Internet Addiction: A
Literature Review
Laura Ann Collins
Northcentral
University
Abstract
From 2000 to 2015, global internet
usage has increased from 400 million users to an estimated 3.2 billion users (ICT Data and
Statistics Division, 2015) . By the end of 2015, the ICT estimates that
there will be over 7 billion cellular phone subscriptions (ICT Data and Statistics Division, 2015) . As the trend of internet connectivity is
unlikely to reverse, understanding how internet usage fits into peoples’ lives
has become of increasing interest. Since
1995, when the term internet addiction (IA) started emerging (Hsu, Lin, Chang, Tseng, & Chiu, 2015; Young, In
Press), questions have arisen about what is adaptive use versus
maladaptive use of internet. While Cheng
and Li (2014) found “considerable” national variance in prevalence of IA, the
results of their research yielded a global prevalence estimate of 6.0% of IA
among internet users. As IA is still an
emerging disorder, controversy about what exactly IA is and is not continues to
impede progress toward detecting and treating IA. With such a significant possible impact, it
is essential that researchers solidify the conceptualization of IA. Through a brief literature review, the author
surveys several types of IA studies in order to illuminate why lack of
conceptualization hinders development of research for the field of IA.
Keywords: IA,
Internet Usage, Internet Addiction, pathological internet use, definition,
problematic internet use
Internet
Addiction: A Literature Review
In 1995, Ivan Goldberg suggested IA might be an items of
clinical significance (Hsu et al., 2015)
and Kimberly Young (In Press) started exploring what she called “a pet project”
about possible negative consequences of internet use. Since 1995, researchers have developed a
plethora of information about problems which may occur through internet usage. Young (In Press) traced the evolution of the
concept of IA as indicated in Figure 1.
Laconi, Tricard, and Chabrol (2015) discussed a few other aspects of the
evolution of the concept of IA (also included in Figure 1) in the introduction
to their study. Their additions will be
discussed later in this review. The
terms used to describe problematic internet usage have included internet
addiction (IA), problematic internet use (PIU) which may be generalized (GPIU)
or specialized (SPIU), pathological internet use, excessive internet use,
cyberaddiction, internet addiction disorder, compulsive internet use, internet
addiction disorder (IAD), etc. When
reading through studies on extent of internet use, the term used to describe
the phenomenon seems to indicate the point of view from which the researcher
evaluates and quantifies internet use.
The World Health Organization estimates that mood disorders
affect 350 million people, bipolar disorder affects 60 million people,
schizophrenia and psychotic disorders affect 21 million people, and dementia
affects 47.5 million people (Mental Disorders,
2015). Combining statistics from
the International Telecommunications Union (an agency of The United Nations) that
there are 3.2 billion internet users and the research from Cheng and Li (2014)
which identified 6% percent of global internet users as experiencing IA, then 192
million peoples’ lives may be adversely impacted by IA. Therefore, IA for
internet users, a disorder which has only been possible since the early 1980’s,
may impact more people than bipolar disorder, dementia, and the psychotic
disorders combined.
If cellular phone subscribers also have potential for IA,
then an additional 7 billion people are at risk. With 6% prevalence, then 420 million people
may experience IA – 70 more million people than those that experience mood
disorders. However, without data to
validate or refute that cellular phone users are as at risk of IA as internet
users, the application of Cheng and Li’s (2104) 6% global prevalence statistic
may not be appropriate. Scenarios such
as this illustrate why solid
conceptualization of the disorder and careful definition of IA is so necessary.
In order to illuminate how the lack of a gold standard
conceptualization (and thereby definition of IA) impacts understanding, the
studies were grouped by stated or implied cause of internet use. To keep this paper brief, only a few studies
were used in each group. The first group
of studies includes those which define PIU as an addiction, just as there are
substance addictions and behavioral addictions.
The second group of studies contains those which suggest PIU is a
symptom of some other psychopathology. The
third group includes studies which suggest PIU is not a pathological disorder,
but is instead a coping skill, albeit a maladaptive one. The final
group includes studies which suggest PIU is not a pathological disorder, but is
instead a manifestation of a learning curve related to the introduction of the
internet into daily life.
Method
The studies by Kuss, Shorter,
van Rooij, Griffiths, and Schoenmakers (2014); Lee, et al. (2012) and Lortie and Guitton (2013) were the
first three studied considered for this review.
These studies were assigned reading for the Northcentral University
class PSY7102: Scholarly Writing and Professional Communication in
Psychology. The other studies were
identified through searching Roadrunner database using keywords: internet
addiction, IA, pathological internet use, and internet addiction disorder. Brief descriptions for studies were browsed
in order to determine articles of interest.
