The Relationship Between Color Code Personality Type and Texting

Transcription

1 Billy Barnes, Brianne Chantry, and Michael Olsen Brigham Young University 788 E 750 N #12 Provo, UT 84601

2 Abstract This study was done to determine whether or not a relationship exists between text messaging behaviors and personality type. Using the Color Code personality test and a homemade survey on text messaging, college students (N=188) took an online survey to determine their personality type and their text messaging behaviors. These responses were examined using analysis of variance (ANOVA) statistical procedures. No relationship was found between Color Code personality type and text messaging behavior, however, extremely significant relationships were found between various settings where students send text messages, showing that students are more likely to send text messages in some contexts (i.e. between classes) than others (i.e. on a date). These results can be applied to academic situations such as implementing text messages into lecture settings. ii

3 Table of Contents Abstract... ii Introduction... 1 Text messaging... 1 Personality... 1 Hypothesis... 2 Methods... 2 Research design... 2 Measures... 2 Participants... 2 Figure Statistical procedures... 3 Results... 4 Descriptive statistics... 4 Table Analytical statistics... 4 Figure Table Discussion... 6 Strengths... 6 Limitations of study... 6 Explanation of observed phenomena and results... 6 Conclusions... 7 Conclusions and Clinical/Daily Implications... 7 References... 8 Appendix A Measures... 10

4 Text messaging and personality type Introduction Text messaging Text messaging is a convenient, quick, and extremely popular form of communication. Approximately 75 billion text messages are sent every month (Text Message Statistics, 2008). Because of this prevalence there has been an increase in research about text messaging and how it relates to society. Text messaging, or texting, refers to the exchange of brief written messages between mobile phones, over cellular networks. While the term mostly refers to messages sent using the Short Message Service (SMS), it has been extended to include messages containing image, video, and sound content, such as Multimedia Messaging Service (MMS) messages. Individual messages are referred to as "text messages" or "texts" (Fendelman, 2009). Although much research about text messaging has been done, most of the studies deal more so with the effects that texting has in various situations than individual text messaging behavior. For example, research has investigated the adverse effects of texting while driving (Hosking, 2006), how encouraging text messages can help people exercise (Prestwich, 2009), support those who suffer from diseases such as diabetes (Franklin, 2008), or examine the effects text messaging has on self-perception and social relationships (Igarashi, 2008; Plester, 2009). The fact that text messaging can be done in any setting where there is cell phone reception provides opportunities for cell phone users to communicate using mobile phones in contexts where verbally speaking would be deemed inappropriate (i.e. during class or religious services). The purpose of our study is to determine if there are specific personality types more likely to send text messages in those kinds of settings than other personality types. This subject is important to the field as it examines another aspect of how personality affects actions. Personality Personality is defined as important and relatively stable characteristics within a person that account for consistent patterns of behavior (Ewen, 2003, p. 11). Individuals are said to possess specific personality traits, or factors that describe personality (Costa et. al, 2002). When comparing differences in behavior between dissimilar personalities, participants are typically categorized into personality types or convenient labels summarizing combinations of traits"(costa et. al, 2002, p 573). One significant direction in recent personality research is the application of various personality models into differing aspects of life. Examples include determining whether there is a relationship between personality type and risky health behaviors in students (Vollrath & Torgersen, 2008), coping behaviors of out-care patients (Kidachi et. al, 2007), cohesion in 1

5 technology teams (Karn, et. all, 2007), and academic behaviors in accounting students (Lawrence & Taylor, 2000). For the purposes of the study personality is defined by the Color Code personality theory (Hartman, 1998), which categorizes individuals into four groups, each labeled by a color: Red, Blue, White, or Yellow. Red people are characterized by a desire for power and control. Blue people are focused on intimacy and relationships, while White people are focused on peace and contentment. Yellow people are characterized by focusing on having fun and receiving attention. Hypothesis We expect that people classified as Red or Yellow personalities are more likely to read or send text messages during class, worship services, at the movie theater, while driving, or at work than people classified as Blue or White personalities. Methods Research design The research was done using a survey design utilizing the SONA online research system available to BYU students. The survey had two focuses, a questionnaire determining the frequency in specified situations the subjects send and read text messages, and a version of the Color Code personality test to determine personality type. The independent variable in the study was the personality type while the dependent variable was the amount of texting in the given situations. Measures No measures or questionnaires designed to measure text messaging behavior could be found in the literature, therefore the Text messaging behaviors measure was created by the investigators for the purposes of the study. It includes 9 items each asking the participant to rate how frequently he or she sends text messages in various contexts common to college students, namely in class, while driving, at the library, at work, while shopping, on a date, between classes, during worship services, and at the movies. Each of these items presented a Likert scale with responses varying from 1 (never) to 5 (consistently). The Color Code test was used to determine the personality type of the participants. This questionnaire consists of 45 questions that determine a primary personality color reflecting personality type. Participants The study was conducted utilizing convenient sampling and employing naturally occurring groups as defined by Color Code personality. Participation was advertised to students of entry-level psychology classes and was accessed using the BYU online psychological research 2

