Music and Stress

The Effects of Music on Stress

(A study on how to reduce stress levels)

Suji Grant, Sina Rostam, and Anthony Van Divner

Introduction:

Stress is a prominent issue in today’s world, with the average American working a fifty-hour week it’s no wonder that we have developed problems such as hypertension and obesity. Stress is caused by anything in the environment that requires the body to adjust its physical processes to adapt. How the body reacts to these changes is different in everyone because everyone has their own coping mechanisms. Generally we react to these changes by physical, emotional, and chemical responses in the body. When stress accumulates in our body with little to no alleviation there is the possibility to develop a plethora of health problems such as: a compromised immune system, a decrease in bone density, high blood pressure, ulcers, muscle aches, weight gain, and heart disease. Our study looks at the effects of different types of music on the stress levels of students taking a critical thinking exam. We are looking to see which of the three types of music (rock, classical, and techno) cause the lowest stress levels in relation to the control.

Being in a stressful environment can cause high blood pressure and can cause the body to release abnormal amounts of cortisol. Cortisol is the main stress hormone that the body releases during times where there is high sympathetic activity, which increases blood pressure and decreases immune response. Normal concentrations of cortisol vary from person to person but typically levels rise and fall throughout the day, being highest in the morning and lower in the evening. However, in stressed out individuals cortisol levels are abnormally high throughout the day and the normal fluctuations of cortisol is absent. Chronically high cortisol levels can cause a variety of problems; the most dangerous being hypertension because cortisol acts as a vasoconstrictor. Conversely, too little cortisol in a person’s system can have adverse effects. If an individual with low cortisol levels is exposed to high stress, they can die from circulatory failure. There are many different types of stress and instead of a different response to each type the body has a uniform response to all of them. Once stress is induced the nervous system sends a signal to the hypothalamus to secrete corticotropin-releasing hormone (CRH). CRH is transported to the anterior pituitary by way of the hypothalmo-pituitary portal vessels. Once in the anterior pituitary CRH stimulates the release of adrenocorticotropic hormone (ACTH) which gets released into the circulatory system. In the blood ACTH makes its way to the cortex of the adrenal glands, which is located above the kidneys, to induce the secretion of cortisol. The sympathetic nervous system plays a crucial role in the response to stress. It is better known for the “fight or flight” response it elicits in our body to cope with a high stress situation, like running from a tiger. The activation of the sympathetic nervous system also induces the release of the hormone epinephrine (also known as adrenaline) from the adrenal medulla. Once epinephrine is released into the body it accelerates heart rate, increases blood pressure, and inhibits digestion. The activation of the sympathetic nervous system also increases hepatic and muscle glyconeogenesis, which acts to provide a quick and ready source of glucose. There is also an increased breakdown of adipose tissue, which provides glycerol for gluconeogenesis and fatty acids for oxidation. There is also a decrease in skeletal muscle fatigue, increased cardiac function, and blood is shunted to vital organs and away from the extremities and skin. The parasympathetic system plays a less crucial role in stress because the activation of the sympathetic nervous system suppresses the parasympathetic nervous system. Other hormones associated with stress include: aldosterone, vasopressin (ADH), growth hormone, glucagon, and beta-endorphin.

The effects of cortisol levels in the body during stress can be broken down into five classifications. First, cortisol has effects on organic metabolism and is able to stimulate protein catabolism in bones, lymph, and muscles. This plays an important role because when a human undergoes a stressful life situation, the release of amino acids due to protein catabolism provides a good source of glucose for energy and can also act to repair tissue damage sustained in an injury. Second, there is increased vascular reactivity that increases the ability to maintain vasoconstriction in response to stimuli. Third, cortisol also provides added protection from the damaging effects of stress on the body, but as stated earlier, too much cortisol in the body all the time can cause adverse health effects. Fourth, the increased cortisol levels can inhibit inflammation and other specific immune responses. By doing this, the body will be susceptible to infection with a compromised immune system. Fifth, constant high cortisol levels in the body also inhibit nonessential bodily functions such as reproduction and growth. This aspect is more important for children who are under constant stress as opposed to adults because adults have already finished growing, but children are in a constant state of change and the inhibition of growth can lead to impeded development.

