ORIGINAL PAPER
Internet use and misuse: a multivariate regression
analysis of the predictive factors of internet
use among Greek adolescents
Artemis Tsitsika
&
Elena Critselis
&
Georgios Kormas
&
Anastasia Filippopoulou
&
Despoina Tounissidou
&
Aliki Freskou
&
Theodora Spiliopoulou
&
Amalia Louizou
&
Eleftheria Konstantoulaki
&
Dimitrios Kafetzis
Received: 30 May 2008 / Accepted: 4 August 2008 / Published online: 2 September 2008
# Springer-Verlag 2008
Abstract The internet is an integral tool for information,
communication, and entertainment among adolescents. As
adolescents devote increasing amounts of time to utilizing
the internet, the risk for adopting excessive and patholog-
ical internet use is inherent. The study objectives include
assessing the characteristics and predictors of excessive
internet use and evaluating the prevalence of pathological
internet use among Greek adolescents. A cross-sectional
study design was applied to this effect. The study
population (
n=897) consisted of a random sample of
adolescents residing in Athens, Greece. Self-completed
questionnaires, pertaining to internet access characteristics
and Young
’s Internet Addiction Scale (YIAS) score, were
applied in order to investigate the study objectives. The
multivariate regression analysis indicated that the most
significant predictors of overall internet use included
accessing the internet via one
’s own home portal and for
the purpose of social interaction. Internet access via the
school environment was a significant deterrent among low
(1
–3 h/week) internet users, while access via internet cafés
was a significant predictor for high (11
–20 h/week) internet
users. Moreover, accessing the internet for the purposes of
game playing was the most significant predictor for
excessive (>20 h/week) internet use. The prevalence of
borderline internet use among the study population was
12.8%, while 1.00% reported addictive internet use. Also,
10.4% of male excessive internet users reported addictive
internet use (
p<0.0001). In conclusion, excessive internet
use is predicted solely by the location of internet access
(own home portal) and the scope of internet use (i.e., sites
relating to socialization and game playing) and may lead to
internet addiction, particularly among male adolescents.
Keywords Adolescent . Internet use .
Internet addiction . Greece
Introduction
In an ever-growing digitalized world, the internet has
become an integral tool for information, social communi-
cation, and entertainment. As novel, albeit savvy, users of
technology, adolescents are reported to spend ever increas-
ing amounts of time utilizing computers and the internet
[
]. For adolescents, the internet serves as an inexpensive,
readily accessible platform for social interaction [
] and
leisurely activities [
].
The positive penetrating effects of enhanced internet use
upon adolescent psychosocial development and behavior
Eur J Pediatr (2009) 168:655
–665
DOI 10.1007/s00431-008-0811-1
A. Tsitsika (
*)
:
G. Kormas
:
A. Filippopoulou
:
D. Tounissidou
:
A. Freskou
:
T. Spiliopoulou
:
A. Louizou
:
E. Konstantoulaki
Second Department of Pediatrics,
“P. & A. Kyriakou” Children’s Hospital,
Adolescent Health Unit (AHU), University of Athens,
Leoforos Mesogeion 24, Goudi,
Athens 11527, Greece
e-mail: info@youth-health.gr
E. Critselis
:
D. Kafetzis
Second Department of Pediatrics,
“P. & A. Kyriakou” Children’s Hospital,
National and Kapodistrian University
of Athens School of Medicine,
Athens, Greece
are primarily signified by the fact that the internet has come
to serve as an interface for creating an entire social context
of its own among members of this age group [
]. It has also
been posited that the internet empowers youth and reduces
anxiety [
], while it has been observed that experiences
via the internet positively affect social and moral knowl-
edge among adolescents [
However, the adoption of daily internet use does include
potential detrimental effects upon the psychosocial devel-
opment and behavior of adolescents. Internet use is
observed to affect each adolescent differently, according
to his/her psycho-emotional and internet use characteristics
[
]. Potential adverse effects arising from internet
use are attributed primarily to the adolescents
’ prior lack of
psychosocial well-being [
]. Since adolescence is a critical
period for addiction vulnerability [
], when compared to
adults, adolescents are more likely to adopt patterns of
excessive internet use. Stressful life events have been
associated with such patterns of behavior in order to
address mood management and social compensation [
Shapira et al. [
] defined problematic internet use by
the following characteristics: (1) uncontrollable internet
use; (2) internet use which is markedly distressing, time-
consuming, or results in social, occupational, or financial
difficulties; and (3) internet use not solely present during
hypomanic or manic clinical episodes [
]. A most recent
definition for addictive internet use (AIU) is described as
presenting with at least five of the six following criteria: (1)
spending increasing amounts of time online; (2) failure to
cut back use with concomitant feelings of restlessness and
depression; (3) staying online longer than originally
intended; (4) running the risk of losing a relationship or
other opportunity due to internet use; (5) lying in order to
conceal the extent of internet use; (6) using the internet in
order to escape negative feelings [
]. However, there are
individuals that have a number, but not all, of the proposed
criteria and are at risk of developing future full disorder.
These at-risk individuals are borderline internet users (BIU)
[
], and they evidently belong to the respective category
of Young
’s Internet Addiction Scale (YIAS) tool. Both BIU
and AIU are non-healthy behaviors, as far as internet use is
concerned, and represent subcategories of pathological
internet use (PIU), according to the Kaplan and Sadock
’s
categorization [
].
