Text messaging and personality type
Billy Barnes, Brianne Chantry, and Michael Olsen
Brigham Young University
788 E 750 N #12 Provo, UT 84601
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.
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
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
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 1.68. 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.
The formula for one-way ANOVA is defined in three parts. The total sum of squares:
SStotal = ∑ 𝑋 2 −
(∑ 𝑋)2
𝑁
the group sum of squares, which is the sum of squared deviations of group means from the grand
mean:
SSgroup = 𝑛 ∑(𝑋𝑗 − 𝑋̅.. )2
and the error sum of squares, which is the sum of the squared deviations within each group:
SSerror = SStotal – SS group
SS represents the sum of squares, X is an individual score and Xj represents scores from a
particular group. 𝑋̅ 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
n
Group
Score
23.21
25
Red
23.08
99
Blue
23.06
40
White
22.94
24
Yellow
23.08 (sd = 5.2)
188
Complete sample
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.
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.
95.68
3
31.90
1.175 0.321
Between Groups
4994.12
184
27.14
Within Groups
5089.8
187
Total
“df” = number of degrees of freedom; “F” = F static
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
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.
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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?
0-15
16-30
31-49
50 or more
5. How many text messages do you receive on average per day?
0-15
16-30
31-49
50 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:
During class
Never
1
Rarely
2
Sometimes
3
Often
4
Consistently
5
While driving
1
2
3
4
5
At the library
1
2
3
4
5
While shopping
1
2
3
4
5
At work
1
2
3
4
5
Between classes
1
2
3
4
5
On a date
1
2
3
4
5
During worship services
1
2
3
4
5
At the movie theater
1
2
3
4
5