Other experiments on the effects of music on stress have already been completed. The paper The Effect of Live Music Decreasing Anxiety in Patients Undergoing Chemotherapy Treatment by Ferrer et al explains the effects of music on people undergoing a highly stressful situation; chemotherapy. The study showed a “statistically significant improvement for the experimental group on the measures of anxiety, fear, fatigue, relaxation, and diastolic blood pressure” so overall music had a positive effect on the chemotherapy patients. This study is very similar to our study because we are both looking at stress levels and if those levels can be lowered by listening to music. Our studies differ in that Ferrer et al did not provide different types of music in their study to see if there was a correlation between different types of music and stress levels. A different article, Stress Reduction through Listening to Indian Classical Music during Gastroscopy by Kotwal et al looked at the calming effects of Indian classical music on patients having a gastroscopy. The study had a sample size of 104 patients and out of the 104, fifty-four received Indian classical music while going through their procedure and the remaining fifty received no music at all. This study indicated “the background Indian classical music is efficacious in reducing psychological distress during a gastroscopic examination”. Kotwal et al found that the patients who received the Indian classical music treatment had a significantly lower heart rate, blood pressure, and respiratory rate than those who received no music treatment while having their procedure.

We hypothesize that individuals listening to classical music while taking the test will have a lower heart rate and GSR measurement giving them a lower stress level compared to the control. We also hypothesize that rock music will cause subjects to have an increase in heart rate and GSR measurement causing them to be more stresses out. We also think that listening to techno music while taking the test will cause subjects to have a stress level intermediate to that of classical music and rock music. This is due to the fact that techno music has a progressive beat, meaning that some parts of the song will have slow parts and some parts will have fast parts. Techno music also does not have lyrics, which could cause the subject to react. Also we hypothesize that subjects listening to no music during the test will experience lower stress levels than that when compared to subjects listening to music and taking the test. This should produce a varying level of stress in the subjects while they take the critical thinking stress test. Rock music is loud with a constant beat throughout the length of the song that should produce elevated stress levels in the subjects. Also, the song we chose for rock music has a lot of screaming in the lyrics and deep base which may cause the subject to become excited and pumped up. We think that listening to classical music while taking the test will yield lower heart rate and GSR response because classical music does not have lyrics or beats that would cause the subject to have a large response. We will measure the individual’s stress levels by looking at their GSR and heart rate and then compare those values to see if there is any correlation. We will look at average heart rate, percent change in heart rate, and average GSR values to see if there is any distinction between the music types while taking the test.

Methods:

This study consisted of sixteen subjects, nine male and six female, all between the ages of twenty-two and thirty-five. Each subject was asked to fill out a questionnaire detailing their caffeine intake, music preference, age, type of employment, exercise habits, and stress level as these are factors that may effect our the study. Subjects were then hooked up to galvanic skin response (GSR) sensors with lubricating gel attached to their first and second fingers of their non-dominant hand so that during the test they could write with their dominant hand. Subjects were also hooked up to the ECG sensors to record heart rate in beats per minute; one lead on their upper right chest inferior to the clavicle and lateral to the sternum attached to the white wire and two leads on their right and left lower rib cage attached to the black and red wires respectively. This was done in order to mimic the Einthoven triangle, which looks at the electrical activity of the heart. The experiment was conducted in a quiet room so outside noise would not affect the study. Subjects were asked to sit quietly while the program calibrated for thirty-seconds. We did a thirty-second calibration as opposed to a ten-second calibration because we wanted more accurate measurements out of the equipment.

The experiment was conducted as follows: To establish a negative control subjects sat in a quiet room for one minute to establish a baseline heart rate and GSR reading. They were then asked to begin taking a Mensa IQ test (the critical thinking exam to induce stress) for two minutes to establish a control level of stress without sound. Participants then rested for a minute to give their heart rate and GSR a chance to return to normal which would establish a new baseline. For the first treatment subjects listened to one of the three types of music chosen at random (classical, rock, or techno) for one minute to see how much of their stress is due to the music alone. Subjects then took a test for two minutes while listening to the first music type. Again subjects relaxed to obtain a new baseline reading of heart rate and GSR. Subjects listened to the second type of music chosen at random for one minute. They then listened to music type two and took the test for two minutes. Participants relaxed for one minute to establish new baseline and then listened to music type three for one minute. Finally subjects listened to music type three and took test for two minutes.

Data was obtained and analyzing using the Biopac software, hardware, and a Dell and Mac computer. We used Biopac lesson nine for GSR and lesson five for ECG for our experiment and followed the protocol for calibration that was detailed in our lab notebooks. Heart rate data was analyzed by using the I-bar to select the entire section and recorded the mean in beats per minute. GSR data was analyzed by using the I-bar function. We measured the three highest peaks in a section and averaged them together in order to obtain the mean GSR value. Once we had all of our data in the correct format, we used Microsoft Excel in order to produce graphs that made our results easy to see.