Excessive and pathological internet users are inevitably
led to make regular and intense use of the internet, with
regard to both the frequency and duration of each internet
session, especially for accessing e-mail, chat rooms, and
internet games [
]. Since both excessive (a time-dependent
definition of internet use) and PIU (a behavioral-dependent
definition of internet use) may lead adolescents to problem-
atic academic achievement [
], as well as dysfunctional
psychosocial interactions and interpersonal relationships
], it is imperative to examine the manner by which
adolescents utilize the internet [
] and the association
between the predefined types of internet use.
Thus, the objectives of the present study include the
following: (1) to evaluate the prevalence of internet use,
according to the average total hours per week of internet
use, among Greek adolescents; (2) to assess the charac-
teristics of internet use, according to the average total hours
per week of internet use; and (3) to measure the prevalence
of PIU, including both BIU and AIU, among Greek
adolescents.
Materials and methods
Study design and study population
A cross-sectional study design was applied for the
implementation of the present investigation. All data were
collected during the period from 1st January 2007 to 1st
January 2008. The study proposal was approved by the
Ethical Committee of both the
“P. & A. Kyriakou”
Children
’s Hospital in Athens, Greece, and the Hellenic
Ministry of Education and Religious Affairs. Informed
consent for study participation was requested from the
parents of eligible study participants two weeks prior to the
initiation of the investigation by their respective high
school authority.
The source population for the present study consisted of
a random sample, stratified according to locality and
population density, of public junior high and high schools
located in the urban district of Attica, Greece. All students
enrolled in Grades 9 and 10 at the aforementioned
randomly selected schools were invited to participate in
the study (
n=953). No exclusion criteria for participation
in the present study were applied. The source population of
the study consisted of 438 boys and 499 girls, with an
overall mean age of 15.21 years. Sixteen participants
(1.7%) did not specify their gender and were excluded
from all further statistical analyses. Among the remaining
eligible source population (
n=937), the response rate for
specifying the total weekly hours of internet use was
95.73% (
n=897). Hence, it is upheld that a selection bias
was deterred in the present study.
Data collection
Anonymous self-completed questionnaires were distributed
to all of the study participants on-site at their respective
schools. The study participants were requested to complete
the questionnaire anonymously in order to minimize any
potential reporting bias. The questionnaire consisted of five
components: (1) average total hours per week of internet
656
Eur J Pediatr (2009) 168:655
–665
use; (2) demographic information; (3) history of internet
use; (4) characteristics of internet use; and (5) YIAS.
The study participants reported the average quantity of
hours per week that they utilized the internet, irrespectively
of the scope of the sites accessed. With regard to the average
quantity of hours per week of internet use, the following
cutoff points were applied: (1) non-users (controls): 0
–1 h/
week; (2) low internet users (case group 1): 1
–3 h/week; (3)
medium internet users (case group 2): 4
–10 h/week; (4) high
internet users (case group 3): 11
–20 h/week; and (5) excessive
internet users (case group 4): >20 h/week of internet use.
The demographic variables examined included those of
age, gender, body mass index (BMI), and current academic
achievement (grade point average or GPA). The history of
internet use was assessed by examining when study
participants had first initiated the use of the internet. With
respect to the history of internet use, the following cutoff
points were applied: (1) 0
–6 months; (2) 6–12 months; and
(3) >12 months. The characteristics of internet use assessed
included both the locations of internet use and the scope of
the sites visited. The locations of internet access included
the following categories: (1) internet access via one
’s own
home portal; (2) a friend
’s home portal; (3) school portal;
(4) library portal; and (5) internet café portal. The purpose
and scope of the internet sites visited included the following
categories: (1) e-mail correspondence; (2) retrieval of
newspapers, journals, and periodicals; (3) chat room use;
(4) internet games; (5) retrieval of information pertaining to
services; (6) retrieval of information pertaining to work and
education; (7) retrieval of information pertaining to sexual
education; and (8) the purchases of goods and services.
The YIAS was applied in order to assess the prevalence
of BIU and AIU, respectively, as validated in the scientific
literature [
]. This scale examines the degree of
preoccupation, compulsive use, behavioral problems, emo-
tional changes, and impact upon functionality, as related to
internet usage. The YIAS consists of 20 items, which
provide calibrated scores ranging from 1 to 5, where a score
of 1 is defined as
‘‘not at all’’ and a score of 5 as ‘‘always,’,
respectively. Hence, the total YIAS score may range from
20 to 100, where higher total scores reflect a greater
tendency toward internet addiction [
]. As established in
the scientific literature [
], the following cutoff points
were applied to the total YIAS scores: (1) normal internet
use: scores 0
–39; (2) BIU: scores 40–69; and (3) AIU:
scores 70
–100.
Statistical analysis
All statistical analyses were conducted with the application
of the SAS version 9.0 (SAS Institute Inc., USA) software
package. The predefined control group (0
–1 h/week) was
applied as the basis of comparison for all of the statistical
analyses undertaken. A
p-value of ≤0.05 was considered as
the criterion for statistical significance for all analyses.
The Mantel-Haenszel method was applied in order to
calculate the odds ratios (OR) and their respective 95%
confidence intervals (95% CI) for demographic variables
and characteristics of internet use between each case group,
as defined by the average total hours per week of internet
use, and the control group. The Mantel-Haenszel method
was also applied in order to calculate the OR and respective
95% CI for the characteristics of internet use between each
case group, as defined by the average total hours per week
of internet use, and the control group, according to the
gender of the study participants.
Furthermore, the Chi-square test (
X
2
) was also applied in
order to evaluate the association between both BIU and
AIU, respectively, and each case group of weekly hours of
internet use according to gender. It is in this manner that
the study aimed to decipher the association between PIU
(a psychiatric component of internet use) and excessive
internet use (a time-dependent component of internet use).
