacy, which may be mediated through differences in music selection and preference. Emerging evidence has shown that, whether an individual prefers or does not prefer the music they are listening to during exercise greatly influences their ergogenic potential in addition to physiological, psychological, and psychophysiological responses to exercise. From a practical standpoint, music may be controlled by the individual through headphones but is often played communally over speakers in locker rooms, gyms, and health clubs, which may have consequences on performance and training. The following review will describe the physiological, psychological, and psychophysiological responses to exercise while listening to music and how music preference may particularly alter them. Current knowledge and new evidence on how music preference factors into enhancing performance in various modes of exercise will be further discussed, incorporating practical considerations for individuals and practitioners in real-world applications to optimize performance.

On the Effect of Background Music Preference on Emotions During Walking

Objective: To study the influence of background music preference on emotion during walking. Method: The experiment is a single factor research design, and the independent variable is the type of background music (preferred, disliked, no background music). The subjects performed three 20-minute walking tasks with no background music, favorite background music, and disliked background music during the experiment. After the experiment, the positive and negative affect scales (PANAS) were filled to compare the difference between positive and negative emotion in the three tasks through statistical analysis. Result: It was found that people’s preference for background music affected the foreground work emotions. Subjects’ positive emotions increased under the background music they liked, and their negative emotions aggravated under the background music they disliked.

Emotion Recognition and Regulation Based on Stacked Sparse Auto-Encoder Network and Personalized Reconfigurable Music

Music can regulate and improve the emotions of the brain. Traditional emotional regulation approaches often adopt complete music. As is well-known, complete music may vary in pitch, volume, and other ups and downs. An individual’s emotions may also adopt multiple states, and music preference varies from person to person. Therefore, traditional music regulation methods have problems, such as long duration, variable emotional states, and poor adaptability. In view of these problems, we use different music processing methods and stacked sparse auto-encoder neural networks to identify and regulate the emotional state of the brain in this paper. We construct a multi-channel EEG sensor network, divide brainwave signals and the corresponding music separately, and build a personalized reconfigurable music-EEG library. The 17 features in the EEG signal are extracted as joint features, and the stacked sparse auto-encoder neural network is used to classify the emotions, in order to establish a music emotion evaluation index. According to the goal of emotional regulation, music fragments are selected from the personalized reconfigurable music-EEG library, then reconstructed and combined for emotional adjustment. The results show that, compared with complete music, the reconfigurable combined music was less time-consuming for emotional regulation (76.29% less), and the number of irrelevant emotional states was reduced by 69.92%. In terms of adaptability to different participants, the reconfigurable music improved the recognition rate of emotional states by 31.32%.