To be considered, studies had to be from peer-reviewed journal articles
with full text available online, written in English, written within the last 5
years (unless seminal work), and pertaining to conceptualization or definition
of IA/PIU. Abstracts for over 100
studies were read.
Thirty-two studies were selected as possibly pertinent and
were read in their entirety (for a complete list of studies which were read see
Table 1). The studies were grouped by
their relevance to IA/PIU, resulting in the following groups: prevalence &
comorbidity, factors, definition of IA, and tools & assessments (Table
1). Through reading the studies, the
theme of need for consensus regarding theoretical base and definition of IA
became obvious. That 20 years of
research has not yielded either a gold standard for definition or a theory by
which a predictive model of IA can be constructed is a significant concern to
most researchers.
As this was the most common theme, the 32 studies were
grouped through stated or implied cause(s) of IA in an attempt to understand
what theories exist to explain IA/PIU. In
order to keep this review to brief length, the most relevant of the studies
were divided into the following groups:
group 1 (addiction), group 2 (symptom), group 3 (coping skills), and
group 4 (learning curve).
Possible Theories/Etiology
Is PIU an addiction?
In 1995, when Young developed the concept of IA, she
utilized the criteria for addictions set forth by the American Psychological
Association, changing the terms related to the addiction to apply to online
activities or internet addiction (OReilly, 1996) .
Since 1995, there has been significant amounts of research attempting to
validate that IA is, indeed, an addiction.
Douglas et al. (2008) completed a qualitative meta-synthesis of studies
from 1996 to 2006 in order to identify the aspects which combine to create
IA. They found that persons with IA
utilized the internet at least 8 times as much as persons not experiencing
IA. Douglas et al. (2008) created a
model of IA in which the addiction is developed from a complex interplay
between personal factors (such as self-esteem), push factors (things which
drive an individual to use the internet, like development of a social group),
negative effects (such as academic difficulty), deviant behaviors (such as
accessing child pornography), and control strategies (such as participating in
non-online activities). They suggested
that the most pressing need was for “development of IAD theory” (Douglas et
al., 2008, p. 3042).
Hsu et al. (2015) asked “20 psychiatrist specialists” to
examine an internet addiction assessment tool widely used in Taiwan, the
diagnostic criteria for internet addiction for adolescents (DC-IA-A). Their results showed that “characteristic
symptoms, functional impairment, and exclusion criteria” were agreed upon as
significant to IA (Hsu et al., 2015, p. 506).
Like Douglas et al. (2008), Hsu et al. identified symptoms of PIU and
conceptualized it as an addiction.
Neither Douglas et al. nor Hsu et al. identified clear theory of how IA
might originate.
Brand, Young, and Laier (2014) reviewed selected published
reviews and research articles discussing the convergence of PIU and
neuroimaging/neuropsychology. Their
review highlighted similarities in brain function and structure between persons
who have behavioral/substance addictions and persons who exhibited PIU. The structural and functional brain changes
occurred in areas which are implicated in executive functioning and in
impulsivity (cue-reactivity).
Lortie and Guitton (2013) suggested that IA is like other
addictions in that biochemical and neurological changes evidenced in persons
exhibiting symptoms of IA are similar to those seen in other forms of addiction
and dependence. They defined
“dysfunctional internet use” as use which had characteristics of tolerance,
loss of sense of time, increased real-life isolation, and negative real-life
consequences (Lortie & Guitton, 2013) . Brand et al. (2014) state “Most of the
current articles on neuropsychological and neuroimaging correlates of Internet
addiction conclude that this clinically relevant disorder should be classified
as a behavioral addiction. We agree…”
(p.10).
Lee et al. (2012) examined how IA compared with pathological
gambling. They determined that
impulsivity, which is related to both substance addictions and behavioral
addictions (such as pathological gambling), is also related IA. Lee et al. (2012) noted that abnormalities in
brain function in areas related to impulse control of persons exhibiting IA
which are similar to those of persons with addictions and/or with impulse
control disorders.
Lee et al. (2012) controlled for comorbid depression and
anxiety, and found that impulsivity is still increased in persons exhibiting
IA. Lee et al. (2012) defined IA is “an
inability to control Internet use, [which] can lead to serious impairment in
psychological and social functioning” (p. 373) and therefore, concluded that
“Internet addiction can be conceptualized as an impulse control disorder and
that trait impulsivity is a marker for vulnerability to develop Internet
addiction” (p. 376).
If PIU is considered
an addiction, the evidence supporting this includes brain imaging which shows
similarities between the brains of persons with PIU and of persons with
substance/behavioral addictions.
