Flying high? Is the playing ‘Flappy Bird’ excessively something to worry about?

The following blog is an expanded version of an article that first appeared in Nottingham Trent University’s Expert Opinion column

A few weeks ago I was introduced to the game Flappy Bird by my kids while celebrating the 80th birthday of their grandma. Within an hour, everyone – from the toddlers to the octogenarians – was playing it. Flappy Bird is another one of those free games that is very hard to put down once you start playing it. The game’s premise is so simple, almost banal – just keeping a bird flying by tapping one finger on the touch screen of a phone or tablet and guiding the bird between a series of pipes with gaps. For each gap in a pipe that the bird flies through, the player gets one point. Hitting or touching a pipe – or touching the ground – and it’s game over. Embarrassingly, I have yet to get into double figures. As one media commentator noted, it’s a game you love to hate – but end up just loving it!

Do a quick Google search on Flappy Bird and the one phrase that keeps coming up is that the game is “infuriatingly addictive” – and I couldn’t agree more. As soon as the game is over, the only way I can dissipate the feeling of frustration, annoyance, and anger of not doing very well is to play again immediately. For those that do well, they immediately want to play again to beat their high score. As one reviewer of the game noted:

“I was perusing the App Store, as one often does, when I noticed a new title sitting at the top of the free app chart. I decided to download it and take it for a spin as, if it is the most popular free app at the moment, it must at least be worth a look. From that point forward, that title – Flappy Bird – irritated the hell out of me and I couldn’t stop playing it…So, why can’t I stop playing? I’m actually not entirely sure myself. Maybe it’s that the game is incredibly easy to pick up and play. The one-finger gameplay is easy to grasp immediately but Flappy Bird is ridiculously difficult from the get go. Making it through a few sets of pipes feels like a humongous achievement as crashing is so much easier – it’s almost as if the game starts off at the highest difficulty level and just remains that way rather than gradually becoming more challenging. After a few hours playing Flappy Bird a double-digit score would probably be all you could expect. Then there is the ease in which you can start the next game immediately after failing your last effort. As soon as one game ends you can be into the next one in seconds making for an incredibly addictive experience. Each attempt is frustrating and you think you can do better next time, or at least prove that you’re not an idiot incapable of simply guiding a bird past some pipes… Despite all of its obvious and irritating flaws, Flappy Bird remains incredibly addictive and is certainly worth taking a few minutes to check out (although that few minutes may well turn into a few hours). I found that playing it was fun as well as frustrating and, if I’m being totally honest, the game fulfils its own mission entirely. It’s a simple arcade game but unique in its incredible difficulty, just as the developer’s clearly intended.

Earlier this month, the game’s creator, Dong Nguyen, withdrew Flappy Bird from online app stores – even though he was earning over 50,000 a day via in-app advertising revenue. He was quoted as saying:

“Flappy Bird was designed to play in a few minutes when you are relaxed. But it happened to become an addictive product. I think it has become a problem. To solve that problem, it’s best to take down Flappy Bird. It’s gone forever.”

As someone that has spent over 25 years researching into video game play, Flappy Bird is the latest in a long line of fun and deceptively simple games that someone can end up playing for hours on end. The game is gender-neutral and has a ‘moreish’ quality (a bit like chocolate in that it’s really hard just to eat one piece) and can fit in flexibly around what individuals do in their day-to-day life. Most simple games like Flappy Bird take up all the player’s cognitive ability because anyone playing on it has to totally concentrate on it. By being totally absorbed players can forget about everything else for a few minutes. This can be particularly appealing for players that want to use games as a way of temporarily forgetting about everything else that’s going on in their lives. One video game review I came across said:

“Flappy Bird is the latest weirdly addicting game to captivate mobile users. The reason is simple, if not straightforward. In the guise of a cartoonish time-waster, Flappy Bird offers some of the most punishing, hardcore gameplay you can imagine. And it’s sucking in players by the millions”.

Psychologically, casual games like Flappy Bird rely on both positive and negative reinforcement over speedy gameplay. I have noted that many games played via social networking sites that ‘freemium’ games are psychological ‘foot-in-the-door‘ techniques that lead a small minority of people to pay for games and/or game accessories that they may never have originally planned to buy before playing the game (akin to ‘impulse buying’ in other commercial environments). I’ve also argued that many casual games share similarities with gambling. On first look, games like Flappy Bird may not seem to have much connection to gambling, but the psychology is very similar. Even when games do not involve money, they introduce players to the principles and excitement of gambling. Small unpredictable rewards lead to highly engaged, repetitive behaviour. In a minority, this may lead to addiction. Basically, people keep responding in the absence of reinforcement hoping that another reward is just around the corner (a psychological principle rooted in operant conditioning and called the partial reinforcement extinction effect – something that is used to great effect in both slot machines and most video games).

Physiologically, these games are likely to increase dopamine levels when people are doing well whereas and failure will most likely cause an increase in noradrenaline. The interaction of two competing neurotransmitter systems is likely to keep players engaged in the game for periods longer than they originally intended. In short, the games are ingeniously simple, highly enjoyable, and (as some players describe them) “emotionally intoxicating”. I’ve only ever come across a few people that I would define as genuinely addicted to these games but all the ingredients are there to make it theoretically possible for almost anyone to be psychologically seduced by such games.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (2010). Online gambling, social responsibility and ‘foot-in-the-door techniques. i-Gaming Business, 62, 100-101.

Griffiths, M.D. (2010). Gaming in social networking sites: A growing concern? World Online Gambling Law Report, 9(5), 12-13.

Griffiths, M.D. (2012). The psychology of social gaming. i-Gaming Business Affiliate, August/September, 26-27.

Griffiths, M.D. (2013). Social gambling via Facebook: Further observations and concerns. Gaming Law Review and Economics, 17, 104-106.

Hall, C. (2013). Just how addictive are mobile games? Yahoo! News, October 18. Located at: http://uk.news.yahoo.com/how-addictive-are-mobile-games–143654713.html#P1M3U7a

Lagorio-Chaflkin, C. (2013). Candy Crush Saga’s intoxicating secret source. Inc.com, July 25. Located at: http://www.inc.com/christine-lagorio/candy-crush-secret-sauce.html

Rose, M. (2013). Chasing the Whales: Examining the ethics of free-to-play games. Gamasutra, July 9. Located at: http://www.gamasutra.com/view/feature/195806/chasing_the_whale_examining_the_.php?page=7

Face[book]ing the future: A brief look at social networking addiction

In many areas of behavioural addiction, there has been debate about whether some excessive behaviours should even be considered as genuine addictions (e.g., video game playing, internet use, sex, exercise, etc.) and the same debate holds for addiction to social networking. I recently published an editorial in the Journal of Addiction Research and Therapy examining the empirical research on the topic.

I have has operationally defined addictive behaviour as any behaviour that features what I believe to be the six core components of addiction (i.e., salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse). I have also argued that any behaviour (including social networking) that fulfils these six criteria can be operationally defined as an addiction.

Researchers have suggested that the excessive use of new technologies (and especially online social networking) may be particularly problematic to young people. In accordance with the biopsychosocial framework for the etiology of addictions, and the syndrome model of addiction (put forward by Dr. Howard Shaffer and colleagues in a 2004 issue of the Harvard Review of Psychiatry), it is claimed that those people addicted to using SNSs experience symptoms similar to those experienced by individuals who suffer from addictions to substances or other behaviours. This has significant implications for clinical practice because unlike other addictions, the goal of SNS addiction treatment cannot be total abstinence from using the internet per se it is an integral element of today’s professional and leisure culture. Instead, the ultimate therapy aim is controlled use of the internet and its respective functions, particularly social networking applications, and relapse prevention using strategies developed within cognitive-behavioural therapies.

To explain the formation of SNS addiction, Dr. Ofir Turel and Dr. Alexander Serenko recently summarized three overarching theoretical perspectives in a 2012 issue European Journal of Information Systems that may not be mutually exclusive:

• Cognitive-behavioral model: This model emphasizes that ‘abnormal’ social networking arises from maladaptive cognitions and is amplified by various environmental factors, and eventually leads to compulsive and/or addictive social networking.
• Social skill model: This model emphasizes that ‘abnormal’ social networking arises because people lack self-presentational skills and prefer virtual communication to face-to-face interactions, and it eventually leads to compulsive and/or addictive use of social networking.
• Socio-cognitive model: This model emphasises that ‘abnormal’ social networking arises due to the expectation of positive outcomes, combined with internet self-efficacy and deficient internet self-regulation eventually leads to compulsive and/or addictive social networking behavior.

