The Relative Importance of Teenagers’ Personal Characteristics
on Technology Addiction
Chan Jung Park
1
and Jung Suk Hyun
2
1
Department of Computer Education, Jeju National University, Jeju-si, Jeju-do, Republic of Korea
2
Department of Management Information Systems, Jeju National University, Jeju-si, Jeju-do, Republic of Korea
Keywords: Ethics Education, Internet Addiction, Mobile Phone Addiction, Self-Efficacy, Time Perspective, Dominance
Analysis.
Abstract: As the Internet becomes the major means to conduct business, new types of agenda arise in e-Business
arena. One of them is Ethics. Compared to other topics, ethics education for e-services takes long time
because of its characteristics. Thus, Cyberethics education is required from childhood. In this paper, we
examine the status of the Korean teenagers’ technology addiction, their personal characteristics, and their
environmental factors composed of parents, friends, and media to diagnose their behavior and to boost their
morality. In order to achieve our research goals, we survey 1,421 primary and secondary school students,
and then do factor, regression, and dominance analyses. Also, we examine the relationships between the
students’ characteristics and their technology addiction. We focus on the Internet and mobile phone
addiction as technology addiction. Based on this study, we summarize a few issues to be solved for our
adolescents to do their right actions on e-environment.
1 INTRODUCTION
As people have used the technology such as the
Internet or mobile devices in their daily lives
recently, their dependency on the technology are on
the increase. Most people are already familiar with
shopping on the Internet and studying with e-
Learning contents. Thus, the technology becomes
indispensable to their lives. However, the side
effects of the technology also occur when we use
various kinds of e-services (Smglo, 2006) (Petrovic-
Lazarevic et al., 2004). One of the side effects is
technology addiction. Unlike the substantial
addictions such as alcohol and drug, the technology
addiction has two sides because many companies
and schools require the fluency on the technology to
fulfil their organizations’ profit. Thus, it is not easy
to handle the technology addiction in such an
environment. Also, appropriate educational solutions
and the construction of social and cultural
environment are needed to prevent the technology
addiction and to enhance the technology fluency.
On the ther hand, many scholars have been
interested in time perspective (Zimbardo et al.,
2009) for people’s successful business and lives.
There are several researches on time perspective that
influences academic achievement, socio-economic
status, and leadership (Barber et al., 2008) (Guthrie
et al., 2009) (Humaira, 2006). In summary, time
perspective is regarded as an important yardstick to
explain a person’s characteristics. Recently, the
research about substance addiction combined with
time perspective has started (Apostolidis et al., 2006)
(Romer et al., 2010). However, there rarely exists
the research about technology addiction and time
perspective together. In particular, in spite of the
importance of time perspective, it is hard to find
education about time perspective for children.
In this paper, we analyze how our teenagers’
characteristics have influences on their technology
addiction, especially on the Internet and mobile
phone addiction. In order to achieve the research
objective, we select 5 factors: the present time
perspective (PTP), the future time perspective (FTP),
parents’ negative attitude factor, friend factor, and
media factor. The two time perspectives are self
factors and the rest of the factors are environmental
factors. The friend factor represents the self-efficacy
about friends, called social-efficacy, whereas the
media factor is the self-efficacy about media, called
media-efficacy. In addition, we examine the
relationships between the 5 factors and the two
103
Jung Park C. and Suk Hyun J..
The Relative Importance of Teenagers’ Personal Characteristics on Technology Addiction.
DOI: 10.5220/0004026301030108
In Proceedings of the International Conference on Data Communication Networking, e-Business and Optical Communication Systems (ICE-B-2012),
pages 103-108
ISBN: 978-989-8565-23-5
Copyright
c
 2012 SCITEPRESS (Science and Technology Publications, Lda.)

addictions. Finally, we present the relative
importance of the 5 factors on the two addictions.
Based on these results, we define the potential
problems of the teenagers’ behavior with respect to
media-efficacy and propose a desirable educational
way to solve the problems.
2 BACKGROUND
In this Section, we describe the types of time
perspectives proposed by Zimbardo. And then, we
summarize the previous research related to the time
perspectives to see how they affect people’s lives.