Symptoms for IA and for other addictions seem to be similar –
impulsivity, tolerance, negative effects, denial, etc. Since Young’s beginning research in 1996, the
predominant view has been that PIU is an addiction (Suissa, 2014) .
Is PIU a symptom of an underlying psychopathology?
PIU has been identified as being comorbid with multiple
other pathological disorders. Ko et al.
(2012) completed a literature review which found IA to be “associated with
substance use disorder, ADHD, depressive disorder, social phobia, and
hostility” (p. 6). However, Ho et al.
(2014) states the Ko et al. review “lacked statistical analyses to support such
associations” (para 2). Ho et al. (2014)
completed a meta-analysis utilizing robust statistical procedures to evaluate
studies in order to determine comorbidity between IA and other
psychopathologies. Ho et al. (2014)
found IA was often (in 20-30% of patients) comorbid with alcohol abuse, ADHD,
depression, and anxiety. Of significant
interest is that Ho et al. (2014) suggest the comorbidity may result due to
possible genetic coding of serotonin receptors.
Also of interest is that Ho et al. (2014) discuss environmental
stressors, gender, and interpersonal relationship styles as possible
confounding items.
Laconi et al. (2015) noted the controversy regarding the
term IA and chose to use the less controversial term problematic internet use
(PIU). They then researched the
difference between generalized PIU (GPIU) and specific PIU (SPIU). SPIUs were differentiated into 8
subtypes: gaming, gambling, sex, online
workaholism, shopping, information seeking, online communication, and
video/music listening and/or watching.
Laconi et al. (2015) conceptualized GPIU as addiction to the internet, while each SPIU was
conceptualized as an addiction to that activity which then occurred via the
venue of the internet. In other words,
GPIU was addiction to the computer itself – the ability to use the
internet. SPIUs were addictions to
working too much, to shopping, to gambling, etc. for which the internet was a
convenient way to carry out addictive activities. This conceptualization was reinforced by the
results of Pontes, Szabo, and Griffiths (2015) whose research results showed
that internet users have specific purpose to their internet activities such
that “in case of being prevented from accessing their favorite activities, they
would then either completely stop using the Internet and/or significantly
reduce their weekly time spent online” (p. 23)
Is PIU a coping skill?
Cheng and Li (2014) completed a meta-analysis of internet
addiction as evidenced by people in 31 different nations and 7 different world
regions. They adopted the definition and
conceptualization of IA created by Young.
Eighty reports met criteria for inclusion. They found an average IA global prevalence
rate of 6.0%. Cheng and Li (2014) also
found that prevalence varied with environmental quality. For countries with increased traffic commute
times and increased levels of air pollution, there is an increase in prevalence
of IA. Cheng and Li (2014) suggested
that increased internet use results from increased stress and decreased
opportunity to engage in outdoor activities.
Kardefelt-Winther (2015) developed a model of PIU which
suggested that PIU is “a reaction by the individual to his negative life
situation, facilitated by an internet application” (p. 352). In Kardefelt-Winther’s model, the individual
who feels some lack in his or her life “self-medicates” through internet use. For example, the person who is lonely and
lacks social skills may enter a chat room or develop an avatar which does not
possess the social deficits of the real person.
Kardefelt-Winther (2015) stated that it is also possible that the
symptoms of internet addiction can “be interpreted as a normative shift in how
younger generations entertain or communicate” (p. 353) and as a function of the
ubiquitousness of the internet in everyday life. Kardefelt-Winther (2015) suggested that
considering why a person uses the
internet is the missing piece which explains the lack of theory development for
IA even through there have been significant amounts of data collected through a
plethora of research.
Is PIU a learning curve?
The internet seems to exist between food and
gambling/substance use with respect to the option to choose exposure. Connectivity is becoming part of daily life
for many of the global citizens, much as food is a daily part of life. Of course, one does not die without a certain
amount of internet use. However,
internet use is not as optional as gambling or substance use would be. The world is moving toward a digital society
with information and communication technologies being significant drivers of
global change (ICT Data and Statistics Division, 2015) . If one considers that the internet is a
relatively new aspect of human life (say compared to telephones or letters),
then it is possible that humans are in a period of learning to utilize this new
resource.
Wasinski and Tomczyk (2015)
defined IA as “a specific state of mind in which addicted individuals lose
their grasp of their real existence…. [with] them being deeply intellectually
and emotionally absorbed by the virtual world” (p. 68). Wasinski and Tomczyk evaluated data from the
EU Kids Online Study in their research and determined that parental attitudes
and actions regarding implemenation of boundaries for their childrens’ internet
usage is a protective factor against development of IA.