Stepwise forward multivariate logistic regression analy-
ses were applied in order to evaluate the contribution of
selected demographic variables and characteristics of
internet use variables upon the risk for adolescents adopting
low (1
–3 h/week), medium (4–10 h/week), high (11–20 h/
week), and excessive (>20 h/week) internet use, respec-
tively. A statistical significance criterion of
p<0.05 was
applied for all variables retained in the final multivariate
logistic regression model. Multivariate logistic regression
analyses were also applied in order to calculate the adjusted
OR and 95% CI of the variables retained in the final
regression models.
Results
Low internet use (1
–3 h/week)
Table
shows that low internet use is not statistically
significantly associated with age, gender, BMI, or current
grade point average. However, low internet use is signifi-
cantly associated with a history of internet use. In addition,
low internet users appear to be most likely to access the
internet either via their own home or internet cafés. It is
important to note that internet access via the school
environment appears to be negatively associated with the
adoption of low internet use. Table
indicates that male
low internet users predominantly access the internet for the
purposes of games playing (73.5%), while female users
predominantly use the internet to access e-mail (46.4%).
With regard to the scope of the sites accessed, low internet
use is significantly associated with access to sites relating to
e-mail and chat room use among both genders. However,
Eur J Pediatr (2009) 168:655
–665
657
T
able
1
Demographic
characteristics
and
risk
factors
for
internet
use
among
Greek
adolescents,
according
to
the
total
number
of
hours
per
week
of
internet
us
e(
n
=
897)
0–
1
h/week
(n
=
277)
1–
3
h/week
(n
=
318)
4–
10
h/week
(n
=
191)
1
1–
20
h/week
(n
=
55)
>20
h/week
(n
=
56)
n
(%)
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
Age
<15
years
193
(69.7)
207
(65.1)
0.71
0.49
–1.03
1
1
2
(58.6)
0.59
0.39
–0.90
31
(56.4)
0.48
0.26
–0.90
31
(55.4)
0.60
0.31
–1.15
0.31
–1.15
15
–15.9
years
63
(22.7)
104
(32.7)
––
62
(32.5)
––
21
(38.2)
––
17
(30.4)
––
>16
years
8
(2.9)
7
(2.2)
0.58
0.20
–1.68
8
(4.2)
1.02
0.36
–2.88
1
(1.8)
0.38
0.04
–3.18
3
(5.4)
1.39
0.33
–5.81
Gender
Male
98
(35.4)
132
(41.5)
––
107
(56.0)
––
38
(69.1)
––
48
(85.7)
––
Female
177
(63.9)
183
(57.5)
0.77
0.55
–1.07
84
(44.0)
0.43
0.30
–0.63
18
(32.7)
0.27
0.14
–0.50
8
(14.3)
0.09
0.04
–0.20
BMI
<18.5
kg/m
2
169
(61.0)
194
(61.0)
0.95
0.66
–1.36
104
(54.4)
0.71
0.48
–1.06
27
(49.1)
0.69
0.36
–1.31
26
(46.4)
0.52
0.28
–0.97
18.5
–24.9
kg/m
2
82
(29.6)
99
(31.1)
––
71
(37.2)
––
19
(34.5)
––
24
(42.8)
––
>25.0
kg/m
2
5
(1.8)
5
(1.6)
0.83
0.23
–2.96
4
(2.1)
0.92
0.24
–3.57
4
(7.3)
3.45
0.85
–14.09
3
(5.4)
2.05
0.46
–9.20
GP
A
<C+
74
(26.7)
83
(26.1)
––
51
(26.7)
––
15
(27.3)
––
16
(28.6)
––
B
–
to
B+
1
1
6
(41.9)
131
(41.2)
1.01
0.67
–1.50
79
(41.4)
0.99
0.62
–1.56
24
(43.6)
1.02
0.50
–2.07
27
(48.2)
1.08
0.54
–2.13
A
–
to
A+
70
(25.3)
87
(27.4)
1.1
1
0.71
–1.73
51
(26.7)
1.06
0.64
–1.76
13
(23.6)
0.92
0.41
–2.06
9
(16.1)
0.59
0.25
–1.43
History
of
internet
use
0–
6
months
181
(65.3)
101
(31.8)
––
30
(15.7)
––
5
(9.1)
––
3
(5.4)
––
6–
12
months
18
(6.5)
50
(15.7)
4.98
2.76
–8.99
34
(17.8)
11.40
5.72
–22.71
5
(9.1)
10.06
2.66
–38.05
4
(7.1)
13.41
2.78
–64.66
>12
months
72
(26.0)
163
(51.2)
4.06
2.80
–5.87
127
(66.5)
10.64
6.57
–17.24
45
(81.8)
22.62
8.63
–59.29
48
(85.7)
40.22
12.14
–133.27
OR
=
unadjusted
odds
ratio
95%
CI
=
95%
confidence
interval
for
the
unadjusted
odds
ratio
658
Eur J Pediatr (2009) 168:655
–665
female low internet users are significantly more likely to
access the internet for the purposes of services, as compared
to their non-user counterparts (Table
With regard to the findings of the YIAS, only female
low internet use is significantly associated with BIU.
