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“Internet Addiction”: a Conceptual Minefield

Francesca c ryding, linda k kaye.

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Issue date 2018.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

With Internet connectivity and technological advancement increasing dramatically in recent years, “Internet addiction” (IA) is emerging as a global concern. However, the use of the term ‘addiction’ has been considered controversial, with debate surfacing as to whether IA merits classification as a psychiatric disorder as its own entity, or whether IA occurs in relation to specific online activities through manifestation of other underlying disorders. Additionally, the changing landscape of Internet mobility and the contextual variations Internet access can hold has further implications towards its conceptualisation and measurement. Without official recognition and agreement on the concept of IA, this can lead to difficulties in efficacy of diagnosis and treatment. This paper therefore provides a critical commentary on the numerous issues of the concept of “Internet addiction”, with implications for the efficacy of its measurement and diagnosticity.

Keywords: Internet addiction, Gratifications, Contexts, Platforms, IGD

What Is Internet Addiction (IA)?

Traditionally, the term addiction has been associated with psychoactive substances such as alcohol and tobacco; however, behaviours including the use of the Internet have more recently been identified as being addictive (Sim et al. 2012 ). The concept of IA is generally characterised as an impulse disorder by which an individual experiences intense preoccupation with using the Internet, difficulty managing time on the Internet, becoming irritated if disturbed whilst online, and decreased social interaction in the real world (Tikhonov and Bogoslovskii 2015 ). These features were initially proposed by Young ( 1998 ) based on the criteria for pathological gambling (Yellowlees and Marks 2007 ), and have since been adapted for consideration within the DSM-5. This has been well received by many working in the field of addiction (Király et al. 2015 ; Petry et al. 2014 ), and has been suggested to enable a degree of standardisation in the assessment and identification of IA (King and Delfabbro 2014 ). However, there is still debate and controversy surrounding this concept, in which researchers acknowledge much conceptual disparity and the need for further work to fully understand IA and its constituent disorders (Griffiths et al. 2014 ).

Much of the debate relates to the issue that IA is conceptualised as addiction to the Internet as a singular entity, although it incorporates an array of potential activities (Van Rooij and Prause 2014 ). That is, the Internet, in all its formats, whether accessed via PC, console, laptop or mobile device, is fundamentally a portal through which we access activities and services. Internet connectivity thus provides us with ways of accessing the following types of activities; play (e.g. online forms of gaming, gambling), work (accessing online resources, downloading software, emailing, website hosting), socialising (social networking sites, group chats, online dating), entertainment (film databases, porn, music), consumables (groceries, clothes), as well as many other activities and services. In this way, the Internet is a highly multidimensional and diverse environment which affords a multitude of experiences as a product of the specific virtual domain. Thus, it is questionable as to whether there is any degree of consistency in the concept of IA, in light of these diverse and specific affordances which may relate to Internet engagement. Indeed, it has been indicated that there are several distinct types of IA, including online gaming, social media, and online shopping (Kuss et al. 2013 ), and it has been claimed that through engagement in these behaviours, individuals may become addicted to these experiences, as opposed to the medium itself (Widyanto et al. 2011 ). Thus, IA is arguably too generalised as a concept to adequately capture these nuances. That is, an individual who spends excessive time online for shopping is qualitatively different from someone who watches or downloads porn excessively. These represent distinct behaviours which are arguably underpinned by different gratifications. Thus, the functionality of aspects of the Internet is a key consideration for research in this area (Tokunaga 2016 ). This is perhaps best approached from a uses and gratifications perspective (LaRose et al. 2003 ; Larose et al. 2001a ; Wegmann et al. 2015 ), to more fully understand the aetiology of IA (discussed subsequently). This is often best underpinned by the uses and gratifications theory (Larose et al. 2001a , 2003 ), which seeks to explain (media) behaviours by understanding their specific functions and how they gratify certain needs. Indeed, in the context of IA, this may be particularly useful to establish the extent to which certain Internet-based behaviours may be more or less functional in need gratification than others, and the extent to which it is Internet platform itself which is driving usage or indeed the constituent domains which it affords. If the former, then controlling Internet-based usage behaviour more generically is perhaps appropriate, however, a more specified approach may often be required given the diverse needs the online environment can afford users.

IA from a Gratifications Perspective

It is questionable on the extent to which IA is itself the “addiction” or whether its aetiology relates to other pre-existing conditions, which may be gratified through Internet domains (Caplan 2002 ). One particular theory that has been referenced throughout much developing research (King et al. 2012 ; Laier and Brand 2014 ) is the cognitive-behavioural model, proposed by Davis ( 2001 ). This model suggests that maladaptive cognitions precede the behavioural symptoms of IA (Davis 2001 ; Taymur et al. 2016 ). Since much research focuses on the comorbidity between IA and psychopathology (Orsal et al. 2013 ), this is particularly useful in underpinning the concept of IA, and perhaps provides support that IA is a manifestation of underlying disorders, due to its psychopathological aetiology (Taymur et al. 2016 ). Additionally, the cognitive-behavioural model also distinguishes between both specific and generalised pathological Internet use, in comparison to global Internet behaviours that would not otherwise exist outside of the Internet, such as surfing the web (Shaw and Black 2008 ). As such, it would assume those individuals who spend excessive time playing poker online, for example, are perhaps better categorised as problematic gamblers rather than as Internet addicts (Griffiths 1996 ). This has been particularly advantageous in the contribution to defining IA, as earlier literature tended to focus solely on either content-specific IA, or the amount of time spent online, rather than focussing as to why individuals are actually online (Caplan 2002 ). Indeed, this shows promise in resolving some of the aforementioned issues in the specificity of IA, as well as the likelihood of pre-existing conditions underpinning problematic behaviours on the Internet.

Much of the recent literature in the realm of IA has focused upon Internet Gaming Disorder (IGD) which has recently been included as an appendix as “a condition for further study” in the DSM-5 (American Psychiatric Association 2013 ). This has driven a wide range of research which has sought to establish the validity of IGD as an independent clinical condition (Kuss et al. 2017 ). Among the wealth of research papers surrounding this phenomenon, there remains large disparity within the academic community. Although some researchers claim there is consensus on IGD as a valid clinical disorder (Petry et al. 2014 ), others do not support this (e.g. Griffiths et al. 2016 ). As such, the academic literature has some way to go before more established claims can be made towards IGD as a valid construct, and indeed how this impacts upon clinical treatment.

One means by which researchers could move forward in this regard is to establish the validity of IGD to a wider range of gaming formats. That is, IGD research has predominantly defined the reference point in studies as “online games” or in some cases, is has been even less specific (Lemmens et al. 2015 ; Rehbein et al. 2015 ; Thomas and Martin 2010 ). Arguably, there are a range of forms of “online” gaming, including social networking site (SNS) games which are Internet-mediated and thus by definition, would appear under the remit of IGD. Indeed, links between SNS and gaming have been previously noted (Kuss and Griffiths 2017 ), although this has not specifically been empirically explored in the context of IGD symptomology. For example, causal form of gaming as is typically the case for SNS gaming have their own affordances in respect of where and how they are played, given these are often played on mobile devices rather than on more traditional PC or console platforms. Further, the demographics of who are most likely to play these games can vary from others forms of gaming which have predominated the IGD literature (Hull et al. 2013 ; Leaver and Wilson 2016 ). Accordingly, these affordances present additional nuances, which the literature has not yet fully accounted for in its exploration of IGD. Clearly, IGD relates to a specific form of Internet behaviour which may be conceptualised within IA, yet is paramount to understand it as a separate entity to ensure the conceptualisation and any associated treatment provision is sufficiently nuanced. Likewise, the same case can be made for many other Internet-based behaviours which may be best being established in respect of their functionality and gratification purposes for users.

