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Technological Addictions and Social Connectedness: Predictor Effect of Internet Addiction, Social Media Addiction, Digital Game Addiction and Smartphone Addiction on Social Connectedness

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ABSTRACT Technological addictions and social connectedness: predictor effect of internet addiction, social media addiction, digital game addiction and smartphone addiction on social connectedness Objective: This study examined the predictor effects of four technological addictions, including Internet addiction, social media addiction, digital game addiction and smartphone addiction on social connectedness. Method: The study was conducted on 201 adolescents (101 girls, 100 boys) who have been using Internet, playing digital games, and using social media for at least one year, and have at least one social media account and a smartphone. The Young’s Internet Addiction Test-Short Form, Social Media Disorder Scale, Digital Game Addiction Scale, Smartphone Addiction Scale-Short Version, Social Connectedness Scale, and Personal Information Form were used as data collection tools. Parametric statistical methods were used to analyze the data, taking into consideration the single and multivariable normality, linearity, and multicolinearity. Results: The analysis showed that Internet addiction, social media addiction, digital game addiction and smartphone addiction significantly predicted 25% of social connectedness. In addition, it has been determined that the strongest effect on social connectedness is from Internet addiction followed by social media addiction, digital game addiction, and smartphone addiction respectively. Conclusion: Four technological addictions including Internet addiction, social media addiction, digital game addiction and smartphone addiction significantly affect social connectedness. Keywords: Digital game addiction, internet addiction, smartphone addiction, social connectedness, social media addiction
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202 Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
Technological Addictions
and Social Connectedness:
Predictor Effect of Internet
Addiction, Social Media
Addiction, Digital Game
Addiction and Smartphone
Addiction on Social
Connectedness
Mustafa Savci1, Ferda Aysan2
1
Firat University, Faculty of Education, Department
of Guidance and Psychological Counseling, Elazig - Turkey
2
Dokuz Eylul University, Faculty of Education, Department
of Guidance and Psychological Counseling, Izmir - Turkey
Research / Araştırma
ABSTRACT
Technological addictions and social connectedness: predictor effect of internet
addiction, social media addiction, digital game addiction and smartphone
addiction on social connectedness
Objective: This study examined the predictor effects of four technological addictions, including Internet
addiction, social media addiction, digital game addiction and smartphone addiction on social connectedness.
Method: The study was conducted on 201 adolescents (101 girls, 100 boys) who have been using Internet,
playing digital games, and using social media for at least one year, and have at least one social media
account and a smartphone. The Young’s Internet Addiction Test-Short Form, Social Media Disorder Scale,
Digital Game Addiction Scale, Smartphone Addiction Scale-Short Version, Social Connectedness Scale, and
Personal Information Form were used as data collection tools. Parametric statistical methods were used to
analyze the data, taking into consideration the single and multivariable normality, linearity, and multicolinearity.
Results: The analysis showed that Internet addiction, social media addiction, digital game addiction and
smartphone addiction significantly predicted 25% of social connectedness. In addition, it has been
determined that the strongest effect on social connectedness is from Internet addiction followed by social
media addiction, digital game addiction, and smartphone addiction respectively.
Conclusion: Four technological addictions including Internet addiction, social media addiction, digital game
addiction and smartphone addiction significantly affect social connectedness.
Keywords: Digital game addiction, internet addiction, smartphone addiction, social connectedness, social
media addiction
ÖZET
Teknolojik bağımlılıklar ve sosyal bağlılık: İnternet bağımlılığı, sosyal medya bağımlılığı,
dijital oyun bağımlılığı ve akıllı telefon bağımlılığının sosyal bağlılığı yordayıcı etkisi
Amaç: Bu araştırmada internet bağımlılığı, sosyal medya bağımlılığı, dijital oyun bağımlılığı ve akıllı telefon
bağımlılığı olmak üzere, dört teknolojik bağımlılığın sosyal bağlılığı yordayıcı etkisi incelenmiştir.
Yöntem: Araştırma son bir yıldır internet kullanan, dijital oyun oynayan ve sosyal medya kullanan ve en az bir
sosyal medya hesabı ve akıllı telefonu olan 201 (101’i kız, 100’ü erkek) ergen üzerinde gerçekleştirilmiştir.
Araştırma verileri Young İnternet Bağımlılığı Testi Kısa Formu, Akıllı Telefon Bağımlılığı Ölçeği Kısa Formu, Dijital
Oyun Bağımlılığı Ölçeği, Sosyal Medya Bozukluğu Ölçeği, Sosyal Bağlılık Ölçeği ve Kişisel Bilgi Formu ile
toplanmıştır. Araştırma verileri tek ve çok değişkenli normallik, doğrusallık ve çoklu bağlantı problemi dikkate
alınarak, parametrik istatistiki yöntemlerle çözümlenmiştir.
Bulgular: Analiz sonucunda internet bağımlılığı, sosyal medya bağımlılığı, dijital oyun bağımlılığı ve akıllı telefon
bağımlılığının sosyal bağlılığın %25’ini anlamlı düzeyde yordadığı görülmüştür. Ayrıca sosyal bağlılığın
açıklanmasında en güçlü etkinin internet bağımlılığından geldiği ve bunu sırasıyla sosyal medya bağımlılığı,
dijital oyun bağımlılığı ve akıllı telefon bağımlılığının takip ettiği saptanmıştır.
Sonuç: İnternet bağımlılığı, sosyal medya bağımlılığı, dijital oyun bağımlılığı ve akıllı telefon bağımlılığı olmak
üzere, dört teknolojik bağımlılık sosyal bağlılığı önemli ölçüde etkilemektedir.
Anahtar kelimeler: Dijital oyun bağımlılığı, internet bağımlılığı, akıllı telefon bağımlılığı, sosyal bağlılık, sosyal
medya bağımlılığı
Dusunen Adam The Journal of Psychiatry and Neurological Sciences 2017;30:202-216
DOI: 10.5350/DAJPN2017300304
Address reprint requests to / Yazışma adresi:
Dr. Mustafa Savci,
Firat University, Faculty of Education,
Department of Guidance and Psychological
Counseling, Elazig, Turkey
Phone / Telefon: +90-424-237-0000
E-mail address / Elektronik posta adresi:
mustafasavci045@hotmail.com,
msavci@firat.edu.tr
Date of receipt / Geliş tarihi:
December 26, 2016 / 26 Aralık 2016
Date of the first revision letter /
İlk düzeltme öneri tarihi:
January 12, 2017 / 12 Ocak 2017
Date of acceptance / Kabul tarihi:
February 21, 2017 / 21 Şubat 2017
How to cite this article: Savci M, Aysan F.
Technological addictions and social connectedness:
predictor effect of internet addiction, social media
addiction, digital game addiction and smartphone
addiction on social connectedness. Dusunen Adam
The Journal of Psychiatry and Neurological Sciences
2017;30:202-216.
https://doi.org/10.5350/DAJPN2017300304
Savci M, Aysan F
203
Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
INTRODUCTION
Computers, the internet and smartphones have
become an important part of everyday life. Hence,
by 2016, 46% of the world population are users of
internet, 31% active social media, and 51% smartphone
users (1,2). This situation is also similar in Turkey.
According to Turkish Statistical Institute (TUIK) (3)
data, 61% of Turkey’s population use the internet;
and among internet use purposes social media ranks
first. In Turkey 96% of the household have mobile
phones (3). Besides, 53% of Turkey’s population is
actively using social media (1). Finally, digital games
are commonly played among adolescents (4). These
data and research results show that internet, social
media, smart phones and digital games are used
extensively. The intensive use of technology is
together with problematic or pathological
consumption. In this context, the question “can
technology be an addiction?” is one of the topics
frequently discussed in the literature (5,6). In the recent
years, research has been conducted to answer the
question “whether technological addictions such as
internet addiction, social media addiction, digital game
addiction and smartphone addiction are myths or are
they really behavioral addictions?” Research has
emphasized that individuals with internet addiction,
social media addiction, digital game addiction, and
smartphone addiction exhibit symptoms similar to those
with other behavioral or chemical addictions (7-15).