Addictive use of the internet is not reported in this category
(Table
The multivariate regression analysis rendered for the
prediction of the occurrence of low internet use among
Greek adolescents indicated that the most significant
predictive factors of low internet use included internet
access for the purposes of e-mail use (adjusted OR: 2.10;
95% CI: 1.37
–3.23), chat room use (adjusted OR: 1.91;
95% CI: 1.25
–2.93), accessing the internet via one’s home
portal (adjusted OR 1.22; 95% CI: 1.22
–2.77), and a
history of internet use (adjusted OR: 1.53; 95% CI: 1.23
–
1.89). Internet access via the school environment appears to
have a negative effect on the adoption of low internet use
(adjusted OR: 0.59; 95% CI: 0.37
–0.94), as indicated in
Table
Medium internet use (4
–10 h/week)
Table
shows that medium internet use is statistically
significantly associated with both gender and a history of
internet use. In addition, as shown in Table
, medium
internet users appear to be most likely to access the internet
either via their own home or via internet cafés. It is
important to note that medium internet users are signifi-
cantly less likely to access the internet within either the
school (OR: 0.35; 95% CI: 0.21
–0.58) and/or library (OR:
0.09; 95% CI: 0.012
–0.72) environments. With regard to
the scope of internet sites accessed, medium internet use
is significantly associated with access to sites relating to
e-mail and chat rooms, and are less likely to access the
internet for the purposes of retrieving information pertain-
ing to work or education (OR: 0.59; 95% CI: 0.40
–0.89)
(Table
). Moreover, male medium internet users were
found to be significantly more likely to access the internet
for the purposes of purchasing goods and sexual education
(Table
), while female medium internet users were
significantly more likely to access the internet for the
purposes of services (Table
).
BIU was found to be highest among male medium
internet users. Moreover, BIU was found to be significantly
associated with medium internet use among both genders.
Furthermore, 44.5% (
n=4) of AIU, as defined by the YIAS,
are observed within this group. While the percentage of
addicted male users was found to be twice that of female
users, AIU was not found to be significantly associated
with medium internet use (Table
).
The multivariate regression analysis rendered for the
prediction of the occurrence of medium internet use among
T
able
2
Characteristics
of
internet
use
among
Greek
adolescents,
according
to
the
total
number
of
hours
per
week
of
internet
use
(n
=
897)
0–
1
h/week
(n
=
277)
1–
3
h/week
(n
=
318)
4–
10
h/week
(n
=
191)
1
1–
20
h/week
(n
=
55)
>20
h/week
(n
=
56)
n
(%)
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
Primary
locations
of
internet
access
Own
house
124
(44.8)
229
(72.0)
2.90
2.06
–4.10
159
(83.2)
5.61
3.58
–8.80
52
(94.5)
19.57
5.96
–64.24
50
(89.3)
9.41
3.90
–22.70
Friend
’s
house
63
(22.7)
87
(27.4)
1.20
0.82
–1.75
37
(19.4)
0.77
0.48
–1.21
14
(25.4)
1.09
0.56
–2.13
12
(21.4)
0.87
0.43
–1.75
School
79
(28.5)
49
(15.4)
0.43
0.28
–0.64
25
(13.1)
0.35
0.21
–0.58
10
(18.2)
0.52
0.25
–1.08
6
(10.7)
0.28
0.12
–0.68
Library
14
(5.0)
9
(2.8)
0.52
0.22
–1.22
1
(0.5)
0.09
0.01
–0.72
2
(3.6)
0.67
0.15
–3.05
3
(5.4)
1.01
0.28
–3.64
Internet
café
80
(28.9)
125
(39.3)
1.49
1.05
–2.10
83
(43.4)
1.77
1.20
–2.61
33
(60.0)
3.45
1.89
–6.29
30
(53.6)
2.65
1.48
–4.77
Primary
objects
of
interest
via
internet
use
52
(18.8)
147
(46.2)
3.46
2.38
–5.04
121
(63.4)
6.98
4.57
–10.67
37
(67.3)
8.66
4.52
–16.59
42
(75.0)
11.94
6.07
–23.50
Mass
media
43
(15.5)
51
(16.0)
0.97
0.62
–1.51
38
(19.9)
1.25
0.77
–2.02
10
(18.2)
1.14
0.53
–2.44
1
1
(19.6)
1.26
0.60
–2.62
Chat
room
54
(19.5)
1
1
8
(37.1)
2.26
1.55
–3.30
100
(52.4)
4.17
2.76
–6.30
37
(67.3)
8.26
4.32
–15.79
35
(62.5)
6.32
3.41
–1
1.74
Games
131
(47.3)