IA as a Contextual Phenomenon

There is growing evidence suggesting that context is key towards the processes and cognitions associated with consumption of substances such as alcohol (Monk and Heim 2013 , 2014 ; Monk et al. 2016 ), highlighting some important implications towards understanding IA, as a form of behavioural addiction. That is, the study of IA has rarely been studied in respect of its contextual affordances, even though the combination of Internet connectivity (WiFi) and mobility (smartphones) means that the Internet may be accessed in many ways and in multiple contexts. It has been indicated by Griffiths ( 2000 ) that few studies consider the context of Internet use, despite many users spending a substantial amount of time on the Internet via the use of different platforms, such as mobile devices, as opposed to a computer (Hadlington 2015 ). It has been highlighted by Kawabe et al. ( 2016 ) that smartphone ownership in particular is rapidly increasing, and for some, smartphone devices have become a substitute for the computer (Aljomaa et al. 2016 ). It has also been suggested that the duration of usage on smartphones have been significantly associated with IA (Kawabe et al. 2016 ). This can largely be attributed to the advancement of smartphone technology, which permit them to function as a “one-stop-shop” for a variety of our everyday needs (checking the time, replying to emails, listening to music, interacting with others, playing games), and thus it is understandable that we are spending more of our time in using these devices. This further implicates research in IA, as this has often focussed on users’ Internet engagement through computers as opposed to mobile devices, albeit the numerous Internet subtypes accessible through mobile devices (Sinkkonen et al. 2014 ). One Internet subtype in particular which may facilitate addictive behaviours are social networking sites such as Facebook (Wu et al. 2013 ). Particularly, research has identified a positive relationship between daily usage of smartphones and addictive symptoms towards Facebook (Wu et al. 2013 ). This may also be the case for behaviours such as gaming through SNS which are typically accessed on mobile devices rather than computers. However, of critical interest here, is that addiction to these games has been argued to fall under the classification of IGD, despite being online via Facebook (Ryan et al. 2014 ). This indicates that the platform of Internet access is important in online behaviours, as well as implicating that further distinction between Internet subtypes should be made (particularly within SNS), to establish the different features of these, and how these affordances may be related to excessive usage. This issue is particularly pertinent given the increased interest in “smartphone addiction” (Kwon et al. 2013 ) in which the name assumes we are simply studying addiction to our smartphones themselves, not necessarily the functions they are affording to us. Research such as this is assuming the “problem” is the interaction with the technology (e.g. specific device) itself, when this is most likely not the case. Indeed, recent evidence highlights that different uses/functions of smartphones may be more likely to prompt users to feel more “attached” to the device than others, and that usage is often framed by one’s current context (Fullwood et al. 2017 ).

In addition to being able to access the Internet through multiple platforms, we are often reliant on the Internet for many everyday tasks, which poses a further issue in conceptualising what is “problematic” compared to “required” usage. The increased exposure to the Internet in both work and education make it difficult to avoid usage in such environments (Kiliҫer and Ҫoklar 2015 ; Uçak 2007 ), and it could be argued that the amount of time spent on the Internet for such contexts cannot be reflected as an addiction (LaRose et al. 2003 ). This is pertinent in light of much research, which tends to rely on metrics such as time spent online (e.g. average hours per week) as a variable in research paradigms. Particularly, this tends to be used to correlate against other psychological factors, such as depression or well-being, to indicate how “internet use” may be a problematic predictor of these outcomes (e.g. Sanders et al. 2000 ). In light of the aforementioned issues, this does not offer any degree of specificity in how time spent online is theoretically related to the outcomes variables of interest (Kardefelt-Winther 2014 ). Other studies have approached this with greater nuance by considering specific activities, such as number of emails sent and received in a given time period (Ford and Ford 2009 ; LaRose et al. 2001b ), or studied Internet use for a variety of different purposes, such as for health purposes and communication (Bessière et al. 2010 ). Further, other researchers have highlighted the distinction between behaviours such as smartphone “usage” versus “checking” (Andrews et al. 2015 ), whereby the latter may represent a more compulsive and less consciously driven and potentially more addictive form of behaviour than actual “usage”. These more nuanced approaches provide a more useful and theoretically insightful means of establishing how time spent online may be psychologically relevant as a concept. This suggests that future research which theorises on the impacts of “time spent online” (or “screen-time use”) should provide distinction between usage for work/education and leisure, and the gratification this engagement affords, to obtain greater nuance beyond the typical flawed metrics such as general time spent online.

A further compliment to the existing IA literature would be greater use of behavioural measures which garner users’ actual Internet-based behaviours. This is particularly relevant when considering that almost all existing research on smartphone addiction or problematic use, for example has been based on users’ self-reported usage, with no psychometric measure being validated against behavioural metrics. Worryingly, it has been noted that smartphone users grossly underestimate the amount of times they check their smartphone on a daily basis, with digital traces of their smartphone behaviours illuminating largely disparate findings (Andrews et al. 2015 ). Clearly, there is much opportunity to establish forms of Internet usage by capitalising on behavioural metrics and digital traces rather than relying on self-report which may not always be entirely accurate.

The concept of IA is more complex than it often theorised. Although there have been multiple attempts to define the characteristics of IA, there a numerous factors which require greater clarity in the theoretical underpinnings of this concept. Specifically, IA is often considered from the perspective that the Internet itself (and indeed the technology through which we access it) is harmful, with little specificity in how this functions in different ways for individual users, as well as the varying affordances which can be gained through it. Unfortunately, this aligns somewhat with typical societal conceptions of “technology is harmful” perspective, rather than considering the technology itself is simply a portal through which a psychological need is being served. This perspective is not a new phenomenon. Most new media has been subject to such moral panic and thus this serves a historical tradition within societal conception of new media. Indeed, this has been particularly relevant to violent videogames which scholars have discussed in respect of this issue (Ferguson 2008 ). Whilst many scholars recognise this notion through the application of a user and gratifications perspective, stereotypical conceptions of “technology is harmful” still remain. This raises the question about how we as psychologists can enable a cultural shift in these conceptions, to provide a more critical perspective on such issues. The pertinence of this surrounds two key issues; firstly that moving beyond a “technology is harmful” perspective, particularly for concerns over “Internet addiction” as one example, can enable a more critical insight into the antecedents of problematic behaviour to aid treatment, rather than simply revoking access from the Internet for such individuals. Arguably, this latter strategy would not always address the route of the issue and raises implications about the extent to which recidivism would occur upon reinstating Internet access. Secondly, on a more general level, diverging from an “anti-technology” perspective can enable researchers to draw out the nuances of specific Internet environments and their psychological impacts rather than battling with more blanket assumptions that “technology” (as a unitary concept) is presenting all individuals with the same issues and affordances, regardless of the specific virtual platform or context. In this way, we may be presented with more plentiful opportunities to more critically explore individuals and their interactions across many Internet-mediated domains and contexts.

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Conflict of interest.

The authors declare that they have no conflicts of interest.