Based on these three models, Dr. Haifeng Xu and Dr. Bernard Tan (in a 2012 paper presented at the Thirty Third International Conference on Information Systems) suggest that the transition from normal to problematic social networking use occurs when social networking is viewed by the individual as an important (or even exclusive) mechanism to relieve stress, loneliness, or depression. They contend that those who frequently engage in social networking are poor at socializing in real life. For these people, social media use provides such people continuous rewards (e.g. self-efficacy, satisfaction) and they end up engaging in the activity more and more, eventually leading to many problems (e.g., ignoring real life relationships, work/educational conflicts, etc.). The resulting problems may then exacerbate individuals’ undesirable moods. This then leads such individuals to engage in the social networking behaviour even more as a way of relieving dysphoric mood states. Consequently, when social network users repeat this cyclical pattern of relieving undesirable moods with social media use, the level of psychological dependency on social networking increases.

A behavioural addiction such as SNS addiction may thus be seen from a biopsychosocial perspective. Just like substance-related addictions, it would appear that in some individuals, SNS addiction incorporates the experience of the ‘classic’ addiction symptoms, namely mood modification (i.e., engagement in SNSs leads to a favourable change in emotional states), salience (i.e., behavioural, cognitive, and emotional preoccupation with the SNS usage), tolerance (i.e., ever increasing use of SNSs over time), withdrawal symptoms (i.e., experiencing unpleasant physical and emotional symptoms when SNS use is restricted or stopped), conflict (i.e., interpersonal and intrapsychic problems ensue because of SNS usage), and relapse (i.e., addicts quickly revert back to their excessive SNS usage after an abstinence period).

It is generally accepted that a combination of biological, psychological and social factors contributes to the etiology of addictions that may also hold true for SNS addiction. From this it follows that SNS addiction shares a common underlying etiological framework with other substance-related and behavioural addictions. However, due to the fact that the engagement in SNSs is different in terms of the actual expression of (internet) addiction (i.e., pathological use of SNSs rather than other internet applications), the phenomenon may be worthy of individual consideration, particularly when considering the potentially detrimental effects of both substance-related and behavioural addictions on individuals who experience a variety of negative consequences because of their addiction.

Research into social networking addiction has been relatively sparse. According to a recent book chapter that I published with Dr. Daria Kuss and Dr. Zsolt Demetrovics, the twenty or so empirical studies examining SNS addiction fall into one of four types: (i) self-perception studies of social networking addiction, (ii) studies of social networking addiction utilizing a social networking addiction scale, (iii) studies examining the relationship between social networking and other online addictions, and (iv) studies examining social networking addiction and interpersonal relationships. Our review noted that all the studies suffered from a variety of methodological limitations. Many of the studies attempted to assess SNS addiction, but mere assessment of addiction tendencies does not suffice to demarcate real pathology. Most of the study samples were generally small, specific, self-selected, convenient, and skewed with regards to young adults and female gender. This may have led to the very high addiction prevalence rates (up to 34%) reported in some studies as individuals from these socio-demographic groups are likely to be more heavy social networking users. Consequently, empirical studies need to ensure that they are assessing addiction rather than excessive use and/or preoccupation.

I have also published a couple of papers noting that for many researchers, Facebook addiction has become almost synonymous with social networking addiction. However, Facebook is just one of many websites where social networking can take place. Most of the scales that have been developed have specifically examined excessive Facebook use such as the Bergen Facebook Addiction Scale, the Facebook Addiction Scale, and the Facebook Intrusion Questionnaire, i.e., addiction to one particular commercial company’s service (i.e., Facebook) rather than the whole activity itself (i.e., social networking). The real issue here concerns what people are actually addicted to and what the new Facebook addiction tools are measuring.

For instance, Facebook users can play games like Farmville, can gamble on games like poker, can watch videos and films, and can engage in activities such as swapping photos or constantly updating their profile and/or messaging friends on the minutiae of their life. Therefore, ‘Facebook addiction’ is not synonymous with ‘social networking addiction’ – they are two fundamentally different things as Facebook has become a specific website where many different online activities can take place – and may serve different purposes to various users. What this suggests is that the field needs a psychometrically validated scale that specifically assesses ‘social networking addiction’ rather than Facebook use. In the aforementioned scales, social networking as an activity is not mentioned, therefore the scale does not differentiate between someone potentially addicted to Farmville or someone potentially addicted to constantly messaging Facebook friends.

Whether social networking addiction exists is debatable depending upon the definition of addiction used, but there is clearly emerging evidence that a minority of social network users experience addiction-like symptoms as a consequence of their excessive use. Studies endorsing only a few potential addiction criteria are not sufficient for establishing clinically significant addiction status. Similarly, significant impairment and negative consequences that discriminate addiction from mere abuse have (to date) generally not been assessed in published studies. Thus, future studies have great potential in addressing the emergent phenomenon of SNS addiction by means of applying better methodological designs, including more representative samples, and using more reliable and valid addiction scales so that current gaps in empirical knowledge can be filled.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (2012). Facebook addiction: Concerns, criticisms and recommendations. Psychological Reports, 110, 2, 518-520.

Griffiths, M.D. (2012). Gambling on Facebook? A cause for concern? World Online Gambling Law Report, 11(9), 10-11.

Griffiths, M.D. (2013). Social gambling via Facebook: Further observations and concerns. Gaming Law Review and Economics, 17, 104-106.

Griffiths, M.D. (2013) Social networking addiction: Emerging themes and issues. Journal of Addiction Research and Therapy, 4: e118. doi: 10.4172/2155-6105.1000e118.

Griffiths, M.D. & Kuss, D.J. (2011). Adolescent social networking: Should parents and teachers be worried? Education and Health, 29, 23-25.

Griffiths, M.D., Kuss, D.J. & Demetrovics, Z. (2014). Social networking addiction: An overview of preliminary findings. In K. Rosenberg & L. Feder (Eds.), Behavioral Addictions: Criteria, Evidence and Treatment (pp.119-141). New York: Elsevier.

Kuss, D.J. & Griffiths, M.D. (2011). Online social networking and addiction: A literature review of empirical research. International Journal of Environmental and Public Health, 8, 3528-3552.

Kuss, D.J. & Griffiths, M.D. (2011). Excessive online social networking: Can adolescents become addicted to Facebook? Education and Health, 29. 63-66.

Shaffer, H.J., LaPlante, D.A., LaBrie, R.A., Kidman, R.C., Donato, A.N., & Stanton, M.V. (2004). Toward a syndrome model of addiction: Multiple expressions, common etiology. Harvard Review of Psychiatry, 12, 367-374.

Turel, O. & Serenko, A. (2012). The benefits and dangers of enjoyment with social networking websites. European Journal of Information Systems, 21, 512-528.

Xu, H. & Tan, B.C.Y. (2012). Why Do I Keep Checking Facebook: Effects of Message Characteristics On the Formation of Social Network Services Addiction (http://elibrary.aisnet.org/Default.aspx?url=http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1216&context=icis2012)

Carry on screening: A brief look at Internet Gaming Disorder

In this month’s issue of the Neuropsychiatry journal, I – and my research colleagues (Dr. Daniel King and Dr. Zsolt Demetrovics) – published a paper arguing that Internet Gaming Disorder needs a unified approach to assessment. Over the last 15 years, research into various online addictions has greatly increased. Prior to the publication of the fifth edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in 2013, there had been some debate as to whether ‘internet addiction’ should be introduced into the text as a separate disorder. Alongside this, there has also been debate as to whether those researching in the online addiction field should be researching generalized internet use and/or the potentially addictive activities that can be engaged on the internet (e.g., gambling, video gaming, sex, shopping, etc.)

Following these debates, the Substance Use Disorder Work Group (SUDWG) recommended that the DSM-5 include a sub-type of problematic internet use (i.e., internet gaming disorder [IGD]) in Section 3 (‘Emerging Measures and Models’) as an area that needed future research before being included in future editions of the DSM. According to Dr. Nancy Petry and Dr. Charles O’Brien writing in a 2013 issue of Addiction, IGD will not be included as a separate mental disorder until the (i) defining features of IGD have been identified, (ii) reliability and validity of specific IGD criteria have been obtained cross-culturally, (iii) prevalence rates have been determined in representative epidemiological samples across the world, and (iv) etiology and associated biological features have been evaluated.

Although there is now a rapidly growing literature on pathological video gaming, one of the key reasons that IGD was not included in the main text of the DSM-5 was that the SUDWG concluded that no standard diagnostic criteria were used to assess gaming addiction across these many studies. A 2013 overview of instruments assessing problematic gaming by my colleagues and I in Clinical Psychology Review reported that 18 different screening instruments had been developed, and that these had been used in 63 quantitative studies comprising 58,415 participants. This comprehensive review identified both strengths and weaknesses of these instruments.