Suissa (2104) suggested that when consideration of the
pervasiveness of internet use in modern life is introduced to the discussion,
it then becomes essential to distinguish from use and abuse of the
internet. Suissa inquired if the medical
model of IA is appropriate and suggested that psychoeducation and
skills-training might prevent IA from occurring. Suissa posited that IA cannot be separated
from the sociological context of the society in which the individual is
embedded.
Considering Wasinski and Tomczyk’s (2015) and Suissa’s
(2014) research, IA could be considered as a lack of societal regulation
regarding proper utilization the resource of the internet and on proper
integration of internet use into “real” life activities. Inaba and Cohen (2011) stated that
societies utilize norms and laws to control the amount of substance use and
that these regulating factors have developed over generations. In the case of internet use, there have not
been generations of individuals who have practiced with the internet enough for
regulations to develop.
Discussion
Why do conceptualization and definition matter? The way researchers conceptualize a topic
impacts the questions that are posed about the topic. For example, when the assumption is that
something is medically wrong, then societal factors may not be considered. If IA is a brain disease, then the levels of
air pollution or the amount of time spent on commuting may not be considered as
part of the disorder. Conversely, if IA
is considered a stress response, then brain abnormalities or genetic susceptibility
may not be investigated.
Definition matters because it is through definition that
researchers create hierarchies of acceptable, excessive, and pathological. The individual who spends 35 hours per week
on the internet because he is a media consultant may have a very different
diagnosis than the individual who spends 35 hours per week on Facebook. However, neither individual may be addicted…
or one may be addicted… or both may be addicted. Context, variables, and criteria all are
components of definition.
Conclusion
At this point, there is consensus that some individuals
experience negative consequences from their utilization of the internet. There is consensus that the brain imagery of
some individuals who evidence negative patterns of internet use have some
similarities to the brain imagery of individuals who are diagnosed with other
types of addiction. There is consensus
that a primary need in the still young field of problematic internet usage is
development of a theory driven conceptualization of PIU which then generates a
predictive model and a gold standard definition.
However, as Kardefelt-Winther (2015) stated, “Considering
the amounts of data that have been collected and the efforts made, the lack of
progress indicates that there are issues somewhere along the way that makes
theoretical development difficult” (p. 352).
Kardefelt-Winther called for a re-evaluation of what type of explanations researchers are
seeking. Burnay et al. (2015) found
that 36.6% of internet addiction symptoms was validated by their model of
“urgency, lack of perseverance, obsessive passion, depression, and age”
(p.32). They note that factors
responsible for 63.4% of IA variance are yet to be determined.
Perhaps a simple
step towards reconciling the data points represented by the multitude of
studies would be to separate addictions to the internet from addictions to
other things which use the vehicle of the internet. If addiction to the internet is determined to
exist as a separate entity, then the nest step might be to identify a holistic
frame through which to view IA. This
might then produce a theory which integrates strands of both nature and nurture
to create a predictive model. Until the
data is woven into a cohesive model, research may generate data, but is likely
to continue to fail at explaining origin or predicting occurrence of IA.
References
Brand, M., Young, K. S., & Laier, C. (2014).
Prefrontal control and internet addiction: A theoretical model and review of
neuropsychological and neuroimagining findings. Frontiers in Human
Neuroscience, 8, Article 8, pp 1-13. doi: 10.3389/fnhum.2014.00275.
Burnay, J., Billieux, J., Blairy, S., & Laroi,
F. (2015). Which psychological factors influence internet addiction? Evidence
through an integrative model. Computers in Human Behavior, 43, 28-34.
doi: 10.1016/j.chb.2014.10.039.
Cheng, C., & Li, A. Y.-I. (2014). Internet
addiction prevalence and quality of (real) life: A meta-analysis of 31
nations across seven world regions. Cyberpsychology, Behavior, and Social
Networking, 17(12), 755-760. doi: 10.1089/cyber.2014.0317.
Douglas, A. C., Milles, J. E., Niang, M.,
Stepchenkova, S., Byun, S., Ruffini, C., . . . Blanton, M. (2008). Internet
addiction: Meta-synthesis of qualitative research for the decade 1996-2006. Computers
in Human Behavior, 24, 3027-3044, doi: 10.1016/j.chb.2008.05.009.
Ho, R. C., Zhang, M. W., Tsang, T. Y., Toh, A. H.,
Pan, F., Lu, Y., . . . Mak, H.-K. (2014). The association between internet
addiction and psychiatric co-morbidity: A meta-analysis. BMC Psychiatry,
14, n.p. doi: 10.1186/1471-244X-14-83.