• Aljomaa SS, Al Qudah MF, Albursan IS, Bakhiet SF, Abduljabbar AS. Smartphone addiction among university students in the light of some variables. Computers in Human Behavior. 2016;61:155–164. doi: 10.1016/j.chb.2016.03.041. [ DOI ] [ Google Scholar ]
• American Psychiatric Association . Diagnostic and statistical manual of mental disorders. 5. Washington, DC: American Psychiatric Association; 2013. [ Google Scholar ]
• Andrews S, Ellis DA, Shaw H, Piwek L. Beyond self-report: tools to compare estimated and real-world smartphone use. PloS One. 2015;10:e0139004. doi: 10.1371/journal.pone.0139004. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Bessière K, Pressman S, Kiesler S, Kraut R. Effects of Internet use on health and depression: a longitudinal study. Journal of Medical Internet Research. 2010;12(1):e6. doi: 10.2196/jmir.1149. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Caplan SE. Problematic Internet use and psychosocial well-being: development of a theory-based cognitive–behavioral measurement instrument. Computers in Human Behavior. 2002;18(5):553–575. doi: 10.1016/S0747-5632(02)00004-3. [ DOI ] [ Google Scholar ]
• Davis RA. A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior. 2001;17(2):187–195. doi: 10.1016/S0747-5632(00)00041-8. [ DOI ] [ Google Scholar ]
• Ferguson CJ. The school shooting/violent video game link: casual relationship or moral panic? Journal of Investigative Psychology and Offender Profiling. 2008;5:25–37. doi: 10.1002/jip.76. [ DOI ] [ Google Scholar ]
• Ford, G. S., & Ford, S. G. (2009). Internet use and depression among the elderly . Phoenix Center Policy Paper Series. Retrieved April 26, 2016, from http://www.phoenix-center.org/pcpp/PCPP38Final.pdf .
• Fullwood C, Quinn S, Kaye LK, Redding C. My Virtual friend: a qualitative analysis of the attitudes and experiences of Smartphone users: implications for Smartphone attachment. Computers in Human Behavior. 2017;75:347–355. doi: 10.1016/j.chb.2017.05.029. [ DOI ] [ Google Scholar ]
• Griffiths MD. Gambling on the Internet: a brief note. Journal of Gambling Studies. 1996;12(4):471–473. doi: 10.1007/BF01539190. [ DOI ] [ PubMed ] [ Google Scholar ]
• Griffiths M. Internet addiction - time to be taken seriously? Addiction Research & Theory. 2000;8(5):413–418. doi: 10.3109/16066350009005587. [ DOI ] [ Google Scholar ]
• Griffiths MD, King DL, Demetrovics Z. DSM-5 Internet Gaming Disorder needs a unified approach to assessment. Neuropsychiatry. 2014;4(1):1–4. doi: 10.2217/npy.13.82. [ DOI ] [ Google Scholar ]
• Griffiths MD, Van Rooij AJ, Kardefelt-Winther D, et al. Working towards an international consensus on criteria for assessing internet gaming disorder: a critical commentary on Petry et al. (2014) Addiction. 2016;111:167–175. doi: 10.1111/add.13057. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hadlington LJ. Cognitive failures in daily life: exploring the link with Internet addiction and problematic mobile phone use. Computers in Human Behavior. 2015;51:75–81. doi: 10.1016/j.chb.2015.04.036. [ DOI ] [ Google Scholar ]
• Hull DC, Williams GA, Griffiths MD. Video game characteristics, happiness and flow as predictors of addiction among video game players: a pilot study. Journal of Behavioral Addictions. 2013;2(3):145–152. doi: 10.1556/JBA.2.2013.005. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kardefelt-Winther D. A conceptual and methodological critique of internet addiction research: towards a model of compensatory internet use. Computers in Human Behavior. 2014;31:351–354. doi: 10.1016/j.chb.2013.10.059. [ DOI ] [ Google Scholar ]
• Kawabe K, Horiuchi F, Ochi M, Oka Y, Ueno S. Internet addiction: prevalence and relation with mental states in adolescents. Psychiatry and Clinical Neurosciences. 2016;70(9):405–412. doi: 10.1111/pcn.12402. [ DOI ] [ PubMed ] [ Google Scholar ]
• Kiliҫer K, Ҫoklar AN. Examining human value development of children with different habits of Internet usage. Hacettepe University of Education. 2015;30(1):163–177. [ Google Scholar ]
• King DL, Delfabbro PH. The cognitive psychology of Internet gaming disorder. Clinical Psychology Review. 2014;34(4):298–308. doi: 10.1016/j.cpr.2014.03.006. [ DOI ] [ PubMed ] [ Google Scholar ]
• King DL, Delfabbro PH, Griffiths MD, Gradisar M. Cognitive-behavioral approaches to outpatient treatment of Internet addiction in children and adolescents. Journal of Clinical Psychology. 2012;68(11):1185–1195. doi: 10.1002/jclp.21918. [ DOI ] [ PubMed ] [ Google Scholar ]
• Király O, Griffiths MD, Demetrovics Z. Internet gaming disorder and the DSM-5: conceptualization, debates, and controversies. Current Addiction Reports. 2015;2(3):254–262. doi: 10.1007/s40429-015-0066-7. [ DOI ] [ Google Scholar ]
• Kuss DJ, Griffiths MD. Social networking networking sites and addiction: ten lessons learned. International Journal of Environmental Research and Public Health. 2017;14:311. doi: 10.3390/ijerph14030311. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kuss DJ, van Rooij AJ, Shorter GW, Griffiths MD, van de Mheen D. Internet addiction in adolescents: prevalence and risk factors. Computers in Human Behavior. 2013;29(5):1987–1996. doi: 10.1016/j.chb.2013.04.002. [ DOI ] [ Google Scholar ]
• Kuss, D. J., Grittihs, M. D., & Pontes, H. M. (2017). DSM-5 diagnosis of Internet Gaming Disorder: some ways forward in overcoming issues and concerns in the gaming studies field. Journal of Behavioral Addictions. 10.1556/2006.6.2017.032. [ DOI ] [ PMC free article ] [ PubMed ]
• Kwon M, Lee J, Won W, Park J, Min J, Hahn C, Gu X, Choi J, Kim D. Development and validation of a smartphone addiction scale. PloS One. 2013;8(2):e56936. doi: 10.1371/journal.pone.0056936. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Laier C, Brand M. Empirical evidence and theoretical considerations on factors contributing to cybersex addiction from a cognitive-behavioral view. Sexual Addiction & Compulsivity. 2014;21(4):305–321. doi: 10.1080/10720162.2014.970722. [ DOI ] [ Google Scholar ]
• Larose R, Mastro D, Eastin MS. Understanding Internet usage: a social-cognitive approach to uses and gratifications. Social Science Computer Review. 2001;19(4):395–413. doi: 10.1177/089443930101900401. [ DOI ] [ Google Scholar ]
• LaRose, R., Eastin, M. S., & Gregg, J. (2001b). Reformulating the Internet paradox: social cognitive explanations of Internet use and depression. Journal of Online Behavior, 1 (2). Retrieved Setpember 12, 2017 from http://psycnet.apa.org/record/2002-14047-001 .
• LaRose R, Lin CA, Eastin MS. Unregulated Internet usage: Addiction, habit, or deficient self-regulation? Media Psychology. 2003;5(3):225–253. doi: 10.1207/S1532785XMEP0503_01. [ DOI ] [ Google Scholar ]
• Leaver T, Wilson M. Social networks, casual games and mobile devices: the shifting contexts of gamers and gaming. London: Bloomsbury Publishing Inc.; 2016. [ Google Scholar ]
• Lemmens JS, Valkenburg PM, Gentile DA. The internet gaming disorder scale. Psychological Assessment. 2015;27(2):567–582. doi: 10.1037/pas0000062. [ DOI ] [ PubMed ] [ Google Scholar ]
• Monk RL, Heim D. Environmental context effects on alcohol-related outcome expectancies, efficacy and norms: a field study. Psychology of Addictive Behaviors. 2013;27:814–818. doi: 10.1037/a0033948. [ DOI ] [ PubMed ] [ Google Scholar ]
• Monk RL, Heim D. A real-time examination of context effects on alcohol cognitions. Alcoholism: Clinical and Experimental Research. 2014;38:2452–2459. doi: 10.1111/acer.12504. [ DOI ] [ PubMed ] [ Google Scholar ]
• Monk RL, Pennington CR, Campbell C, Price A, Heim D. Implicit alcohol-related expectancies and the effect of context. Journal of Studies on Alcohol and Drugs. 2016;77:819–827. doi: 10.15288/jsad.2016.77.819. [ DOI ] [ PubMed ] [ Google Scholar ]
• Orsal O, Unsal A, Ozalp SS. Evaluation of Internet addiction and depression among university students. Procedia - Social and Behavioral Sciences. 2013;82:445–454. doi: 10.1016/j.sbspro.2013.06.291. [ DOI ] [ Google Scholar ]
• Petry NM, Rehbein F, Gentile DA, Lemmens JS, Rumpf H, Mӧßle T, et al. An international consensus for assessing Internet Gaming Disorder using the new DSM-5 approach. Addiction. 2014;109(9):1399–1406. doi: 10.1111/add.12457. [ DOI ] [ PubMed ] [ Google Scholar ]
• Rehbein F, Kliem S, Baier D, Mossle T, Petry NM. Prevalence of internet gaming disorder in German adolescents: diagnostic contribution of the nine DSM-5 criteria in a state-wide representative sample. Addiction. 2015;110(5):842–851. doi: 10.1111/add.12849. [ DOI ] [ PubMed ] [ Google Scholar ]
• Ryan T, Chester A, Reece J, Xenos S. The uses and abuses of Facebook: a review of Facebook addiction. Journal of Behavioral Addictions. 2014;3(3):133–148. doi: 10.1556/JBA.3.2014.016. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sanders CE, Field TM, Diego M, Kaplan M. The relationship between Internet use to depression and social isolation among adolescents. Adolescence. 2000;35(138):237–242. [ PubMed ] [ Google Scholar ]
• Shaw M, Black DW. Internet addiction. CNS Drugs. 2008;22(5):353–365. doi: 10.2165/00023210-200822050-00001. [ DOI ] [ PubMed ] [ Google Scholar ]
• Sim T, Gentile DA, Bricolo F, Serpelloni G, Gulamoydeen F. A conceptual review of research on the pathological use of computers, video games, and the Internet. International Journal of Mental Health and Addiction. 2012;10(5):748–769. doi: 10.1007/s11469-011-9369-7. [ DOI ] [ Google Scholar ]
• Sinkkonen H-M, Puhakka H, Meriläinen M. Internet use and addiction among Finnish adolescents (15–19 years) Journal of Adolescence. 2014;37(2):123–131. doi: 10.1016/j.adolescence.2013.11.008. [ DOI ] [ PubMed ] [ Google Scholar ]
• Taymur I, Budak E, Demirci H, Akdağ HA, Güngör BB, Özdel K. A study of the relationship between internet addiction, psychopathology and dysfunctional beliefs. Computers in Human Behavior. 2016;61:532–536. doi: 10.1016/j.chb.2016.03.043. [ DOI ] [ Google Scholar ]
• Thomas NJ, Martin FH. Video-arcade game, computer game and Internet activities of Australian students: participation participation habits and prevalence of addiction. Australian Journal of Psychology. 2010;62(2):59–66. doi: 10.1080/00049530902748283. [ DOI ] [ Google Scholar ]
• Tikhonov MN, Bogoslovskii MM. Internet addiction factors. Automatic Documentation and Mathematical Linguistics. 2015;49(3):96–102. doi: 10.3103/S0005105515030073. [ DOI ] [ Google Scholar ]
• Tokunaga RS. An examination of functional difficulties from Internet use: Media habit and displacement theory explanations. Human Communication Research. 2016;42(3):339–370. doi: 10.1111/hcre.12081. [ DOI ] [ Google Scholar ]
• Uçak NÖ. Internet use habits of students of the department of information management, Hacettepe University, Ankara. The Journal of Academic Librarianship. 2007;33(6):697–707. doi: 10.1016/j.acalib.2007.09.004. [ DOI ] [ Google Scholar ]
• Van Rooij A, Prause N. A critical review of “Internet addiction” criteria with suggestions for the future. Journal of Behavioral Addictions. 2014;3(4):203–213. doi: 10.1556/JBA.3.2014.4.1. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wegmann E, Stodt B, Brand M. Addictive use of social networking sites can be explained by the interaction of Internet use expectancies, Internet literacy, and psychopathological symptoms. Journal of Behavioral Addictions. 2015;4(3):155–162. doi: 10.1556/2006.4.2015.021. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Widyanto L, Griffiths MD, Brunsden V. A psychometric comparison of the Internet Addiction Test, the Internet-Related Problem Scale, and self-diagnosis. Cyberpsychology, Behavior, and Social Networking. 2011;14(3):141–149. doi: 10.1089/cyber.2010.0151. [ DOI ] [ PubMed ] [ Google Scholar ]
• Wu AMS, Cheung VI, Ku L, Hung EPW. Psychological risk factors of addiction to social networking sites among Chinese smartphone users. Journal of Behavioral Addictions. 2013;2(3):160–166. doi: 10.1556/JBA.2.2013.006. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Yellowlees PM, Marks S. Problematic Internet use or Internet addiction? Computers in Human Behavior. 2007;23(3):1447–1453. doi: 10.1016/j.chb.2005.05.004. [ DOI ] [ Google Scholar ]
• Young KS. Internet addiction: the emergence of a new clinical disorder. Cyberpsychology & Behavior. 1998;1(3):237–244. doi: 10.1089/cpb.1998.1.237. [ DOI ] [ Google Scholar ]
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Internet Addiction

