Sunday, February 7, 2016

Internet Addiction: Literature Review - For NCU PSY7102






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
-        1995 – IA is a Pet Project of Kimberly Young[1]
-         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.
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[1] Young, In Press
[2] Laconi, Tricard, & Chabrol, 2015
[3] Laconi, Tricard, & Chabrol, 2015, p 237

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