Loneliness, social contacts and Internet addiction: A cross-lagged panel study

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DOI: 10.1016/j.chb.2013.08.007
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Abstract
This study aims to examine the causal priority in the observed empirical relationships between Internet addiction and other psychological problems. A cross-lagged panel survey of 361 college students in Hong Kong was conducted. Results show that excessive and unhealthy Internet use would increase feelings of loneliness over time. Although depression had a moderate and positive bivariate relationship with Internet addiction at each time point, such a relationship was not significant in the cross-lagged analyses. This study also found that online social contacts with friends and family were not an effective alternative for offline social interactions in reducing feelings of loneliness. Furthermore, while an increase in face-to-face contacts could help to reduce symptoms of Internet addiction, this effect may be neutralized by the increase in online social contacts as a result of excessive Internet use. Taken as a whole, findings from the study show a worrisome vicious cycle between loneliness and Internet addiction.
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Loneliness, social contacts and Internet addiction: A cross-lagged
panel study
Mike Z. Yao
a,
, Zhi-jin Zhong
b
a
Department of Media and Communication, City University of Hong Kong, Run Run Shaw Creative Media Centre, Kowloon, Hong Kong
b
School of Communication and Design, Sun Yat Sen University of China, China
article info
Article history:
Available online 10 September 2013
Keywords:
Internet addiction
Depression
Loneliness
Social isolation
Cross-lagged panel design
abstract
This study aims to examine the causal priority in the observed empirical relationships between Internet
addiction and other psychological problems. A cross-lagged panel survey of 361 college students in Hong
Kong was conducted. Results show that excessive and unhealthy Internet use would increase feelings of
loneliness over time. Although depression had a moderate and positive bivariate relationship with Inter-
net addiction at each time point, such a relationship was not significant in the cross-lagged analyses. This
study also found that online social contacts with friends and family were not an effective alternative for
offline social interactions in reducing feelings of loneliness. Furthermore, while an increase in face-to-face
contacts could help to reduce symptoms of Internet addiction, this effect may be neutralized by the
increase in online social contacts as a result of excessive Internet use. Taken as a whole, findings from
the study show a worrisome vicious cycle between loneliness and Internet addiction.
Ó2013 Elsevier Ltd. All rights reserved.
1. Introduction
Researchers around the world from the domains of communica-
tion, psychology, and psychiatry have paid considerable attention
in recent years to the rising issue of problematic use of the Internet
(PIU), or Internet addiction (IAD) (Griffiths, Miller, Gillespie, &
Sparrow, 1999; Tao et al., 2010; Young, 2004; Zhang, Amos, &
McDowell, 2008). While the ontological and epidemiological issues
surrounding Internet addiction being a clinical pathology are still
the subject of many intellectual debates (Czincz & Hechanova,
2009; Frances & Widiger, 2012; Pies, 2009; Widyanto & Griffiths,
2006), social and behavioral scientists generally believe that such
a phenomenon indeed exists (Chou, Condron, & Belland, 2005)
and that excessive and compulsive Internet use would negatively
impact a person’s physical, psychological, and social well-being
(Davis, 2001; Young, 1998).
Many studies have examined Internet addiction, its social and
psychological correlates, and possible treatments (Beard, 2005).
While this body of research has identified a number of related fac-
tors to the problem, such as depression, loneliness, and social iso-
lation (Ceyhan & Ceyhan, 2008; Chou et al., 2005; Davis, 2001;
Young & Roger, 1998), the causal direction of the relationships be-
tween these psychosocial problems and Internet addiction have
not yet been clearly established (Chou et al., 2005). To fill this void,
this study aims to determine the causal priority in the empirical
relationship between Internet addiction and Internet users’
subjective feelings of depression and loneliness. The effects of
online and offline social interactions are also examined.
2. Conceptualizing Internet addiction
Various labels (e.g., compulsive Internet use, pathological Inter-
net use, Internet addiction disorder, Internet usage disorder, and
problematic Internet use, etc.) have been adopted to describe the
phenomenon of people engaging in excessive and unhealthy use
of the Internet. (Widyanto & Griffiths, 2006). It has been widely
recognized as a significant mental health issue worldwide. In
2012, the American Psychiatric Association recommended includ-
ing ‘‘Internet Use Disorder’’ for further study in Section III of the
DSM-5. In Korea, Internet addiction has been deemed a national
health concern estimated to affect up to 30% of Internet users un-
der 18 (Fackler, 2007; Ha et al., 2007). In China, more than 10% of
adolescent Internet users were identified as Internet addicts (Block,
2008; Wu & Zhu, 2004), and the Chinese government went so far as
sponsoring various treatment clinics to deal with this new ‘‘addic-
tion’’. In Taiwan, nearly 6% of college students were believed to be
affected by problematic Internet use (Chou & Hsiao, 2000).