Neuroscientific Approaches and Therapeutical Implications Including Smartphone Addiction

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• Psychopharmacological Treatment of Internet Addiction
• Structural Brain Imaging
• Neuroscience of internet addiction

Table of contents (22 chapters)

Front matter, introduction to internet addiction.

• Kimberly Young

Theoretical Models of the Development and Maintenance of Internet Addiction

• Matthias Brand

Neuroscientific Approaches to Internet Addiction

Structural brain imaging and internet addiction.

• Fuchun Lin, Hao Lei

Functional Imaging Study of Internet Gaming Disorder

• Chih-Hung Ko, Ju-Yu Yen

Internet Addiction and PET

• Hyun Soo Park, Sang Eun Kim

Functional Brain Changes in Response to Treatment of Internet Gaming Disorder

• Doug Hyun Han, Sun Mi Kim, Perry F. Renshaw

Neuroscientific Approaches to (Online) Pornography Addiction

• Rudolf Stark, Tim Klucken

Quantitative Behavior Genetics of Internet Addiction

• Elisabeth Hahn, Frank M. Spinath

Molecular Genetics, Personality, and Internet Addiction Revisited

• Christian Montag, Martin Reuter

Autonomic Nervous System and Brain Circuitry for Internet Addiction

• Andrew Chih Wei Huang

Psychometric Assessment of Internet Gaming Disorder in Neuroimaging Studies: A Systematic Review

• Halley M. Pontes, Daria J. Kuss, Mark D. Griffiths

A Short Summary of Neuroscientific Findings on Internet Addiction

• Christian Montag, Éilish Duke, Martin Reuter

Therapeutical Interventions in Internet Addiction and Governmental Policies

The impact of psychoinformatics on internet addiction including new evidence.

• Christian Montag, Martin Reuter, Alexander Markowetz

Pharmacological Treatment of Internet Addiction

• Giovanni Camardese, Beniamino Leone, Coco Walstra, Luigi Janiri, Riccardo Guglielmo

Therapeutic Interventions for Treatment of Adolescent Internet Addiction—Experiences from South Korea

Therapeutic interventions for treatment of adolescent internet addiction—experiences from germany.

• Wolfgang Dau, J. D. G. Hoffmann, Markus Banger

Editors and Affiliations

Christian Montag

Martin Reuter

Bibliographic Information

Book Title : Internet Addiction

Book Subtitle : Neuroscientific Approaches and Therapeutical Implications Including Smartphone Addiction

Editors : Christian Montag, Martin Reuter

Series Title : Studies in Neuroscience, Psychology and Behavioral Economics

DOI : https://doi.org/10.1007/978-3-319-46276-9

Publisher : Springer Cham

eBook Packages : Engineering , Engineering (R0)

Copyright Information : Springer International Publishing Switzerland 2017

Hardcover ISBN : 978-3-319-46275-2 Published: 04 April 2017

Softcover ISBN : 978-3-319-83482-5 Published: 08 May 2018

eBook ISBN : 978-3-319-46276-9 Published: 27 March 2017

Series ISSN : 2196-6605

Series E-ISSN : 2196-6613

Edition Number : 2

Number of Pages : XI, 392

Number of Illustrations : 23 b/w illustrations, 22 illustrations in colour

Topics : Biomedical Engineering and Bioengineering , Neurosciences , Cognitive Psychology , Neurology , User Interfaces and Human Computer Interaction

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ORIGINAL RESEARCH article

Internet addiction and related clinical problems: a study on italian young adults.

• 1 Department of Neurosciences, University of Verona, Verona, Italy
• 2 Unit of Addiction Medicine, Department of Internal Medicine, Integrated University Hospital of Verona, Policlinico “G.B. Rossi”, Verona, Italy
• 3 Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
• 4 Amici C.A.S.A. San Simone No Profit Association, Mantova, Italy

The considerable prominence of internet addiction (IA) in adolescence is at least partly explained by the limited knowledge thus far available on this complex phenomenon. In discussing IA, it is necessary to be aware that this is a construct for which there is still no clear definition in the literature. Nonetheless, its important clinical implications, as emerging in recent years, justify the lively interest of researchers in this new form of behavioral addiction. Over the years, studies have associated IA with numerous clinical problems. However, fewer studies have investigated what factors might mediate the relationship between IA and the different problems associated with it. Ours is one such study. The Italian version of the SCL-90 and the IAT were administered to a sample of almost 800 adolescents aged between 16 and 22 years. We found the presence of a significant association between IA and two variables: somatization (β = 7.80; p < 0.001) and obsessive-compulsive symptoms (β = 2.18; p < 0.05). In line with our hypothesis, the results showed that somatization predicted the relationship between obsessive-compulsive symptoms and IA (β = −2.75; t = −3.55; p < 0.001), explaining 24.5% of its variance (Δ R 2 = 1.2%; F = 12.78; p < 0.01). In addition, simple slopes analyses revealed that, on reaching clinical significance (+1 SD), somatization showed higher moderation effects in the relationship between obsessive-compulsive symptoms and IA (β = 6.13; t = 7.83; p < 0.001). These results appear to be of great interest due to the absence of similar evidence in the literature, and may open the way for further research in the IA field. Although the absence of studies in the literature does not allow us to offer an exhaustive explanation of these results, our study supports current addiction theories which emphasize the important function performed by the enteroceptive system, alongside the more cited reflexive and impulsive systems.

Introduction

Internet addiction (IA), also referred to as problematic , pathological , or compulsive Internet use , is a controversial concept in the research field. The frequent use of different terms to describe this new phenomenon, linked to the advent and growth of the Internet, leads to confusion over what it really consists of Tereshchenko and Kasparov (2019) .

Although researchers have yet to find a common definition of IA, it can be considered a “ non-chemical, behavioral addiction, which involves human-machine interaction ” ( Griffiths, 2000 ). Useful clinical criteria were proposed by Block (2008) , who associates IA with (a) increased feelings of anger, anxiety or sadness when the Internet is not accessible (craving); (b) the need to spend more hours on Internet devices in order to feel pleasure or cope with dysregulation of mood (tolerance); (c) poor school performance or vocational achievement; and (d) isolation or social withdrawal.

One aspect that researchers agree on is the importance of IA prevention in children and adolescents ( Lan and Lee, 2013 ). As with other forms of addiction, younger people are at greater risk of the negative effects of out-of-control Internet use ( Ko et al., 2008 ). In adolescence, distress is expressed in the form of behavioral agitation, somatic symptoms, boredom and an inclination to act ( Carlson, 2000 ), all modalities that facilitate the development of a coping strategy based on compulsive Internet use. This is a problem, given that 80% of adolescents use tablets or smartphones ( Fox and Duggan, 2013 ), whereas general population prevalence rates range from 0.8% (Italy) to 26.5% (Hong Kong) ( Kuss et al., 2014 ).

