Most classroom walls and hospital room walls are generally painted with neutral colors, such as beige, tan, light green, or light blue. Why is this so, and why are certain colors, most often bright, used in places such as sports arenas? Our group plans on answering these questions through investigations and surveys of our peers. This project seemed interesting because mood is very important in school, the work place, and in daily life. Therefore, it is pertinent to understand how color affects mood. Furthermore, three out of four of our group members are architecture majors, and color and its impact are of great interest to us.
We plan to use six specific colors to see which ones bring out aggression, relaxation, energy, or other emotions in an individual. We hope that through careful collection of data, a pattern will be evident in how moods relate to colors. This research is relevant as well as of interest to everyone who can see colors because every daily act involves color. Color is everywhere, and however simple it may seem, it affects us all in ways we may never completely know, but hope to understand.
2. Relevance of your research question
There has been very much written on color and how it affects mood as well as behavior. For example, Nancy J. Stone and Anthony J. English say that change in mood may in fact be the result of color in the environment. They also say that color can affect performance in the work place. They believe that a red office is more stimulating and may cause vigor, anger, or tension in a worker. However, a red surrounding may also increase performance. Stone and English go on to state that a blue office may cause greater depression, as well as sadness, fatigue, or relaxation. Emotions such as these are evident because warm colors like red have a longer wavelength and are thus more stimulating, while cool colors such as blue have a shorter wavelength and are thus more sedative.
Stone and English conducted additional experiments to show the influence of color on our emotions. The team studied various colors, some of which were pink, white, green, and violet. Stone and English found that green causes anger and confusion while violet causes sadness and fatigue. Moreover, even though a group of surveyed students claimed that a white office is appropriate and not distracting, it is in fact the opposite. When compared to workers in with red or blue offices, workers in white offices complained of more headaches and instances of nausea. In addition, classroom testing showed that a pink classroom caused greater strength in the children occupying it, blue rooms caused the most weakness, and gray was somewhere in between. Also, in a pink room the children painted positive pictures. In a blue room, the paintings were more negative. Stone and English concluded that color definitely affects mood, yet the extent and details are still very unclear.
N. Kwallek, C.M Lewis, C. Sales, and H. Woodson, the authors of Impact of Three Interior Color Schemes on Worker Mood and Performance Relative to Individual Environmental Sensitivity, are also very confident that color affects mood. They explain that red, blue, and green create the most obvious results. The authors go on to say that white does not usually test well because it is a neutral and common color, red causes alertness and high excitement, and blue causes relaxation as well as low excitement. Lastly, the authors say that blue and green cause feelings of security and tenderness.
Our group also found a lot of information from internet sources. For instance, Starr Walker says that "colors are neither good or bad, but they do influence the human psyche." Walker goes on to say that this is because of the different vibration levels of colors. Red has a much higher vibration level than black, while clear or bright colors are more positive and emit a higher vibration. Dark or muddy colors give off a lower vibration. Walker also discusses the effect of colors of clothes that individuals choose to wear. She claims that mental state is very much affected by the simple detail of color of clothing. The following are her interpretations of colors:
White = purity and clarity; red = power and strength; pink = sensitivity and love; orange = stimulation; yellow/gold = energy; green = harmony in mind, body, and soul; blue = healing and calmness; violet = spirituality; brown = earthlike and natural; and black = depression and seduction.
Other information from the internet states that a person's cultural background and traditions influence their response to color. Many Middle Eastern countries view blue as protective and paint their front doors blue to ward off evil spirits. Therefore, people raised with this idea would feel a great sense of safety in the color blue. Black, a color traditionally perceived to be a color representing mourning, is not the color that signifies mourning in Asian countries. White symbolizes grief in China, and from this it can be see that not every color has universal symbolism.
Our research relates to the real world because there has obviously been an enormous amount of research on color relating to moods. Obviously it is a topic that professionals feel is worthy of our time and energy. Not only does color affect an individual's mood, but color in turn can affect several factors, including the moods of others that are around the individual. Therefore, it is very important to see which colors cause which moods. The information that our group collects will hopefully give our peers greater knowledge on colors and moods. Information on colors and mood may be of much interest to the class for several reasons. For example, a majority of the class is architecture or interior design majors, and color is extremely important in both of these fields. Every student will benefit from our studies because they can provide insight on how to achieve and retain another individual's attention. This ability could prove to be useful in the many presentations that will inevitably be given in the years to come.