Hsu, W.-Y., Lin, S. S., Chang, S.-M., Tseng, Y.-H.,
& Chiu, N.-Y. (2015). Examining the diagnostic criteria for internet
addiction: Expert validation. Journal of the Formosan Medical Association,
114, 504-508. doi: 10.1016/j.jfma.2014.03.010.
ICT Data and Statistics Division. (2015, May). ICT
facts & figures. Retrieved from International Telecommunication
Union: Retrieved from the International Telecommunication Union:
https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2015.pdf
ICT Data and Statistics Division. (2015, May). ICT
facts & figures. Retrieved from International Telecommunication
Union: Retrieved from the International Telecommunication Union at
https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2015.pdf
Inaba, D. S., & Cohen, W. E. (2011). Uppers,
downers, all arounders: Physical and mental effects of psychoactive drugs
[7th. ed.]. Medford, OR: CSN Productions, Inc.
Kardefelt-Winther, D. (2014). A conceptual and
methodological critique of internet addiction research: Towards a model of
compensatory internet use. Computers in Human Behavior, 31, 351-354.
doi: 10.1016/j.chb.2013.10.059.
Ko, C.-H., Yen, J.-Y., Yen, C.-F., Chen, C.-S.,
& Chen, C.-C. (2012). The association between internet addiction and
psychiatric disorder: A review of the literature. European Psychiatry, 27,
1-8. doi: 10.1016/j.eurpsy.2010.04.011.
Kuss, D. J., Shorter, G. W., van Rooij, A. J.,
Griffiths, M. D., & Schoenmakers, T. M. (2014). Assessing internet
addiction using the parsimonious internet addiction components model - A preliminary
study. 12. International Journal of Mental Health Addiction, 351-366.
doi:10.1007/s11469-013-9459-9.
Laconi, S., Rodgers, R., & Chabrol, H. (2014).
The measurement of internet addiction: A critical review of existing scales
and their psychometric properties. Computers in Human Behavior, 41,
190-202. doi: 10.1016/j.chb.2015.04.056.
Laconi, S., Tricard, N., & Chabrol, H. (2015).
Differences between specific and generalized problematic internet uses
according to gender, age, time spent online and psychopathological symptoms. Computers
in Human Behavior, 48, 236-244. doi: 10.1016/j.chb.2015.02.006.
Lee, H., Choi, J.-S., Shin, Y.-C., Lee, J.-Y., Jung,
H., & Kwon, J. (2012). Impulsivity in internet addiction: A comparison
with pathological gambling. Cyberpsychology, Behavior, and Social
Networking, 15(7), 373-377. doi: 10.1089/cyber.2012.0063.
Lortie, C. L., & Guitton, M. J. (2013). Internet
addiction assessment tools: Dimensional structure and methodological status. Addiction,
108, 1207-1216. doi: 10.1111/add.12202.
Mental Disorders. (2015, October). Mental
disorders (Fact sheet N°396). Retrieved from World Health Organization:
http://www.who.int/mediacentre/factsheets/fs396/en/#
Milani, L., Osualdella, D., & Di Blasio, P.
(2009). Quality of interpersonal relationships and problematic internet use
in adolescence. CyberPsychology and Behavior, 12(6), 681-684.
OReilly, M. (1996). Internet addiction: A new
disorder enters the medical lexicon. CMAJ: Canadian Medical Association
Journal = Journal De L'association Medicale Canadienne.154(12),
1882-1883. Retrieved from:
http://eds.b.ebscohost.com.proxy1.ncu.edu/eds/pdfviewer/pdfviewer?sid=b245519e-13aa-4839-8337-d5af81b43fd0%40sessionmgr112&vid=3&hid=117.
Pontes, H. M., Szabo, A., & Griffiths, M. D.
(2015). The impact of internet-based specific activities on the perceptions
of internet addiction, quality of life, and excessive usage: A
cross-sectional study. Addictive Behaviors Reports, 1, 19-25. doi:
10.1016/j.abrep.2015.03.002.
Sariyask, R., Reuter, M., Bey, K., Sha, P., Li, M.,
Chen, Y.-F., . . . Montag, C. (2014). Self-esteem, personality, and Internet
addiction: A cross-cultural comparison study. Personality and Individual
Differences, 61-62, 28-33. doi: 10.1016/j.paid.2014.01.001.
Siomos, K., Floros, G., Makris, E., Christou, G.,
& Hadjulis, M. (2014). Internet addiction and psychopathology in a
community before and during an economic crisis. Epideomiology and
Psychiatric Sciences, 23, 301-310. doi: 10.1017/S2045796013000437.