181
(56.9)
1.31
0.94
–1.82
1
1
3
(59.2)
1.42
0.97
–2.06
41
(74.5)
3.08
1.58
–6.02
52
(92.8)
12.70
4.46
–36.14
Services
51
(18.4)
74
(23.3)
1.25
0.83
–1.86
48
(25.1)
1.37
0.87
–2.14
17
(30.9)
1.87
0.98
–3.59
23
(41.1)
2.84
1.54
–5.25
W
ork
and
education
100
(36.1)
103
(32.4)
0.77
0.54
–1.08
52
(27.2)
0.59
0.40
–0.89
12
(21.8)
0.45
0.23
–0.90
18
(32.1)
0.75
0.41
–1.39
Sexual
education
14
(5.0)
31
(9.7)
1.88
0.97
–3.61
26
(13.6)
2.77
1.40
–5.48
8
(14.5)
2.95
1.17
–7.45
15
(26.8)
6.40
2.86
–14.32
Purchases
of
goods
10
(3.6)
24
(7.5)
2.05
0.96
–4.36
28
(14.6)
4.28
2.02
–9.04
10
(18.2)
5.66
2.22
–4.39
14
(0.25)
8.30
3.46
–19.91
Eur J Pediatr (2009) 168:655
–665
659
T
able
3
Characteristics
of
internet
use
among
Greek
adolescent
boys,
according
to
the
total
number
of
hours
per
week
of
internet
use
(n
=
422)
0–
1
h/week
(n
=
98)
1–
3
h/week
(n
=
132)
4–
10
h/week
(n
=
107)
1
1–
20
h/week
(n
=
37)
>20
h/week
(n
=
48)
n
(%)
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
Primary
locations
of
internet
access
Own
house
39
(39.8)
88
(66.7)
2.62
1.50
–4.54
83
(77.6)
4.52
2.44
–8.38
34
(91.9)
14.82
4.24
–51.83
42
(87.5)
9.15
3.53
–23.71
Friend
’s
house
16
(16.3)
33
(25.0)
1.54
0.79
–3.01
22
(20.6)
1.20
0.58
–2.45
8
(21.6)
1.28
0.49
–3.30
10
(20.8)
1.22
0.50
–2.94
School
22
(22.4)
14
(10.7)
0.37
0.18
–0.76
15
(14.0)
0.50
0.24
–1.04
6
(16.2)
0.60
0.22
–1.62
4
(8.3)
0.28
0.09
–0.87
Library
5
(5.1)
3
(2.3)
0.40
0.09
–1.70
0
(0.0)
––
1
(2.7)
0.47
0.05
–4.19
3
(6.3)
1.13
0.26
–4.96
Internet
café
44
(44.9)
78
(59.1)
1.51
0.88
–2.59
57
(53.3)
1.19
0.68
–2.09
24
(64.9)
1.93
0.87
–4.26
27
(56.3)
1.34
0.66
–2.72
Primary
objects
of
interest
via
internet
use
20
(20.4)
61
(46.2)
3.01
1.64
–5.50
57
(53.3)
4.01
2.14
–7.52
21
(56.8)
4.83
2.1
1–
11.06
35
(72.9)
9.29
4.14
–20.84
Mass
media
13
(13.3)
19
(14.4)
0.99
0.46
–2.13
19
(17.8)
1.26
0.58
–2.72
8
(21.6)
1.67
0.62
–4.46
9
(18.8)
1.35
0.53
–3.43
Chat
room
20
(20.4)
47
(35.6)
1.93
1.05
–3.56
54
(50.5)
3.51
1.88
–6.57
24
(64.9)
6.90
2.94
–16.20
33
(68.8)
7.59
3.45
–16.68
Games
57
(58.2)
97
(73.5)
1.60
0.89
–2.87
78
(72.9)
1.51
0.82
–2.77
32
(86.5)
4.49
1.46
–13.85
46
(95.8)
12.91
2.94
–56.75
Services
28
(28.6)
32
(24.2)
0.70
0.39
–1.28
26
(24.3)
0.70
0.37
–1.31
13
(35.1)
1.23
0.54
–2.78
18
(37.5)
1.31
0.63
–2.73
W
ork
and
education
21
(21.4)
26
(19.7)
0.80
0.42
–1.54
21
(19.6)
0.79
0.40
–1.57
8
(21.6)
0.92
0.37
–2.33
15
(31.2)
1.47
0.67
–3.22
Sexual
education
7
(7.1)
21
(15.9)
2.13
0.86
–5.28
21
(19.6)
2.73
1.10
–6.81
8
(21.6)
2.90
0.96
–8.75
13
(27.1)
4.12
1.50
–1
1.30
Purchases
of
goods
5
(5.1)
10
(7.6)
1.39
0.46
–4.21
21
(19.6)
4.10
1.48
–1
1.38
7
(18.9)
4.06
1.19
–13.77
1
1
(22.9)
4.99
1.62
–15.39
T
able
4
Characteristics
of
internet
use
among
Greek
adolescent
girls,
according
to
the
total
number
of
hours
per
week
of
internet
use
(n
=
470)
0–
1
h/wee
k
(n
=
177)
1–
3
h/w
eek
(n
=
183)
4–
10
h/w
eek
(n
=
84)
1
1–
20
h/week
(n
=
18)
>20
h/w
eek
(n
=8
)
n
(%
)
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
n
(%)
OR
95%
CI
n
(%
)
O
R
95%
CI
Primary
locations
o
f
internet
access
O
w
n
hous
e
8
3
(46.
9)
140
(76.
5)
3.49
2.22
–5.50
76
(90.5)
10.1
9
4.63
–22.3
9
18
(100.0)
1.22
1.1
1–
1.33
8
(100.0)
1.10
1.03
–1.17
Fr
iend
’s
hous
e
4
6
(26.
0)
53
(29.0)
1.12
0.70
–1.78
15
(17.8)
0.60
0.31
–1.14
6
(33.3)
1.37
0.48
–3.86
2
(25.
0)
0.91
0.18
–4.69
Sc
hool
56
(31.
6)
33
(18.0)
0.46
0.28
–0.75
10
(1
1.9)
0.28
0.13
–0.58
4
(22.2)
0.59
0.19
–1.88
2
(25.
0)
0.69
0.14
–3.53
Li
brary
8
(4.5
)
6
(3.3)
0.69
0.24
–2.04
1
(1.2)
0.25
0.03
–2.01
1
(5.6)
1.20
0.14
–10.2
3
0
(0.0
)
1.14
*
0.06
–21.4
1
Inte
rnet
café
36
(20.
3)
46
(25.1)
1.27
0.77
–2.08
26
(31.0)
1.69
0.94
–3.06
9
(50.0)
3.78
1.40
–10.2
1
3
(37.
5)
2.27
0.52
–9.93
Primary
obje
cts
of
interest
via
internet
use
E-
31
(17.
5)
85
(46.4)
3.87
2.38
–6.30
64
(76.2)
14.1
4
7.49
–26.7
0
16
(88.9)
35.3
5
7.73
–161.