The main strengths of the instrumentation included the: (i) the brevity and ease of scoring, (ii) excellent psychometric properties such as convergent validity and internal consistency, and (iii) robust data that will aid the development of standardized norms for adolescent populations. However, the main weaknesses identified in the instrumentation included: (i) core addiction indicators being inconsistent across studies, (iii) a general lack of any temporal dimension, (iii) inconsistent cut-off scores relating to clinical status, (iv) poor and/or inadequate inter-rater reliability and predictive validity, and (v) inconsistent and/or dimensionality. It has also been noted by a number of authors that the criteria for IGD assessment tools are theoretically based on a variety of different potentially problematic activities including substance use disorders, pathological gambling, and/or other behavioral addiction criteria. There are also issues surrounding the settings in which diagnostic screens are used as those used in clinical practice settings may require a different emphasis that those used in epidemiological, experimental and neurobiological research settings.

Video gaming that is problematic, pathological and/or addictive (i.e., IGD) lacks a widely accepted definition. In a recent book chapter (in the 2014 book Behavioral Addictions: Criteria, Evidence and Treatment edited by Dr. Ken Rosenberg and Dr. Laura Feder), I and some of my Hungarian colleagues argued that some researchers consider video games as the starting point for examining the characteristics of this specific disorder, while others consider the internet as the main platform that unites different addictive internet activities, including online games. Recent studies have made an effort to integrate both approaches Consequently, IGD can either be viewed as a specific type of video game addiction, or as a variant of internet addiction, or as an independent diagnosis.

As I argued in one of my previous blogs, although all addictions have particular and idiosyncratic characteristics, they share more commonalities than differences (i.e., salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse), and this likely reflects a common etiology of addictive behavior. Consequently, online game addiction may be viewed as a specific type of video game addiction. Similarly, Dr. G. Porter and colleagues in a 2010 issue of the Australian and New Zealand Journal of Psychiatry, do not differentiate between problematic video game use and problematic online game use. They conceptualized problematic video game use as excessive use of one or more video games resulting in a preoccupation with and a loss of control over playing video games, and various negative psychosocial and/or physical consequences. However, unlike my conceptualization of gaming addiction, their criteria for problematic video game use does not include other features usually associated with dependence or addiction, (e.g., tolerance, physical symptoms of withdrawal), as they say there is no clear evidence that problematic gaming is associated with such phenomena. Researchers such as Dr. Kimberley Young view online gaming addiction as a sub-type of internet addiction and that the internet itself provides situation-specific characteristics that facilitate gaming becoming problematic and/or addictive.

In a 2010 issue of Computers in Human Behavior, Dr. M.G. Kim and Dr. J. Kim’s [11] proposed a Problematic Online Game Use (POGU) model that takes a more integrative approach and claims that neither of the approaches outlined above adequately capture the unique features of online games such as Massively Multiplayer Online Role Playing Games (MMORPGs). They argue that the internet is just one channel where people may access the content they want (e.g., gambling, shopping, sex, etc.) and that such users may become addicted to the particular content rather than the channel itself. This is analogous to the argument that I made over 15 years ago in a number of different papers that there is a fundamental difference between addiction to the internet, and addictions on the internet. However, MMORPGs differ from traditional stand-alone video games as there are social and/or role-playing dimension that allow interaction with other gamers.

The POGU model resulted in five underlying dimensions of addictive gameplay (i.e., euphoria, health problems, conflict, failure of self-control, and preference of virtual relationship). I also support the integrative approach and stress the need to include all types of online games in addiction models in order to make comparisons between genres and gamer populations possible (such as those who play online Real-Time Strategy (RTS) games and online First Person Shooter (FPS) games in addition to the widely researched MMORPG players). The POGU model comprises six dimensions (i.e., preoccupation, overuse, immersion, social isolation, interpersonal conflicts, and withdrawal).

Irrespective of approach or model, the components and dimensions that comprise online gaming addiction outlined above are very similar to the IGD criteria in Section 3 of the DSM-5. For instance, my six addiction components directly map onto the nine proposed criteria for IGD (of which five or more need to be endorsed and resulting in clinically significant impairment). More specifically: (1) preoccupation with internet games [salience]; (2) withdrawal symptoms when internet gaming is taken away [withdrawal]; (3) the need to spend increasing amounts of time engaged in internet gaming [tolerance], (4) unsuccessful attempts to control participation in internet gaming [relapse/loss of control]; (5) loss of interest in hobbies and entertainment as a result of, and with the exception of, internet gaming [conflict]; (6) continued excessive use of internet games despite knowledge of psychosocial problems [conflict]; (7) deception of family members, therapists, or others regarding the amount of internet gaming [conflict]; (8) use of the internet gaming to escape or relieve a negative mood [mood modification];  and (9) loss of a significant relationship, job, or educational or career opportunity because of participation in internet games [conflict].

The fact that IGD was included in Section 3 of the DSM-5 appears to have been well received by researchers and clinicians in the gaming addiction field (and by those individuals that have sought treatment for such disorders and had their experiences psychiatrically validated and feel less stigmatized). However, for IGD to be included in the section on ‘Substance-Related and Addictive Disorders’ along with ‘Gambling Disorder’, the gaming addiction field must unite and start using the same assessment measures so that comparisons can be made across different demographic groups and different cultures.

For epidemiological purposes, Dr. B. Koronczai and colleagues in a 2011 issue of Cyberpsychology, Behavior and Social Networking, asserted that the most appropriate measures in assessing problematic online use (including internet gaming) should meet six requirements. Such an instrument should have: (i) brevity (to make surveys as short as possible and help overcome question fatigue); (ii) comprehensiveness (to examine all core aspects of IGD as possible); (iii) reliability and validity across age groups (e.g., adolescents vs. adults); (iv) reliability and validity across data collection methods (e.g., online, face-to-face interview, paper-and-pencil); (v) cross-cultural reliability and validity; and (vi) clinical validation. It was also noted that an ideal assessment instrument should serve as the basis for defining adequate cut-off scores in terms of both specificity and sensitivity. To fulfill all these requirements, future research should adjust the currently used assessment tools to the newly accepted DSM-5 criteria and take much more efforts to reach and study clinical samples, which is an unequivocal shortcoming of both internet and gaming research.

In addition to further epidemiological and clinical research, further research is also needed on the neurobiology of IGD. A systematic review of 18 neuroimaging studies examining internet addiction and IGD by Dr. Daria Kuss and Griffiths in a 2012 issue of Brain Sciences noted that:

“These studies provide compelling evidence for the similarities between different types of addictions, notably substance-related addictions and Internet and gaming addiction, on a variety of levels. On the molecular level, Internet addiction is characterized by an overall reward deficiency that entails decreased dopaminergic activity. On the level of neural circuitry, Internet and gaming addiction lead to neuroadaptation and structural changes that occur as a consequence of prolonged increased activity in brain areas associated with addiction. On a behavioral level, Internet and gaming addicts appear to be constricted with regards to their cognitive functioning in various domains” (p.347).

The good news is that research in the gaming addiction field does appear to be reaching an emerging consensus. We noted in our 2013 Clinical Psychology Review paper that across many different studies, IGD is commonly defined by (a) withdrawal, (b) loss of control, and (c) conflict. However, it is critical that a unified approach to assessment of IGD is urgently needed as this is the only way that there will be a strong empirical basis for IGD to be included in the next DSM.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders – Text Revision (Fifth Edition). Washington, D.C.: Author.

Demetrovics, Z., Urbán, R., Nagygyörgy, K., Farkas, J., Griffiths, M. D., Pápay, O., . . . Oláh, A. (2012). The development of the Problematic Online Gaming Questionnaire (POGQ). PLoS ONE, 7(5), e36417.

Griffiths, M.D. (2000). Internet addiction – Time to be taken seriously? Addiction Research, 8, 413-418.

Griffiths, M. D. (2005). A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 10(4), 191-197.

Griffiths, M.D., King, D.L. & Demetrovics, Z. (2014). DSM-5 Internet Gaming Disorder needs a unified approach to assessment. Neuropsychiatry, under review.

Griffiths, M.D., Kuss, D.J. & King, D.L. (2012). Video game addiction: Past, present and future. Current Psychiatry Reviews, 8, 308-318.

Kim, M. G., & Kim, J. (2010). Cross-validation of reliability, convergent and discriminant validity for the problematic online game use scale. Computers in Human Behavior, 26(3), 389-398.

King, D. L., Delfabbro, P. H., Griffiths, M. D., & Gradisar, M. (2011). Assessing clinical trials of Internet addiction treatment: A systematic review and CONSORT evaluation. Clinical Psychology Review, 31, 1110-1116.

King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2012). Cognitive-behavioral approaches to outpatient treatment of Internet addiction in children and adolescents. Journal of Clinical Psychology, 68, 1185-1195.

King, D.L., Haagsma, M.C.,Delfabbro, P.H.,Gradisar, M.S.^, Griffiths, M.D. (2013). Toward a consensus definition of pathological video-gaming: A systematic review of psychometric assessment tools. Clinical Psychology Review, 33, 331-342.