2.1 Zimbardo et al.’s Time Perspective
Zimbardo et al. (2009) proposed 6 types of time
perspectives as follows: the Past-negative (PN), the
Past-positive (PP), the Present-fatalistic (PF), the
Present-hedonistic (PH), the Future (F), and the
Transcendental-future (TF). In addition, in 1997 and
in 1999, they made ZTPI (ZTIP, n.d.) and TTPI
(Transcendental-future Time Perspective Inventory)
(TTPI, n.d.).
The web site for Ideal Time Perspective (http://
www.thetimeparadox.com/surveys/) shows a figure
that contains the survey result of the average score
for the 6 time perspectives so far. According to the
survey, the 6 average scores are 3.0 (PN), 3.7 (PP),
2.4 (PF), 3.4 (PH), 3.5 (F), and 3.3 (TF). The ideal
scores are 1.95 (PN), 4.6 (PP), 1.5 (PF), 3.9 (PH),
4.0 (F), and 3.3 (TF). The maximum score is 5.0 and
the minimum score is 1.0. It means that the ideal
time perspective is the combination of the low level
past negative, the high level past positive, the low
level present fatalism, the high level present
hedonism and future, and middle level trans-
cendental future time perspectives.
However, it remains unexplored whether we can
apply the same time perspective rules to teenagers
for measuring their time perspectives. In other
words, there is no evidence if the high level of the
present hedonistic time perspective is desirable for
teenagers who are morally immature.
2.2 Related Works
In Barber et al.’s research (2008), the relationship
between time perspective of college students and
their academic achievement levels were described.
The number of the students was 255. GPA was the
measure for their academic achievement. According
to their experiment, when students have high levels
of self-control, their time perspectives do not work
well. However, when the students have low levels of
self-control, the results are different. The students at
a high level FTP have higher GPAs than the students
at a high level PTP.
In Guthrie et al.’s research (2010), people’s
socio-economic status was included. The subjects
were 525 adults. The more the subjects are educated,
the higher the levels of their FTP are. The more
professional job they have, the higher the levels of
their FTP are. Besides, there are lots of researches
on the relationship between the time perspective and
value (Taciano et al., 2006), happiness (Zhang et al.,
2011), health (Daugherty et al., 2010), suicide
(Laghi et al., 2009), and so on.
3 EXPERIMENT
3.1 The Respondents
In our experiment, there were 1,421 students as
shown in Table 1. As already described in Section 1,
the students were in the 5
th
~ 6
th
, the 8
th
~ 9
th
, and the
11
th
~ 12
th
grades. We surveyed at 1 primary school,
2 middle schools, and 2 high schools.
Table 1: The respondents.
Gender
School
Male
Female
Total
Primary school
87
95
182(12.8%)
Middle school
254
382
636(44.8%)
High school
297
306
603(42.4%)
Total
638
(44.9%)
783
(55.1%)
1421
(100%)
3.2 Test Measurements
Our questions for the Internet addiction test were
made based on Young’s measures (Young, 1998).
They were composed of 25 questions. For each
question, there are 5 levels such as rarely (1 point),
occasionally (2 points), frequently (3 points), often
(4 points), and always (5 points). Thus, a person can
get 25 points as the minimum and 120 points as the
maximum. Based on the range of the total score, we
could divide the respondents into three groups (mild,
moderate, and severe). Recently, several researches
indicated the drawbacks of the Young’s measure
(Kang et at., 2001) (Park et al., 2010). The measure
is not suitable for Korean adolescent in some aspects.
Unlike Young’s measure, we added students’
emotion category such as intoxication in the virtual
world and patience to the measures, and then
modified them to be suitable to our teenagers. Our
ICE-B 2012 - International Conference on e-Business
104

questions fall into 4 categories: cyber world
directivity, overindulgence in the Internet, ordinary
life disorder, and the loss of self-control.
Similarly, the measures for testing mobile phone
addiction were prepared based on the research
outcome of Koh et al. (2011). Basically, since the
testing measures for mobile phone addiction came
from the Internet addiction test measures, the
measures had similar categories to the Internet
addiction test measures. There were also four
categories such as the loss of self-control, depression
and obsession, ordinary life disorder, and refreshing
in emotion.
3.3 The Five Predictors
We proposed 5 predictors as shown in Table 2. The
factors were recomposed from several research
works such as (Ryu et al., 2004), (Shin, 2008), and
(Han et al., 2009). And then, we performed the focus
group interview with 5 teachers to examine the
questions. In fact, Table 2 shows the result of the
factor analysis we performed. The 2 types of time
perspective represent a student’s own self factors.