In general, Internet addiction has been conceptualized as a
behavioral control problem. It refers to Internet users’ inability to
control their use of the medium, which in turn might cause one’s
marked distress and functional impairment in daily life (Shek,
Sun, & Yu, 2013). This condition often shares similar epidemiolog-
ical properties and consequences as some classified addictions
0747-5632/$ - see front matter Ó2013 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.chb.2013.08.007
Corresponding author. Tel.: +852 3442 8611.
E-mail address: mike.yao@cityu.edu.hk (M.Z. Yao).
Computers in Human Behavior 30 (2014) 164–170
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such as substance dependency (Brenner, 1997) and impulse con-
trol disorders (Young, 1998, 1999, 2004, 2009). To this extent, a
number of diagnostic criteria have been proposed and tested
(Beard, 2005; Brenner, 1997; Byun et al., 2009; Chou et al., 2005;
Demetrovics, Szeredi, & Rozsa, 2008; Ha et al., 2007; Young,
1999). However, methods of clinically assessing Internet addiction
disorder remain limited and inconsistent (Chou et al., 2005; Del-
l’Osso, Altamura, Allen, Marazziti, & Hollander, 2006). A number
of epidemiological and theoretical issues related to the proposed
disorder have not been fully resolved through empirical research;
for example, internet addiction may be a symptom resulted from
other existing psychiatric disorders, such as depression, social anx-
iety, and generalized obsessive and compulsive disorder (Beard,
2005; Ha et al., 2007; Pies, 2009).
Adding to the complexity in conceptualizing Internet addiction
as a psychiatric condition, the very notion of ‘‘Internet use’’ has also
changed dramatically since researchers began to investigate this
problem almost 20 years ago. Early forms of the Internet were sim-
ply channels of electronic communication. Users mainly browsed
information displayed on static webpages and/or sent text-based
messages to each other. As computing and network technologies ad-
vance, however, the Internet is no longer just a communication
channel. People nowadays conduct more and more of their routine
social and professional activities online. The Internet is now quite
literally a common thread that weaves the fabric of our lives. Fur-
thermore, mobile devices such as smartphones and wearable com-
puters allow people to stay connected wherever and whenever. A
growing number of Internet users spend nearly as much, if not more
time, online as they do offline. Thus, it is problematic to use the
amount of time spent online or a general dependency on the Internet
technology as primary indicators of problematic use. It is also diffi-
cult to determine to what aspects of the Internet people are
‘‘addicted’’.
Despite a lack of consensus on the conceptualization and
assessment of Internet addiction and the ambiguity in defining
‘‘Internet use’’, most social scientists agree that Internet addiction,
as a general social phenomenon, indeed exists (Chou et al., 2005).
Those who are affected by this problem often spend an excessive
amount of time on the Internet, which adversely affects their
offline lives; they may develop a preoccupation with online activ-
ities, feel the need to escape into cyberspace, and express an in-
creased amount of irritability when trying to cut back their
Internet use (Dell’Osso et al., 2006). These individuals may also
experience a number of functional impairments as a result of
using the Internet such as marital or family strife, job loss or de-
creased job productivity, and legal difficulties or school failure
(Chou & Hsiao, 2000).
In the present study, we are not interested in engaging the de-
bate surrounding Internet addiction in a clinical sense, but rather
as a widely observed social phenomenon. As such, we will use
the term Internet addiction throughout this paper to describe a
general psychological condition in which an individual’s mental
and emotional states are adversely affected by the overuse of the
medium (Beard, 2005).