Suissa, A. J. (2014). Cyberaddictions: Toward a
psychosocial perspective. Addictive Behaviors, 39, 1914-1918. doi:
10.1016/j.addbeh.2014.07.027.
Wasinski, A., & Tomczyk, L. (2015). Factors
reducing the risk of internet addiction in young people in their home
enviornment. Children and Youth Services Review, 57, 68-74. doi:
10.1016/childyouth.2015.07.022.
Young, K. (2013). Retrieved from Center for Internet
Addiction: http://netaddiction.com/
Young, K. (In Press). The evolution of internet
addiction. Addictive Behaviors, doi: 10.1016/j.addbeh.2015.05.016.
Appendix A:
FIGURE
1: Evolution of Internet Addiction
-
1998
-1st study of IA by Kimberly Young is published1
-
1999
– Research and Publications by “early pioneers” David Greenfield and Marissa
Hecht Orzack1
-
Early
2000s – China, Korea, and Taiwan –
publication of studies on IA1
-
2000
– IA is subdivided into types:
Cybersexual, Cyber-relationship, Compulsive (gambling, shopping,
trading), Information, Gaming[2]
-
2001
– Two categories of problematic internet use:
Specific Problematic Internet Use (SPIU) and Generalized Problematic
Internet Use (GPIU). SPIU is subdivided
into types and “could be considered addictions on the internet” while GPIU is “addiction to the internet”[3] [italics added].
-
2006
– 1st inpatient IA treatment center – Beijing China1
-
Late
2000s – Several Asian Cultures developed comprehensive prevention programs1
-
Late
2000s – New statistical models emerged which identified factors/components1
-
2103
– Development of Internet Addiction Gaming Disorder1
-
2013
– IA Inpatient Treatment Center in Pennsylvania1
-
2014
– American Academy of Pediatrics recommends no media access for children under
21
-
2015
– IA continues to be a disputed term. Problematic
Internet Use is gaining popularity in literature as a descriptive term.2
-
2015
– Laconi, Ticard & Chabrol suggested that each type of SPIU should be
researched individually as well as part of overarching problematic internet
use.2
TABLE 1: STUDIES
READ IN ENTIRETY
Author(s) & Date
|
Relevance to Literature Review
|
Adiele & Olatokun, 2014
|
Prevalence & Comorbidity
|
Brand, Young, & Laier,
2014
|
Models & Conceptualization
|
Burnay, Billieux, Blairy,
& Laroi, 2015
|
Models & Conceptualization
|
Cheng & Li, 2014
|
Prevalence & Comorbidity
|
Dhir, Chen, & Nieminen,
2014
|
Factors
|
Douglas, et al., 2008
|
Definition of IA
|
Floros, Siomos,
Stogiannidou, Giouzepas, & Garyfallos, 2014a
|
Prevalence & Comorbidity
|
Floros, Siomos,
Stogiannidou, Giouzepas, & Garyfallos, 2014b
|
Prevalence & Comorbidity
|
Ho, et al., 2014
|
Prevalence & Comorbidity
|
Hsu, Lin, Chang, Tseng,
& Chiu, 2015
|
Definition of IA
|
Kardefelt-Winther, 2014
|
Models & Conceptualization
|
Kim, Park, Ryu, Yu, &
Ha, 2013
|
Tools & Assessments
|
Ko, Yen, Yen, Chen, & Chen,
2012
|
Prevalence & Comorbidity
|
Kuss, Shorter, van Rooij,
Griffiths, & Schoenmakers, 2014
|
Models & Conceptualization
|
Kuss, Shorter, van Rooij,
van de Mheen, & Griffiths, 2014
|
Models & Conceptualization
|
Laconi, Rodgers, &
Chabrol, 2014
|
Tools & Assessments
|
Laconi, Tricard, &
Chabrol, 2015
|
Definition of IA
|
Lee, et al., 2012
|
Factors
|
Lortie & Guitton, 2013
|
Tools & Assessments
|
Milani, Osualdella, & Di
Blasio, 2009
|
Factors
|
OReilly, 1996
|
Definition of IA
|
Pontes, Szabo, &
Griffiths, 2015
|
Factors
|
Saliceti, 2015
|
Definition of IA
|
Sariyask, et al., 2014
|
Prevalence & Comorbidity
|
Siomos, Floros, Makris,
Christou, & Hadjulis, 2014
|
Prevalence & Comorbidity
|
Suissa, 2014
|
Models & Conceptualization
|
Wasinski & Tomczyk, 2015
|
Factors
|
Widyanto, Griffiths, &
Brunsden, 2011
|
Tools & Assessments
|
Yang, et al., 2014
|
Factors
|
Young, 2013
|
Definition of IA
|
Young, In Press
|
Definition of IA
|
Zhang & Xin, 2013
|
Tools & Assessments
|
References:
Table 1
Adiele, I., & Olatokun, W. (2014). Prevalence
and determinants of internet addiction among adolescents. Computers in
Human Behavior, 31, 100-110. doi: 10.1016/j.chb.2013.10.028.