Results:

Table 1A: Average Heart Rate vs. Music Type shows the differences in average beats per minute depending on the music the subject was listening to. This graph shows the error bars for the study.

Table 1B: Average Heart Rate vs. Music Type is the same graph as table 1A only in this graph we have altered the scale on the y-axis to make the differences in heart rate more apparent. The blue bars represent a baseline measurement where the subject is not listening to any music or taking a test. This measurement is used to determine how much heart rate increased or decreased after each treatment. The red bars represents the subject listening to music but not taking a test. This is used to tell how much of the stress the subject is experiencing is due to music alone. The green bars represent the average heart rate of the subjects while they were taking the test and listening to music. From this graph we can tell heart rate during the test was lowest when subjects were listening to classical music. When subjects took the test without music, the control, they had the second lowest heart rate followed by techno music. Listening to rock music while taking the test caused subjects to have the highest heart rate. When subjects were just listening to music they had the lowest heart rate while listening to classical music followed by techno and then rock. Another point to notice on this graph is the base line measurements. We can see that the baseline measurements taken before the classical music and rock music treatments are very similar. However the baseline measurement taken prior to the techno music treatment is elevated compared to that of classical music and rock music.

Table 2: Percent Change in Heart Rate vs. Music Type shows the percent change in listening to music without the test to taking the test with music. This graph illustrates the change in heart rate due to the test alone. From this graph we can see that listening to classical music yielded the smallest percent change. Subjects listening to rock music while taking the test had the highest percent change in heart rate. Subjects listening to techno music had a low percent change but still higher than classical. The control had the second highest percent change in heart rate due to testing alone. Although this graph is of percent change from just listening to music to taking the test with music it should be noted that the control is sill just a percent change measurement from baseline to taking the test without music.

Table 3: Percent Change in Heart Rate vs. Music Type illustrates the change in heart rate due to listening to music only. In this graph we see that techno music had the smallest percent change. Classical music has the second smallest percent change. Rock music had the highest percent change in heart rate.

Table 4A: GSR Value vs. Music Type shows the average GSR values for baseline to music only, music only to test with music, and baseline to test with music. In this graph we have shown error bars for GSR values.

Table 4B: GSR Value vs. Music Type is the same as table 4A graph only this one does not have error bars so we can see the values for GSR. The blue bars represent the change in GSR from baseline to music only. The red bars represent the change in GSR from music only to test with music. The green bars represent the GSR change from baseline to test with music. In this graph we can see that the control had the smallest change in GSR from baseline to test with music, classical music had the second smallest, followed by techno music. Rock music had the greatest change in GSR value from baseline to test with music. Classical music has the smallest change from baseline to music only followed by techno and then rock. Rock music had the smallest change from music only to test with music followed by classical followed by techno music.

Discussion:

Based on table 1 A and B: Average Heart Rate vs. Music Type we can conclude that that subjects who listened to classical music during the test had the lowest heart rate which suggests that classical music reduced their stress. Subjects who listened to rock music while taking the test had the highest heart rate, which leads us to conclude that taking the test with rock music increases stress levels. If we look only at the effects of music without taking the test on heart rate we find that listening to classical music yields the lowest heart rate and thereby induces the least amount of stress whereas rock music creates the most. However, we found that listening to music by itself does cause some excess level of stress because the control (silence) has the lowest average heart rate for all groups. The error bars are large on this graph meaning that we cannot accept these results. Ideally we would like to see a 95% confidence level in order for us to accept the data. This is due to the fact that we had outliers in the data. In our outliers we had people with previous health conditions and we had fit and unfit people in our sample size. This will result in a spread of the standard deviation, which would skew our confidence level in the data. It was interesting to see a uniform increase in mean heart rate so we wondered why that would be. In order to clarify our results we made some minor changes to the graphs scale. In table 1B we adjusted the scale on the Y-axis and we also took off the error bars in order to better view the results.

In table 2: Percent Change in Heart Rate vs. Music Type we can see that the change in heart rate from listening to rock music only to taking the test with rock music has the greatest percent change. Based on this we can say that rock music causes the most stress out of all that music types. Since this is a graph of stress caused by the test alone we can include the control with had the second highest percent change in heart rate making it the second most stressful. Classical music has the smallest percent change in heart rate making taking the test while listening to classical music the least stressful out of all the music types and the control. Techno music caused the second smallest percent change so it caused the second least amount of stress.