Internet addiction, social media addiction and
smartphone addiction are not classified as a disorder in
DSM-5. However, in chapter 3 of DSM-5 it is
suggested that digital game addiction can be recognized
as “internet gaming disorder”. In the DSM-5 internet
gaming disorder is defined with 9 diagnostic criteria:
preoccupation with internet games (internet gaming
becomes the dominant activity in daily life), tolerance
(the need to spend increasing amounts of time engaged
in internet games), withdrawal symptoms (irritability,
anxiety, or sadness), continuity/permanence
(unsuccessful attempts to control the participation in
internet games), replacement (preferring internet games
against previous hobbies and entertainment), continued
excessive use of internet games despite knowledge of
psychosocial problems, deceiving (deceiving others
regarding the amount of internet gaming), escape
(use of internet games to escape from a negative
mood), conflict/lost (having lost educational or career
opportunities). Observation of five or more criteria in
the last one year indicates internet gaming disorder.
Besides, for the first time the concept of internet
addiction took place in DSM-5 (7). It is anticipated
that technological addictions will be included in a
wider range in later versions of DSM. In the literature,
internet addiction, social media addiction and smart
phone addiction are considered as behavioral
addiction. Griffiths (16), Young (17), Anderson (18)
and Shapira et al. (19) have described smartphone
addiction as a behavioral addiction; Kuss and
Griffiths (20), Griffiths (21), van den Eijnden et al.
(14) and Lin et al. (23) have described smartphone
addiction as a behavioral addiction.
Internet addiction is the main framework of other
internet related addictions. In this context, Griffiths
and Szabo (13) emphasize that the internet activities
as well as the internet are addictive sources. Therefore,
concepts such as social media addiction, digital game
addiction and smart phone addiction can be
considered as addictions in which the active substance
is internet (14,22). Regardless of the type of addictive
practice or application, internet addiction is
considered as a whole. But the concepts of social
media addiction, digital game addiction, smartphone
addiction are more specific and more purposeful.
internet addiction can be likened to “volatile
substances” in this respect. The concept of volatile
substances constitutes the basic framework of
materials such as adhesives, thinners, cooler sprays
and lighter gas. Knowing what type of volatile
substance an individual is addicted, facilitates
intervention and prevention efforts. Similarly, internet
addiction is a general and inclusive concept. It is very
critical in terms of preventive and intervention efforts
to know which application or activity of the internet
is the person addicted. In this context, Kuss and
Griffiths (20) consider internet addiction, social media
addiction, digital gaming addiction and smart phone
Technological addictions and social connectedness: predictor effect of internet addiction, social media addiction, digital game ...
204 Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
addiction as technological addictions. Therefore, it is
possible to judge all these addictions as technological
addictions or technology related addictions as
technological addictions or technology related
addictions.
Examining the literature, a common definition can
be given to the concepts of internet addiction, social
media addiction, digital game addiction and
smartphone addiction. According to this, “the state of
excessive use, unsatisfied desire to use, neglect of
activities due to excessive use, disrupting social
relations due to excessive use, use as an escape tool
from negative emotions and life stress, having
problems in giving up and reducing the use, becoming
nervous and anxious when it is not possible to use,
and deceiving others regarding the duration and
amount of use” defines internet addiction, social
media addiction, digital game addiction and
smartphone addiction (7,14,17,22). Since internet
addiction is the main component of social media
addiction, digital game addiction and smart phone
addiction, it is possible to say that internet addiction is
highly related to these addictions.
In the literature, technological addictions are related
to biopsychosocial problems. Research have shown
that internet addiction, social media addiction,
smartphone addiction and digital game addiction are
associated with “depression” (24-27), “impulsivity”
(7,28-30), “loneliness” (31-34), “sleep quality”
(25,27,35,36), “well-being” (25,37-39), “self-esteem”
(33,34,40,41) and “academic performance” (24,42-44).
On the other hand, according to some researchers, the
use of technology strengthens friendship, facilitates
interpersonal conversations and communication, and
allows establishing new social relations (45-47).
Therefore, the problematic use of technology should
be regarded as an important criterion. Hence, research
emphasize that problematic internet usage is related to
psychopathological symptoms (48).
The literature discusses the effects of internet
addiction, social media addiction, smartphone
addiction and digital gaming addiction on social
connectedness. Grieve et al. (49) emphasize that the
use of social media provides positive contributions to
the development and maintenance of social
connectedness. Similarly, Quinn and Oldmeadow (50)
found that adolescents using social media had a higher
sense of belonging than adolescents who did not.
Additionally, Davis (51) emphasizes that the use of
technology strengthens friendship and increases social
connectedness. Use of appropriate and effective
technology can provide significant contributions to
social relationships, but harms social relationships
when technology use reaches a problematic level.
In the literature, there is no research on which of
the technological addictions such as internet addiction,
social media addiction, smart phone addiction and
digital game addiction have a higher effect on social
connectedness. However, it can be said that internet
addiction has a higher effect on social connectedness
because internet addiction constitutes the main
framework of other addictions related to internet
(social media addiction, smart phone addiction and
digital game addiction). In the research, the effects of
internet addiction, social media addiction, smartphone
addiction and digital game addiction on social
connectedness have been investigated separately. In
this context, researchers emphasize that the use of
internet, social media, digital gaming and smartphone
at the level of addiction hinders real social relations and
consequently social connectedness is reduced (52-54).
Social connectedness is the subjective perception of
whether an individual feels himself or herself as a
significant part of his/her social and emotional
relationships (55). As this subjective perception
increases, social connectedness becomes stronger.
Moore (56) emphasizes that social connectedness
should be regarded as a talent. According to Moore (56),
social connectedness is defined as the ability to
develop meaningful relationships that will facilitate
the individual to view himself/herself as part of his/her
relationships. Maslow (57) also considers social
connectedness as a basic human need. Technology
can be used as an alternative tool to address this need.
In this context, it is possible to say that communication
technologies in particular have a critical importance in
the development and maintenance of social
connectedness. Hence, Chayko (58) emphasizes that
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Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
the internet and digital technologies connect people
living in different regions of the world, which
contributes to people get aware of each other and have
communication. Therefore, it can be said that internet
and digital technologies strengthen social
connectedness.
Problematic use of technology is an important
criterion in the relationship between technology use and
social connectedness. Social connectedness is negatively
affected if the use of technology restricts real social
relations and leads to isolation and alienation (59).
Intense use of technology restricts the individual’s true
social environment interactions and interpersonal
relations which cause the individual to move away
from the real social environment. When isolated from
the true social environment the individual starts to
perceive himself as not being a meaningful part of his
relationships (53,54,60). Similarly, McIntyre et al. (61)
emphasize that compulsive internet use can directly
affect social connectedness as well as through
personality traits. According to McIntyre et al. (61),
when the internet is used at the compulsive level, it
becomes difficult for the individual to develop
meaningful and sustainable relations and to feel himself
as a meaningful part of his relations.
Adolescence is regarded as a critical period in terms
of social connectedness (55,62) and technological
addictions such as internet addiction, social media
addiction, digital game addiction and smartphone
addiction (4,15,22). The use of technologies such as
the internet and social media is more common among
adolescents. This makes the adolescents more
vulnerable to technological addictions (63). In this
context, Andreassen (64) emphasizes that the fact that
there are no authority figures in virtual environments
leads the adolescents to virtual environments.
Adolescence is a period when conflicts with the
authority figure are experienced. Adolescent frequently
prefers virtual environments to avoid this conflict.
Hence, Yen et al. (65) indicate that adolescents use
virtual environments as an alternative means of coping
with psychosocial problems. During adolescence, the
individual is in search of a group or individual to whom
he or she can associate or feel belonging. This is quite
critical in terms of the development of the adolescent’s
social connectedness. Social connectedness affects
both adolescence and adulthood developmental tasks.
It has been emphasized that individuals with low levels
of social connectedness tend to be isolated from
society, have problems in associating themselves or
sense of belonging, have negative perceptions towards
themselves and others, and have distrust (55,62,66). In
this context, particular attention should be paid to
technological addictions and social connectedness in
biopsychosocial evaluation of adolescents.
Technological addictions cause the adolescent become
lonely, get isolated from the society and deteriorate
interpersonal relations. This prevents the adolescent
from developing social connectedness or reduces the
existing level of social connectedness.
In addition to internet addiction, social media
addiction, digital game addiction and smart phone
addiction, TV addiction (67), phubbing (68), online
pornography addiction (69), online shopping
addiction (70), and online sex addiction (71) are
considered within the scope of technological
addictions in the literature. However, in this study,
the concept of technological addiction is limited to
internet addiction, social media addiction, digital
game addiction and smart phone addiction. In this
study, the predictive effect of technological addictions
on social connectedness in adolescents was examined.
There are many studies in the literature that examine
the relation of technological addiction to social
connectedness. However, no research has been found
on which technological addiction is more risky in
terms of social connectedness. No studies
investigating the effects of multiple technological
addictions on social connectedness have been
available. It is conceivable that this research can reach
important conclusions about how social
connectedness is affected by technological addictions.