6 system. During the three weeks that the survey was available, 209 volunteers took the online survey. After timing a couple practice runs of the survey, it was decided that if a participant were to read and answer each question, it would take at least seven minutes. All participants who completed the survey in six minutes or less were excluded from data analysis, leaving 188, or 90% of the original participants. Of these, 133 were female (71%) and only 55 were male (29%). The mean age was 19.4 with a standard deviation of The average time used to complete the survey was 12.5 minutes. After completing the survey, the participants responses were used to determine the Color Code personality type of each individual. The total distribution was 99 Blue, 40 White, 25 Red and 24 Yellow (see Figure 1). This distribution was similar within each gender. Figure 1. Distribution of Color Code personality type, n=188 Statistical procedures The results of the Text messaging behaviors measure for each participant were summarized by calculating the total texting score for each participant. This was done by simply adding the Likert values (1-5) for each texting context item on the questionnaire, i.e in class, while driving, etc. This total was treated as the summary of individual text messaging behavior regardless of context. As the hypothesis speculates that the context will play an important role along with personality type in individual texting behavior, it was necessary to determine which contexts were similar and which differed significantly in order to isolate groups of contexts for analysis. In order to determine whether there were significant differences, an analysis of variance (ANOVA) was preformed, which is a test of variability across multiple groups. This was done by treating each context as a separate group and comparing the mean scores for each context. If the ANOVA test returns significant values, then it can be inferred that the measured variable differs significantly from group to group. Post-hoc tests show which groups are similar and which groups differ. 3

7 The formula for one-way ANOVA is defined in three parts. The total sum of squares: SS total = X 2 ( X)2 the group sum of squares, which is the sum of squared deviations of group means from the grand mean: N SS group = n (X j X.. ) 2 and the error sum of squares, which is the sum of the squared deviations within each group: SS error = SS total SS group SS represents the sum of squares, X is an individual score and X j represents scores from a particular group. X represents the grand mean. N is the total sample size, and n is the group sample size. ANOVA testing was then applied to the data to determine if the four groups of Color Code personality vary from one another in texting behaviors. The same procedure was then applied to any groupings of contexts provided by the data. Results Descriptive statistics The first value used from the texting measure was the total texting score for each participant. The mean total texting score was 23.08, with a standard deviation of 5.2. The averages for each color personality type did not vary significantly from the sample mean, and are shown in Table 1. Table 1. Mean total texting score, by personality type (little variation about grand mean) Mean Total Texting Group Score n Red Blue White Yellow Complete sample (sd = 5.2) 188 sd = standard deviation Analytical statistics As a measure of control, t-tests were performed on the data to determine whether there existed correlational relationships between the variables of age, gender, and how long the participant had owned a personal cell phone, with the dependent variable of total texting score. No significant relationships between these variables were found. 4

8 To determine the text messaging context groups, the scores from each setting were analyzed using ANOVA tests. This revealed a highly significant p-value (p < 0.00) indicating differences between the various contexts. The post-hoc Tukey tests then placed the settings into groups by determining which settings were significantly different from one another and which were similar. Results were revealing, and placed the texting contexts into five groups where the in-group contexts were seen as statistically equivalent. The results grouped During worship services and On a date as statistically identical, and similar relationships exist between At the movies, While driving and At work; In class was different from all other contexts; At the library and While shopping were identical, and Between classes was different from all other contexts. Figure 2. Similar groups based on ANOVA, with averaged response of text messaging behavior by context, n=188 Contexts placed groups together in a group were overwhelmingly similar (p < 0.00), while simultaneously unquestionably different from each context in each other group (p = 1.00). The only exception was that of the context At work, which approached significance as its own group, with p=0.54. However, as this figure is not significant, At work has been grouped with Movies and Work. As per the hypothesis, the final tests run were designed to determine whether personality type exhibits a significant effect on text messaging behavior. This was done by performing an ANOVA of the total texting scores grouped by Color Code personality type. As shown in Table 2, there were no significant differences between the four groups, with a p-value of.321. Table 2. ANOVA results of total texting score and personality, no relationship found Sum of Squares df Mean Square F Sig. Between Groups Within Groups Total df = number of degrees of freedom; F = F static 5