Table 3: Percent Change in Heart Rate vs. Music type illustrates the stress caused by music alone. In this graph we see that techno music caused the least amount of stress but this is not accurate. Upon closer examination we noticed that the baseline reading prior to the techno treatment was unusually high. When we went back and looked at the raw data we found that some subject’s heart rates were abnormally high this caused the average to be higher than it souls be. Since this is a graph taken from the baseline it caused the percent change to be very small. Classical music had the second lowest percent change and rock music have the largest which is what we would expect. So we can say that the rock music alone caused the most stress and classical music alone caused the least amount of stress.

Another thing that affect our heart rate data was the presence of outliers. We had one subject who was extremely fit which caused his heart rate to be lower than average. We also had a subject who had a prior medical condition in which his heart rate was elevated almost throughout the entire experiment. Having this elevated study would cause the average heart rate to be higher than expected. There were also random points in our baseline data where some subject’s heart rates randomly peaked. These points would cause the heart rate average to be higher than expected.

Table 4: GSR Value vs. Music Type shows the changes in GSR and the error bars. After making the graphs for GSR values and looking at the standard deviations it became apparent that we could not accept these results. The standard deviations for the GSR during all music types were grossly exaggerated. Standard deviation is a measurement of how far away outliers are from the mean. The bigger the standard deviation the more spread out that data is. In table 4B we can see what the GSR values would be if we could accept these results. Had our error bars been lower we would have seen that listening to classical music alone had the smallest change in GSR value from which would lead up to believe that classical music caused the lease amount of stress. We would have also seen that out of all the music types classical had the smallest GSR value change from baseline to test with music and rock had the greatest. In an experiment we want data to be close to the average as possible as this would indicate that the results are trustworthy. There are several reasons that could have made the GSR results so skewed. First, there is the possibility that we set up the GSR sensors wrong, which would lead to false data. Secondly, we may have interpreted the data wrong and taken incorrect measurements, perhaps taking the three highest peaks was not the best was to measure GSR. Thirdly, and most probable, GSR is too variable person to person which would cause extreme highs and lows which would cause data to be further away from the mean. Everyone reacts to stress differently and have different sweating capabilities. There is also a huge difference between the sweating capabilities of men and women. Men typically sweat more than women because men are typically larger than women and therefore produce more body heat. These differences in people’s sweating capabilities would cause extreme highs and lows, which would cause the average GSR values to be inaccurate.

Other possible sources of error in out experiment came from data collection; there is the possibility that we attached the GSR sensors and ECG leads wrong, which would lead to inaccurate measurements. We did notice that some of the GSR sensors gave us different results on different days, which means that possibly they were not all properly calibrated or some were broken. In order to eliminate this source of error we used the same GSR sensor every time we preformed our experiment. There could have also been problems with the Biopac equipment that we could not control for. Perhaps the GSR or ECG software was not working properly which would cause our measurements to be inaccurate. Also, there could have been experimental error while analyzing the data. Maybe our method for analyzing data yielded inaccurate results, it could be that taking the three highest peaks in GSR and averaging them does not give an accurate measurement of GSR. In order to make our analyzing error smaller we could be less biased and look at the GSR information as a whole rather than just picking the three highest peaks. Musical preference also was a possible source of error. We had some subjects who periodically listened to loud rock music while they studied. They would be somewhat desensitized to the rock music played during our experiment, which was there in order to induce stress. But for these people, the rock music wouldn’t necessarily induce stress. We also had a few individuals in our study that had very low heart rates during the tests with music, indicating that they were fit and there were also individuals who had extremely high heart rates while taking the test, indicating that they were unfit. These outliers in the sample size would stretch our data out and increase the standard deviation when it should not be. We also noted that individuals who were sleep deprived prior to the experiment would be less inclined to fully concentrate on the critical thinking stress exam and become stressed out over it. This would cause them to relax during the test rather than stress out, which would show inconclusive results in the data. We did attempt to control for this by asking the individuals in the study how many hours of sleep they got the night prior to partaking in our experiment in the questionnaire so that we could explain any erroneous data points in our data. During our study there was a day that was unusually warm and humid in the room here we were running our experiment. This could have caused people to sweat more, which would come across as spikes in GSR and heart rate that was unrelated to the study. Although we tried our best for caffeine intake prior to our experiment, we cannot assume that every subject followed directions. A caffeinated beverage would stay in our system for 12 hours and increases heart rate, which means that our data would be skewed for that individual. Also related to caffeine, another group in the lab was conducting an study where participants were asked to drink coffee. Since many of our subjects were shared between the different lab groups it is possible that some of our subjects ingested caffeine right before that participated in out experiment. This would affect heart rate and thus affect our experiment tremendously. Lastly, the fact that we only had sixteen subjects could have been a confounding factor. To have reliable data we would need a larger sample size, say if we had 100 individuals out of whom 50 were male and 50 were female, we would have data that would be more acceptable. Sixteen subjects is just not large enough of a sample size to draw any trustworthy conclusions from.

