Comparison of the Effect of Classical and Heavy Metal Music on Productivity and Mental Health

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Introduction

Music background

Music has historically been a key player in society and personal life. It is something that has been used for many purposes such as motivation, coordination, entertainment, communication, productivity, and other aspects of life. Individuals choose to have specific musical taste in genres which help them express and enjoy aspects of their lives. An interesting question sparks when wondering how different music genres, when compared to each other, influence a person’s productivity and mindset.  Previous studies have been able to develop a better understanding of music and how it affects people in todays society, both positively and negatively. We see that the various attributes of music such as tempo, pitch, volume, duration and etcetera, have given it a unique identity, which can be categorized into specific genres. In the research community, there has been great difficulty in gathering a universal agreement on defining musical genre (Scaringella, Zoia, & Mlynek, 2006). The general population, however, has been able to categorize music based on the styles that share a lot of similarities. Each genre has a unique way of influencing the mindset of people depending on their qualities and preferences. Music has been studied to have influences on a wide range of aspects in people’s daily lives.

Music influence on aspects of life

In the food aspect of life, studies show that “music genre has the ability to alter flavor pleasantness and impression of food stimuli” (Fiegel, Meullenet, Harrington, Humble, & Seo, 2014). This implies that music can activate certain sensory mechanisms in the body to enhance experiences in a way that can be beneficial to the user. When looking at the physical aspects of life, a study was done for sprinters to determine whether synchronous music can increase performance. It is concluded that “synchronous music results in better sprint performance than a no-music control”(Simpson & Karageorghis, 2006) but it was also noted; “motivational synchronous music does not affect performance the way regular synchronous music does” (Simpson & Karageorghis, 2006). It has also been stated that “importance of beats and the degree to which participants are able to synchronise their movements to the tempo of the beats have a greater affect than music with motivational qualities” (Terry, Karageorghis, Saha, & D’Auria, 2012). This is an implication that music deemed motivational does not always increase performance. However, when listening to music that is preferred and performing spatial rotation tasks, it was found that “liked music was associated with significantly better spatial rotation performance than disliked music.”(Perham & Withey, 2012). This study implies that preference can play a role in the productivity of certain tasks.

The Role of Classical Music and Heavy Metal

The statement of liked music on certain task performance is because not all tasks are the same, there are studies that conflict the previous one which show that performance does not correlate with musical preference. In fact, there are musical genres which seem to increase productivity and learning universally. More specifically, it has been noted that Mozart’s classical music seems to have an influence on the process of learning. A study related to Mozart’s music and temporal tasks found that “Mozart’s music enhances the learning of spatio-temporal rotation tasks by activating task-relevant brain areas”(Jaušovec, Jaušovec, & Gerlič, 2006). Furthermore, studies done across different age groups and demographics were also conducted to see whether classical music can be just as effective. It was concluded that “exposure to different types of classical music can enhance performance on a variety of cognitive tests but these effects are possible if there are changes in emotional state. Also, the effects can be generalized across cultures and age groups.”(Schellenberg, Nakata, Hunter, & Tamoto, 2007) This implies that classical music can play a role in the productivity and creativity of individuals but on the condition that it has to be able to “induce reliable differences in arousal and mood” (Schellenberg et al., 2007).

There are also conflicting studies that state some preferred musical genres can influence individuals in a negative way. A study done on heavy metal music stated that “60% of drug using youngsters designated heavy metal as their musical choice” (King, 1988). This implies that majority of young individual abusing drugs seem to have a preference to heavy metal music. The reason being that drug use relates to counterproductive activity (Mangione & Quinn, 1975). If music such as heavy metal can induce drug use, then overall understanding from these studies can infer that some genres, regardless of preference can potentially hinder productivity.