77
7
(87.
5)
30.9
4
3.67
–260.
64
Mas
s
media
29
(16.
4)
31
(16.9)
0.98
0.56
–1.72
19
(22.6)
1.40
0.73
–2.68
2
(1
1.1)
0.60
0.13
–2.75
2
(25.
0)
1.92
0.35
–10.3
7
Ch
at
room
34
(19.
2)
70
(38.2)
2.46
1.52
–3.98
46
(54.8)
4.77
2.69
–8.45
13
(72.2)
10.2
5
3.42
–30.7
2
2
(25.
0)
1.31
0.25
–6.80
G
ames
73
(41.
2)
81
(44.3)
1.04
0.68
–1.59
35
(41.7)
0.93
0.55
–1.58
9
(50.0)
1.30
0.49
–3.44
6
(75.
0)
3.90
0.76
–19.9
1
Se
rvices
22
(12.
4)
40
(21.8)
1.87
1.06
–3.30
22
(26.2)
2.35
1.22
–4.56
4
(22.2)
1.90
0.57
–6.28
5
(62.
5)
11.06
2.47
–49.5
6
W
ork
and
education
77
(43.
5)
76
(41.5)
0.85
0.56
–1.29
31
(36.9)
0.69
0.40
–1.18
4
(22.2)
0.34
0.1
1–
1.07
3
(37.
5)
0.71
0.16
–3.06
Se
xual
educa
tion
7
(4.0
)
9
(4.9)
1.19
0.43
–3.28
5
(6.0)
1.49
0.46
–4.84
0
(0.0)
0.62
*
0.03
–1
1.43
2
(25.
0)
7.33
1.25
–43.0
7
Pur
chases
of
good
s
5
(2.8
)
1
3
(7.1)
2.51
0.87
–7.19
7
(8.3)
2.96
0.91
–9.64
3
(16.7)
6.52
1.42
–29.9
9
3
(37.
5)
19.5
6
3.62
–105.
52
*Logit
estimator:
a
correction
of
0.5
in
every
cell
of
those
tables
that
contain
a
zero
has
been
applied
660
Eur J Pediatr (2009) 168:655
–665
Greek adolescents indicated that the most significant
predictive factors of medium internet use include e-mail
access (adjusted OR: 4.14; 95% CI: 2.39
–7.19), access to
chat rooms (adjusted OR: 2.80; 95% CI: 1.62
–4.84),
internet access via one
’s own home (adjusted OR: 2.74;
95% CI: 1.47
–5.10), and a history of internet use (adjusted
OR: 2.19; 95% CI: 1.63
–2.93). Accessing the internet for
the purposes of retrieving information pertaining to work
and education were negative predictors of medium internet
use, as shown in Table
High internet use (11
–20 h/week)
High internet use is inversely associated with both younger
age and female gender. However, it is also strongly
associated with a history of internet use (Table
). In
addition, as indicated in Table
, high internet users are
most likely to access the internet either via their own home
or via internet cafés. It is significant to note that, in the
gender analysis conducted, only female high internet users
are found to access the internet via internet café portals
significantly more than their non-user counterparts
(Table
). Internet access via the school and/or library
environments is not observed to be negatively associated
with the adoption of high internet use (Table
). Both
male and female high internet users primarily utilize the
internet for the purposes of socializing and purchases
(Tables
and
). However, only male high internet users
were significantly more likely to adopt internet games
playing as compared to their non-user counterparts
(Table
).
With regard to the findings of the YIAS, BIU is
significantly associated only with male high internet use.
No cases of internet addiction are reported within this group
(Table
).
The multivariate regression analysis rendered for the
prediction of the occurrence of high internet use among
Greek adolescents indicated that the most significant
predictive factors of high internet use included internet
access via one
’s own home portal (adjusted OR: 11.26; 95%
CI: 2.60
–48.73), chat room use (adjusted OR: 4.30; 95% CI:
1.78
–10.41), e-mail access (adjusted OR: 3.96; 95% CI:
1.61
–9.76), internet cafés (adjusted OR: 3.09; 95% CI: 1.22–
7.78), and a history of internet use (adjusted OR: 2.19; 95%
CI: 1.30
–3.71). Male gender was also a strong predictor of
high internet use.
Excessive internet use (>20 h/week)
Excessive internet use is significantly negatively associated
with both female gender and a low BMI. It is also strongly
associated with a history of internet use (Table
). In
addition, as indicated in Table
, excessive internet users
are most likely to access the internet either via their own
Table 5 Association between the YIAS and the total number of hours per week of internet use among Greek adolescents, according to
gender (
n=897)
0
–1 h/
week
(
n=277)
1
–3 h/week (n=318)
4
–10 h/week (n=191)
11
–20 h/week (n=55)
>20 h/week (
n=56)
n (%)
n (%)
X
2
p-
value
n (%)
X
2
p-value n (%)
X
2
p-value n (%)
X
2
p-value
Normal internet use
Overall 251 (90.6)
280
(88.0)
–
–
140
(73.3)
–
–
36
(65.4)
–
–
22
(39.3)
–
–
Boys
82 (83.7)
115
(87.1)
–
–
76 (71.0)
–
–
23
(62.2)
–
–
17
(35.4)
–
–
Girls
167 (94.3)
164
(89.6)
–
–
64 (76.2)
–
–
13
(72.2)
–
–
5 (62.5)
–
–
Borderline internet use
Overall 8 (2.9)
23 (7.2)
5.4303
0.0198 40 (20.9) 39.9212 <0.0001 18
(32.7)
53.6632
<0.0001 26
(46.4)
107.2762
<0.0001
Boys
7 (9.2)
10 (7.6)
0.0013 0.9713 24 (22.4)
8.9405
0.0028
14
(37.8)
16.9046
<0.0001 23
(47.9)
38.0940
<0.0001
Girls
1 (0.6)
12 (6.6)
9.1538
0.0025 16 (19.0) 31.9600 <0.0001 4 (22.2) 30.8783 <0.0001 3 (37.5) 46.8261 <0.0001
Addictive internet use
Overall 0 (0.0)
0 (0.0)
–
–
4 (2.1)
–
–
0 (0.0)
–
–
5 (8.9)
–
–
Boys
0 (0.0)
0 (0.0)
–
–
3 (2.8)
3.1730
0.0749
0 (0.0)
–
–
5 (10.4)
19.5776
<0.0001
Girls
0 (0.0)
0 (0.0)
–
–
1 (1.2)
2.5804
0.1082
0 (0.0)
–
–
0 (0.0)
–
–
Eur J Pediatr (2009) 168:655
–665
661
home (OR: 9.41; 95% CI: 3.90
–32.70) or via internet cafés
(OR: 2.65; 95% CI: 1.48
–4.77).