Brand, M., Young, K. S., & Laier, C. (2014).
Prefrontal control and internet addiction: A theoretical model and review of
neuropsychological and neuroimagining findings. Frontiers in Human
Neuroscience, 8, Article 8, pp 1-13. doi: 10.3389/fnhum.2014.00275.
Burnay, J., Billieux, J., Blairy, S., & Laroi,
F. (2015). Which psychological factors influence internet addiction? Evidence
through an integrative model. Computers in Human Behavior, 43, 28-34.
doi: 10.1016/j.chb.2014.10.039.
Cheng, C., & Li, A. Y.-I. (2014). Internet
addiction prevalence and quality of (real) life: A meta-analysis of 31
nations across seven world regions. Cyberpsychology, Behavior, and Social
Networking, 17(12), 755-760. doi: 10.1089/cyber.2014.0317.
Dhir, A., Chen, S., & Nieminen, M. (2014).
Predicting adolescent internet addiction: The roles of demographics, technology
accessibility, unwillingness to communicate and sought internet
gratifications. Computers in Human Behavior, 51, 24-33. doi:
10.1016/j.chb.2015.04.056.
Douglas, A. C., Milles, J. E., Niang, M.,
Stepchenkova, S., Byun, S., Ruffini, C., . . . Blanton, M. (2008). Internet
addiction: Meta-synthesis of qualitative research for the decade 1996-2006. Computers
in Human Behavior, 24, 3027-3044, doi: 10.1016/j.chb.2008.05.009.
Floros, G., Siomos, K., Stogiannidou, A., Giouzepas,
I., & Garyfallos, G. (2014a). Comorbidity of psychiatric disorders with
internet addition in a clinical sample: The effect of personality, defense
style and psychopathology. Addictive Behaviors, 39, 1839-1845. doi:
10.1016/j.addbeh.2014.07.031.
Floros, G., Siomos, K., Stogiannidou, A., Giouzepas,
I., & Garyfallos, G. (2014b). The relationship between personality,
defense styles, internet addiction disorder, and psychopathology in college
students. Cyberypsychology, Behavior, and Social Networking, 17(10),
672-676. doi: 10-1089/cyber.2014.0182.
Ho, R. C., Zhang, M. W., Tsang, T. Y., Toh, A. H.,
Pan, F., Lu, Y., . . . Mak, H.-K. (2014). The association between internet
addiction and psychiatric co-morbidity: A meta-analysis. BMC Psychiatry,
14, n.p. doi: 10.1186/1471-244X-14-83.
Hsu, W.-Y., Lin, S. S., Chang, S.-M., Tseng, Y.-H.,
& Chiu, N.-Y. (2015). Examining the diagnostic criteria for internet
addiction: Expert validation. Journal of the Formosan Medical Association,
114, 504-508. doi: 10.1016/j.jfma.2014.03.010.
Kardefelt-Winther, D. (2014). A conceptual and
methodological critique of internet addiction research: Towards a model of
compensatory internet use. Computers in Human Behavior, 31, 351-354.
doi: 10.1016/j.chb.2013.10.059.
Kim, S. J., Park, D.-H., Ryu, S.-H., Yu, J., &
Ha, J. J. (2013). Usefulness of Young's internet addiction test for clinical
populations. Nordic Journal of Psychiatry, 67(6), 393-399. doi:
10.3109/08039488.2012.748826.
Ko, C.-H., Yen, J.-Y., Yen, C.-F., Chen, C.-S.,
& Chen, C.-C. (2012). The association between internet addiction and
psychiatric disorder: A review of the literature. European Psychiatry, 27,
1-8. doi: 10.1016/j.eurpsy.2010.04.011.
Kuss, D. J., Shorter, G. W., van Rooij, A. J.,
Griffiths, M. D., & Schoenmakers, T. M. (2014). Assessing internet
addiction using the parsimonious internet addiction components model - A
preliminary study. 12. International Journal of Mental Health Addiction,
351-366. doi:10.1007/s11469-013-9459-9.