Music and Mental Health

The ability to induce difference in arousal and mood has a great relationship with another aspect of human life; the mental health aspect. Since the specialization and evolution in the field of psychology, it has been studied that “anxiety disorders are the most prevalent mental health conditions”(Craske & Stein, 2016). Anxiety disorders include a wide variety of sub-disorders. Disorders such as “separation anxiety disorder, selective mutism, specific phobias, social anxiety disorder, panic disorder, agoraphobia, and generalised anxiety disorder are common and disabling conditions that mostly begin during childhood, adolescence, and early adulthood”(Craske & Stein, 2016). It has also been stated in this study that “since 2013, one in nine people worldwide have had anxiety disorder in the past year” (Craske & Stein, 2016). There are many causes of anxiety which have been studied and multiple psychological factors tend to play a role. In one study about music performance anxiety, it was found that “Thirty-nine per cent of the musicians had indicators of music performance anxiety. The most commonly reported causes were repertoire difficulty (57%), concerns about audience response (52%), and self-pressure (51%).”(Osório, Burin, Nirenberg, & Barbar, 2017). Also, this study stated the ways the musicians coped with the problem “included breathing/relaxing techniques (66%) and increased practice (53%) which were regarded as efficient by at least 49% of the musicians.” (Osório et al., 2017).   Studies have also shown that music can be a great mechanism when trying to cope with these mental anxiety issues. One study that explores reducing anxiety amongst breast cancer patients with music found that “Music therapy is found to have positive effects on decreasing state anxiety score.”(Li, Zhou, Yan, Wang, & Zhang, 2012).

Overall Outlook and Research Question

The general trend to note is that if coupled with the right environmental and emotional cues, productivity and mood can be greatly impacted. The few ways that productivity can be optimized while listening to music is if the music is able to alter the mood of the individual or activate areas of the brain related to completing tasks (Schellenberg et al., 2007).  Also, it can be noted that the ability to alter mood with music also plays a key role when trying to deal with anxiety or stress. When faced with a stressful event, those that can alter their mood with music can improve their mental health and prevent and detrimental outcomes in their daily lives. The major question of this paper is to explore how two different forms of music impact a person’s productivity and their mental health. When comparing the different types of music, we wish to see what the implications are in an individual and if they can have better results with one genre as opposed to another. For this study the general question arises, does classical music have a better impact on productivity and mental health in comparison to heavy metal music? The way to test this is going to be by taking a two-step quantitative approach using the understandable techniques of social research.

METHODS

A two-step quantitative approach was taken when conducting this study. Both approaches involved using students at Bond University to answer questions while listening to the heavy metal and classical music genres. Their results were then collected and interpreted on data graphs. For the first step of the quantitative portion, a survey was set up to examine the mental health effects of classical music versus heavy metal music. The survey comprised of 3 questions which included a scale ranging from 1 to 10 to assess the mood of an individual when listening to these types of genres. A total of 15 participants were selected and sampled a 40 second cut of Mozart’s allegro composition, then answered the first three questions of the questionnaire. After listening to Mozart and answering the first three questions, participants then listened to Breaking Benjamin – Blow me away song for 40 seconds and answer the same questions again on a separate sheet. The questionnaire included the following statements:

  1. On  a scale of 1 to 10 how happy did you feel listening to this track (one being not happy, ten being really happy)
  2. On a scale of 1 to 10, how calm did you feel after listening to this track (one being not not, ten being really calm)
  3. On a scale of 1 to 10, would you prefer to relax to this song (1 being no 10 being definitely)

After the completion of the first questionnaire, results were recorded (table 1). The second portion of the quantitative analysis was conducted afterwards. This portion involved 10 students that were split up into two groups. The first group of five students listened to Mozart’s allegro composition and completed a 60-question simple mental math sheet (figure 1). The question set included simple, one digit, addition and subtraction questions. The students were given one minute to complete as many questions as possible and the results were obtained (table 2). The second group of five students listened to Breaking Benjamin Blow me away song and completed a 60-question simple mental math sheet (figure 1). The students were given one minute to complete as many questions as possible and the results were obtained and recorded (table 2)..

The number of participants sampled in this study totaled 25 students. The first portion consisted of 15 students and the second portion consisted of 10 students. Sampling was done in an attempt to randomize the selection. This was done by selecting students at Bond University at random during different time intervals and ensuring they were willing to partake in the experiment. The time intervals ranged from 9am to 5pm to try and cover school operating hours so that majority of students can be taken into account for this study.