Koronczai, B., Urban, R., Kokonyei, G., Paksi, B., Papp, K., Kun, B., . . . Demetrovics, Z. (2011). Confirmation of the three-factor model of problematic internet use on off-line adolescent and adult samples. Cyberpsychology, Behavior and Social Networking, 14, 657–664.

Kuss, D.J. & Griffiths, M.D. (2012). Internet and gaming addiction: A systematic literature review of neuroimaging studies. Brain Sciences, 2, 347-374.

Kuss, D.J., Griffiths, M.D., Karila, L. & Billieux, J. (2013).  Internet addiction: A systematic review of epidemiological research for the last decade. Current Pharmaceutical Design, in press.

Pápay, O., Nagygyörgy, K., Griffiths, M.D. & Demetrovics, Z. (2014). Problematic online gaming. In K. Rosenberg & L. Feder (Eds.), Behavioral Addictions: Criteria, Evidence and Treatment. New York: Elsevier.

Petry, N.M., & O’Brien, C.P. (2013). Internet gaming disorder and the DSM-5. Addiction, 108, 1186–1187.

Porter, G., Starcevic, V., Berle, D., & Fenech, P. (2010). Recognizing problem video game use. The Australian and New Zealand Journal of Psychiatry, 44, 120-128.

Young, K. S. (1998). Internet addiction: The emergence of a new clinical disorder. Cyberpsychology and Behavior, 1, 237-244.

No time for the crime: Excessive adolescent video game playing, social networking and crime reduction

On Sunday February 9, 1964, The Beatles made their debut on US television. Their appearance on the Ed Sullivan Show drew an estimated audience of 73 million people. One of the most quoted consequences associated with this particular show was that between 8pm and 9pm when the show was aired, a number of news reports claimed that there was no reported incidence of juvenile crime across America during the time of the broadcast.  The editor of Newsweek, B.F. Henry, went as far as to claim that “there wasn’t so much as a hubcap stolen” during the hour that The Beatles were on the show.

This apocryphal tale, at the very least, shows the apparent compelling logic in the argument that when an activity is so engrossing it has the capacity to stop people engaging in other types of activity such as crime. Inspired by a speculative blog post on the topic, my friend and research colleague Dr. Mike Sutton failed to disconfirm what Dr. Sutton and I have called the Crime Substitution Hypothesis. We recently published a small paper in the journal Education and Health that examined the extent to which popular youth activity (namely video gaming and social networking) may be having an effect on youth offending and victimization.

Young people’s use of technology (the so called ‘screenagers’ and ‘digital natives’) has increased greatly over the last two decades and a significant proportion of daily time is spent in front of various screen interfaces most notably videogames, mobile phones (e.g., SMS) and the internet (e.g., social networking sites like Bebo, Facebook). These ‘digital natives’ have never known a world without the internet, mobile phones and interactive television, and are therefore tech-savvy, have no techno-phobia, and very trusting of these new technologies.

One of the most empirically researched areas is in the area of adolescent video gaming. Negative consequences of gaming have included addiction, increased aggression, and a variety of medical consequences, such as repetitive strain injuries, obesity, and photosensitive epilepsy. There is certainly evidence that when taken to excess, videogame playing can in some cases be addictive, especially online videogame playing where the game never pauses or ends, and has the potential to be a 24/7 activity. However, there are many reported benefits that adolescents can get from playing videogames. These can be educational, social and/or therapeutic.

Another positive benefit of playing video games along with activities like social networking may be the capacity to reduce youth crime. The reason why videogames may have implications for crime reduction is their use as ‘distractors’ (such as in the role of pain management). The reasoning is that ‘distractor tasks’ consume some degree of the attentional capacity that would otherwise be devoted to pain perception. I have noted in a number of my academic papers that the main reasons that videogames make good distractors are because they:

• Are likely to engage much of a person’s individual active attention because of the cognitive and motor activity required.
• Allow the possibility to achieve sustained achievement because of the level of difficulty (i.e. challenge) of most games during extended play.
• Appear to appeal most to adolescents

For instance, one study reported the case of an eight-year-old boy with neurodermatitis being given a handheld videogame to prevent him from picking at his face. Where previous treatments had failed, the use of the game kept his hands occupied and within two weeks the affected area had healed. A number of studies have demonstrated that videogames can provide cognitive distraction for children undergoing chemotherapy. All these studies have reported that distracted child patients report less nausea after treatment (when compared with control groups), and that playing videogames reduced the amount of painkillers the children needed during treatment. The very reasons why video games may be of benefit therapeutically may also be applied to video games in a crime reduction context (i.e., the playing of video games is so cognitively distracting that that there is little time to do or think about anything else).

Consequently, there is a developing school of thought arguing that peoples’ participation (especially excessive use) in video gaming and social networking may be contributory factors that may partly explain the fall in crime rates in recent years. For instance, the economist Larry Katz was quoted in a 2010 issue of The Economist suggesting that the playing of video games may be playing a role in crime reduction. Katz’ reasoning is simple – keeping people busy keeps them out of trouble. There appears to be some statistical support for such a hypothesis as the decrease in US crime rates appears to show an inverse correlational relationship with increased sales of video game consoles and video games. Clearly this correlational evidence should be treated with caution as it says nothing about causation. However, it does provide a hypothesis that could be the subject of future empirical testing.

Could the rise in video game playing and social networking be a major cause of what criminologists claim is an unfathomable drop in crime, and if not, then why not? Routine Activity Theory predicts that if a substantial numbers of young people are not on the streets either as victims or offenders then overall high volume ‘crime opportunities’ would diminish, resulting in an overall drop in high volume crime rates. We have no idea yet whether what we might call the ‘crime substitution hypothesis’ is plausible. Therefore, in our recent paper, Dr. Sutton and I set out some ideas that support it as something possibly worthy of further exploration.

As highlighted above, research suggests some young people are spending many hours playing video games or social networking. Research also suggests that video games can be engrossing, addictive and in some cases compulsive. Additionally, research has failed to establish that violent media is either a necessary or sufficient condition for causing crime. Therefore, taking a Routine Activity Approach, it would seem that an increase in video gaming might feasibly lead to a rise in the illicit market for stolen computers and games consoles. However, there might be fewer thieves to supply it if:

• Fewer potential offenders are getting addicted to opiates and other drugs, and/or misusing alcohol out of boredom because they have escaped boredom in the real world by entering the more exciting world of cyberspace to play and interact with others.
• Potential offenders and victims are gaming excessively and/or compulsively checking Facebook and/or other social networking sites.
• The game players and other ‘netizens’ are playing at home so (a) fewer potential offenders on the streets and fewer potential victims, and (b) houses are occupied for longer and so less susceptible to burglary.
• Immersion and gaming prowess and reputation may be sufficient substitutes for the same things in the offline (real) world
• The Internet allows more people to work from home so teleworking may reduce the pool of “available” victims on the street and also ensure fewer homes are empty during the day.

The evidence provided for the ‘crime substitution hypothesis’ in our paper was anecdotal and/or correlational in nature but we would argue that this would provide a fruitful avenue for further research. Such research into ‘crime substitution’ and gaming/social networking might involve: (i) measuring time spent gaming and social networking by groups that empirical research predicts are at greater risk of becoming offenders, (ii) conducting ethnographic studies with young people to gauge whether, and if so to what extent, gaming and social networking are used as a substitute for risky activities in the offline (real) world, and do this in relation to both potential offending and victimization, (iii) examining issues of offline and online peer status and how this may impact on consequent behaviour (including criminal activity), and (iv) further examining the correlation between console and game sales – and any data on playing time and type of games – with the general crime trend over the past 20 years.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Cole, H. & Griffiths, M.D. (2007). Social interactions in Massively Multiplayer Online Role-Playing gamers. CyberPsychology and Behavior, 10, 575-583.

De Freitas, S. & Griffiths, M.D. (2008). The convergence of gaming practices with other media forms: what potential for learning? A review of the literature. Learning, Media and Technology, 33, 11-20.

Griffiths, M.D. (2005). Video games and health. British Medical Journal, 331, 122-123.

Griffiths, M.D. (2005b). The therapeutic value of videogames. In Goldstein J. & Raessens J. (eds.) Handbook of Computer Game Studies (pp. 161-171). Boston: MIT Press.

Griffiths, M.D. (2008). Internet and video-game addiction. In C. Essau (Ed.), Adolescent Addiction: Epidemiology, Assessment and Treatment (pp.231-267).  San Diego: Elselvier.

Griffiths, M.D. (2010). Trends in technological advance: Implications for sedentary behaviour and obesity in screenagers. Education and Health, 28, 35-38.