Determining the extent to which social connectedness
is affected by technological addictions and which
technological addiction has more effect on social
connectedness will provide a significant contribution
to the protection of social connectedness against
technological addictions. Since social connectedness
Technological addictions and social connectedness: predictor effect of internet addiction, social media addiction, digital game ...
206 Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
is an evolving construct, it is critical to determine the
risk factors regarding social connectedness.
Accordingly, the identification of risk factors may
contribute to the development and protection of
social connectedness.
METHOD
Study Design
This is a descriptive study examining the predictive
effect of internet addiction, social media addiction,
digital game addiction and smartphone addiction on
social connectedness in adolescents.
Study Group
The study was carried out with the students
attending four high schools (Anatolian High School,
Science High School, Vocational and Technical High
School and Religious Vocational High School) affiliated
to Elazig Provincial Directorate of National Education
in 2015-2016 academic year. The Convenience
Sampling method was used in the study. The study
has been conducted on adolescents who have been
using the internet, playing digital games, and using
social media and having at least one social media
account and a smartphone over the past year. It has
been found that 21 adolescents who met these criteria
did not want to participate in the study. Upon
administration, data was collected from 209
adolescents. Data of the 8 subjects were not included
in the analyzes because they were incomplete, sloppy
and incorrect. Consequently, 201 volunteers who met
the criteria were included in the study. Of the
adolescents, 101 (50.2%) were female and 100 (48.8%)
were male. The adolescents ranged 14-18 years old.
Measures
In this study, Young’s Internet Addiction Test
Short Form (YIAT-SF), Smart Phone Addiction Scale
Short Form (SAS-SF), Digital Game Addiction Scale
(DGAS-7), Social Media Disorder Scale (SMDS), Social
Connectedness Scale (SCS) and Personal Information
Form were used as data collection tools.
Young’s Internet Addiction Test Short Form
(YIAT-SF): YIAT-SF, developed by Young (17) and
transformed into a short form by Pawlikowski et al. (72),
is a 5-point Likert type measure consisting of 12 items.
The Turkish version of YIAT-SF was conducted by
Kutlu et al. (73) on both adolescents and university
students. As a result of the Exploratory Factor Analysis
(EFA), it was seen that it was a one-factor scale in both
university students and adolescents. One-factor
structure of the scale was tested with Confirmatory
Factor Analysis (CFA). The fit index values for CFA
showed good fit both in university students
(χ2=144.930, sd=52, RMSEA=0.072, RMR=0.70,
GFI=0.93, AGFI=0.90, CFI=0.95 and IFI=0.91) and in
adolescents (χ2=141,934, sd=51, RMSEA=0.080,
GFI=0.90, CFI=0.90 ve IFI=0.90). The Cronbach alpha
reliability coefficient of the scale was 0.91 in university
students and 0.86 in adolescents. The test-retest
reliability of the YIAT-SF was 0.93 in the university
students and 0.86 in the adolescents. There are no
reversed scored items and the high scores indicate
increased risk of internet addiction.
Social Media Disorder Scale (SMDS): SMDS
is a Likert-type measure consisting of 9 items and
one dimension that was developed by van den
Eijnden et al. (22) and adapted to Turkish by Savci,
Ercengiz and Aysan (74). As a result of the EFA, it was
seen that it has a one-factor structure which accounts
for 47.88% of total variance. This one-factor structure
was tested with CFA in two separate samples. As a
result of the analysis, it was found that the social media
disorder model had good fit values in both samples
[(χ2=39.237, sd=27, χ2/sd=1.453, RMSEA=0.055,
GFI=0.95, AGFI=0.91, CFI=0.97, IFI=0.97 ve TLI
(NNFI)=0.96, (χ2=50.725, sd=26, χ2/sd=1.951,
RMSEA=0.072, GFI=0.94, AGFI=0.90, CFI=0.94,
IFI=0.94 ve TLI (NNFI)=0.92]. The factor loadings of
SMDS for EFA range from 0.58 to 0.77 and for CFA
range from 0.44 to 0.75. According to the results of
criterion-related validity analysis of SMDS is positively
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Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
related with the duration of social media usage, number
of social media accounts, negative emotions and
impulsivity, but negatively related with self-esteem,
social connectedness, and positive emotions. The
reliability of SMDS was examined with test-retest
method and Cronbach’s α internal consistency
reliability coefficient in three different samples.
Cronbach’s alpha coefficient was 0.83, 0.86 and 0.86;
and a three-week test-retest correlation was 0.805.
There are no reverse-scored items, and high scores
indicate an increased risk of social media disorder/
addiction.
Digital Game Addiction Scale (DGAS-7):
DGAS-7 is a Likert-type scale consisting of 7 items and
one dimension developed by Lemmens et al. (4) and
adapted to Turkish by Yalcin-Irmak and Erdogan (75).
In EFA results it was seen that DGAS-7 has a one-factor
structure that accounts for 56.96% of the total variance.
This one-factor structure was tested with CFA. As a
result of the analysis, it was found that the digital game
addiction model had acceptable fit index values
(χ2=14.22, p=0.37, sd=14, RMSEA=0.012, AGFI=0.92,
CFI=0.99, GFI=0.96 ve SRMR=0.06). The factor
loadings of the DGAS-7 ranged from 0.52 to 0.77 and
the item total score correlation coefficients ranged from
0.52 to 0.76. The Cronbach alpha coefficient of the
DGAS-7 was 0.72 and the three-week test-retest
correlation was 0.80. There are no reverse-scored
items, and high scores indicate increased risk of digital
game addiction.
Smartphone Addiction Scale Short Version
(SAS-SV): SAS-SV is a Likert-type scale consisting
of 10 items and one dimension that was developed
by Kwon et al. (14) and adapted to Turkish by
Noyan et al. (76). The one-dimensional structure of
SAS-SF accounts for 46.3% of the total variance. The
factor loadings of SAS-SF range from 0.49 to 0.83.
The criterion validity of SAS-SF was examined
with internet addiction. As a result of the analysis,
it was seen that SAS-SF is related to internet
addiction in expected direction and level. The
reliability of SAS-SF was examined by Chronbach
alpha coefficient and test-retest reliability coefficient.
As a result of the analysis, Chronbach alpha
coefficient of SAS-SF was 0.87 and test-retest
reliability coefficient was 0.93. There are no reverse-
scored items, and high scores indicate increased risk
for smartphone addiction.
Social Connectedness Scale (SCS): The SCS
which was developed by Lee and Robbins (62) and
adopted to Turkish by Duru (77), is a one-dimensional
measure with 8 negative items. The SCS is assessed
over 6 points. As a result of EFA, it was seen that
Turkish version of SCS had one dimension. Criterion
validity of the SCS was assessed by UCLA Loneliness
Scale, Life Satisfaction Scale and Social Provisions
Scale. As a result of the criterion-related validity
analysis, it was seen that the SCS was associated with
these scales in the expected direction and level.
Cronbach’s alpha internal consistency reliability
coefficient of the SCS was 0.90 and test-retest reliability
coefficient was 0.90. There are no reverse-scored items,
and high scores indicate high level of social
connectedness.
Data Collection Phase
This study was conducted within the scope of the
first author’s doctoral dissertation that was executed
under the supervision of the second author. Therefore,
the data of the research has been collected within the
permission granted to the doctoral dissertation. The
research data were collected in classrooms of the
adolescents. Administration took place at four high
schools affiliated to Elazig Provincial Directorate of
National Education in 2015-2016 academic year. The
researcher explained the purpose of the research, the
administration method and the principles of privacy
and volunteering, and read the informed consent form.
Since the sample group was large, the Informed
Volunteer Consent Form was read by the researcher in
order that the administration did not interfere with the
lectures and that it could be completed in one lecture
hour. Consents were not obtained from the
participants’ families. However, the administration was
Technological addictions and social connectedness: predictor effect of internet addiction, social media addiction, digital game ...
208 Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
carried out by the researcher within the implicit
knowledge and approval of the school management
and under the supervision of the teachers. Volunteer
adolescents who have been using the internet, playing
digital games, and using social media, and having at
least one social media account and a smartphone in the
past year have been included in the study. Adolescents
who did not meet these criteria or met the criteria but
did not volunteer, were not included in the study. It
was observed that the administration lasted 25-30
minutes. At the end of the administration, 8 subjects
with incomplete, sloppy or incorrect data were
excluded and analyses were carried out on the
remaining data. The researchers declare that this study
was carried out in accordance with the Helsinki
Declaration.