Male excessive internet users are found to predominantly
utilize the internet for the purposes of games (95.8%), while
female users of the same category predominantly utilize
e-mail (87.5%). Both genders are found to be significantly
more likely to utilize the internet for the purposes of sexual
education and purchases, as compared to their non-user
counterparts. However, of this internet use category, boys
are found to be significantly more likely to utilize the
internet for the purposes of chat rooms and games (Table
),
while girls are more likely to utilize the internet for the
purposes of services, as compared to the controls (Table
With regard to the findings of the YIAS, a significant
association is observed between excessive internet use and
BIU for both genders. Moreover, 55.5% (
n=5) of AIU was
observed within this group. It is of utmost significance to
note that 10.4% of male excessive internet users are observed
to be AIU. The significant association observed between
excessive and AIU indicates that internet misuse among this
study population may be dependent on both the time allotted
and the behavioral responses to internet usage (Table
).
The multivariate regression analysis rendered for the
prediction of the occurrence of excessive internet use
among Greek adolescents indicated that the most significant
predictive factors of excessive internet use included access
to internet games (adjusted OR: 8.26; 95% CI: 2.16
–31.49),
internet access via one
’s home portal (adjusted OR: 6.96;
95% CI: 1.72
–28.27), e-mail use (adjusted OR: 5.52; 95%
CI: 2.01
–15.21), chat room use (adjusted OR: 3.37; 95%
CI: 1.24
–9.12), and a history of internet use (adjusted OR:
3.63; 95% CI: 1.84
–7.15). Female gender is a negative
predictor of excessive internet use, as shown in Table
Discussion
With respect to the demographic profile of adolescent
internet users, it is important to note that the study findings
indicated that demographic variables (such as age, BMI,
and current grade point average) were not significantly
associated with any of the predefined categories of the
average total number of hours per week of internet use.
However, it is important to note that the female gender was
Table 6 Multivariate analysis
for the association between
predictors of the total number
of hours per week of internet
use among Greek adolescents
(
n=897)
Maximum likelihood estimates
Wald estimates
Parameter
estimate (
β)
p-value
Adjusted
odds ratio
95% confidence
interval
1
–3 h/week (n=524)
0.7438
0.0007
2.10
1.37–3.23
Chat room
0.6489
0.0028
1.91
1.25–2.93
Own house
0.6069
0.0038
1.84
1.22–2.77
History of use
0.4238
<0.0001
1.53
1.23–1.89
School
−0.5296
0.0276
0.59
0.37–0.94
4
–10 h/week (n=381)
1.4216
<0.0001
4.14
2.39–7.19
Chat room
1.0284
0.0002
2.80
1.62–4.84
Own house
1.0081
0.0015
2.74
1.47–5.10
History of internet use
0.7828
<0.0001
2.19
1.63–2.93
Work and education
−0.6945
0.0228
0.50
0.28–0.91
Gender
−0.7748
0.0051
0.46
0.27–0.79
11
–20 h/week (n=262)
Own house
2.4214
0.0012
11.26
2.60–48.73
Chat room
1.4594
0.0012
4.30
1.78–10.41
1.3772
0.0027
3.96
1.61–9.76
Internet café
1.1267
0.0170
3.09
1.22–7.78
History of internet use
0.7852
0.0034
2.19
1.30–3.71
Gender
−1.0876
0.0174
0.34
0.14–0.83
>20 h/week (
n=264)
Games
2.1111
0.0020
8.26
2.16–31.49
Own house
1.9409
0.0066
6.96
1.72–28.27
1.7089
0.0009
5.52
2.01–15.21
History of internet use
1.2880
0.0002
3.63
1.84–7.15
Chat room use
1.2144
0.0169
3.37
1.24–9.12
Gender
−1.8725
0.0008
0.15
0.05–0.46
662
Eur J Pediatr (2009) 168:655
–665
negatively associated with medium, high, and excessive
internet use. Similar gender differences in the frequency
and nature of computer and internet use are established in
the current scientific literature [
With respect to the location of internet access, the study
findings indicate that it is a significant predictor of the
average total number of hours per week of internet use
across all categories. Across all of the above categories,
internet users are significantly more likely to utilize
primarily their own home and secondarily an internet café,
in order to access the internet, as compared to the controls.
It is of importance to note that both locations allow for
adolescents to freely surf the internet, most likely
without the pressures of parental control or authority.