3. Materials and Methods
To collect the data needed to determine which colors cause which moods, our group handed out 240 surveys to our peers as well as people on main campus. There are 40 surveys printed on red paper, 40 on orange paper, 40 on yellow paper, 40 on green paper, 40 on blue paper, and 40 on black paper. We distributed 20 of each color to males and 20 of each color to females. Our group started out with 120 surveys, with 20 of each color, but this did not produce enough results. Further, the first 120 surveys had not all been filled out on the same day, so we felt that we should pass out 120 more surveys, all of which would be filled out on the same day.
There are four multiple-choice questions and one free response question, however none of the questions imply any information about color, as our group feels that this would make the answers biased (see attached survey). There are six choices after each of the multiple-choice questions, each one corresponding to a characteristic of one of the six colors. Our hope is that the answers given will reflect and be affected by the background color on which the answers are written. We feel that forty surveys for each color is sufficient for unbiased results. The students did not know the reason for the test, and they therefore were not be jaded by this knowledge. Further, we tested an equal number of males as females, and main campus students were included as well as western students. When giving out the surveys, each person had five minutes to fill them out so that time was consistent. We also asked the students to fill the surveys out as we waited so that they were not lost or forgotten.
The attached survey was given to the 240 students (without the color coding of course) on red, orange, yellow, green, blue, or black paper from Copy Nation uptown. After collecting all of the surveys, our group put a "+" by the questions in which the answer corresponded to the color of the paper and put an "x" by the answers that did not. We then counted how many plusses the females received and then counted how many plusses the males received. We calculated the ratio of "+" to "x" and see if these colors do truly affect mood in the way that we found in our research or if there are dominant moods corresponding with other colors.
We include the class in our study by giving them surveys, but since they read our lab packet, they may have been biased in their answers. Our group also explained our project in full to the class on two separate occasions to make sure that they were completely knowledgeable of our intentions and our project.
The following is a timeline for the collecting of our data:
October 20, 1999- went to Copy Nation uptown to make 120 copies of the surveys on the colored paper
October 22, 1999- began asking people to take the surveys while we waited. We will give out 20 surveys a day for 6 days.
October 29, 1999- have 120 completed surveys of which we derived calculations from
November 9, 1999- Discovery Lab Manual 3 (our group teaches class)
November 15, 1999- met with Hays to discuss our project
November 21, 1999- made 120 more copies of the surveys uptown
November 22, 1999- passed out all of the 120 surveys
November 29, 1999- made Spearman Rank tables of our data
November 30, 1999- used Statview to record our data
December 1-8, 1999- made tables and graphs of our data
December 9, 1999- final class presentation
December 10, 1999- turned in lab packet
After we completed handing out the first 120 surveys, we then had to interpret them. We were unsure at first what kind of tables and graphs to make, so we made several to see which ones worked the best. The first data tables that we made included six tables that only included the first 120 surveys. The first table showed how many males answered each question corresponding to each color of the paper. The second table is the same organization, except it is for females. The third and fourth tables show the letter answers that were picked for each color and each question. From these two tables, our group made two more tables that translated these letters into how many times each letter was put for each color, question, and sex. From the numbers that we discovered, the dominant themes seemed to be that males answered predominately answer "E" for question number one, "C" for question number two, "B" for question number three, and "D" for question number four. All of these dominant answers, except for question number two, which was mainly "black" answers, correspond to green feelings and emotions, which constitute a relaxing feeling (See tables).
After completing the above tables, we made graphs that portray the number of people, for each sex, that put answers that complied with the color of the paper. For example, if an individual put answer "A" for question number one, "F" for question two, "D" for question three, or "E" for question four, these are all "blue" answers, and the graphs counted how many times a blue answer was put on blue paper. For males, the results were very evident. Seventeen males put green answers on green paper, and the next highest number was that 7 males put yellow answers on yellow paper. For females, 9 individuals put green answers on green paper, and 9 females also put yellow answers on yellow paper. These results agree with the male results, in that in both, the two highest colors are green and yellow (see "Number of People vs. Color" graphs).
Once again, our group decided that 120 surveys just did not produce enough numbers. Therefore, we passed out the second group of surveys to make a total of 240. After we had 240 completed surveys, our group made Spearman Rank tables on the computers in the Boyd Hall computer lab. These tables compared the question, sex, and color of the paper to how many people answered each letter. For example, for males who answered question number one on red paper, 6 answered "A," 2 answered "B," 2 answered "C," 4 answered "D," 5 answered "E," and 1 answered "F." After entering all possible data of this sort, we had 48 columns with 6 answers in each column, so there were a total of 288 numbers of data (see "final data tables").