3. Internet addiction and psychosocial problems
Numerous studies from around the world found Internet addic-
tion to be positively associated with other psychosocial problems,
such as feelings of depression and loneliness (Beard, 2005; Chou
et al., 2005; Ha et al., 2007; Tokunaga & Rains, 2010). Morahan-
Martin and Schumacher (2000) found that 8% of their sample of
undergraduate students in the United States were engaging in
pathological Internet use, and were experiencing a greater degree
of loneliness than their non-addicted counterparts. In a cross-
sectional study, Kim, LaRose, and Peng (2009) identified loneliness
to be the cause, as well as the effect, of problematic Internet use
among American college students. Yen, Ko, Yen, Chang, and Cheng
(2009) recently surveyed 8941 adolescents in Taiwan; they found
depression and a lack of family contact to be discriminating factors
for Internet addiction. Similar patterns were also found in China
(Huang & Deng, 2009; Liu, Xu, & Hu, 2009), South Korea (Byun
et al., 2009; Park, 2009), Norway (Bakken, Wenzel, Götestam,
Johansson, & Øren, 2009), and Iran (Ghassemzadeh, Shahraray, &
Moradi, 2008). Most recently, Tokunaga and Rains (2010) con-
ducted a meta-analysis of 94 studies from 22 different countries
and found moderate and consistent links between loneliness,
depression, and problematic Internet use.
Davis (2001) posited that existing psychopathological disorders,
such as depression, loneliness, social anxiety, and substance
dependence were necessary elements in the etiology of pathologi-
cal Internet use. Specifically, people with psychosocial dispositions
such as depression and loneliness would be prone to hold mal-
adaptive cognitions (e.g., they would only feel good on the Internet
and/or the offline world is awful). Therefore, those who feel de-
pressed and lonely would be especially vulnerable to Internet
addiction. Extending from Davis’s cognitive–behavioral model of
problematic Internet use, Caplan (2003) further argued that indi-
viduals with psychosocial problems (e.g., depression and loneli-
ness) were more likely to perceive themselves as unskilled in
social competence. They would prefer computer-mediated interac-
tions rather than face-to-face communication because the ano-
nymity and a lack of non-verbal cues in computer-mediated
communication would make online social interaction less threat-
ening. As a result, these individuals would be inclined to perceive
themselves as more sophisticated or successful in online social
interactions. This preference would in turn lead to excessive and
compulsive use of the Internet. Based on the theoretical reasoning
outlined above, we would predict that:
H1. Feelings of depression will lead to higher levels of Internet
addiction.
H2. Feelings of loneliness will lead to higher levels of Internet
addiction.
More interestingly, if depression and loneliness drive people to
use the Internet more often, will such an increase of usage provide
a relief for these negative psychological feelings? From a social
network and social capital perspective, Wellman et al. (1996) ar-
gued that the Internet could strengthen previously formed social
relations because it would add effective means of communication
and social contact. Supporting this view, Howard, Raine, and Jones
(2002) found that, after controlling for basic socio-demographics,
those who had gone online had a 24% greater likelihood of saying
that they knew people who could be helpers in times of need than
those who had never gone online. A variety of early studies (Con-
stant, Sproull, & Kiesler, 1996; Rice, 1999; Sproull & Kiesler, 1991)
have also found that computer-mediated communication ex-
tended possibilities for social connection by crossing time, geogra-
phy and space, allowing people with different backgrounds to
share interests and to come together in a virtual world. From this
perspective, it seems that Internet use may foster virtual, but still
real and meaningful, social interactions that would in turn reduce
feelings of loneliness. This suggests that while feelings of depres-
sion and loneliness may lead to Internet addiction in the short
run, as predicted in H1 and H2, the reduction of these feelings
associated with greater virtual social connections may therefore
also reduce Internet addiction over time. Based on this line of
reasoning, we propose the following hypothesis and research
question:
M.Z. Yao, Z.-j. Zhong / Computers in Human Behavior 30 (2014) 164–170 165
Author's personal copy
H3. Online social contacts will help reduce the effects of loneliness
and depression on Internet addiction.
Despite the optimistic view that online social contacts might be
socially beneficial, some evidence suggest that if Internet use is
excessive, it may lead to increased social isolation from a decrease
of face-to-face social interactions. Young and Roger (1998) sug-
gested that increased levels of social isolation and depression
may result from excessive Internet use, rather than being the cause
of Internet addiction. Young (1998) found that excessive use of the
Internet led to family problems because some users indulged in cy-
ber-affairs or extramarital relationships that would destabilize
real-life social relationships. Kim et al. (2009), through a path anal-
ysis of a cross-sectional survey, showed that individuals who were
lonely or lacked good social skills could develop strong compulsive
Internet use behaviors. Such compulsive Internet use may further
prevent users from forming healthy social interactions and thus
lead to more loneliness. Furthermore, from the perspective of dis-
placement theory (Kraut et al., 1998; Nie, Hillygus, & Erbring,
2002), one could also argue that the Internet may undermine peo-
ple’s social development by taking away time that would other-
wise be spent with family and friends. The following hypothesis
and research question can thus be derived:
H4. Internet addiction will lead to a reduction in the frequency of
face-to-face social contacts, and therefore lead to an increase in
feelings of depression and loneliness.