The rest of the predictors represent his/her
environmental factors.
4 RESULTS
4.1 Time Perspective
Firstly, we describe the result of the analysis of
variance which contains the differences in time
perspectives among school groups (primary, middle,
and high). The questions for measuring time
perspectives came from (ZTPI, n.d.). The maximum
score for each time perspective is 5. As shown in
Table 3, the differences among school groups were
significantly different (PTP: F(2, 1418) = 7.53, p
< .005, FTP: F(2, 1418) = 6.00, p < .005). We
confirmed that primary school students had the
lowest average PTP score and the highest average
FTP score. The middle and high school students had
similar time perspectives. The average PTP score
increased as the school grade went up whereas the
average FTP score decreased as the school grade
went up. These results were similar to those of
Mello et al. (2006). One difference was that in case
of the FTP score, high school students had a little bit
higher score than middle school students.
Table 2: The 5 predictors.
Factors
Related items
PTP
(Present Time
Perspective)
Factor
 It is important to establish my future plan.
 Since whatever will be will be, it doesn’t really
matter what I do.
 If things don’t get done on time, I don’t worry
about it.
 I take each day as it is rather than try to plan it
out.
 Fate determines much in my life.
 There is enough time to do my postponed
works.
 My life path is controlled by forces I cannot
influence.
 Fortune brings better outcomes than effort do.
 Spending what I earn on pleasures today is
better than saving for tomorrow’s security.
FTP
(Future Time
Perspective)
Factor
 I meet my obligations to friends and authorities
on time.
 It upsets me to be late for appointments.
 I complete projects on time by making steady
progress.
 I am able to resist temptations when I know that
there is work to be done.
Parents
(negative
attitude toward
their children)
Factor
 Parents shout and scold me.
 Parents neither respect my individuality nor pay
attention to me.
 Parents meddle in my affairs very much.
 Parents are uncooperative.
Friends
(social-efficacy)
Factor
 When I make friends, I approach them first.
 I rarely give up friendship.
 It is easy for me to make friends.
Media
(media-efficacy)
Factor
 If I can know about the Internet very well, I can
study better than now.
 If I can study with the Internet, then I can
achieve higher learning efficiency.
 I can teach my friends about the Internet.
Table 3: School group difference in the PTP scores and the
FTP scores.
N
Mean
Standard Deviation
PTP
score
P
182
2.37
.66
M
636
2.53
.55
H
603
2.54
.52
FTP
score
P
182
3.26
.47
M
636
3.12
.45
H
603
3.14
.47
SS
df
F
Sig.
PTP
Inter
4.7
2
7.53
.001
*
Intra
437.5
1418
Total
442.2
1420
FTP
Inter
2.6
2
6.00
.003
*
Intra
302.1
1418
total
304.7
1420
Note. P: primary school, M: middle school, H: high school, SS:
sum of square, df: degree of freedom, Sig.: significance
However, their difference was not significantly
different. The result of the post-hoc analysis by
using the LSD (Least Significant Difference) test
was as follows: for the PTP, (i) the mean differences
between primary-middle school and between
primary-high school were -.16(p < .005) and -.18(p <
.0005) and for the FTP, the mean differences
between primary- middle and between primary-high
were -.13 (p < .005) and -.11(p < .01) respectively.
Next, we describe the result of t-test which shows
The Relative Importance of Teenagers' Personal Characteristics on Technology Addiction
105

the differences between male and female students.
The differences were significantly different (PTP: t
= 3.44, df = 1419, p < .005, FTP: t = -2.32, df =
1419, p < .05). Also, the male students had a higher
average PTP score (2.59) than the female students
(2.5), whereas the female students have a higher
average FTP (3.03) score than the male students
(2.96).
4.2 Technology Addiction
In this Subsection, we describe the result of the
analysis of variance which tells the differences in the
Internet and mobile phone addiction points among
school groups. For the two addiction points, the
middle and the high school students had higher
scores than the primary school students. And, their
gap was significantly different as shown in Table 4
(Internet: F(2, 1418) = 88.81, p < .0005, Mobile:
F(2, 1418) = 63.63, p < .0005). As school grade
went up, the Internet and mobile phone addiction
points also increased (Internet: 34.3(P) < 44.6(M) <
45.4(H), Mobile: 29.7(P) < 44.2(M) < 46.6(H)).