Griffiths, M.D. & Kuss, D. (2011). Adolescent social networking: Should parents and teachers be worried? Education and Health, 29, 23-25.

Griffiths, M.D. & Sutton, M. (2013). Proposing the Crime Substitution Hypothesis: Exploring the possible causal relationship between excessive adolescent video game playing, social networking and crime reduction. Education and Health, 31, 17-21.

Kuss, D.J. & Griffiths, M.D. (2011). Online social networking and addiction: A literature review of empirical research. International Journal of Environmental and Public Health, 8, 3528-3552.

Kuss, D.J. & Griffiths, M.D. (2011). Excessive online social networking: Can adolescents become addicted to Facebook? Education and Health, 29. 63-66.

Kuss, D.J. & Griffiths, M.D. (2012). Online gaming addiction in adolescence: A literature review of empirical research. Journal of Behavioral Addictions, 1, 3-22.

Sutton, M (2010) Routine Activities Theory, the Internet and the 15-Year crime drop. Criminology: The Blog of Mike Sutton. Best Thinking: http://www.bestthinking.com/thinkers/science/social_sciences/sociology/mike-sutton?tab=blog&blogpostid=9634,9634

Stats entertainment (Part 2): A 2013 review of my personal blog

My last blog of 2013 was not written by me but was prepared by the WordPress.com stats helper. I thought a few of you might be interested in the kind of person that reads my blogs. I also wanted to wish all my readers a happy new year and thank you for taking the time to read my posts.

Here’s an excerpt:

The Louvre Museum has 8.5 million visitors per year. This blog was viewed about 860,000 times in 2013. If it were an exhibit at the Louvre Museum, it would take about 37 days for that many people to see it.

Click here to see the complete report.

Character formation: Another look at addiction to buying virtual in-game items

I was recently interviewed at length by Mike Rose for an article he published on the Gamasutra website entitled ‘Chasing the Whale’ that examined the ethics and sometimes addicting nature of free-to-play games. The article began with the story of Chris, a man in his mid-20s who played a lot of the game Team Fortress 2 (TF2). While playing TF2 he started to buy virtual items from the online store to use in-game (such as keys to open in-game crates). After opening some of the crates, Chris would share the online booty with other online gamers and “keep the good stuff” for himself. Chris got social benefits from giving away some of the virtual items to other players and this alone was worth paying real money for. Within half a year of buying his first virtual item, he ended up spending all the money he had:

“I’d use birthday money, I’d eat cheaper lunches, I’d ask my wife to pay for dinner so I’d have a spare $10-$20 to spend in the store. Which does mean, I guess, that I was thinking about it even away from the game. [After buying my first ‘unusual’ item marked with a purple seal] I had this unbeatable rush of adulation and excitement. For someone who didn’t get out much I was on cloud nine. And at that point things changed. I started chasing that high. My savings got wiped out pretty quickly – although it should be noted that at the time I didn’t have much put away to begin with. The real trouble wasn’t that it cleaned out my bank account, but that it put me in a really delicate situation. With no savings and every dollar not spent on food, shelter, or utilities going to digital hats, any unexpected expense became a really big deal.It got so bad that at one point Steam actually blocked my credit card, thinking I was some sort of account scammer [playing a] stupid game with fake hats. And like any addicted user, my social element didn’t help – most of my outside-of-work contacts were people I just played TF2 with.

At work I just wanted to be uncrating things, and when I was uncrating things I just wanted to see better results. [This then affected the relationship with my wife]. I’ve never really been addicted to anything else, so I can’t say for certain whether a ‘real’ addiction would be stronger. I would say that it felt akin to what I’d expect a compulsive gambling addiction would feel like – social pressures reinforced a behavior that kept me searching for an adrenaline rush I’d never be able to recapture, even as it kept me from making progress in life. There were nights where I’d be up until 3am drinking beer and playing Team Fortress and chasing those silly hats with purple text, ignoring the gambler’s fallacy and swearing that if I dropped another $50 I’d be sure to win this time. Then I’d wake up the next morning and see that I’d not only spent over a hundred dollars on digital hats, but failed my only objective by uncrating a bunch of junk”.

According to Rose’s account, it was on these mornings that Chris felt the worst. When the reality of what Chris had done hit him, he felt depressed and worthless. He told himself that he wouldn’t spend another penny on buying in-game items but just like a gambler, as soon as he got his next pay cheque, every last penny would go on buying new virtual items. To the game developers and operators, Chris is known colloquially as a ‘whale’ (i.e., one of the 1% of players that spends large amounts of money within free-to-play games and allows the gaming companies to make profits despite the fact that 99% of players don’t buy anything in-game). Chris said:

“I have to question whether a business model built on exploiting ‘whales’ like me isn’t somewhat to blame. Free-to-play games aren’t after everyone for a few dollars – they’re after weak people in vulnerable states for hundreds, if not thousands [of dollars]” 

Rose then started tracking down other ‘whales’ to get their stories. Many 9but by no means all) were similar to that of Chris. Rose questioned how many free-to-play game developers are building their profits on vulnerable players like Chris. More specifically he “pondered whether these ‘whale’ players are fully consenting to the hundreds and thousands of dollars that they are spending, or whether they are being manipulated and exploited by underhanded design that purposely aims to make the player feel like they simply have no choice”.

Rose’s own research highlighted that many whales (even those that had spent thousands of dollars) felt they had got their money’s worth (i.e., they had lots of fun playing and had simply bought their entertainment). Others said they were spending money they could afford and could stop any time they wanted to. Despite Chris being in the minority, Rose asserted that:

“A business model where even the smallest portion of players can find themselves losing control and essentially ruining their lives, is a model that must surely face scrutiny, whether on a industry or governmental level”.

To me, this has a large similarity with the gambling industry that has recently started to put social responsibility at the heart of its business model. Rose interviewed Ben Cousins, industry insider and an outspoken proponent of the free-to-play business model who said:

“I believe that the responsibility to control spending on any product or service lies with the consumer, unless there is some scientifically proven link to addiction as is the case with products and services like alcohol and gambling. When these links are established, I feel industries should self-govern first and if they fail to act responsibly, be subject to governmental control. I would personally like to see wide-ranging independent studies done before we jump to any conclusions about any negative psychological effects. When looking at a small sample size there is always going to be a lack of certainty in extrapolating that data to a larger population. I think if we see a broad proportion of the spending userbase reacting as they claim to have in these accounts, it’s easier to read this as the developers having discovered a damaging method of psychological consumer manipulation. When a very, very small proportion of the userbase react in this manner, while sad, it’s easier to read this as perhaps individual issues with those people which may be expressed in any number of negative ways, not just with spending in free-to-play games. I’m sure small numbers of very negative stories could be found for spending on almost any product or service”.

This line of reasoning was often used by the gambling industry 20 years ago and is currently being used by the video game industry more generally. I certainly believe that all forms of gaming (offline video gaming, social gaming, online gaming, etc.) will eventually embed player protection, harm minimization, and social responsibility into all of its products. In my interview for Rose’s article, I made a number of observations based on my many years studying both gambling and gaming. More specifically, I was quoted as saying:

“On first look, games like FarmVille may not seem to have much connection to gambling, but the psychology behind such activities is very similar. Even when games do not involve money, they introduce players to the principles and excitement of gambling. Companies like Zynga have been accused of leveraging the mechanics of gambling to build their empire. One element particularly key in encouraging gambling-like behaviour in free-to-play games is the act of random reinforcement – that is, the unpredictability of winning or getting other types of intermittent rewards. Small unpredictable rewards lead to highly engaged and repetitive behavior. In a minority of cases, this may lead to addiction. In those instances when there is no money changing hands, players “are learning the mechanics of gambling and there are serious questions about whether gambling with virtual money encourages positive attitudes towards gambling. The introduction of in-game virtual goods and accessories (that people pay real money for) was a psychological masterstroke. It becomes more akin to gambling, as social gamers know that they are spending money as they play with little or no financial return. The one question I am constantly asked is why people pay real money for virtual items in games like FarmVille. As someone who has studied slot machine players for over 25 years, the similarities are striking. The real difference between pure gambling games and some free-to-play games is the fact that gambling games allow you to win your money back, adding an extra dimension that can potentially drive revenues even further. The line between social free-to-play games and gambling is beginning to blur, bringing along with them various moral, ethical, legal, and social issues”.

Given my research background and my interest in gaming convergence, this is certainly an area I will be keeping a close eye on over the coming months and years.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (2008). Digital impact, crossover technologies and gambling practices. Casino and Gaming International, 4(3), 37-42.

Griffiths, M.D. (2010). Gaming in social networking sites: A growing concern? World Online Gambling Law Report, 9(5), 12-13.

Griffiths, M.D. (2011). Gaming convergence: Further legal issues and psychosocial impact. Gaming Law Review and Economics, 14, 461-464.