We currently know that IA is associated with symptoms of ADHD in teens ( Yoo et al., 2004 ), pathological gambling ( Phillips et al., 2012 ), depression ( Andreou and Svoli, 2013 ; Ho et al., 2014 ), anxiety ( Griffiths and Meredith, 2009 ; Zboralski et al., 2009 ), social phobia ( Carli et al., 2013 ; Gonzalez-Bueso et al., 2018 ), experiential avoidance ( Hayes et al., 1996 ; García-Oliva and Piqueras, 2016 ), obsessive-compulsive disorder (OCD) ( Jang et al., 2008 ; Cecilia et al., 2013 ), eating disorders ( Shapira et al., 2003 ; Bernardi and Pallanti, 2009 ), and sleep disorders ( Nuutinen et al., 2014 ; Tamura et al., 2017 ), as well as with relational conflicts ( Gundogar et al., 2012 ), aggression ( Cecilia et al., 2013 ), self-destructive behaviors ( Sasmaz et al., 2014 ), suicidal behaviors ( Durkee et al., 2016 ), physical health problems ( Sung et al., 2013 ), and chronic pain syndrome ( Wei et al., 2012 ). However, little is known about the factors potentially implicated in the etiopathogenesis of IA ( Tereshchenko and Kasparov, 2019 ).

Many of the most common symptoms of addiction and OCD are similar to each other, to the point that some authors define IA as compulsive computer use ( Kuss et al., 2014 ). However, there are also significant differences between the two sets of psychopathological symptoms. The obsessive-compulsive symptoms that characterize OCD can be described as recurring and persistent inappropriate thoughts (obsessions) that lead the individual to implement behaviors (compulsions) aimed at reducing the intensity of the distress deriving from these obsessive thoughts ( American Psychiatric Association [APA], 2013 ). Instead, the obsessive-compulsive symptoms reported in the context of addiction can also derive from positive thoughts about the object of the addiction, which drive the individual to seek and, in this case, engage in the activity in order to obtain gratification ( Robbins and Clark, 2015 ).

In this framework, the obsessive-compulsive component of IA can be considered in terms of (a) recurrent positive and negative thoughts (obsessions), associated, respectively, with the memory of the enjoyable experience of using the Internet, and with craving or withdrawal syndrome; and (b) instrumental behaviors (compulsion) geared toward seeking the former (positive reward) or reducing the discomfort associated with the latter (negative reward).

Adolescents with IA can be expected to display: (a) a lower ability to use reflexivity to manage their internal states; and (b) a greater propensity for impulsive behaviors to manage these states. This is the hypothesis recently proposed by Wei et al. (2017) to explain internet gaming disorder (IGD), a form of IA. However, alongside the presence of a hypoactive reflective system and an overactive impulsive system, these authors also hypothesize a dysregulation of the interoceptive awareness system, and suggest that this dysregulation increases the incentive salience of Internet use, as well as the feeling of craving deriving from its compulsive use ( Wei et al., 2017 ). This thesis could explain the relationship commonly observed between compulsive use of the Internet and somatization ( Yang et al., 2005 ).

Somatization is defined as the “ unconscious process of expressing psychological distress in the form of physical symptoms ” ( Nakkas et al., 2019 ), and it is commonly found among adolescents with IA. It is estimated that 9% of Internet-addicted adolescents display somatization ( Yang, 2001 ), reported in the literature to consist of somatic symptoms ( Potembska et al., 2019 ), chronic pain ( Wei et al., 2012 ; Fava et al., 2019 ), physical health problems ( Sung et al., 2013 ), and sleep disorders ( Tamura et al., 2017 ). Moreover, in late adolescence, the presence of somatization has been positively associated with the intensity of specific forms of IA, such as IGD ( Cerniglia et al., 2019 ). One study showed that higher somatization and interpersonal sensitivity scores predict problematic smartphone use ( Fırat et al., 2018 ). Ballespi et al. (2019) , illustrate that inability to mentalize is associated with a higher frequency of somatic complaints.

Although the involvement of somatization in the etiopathogenesis of IA is not yet clear, models recently advanced to explain the development of addiction assign it a primary role. In the triadic neurocognitive model of addiction ( Noël et al., 2013 ), for example, perception of the somatic state of the organism, governed by the insular cortex, is considered a factor that mediates the development of addiction. In fact, in the absence of cognitive processing of the bottom-up somatic signals mediated by this cerebral structure, the main symptoms of addiction suddenly disappear.

These data were recently confirmed by Naqvi et al. (2007) , who showed that absence of the somatic symptoms typical of craving and physical abstinence, induced by ischemic damage to the insula, allowed heavy smokers to give up smoking.

Somatization has been reported in association with IA in a college student population ( Alavi et al., 2011 ), and it has also been identified among the causal factors and predictors of IA among first-year college students ( Yao et al., 2013 ). Indeed, this latter study confirmed that students with somatization seem to have a greater tendency to develop IA. In addition, a study by Biby (1998) showed that higher somatization scores are linked to higher obsessive-compulsive tendency scores. Therefore, if a key role of somatic symptoms in modulating the activity of the reflexive and impulsive systems can be taken to explain the development of IA, it seems possible to hypothesize that the presence of obsessive-compulsive symptoms, commonly found in adolescents with IA ( Yen et al., 2008 ), may also be linked to the presence of somatization. In this sense, an additional hypothesis is that higher somatization in adolescents might exacerbate the effect of obsessive-compulsive symptoms on IA. Surprisingly, this hypothesis has not been investigated in the literature to date, although contemporary etiopathogenetic models suggest the importance of bottom-up somatic signals in addiction disorders ( Verdejo-García and Bechara, 2009 ). In fact, somatic symptoms may be linked to the presence of the same top-down processing of body signals related to craving or abstinence. According to the above hypothesis, these symptoms may upset the activity of the cognitive system, shifting it away from inhibitory control of Internet use, implemented by the reflexive system, toward compulsive behaviors, driven by the impulsive system ( Wei et al., 2017 ). In this way, high levels of somatization could both promote the development of IA and reinforce the relationship between obsessive-compulsive symptoms and IA.

In conclusion, our hypothesis is that somatization moderates the positive relationship between OC symptoms and IA. Specifically, the higher the level of somatization, the stronger the relationship.

Materials and Methods

Participants.

Participants were recruited from schools in the north of Italy. The study was presented during the participants’ classes. Students were invited to take part in a research study that aimed to investigate: drug use/abuse, gambling problems, alcohol use/abuse, mood. Students who provided informed consent were given two self-report instruments. All the participants were free to stop filling in the questionnaires at any time. Underage subjects needed parental permission to participate in this study.

The participants (57.7% females) ranged in age from 16 to 22 years (mean age 17.52 ± 1.15). All were third (35%), fourth (37%), or fifth grade (28%) Italian secondary school students.

Instruments

Symptom checklist 90—revised (scl-90-r; derogatis, 1994 ).

The Somatization (SOM;12 items) and Obsessive-Compulsive (OC; 10 items) subscales of the Italian version of the SCL-90-R were used. The participants used a five-point Likert scale, ranging from 0 (Not at all) to 4 (Extremely), to rate the extent to which they had experienced the listed symptoms during the past week. Cronbach’s alpha was 0.86 for SOM, and 0.82 for OC.

Internet Addiction Test (IAT; Young, 1998 )

This is a 20-item questionnaire on which respondents are asked to rate, on a five-point Likert scale, items investigating the degree to which their Internet use affects their daily routine, social life, productivity, sleeping patterns, and feelings. The minimum score is 20, and the maximum is 100; the higher the score, the greater the problems caused by Internet use. Young suggests that a score of 20–39 points is that of an average on-line user who has complete control over his/her Internet use; a score of 40–69 indicates frequent problems due to Internet use; and a score of 70–100 means that the individual’s Internet use is causing significant problems. Cronbach’s alpha was 0.88.

Socio-Demographics

The participants reported their age, gender, school and grade. In order to maintain privacy, no other personal information was requested.

Control Variables

The use of illicit drugs and gambling behavior were introduced as control variables. Specifically, the participants answered questions on their habits regarding any use of illicit drugs (cannabis, cocaine, heroin), alcohol consumption, and gambling activities, such as scratch cards, lottery tickets, football pools, new slot machines (VLTs) and video poker, betting on sporting or other events, poker and other card games.

Statistical Analyses

All the analyses were carried out using IBM SPSS Statistics 26.0 and AMOS ( Arbuckle, 2012 ). A series of confirmatory factor analyses (CFAs) was conducted to establish the discriminant validity of the scales. A full measurement model was initially tested, comparing it to a one-factor structure (in which all the items loaded into a common factor). The model fit was tested by using the comparative fit index (CFI), the incremental fit index (IFI), and the root-mean-square error of approximation (RMSEA). According to Kline (2008) and Byrne (2016) , the CFI and IFI values should have a cutoff value of ≥0.90, and the RMSEA a value of ≤ 0.08 to indicate a good fit of the model. Internal consistency of the constructs was evaluated using Cronbach’s alpha (α).

We tested the effects of somatization symptoms, obsessive-compulsive symptoms, and their interaction on IA by using the SPSS version of Hayes’s (2017) bootstrap-based PROCESS macro ( Hayes, 2012 , 2013 ; Model 1). All predictors were mean-centered prior to computing the interaction term and simple slopes were calculated at ± 1 SD. Age, sex, type of school, grade, use of illicit drugs, and gambling behaviors were included as covariates. To account for non-normality, analyses were performed with bootstrapping with 5,000 resamples.