9 Another series of ANOVA tests were performed comparing the average texting score of each context group with personality type. There were no significant variations by Color Code personality type for any of the context groups. Discussion Without significant figures from the analysis of personality type and texting behavior, we fail to reject the null hypothesis and conclude that text messaging behavior is not affected by the personality type of the individual, as defined by the Color Code personality test. However, the context in which messages are sent plays an important role in text messaging behavior. Strengths One strength is the validity of the Color Code test as a measure of personality. Ault and Barney (2007) showed that the Color Code test employed in the study validly assesses personality traits associated with each color type. This test is widely used and easy to use statistically. Another strength is using the SONA system to administer the survey. This made the survey appealing and convenient for participants. Finally, one more strength is that the ratio of color personalities from the study is similar to Ault and Barney s (2007) study of the validity of the Color Code. This helps confirm that the participants in the study are representative of the population. Limitations of study Due to the popularity of the Color Code personality test, it is possible that some of the participants have taken it before and experienced some degree of practice effects while participating. Another limitation could be the Text messaging behaviors measure created by the researchers, which may not validly assess text messaging behavior. Also, a third limitation to the study is that participants might not have known the meanings of some words in the personality survey, or may not feel some of the questions were applicable resulting in a forced response not necessarily reflecting their personality. Explanation of observed phenomena and results One possible explanation for the consistency of text messaging is that sending text messages has become a slight addiction for some individuals. An addiction is defined as a compulsive need to engage in a specific behavior (Fundukian & Wilson, 2008). Some respondents reported to text consistently in multiple contexts, such as in and between classes as well as low-scoring contexts like in worship services. This constant texting could be seen as evidence that texting can form slightly addictive tendencies in some individuals. Boredom could also be related to why our text messaging behaviors are high in some settings and low in others. Specifically in a classroom setting, research shows that 59% of students find their lectures boring half of the time, and 30% find all or most of all their lectures boring (Mann, 2009). Contexts with low text messaging scores included the entertaining contexts of At the movies and On a date. It is possible that students are more likely to send text messages when bored than when entertained. Social influences may also explain the differences in text messaging scores for different contexts. Research shows that perceived social influences can inhibit or encourage behavior in 6

10 different settings, such as at the gym (Miller & Miller, 2009) or with teen substance abuse (Mayberry, et. al, 2009). Social influences and pressures may play a role in whether or not individuals feel comfortable sending text messages in certain contexts, such as on a date or at the movies. Conclusions Conclusions and Clinical/Daily Implications This study gives insight into context and frequency of text messaging. A better understanding of the situations in which students are likely to send text messages and where they are not likely to send text messages is now more predictable. Given this understanding, it would be reasonable for teachers to use more multimedia programs in class. The results show that text messaging is less frequent at the movies than in class, so if teachers use videos or other visually stimulating teaching methods it is possible that students will send fewer text messages during class. On the other end of the spectrum, teachers could implement text messaging into their lectures. Text messaging during class has a higher frequency so if teachers were to set up a program to receive text messages from students regarding the lecture in class, the frequency of text messaging may not decrease, but the text messages sent would be academically geared and the frequency of non-class related text messages would decrease. Class participation would increase resulting in a more interactive classroom environment. 7

11 References Ault, John T.; Barney, Steve T. (March 2007). Construct Validity and Reliability of Hartman's Color Code Personality Profile. International Journal of Selection and Assessment. Blackwell Publishing Ltd. Volume 15, number 1. Austin, M. (2009, August). Unprotected Text. Car & Driver Vol. 55 Issue 2, Costa Jr., P., Herbst, J., McCrae, R., Samuels, J., & Ozer, D. (2002). The replicability and utility of three personality types<fnr></fnr><fn>this article is a US government work and is in the public domain in the United States. </FN>. European Journal of Personality, 16S73- S87. doi: /per.448. Cross, T., Cassady, J., & Miller, K. (2006). Suicide Ideation and Personality Characteristics Among Gifted Adolescents. Gifted Child Quarterly, 50(4), Retrieved from Academic Search Premier database. Eperjesi, F "Do tinted spectacle lens wearers have a different personality?." Ophthalmic & Physiological Optics 27, no. 2: Academic Search Premier, EBSCOhost (accessed November 19, 2009). Ewen, R. E. (2003). An Introduction to Theories of Personality, 6th Edition.Mahwah, NJ: Lawrence Erlbaum Associates. Fendelman, Adam. (2009). Retrieved September 17, 2009, from about.com/od/phoneglossary/g/ smstextmessage.htm Fundukian, L., & Wilson, J. (2008). The Gale Encycopledia of Mental Health (2nd ed.). Detriot: Gale Grant, T., & Dajee, K. (2003). Types of task, types of audience, types of actor: interactions between mere presence and personality type in a simple mathematical task. Personality & Individual Differences, 35(3), 633. doi: /s (02) Hartman, T. (1998). The Color Code: A New Way to See Yourself, Your Relationships, and Life. New York, NY: Simon & Schuster. Karn, J., Syed-Abdullah, S., Cowling, A., & Holcombe, M. (2007). A study into the effects of personality type and methodology on cohesion in software engineering teams. Behaviour & Information Technology, 26(2), doi: / Kidachi, R., KikuchiI, A., Nishizawa, Y., Hiruma, T., & Kaneko, S. (2007). Personality types and coping style in hemodialysis patients. Psychiatry & Clinical Neurosciences, 61(4), doi: /j x. 8

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13 Appendix A Measures Age Gender: M F 1. How long have you had a personal mobile phone? 2. Does your wireless phone plan have unlimited texting? Yes No 3. If you don t have an unlimited text plan, do you ever go over your monthly text messaging limit? Yes No Doesn t apply 4. How many text messages do you send on average per day? or more 5. How many text messages do you receive on average per day? or more 6. Do you use other people s cell phones to send text messages? Yes No 7. Do you prefer text messaging over calling? Yes no On a scale from 1-5, how likely are you to send personal text messages in the following circumstances: Never Rarely Sometimes Often Consistently During class While driving At the library While shopping At work Between classes On a date During worship services At the movie theater