Ideas for Future Studies:

For future studies and ideas we could start off by increasing the sample size in order to reduce the standard deviations. We recommend at least 50 participants, half male and half female. In order to reduce the standard deviation for the graphs, we need to increase the number of participants. Being careful to screen the participants for various confounding variables creates better data. We need to make sure that participants do not consume any caffeinated drinks, at least twenty-four hours prior to the experiment. Food should not be allowed six to twelve hours as well because it increases the body’s glucose levels, which can make the data unreliable. We can use more music types per genre to ensure that subjects are not sensitive to one particular type of music since this could affect the data. Also by adjusting the volume of the music played and doing the test on different levels, we can check our results to make sure that they stay uniform throughout the experiment. Instead of choosing one song per genre, we can use multiple songs to see the effect on heart rate and GSR. More instrumental music in the experiment could lower the heart rate even than classical. Instrumental music would be a lot more beneficial to the experiment because lyrics in the music we had might incite feelings or emotions, which would result in a change in heart rate and GSR. Since our main focus was classical music, we could have used the more instrumental song than one where there is background noise.

Using a respiratory transducer, instead of GSR, would give a broader range of results, from which we can draw a better conclusion from. We noticed in other research projects focusing on music, the respiratory system was highly analyzed. Since GSR data was not reliable enough, we could use the Biopac’s respiratory system analysis lesson to see the effect of respiration as the subjects listen to different kinds of music. By increase the recording period, we can acquire the best possible data for the experiment. To get the best data possible, we need to increase the time of recording from at least two minutes to seven minutes and the recovery period to at least five minutes. By running the experiment longer, participants would be able to relax and return to normal resting heart rate better. By doing the experiment this way it gives us more confidence to our data. Biological methods might also be very helpful since they provide us with more detailed and accurate overall results. By taking blood samples, we can measure the cortisol, adrenaline, and epinephrine levels. These biological methods are more expensive than traditional methods but yield far more conclusive and acceptable results.

We could also use an EEG in order to measure the alpha and beta waves of the brain. Alpha waves could be used to measure the relation since they predominant in individuals who are less stressed and more relaxed. Beta waves are more predominant in people who are alert, anxious, and concentrating. In other words beta waves are more predominant in people who are more stressed out. By looking at the different levels of each wave while performing our critical thinking stress test we can see if music has any effect on them.

Conclusion:

According on the result of our study, we can only accept our hypothesis based on our heart rate data. The standard deviations for the GSR data were too high to accept any of the results from the data. Based on heart rate analysis, we can conclude that classical music had the lowest average heart rate, making participants more relaxed. This was true regardless of taking the test or not. Our results were conclusive enough to prove that classical music reduced stress level by reducing heart rate. As far as rock music, we noticed the increase in stress levels, as well as taking the test. Rock music had the highest heart rate and therefore stress level due to the nature of the music. We can conclude that rock music will increase stress levels, because it induces anxiety. Our experiment has medical significance that could change people’s lives. Anxiety disorder could be treated and number of patients could be reduced, saving us a lot of money and resources every year. According to NIH, National Institute of Health, “Anxiety disorders affect about forty million American adults age eighteen years and older (about 18%) in a given year, causing them to be filled with fearfulness and uncertainty.” This is an astronomical number of patients who sometimes go untreated. If new ways of treating patients, with the lowest possible costs are to be found (music therapy) we could drive down the number of patients, save our money, resources, and redirect them to new research toward building a healthier community. Hypertension is also another important diseases, which is caused by an increased stress level. If not treated, it could cause serious health problems, such as stroke, heart attack, and kidney failure. By inducing music therapy, a low cost effective method, we can reduce the heart related diseases.

References:

Kotwal, R (1997). Stress reduction through listening to Indian classical music during gastroscopy. Journal of Gastroenterology and Hepatology. 21, 191-197.

Ferrer, A (2007). The effect of live music on decreasing anxiety in patients undergoing chemotherapy treatment. Journal of Music Therapy. 44, 242-255.

Widmaier E., Raff H., & Strang K. (2008). Vander's Human Physiology. New York, NY: McGraw-Hill Higher Education.

Manuguid, (2008). Human Physiology Lab Manual. San Francisco, CA: Fog City Readers.