Preliminary Analyses

Table 1 shows the means, standard deviations and internal consistencies obtained for each scale, and the correlations between the measures used in the current study.

Table 1. Descriptives of study variables ( n = 796).

Measurement Model

Prior to testing our hypothesis, we used CFAs to examine the convergent and discriminant validity of our study variables. The data were found to fit the measurement model: χ 2 (811) = 1150.99, p < 0.001, CFI = 0.90, TLI = 0.90, RMSEA = 0.035. All items loaded significantly on the intended latent factors.

Moderation Analysis

It was hypothesized that obsessive-compulsive symptoms would predict IA, depending on the somatization symptoms (moderation hypothesis). Regression analyses ( Table 2 ) conducted with the PROCESS macro (Model 1; Hayes, 2012 ) showed that obsessive-compulsive symptoms (β = 7.80, p < 0.001) and somatization symptoms (β = 2.18, p < 0.05) were related to IA after controlling for age, sex, grade, school, illicit drug use, and gambling behaviors. The moderation effect was significant t (788) = −3.55; p < 0.001 (β = −2.75, SE = 0.77, CI −4.27 to −1.2) and accounted for a significant portion of variance of IA [Δ R 2 = 1.2%; F ( 788 ) = 12.78 p < 0.01]. In this sense, increasing obsessive-compulsive symptoms predicted increased IA, but this effect was greatest at higher levels of somatization symptoms. The final model accounted for a total of 24.5% of the variance in IA.

Table 2. Results of the moderation analysis.

Simple slopes analyses revealed that when somatization symptoms were low (−1 SD), there was a statistically significant effect of obsessive-compulsive symptoms on increased IA (β = 9.48, SE = 0.88, t = 10.80, p < 0.01). Furthermore, also when somatization symptoms were high (+1 SD), there was a significant effect of obsessive-compulsive symptoms on IA (β = 6.13, SE = 0.79, t = 7.83, p < 0.001). Simple slopes analyses ( Figure 1 ) revealed that when somatization symptoms were low.

Figure 1. Interaction term for two levels of somatization: low (−1 SD) and high (+1 SD). Using the Johnson-Neyman technique ( Bauer and Curran, 2005 ), we identified the region where the effect of somatization symptoms on the relationship between OC and IA ceased to be statistically significant. Application of the Johnson-Neyman technique gave cutoff scores for somatization symptoms of below 1.81 and above 1.63.

The aim of this study was to increase current knowledge about the relationship between somatization symptoms, obsessive-compulsive symptoms, and IA in adolescents. Specifically, we hypothesized that the relationship between obsessive-compulsive symptoms and IA would be stronger at higher levels of somatization symptoms.

First, findings from our study suggest that obsessive-compulsive symptoms are associated with IA. These results are in line with prior research, which found that high levels of obsessive-compulsive symptoms are linked to higher IA risk ( Jang et al., 2008 ; Dong et al., 2011 ; Ko et al., 2012 ). Furthermore, IA has typically been described as a secondary condition resulting from various primary disorders, although findings in young adult samples have suggested that, within a range of psychopathologies, only obsessive-compulsive symptoms preceded IA ( Dong et al., 2011 ; Ko et al., 2012 ). The obsessive-compulsive symptoms observed in association with IA are similar to those of OCD, so much so that many researchers define IA as compulsive computer use ( Kuss et al., 2014 ). However, the obsessive-compulsive symptoms of OCD have been described as more ego-dystonic than those of IA ( Shapira et al., 2000 ). In general, the obsessive-compulsive symptoms of IA stem from recurring or persistent positive or negative thoughts (obsessions) that motivate the individual to implement behaviors (compulsions) intended to allow him/her to experience the hedonic satisfaction deriving from obtaining a positive reinforcement ( Robbins and Clark, 2015 ), or to reduce the distress typically associated with craving and abstinence states. IA may thus serve as a strategy for relieving pre-existing obsessive-compulsive psychopathology, a mechanism that, in turn, could actually reinforce the symptoms ( Ko et al., 2012 ). Similarly, this association could be further reinforced by underlying mechanisms shared by OC and IA behaviors ( Ko et al., 2012 ). Repetitive behavioral manifestations aimed at achieving immediate gratification or de-escalating the distress triggered by obsessive thoughts in order to improve one’s feelings are typical of addictions and compulsive behaviors ( Robbins and Clark, 2015 ). In the present study, the main effect of somatization symptoms on IA was in line with the findings of previous research ( Yang et al., 2005 ; Yen et al., 2008 ; Alavi et al., 2011 ; Yao et al., 2013 ). Somatization is conceptualized as a process that leads to translation of psycho-emotional distress into bodily discomfort ( Nakkas et al., 2019 ). Subjects with somatization disorders requiring inpatient treatment manifest deficits in both emotional awareness and Theory of Mind functioning. These deficits may underlie the phenomenon of somatization ( Subic-Wrana et al., 2010 ).

As regards our moderation hypothesis, we found that the relationship between obsessive-compulsive symptoms and IA was greatest at higher levels of somatization symptoms. Our results showed that in adolescents with higher somatization (+1 SD), the relationship between obsessive-compulsive symptoms and IA was stronger. To our knowledge, this is the first study that has investigated this relationship. Our results are in line with the triadic theory of addiction ( Noël et al., 2013 ), where somatization, as a major expression of the enteroceptive system, could hinder the management of normal emotional distress through problem-focused coping strategies based on reflexive system mentalization skills. This apparent partial impairment of the reflexive system’s capacity to regulate emotional distress could therefore lead adolescents to adopt emotion-focused coping strategies, such as ones related to implementation of the same obsessive-compulsive behaviors promoted by the impulsive system. Somatization could therefore impair the mentalization skills used by the reflexive system to inhibit compulsive behaviors driven by the impulsive system, predisposing the adolescent to develop IA. This could explain why obsessive-compulsive symptoms are often found in the literature as prodromes of IA development ( Dong et al., 2011 ; Ko et al., 2012 ), as well as why IA has typically been described as a secondary disorder resulting from a primary one, like obsessive-compulsive symptomatology ( Dong et al., 2011 ; Ko et al., 2012 ), a relationship that is confirmed in our study.

Our analyses were performed controlling for gender, age, grade, and school. Specifically, a significant gender difference emerged, as showed in previous studies ( Cao et al., 2011 ; Barke et al., 2012 ; Kuss et al., 2013 ). As showed in a study by Feng et al. (2019) , we have found a significant grade difference.

The present study has several limitations. First, the cross-sectional design used does not allow the identification of causal relationships among variables. We cannot definitively conclude that obsessive-compulsive symptoms cause IA and that this relationship depends on levels of somatization. Future studies should consider longitudinal data to overcome the cross-sectional limitations. A second, potential, limitation concerns the reliance on self-reported data, which might have caused common method bias. However, we ran the Harman’s single factor test, which suggested that common method bias did not affect the results of this study. A third limitation concerns mentalization ability. Good mentalization could be protective against somatization, but we did not measure it. Future research could explore this aspect through specific questionnaires.

Adolescence is an important period of physical and psychological development. From a clinical perspective, the results of this study show that somatization is an important moderation factor in adolescence. The incapacity to use coping strategies and mentalization strategies to counter negative emotions could increase the somatization effect. In adolescents, obsessive-compulsive symptoms can be moderated by somatization. In this period of development, it is very important to pay attention to bodily signals, as they can mask psychological problems. Obsessive-compulsive symptoms can be very invalidating, and they can be exacerbated by somatization. Teenagers seeking a coping response in technological devices are at considerable risk of developing pathological use of these devices.

In conclusion, somatization is an important aspect to consider when dealing with adolescent patients. It could be a moderation factor capable of exacerbating obsessive-compulsive symptoms or IA. This particular aspect needs more studies in the future.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.

Ethics Statement

The studies involving human participants were reviewed and approved by the CARU-Comitato di Approvazione per la Ricerca sull’Uomo, Università di Verona. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Author Contributions

FL, AR, and LZ were responsible for the study concept and design. SC, FC, and RM contributed to the data acquisition. IP assisted with the data analysis and interpretation of findings. AF, LZ, IP, and AC drafted the manuscript. All authors critically reviewed the content and approved the final version of the manuscript for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Alavi, S. S., Maracy, M. R., Jannatifard, F., and Eslami, M. (2011). The effect of psychiatric symptoms on the Internet addiction disorder in Isfahan’s university students. J. Res. Med. Sci. 16, 793–800.

Google Scholar

American Psychiatric Association [APA] (2013). Manuale Diagnostico e Statistico dei Disturbi Mentali, DSM-5 , 5th Edn. Milano: Tr. it. Raffaello Cortina.

Andreou, E., and Svoli, H. (2013). The association between internet user characteristics and dimensions of internet addiction among Greek adolescents. Int. J. Ment. Health Addict. 11, 139–148. doi: 10.1007/s11469-012-9404-3

CrossRef Full Text | Google Scholar

Arbuckle, J. L. (2012). IBM SPSS AMOS (Version 21.0) [Computer Program] . Chicago, IL: IBM.