Statistical Analysis
Statistical analyzes were performed considering loss
and extreme values, single and multivariable normality,
linearity, and multicolinearity problems. In this context,
firstly data set was examined in terms of loss and
extreme values. Missing data was replaced with series
mean. Then extreme values were examined and no
extreme data which could adversely affect the analysis
were detected. The research data were examined in
terms of single and multivariable normality and it was
found that the skewness (-0.36 to 0.58) and the kurtosis
coefficients (-0.69 to 0.47) for the research variables
were within acceptable values. In addition, the
Scattering Diagram Matrix was examined and it was
seen that there are elliptical distributions. These findings
indicate that the research data meet the assumptions of
linearity and single and multivariable normality (78).
The correlations between variables and VIF and
tolerance values were examined to evaluate whether or
not the research data caused multicolinearity problems.
The multicolinearity problem occurs when the
correlation between variables is greater than 0.90, VIF
values are greater than 10, and tolerance values are less
than 0.10 (78). Binary correlations between the
independent variables of the study do not cause a
multicolinearity problem (r<0.90 for all binary
correlations). In addition, the VIF (all VIF values of
independent variables are less than 10) and the tolerance
values (all tolerance values of independent variables are
greater than 0.10) of independent variables do not cause
a multicolinearity problem. Taking into account these
statistical analyzes, the data of the research was
analyzed by parametric statistical methods.
RESULTS
Descriptive Statistics and Correlation Values
Descriptive statistics and correlation values for
dependent variables and independent variables are
presented in Table 1.
The skewness coefficients of the variables in the
study ranged from -0.36 to 0.58, the kurtosis
coefficients ranged from -0.69 to 0.47, and the
Cronbach alpha internal consistency reliability
coefficients ranged from 0.77 to 0.93. Social
connectedness was negatively and moderately related
with internet addiction (r=-0.34, p<0.01) and social
Table 1: Descriptive statistics and correlation values of variables
Descriptive Statistics Correlation Values
Mean SD Skewness Kurtosis Cronbach’s
Alpha
Social
connectedness
Social connectedness 35.38 9.57 -0.36 -0.69 0.91 Internet addiction -0.34*
Internet addiction 30.90 8.29 0.57 0.47 0.84 Social media addiction -0.33*
Social media addiction 21.54 5.83 0.32 -0.53 0.78 Digital game addiction -0.28*
Digital game addiction 16.79 4.64 0.15 -0.44 0.77 Smartphone addiction -0.22*
Smartphone addiction 21.64 8.87 0.58 -0.58 0.93
*p<0.01, SD: Standard deviation
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media addiction (r=-0.33, p<0.01); and it was
negatively and mildly related with digital game
addiction (r=-0.28, p<0.01) and smart phone addiction
(r=-0.22, p<0.01).
The Predictive Effect of Technological
Addictions on Social Connectedness
The results of multiple regression analysis regarding
the predictive effect of technological addictions on
social connectedness are presented in Table 2.
According to the results of multiple regression analysis
given in Table 2, internet addiction, social media addiction,
digital game addiction and smartphone addiction
predicted 25% (R2=0.25 p<0.001) of social connectedness
significantly (F[4,196]=16.438, p<0.001). When t-test
results regarding the significance of the regression
coefficients are examined, the greatest contribution to the
prediction of social connectedness is from internet
addiction, followed by social media addiction, digital
game addiction and smartphone addiction.
Internet addiction is the main framework of social
media addiction, digital game addiction, and
smartphone addiction. This fact can cause a concern
that social connectedness is predominantly predicted
by internet addiction. For that reason, internet
addiction has been removed from the model and the
predictive effect of social media addiction, digital game
addiction, and smartphone addiction on social
connectedness has been examined. The results of
multiple regression analysis are presented in Table 3.
According to the results of multiple regression
analysis given in Table 3, social media addiction, digital
game addiction and smartphone addiction predicted
20% (R2=0.20 p<0.001) of social connectedness
significantly (F[3,197]=16.072, p<0.001). When the
results of the t-test on the significance of the regression
coefficients are examined, it has been found that social
media disorder, digital game addiction and smartphone
addiction, respectively, contribute significantly to the
prediction of social connectedness.
DISCUSSION
In this study, the predictive effect of internet
addiction, social media addiction, digital game
addiction, and smartphone addiction on social
connectedness has been investigated. As a result of the
study, it is seen that these technological addictions
predict the social connectedness negatively and
Table 2: Results of multiple regression analysis regarding predictive effect of ınternet addiction, social media
addiction, digital game addiction, and smartphone addiction on social connectedness
Predicted Variable Predictors B Standard Error Beta t p
Social Connectedness Constant 62.940 3.461 18.185 <0.001
Internet addiction -0.283 0.075 -0.245 -3.780 <0.001
Social media disorder -0.376 0.107 -0.229 -3.531 <0.001
Digital game addiction -0.398 0.131 -0.193 -3.041 <0.001
Smartphone addiction -0.186 0.068 -0.172 -2.749 <0.001
R=0.50 R2=0.25, Adj R2=0.24, F (4,196)=16.438, p<0.001
Table 3: Results of multiple regression analysis regarding predictive effect of social media addiction, digital game
addiction and smartphone addiction on social connectedness
Predicted Variable Predictors B Standard Error Beta t p
Social Connectedness Constant 57.396 3.239 17.721 <0.001
Social media disorder -0.489 0.106 -0.298 -4.628 <0.001
Digital game addiction -0.440 0.135 -0.213 -3.266 <0.001
Smartphone addiction -0.189 0.070 -0.175 -2.705 <0.001
R=0.44 R2=0.20, Adj R2=0.18, F (3,197)=16.438, p<0.001
Technological addictions and social connectedness: predictor effect of internet addiction, social media addiction, digital game ...
210 Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
significantly. It has been seen that the greatest
contribution to the prediction of social connectedness
is from internet addiction. Social media addiction,
digital game addiction and smartphone addiction,
respectively, provide significant contributions to the
prediction of social connectedness.
The effects of internet addiction, social media
addiction, digital game addiction, and smart phone
addiction on social connectedness can be explained by
real social environments, loneliness, peer groups and
friendship, communication skills and socialization
tendencies, intimate relationship and personality traits.
Theoretical explanations and research results regarding
these factors are presented below.
Technology is used as an alternative to real social
environments in the development and maintenance of
social connectedness. With technological advances,
individuals in different continents of the world have the
opportunity to communicate and interact at the speed of
light. This provides crucial contributions to the
establishment and maintenance of interpersonal
relationships and to the participation in the society (58).
However, technology can be overused to disrupt
functioning in some individuals. Such use can cause the
individual move away from the true social environment
(31,33,52). In this context, it can be said that the
pathological or problematic use of technology negatively
affects social connectedness. Lee and Robbins (55)
emphasize that social connectedness developes through
interpersonal relationships established in the real social
world. Therefore, it is possible to say that individuals
who spend a considerable part of their time in virtual
environments and play games are at risk in terms of
social connectedness.
Bargh and McKenna (79) emphasize that using the
internet in a non-functional way causes young people
to get trapped in pornography and become addicted to
the internet. According to Bargh and McKenna (79),
these individuals spend limited time with their family
and friends and become lonely. As a consequence,
social ties weaken and social connectedness decreases.
In addition, van den Eijnden et al. (22) emphasize that
social media addiction, Bian and Leung (31)
smartphone addiction, and van Rooij et al. (34) game
addiction cause young people to be isolated from the
real social environment. In this context, it can be said
that the individuals with technological addictions
become lonely, and social connectedness decreases in
the individuals who become lonely. As a matter of fact,
Lee and Robbins (55) emphasize that loneliness is a
risk factor in terms of social connectedness.
During adolescence, peer groups and friendships
gain importance. Adolescents meet the need of
belonging by joining peer groups and developing
friendships. During adolescence, peer groups and
friendships become more meaningful than all other
relationships that adolescents have (80,81). This shows
that peer groups and friendship relations have a critical
importance in adolescent social connectedness. In
addition, the family is also considered as an important
factor in the development of adolescent social
connectedness (82). Social connectedness weakens if
peer, friendship, and family relations of the adolescent
is restricted. In other words, the quality of the
relationship that the adolescent has developed with
his peers and family affects social connectedness.