The odds for such internet access increase logarithmi-
cally from the lowest to highest internet use categories,
exhibiting peak values among high internet users. The
study findings are the first to identify one
’s home as a
significant predictor of internet use and misuse, whilst
with regard to the role of internet café access, relevant
data have already been published for the Taiwanese
youth [
]. Thus, it appears that these locations serve as
the gateway for initiating and continuing internet use
among adolescents.
It is of particular interest that the study findings indicate
that internet use within the school environment appears to
have a negative effect upon the adoption of all categories of
internet use. This may be due either to the limited scope of
unauthorized internet sites that may be readily accessed
within the Greek school environment or to the limited
access that such adolescents have in alternative environ-
ments (e.g., home environments or internet café).
With regard to the scope of interest of internet sites
accessed, sites related to social communication (i.e., e-mail
and chat rooms) serve as consistent predictors of the
average number of total hours per week of internet use
across all respective case groups. Moreover, across all
internet use categories, while male adolescents were found
to predominantly utilize the internet for games and
socialization, female adolescents were found to predomi-
nantly utilize the internet only for e-mail. However,
excessive internet use is primarily predicted by access to
internet sites pertaining to entertainment (i.e., games) and
only secondarily predicted by internet sites related to social
interaction. Moreover, while not retained in the final
regression models, it is of importance to note that access
to sites pertaining to the purchases of goods and services, as
well as sexual education/behavior, is significantly asso-
ciated and increases logarithmically with all internet use
categories. Access to newspapers and periodicals is not
significantly associated with the total number of hours per
week of internet use in any of the respective case groups.
Hence, it is upheld that the scope of internet access among
adolescents is more likely to be focused upon social
interactions and entertainment.
The significance of the specific scope of interest of
entertainment (i.e., games) internet sites accessed, particu-
larly among excessive internet users who have the highest
possibility for establishing a pathological use of the
internet, is signified by the finding that internet games,
and in particular role-playing games [
], may serve as an
independent factor for adopting dependent internet behavior
[
]. The mechanism for the establishment of such
dependent behavior may be either through excessive
internet use or through modes of behavior similar to those
of pathological gambling without monetary awards [
]. This association is predominantly observed among
male adolescents [
,
], as also indicated in the present
study findings.
In addition, with regard to excessive internet users
’
access to internet sites related to sexual education/behavior,
it has already been established that approximately half of all
adolescent internet users access health information internet
sites [
], and, in particular, sites related to sexual education
and/or health [
]. It is of particular interest to note that the
present study findings relating to such information being
rarely accessed through internet use within the school
environment corroborates with those of the scientific
literature [
]. Thus, it may be concluded that access to
sexual education/behavior internet sites is made readily
available to adolescents through their enhanced internet
access via portals within their own homes.
Finally, BIU is observed to increase geometrically with
increasing total number of hours per week of internet use
among both genders. However, it is observed to be
statistically associated concurrently with both genders only
among the medium and excessive internet use categories.
AIU, according to the YIAS, is observed in nine (1.00%)
adolescents of the study population. AIU is observed to
occur predominantly among medium (
n=4) and excessive
internet users (
n=5). The absence of AIU among high
internet use may be justified by the fact that such
pathological use is defined predominantly by an abnormal
psychosocial behavior, dependent association with the
internet, and compromised functionality, and only second-
arily by the average weekly number of hours devoted to
internet use [
]. However, the elevated prevalence of
internet addiction among male excessive internet users
observed in this study, as well as the significant association
established between excessive and AIU, may indicate that
internet addiction in this particular sub-population may be
dependent on both the time allotted and behavioral
responses to internet usage.
The prevalence of internet addiction among Greek
adolescents participating in this study is markedly lower
than those reported in other European (e.g.,
Νοrway:
Eur J Pediatr (2009) 168:655
–665
663
1.98%, Great Britain: 18.3%, Romania: 1.4%, Italy: 5.4%)
[
,
,
,
] and Asian countries (e.g., India: 18%,
Korea: 18.4%, China: 2.4%) [
,
]. However, one is
unable to decipher whether the observed cross-cultural
variance in the prevalence of internet addiction may be
attributed to the varying penetration rates of computer/
internet access cross-culturally or to a measurement bias
inherent in the application of the modified YIAS and other
assessment tools in the aforementioned scientific literature.
The location of internet access and scope of internet sites
accessed, including those of social interaction and enter-
tainment, is similar to those reported in the scientific
literature [
].
Furthermore, as a significant proportion of study
participants are identified as having BIU according to the
YIAS (
n=115; 12.8%), it is deemed necessary that public
health interventions should be designed and implemented in
order to prevent the occurrence of problematic internet use
among such adolescents. According to the present study
findings, since the predictors of internet use vary signifi-
cantly based on the average total weekly number of hours,
this could serve as a basis for modeling appropriate public
health intervention programs.
The strengths of the present study include, primarily, that
it serves as the first such study conducted in order to assess
the predictive factors of internet use among Greek
adolescents. Second, due to the random sampling applied
in order to select the study population, the potential for
selection bias has been minimized.
The limitations of the study include the following. First,
due to the limitations of the cross-sectional study design
applied, the study fails to assess the psychosocial profile of
the study participants prior to and/or following the onset of
PIU. Second, due to the reporting bias which may be
inherent when assessing socially unacceptable conduct
through the application of a self-completed questionnaire,
the study may underestimate the true prevalence of PIU.
Third, due to the limited number of study participants, an
analogous future study at the Greek national level must be
implemented in order to validate the extrapolation of the
study results at the national level.
Acknowledgments
The statistical analyses and respective results
presented in this publication were completed by Elena Critselis BSc,
MPH.
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