Griffiths, M.D. (2012). Gambling on Facebook? A cause for concern? World Online Gambling Law Report, 11(9), 10-11.

Griffiths, M.D. (2013). Social gambling via Facebook: Further observations and concerns. Gaming Law Review and Economics, 17, 104-106.

Griffiths, M.D., Kuss, D.J. & King, D.L. (2012). Video game addiction: Past, present and future. Current Psychiatry Reviews, 8, 308-318.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2010). The convergence of gambling and digital media: Implications for gambling in young people. Journal of Gambling Studies, 26, 175-187.

King, D.L., Haagsma, M.C.,Delfabbro, P.H.,Gradisar, M.S.^, Griffiths, M.D. (2013). Toward a consensus definition of pathological video-gaming: A systematic review of psychometric assessment tools. Clinical Psychology Review, 33, 331-342.

Kuss, D.J. & Griffiths, M.D. (2011). Online social networking and addiction: A literature review of empirical research. International Journal of Environmental and Public Health, 8, 3528-3552.

Kuss, D.J. & Griffiths, M.D. (2011). Excessive online social networking: Can adolescents become addicted to Facebook? Education and Health, 29. 63-66.

Kuss, D.J. & Griffiths, M.D. (2012). Online gaming addiction in adolescence: A literature review of empirical research. Journal of Behavioral Addictions, 1, 3-22.

Screenage kicks: A brief look at children’s use of information technology

The following blog is an expanded version of an article that was published on my university website as one of the regular ‘Expert Opinion’ columns.

Last week week, a lot of media coverage was given to research on young children’s IT use carried out by the US pressure group Common Sense Media and electronic learning experts VTech. Based on a survey of 1,463 parents of children aged under eight years, it was reported that 38% of children aged under two years of age had used iPhones and/or Kindles for playing games or watching films. The study, called ‘Zero to Eight: Children’s Media Use in America, 2013’ also reported that (i) one in three young children use a mobile phone or tablet before they could talk, (ii) 29% of children started using electronic gadgets as toddlers, (iii) children aged under two years spent an average of 15 minutes a day using electronic gadgets, and that (iv) children aged between two and four years spent average of two hours a day watching television. Are these findings a cause for concern?

Over the last decade I have taken part in many radio debates about the influence of information technology on the lives of children. Typically, I am invited onto such programmes to inject a hint of caution along the lines that engaging with technology is OK for children and adolescents in moderation, but that excess involvement with all things electronic may have a downside. To me this seems little more than common sense. As I repeatedly say to people, I am certainly not anti-technology, but pro-responsible the use of it.

Most people will be aware that computers were first introduced into schools in the early-1980s. Since then, information technology has been steadily growing in importance in education rising from a minority option to a compulsory subject in the National Curriculum. Over the years I have watched as many national initiatives have attempted to get children acquainted with IT as early as possible.

No-one can deny that IT skills should be an important part of children’s educational development. However, there seem to be endless numbers of questions that we need to answer before proceeding at the current pace. For instance, should the seemingly growing emphasis on IT be continued at the expense of more traditional classroom learning experiences? Is the idea to increase the amount of classroom work done on computers going to breed a new generation of children who have forgotten how to hold a pen? Should we be introducing children to computers from the earliest age possible? Will computers ever replace teachers?

As a psychologist specializing in the effect of interactive technology in the lives of children, it still surprises me how late in my own life I was acquainted with modern technology. Back in 1982, I experienced my first taste of computers as a teenager playing Donkey Kong on my father’s Commodore 64. It wasn’t until I was 18 years of age and at university that I first did something educational on a computer. The fact that I do not feel I have been left behind in today’s technological generation suggests that children do not necessarily have to begin as young as possible to appreciate the educational benefits of IT (i.e. if I can catch up having not started until I was in my late teens, then there is no reason why others shouldn’t be able to do so).

There is no doubt that children’s day-to-day leisure habits have changed dramatically in the last 30 years. Today’s modern teenager may well have a television, CD player and computer game console in their bedroom and many have online access to the internet at home and at home via smartphones, tablets, and laptops. In essence, today’s teenagers live their lives in a multi-media world and are more “screenager” than teenager. What is the long-term effect of this change in children’s leisure behaviour? Over the last decade there have been countless independent research projects all claiming to give pointers as to the long-term effects of children spending more and more time in front of the screen. A decade ago, eminent psychologists (such as Philip Zimbardo) made the observation that there had been a dramatic increase in shyness rates, a doubling of children’s obesity levels, and that children were spending less time involved in physical activities (e.g. sports) than they used to. I cannot put all the blame for these observations at the door of IT developments, but I do think they play a contributory role.

There appears to be a movement that automatically views IT as the way forward on lots of things (particularly in education), and that the only way of self-betterment amongst our children is through increasing IT use. There is little good reason to assume that more always means better. It is my belief that children at school need an integrated balance between computer-assisted learning (including the development of IT skills), traditional learning methods (paper and pen, the three ‘R’s’ etc.), physical sporting activities, and enhancement of play and peer development. That is not to say that computers and the internet do not have their positive side. Even a quick think on the subject would indicate that computers can:

• Be fun and exciting providing an innovative way of learning
• Provide elements of interactivity that can stimulate learning
• Provide elements of curiosity and challenge which can be crucial to learning
• Equip children with state-of -the-art technology
• Help overcome techno-phobia (a condition well-known among many adults)
• Eliminate gender imbalance in IT use (males have traditionally tended to be more avid IT users)
• Help in the development of transferable IT skills

However, on the down side, (and the last thing I want to be is a kill-joy here) computers (including internet use) can in some cases:

• Be socially isolating (perhaps leading to increased shyness)
• Be socially limiting (perhaps leading to physical inactivity and obesity)
• Be time-consuming, engrossing, and in extreme cases addictive
• Provide easy accessibility to exploitative material (e.g. pornography)
• Provide easy accessibility to adult activities (e.g. internet gambling)
• Provide IT skills that quickly change or become obsolete
• Cause repetitive strain injuries
• Produce unintended “sloppiness” (i.e. computers can correct spelling and grammar)

As can be seen by the list of ‘negatives’, some of the problems are not from the IT medium itself but from what children can do in that medium (e.g., access pornography or gamble at virtual casinos on the internet). Both parents and teachers need to be aware of IT’s limitations and need to put safeguards in place to protect children from unwanted exposure to adult material.

To re-iterate and expand on what I said earlier, there needs to be integration between lots of different activities (not just IT), and there needs to be a balance between IT and traditional education so that they can combine to form a richer experience for the children of tomorrow. IT will continue to have a large impact in the lives of our children. What teachers and parents need to concentrate on is not what to learn but how to learn. This in itself will have an impact on both the role of teachers and the contribution that parents can make.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (2010). Adolescent video game playing: Issues for the classroom. Education Today: Quarterly Journal of the College of Teachers, 60(4), 31-34.

Griffiths, M.D. (2010). Trends in technological advance: Implications for sedentary behaviour and obesity in screenagers. Education and Health, 28, 35-38.

Griffiths, M.D. (2013). Adolescent mobile phone addiction: A cause for concern? Education and Health, 31, 76-78.

Griffiths, M.D. (2013). Adolescent gambling via social networking sites: A brief overview. Education and Health, 31, 84-87.

Griffiths, M.D. & Kuss, D.J. (2011). Adolescent social networking: Should parents and teachers be worried? Education and Health, 29, 23-25.

Griffiths, M.D. & Parke, J. (2010). Adolescent gambling on the Internet: A review. International Journal of Adolescent Medicine and Health, 22, 59-75.

Kuss, D.J. & Griffiths, M.D. (2012). Online gaming addiction in adolescence: A literature review of empirical research. Journal of Behavioral Addictions, 1, 3-22.

Kuss, D.J., van Rooij, A.J., Shorter, G.W., Griffiths, M.D. & van de Mheen, D. (2013). Internet addiction in adolescents: Prevalence and risk factors. Computers in Human Behavior, 29, 1987-1996.

Spekman,M.L.C., Konijn,E.A, Roelofsma,P.H.M.P. & Griffiths, M.D. (2013). Gaming addiction, definition, and measurement: A large-scale empirical study, Computers in Human Behavior, 29, 2150-2155.

Gaming desire: Online behavioural tracking in Facebook

In a previous blog I examined how researchers in the gambling studies field are using online behavioural tracking data to study excessive gambling. However, online tracking data is used all the time in lots of contexts by lots of companies to better understand human behaviour. Most people view the internet as a very anonymous medium but rest assured, someone, somewhere, is monitoring everything you do online. The internet is the most non-anonymous place I can possibly think of.