Therefore, it is possible to say that factors that restrict
or block these relationships of adolescents negatively
affect social connectedness (55,56,62). It is
emphasized in the literature that technological
addictions restrict and hinder the development of
these relations (7,17,22). In sum, technological
addictions adversely affect the quality of relationship
of adolescents with their peers, friends and family.
This prevents the adolescent from seeing himself as a
meaningful part of his relationships. Therefore, level
of social connectedness of adolescents with
technological addictions decreases or the development
of social connectedness is hampered.
Technological addiction negatively affects the
person’s interpersonal communication skills and
tendency to socialize (7,15). Individuals with
technological addictions spend a noteworthy amount
of their daily life in virtual environments. This leads
to weakening of the features used in the real social
environment. Therefore, the skills and tendencies
required by the actual social environments are
distorted. Indeed, virtual environments lack in clues
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to true social communication and do not reflect the
spirit of real social environments (83). In this context
Ogel (84) emphasizes that virtual environments are the
loss of social life which is called reality. According to
Ogel (84), virtual environments cause deformation of
real socialization. In the literature, communication skills
and tendency to socialization are considered to be
positive contributors to social connectedness (62,85). In
this context, the effect of technological addictions on
social connectedness can be explained by
communication skills and the tendency to socialize.
Therefore, it can be said that tendency to socialize and
communication skills of the individuals with
technological addictions decrease, and as a result, their
social connectedness weakens.
Technological addiction causes the deterioration of
intimate relations of the individual. Hence, in the two
items of Young’s eight-item list proposed for the
diagnosis of internet addiction, refers to the
interpersonal relations (17). Young (17) suggests
“excessive internet use causes problems with family,
school, work and friend” and “false statements about
internet usage” as two criteria for diagnosing internet
addiction. Similarly, two of the nine criteria for DSM-5
internet gaming disorders are related to interpersonal
relationships (7). In DSM 5, the two criteria: “has
deceived family members, therapists, or others
regarding the amount of internet gaming” and “has
jeopardized or lost a significant relationship, job, or
educational or career opportunity because of
participation in internet games” are used to diagnose
internet gaming disorder (7). In addition, three of the
nine criteria proposed by van den Eijnden and
colleagues (22) to measure social media disorder/
addiction are about interpersonal relationships.
According to this, “regularly had arguments with others
because of social media use”, “ regularly lied to parents
or friends about the amount of time spent on social
media” and “had serious conflict with parent(s) and
sibling(s) because of social media use” are considered
as criteria of social media disorder/addiction. Finally, in
the scale developed to measure smartphone addiction
by Kwon et al. (14) it is emphasized that the use of
smartphones negatively affects interpersonal
relationships. In the diagnoses of internet addiction,
social media addiction, digital game addiction and
smartphone addiction, it is emphasized that intensive
use negatively affects interpersonal relationships and
causes deceptive behaviors in interpersonal
relationships. Individual’s feeling himself or herself as a
meaningful part of his/her relationships is considered
as a critical indicator of social connectedness (55).
However, technological addictions cause the individual
to have arguments and conflicts in interpersonal
relations and to get deceptive behaviors in interpersonal
relations. For this reason, it is possible to say that the
social connectedness is negatively affected in the
individuals with technological addictions.
It is possible to explain the effect of technological
addictions on social connectedness with personality
traits. According to McIntyre et al. (61), internet
addiction causes progression of individual’s introverted
personality traits. Introverted personality traits cause
the individual to move away from the real social
environment. This negatively affects social
connectedness. Indeed, Lee et al. (85) emphasize that
extroverted personality trait is a factor strengthening
social connectedness. Extroverted adolescents prefer
face-to-face interaction rather than interacting with the
virtual world. However, introverted adolescents avoid
interaction with other people because they are shy.
This leads to a more intense use of the virtual world in
maintaining communications and relationships (86).
However, Savci and Aysan (87) found that the internet
contributed to the coalescence of adolescents with
their friends and that adolescents with high internet
addiction experienced a higher level of peer association.
Therefore, the question arises: “Does internet use have
different consequences for individuals with different
personality traits?” The negative consequences of the
internet use are susceptible to personality traits (61).
internet use can weaken extroverted personality traits,
trigger introverted personality traits, or can cause
progression of extroverted personality traits. The
internet and social media can contribute to the
development and maintenance of social relations of
individuals with extroverted personality traits (20).
Hence, the motivation of extrovert individuals to use
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212 Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
social media is different from the introverted
individuals. However, Rothschild (88) emphasizes that
social media use positively affects social connectedness
in individuals with low levels of social skills and affects
negatively in individuals with high social skills.
It has been seen in the literature that there are
conflicting explanations and research results regarding
the relationship between introverted and extroverted
personality traits and the use of the internet, social
media and smartphones. When the internet, social
media, and smartphone are used functionally, they can
have positive results in extroverted and introverted
individuals. However, using the internet at the level of
addiction leads to increased introverted personality
traits and decreased extroverted personality traits. It
has also been found that digital game addicts have low
extroverted personality traits (89). Lee et al. (85)
emphasize that extroverted personality trait is an
important source in the development of social
connectedness. Therefore, when the effects of
technological addictions on social connectedness are
examined, it is necessary to take personality traits into
account. Hence, it has been found in research that
technological addictions are closely related to
personality traits (90-94).
The strongest predictive effect on social
connectedness is from internet addiction and the
weakest effect from smart phone addiction. This is due
to the specific characteristics of technological addictions
(internet addiction, social media addiction, digital game
addiction and smartphone addiction). It is not
anticipated that an addiction to a smartphone without
the internet, mobile applications (especially social media
applications) and games will develop. The development
of smartphone addiction is due to the smartphone’s
internet access, the use of social media applications and
the ability to play games. The adolescents involved in
the research may have been using the internet, social
media and digital games on different devices. Smart
phone addiction is significant with internet, social media
and gaming. Having a smart phone alone is not
addictive, it is necessary to use these features. For this
reason, smartphone addiction may be a weaker predictor
than other independent variables. The reason for internet
addiction’s being the strongest predictor of social
connectedness is due to the fact that the internet is the
center point of other technological addictions (social
media, digital gaming and smartphones).
In this study, it was determined that internet
addiction, social media addiction, digital game
addiction and smart phone addiction are important
predictors of social connectedness in adolescents.
Therefore, these addictions should be taken into
consideration in social connectedness work and
studies. Real social environments are considered to be
an effective factor in the development of social
connectedness (55) and in the prevention and treatment
of technological addictions (87,95). For this reason,
adolescents should be directed to real social
environments by their parents and their school
teachers. Also the relationships established by the
adolescents in the real social environment should be
supported. Parents should have an encouraging and
permissive attitude towards adolescent to spend time
with the peers. Finally, the internet and its associates
can be used to contribute positively to social
connectedness. In other words, the internet and its
associates can help the adolescent to develop new
social relationships and maintain existing relationships.
This requires conscious and functional use. In this
context, especially education of adolescents on the
effective and functional use of internet and its
associates should be increased. In addition, activities to
prevent technological addictions and to promote social
connectedness should be implemented within the
counseling activities at schools.
Digital gaming addiction can be avoided with real
social games. This can both associate the adolescent to
the real social environment and prevent from developing
digital games addiction. Therefore, games based on true
social interactions should be foregrounded at home and
at school. Smartphones are heavily used by adolescents
because they are user friendly and widespread tools
that combine numerous possibilities such as online
communication-interaction, entertainment and
shopping. When the use reaches to a level enough to
hamper daily functioning, it can lead to a wide range of
harmful results from preventing the adolescent from
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having eye contact in communication to weakening of
social connectedness. Hence, smartphone usage habits
of adolescents should be followed carefully by parents.
Parents should stop or limit the adolescent’s smartphone
use if the use negatively affects the academic success of
the adolescent or the relationships and interactions, and
leads to the adolescent become lonely and socially
isolated.
This research has included adolescents who have
been using the internet, playing digital games, using
social media, and having at least one social media
account and a smartphone for the past year. However,
this is a non-clinical sample. Therefore, the effect of
technological addiction on social connectedness can be
examined in a clinical sample in future studies. The
scales used in this research are self-report measures.
Future research may use measures based on parent,
teacher, or peer feedback. Such scales are not currently
available in the literature. However, the development
of these scales and the repetition of this research will
provide critical contributions to the study findings. In
addition, the impact of technological addiction on
social connectedness should be supported by
longitudinal, empirical and qualitative studies. In this
study, social connectedness was measured on a one-
dimensional scale. Future studies should also consider
family connectedness, school connectedness, peer
connectedness, and belonging. In this research, internet
addiction, social media addiction, digital game
addiction and smartphone addiction were evaluated in
the context of technological addictions. TV addiction,
phubbing, online pornography addiction, online
shopping addiction and online sex addiction should
also be taken into account in later research.