Ethical considerations such as gender and background were also taken to consideration. This was done by attempting to equalize both males and females participating in the study and by selecting the most diverse group of students that were available. This was done so that a gender and racial biased did not develop in the results.

The results were recorded and analyzed for further discussion. After the completion of the first questionnaire, results were recorded (table 1). The three values for each music group values were added and averaged to give a score rating from 1-10, with 10 being best mood. These were then interpreted into a bar graph (figure 2). The graph in figure 1 was meant to compare and discuss the individuals personal rating of mood when listening to the musical genres. They were discussed to determine whether the data was relevant and whether it would stand as a fair means to interpret the implications. Results from table 2 were converted and interpreted on a bar graph (figure 3) to show the number of right answers when listening to Mozart’s Allegro in comparison to Breaking Benjamin – Blow me away. The graph in figure 3 was made to analyze how each musical genre impacted the correctness of the mathematical problems. The use of simple mathematical questions became a way to measure overall productivity. Considerations about mental capability and preferences to mathematical problems were also discussed in the results. Discussions about the validity and reliability of the experiment were also explored.

REFERENCES

Azoulay, E., Chaize, M., & Kentish-Barnes, N. (2013). Music therapy for reducing anxiety in critically ill     patients. JAMA, 309(22), 2386-7

Craske, M. G., & Stein, M. B. (2016). Anxiety. The Lancet, 388(10063), 3048–3059. https://doi.org/10.1016/S0140-6736(16)30381-6

Fiegel, A., Meullenet, J. F., Harrington, R. J., Humble, R., & Seo, H. S. (2014). Background music genre can modulate flavor pleasantness and overall impression of food stimuli. Appetite, 76, 144–152. https://doi.org/10.1016/j.appet.2014.01.079

Jaušovec, N., Jaušovec, K., & Gerlič, I. (2006). The influence of Mozart’s music on brain activity in the process of learning. Clinical Neurophysiology, 117(12), 2703–2714. https://doi.org/10.1016/j.clinph.2006.08.010

Li, X.-M., Zhou, K.-N., Yan, H., Wang, D.-L., & Zhang, Y.-P. (2012). Effects of music therapy on anxiety of patients with breast cancer after radical mastectomy: a randomized clinical trial. Journal of Advanced Nursing, 68(5), 1145–1155. https://doi.org/10.1111/j.1365-2648.2011.05824.x

Mangione, T. W., & Quinn, R. P. (1975). Job satisfaction, counterproductive behavior, and drug use at work. Journal of Applied Psychology, 60(1), 114-116.http://dx.doi.org/10.1037/h0076355

Osório, F. L., Burin, A. B., Nirenberg, I. S., & Barbar, A. E. M. (2017). Music performance anxiety: Perceived causes and coping strategies. European Psychiatry, 41, S110. https://doi.org/10.1016/j.eurpsy.2017.01.1883

Paul King (1988) Heavy metal music and drug abuse in adolescents, Postgraduate Medicine, 83:5, 295-304, DOI: 10.1080/00325481.1988.11700240

Perham, N., & Withey, T. (2012). Liked Music Increases Spatial Rotation Performance Regardless of Tempo. Current Psychology, 31(2), 168–181. https://doi.org/10.1007/s12144-012-9141-6

Scaringella, N., Zoia, G., & Mlynek, D. (2006). Automatic genre classification of music content. IEEE Signal Processing Magazine, 23(2), 133–141. https://doi.org/10.1109/MSP.2006.1598089

Schellenberg, E. G., Nakata, T., Hunter, P. G., & Tamoto, S. (2007). Exposure to music and cognitive performance: Tests of children and adults. Psychology of Music, 35(1), 5–19. https://doi.org/10.1177/0305735607068885

Simpson, S. D., & Karageorghis, C. I. (2006). The effects of synchronous music on 400-m sprint performance. Journal of Sports Sciences, 24(10), 1095–1102. https://doi.org/10.1080/02640410500432789

Terry, P. C., Karageorghis, C. I., Saha, A. M., & D’Auria, S. (2012). Effects of synchronous music on treadmill running among elite triathletes. Journal of Science and Medicine in Sport, 15(1), 52–57. https://doi.org/10.1016/j.jsams.2011.06.003

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