Ballespi, S., Vives, J., Alonso, N., Sharp, C., Ramirez, M. S., Fonagy, P., et al. (2019). To know or not to know? Mentalization as protection from somatic complaints. PLoS One 14:e0215308. doi: 10.1371/journal.pone.0215308

PubMed Abstract | CrossRef Full Text | Google Scholar

Barke, A., Nyenhuis, N., and Kröner-Herwig, B. (2012). The German version of the internet addiction test: a validation study. Cyberpsychol. Behav. Soc. Netw. 15, 534–542. doi: 10.1089/cyber.2011.0616

Bauer, D. J., and Curran, P. J. (2005). Probing interactions in fixed and multilevel regression: inferential and graphical techniques. Multi. Behav. Res. 40, 373–400. doi: 10.1207/s15327906mbr4003_5

Bernardi, S., and Pallanti, S. (2009). Internet addiction: a descriptive clinical study focusing on comorbidities and dissociative symptoms. Compr. Psychiatry 50, 510–516. doi: 10.1016/j.comppsych.2008.11.011

Biby, E. L. (1998). The relationship between body dysmorphic disorder and depression, self-esteem, somatization, and obsessive-compulsive disorder. J. Clin. Psychol. 54, 489–499. doi: 10.1002/(sici)1097-4679(199806)54:4<489::aid-jclp10<3.0.co;2-b

Block, J. J. (2008). Issues for DSM-V: internet addiction. Am. J. Psychiatry 165, 306–307. doi: 10.1176/appi.ajp.2007.07101556

Byrne, B. M. (2016). Structural Equation Modeling With AMOS: Basic Concepts, Applications and Programming. London: Routledge.

Cao, H., Sun, Y., Wan, Y., Hao, J., and Tao, F. (2011). Problematic internet use in Chinese adolescents and its relation to psychoso- matic symptoms and life satisfaction. BMC Public Health 11:802. doi: 10.1186/1471-2458-11-802

Carli, V., Durkee, T., Wasserman, D., Hadlaczky, G., Despalins, R., Kramarz, E., et al. (2013). The association between pathological internet use and comorbid psychopathology: a systematic review. Psychopathology 46, 1–13. doi: 10.1159/000337971

Carlson, G. A. (2000). The challenge of diagnosing depression in childhood and adolescence. J. Affect. Disord. 61, S3–S8. doi: 10.1016/s0165-0327(00)00283-4

Cecilia, M. R., Mazza, M., Cenciarelli, S., Grassi, M., and Cofini, V. (2013). The relationshipbetween compulsive behavior and internet addiction. Styles Commun. 5, 24–31.

Cerniglia, L., Guicciardi, M., Sinatra, M., Macis, L., Simonelli, A., and Cimino, S. (2019). The use of digital technologies, impulsivity and psychopathological symptoms in adolescence. Behav. Sci. 9:82. doi: 10.3390/bs9080082

Derogatis, L. R. (1994). Symptom Checklist-90-R (SCL-90-R): Administration, Scoring and Proce- dures Manual , 3rd Edn. Minneapolis, MN: National Computer Systems.

Dong, G., Lu, Q., Zhou, H., and Zhao, X. (2011). Precursor or sequela: pathological disorders in people with Internet addiction disorder. PLoS One 6:e14703. doi: 10.1371/journal.pone.0014703

Durkee, T., Carli, V., Floderus, B., Wasserman, C., Sarchiapone, M., Apter, A., et al. (2016). Pathological internet use and risk-behaviors among European adolescents. Int. J. Environ. Res. Public Health 13, 1–17. doi: 10.3390/ijerph13030294

Fava, G. A., McEwen, B. S., Guidi, J., Gostoli, S., Offidani, E., and Sonino, N. (2019). Clinical characterization of allostatic overload. Psychoneuroendocrinology 108, 94–101. doi: 10.1016/j.psyneuen.2019.05.028

Feng, Y., Ma, Y., and Zhong, Q. (2019). ‘The relationship between adolescents’ stress and internet addiction: a mediated-moderation model’. Front. Psychol. 10:2248. doi: 10.3389/fpsyg.2019.02248

Fırat, S., Gül, H., Sertçelik, M., Gül, A., Gürel, Y., and Kılıç, B. G. (2018). The relationship between problematic smartphone use and psychiatric symptoms among adolescents who applied to psychiatry clinics. Psychiatry Res. 270, 97–103. doi: 10.1016/j.psychres.2018.09.015

Fox, S., and Duggan, M. (2013). Health Online, 2013. Washington, D.C: Pew Research Center.

García-Oliva, C., and Piqueras, J. A. (2016). Experiential avoidance and technological addictions in adolescents. J. Behav. Addict. 5, 293–303. doi: 10.1556/2006.5.2016.041

Gonzalez-Bueso, V., Santamaria, J. J., Fernandez, D., Merino, L., Montero, E., and Riba, J. (2018). Association between internet gaming disorder or pathological video-game use and comorbid psychopathology: a comprehensive review. Int. J. Environ. Res. Public Health 15:668. doi: 10.3390/ijerph15040668

Griffiths, M. (2000). Does internet and computer addiction exist? Some case study evidence. Cyberpsychol. Behav. 3, 211–218. doi: 10.1089/109493100316067

Griffiths, M. D., and Meredith, A. (2009). Videogame addiction and its treatment. J. Contemp. Psychotherapy 39, 247–253. doi: 10.1007/s10879-009-9118-4

Gundogar, A., Bakim, B., Ozer, O., and Karamustafalioglu, O. (2012). P-32 – The association between internet addiction, depression and ADHD among high school students. Eur. Psychiatry 27:1. doi: 10.1016/s0924-9338(12)74199-8

Hayes, A. F. (2012). PROCESS: A Versatile Computational Tool for Observed Variable Mediation, Moderation, and Conditional Process Modeling [White Paper] .

Hayes, A. F. (2013). An Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach . New York, NY: Guilford Press.

Hayes, A. F. (2017). An Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach , 2nd Edn. New York, NY: Guilford.

Hayes, S. C., Wilson, K. G., Gifford, E. V., Follette, V. M., and Strosahl, K. (1996). Experiential avoidance and behaviour disorder: a functional dimensional approach to diagnosis and treatment. J. Consul. Clin. Psychol. 64, 1152–1168. doi: 10.1037//0022-006x.64.6.1152

Ho, R. C., Zhang, M. W., Tsang, T. Y., Toh, A. H., Pan, F., and Lu, Y. (2014). The association between internet addiction and psychiatric co-morbidity: a meta-analysis. BMC Psychiatry 14:183. doi: 10.1186/1471-244X-14-183

Jang, K. S., Hwang, S. Y., and Choi, J. Y. (2008). Internet addiction and psychiatric symptoms among Korean adolescents. J. Sch. Health 78, 165–171. doi: 10.1111/j.1746-1561.2007.00279.x

Kline, R. B. (2008). Principles and Practice of Structural Equation Modeling , 2nd Edn. New York, NY: Guilford.

Ko, C.-H., Yen, J.-Y., Chen, C.-S., Chen, C.-C., and Yen, C.-F. (2008). Psychiatric comorbidity of Internet addiction in college students: an interview study. CNS Spectrums 13, 147–153. doi: 10.1017/s1092852900016308

Ko, C.-H., Yen, J.-Y., Yen, C.-F., Chen, C.-S., and Chen, C.-C. (2012). The association between Internet addiction and psychiatric disorder: a review of the literature. Eur. Psychiatry 27, 1–8. doi: 10.1016/j.eurpsy.2010.04.011

Kuss, D. J., Griffiths, M. D., and Binder, J. F. (2013). Internet addiction in students: prevalence and risk factors. Comput. Hum. Behav. 29, 959–966. doi: 10.1016/j.chb.2012.12.024

Kuss, D. J., Griffiths, M. D., Karila, L., and Billieux, J. (2014). Internet addiction: a systematic review of epidemiological research for the last decade. Curr. Pharm. Des. 20, 4026–4052. doi: 10.2174/13816128113199990617

Lan, C. M., and Lee, Y. H. (2013). The predictors of internet addiction behaviours for taiwanese elementary school students. Sch. Psychol. Int. 34, 648–657. doi: 10.1177/0143034313479690

Nakkas, C., Annen, H., and Brand, S. (2019). Somatization and coping in ethnic minority recruits. Milit. Med. 184, 11–12. doi: 10.1093/milmed/usz014

Naqvi, N. H., Rudrauf, D., Damasio, H., and Bechara, A. (2007). Damage to the insula disrupts addiction to cigarette smoking. Science 315, 531–534. doi: 10.1126/science.1135926

Noël, X., Brevers, D., and Bechara, A. (2013). A triadic neurocognitive approach to addiction for clinical interventions. Front. Psychiatry 4:179. doi: 10.3389/fpsyt.2013.00179