Conflict of Interest: Authors declared no conflict of interest.
Financial Disclosure: Authors declared no financial support.
Contributions category Authors name
Development of study idea M.S., F.A.
Methodological design of the study M.S., F.A.
Data acquisition and process M.S., F.A.
Data analysis and interpretation M.S., F.A.
Literature review M.S., F.A.
Manuscript writing M.S., F.A.
Manuscript review and revisation M.S., F.A.
REFERENCES
1. Kemp S. Digital in 2016. http://wearesocial.com/uk/special-
reports/digital-in. Accessed date: October 11, 2016.
2. Worldometers. http://www.worldometers.info/tr/. Accessed
date: October 11, 2016.
3. Turkish Statistical Institute (TUIK). The research of household
use of comminucation technologies. http://www.tuik.gov.tr/
PreHaberBultenleri.do?id=21779. Accessed date: October 11, 2016.
4. Lemmens JS, Valkenburg PM, Peter J. Development and
validation of a game addiction Scale for adolescents. Media
Psychology 2009; 12:77-95. [CrossRef]
5. Griffiths M. Internet addiction: Fact or fiction? The Psychologist:
Bulletin of the British Psychological Society 1999; 12:246-250.
6. Griffiths M. Does internet and computer “addiction” exist? Some case
study evidence. Cyberpsychol Behav 2004; 3:211-218. [CrossRef]
7. American Psychiatric Association. Diagnostic and Statistical
Manual of Mental Disorders (DSM-5). Arlington: American
Psychiatric Publishing; 2013.
8. Beard KW, Wolf EM. Modification in the proposed diagnostic
criteria for Internet addiction. Cyberpsychol Behav 2001; 4:377-
383. [CrossRef]
9. Caplan SE. Problematic Internet use and psychosocial well-
being: Development of a theory-based cognitive-behavioral
measurement instrument. Comput Hum Behav 2002; 18:553-
575. [CrossRef]
10. Davis RA. A cognitive-behavioral model of pathological internet
use. Comput Human Behav 2001; 17:187-195. [CrossRef]
11. Echeburúa E, De Corral P. Addiction to new technologies and
to online social networking in young people: a new challenge.
Adicciones 2010; 22:91-95. (Spanish) [CrossRef]
12. Griffiths M. A ‘components’ model of addiction within a
biopsychosocial framework. J Subst Use 2005; 10:191-197.
[CrossRef]
13. Griffiths MD, Szabo A. Is excessive online usage a function of
medium or activity? An empirical pilot study. J Behav Addict
2014; 3:74-77. [CrossRef]
Technological addictions and social connectedness: predictor effect of internet addiction, social media addiction, digital game ...
214 Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
14. Kwon M, Lee JY, Won WY, Park JW, Min JA, Hahn C, Gu X,
Choi JH, Kim DJ. Development and validation of a Smartphone
Addiction Scale (SAS). PLoS One 2013; 8:e56936. [CrossRef]
15. Young KS, Yue XD, Ying L. Prevalence Estimates and Etiologic
Models of Internet Addiction. In Young KS, de Abreu CN
(Editors.) Internet Addiction: A Handbook and Guide to
Evaluation and Treatment. Hoboken, New Jersey: John Wiley &
Sons, Inc, 2011; 19-31.
16. Griffiths MD. Internet addiction: An issue for clinical psychology?
Clinical Psychology Forum 1996; 97:32-36.
17. Young KS. Caught in the Net: How to Recognize the Signs of
Internet Addiction and a Winning Strategy for Recovery. New
York: John Wiley & Sons, 1998.
18. Anderson KJ. Internet use among college students: an exploratory
study. J Am Coll Health 2001; 50:21-26. [CrossRef]
19. Shapira NA, Lessig MC, Goldsmith TD, Szabo ST, Lazoritz
M, Gold MS, Stein DJ. Problematic internet use: proposed
classification and diagnostic criteria. Depress Anxiety 2003;
17:207-216. [CrossRef]
20. Kuss DJ, Griffiths MD. Online social networking and addiction-
a review of the psychological literature. Int J Environ Res Public
Health 2011; 8:3528-3552. [CrossRef]
21. Griffiths MD. Social networking addiction: emerging themes and
ıssues. J Addict Res Ther 2013; 4:e118. [CrossRef]
22. van den Eijnden RJJM, Lemmens JS, Valkenburg PM. The Social
Media Disorder Scale. Comput Human Behav 2016; 61:478-487.
[CrossRef]
23. Lin YH, Chang LR, Lee YH, Tseng HW, Kuo TB, Chen SH.
Development and validation of the Smartphone Addiction
Inventory (SPAI). PLoS One 2014; 9:e98312. [CrossRef]
24. Brunborg GS, Mentzoni RA, Frøyland LR. Is video gaming, or
video game addiction, associated with depression, academic
achievement, heavy episodic drinking, or conduct problems? J
Behav Addict 2014; 3:27-32. [CrossRef]
25. Demirci K, Akgonul M, Akpinar A. Relationship of smartphone
use severity with sleep quality, depression, and anxiety in
university students. J Behav Addict 2015; 4:85-92. [CrossRef]
26. Young KS, Rogers RC. The relationship between depression
and Internet addiction. Cyberpsychol Behav 2009; 1:25-28.
[CrossRef]
27. Woods HC, Scott H. #Sleepyteens: Social media use in
adolescence is associated with poor sleep quality, anxiety,
depression and low self-esteem. J Adolesc 2016; 51:41-49.
[CrossRef]
28. Billieux J, Van der Linden M, d’Acremont M, Ceschi G,
Zermatten A. Does impulsivity relate to perceived dependence
on and actual use of the mobile phone? Appl Cogn Psychol
2007; 21:527-537. [CrossRef]
29. Cao F, Su L, Liu T, Gao X. The relationship between impulsivity
and internet addiction in a sample of Chinese adolescents. Eur
Psychiatry 2007; 22:466-471. [CrossRef]
30. Savci M. Aysan, F. Relationship between impulsivity, social
media usage and loneliness. Educational Process: International
Journal 2016; 5:106-115. [CrossRef]
31. Bian M, Leung L. Linking loneliness, shyness, smartphone
addiction symptoms, and patterns of smartphone use to social
capital. Soc Sci Comput Rev 2014; 33:61-79. [CrossRef]
32. Bonetti L, Campbell MA, Gilmore L. The relationship of
loneliness and social anxiety with children’s and adolescents’
online communication. Cyberpsychol Behav Soc Netw 2010;
13;279-285. [CrossRef]
33. Bozoglan B, Demirer V, Sahin I. Loneliness, self-esteem, and life
satisfaction as predictors of internet addiction: a cross-sectional
study among Turkish university students. Scand J Psychol 2013;
54:313-319. [CrossRef]
34. van Rooij AJ, Schoenmakers TM, van den Eijnden RJ, Vermulst
AA, van de Mheen D. Video game addiction aest: validity and
psychometric characteristics. Cyberpsychol Behav Soc Netw
2012; 15:507-511. [CrossRef]
35. Espinoza G, Juvonen J. The pervasiveness, connectedness, and
intrusiveness of social network site use among young adolescents.
Cyberpsychol Behav Soc Netw 2011; 14:705-709. [CrossRef]
36. Lam LT. Internet gaming addiction, problematic use of the
Internet, and sleep problems: a systematic review. Curr
Psychiatry Rep 2014; 16:444. [CrossRef]
37. Brooks S. Does personal social media usage affect efficiency and
well-being? Comput Human Behav 2015; 46:26-37. [CrossRef]
38. Kardefelt-Winther D. The moderating role of psychosocial well-
being on the relationship between escapism and excessive online
gaming. Comput Human Behav 2014; 38:68-74. [CrossRef]
39. Wang L, Luo J, Bai Y, Kong J, Luo J, Gao W, Sun X. Internet addiction
of adolescents in China: Prevalence, predictors, and association with
well-being. Addict Res Theory 2013; 21:62-69. [CrossRef]
40. Ehrenberg A, Juckes S, White KM, Walsh SP. Personality and
self-esteem as predictors of young people’s technology use.