Data from online environments provide potential advantages to many sectors (particularly those in the fields of marketing and advertising). This is because every click and transaction of every customer is automatically stored in a database and provides very high data quality for those who know what to do with it. This is very much in contrast to market surveys where such data have to be gathered at high costs, with lots of manual work involved, and may be prone to error. Within my own gambling studies field, a number of different teams across the world (including my own) have now been given access to behavioural tracking data of gamblers. Such data include:

• Account data (i.e., general information about each player) including user ID, date of birth, gender, other demographic data (if available), and geographic data (e.g., postal codes).
• Game data (for each player) including game ID, game type (if available), amount of winnings, amount of money spent, number of bets/spins (or equivalent), chasing behaviour, bonus usage, and session time.
• Financial data (for each player, and game, if applicable) including the number and amount of deposits, the number of money withdrawals, and the number of accounts.
• Responsible gaming limit data (i.e., time, spending, etc) for each player, and game (if applicable) including current time and spend limits, changes of limits, and the number of limit strikes (i.e., when players reach their pre-determined limit for deposits or time.).
• Miscellaneous data for each player (and game if applicable) including the length of playing session, login information, number of ‘cool-off periods’ (when players lock themselves out of their accounts for pre-defined periods of time), and any other data that might be relevant or of interest.

Many of these types of data are also held by those who operate games via social networking sites and could potentially be used for research purposes. Online social networking sites (e.g., Facebook) typically collect two types of information. These are (i) personal details provided by a user (e.g., name, email address, telephone number, address, gender and schools attended, etc.) and (ii) usage data collected automatically as the user clicks from one webpage to another (e.g., how users access the site, type of web browser used, time spent logged onto the site, etc.). Other day-to-day types of data collected from social network users include:

• The IP address used every time a user logs on to the social networking site.
• Every friend request a user has ever received and how they responded.
• A list of all users’ family and friends (including relationship status)
• Every pressing of ‘Like’ that a user has used on a wide variety of topics and events.
• Credit card information, if the user ever purchased credits or advertising on the social networking site.
• Every poke a user has exchanged (including both pokes made by the user on someone else and a record of all the times a user has been poked).
• Every event a user has been invited to through via the networking site and how they responded.
• Dates of user name changes and historical privacy settings changes.
• Photographs of life events and camera metadata including time stamps and latitude/longitude of picture location, as well as tags from photos – even if users have untagged them.
• The last known physical location of the user, with latitude, longitude, time/date, altitude, and more.
• A history of every private and public message and chat on the social networking site.
• Lists of every song the user has listened to online and every article that they have read.

Almost any variable (beyond the usual demographic ones such as age, gender, education, relationship status, etc.) could be examined as a risk and/or protective factor in the context of social gaming (e.g., Is the number of credit cards registered related to time and/or money spent on social gaming? How often does a person access a social game following the recommendation of another person? Does the type of social gaming differ by geographical location of where the user logged on? Does poking facilitate social gaming?). Facebook currently stores up to 800 pages of data on each of its users.

It has also been revealed that some social networking sites (e.g., Facebook) collect data from users who have logged out (usually – say the company – “for security purposes”) through the use of ‘cookies’. Cookies relay information from any site a user visits that contains a link to the social networking site such as a ‘like’ button.  With these data, the company can map out any users more general web usage.

Access to such data sets may provide insights into a number of important areas such as transitions from social gaming to social gambling, and how social gaming might be integrated with other online behaviours (such as gambling). However, other types of research are also needed including longitudinal studies so that people can be tracked over time (either via behavioural tracking and/or surveys), and more detailed qualitative work (interviews and focus groups) with different player types (e.g., regular and/or problematic gamblers/social gamers).

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Delfabbro, P.H., King, D.L & Griffiths, M.D. (2012). Behavioural profiling of problem gamblers: A critical review. International Gambling Studies, 12, 349-366.

Griffiths, M.D. (2003). Internet gambling: Issues, concerns and recommendations. CyberPsychology and Behavior, 6, 557-568.

Griffiths, M.D. (2009). Social responsibility in gambling: The implications of real-time behavioural tracking. Casino and Gaming International, 5(3), 99-104.

Griffiths, M.D. (2013). Social gambling via Facebook: Further observations and concerns. Gaming Law Review and Economics, 17, 104-106.

Griffiths, M.D. & Parke, J. (2002). The social impact of internet gambling. Social Science Computer Review, 20, 312-320.

Griffiths, M.D. & Whitty, M.W. (2010). Online behavioural tracking in Internet gambling research: Ethical and methodological issues. International Journal of Internet Research Ethics, 3, 104-117.

Griffiths, M.D. & Wood, R.T.A. (2008). Gambling loyalty schemes: Treading a fine line? Casino and Gaming International, 4(2), 105-108.

Kuss, D.J. & Griffiths, M.D. (2011). Online social networking and addiction: A literature review of empirical research. International Journal of Environmental and Public Health, 8, 3528-3552.

Track to the future: Online behavioural tracking and problem gambling

Almost everyone reading this will be aware that problem gambling lies towards one end of a continuum that ranges from non-gambling at one end through to pathological gambling at the other. However, it should also be noted that there will always be some behaviours that are typically engaged in by problem gamblers that some non-problem gamblers may also engage in at least occasionally (e.g., chasing behaviour when gamblers try to recoup their losses).

Worldwide, there are many different screening instruments that can be used by clinicians and researchers to help identify problem gambling. One of most regularly used is the Diagnostic and Statistical Manual, Fourth Edition (of which the fifth edition has just been published) that includes criteria that can aid the diagnosis of problem and pathological gambling (but now called disordered gambling in its latest incarnation). The previous (DSM-IV) criteria were used in the most recent British Gambling Prevalence Survey published in 2011. If a person answered positively to at least five of the criteria, a diagnosis of pathological gambling would be made whereas endorsement of three or four of the criteria would indicate a diagnosis of problem gambling. Using the DSM-IV, the latest BGPS reported a problem gambling rate of 0.9% among British adults.

In contrast to offline gambling, the use of online behavioural tracking presents an opportunity for researchers to examine the actual and real-time behaviour engaged in by gamblers. Analysis of behavioural tracking data has been carried out by various groups of researchers. For instance, one group affiliated to Harvard University have published a series of papers examining a data set of online gamblers provided by the bwin gaming company. My own research unit has also been publishing data using behavioural tracking data provided by the win2day gaming company.

During my consultancy for various online gaming companies, I have been informed by industry insiders that problem gambling can be identified online by examining the patterns and behaviours of online gamblers. If this is true, it has implications for current problem gambling screens (including the new DSM-V). This is because most criteria found in these screens are associated with the consequences of problem gambling rather than the gambling behaviour itself. Take the DSM-IV. I have argued that only a few of the behaviours in the DSM criteria for pathological gambling can be reliably spotted online using online behavioural tracking (the most obvious being chasing losses, salience/preoccupation, and tolerance). The following list highlights each of the DSM-IV questions for pathological gambling and the component of pathological gambling that each criterion is assessing. This is followed by an assessment as to what extent each criterion can be identified online.

• Salience/Preoccupation (Do you find that you are becoming preoccupied with past gambling successes or find yourself spending increasingly more time planning future gambling?) – An online problem gambler is likely to spend a lot of time gambling online although this behaviour in itself does not necessarily indicate a problem. Anything above four hours daily play over a protracted period could be considered excessive although some forms of online gambling (e.g., online poker) may take up a lot of time and be played relatively inexpensively.
• Tolerance (Do you find that you need to increase the amount of money you gamble to achieve the same enjoyment and excitement?) – If experiencing tolerance to gambling, an online problem gambler is likely to have changed their gambling behaviour in one of two ways over time. The first example of tolerance is a gradual increase of daily play in terms of time. For instance, the gambler might start off playing 30-60 minutes a day but over the course of a few months starts to play increasing amounts of time. The second example of tolerance is the act of gambling using gradually bigger stakes over time. An online problem gambler is more likely to experience both of these combined (i.e., gambling for longer and longer periods of time with bigger and bigger amounts of money).
• Relapse (Have you recently tried to stop gambling but were unsuccessful?) – Although this is difficult to detect with absolute certainty online, a typical pattern would be a gambler who gambles heavily, day-in day-out, for a period of time and then “disappears” for a period of time (which could be days, weeks, and sometimes even months), only to suddenly re-appear and gamble heavily again.
• Withdrawal  (Do you become moody or impatient when you are cutting down how much you gamble?) – This is again difficult to detect with absolute certainty online but is most likely to surface with the use of verbally aggressive comments in those games that have chat room facilities (such as online poker).
• Escape from reality (Do you ever use gambling a way of ignoring stress in your in life or even pick you up when you feel down?) – This is almost impossible to detect online although those players who play for long hours every day are more likely to experience escape-like feeling.
• Chasing losses (Do you ever try to win back the money you lost by increasing the size or frequency of your wagers?) – This is one of the key indicators of problem gambling and can be spotted online more easily than many other problem gambling criteria. Typical chasing patterns will include repeated ‘double or quit’ strategies in an effort to recoup losses. Although many gamblers use this strategy on occasion, the online problem gambler will do it repeatedly. This behaviour, above and beyond any other criteria, is most likely to signal problem gambling.
• Conceal Involvement (Do you ever hide how much or how often you gamble from significant others?) – There is no way that an online gambling operator can spot this during online gambling unless such admissions are given to other players in online chat rooms.
• Unsociable Behaviour (Have you ever committed fraud or theft to get money to gamble with?) – Again, there is no way that an online gambling operator can spot this during online gambling unless such admissions are given to other players in online chat rooms.
• Ruin a Relationship/Opportunity (Has gambling ever ruined a personal relationship or an occupational or educational opportunity?) – As with the previous two criteria, there is no way that an online gambling operator can spot this during online gambling unless such admissions are given to other players in online chat rooms.
• Bail-out  (Have you ever needed others to relieve a financial problem created by gambling?) – When an online gambler has exhausted all their own funds, they will often ‘beg, borrow and (eventually) steal’ money to continue gambling. A player whose account is constantly ‘topped up’ by people other than themselves may be a problem gambler.