4. Method
A two-wave panel survey was conducted. Students in two major
public universities in Hong Kong were invited to fill out two online
questionnaires four months apart. Each participant received a
HK$50 cash coupon from a local supermarket (approximately
US$6.5) for completing the first survey and another HK$50 upon
completion of the follow-up questionnaire. The second-wave ques-
tionnaire was nearly identical to the first one.
5. Sample
An invitation email for the survey was distributed through the
student unions of the two universities. A total of 636 participants
completed the first wave of questionnaires within a period of
2 weeks. A follow-up email was sent to these 636 participants after
four months, inviting them to participate in the second-wave sur-
vey. A reminder was sent out one week later. In total, 361 of the
636 participants completed both questionnaires. Among the par-
ticipants, 51.7% of them were males, 37.6% of them were females,
while about 10% of them did not report their sex. The mean age
of the participants was 21.63 years (SD = 2.60), ranging from 18
to 37. Overall, the sample had a high level of Internet usage. 89%
of participants reported daily Internet use, and 62% of them said
that they would spend three or more hours online every day.
6. Questionnaire development and measurement
Over 90% of the population in Hong Kong is ethnically Chinese.
However, being a British colony for nearly a century, the majority
of educated individuals in Hong Kong are bilingual. Both Chinese
and English are official languages, and all public documents pub-
lished by the Government are in both languages. English is also
the medium of instruction at the two universities from which
our sample was drawn. Given this situation, a bilingual question-
naire was used, with each item in the survey presented in both
English and Chinese. Pilot tests, as well as an independent back-
translation, were conducted to ensure accuracy of the translations.
6.1. Level of Internet addiction
While a number of diagnostic assessments are available for
measuring Internet addiction or problematic Internet use (cf.
Beard, 2005; Shapira et al., 2003), this study adapted Young
(1998) 20-item Internet Addiction Test (IAT) because of its wide
adoption by academic researchers and medical professionals, par-
ticularly in Asia. Examples of the questions include: ‘‘how often
do you find that you stay online longer than you intended’’;
‘‘how often do you neglect household chores to spend more time
online’’; and ‘‘how often do you prefer the excitement of the inter-
net to intimacy with your partner’’. All items were measured on a
7-point scale. An average score serves as the final indicator.
6.2. Feelings of depression
A shortened version of Hamilton (1960) depression rating scale
(HDRS) was used in the present study to gauge participants’ self-
reported feelings of depression. This scale included 12 items. Par-
ticipants were asked the report the extent to which they experi-
ence symptoms of depression such as feelings of guilt, depressive
mood and insomnia. Created for the purpose of clinically assessing
depression, the HDRS is a checklist. However, in this study we are
primarily interested in evaluating a persons’ subjective feelings of
depression rather than clinically screening for depression, the
items in this scale were measured on a 7-point Likert scale. The
average score of all items was used as an indicator for depression.
6.3. Loneliness
Participants’ subjective feelings of loneliness were assessed by
Russell (1996) 20-item UCLA loneliness scale, measured on a 7-
point scale. The average scores were used in all subsequent analy-
ses. Some examples of the items from the scale include: ‘‘I am un-
happy doing so many things alone’’; ‘‘I have nobody to talk to’’; and
‘‘I lack companionship’’.
6.4. Social contact
An individual’s frequency of being in contact with family and
friends, both online and offline, were measured. In each wave of
the survey, participants were asked, using a 7-point scale, how of-
ten they had contacted family and friends face-to-face, via instant
messengers, via email, and via social networking sites in the previ-
ous month. A summed score of individuals’ face-to-face contacts
with family and friends was used to gauge offline social interac-
tions, and the summed score of contacts via other means was used
to measure online social contact.
Table 1 presents the descriptive statistics of key variables in
both waves, while all bivariate correlations are presented in
Table 2.