Nuutinen, T., Roos, E., Ray, C., Villberg, J., Valimaa, R., and Rasmussen, M. (2014). Computer use, sleep duration and health symptoms: a cross-sectional study of 15-year olds in three countries. Int. J. Public Health 59, 619–628. doi: 10.1007/s00038-014-0561-y

Phillips, J. G., Ogeil, R. P., and Blaszczynski, A. (2012). Electronic interests and behavioursassociated with gambling problems. Int. J. Ment. Health Addict. 10, 585–596. doi: 10.1007/s11469-011-9356-z

Potembska, E., Pawłowska, B., and Szymańska, J. (2019). Psychopathological symptoms in individuals at risk of Internet addiction in the context of selected demographic factors. Ann. Agric. Environ. Med. 26, 33–38. doi: 10.26444/aaem/81665

Robbins, T. W., and Clark, L. (2015). Behavioral addictions. Curr. Opin. Neurobiol. 30, 66–72. doi: 10.1016/j.conb.2014.09.005

Sasmaz, T., Oner, S., Kurt, A. O., Yapici, G., Yazici, A. E., Bugdayci, R., et al. (2014). Prevalence and risk factors of internet addiction in high school students. Eur. J. Public Health 24, 15–20. doi: 10.1093/eurpub/ckt051

Shapira, N. A., Goldsmith, T. D., Keck, P. E., Khosla, U. M., and McElroy, S. L. (2000). Psychiatric features of individuals with problematic internet use. J. Affect. Disord . 57, 267–272. doi: 10.1016/s0165-0327(99)00107-x

Shapira, N. A., Lessig, M. C., Goldsmith, T. D., Szabo, S. T., Lazoritz, M., Gold, M. S., et al. (2003). Problematic internet use: proposed classification and diagnostic criteria. Depress. Anxiety 17, 207–216. doi: 10.1002/da.10094

Subic-Wrana, C., Beutel, M. E., Knebel, A., and Lane, R. D. (2010). Theory of mind and emotional awareness deficits in patients with somatoform disorders. Psychosom. Med. 72, 404–411. doi: 10.1097/PSY.0b013e3181d35e83

Sung, J., Lee, J., Noh, H., Park, Y. S., and Ahn, E. J. (2013). Associations between the risk of internet addiction and problem behaviors among Korean adolescents. Korean J. Fam. Med. 34, 115–122. doi: 10.4082/kjfm.2013.34.2.115

Tamura, H., Nishida, T., Tsuji, A., and Sakakibara, H. (2017). Association between excessive use of mobile phone and insomnia and depression among Japanese adolescents. Int. J. Environ. Res. Public Health 14, 1–11.

Tereshchenko, S., and Kasparov, E. (2019). Neurobiological risk factors for the development of internet addiction in adolescents. Behav. Sci. 9:62. doi: 10.3390/bs9060062

Verdejo-García, A., and Bechara, A. (2009). A somatic-marker theory of addiction. Neuropharmacology 56, 48–62. doi: 10.1016/j.neuropharm.2008.07.035

Wei, H. T., Chen, M. H., Huang, P. C., and Bai, Y. M. (2012). The association between online gaming, social phobia, and depression: an internet survey. BMC Psychiatry 12:92. doi: 10.1186/1471-244X-12-92

Wei, L., Zhang, S., Turel, O., Bechara, A., and He, Q. (2017). A tripartite neurocognitive model of internet gaming disorder. Front. Psychiatry 8:285. doi: 10.3389/fpsyt.2017.00285

Yang, C. K. (2001). Sociopsychiatric characteristics of adolescents who use computers to excess. Acta Psychiatr. Scand. 104, 217–222. doi: 10.1034/j.1600-0447.2001.00197.x

Yang, C. K., Choe, B. M., Baity, M., Lee, J. H., and Cho, J. S. (2005). SCL-90-R and 16PF profiles of senior high school students with excessive internet use. Can. J. Psychiatry 50, 407–414. doi: 10.1177/070674370505000704

Yao, B., Han, W., Zeng, L., and Guo, X. (2013). Freshman year mental health symptoms and level of adaptation as predictors of internet addiction: a retrospective nested case-control study of male Chinese college students. Psychiatry Res. 210, 541–547. doi: 10.1016/j.psychres.2013.07.023

Yen, J. Y., Ko, C. H., Yen, C. F., Chen, S. H., Chung, W. L., and Chen, C. C. (2008). Psychiatric symptoms in adolescents with Internet addiction: comparison with substance use. Psychiatry Clin. Neurosci. 62, 9–16. doi: 10.1111/j.1440-1819.2007.01770.x

Yoo, H. J., Cho, S. C., Ha, J., Yune, S. K., Kim, S. J., Hwang, J., et al. (2004). Attention deficit hyperactivity symptoms and Internet addiction. Psychiatry Clin. Neurosci. 58, 487–494.

Young, K. S. (1998). Internet addiction: the emergence of a new clinical disorder. CyberPsychol. Behav. 1, 237–244. doi: 10.1089/cpb.1998.1.237

Zboralski, K., Orzechowska, A., Talarowska, M., Darmosz, A., Janiak, A., Janiak, M., et al. (2009). The prevalence of computer and internet addiction among pupils. Postępy Higieny i Medycyny Doświadczalnej 63, 8–12.

Keywords : somatization, internet addiction, adolescent, moderation, obssessive-compulsive disorder

Citation: Zamboni L, Portoghese I, Congiu A, Carli S, Munari R, Federico A, Centoni F, Rizzini AL and Lugoboni F (2020) Internet Addiction and Related Clinical Problems: A Study on Italian Young Adults. Front. Psychol. 11:571638. doi: 10.3389/fpsyg.2020.571638

Received: 11 June 2020; Accepted: 21 October 2020; Published: 10 November 2020.

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Copyright © 2020 Zamboni, Portoghese, Congiu, Carli, Munari, Federico, Centoni, Rizzini and Lugoboni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Lorenzo Zamboni, [email protected]

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Mental Health Review Journal

ISSN : 1361-9322

Article publication date: 11 July 2018

Issue publication date: 15 August 2018

The purpose of this paper is to delineate the overall theoretical framework on the topic of internet addiction through the comprehensive narrative review to make readers aware of the conceptual growth and development in the respective field. The paper evolves theoretically from the historical foundation, phenomenology, clinical feature, etiological model to the treatment outcome of internet addiction. Multiple studies have been done in the field of mental health but dearth of work given head to toe theoretical overview for understanding of this trendsetter research area in mental health.

Design/methodology/approach

Extensive review of literature has been carried out to make a systematic layout for conceptual paper.

The internet has been a source of gratification for several behavioral addictions as well as psychiatric disorders. Mainly because of the lack of established diagnostic criteria and a dearth of large sample surveys, the prevalence of problematic internet use (PIU) in general population has not been established. Still, from all the consolidated data, PIU seems to have a male preponderance and manifests itself in late adulthood. Symptoms of PIU can easily be masked with signs of dependence, tolerance and withdrawal which is quite similar to the phenomenology of substance addiction. Psychiatric co-morbidities are more of a norm than the exception in case of PIU. Even though the clinical status of PIU is doubtful, still there is a significant demand for its treatment all over the world. Overall, the excessive use of internet has been strongly debated in literature from PIU to a positive addiction. Only time will tell how it affects our civilization as a phenomenon of evolutionary significance.

Originality/value

The paper is providing a general conceptual framework for internet addiction/PIU to enable readers to know about the topic in depth from the evolution of the concept to the recent developments in the area.

• Substance use disorder
• Internet addiction
• Behavioural addiction
• Problematic internet use (PIU)
• Psychiatric co-morbidity

Acknowledgements

Conflict of interest statement: the authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Bisen, S.S. and Deshpande, Y.M. (2018), "Understanding internet addiction: a comprehensive review", Mental Health Review Journal , Vol. 23 No. 3, pp. 165-184. https://doi.org/10.1108/MHRJ-07-2017-0023

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Internet Addiction: A Brief Summary of Research and Practice

Affiliation.

• 1 reSTART Internet Addiction Recovery Program, Fall City, WA 98024.
• PMID: 23125561
• PMCID: PMC3480687
• DOI: 10.2174/157340012803520513

Problematic computer use is a growing social issue which is being debated worldwide. Internet Addiction Disorder (IAD) ruins lives by causing neurological complications, psychological disturbances, and social problems. Surveys in the United States and Europe have indicated alarming prevalence rates between 1.5 and 8.2% [1]. There are several reviews addressing the definition, classification, assessment, epidemiology, and co-morbidity of IAD [2-5], and some reviews [6-8] addressing the treatment of IAD. The aim of this paper is to give a preferably brief overview of research on IAD and theoretical considerations from a practical perspective based on years of daily work with clients suffering from Internet addiction. Furthermore, with this paper we intend to bring in practical experience in the debate about the eventual inclusion of IAD in the next version of the Diagnostic and Statistical Manual of Mental Disorders (DSM).