In addition, according to the result of the post-
hoc analysis by using the LSD test, all groups were
different for mobile phone addiction ((i) primary-
middle = -14.46(p < .0005), (ii) middle-high = -2.39
(p < .001), (iii) high-primary = 16.85(p < .0005). In
case of the Internet addiction, there was a significant
difference between primary-middle and between
primary-high ((i) primary-middle=-10.31(p <
.0005), (ii) high-primary = 11.08 (p < .0005).
Table 4: School group differences in the two addictions.
Average square
df
F
Sig.
Internet
Inter
20249.3
2
88.81
.000
*
Intra
228.0
1418
Total
1420
Mobile
phone
Inter
9150.8
2
63.63
.000
*
Intra
143.8
1418
total
1420
Note. P: primary school, M: middle school, H: high school
Next, we describe the result of t-test which
shows the difference between two genders. The
differences are significantly different (Internet: t =
10.36, df = 1419, p < .0005, Mobile Phone: t =-6.83,
df = 1419, p < .0005) as shown in Table 5. In case
of the Internet addiction, the male students’ mean
score was higher than the female students’ average.
However, in case of mobile phone addiction, the
female students’ mean score was higher than the
male students’ mean score.
4.3 Regression Analysis
In this Subsection, based on the result of our factor
analysis shown in Table 2, we present the result of
regression analysis to see which factors influence the
Internet addiction and mobile phone addiction.
Table 5: Gender difference in two addictions.
N
Mean
Standard Deviation
Internet
Male
638
47.3
11.66
Female
783
40.6
12.38
Mobile
phone
Male
638
40.2
15.13
Female
783
46.0
16.24
Firstly, Table 6 describes how the 5 factors
influenced the students’ Internet addiction. All
predictors were statistically significant to the
Internet addiction. Among the 5 factors, the FTP and
the social-efficacy had negative relationships with
the Internet addiction. In other words, a student’s
Internet addiction point decreased when his/her FTP
score increased. The social-efficacy had the same
result as the FTP score. However, the present time
perspective, parents’ negative attitude toward
children, and high levels of media-efficacy affected
the Internet addiction positively.
Table 6: The student’s individual 5 factors and the Internet
addiction.
Factors
B
Beta
T
Sig.
constant
43.63
-
151.63
.000
PTP (X
1
)
4.67
.37
16.23
.000
*
Parents (X
2
)
2.50
.20
8.68
.000
*
FTP (X
3
)
-1.63
-.13
-6.67
.000
*
Friends (X
4
)
-1.07
-.09
-3.72
.000
*
Media (X
5
)
2.72
.22
9.45
.000
*
R
2
=.251, F=94.78, p <.0005
Next, Table 7 shows how the 5 predictors
influence the students’ mobile phone addiction.
Similar to the Internet addiction, the PTP, parents,
and media-efficacy factors affected on mobile phone
addiction and had positive relationships with it.
Also, the FTP factor had a negative relationship with
mobile phone addiction. However, in case of mobile
phone addiction, the social-efficacy did not
influence mobile phone addiction.
Table 7: The student’s individual 5 factors and mobile
phone addiction.
Factors
B
Beta
t
Sig.
constant
43.36
106.00
.000
PTP (X
1
)
2.66
.17
6.50
.000
*
Parents (X
2
)
2.77
.17
6.76
.000
*
FTP (X
3
)
-1.36
-.09
-3.33
.001
*
Friends (X
4
)
.71
.04
1.73
.083
Media (X
5
)
1.48
.09
3.62
.000
*
R
2
=.075, F=23.04, p <.0005
ICE-B 2012 - International Conference on e-Business
106

4.4 Relative Importance
In this Subsection, we use dominance analysis
(Budescu, 1993) to investigate the relative effects of
the 5 predictors on the Internet and mobile phone
addictions. We cannot assure the relative importance
among predictors by using the coefficient value, B,
in a regression analysis. In order to measure that,
Budescu (1993) proposed a novel way to calculate
the dominance among predictors. In Budescu’s
research, the dominance analysis is defined to
measure the relative importance among different
variables, which are obtained from a factor analysis.