Table 1
Descriptive statistics of key measures.
Variables 1st Wave 2nd Wave
Mean (SD)
a
Mean (SD)
a
Depression 3.11 (1.01) .88 3.09 (.94) .87
Loneliness 3.98 (.63) .71 3.84 (.63) .77
e-Contact (sum of 6 items) 22.80 (6.64) n/a 22.68 (6.04) n/a
F2F contact (sum 2 items) 11.64 (1.94) n/a 11.99 (2.02) n/a
Internet addiction 3.44 (.93) .91 3.37 (.98) .92
166 M.Z. Yao, Z.-j. Zhong / Computers in Human Behavior 30 (2014) 164–170
Author's personal copy
7. Data analysis
The present study adopted a classic two-wave cross-lagged pa-
nel design (Campbell, 1963; Kenny, 1973). A path analysis ap-
proach to analyzing cross-lagged panel data as suggested by
Kessler and Greenberg (1981) was employed to test our hypothe-
ses. Specifically, we were interested in evaluating the relative
strength of the cross-lagged relationships between the set of vari-
ables Xand Ymeasured in time 1 and time 2 in a cross-lagged pa-
nel structural model (Fig. 1). To ensure consistency in our
interpretations of the results we used the standardized z-scores
of the key variables in all analyses. All path models were tested
in AMOS 19.
8. Results
8.1. Depression and symptoms of Internet addiction
The first hypothesis (H1) predicted that individuals’ subjective
feelings of depression would lead to symptoms of Internet addic-
tion. As can be seen from Table 1, the bivariate correlations be-
tween depression and Internet addiction at both time 1 and time
2, and all cross-lagged correlations between the two variables were
significant and positive, suggesting that there was indeed a posi-
tive relationship between feelings of depression and symptoms
of Internet addiction. However, a test of the cross-lagged structural
model revealed that once the stability effect (i.e. the influence of a
measure at time 1 on the same measure at time 2) is controlled for,
the influence of depression at time 1 on Internet addiction at time
2 became non-significant, so did the influence of Internet addiction
at time 1 on depression at time 2. This finding indicates that the
relationship between depression and Internet addiction might
have been caused by other factors (see Fig. 2). As such, we did
not find support for H1, and depression was excluded from the
subsequent hypotheses testing.
8.2. Loneliness and symptoms of Internet addition
Our second hypothesis (H2) concerns the relationship between
a person’s subjective feelings of loneliness and Internet addiction.
We expected that feelings of loneliness would not only be posi-
tively associated with, but also a causal factor leading to symptoms
of Internet addiction. Simple bivariate correlational analyses (see
Table 2) showed moderate and positive relationships between
loneliness and Internet addiction at each time point. However,
after controlling the stability effects (i.e., the influence of loneliness
at time 1 on loneliness at time 2 and the influence of IAD at time 1
on IAD at time 2), the cross-lagged effect of loneliness at time 1 on
IAD at time 2 faded, but the significant effect from Internet addic-
tion at time 1 on loneliness at time 2 remained (see Fig. 3). This
suggests that Internet addiction may be a cause of loneliness,
which is the opposite of what we have predicted. H2 is not
supported.
8.3. Social contacts and Internet addiction
Hypothesis 3 (H3) predicted that individuals would seek com-
fort from online social contacts when they feel lonely and de-
pressed, which will in turn reduce symptoms of Internet
addiction. We found that the frequency of individuals’ online social
contacts with family and friends in the months prior to each wave
of surveys had a positive correlation with symptoms of Internet
addiction at both time points. This is opposite to what we had ex-
pected. H3 was not supported.
Table 2
Bivariate correlations between key measures.
IAD
(T1)
IAD
(T2)
Depression
(T1)
Depression
(T2)
Loneliness
(T1)
Loneliness
(T2)
e-Contact
(T1)
e-Contact
(T2)
F2F-Contact
(T1)
F2F-Contact
(T2)
IAD (T1 1
IAD (T2) .661
**
1
Depression
(T1)
.498
**
.344
**
1
Depression
(T2)
.352
**
.406
**
.571
**
1
Loneliness
(T1)
.467
**
.280
**
.639
**
.437
**
1
Loneliness
(T2)
.343
**
.351
**
.416
**
.622
**
.449
**
1
e-Contact (T1) .133
**
.154
**
.019 .044 .055 .067 1
e-Contact (T2) .043 .205
**
.008 .018 .095 -.060 .468
**
1
F2F-contact
(T1)
.056 .008 .141
**
.124
*
.115
*
.083 .293
*
.197
**
1
F2F-contact
(T2)
.025 .054 .178
**
.168
**
.150
*
.121 .156 .368
**
.399
**
1
*
Correlation is significant at the 0.05 level (2-tailed).