Kuss, D. J., Shorter, G. W., van Rooij, A. J., van de
Mheen, D., & Griffiths, M. D. (2014). The internet addiction components
model and personality: Establishing construct validity via a nomological
network. Computers in Human Behavior, 39, 312-321. doi:
10.1016/j.chb.2014.07.031.
Laconi, S., Rodgers, R., & Chabrol, H. (2014).
The measurement of internet addiction: A critical review of existing scales
and their psychometric properties. Computers in Human Behavior, 41,
190-202. doi: 10.1016/j.chb.2015.04.056.
Laconi, S., Tricard, N., & Chabrol, H. (2015).
Differences between specific and generalized problematic internet uses
according to gender, age, time spent online and psychopathological symptoms. Computers
in Human Behavior, 48, 236-244. doi: 10.1016/j.chb.2015.02.006.
Lee, H., Choi, J.-S., Shin, Y.-C., Lee, J.-Y., Jung,
H., & Kwon, J. (2012). Impulsivity in internet addiction: A comparison
with pathological gambling. Cyberpsychology, Behavior, and Social
Networking, 15(7), 373-377. doi: 10.1089/cyber.2012.0063.
Lortie, C. L., & Guitton, M. J. (2013). Internet
addiction assessment tools: Dimensional structure and methodological status. Addiction,
108, 1207-1216. doi: 10.1111/add.12202.
Milani, L., Osualdella, D., & Di Blasio, P.
(2009). Quality of interpersonal relationships and problematic internet use
in adolescence. CyberPsychology and Behavior, 12(6), 681-684.
OReilly, M. (1996). Internet addiction: A new
disorder enters the medical lexicon. CMAJ: Canadian Medical Association
Journal = Journal De L'association Medicale Canadienne.154(12),
1882-1883. Retrieved from:
http://eds.b.ebscohost.com.proxy1.ncu.edu/eds/pdfviewer/pdfviewer?sid=b245519e-13aa-4839-8337-d5af81b43fd0%40sessionmgr112&vid=3&hid=117.
Pontes, H. M., Szabo, A., & Griffiths, M. D.
(2015). The impact of internet-based specific activities on the perceptions
of internet addiction, quality of life, and excessive usage: A
cross-sectional study. Addictive Behaviors Reports, 1, 19-25. doi:
10.1016/j.abrep.2015.03.002.
Saliceti, F. (2015). Internet Addiction Disorder
(IAD). Procedia Social and Behavioral Sciences, 191, 1372-1376. doi:
10.1016/j.sbspro.2015.04.292.
Sariyask, R., Reuter, M., Bey, K., Sha, P., Li, M.,
Chen, Y.-F., . . . Montag, C. (2014). Self-esteem, personality, and Internet
addiction: A cross-cultural comparison study. Personality and Individual
Differences, 61-62, 28-33. doi: 10.1016/j.paid.2014.01.001.
Siomos, K., Floros, G., Makris, E., Christou, G.,
& Hadjulis, M. (2014). Internet addiction and psychopathology in a
community before and during an economic crisis. Epideomiology and
Psychiatric Sciences, 23, 301-310. doi: 10.1017/S2045796013000437.
Suissa, A. J. (2014). Cyberaddictions: Toward a
psychosocial perspective. Addictive Behaviors, 39, 1914-1918. doi:
10.1016/j.addbeh.2014.07.027.
Wasinski, A., & Tomczyk, L. (2015). Factors
reducing the risk of internet addiction in young people in their home
enviornment. Children and Youth Services Review, 57, 68-74. doi:
10.1016/childyouth.2015.07.022.
Widyanto, L., Griffiths, M. D., & Brunsden, V.
(2011). A psychometric comparison of the internet addiction test, the
internet-related problem scale, and self-diagnosis. Cyberpsychology,
Behavior, and Social Networking, 14(3), 141-149. doi:
10.1089/cyber.2010.0151.
Yang, L., Sun, L., Zhang, Z., Sun, Y., Wu, H., &
Ye, D. (2014). Internet addiction, adolescent depression, and the mediating
role of life events: Finding from a sample of Chinese adolescents. International
Journal of Psychology, 49(5), 342-347. doi: 10.1002/ijop.12063.
Young, K. (2013). Retrieved from Center for Internet
Addiction: http://netaddiction.com/
Young, K. (In Press). The evolution of internet
addiction. Addictive Behaviors, doi: 10.1016/j.addbeh.2015.05.016.
Zhang, J., & Xin, T. (2013). Measurement of
internet addiction: An item response analysis approach. Cyberpsychology,
Behavior, and Social Networking, 16(6), 464-468. doi:
10.1089/cyber.2012.0525.
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