Cyberpsychol Behav 2008; 11:739-741. [CrossRef]
41. Wilson K, Fornasier S, White KM. Psychological predictors of
young adults’ use of social networking sites. Cyberpsychol
Behav Soc Netw 2010; 13:173-177. [CrossRef]
Savci M, Aysan F
215
Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
42. Kirschner PA, Karpinski AC. Facebook® and academic performance.
Comput Hum Behav 2010; 26:1237-1245. [CrossRef]
43. Samaha M, Hawi NS. Relationships among smartphone
addiction, stress, academic performance, and satisfaction with
life. Comput Human Behav 2016; 57:321-325. [CrossRef]
44. Stavropoulos V, Alexandraki K, Motti-Stefanidi F. Recognizing
internet addiction: prevalence and relationship to academic
achievement in adolescents enrolled in urban and rural Greek
high schools. J Adolesc 2013; 36:565-576. [CrossRef]
45. Kraut R, Kiesler S, Boneva B, Cummings J, Helgeson V,
Crawford A. Internet paradox revisited. J Soc Issues 2002; 58:49-
74. [CrossRef]
46. Lin SSJ, Tsai CC. Internet addiction among high schoolers in
Taiwan. 107th American Psychology Association (APA) Annual
Convention, Boston, Proceeding Book, 1999.
47. Parks MR, Roberts LD. `Making Moosic’: The development of
personal relationships on line and a comparison to their off-line
counterparts. J Soc Pers Relat 1998; 15:517-537. [CrossRef]
48. Ikiz FE, Savci M, Asici E, Yoruk C. Investigation of relationship
between problematic internet use and psychological symptoms
of university students. International Journal of Human Sciences
2015; 12:688-702. (Turkish) [CrossRef]
49. Grieve R, Indian M, Witteveen K, Anne Tolan G, Marrington J.
Face-to-face or Facebook: Can social connectedness be derived
online? Comput Human Behav 2013; 29:604-609. [CrossRef]
50. Quinn S, Oldmeadow JA. Is the igeneration a ‘we’ generation?
Social networking use among 9- to 13-year-olds and belonging.
Br J Dev Psychol 2013; 31:136-142. [CrossRef]
51. Davis K. Friendship 2.0: adolescents’ experiences of belonging and
self-disclosure online. J Adolesc 2012; 35:1527-1536. [CrossRef]
52. Hu M. Will online chat help alleviate mood loneliness?
Cyberpsychol Behav 2009; 12:219-223. [CrossRef]
53. Shen C, Williams D. Unpacking time online: Connecting internet
and massively multiplayer online game use with psychosocial
well-being. Communic Res 2010; 38:123-149. [CrossRef]
54. Valkenburg PM, Peter J. Social consequences of the Internet for
adolescents: A decade of research. Curr Dir Psychol Sci 2009;
18:1-5. [CrossRef]
55. Lee RM, Robbins SB. The relationship between social
connectedness and anxiety, self-esteem, and social identity. J
Couns Psychol 1998; 45:338-345. [CrossRef]
56. Moore TL. Social connectedness and social support of doctoral
students in counselor education. Doctoral Dissertation, Idaho
State University, Idaho, 2006.
57. Maslow AH. The Farther Reaches of Human Nature. New York:
Viking Press, 1971.
58. Chayko M. Techno-social life: The internet, digital technology,
and social connectedness. Sociol Compass 2014; 8:976-991.
[CrossRef]
59. Allen KA, Ryan T, Gray DL, McInerney DM, Waters L. Social
media use and social connectedness in adolescents: The positives
and the potential pitfalls. The Educational and Developmental
Psychologist 2014; 31:18-31. [CrossRef]
60. Mesch GS. Social relationships and Internet use among
adolescents in Israel. Soc Sci Q 2001; 82:329-339. [CrossRef]
61. McIntyre E, Wiener KKK, Saliba AJ. Compulsive Internet use
and relations between social connectedness, and introversion.
Comput Human Behav 2015; 48:569-574. [CrossRef]
62. Lee RM, Robbins SB. Measuring belongingness: The social
connectedness and the social assurance scales. J Couns Psychol
1995; 42:232-241. [CrossRef]
63. Valkenburg PM, Peter J. Online communication among
adolescents: an integrated model of its attraction, opportunities,
and risks. J Adolesc Health 2011; 48:121-127. [CrossRef]
64. Andreassen CS. Online social network site addiction: a
comprehensive review. Curr Addict Rep 2015; 2:175-184.
[CrossRef]
65. Yen JY, Ko CH, Yen CF, Chen SH, Chung WL, Chen CC.
Psychiatric symptoms in adolescents with Internet addiction:
Comparison with substance use. Psychiatry Clin Neurosci 2008;
62:9-16. [CrossRef]
66. Lee RM. The role of social connectedness in the social support
process and small group interactions. Doctoral Dissertation,
Virginia Commonwealth University, Virginia, 1996.
67. Kubey R, Csikszentmihalyi M. Television addiction is no mere
metaphor. Sci Am 2002; 286:74-80. [CrossRef]
68. Karadag E, Tosuntas SB, Erzen E, Duru P, Bostan N, Mizrak-
Sahin B, Culha I, Babadag, B. The virtual world’s current
addiction: phubbing. Addicta: The Turkish Journal on Addiction
2016; 3:223-269. (Turkish) [CrossRef]
69. Owens EW, Behun RJ, Manning JC, Reid RC. The impact of
internet pornography on adolescents: a review of the research.
Sex Addict Compulsivity 2012; 19:99-122. [CrossRef]
70. Dittmar H, Long K, Bond R. When a better self is only a button
click away: Associations between materialistic values, emotional
and identity-related buying motives, and compulsive buying
tendency online. J Soc Clin Psychol 2007; 26:334-361. [CrossRef]
Technological addictions and social connectedness: predictor effect of internet addiction, social media addiction, digital game ...
216 Dusunen Adam The Journal of Psychiatry and Neurological Sciences, Volume 30, Number 3, September 2017
71. Griffiths M. Sex on the Internet: observations and implications for
internet sex addiction. J Sex Res 2001; 38:333-342. [CrossRef]
72. Pawlikowski M, Altstötter-Gleich C, Brand M. Validation and
psychometric properties of a short version of Young’s Internet
Addiction Test. Comput Human Behav 2013; 29:1212-1223.
[CrossRef]
73. Kutlu M, Savci M, Demir Y, Aysan F. Turkish adaptation of
Young’s Internet Addiction Test-Short Form: a reliability and
validity study on university students and adolescents. Anadolu
Psikiyatri Derg 2015; 17(Suppl.1):69-76. (Turkish)
74. Savci M, Ercengiz M, Aysan F. Turkish adaptation of Social
Media Disorder Scale in adolescents. Arch Neuropsychiatry
2017, In press. (Turkish)
75. Irmak AY, Erdogan S. Validity and reliability of the Turkish
version of the Digital Game Addiction Scale. Anatolian Journal
of Psychiatry 2015; 16(Suppl.1):10-18. (Turkish)
76. Noyan CO, Darcin AE, Nurmedov S, Yilmaz O, Dilbaz N.
Validity and reliability of the Turkish version of the Smartphone
Addiction Scale-Short Version among university students.
Anadolu Psikiyatri Derg 2015; 16(Suppl.1):73-81. (Turkish)
77. Duru E. An adaptation study of Social Connectedness Scale in
Turkish Culture. Eurasian Journal of Educational Research 2007;
26:85-94. (Turkish)
78. Cokluk O, Sekercioglu G, Buyukozturk S. Multivariable SPSS
and LISREL applications for Social Sciences. Ankara: Pegem A
Publishing, 2012. (Turkish)
79. Bargh JA, McKenna KY. The internet and social life. Annu Rev
Psychol 2004; 55:573-590. [CrossRef]
80. Brown BB. Peer Groups and Peer Culture: In Feldman SSE, Elliott
GR. (Editors). At the Threshold: The Developing Adolescent.
Cambridge: Harvard University Press, 1990, 171-196.
81. Demir NO, Baran AG, Ulusoy D. Relations of adolescents with
their peer groups-friends in Ankara and deviated behaviors. Bilig/
Journal of Social Sciences of the Turkic World 2005; 32:83-108.
82. Karcher MJ. Connectedness and School Violence: A Framework
for Developmental İnterventions: In Gerler E (Editor). Handbook
of School Violence. Binghamton: Haworth Press, 2004, 7-42.
83. Kearney CJ. Friendship quality, Facebook and self-concept: Social
networking and adolescent development. Doctoral Dissertation,
Fairleigh Dickinson University, Teaneck, 2012.