**
Correlation is significant at the 0.01 level (2-tailed).
Fig. 1. A two-wave two-variable cross-lagged panel model.
Fig. 2. Standardized regression coefficients in a cross-lagged panel structural model
testing the influence of depression on Internet addiction.

Coefficient is significant
at the 0.001 level. n.s. Non-significant.
M.Z. Yao, Z.-j. Zhong / Computers in Human Behavior 30 (2014) 164–170 167
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  • Problem: An important environmental factor affecting adolescents today is undoubtedly technological tools. This descriptive and cross-sectional study was conducted to evaluate the relationship of adolescents' Internet and mobile phone usage, cyberbullying behaviors, and their self-reported mental health. Methods: The sample of the study consisted of a total of 426 students including 215 male students and 211 female students. A questionnaire was prepared by the researcher to determine the sociodemographic and personal characteristics and virtual behavioral characteristics of individuals. The Brief Symptom Inventory was used to determine the participants' mental status. Findings: It was found that adolescents' daily Internet usage duration, Internet usage purpose, the place where they use Internet, cyberbullying, and exposure to cyberbullying were related to the adolescents' self-reported mental health (p < .05). Conclusion: Several aspects of the virtual behaviors of the adolescents were associated with their sense of mental health issues. In this context, the school health nurse should raise awareness among adolescents about the use of technology and how it might impact their mental wellbeing.
  • Article
    In today’s contemporary living, the proliferation of internet has become a major component to complete each individual, especially the Z generation. They had been exposed to technological advancements especially in the virtual world since birth. Now, this generation has entered the world of higher education. Educators now face challenges in educating them, primarily because of their attitude issues. This Gen Z has been labeled as spoilt, rebellious and selfish. Therefore, the purpose of this study is to identify that major problem in their attitude and to investigate whether cyber addiction plays a major role in this problem hence affecting their studies. This study will involve quantitative method by using semi-structured interview and Likertscale questionnaire. The interview involving 65 educators and will be recorded and analyzed, while as the questionnaire will be handed out to 300 undergraduates (born in year 1997 above) for later analysis through SPSS and AMOS version 22. Results achieved will prove as solid evidence that when these young adults are left unmanaged in the cyber world it may prove to create negative impacts in the future. Parents in particular, must focus concern and awareness in them so as our future leaders will not continue to be distracted and engrossed to the point of losing their faith. This study is also parallel to one of the tier in the 11th RMK emphasizing that the 21st century graduates are to be apt leaders, ethically and morally. Keywords: Attitude, Learning, Gen Z, Cyber Addiction
  • Thesis
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    The aim of the present study was to examine the mediating role of self-compassion in the relationship between ostracism and internet addiction. Besides, the roles of daily and weekly internet usage and the demographic variables like age, gender, parent education level in predicting internet usage habits were also explored. The sample was composed of 457 university students studying in Necmettin Erbakan University Ahmet Keleşoğlu Faculty of Education. Data was gathered by using a personal information form and Internet Addiction Scale, Self Compassion Scale and Ostracism Experience Scale for Adolescents. Mediation analyses were carried out to examine the mediating role of self-compassion. The results showed that self-compassion mediate the relationships between “ignored” dimension of ostracism and all subdimensions of internet addiction; and the relationship between “excluded” dimension of ostracism and tolerance and interpersonal and health problems dimensions. The role of daily and weekly internet usage and demographic factors in predicting internet using habits were examined using separate step-wise multiple regression analysis for each internet addiction dimension. Weekly internet usage and gender emerged as variables that predict compulsive use, withdraw, tolerance and time management dimensions. Moreover, daily internet usage predicted interpersonal and health problems subdimensions. Gender was found to be associated with compulsive use, withdraw, tolerance, and time management dimensions. Age and parental education level did not show any significant relation to internet addiction. Key Words: Internet usage, Internet addiction, Ostracism, Self compassion, Ignored, Excluded