The calculation method and its proof are given in
(Behson, 2002). Let k be the number of variables
already in the equation. For a predictor, x
i
, (1  i  the
number of predictors), M(Cx
i
) is defined as a mean
usefulness index and it means the average of the
average R
2
for all k (0 k < 5). The total R
2
was .251
and each M(Cx
i
)s were .1393, .0400, .0170, .0073,
and .0473 respectively. The sum of all M(Cx
i
)s
equals to the total R
2
. The result indicated that
among the 5 predictors, the PTP took the biggest
portion (55.6%). It was followed by media-efficacy
(18.8%). The rest were 15.9% (parents), 6.8% (the
FTP), and 2.9% (social-efficacy). Thus, the PTP
exerted the greatest marginal influence on the
Internet addiction. The next three factors were
media-efficacy, parents, and the FTP.
Next, for mobile phone addiction, the M(Cx
i
)s
were .0276 (PTP, 36.75%), .0299 (parents, 39.81%), .0071
(FTP, 9.45%), .002 (social-efficacy, 2.66%), and .0086
(media-efficacy, 11.33%). In case of mobile addiction,
the PTP factor and the parental factor had similar
portion in their importance. In fact, the social-
efficacy was not significant for mobile addiction.
Unlike the Internet addiction, parents’ negative
attitude toward their children exerted the greatest
influence. The next three factors were the PTP,
media-efficacy, and the FTP. From our experiment,
we confirmed that there were differences in factors
which influence the Internet and mobile phone
addictions.
4.5 Media-efficacy
According to the results of the dominance analysis,
the media-efficacy is an important factor which can
influence the two addictions. The media-efficacy is
important when we use new technologies. The
positive effect of the media-efficacy brings
technology fluency. However, the negative effect of
the media-efficacy brings technology addiction. We
show the media-efficacy effect with the purposes of
the Internet usages and academic achievement levels.
Firstly, as the Internet addiction level increased,
students used the Internet usage to play on-line
games more (20% < 30.4% < 42.5%). However, the
less the number of students who used the Internet for
‘information acquisition for homework’ was, the
lower the addiction level was (10.7% < 5.1% < 3.1%).
Next, we compared the same analysis with academic
achievement levels and the purposes of the Internet
usage. The higher the academic achievement level
was, the higher the number of students who use the
Internet for ‘information acquisition for homework’
was.
In summary, having media-efficacy is important
to teenagers because they must have media-efficacy
for a better use of technology. However, if they are
educated in a wrong way and if they have a biased
attitude towards technology or they have a wrong
concept on media-efficacy, then they can be
addicted to the technology. Thus, schools and
institutes should examine their instructional methods
and contents to educate teenagers to use technology
positively in the future.
5 CONCLUSIONS
In this paper, we examine the relationship between
the self and the environmental factors of Korean
teenagers and technology addiction. As the factors,
the present time perspective, the future time
perspective, parents, friends, and media were studied.
We focused on the Internet and mobile phone
addiction as technology addiction. Also, we
presented which factor was the most influential to
the two addictions by dominance analysis.
In case of the Internet addiction, all the 5 factors
influenced the Internet addiction. Among the 5
factors, the present time perspective was the greatest
factor that influences the addiction. On the other
hand, in case of mobile phone addiction, 4 factors
(except social-efficacy) influenced mobile phone
addiction. And, the parental factor was the greatest
among the factors.
We confirmed that time perspective factor is
important to control the addiction level from our
research. Therefore, if teachers can make their
students have a high level of the future time
perspective and a low level of the present time
perspective, then their education will contribute to
reduce the technology addiction level in the future.
In addition, media also plays an important factor
for the two addictions. This result may bring
misunderstanding that if students can use the
The Relative Importance of Teenagers' Personal Characteristics on Technology Addiction
107

Internet very well, then they are easy to be addicted
to the Internet. However, students cannot study
without technology in the future. To prohibit the use
of technologies is not the right answer. The existing
educational methods for media including the Internet
and mobile devices should be modified. There has
been no consideration of ethics in technology
education. In the future, new educational methods
should be developed for teenagers.
ACKNOWLEDGEMENTS
The authors would like to thank Mr. Dong Hwan
Kim to help us make the questionnaires and to
gather data.
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