84. Ogel K. Internet addiction, Understanding the psychology
of Internet and overcoming addiction. 2. Ed, Istanbul: Kultur
Publishing 2014. (Turkish)
85. Lee RM, Dean BL, Jung KR. Social connectedness, extraversion,
and subjective well-being: Testing a mediation model. Pers
Individ Dif 2008; 45:414-419. [CrossRef]
86. Zamani BE, Abedini Y, Kheradmand A. Internet addiction based
on personality characteristics of high school students in Kerman,
Iran. Addict Health 2011; 3:85-91.
87. Savci M, Aysan F. The role of attachment styles, peer relations,
and affections in predicting Internet addiction. Addicta: The
Turkish Journal on Addictions 2016; 3:401-432.
88. Rothschild LB. Facebook use and its relationship to social
connectedness and loneliness: The moderating role of social
skills. Master Dissertation, American University, Washington,
USA, 2015.
89. Saini VK, Baniya GC, Verma KK, Soni A, Kesharwani SK. A
study on relationship of facebook and game addictive behaviour
with personality traits among medical students. International
Journal Of Research In Medical Sciences 2016; 4:3492-3497.
[CrossRef]
90. Dalbudak E, Evren C. The relationship of internet addiction
severity with Attention Deficit Hyperactivity Disorder symptoms
in Turkish University students; impact of personality traits,
depression and anxiety. Compr Psychiatry 2014; 55:497-503.
[CrossRef]
91. Durak-Batigun A, Kilic N. The relationships between internet
addiction, social support, psychological symptoms and some
socio-demographical variables. Turkish Journal of Psychology
2011; 26:1-13. (Turkish)
92. Eksi F. Examination of Narcissistic Personality Traits’ Predicting
Level of Internet Addiction and Cyber Bullying through Path
Analysis. Educational Sciences: Theory & Practice 2012; 12:1683-
1706. (Turkish)
93. Demir Y, Kutlu M. The Relationship between loneliness and
depression: Mediation role of Internet addiction. Educational
Process: International Journal 2016; 5:97-105. [CrossRef]
94. Tas I, Ayas T. Relationship the level of internet addiction with
personality traits of high school students. International Journal of
Human Sciences 2015; 12:150-162. (Turkish) [CrossRef]
95. Savci M, Aysan F. Social-emotional model of Internet addiction.
Psychiatry and Clinical Psychopharmacology 2017; 1-10.
[CrossRef]
... Chou and Hsiao (25) determined that as adolescents use internet excessively, they became socially isolated and their peer relationships reduced. Savcı and Aysan (26) found in their study that peer relationships of adolescents were effective on internet addiction. Milani et al. (27) determined that weak interpersonal relationships were risk factors for increasing internet addiction. ...
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Aim: This study is aimed at determining the effect of peer relationships on smartphone addiction among adolescents. Material and Method: This cross-sectional study’s population was composed of students in the high schools of the Directorate of National Education in the city center of Batman province. For the sample, three high schools (3000 students) were selected by using the method of drawing lots in terms of the student intensity from the Provincial Directorate for National Education. The sample size was calculated as 707 students based on the power analysis. In the study, “Introductory Information Form”, “Peer Relationship Scale”, and “Smartphone Addiction Scale” were used. The data collection process took place between May 2018 and June 2018. Percentage distribution, mean, independent samples t-test, analysis of variance, Kruskal-Wallis and regression analysis were employed to assess the data. Results: The participants’ total mean scores were 45.61±11.93 in Peer Relationship Scale and 28.93±12.61 in Smartphone Addiction Scale. Peer relationships of the adolescents influenced smartphone addiction at the rate of 38% (p˂0.05). Conclusion and Recommendations: It was concluded that peer relationships and smartphone addictions of the adolescents were moderate. Peer relationships of the adolescents affected smartphone addition. In the study, it is recommended to inform the students and to organize trainings by the psychiatric nurses to increase the peer relationships of adolescents and decrease their smartphone addiction.
... Internet addiction is the umbrella term of the other internet related addictions like social media addiction (Savci & Aysan, 2017). In the literature, it was found that internet addiction leads to deprivation and withdrawal symptoms like substance and drug addiction, and it also causes some functional failures not only in work but also in family lives (Young, 1998). ...
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With the acceleration of internet use, social media addiction is included in our lives. When looking at the antecedents of SMA, being young has been found to be a risk factor for SMA. It is more important to investigate the effects of SMA on adolescents because, in addition to being in the risk group, adolescents adopt the latest technologies more easily and they are vulnerable to the negative effects of these technologies. The internet is not always used for "innocent" purposes such as self-entertainment or getting information; sometimes it can also be used for malicious purposes, such as humiliating or bullying others. In addition to the benefits of technological advances in education and training, rapid technological developments may also result in problematic behaviors especially among children and young and recently, possibilities brought by technology and more widespread use of technology by young people have created a new concept, namely, cyberbullying, which expands the concept of traditional bullying and that includes using technology for bullying others. The aim of the present study is to examine the effects of attachment anxiety and attachment avoidance on SMA and cyberbullying as distal outcome variables and partial mediating effects of the Dark Triad (DT) personality v traits, angry rejection sensitivity (RS) and anxious RS, and friendship quality in the links of attachment anxiety and avoidance among adolescences. In general, the findings supported the proposed theoretical model. The findings revealed that attachment anxiety was found to be a significant predictor of SMA among adolescent sample. The effect of attachment anxiety on cyberbullying was found to be insignificant. However, angry RS and anxious RS mediated the link between attachment anxiety and cyberbullying. Angry and anxious RS also fully mediated the link between attachment anxiety and friendship quality. The association between attachment avoidance and cyberbullying was mediated by psychopathy. Machiavellianism and psychopathy partially mediated the link between attachment avoidance and friendship quality. The results are discussed in terms of theoretical and practical implications along with suggestions for future research.
... Studies have shown that individuals with low social connectedness, underlying psychopathologies, and psychological distress (Anderson et al., 2017;Kraut & Burke, 2015;Quesnel et al., 2017) use the Internet as a way of distracting themselves from their psychological challenges or as compensation for an unmet need for connection (McIntrye et al., 2015;Meerkerk, 2007;Gentzler et al., 2011;Kraut & Burke, 2015;Quesnel et al., 2017;Romano et al., 2013;Kardefelt-Winther, 2014;Schimmenti & Caretti, 2010). Those lacking social connection often report experiences of withdrawal symptoms when Internet use declines (Li & Chung, 2006;Nichols & Nicki, 2004) which leads individuals to require greater and continuous amounts of Internet use (Yellowlees & Marks, 2007); While it may appear that increased usage are attempts at seeking connection, excessive use of the Internet to address low social connectedness only serves to perpetuate low social connectedness (Savci & Aysan, 2017). ...
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The prevalence of problematic Internet use (PIU) and its associated negative outcomes among college students has been heavily researched in developed countries. However, despite the increased accessibility of the Internet and indicators which may suggest PIU in developing countries such as Jamaica, PIU in this context remains grossly understudied. This study surveyed 277 Jamaican university students and found evidence of PIU, with younger respondents (ages 18–23) at risk. The findings also indicate that the predictors of PIU in this sample are depressive symptomatology, avoidant-attachment, and low social connectedness (R² = .208, F[7, 269] = 10.112, p < .001). Findings from the current study highlight that problematic Internet use is of concern in this developing context and warrants further exploration.
... Bunun yanında eğlence, rekabet, başka bir etkinliğin olmaması, sosyalleşme, hayal ortamı oluşturma, bulunulan zaman ve mekandan kaçma gibi nedenler de sıralanabilir (9). Kontrolsüz ve uzun zaman oynanan dijital oyunlar çocuk ve ergenlerin uyku alışkanlıklarının değişmesine, olumsuz alışkanlıklar kazanmalarına neden olmaktadır (7,10). Yapılan çalışmalar ergenlerin uyku ihtiyaçlarının yeterli düzeyde ve yeterli kalitede karşılanamamasında dijital oyunlar oynama, bilgisayar, akıllı telefon, tablet ve televizyon izleme alışkanlıkları gibi çevresel nedenlerin önemli yeri olduğu belirtilmektedir (11). ...
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... It is well documented in previous literature that SNSs addiction or problematic use of SNSs is associated with a number of negative physiological, social and psychological factors such as poor life satisfaction [30,31], lower psychological well-being [30][31][32], health [15,33], sleep problems [34], social connectedness [35], social anxiety and higher depression [31], and loneliness [36]. However, the above-mentioned studies either focused on SNSs in general or they specifically focused on SNSs such as Twitter and Facebook. ...
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