With different disciplines now willing to come together to try to find new solutions to old problems, several types of work-, medicine-, and school-related fields have been looking to scientific researchers to find ways of enhancing the performance of employees and students, as well as speeding up recovery time of medical patients. Recent literature published in the last several years has shown a trend of research involving the use of music and other background noises to enhance performance in the areas of motor skills (Groeneweg, Stan, Celser, MacBeth, Vrbancic, 1988), and cognitive functioning (Burleson, Center, & Reeves, 1989; Davidson & Powell, 1986; Mayfield & Moss, 1989; Sogin, 1988; Wilson & Brown, 1997).
Several different population groups have been studied including, but not limited to normal adults, and significant results have been found involving several populations that shows that performance improvements facilitated by music are generalizable beyond just the so-called normal people. For example, the Vocational and Rehabilitation Research Institute in Calgary, Alberta conducted a study on the ways background music can affect the job performance of mentally handicapped adults. The researchers found that exposure to music during work-related activities significantly decreased behaviors that were not on-task, which allowed the workers to complete their jobs more efficiently (Greoneweg, et. al, 1988).
Significant or noticeable improvements in cognitive and spatial tasks were shown in groups of psychotic children (Burleson, et. al 1989), fifth-grade children (Davidson & Powell, 1986), and college students (Mayfield & Moss, study 2, 1989; Wilson & Brown, 1997) as well, although another study involving college-age students failed to find any effects on a coding task between groups that listened to either one of three different types of music or silence (Sogin, 1988). These findings suggest that music can be a valuable tool for many different types of people in many different types of situations.
Another interesting finding by Mayfield and Moss in their second study (1989) was that although rock music seemed to facilitate improvement in task performance over a control group that worked in silence, the sound of a heartbeat seemed to worsen performance, even though subjects in the rock music condition reported that they were significantly more distracted during task completion than those in the heartbeat condition. The authors formed a theory to explain this phenomenon, claiming that the sound of a heartbeat had a calming effect on the subjects, thereby reducing anxiety about the task and making them less likely to work hard to complete the task. They also stated that the rock music group probably felt distracted because of anxiety due to the faster rhythm, but that the anxiety made them work harder (1989). More research should probably be done studying the effects of anxiety and calmness on performance before jumping to such conclusions.
Although not all of the literature reviewed supports music as a way of enhancing performance or rehabilitation, there does seem to be enough evidence in favor of the beneficial effects of music to warrant additional research. However, some changes need to be made in order to produce more useful findings. Besides the inconsistencies in the research findings, with some studies finding that noise affects task performance, while others studies have found no such effects, some of the studies reviewed in this paper seem to have methodological problems that might have affected the results. For example, Burleson, et. al (1989) found a 60% or greater improvement in task performance in all of the psychotic children they studied when background music was present, but the results were not statistically significant because they only studied four children. Another study involving fifth-grade children found that on-task performance in boys significantly increased in the treatment period, but there was no significant increase for the girls. This was thought by the authors to be due to a ceiling effect, since the girls performed much better than the boys (nearly perfect, in fact) in the pretreatment period (Davidson & Powell, 1986).
It might be useful if some research were done studying the effects of music on real-life, job-related tasks such as product assembly, as well as employees’ satisfaction with their jobs. Depending on the results of such research, factories and other types of corporate and private businesses that make their living putting products together might be able to find a way to improve the satisfaction and performance of their employees, which could be quite profitable for the companies as well as the employees themselves.
Perhaps areas such as liking of a task, level of perceived distraction, type of music listened to frequently versus type of music played in the background, and music tempo and loudness could be studied in relation to each other in order to find a good way, if not the best way, to help people work more efficiently in assembly tasks.
The present study examines the effects that four different types of background noise have on the performance of an assembly task. These types of noise are ambient noise (no additional noise other than normal classroom sounds), white noise, slow music, and fast music. It is hypothesized that participants in the group that hears fast music will produce the best performance, followed by the groups that hears slow music, then the ambient noise group, and finally the white noise group.
Method
Participants
Forty undergraduate university students volunteered to participate. The data were only used from thirty-nine of these participants, as one of them made a substantially higher number of errors than the others, which would have skewed the data, and so was dropped from the analysis. The groups that heard ambient noise, white noise, and slow music each contained ten participants, while the group that heard fast music contained nine, after the data from the above-mentioned participant were removed.
Participants were tested in groups, the numbers ranging from one to seven participants in each testing group. None of the participants received any incentive from the researcher for their participation, and all were treated in accordance with the “Ethical
Principles of Psychologists and Code of Conduct” (American Psychological Association, 1992).
Apparatus
Four different types of background noise were used. One group heard ambient noise, which is simply the normal background noise which exists in a classroom. No additional noise was provided by the researcher. The second group heard white noise, which was static that the researcher played by tuning a radio to an unused frequency.
The third group heard a slow song, which was “Nothing Else Matters” by Metallica, from the album “Metallica”, and was played by the researcher using the compact disc and a compact disc player. The last group heard a fast song, “Disposable Heroes”, by Metallica, from the album “Master of Puppets,” and was played in the same manner as the slow song. Four minutes of each type of background noise was used, and was timed by a stopwatch.
The items being put together by the participants each consisted of two bolts, two flat washers, two lock washers, and a connecting hexagonal nut. These parts were put into cardboard boxes and placed in front of each participant. After completion of the manipulation, participants answered a short questionnaire developed by the researcher, which contained questions such as, “Please rate the noise you heard in the background according to how distracting it was”, “Please indicate how often you listen to music while working or studying”, “If you heard music during the study, please indicate how often you listen to this type of music”, and “Have you ever held a job that involved assembly tasks similar to those in this study?”. The first three questions were answered by the participants with a four-point Likert scale. The last question was simply answered “Yes” or “No”.