After filling in all of this data, we were able to make charts on the computer that showed us every possible combination of columns. For example, for question number one, we compared the answers of females on green paper to males on red paper. We did this for every possible combination of data, keeping each question separate. The charts that we developed from the data gave us the "p" values of each comparison. We marked every comparison, pink if the "p" value was above .05, therefore making it and independent comparison, and blue if the "p" value was below .05, making it a dependent comparison (see "question #Íp-values" charts).
Once we had a count of independent comparisons versus dependent comparisons, we were able to make a graph of this. On the x-axis, we put the question number and whether it was a female to female comparison, male to male comparison, or female to male comparison. On the y-axis we put the percentage. The graph clearly shows that a majority of the comparisons were independent, as all of the independent comparisons range from 73% to 100% of the answers. The dependent comparisons range from 0% to 27% of the answers (see "Independent/Dependent vs. Percentage" graph). Thus, our group can safely say that the colors were almost always independent from each other.
Our group went on to make 8 more graphs. Each one of the graphs corresponds with one question as well as one sex. The x-axis displays the color and the y-axis displays the number of people that put each letter answer (see graphs). Each color on the x-axis has six pieces of information protruding from it, one for each letter answer. Looking at these graphs, our group can see once again that answers varied greatly from color to color.
Our group tried several different ways to display our data. We made many different kinds of tables and graphs, and we also found many different numbers that meant many different things. However, once we were finished with our project, we found that some of the data was more helpful than other information. The most useful information includes the p-values, the graphs comparing these values that show independence or dependence from color to color, and the graphs that compared the number of people who put each letter answer for each question and sex. We learned a lot from these pieces of information.
5. Discussion and Conclusions
Our group got the results that we did because colors truly do affect how people react in different situations. Even though we did not necessarily receive answers that corresponded to the hypothesized emotions for each color, we did prove our hypothesis that different colors receive different reactions. Further, once again, our results may be a little bit biased because of other factors that could affect someone's mood, completely unrelated to color. The weather, workload, relationship, and much more could just as easily affect how certain individuals filled out the surveys.
Our work fits in with what others have done because several others, including many professionals, have tested how color affects mood and emotions. Like these other individuals, our group discovered that red, orange, yellow, green, blue, and black all receive such different responses, and all colors need to be placed with thought wherever they exist. Orange cannot be placed in a nursery, or else it will create too much activity or nervousness in otherwise calm babies. Further, an excess amount of black can create depression. Therefore, our work greatly relates to issues that everyone deals with every day, including architects, clothes designers, and ordinary people across the world.
Our group has several suggestions for further investigation. For example, we would hand out many more surveys that we did not have the time to hand out. We would also ask many more questions on the surveys than just four. Moreover, we would record who filled out the surveys so that the same person could not fill out more than one and we would hand out all surveys on the same day.
Even though we have many suggestions for further investigation, we feel that we did a very trustable job in collecting data. Human error is always a factor in student generated experiments and there will always be some questions as to how reliable the results are. We feel that we did the best that we could with these boundaries.
6. Literature Cited
All About Color-Color Information and Trends. October 17, 1999, http://www.pantone.com/allaboutcolor/allaboutcolor.asp?ID=43.
English, Anthony J. and Nancy J. Stone. Task Type, Posters, and Workspace Color on Mood, Satisfaction, and Performance. Creighton University, Omaha, Nebraska: Department of Psychology, Volume 18 Issue 2 1998.
Keltner, Dacher. "Appeasement in Human Emotion, Social Practice, and Personality."
Ohio Link 23 (1997): 359-374.
Kwallek, N., Lewis, C.M., Sales, C., and Woodson, H. Impact of Three Interior Color Schemes on Worker Mood and Performance Relative to Individual Environmental Sensitivity. Color Research and Application, Volume 22 Issue 2 1997.
Pfaus, James G. "Frank A. Beachward: Hormones+Behavior."v309(1996):186-200.
Plaud, Joseph J. "Human Behavioral Momentum: Implications for applied behavior analystic therapy." OhioLink v27 (1996):139-148.
Sato, Thomasa. "Robotic Room: symbiosis with Humans Through Behavioral Media." Ohio link 18 (1996): 185-194
Tyron,WarrenW." Synthesizing Animal and Human Behavior research via neural network learning theory." OhioLink26(1995):303-312.
Walker, Starr. Healing With Color. Phases Spring: Temple of the Triple Goddess, 1999.
Return to the Topic Menu
IMPORTANT: For each Response, make sure the title of the response is different than previous titles shown above!
Weather & Earth Science Resources
Tropical Ecosystem Courses
Tools & Other Stuff