Design and Procedure
The researcher utilized a one-way, between-subjects design. Participants were randomly divided into four noise groups: those who heard ambient noise, those who heard white noise, those who heard slow music, and those who heard fast music. The participants sat at tables, with a cardboard box of the nuts, bolts, and washers in front of
them, and the radio was on a table in the front of the room for the groups who were provided with additional noise.
The researcher gave verbal instructions and a visual demonstration on how the items were to be assembled, and were told that they would be expected to assemble as many of the items as possible during the time allowed. Participants were then asked if they had any questions, which were then answered by the researcher. At this point, they were told to begin, and four minutes were counted down on the stopwatch while noise played in the background in three groups, and classroom sounds were heard by the other group. At the end of the four minutes, they were told that the time was up, and were given the short questionnaire to complete. The participants were then thanked for their time, given a debriefing sheet, and allowed to leave.
After the participants had left, the researcher counted the number of items each participant completed, and the number of errors each participant made. An error was defined as any part of the item that was in the incorrect place; incomplete items were not counted at all.
Results
All analyses were conducted with an alpha level of .05. Using separate one-way analyses of variance, there was no significant effect of type of background noise on number of items completed F(3, 36) = 2.0326, MSE = 4.3417, p = 0.1266. There was no significant effect of type of background noise on number of errors made F(3, 36) = 0.9351, MSE = 40.1389, p = 0.4388. There was no significant effect of previous assembly task experience on number of items completed F(1, 37) = 0.1890, MSE = 4.8829, p = 0.6662, or on number of errors made F(1, 37) = 0.5074, MSE = 41.5275, p = 0.4807. There was no significant effect of type of background noise on level of perceived distraction among the participants F (3, 38) = 0.9193, MSE = 0.4686, p = 0.4416.
Table 1 presents the correlations between several relevant variables and number of items completed and number of errors made. There is a significant correlation between the tendency of participants to listen to music while working or studying, and number of errors made.
Discussion
This study was designed after several previous studies involving the use of music and its effects, or lack thereof, on behavior. The use of different types of background noise was modeled, in part, after a study by Sogin (1988), which also used two speeds of music, another type of sound (in that case, the sound of a heartbeat), and a condition involving only regular sounds that occurred in the room without the addition of other background noises.
The findings in this study seem to be similar to those of Sogin (1988), in that different types of background noise did not appear to have any effect on the participants’ performance, although Sogin (1988) used a coding task, while this researcher decided on an assembly task. Perhaps this study, as well as that of Sogin (1988) found the same non-significant results utilizing different tasks because neither coding nor assembly tasks depend on the level of concentration of the participant. This could be a factor because the noise playing in the background could disrupt concentration, thereby affecting performance on tasks that require a high level of concentration.
In the present study, however, students who usually listen to music while they work or study tend to make fewer errors than those who do not usually listen to music during these activities. It is possible that already being accustomed to working with music in the background, and possibly learning to block out the sound, helped these participants concentrate better on the task and therefore commit fewer errors.
It does appear that music may have an effect on some types of tasks, or some special populations, because other studies have found such differences in performance. For example, a study that exposed mentally handicapped adults to music in the workplace did find that off-task behaviors were decreased (Groenweg, et. al, 1988). Significant or noticeable improvements in cognitive and spatial tasks were also found in groups of psychotic children (Burleson, et. al, 1989), fifth grade children (Davidson & Powell, 1986), and college students (Mayfield & Moss, study 2, 1989; Wilson & Brown, 1997). Perhaps this study could be improved upon in the future, and different results may be found. For instance, the assembly task that was performed by the participants mayhave been too simple for them, as the researcher was surprised with the speed and accuracy shown by the majority of the participants in completion of the task. Another change that might be beneficial would be to give explicit instructions on the exact manner in which to assembly the items. The participants used all types of methods of putting the items together, and some of these methods were inherently slower than others.
However, it may be possible that some elements of this study are fundamentally different from those of the studies that did find significant effects of noise on performance. For example, the study by Sogin, (1988) included at least one song that contained lyrics, which is similar to this study, which included two songs that contained lyrics, and some of the studies that did find significant or near significant effects of noise did not specify whether lyrics were present in the music that was used, including Mayfield and Moss (1989), Burleson et. al (1989), and Davidson and Powell (1986). It has been stated that music is processed predominantly in the right hemisphere of the brain (Flohr, Miller, & Debeus, 2000), while language is largely accepted as being processed in Broca’s Area in the left hemisphere. Perhaps the presence of lyrics in the music, which would activate the left, as well as the right hemispheres of the brain, interferes with the ability to concentrate on and perform certain tasks. It would probably be helpful if more research were done in which the presence of lyrics was manipulated, in order to look for what effect lyrics alone might have on the performance of certain tasks.
Table 1
Intercorrelations Between Variables Related to Number of Items Completed and Number of Errors Made
_____________________________________________________________________________________________
Variable 1 2 3 4 5 M (SD)
1. Complete – -1.1468 -0.1224 -0.0252 0.1448 9.92 (2.19)
2. Errors – 0.0462 0.3627* 0.3254 0.10 (0.38)
3. Distract – -0.0148 -0.3254 1.53 (0.69)
4. Listen? – 0.5858 2.32 (0.84)
5. Type – 2.00 (0.77)
Note. N = 39
*p < .05.
Complete = number of items completed. Errors = number of errors made. Distract = level of perceived distraction of the background noise. Listen? = tendency of the participants to listen to music while working or studying. Type = tendency of the participants to listen to the type of music they heard during the study (for those who did hear music).
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