This brief analysis of the extent to which each DSM criterion of problem gambling can be identified online shows that only a few behaviours can be reliably spotted via online behavioural tracking. The following list contains a number of behaviours that are engaged in by online problem gamblers. This was devised and based on my conversations with members of online gaming industry. These are additional to those identified above (i.e., chasing losses, spending high amounts of time and money, and increasing the amount of gambling over time). As a general ‘rule of thumb’, it is assumed that the more of these online behaviours that are engaged in by an individual, the more likely that person is to be a problem gambler.

• Playing a variety of stakes – Playing a variety of different stakes (in games like online poker) indicates poor planning and may be a cue or precursor to chasing behaviour.
• Playing a variety of games – Evidence from national prevalence surveys (e.g. Wardle et, al, 2011) demonstrates that the more types of gambling engaged in, the more likely the person is to be a problem gambler. Although this factor on its own is unlikely to indicate problem gambling, when combined with other indicators on this list may be indicative of problem gambling.
• Player ‘reload’ within gambling session – Although any gambler can engage in such behaviour, players who deposit more money within session (‘reload’) are more likely to be problem gamblers. This indicates poor planning and is a cue to chasing behaviour.
• Frequent payment method changes – The constant changing of deposit payment methods indicates poor planning and is may be a cue to chasing behaviour. This online behaviour usually indicates shortage of funds and need to extract monies from a variety of sources. Such behaviour can also indicate bank refusal.
• Verbal aggression – Aggressive verbal interaction via relay chat is common among problem gamblers although any gambler losing money may cause such behaviour. Such behaviour may be evidence of gamblers going on ‘tilt’ (i.e., negative cognitive and emotional reaction to losing) or withdrawal effects if out of money to gamble.
• Constant complaints to customer services – Constant complaints to the customer service department is common among problem gamblers although any gambler losing money may cause such behaviour. As with verbal aggression, such behaviour may be evidence of gamblers going on ‘tilt’ (i.e., negative cognitive and emotional reaction to losing).

Clearly, each of these behaviours needs to be examined in relation to at least three or four other indicative behaviours. Perhaps most importantly, and according to online gambling companies who use socially responsible behavioural tracking tools, it is a significant change in usual online behaviour that is most indicative of a problem gambler. Most statistical modelling of player behaviour predicts future problematic behaviour on the basis of behavioural change over time. The behaviours highlighted suggest that screening instruments in the future may be able to be developed that concentrate on the gambling behaviour itself, rather than the associated negative consequences.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Auer, M. & Griffiths, M.D. (2013). Limit setting and player choice in most intense online gamblers: An empirical study of online gambling behaviour. Journal of Gambling Studies, in press.

Auer, M. & Griffiths, M.D. (2013). An empirical investigation of theoretical loss and gambling intensity. Journal of Gambling Studies, in press.

Delfabbro, P.H., King, D.L & Griffiths, M.D. (2012). Behavioural profiling of problem gamblers: A critical review. International Gambling Studies, 12, 349-366.

Dragicevic, S., Tsogas, G., & Kudic, A. (2011). Analysis of casino online gambling data in relation to behavioural risk markers for high-risk gambling and player protection. International Gambling Studies, 11, 377–391.

Griffiths, M.D. (2009). Social responsibility in gambling: The implications of real-time behavioural tracking. Casino and Gaming International, 5(3), 99-104.

Griffiths, M.D. & Auer, M. (2011). Approaches to understanding online versus offline gaming impacts. Casino and Gaming International, 7(3), 45-48.

Griffiths, M.D. & Whitty, M.W. (2010). Online behavioural tracking in Internet gambling research: Ethical and methodological issues. International Journal of Internet Research Ethics, 3, 104-117.

LaBrie, R.A., Kaplan, S., LaPlante, D.A., Nelson, S.E., & Shaffer, H.J. (2008). Inside the virtual casino: A prospective longitudinal study of Internet casino gambling. European Journal of Public Health, DOI:10.1093/eurpub/ckn021.

LaPlante, D.A., Kleschinsky, J.H., LaBrie, R.A., Nelson, S.E. & Shaffer, H.J. (2009). Sitting at the virtual poker table: A prospective epidemiological study of actual Internet poker gambling behavior. Computers in Human Behavior 25, 711-717.

Wardle, H., Moody, A., Spence, S., Orford, J., Volberg, R., Jotangia, D., Griffiths, M., Hussey, D. & Dobbie, F. (2011). British Gambling Prevalence Survey 2010. London: The Stationery Office.

Screen play ideas: A speculative look at trends in video game addiction

Gaming addiction has become a topic of increasing research interest. Over the last decade there has been a significant increase in the number of scientific studies examining various aspects of video game addiction. This has resulted in a wide-ranging selection of review papers focusing on different aspects of the topic. These include general literature reviews of video game addiction, reviews of online (as opposed to offline) gaming addiction, reviews of the main methodological issues in studying video game addiction, reviews of structural characteristics and their relationship with video game addiction, reviews of video game addiction treatment, reviews of video game addiction and co-morbidity/convergence with other addictions such as gambling addiction and Internet addiction, and miscellaneous review papers on very specific aspects of video game addictions such as social responsibility, screening instruments, or reviews refuting that video game addiction even exists.

Furthermore, the amount and the quality of research in the gaming addiction field has progressed much over the last decade but is still in its infancy compared to other more established behavioural addictions, such as pathological gambling. Today’s blog briefly provides a considered (and somewhat speculative) examination of what might happen in the gaming addiction field from a number of different standpoints (e.g., methodological, conceptual, technological). These are taken from a paper I recently published in Current Psychiatry Reviews with Dr. Daniel King (University of Adelaide, Australia) and Daria Kuss (Nottingham Trent University, UK). These trends were loosely modeled on a 2011 paper I wrote on the technological trends in gambling and published in Casino and Gaming International.

• There is likely to be an even bigger increase in empirical research into problematic video game playing and video game addiction. This will of course be dependent on both appropriate funding streams and/or whether gaming addiction ends up being included in future psychiatric disorder classifications (e.g., Diagnostic and Statistical Manual, International Classification of Diseases, etc.). Future research is likely to include more epidemiological and/or general population data on media use, leading to better insights into the onset and course of problematic video game play and addiction.

• Given the many different screening instruments that have been developed over the last decade, there is likely to be a refinement of video game addiction measures and greater consensus on its conceptualization, either as a single disorder and/or incorporated into other known disorders (e.g., impulse control disorder). This is also likely to lead to improved assessment tools based on such conceptualization(s).

• Measures of gaming use and subsequent behaviour are likely to diversify in terms of media use, including social networking sites (SNS) and associated Internet resources. Already, games such as Call of Duty and Battlefield 3 are being released with their own SNS (e.g., COD Elite) that track player behaviour and provide feedback to players as to how to improve their game (thus functionally reinforcing video game play and thus have implications for excessive and/or potentially addictive play).

• Given the pressure on media enterprises to ‘monetize’ their business and look for different revenue streams, there is likely to be even greater media convergence between gaming and other more profit-making activities such as gambling. Given the well established addictive potential of gambling, this may also have implications for the incidence of video game addiction.

• Gaming on the move is likely to be a big growth area that may have implications for excessive gaming via ‘convenience’ hardware such as handheld gaming consoles, PDA devices, mobile phones, tablet computers, and MP3 players.

• Given the fact that the Internet is gender-neutral, there is likely to be increasing feminization of gaming where increasing numbers of females not only engage in the playing of online games, but also develop problems as a result. Casual gaming online is already popular among females. However, the biggest difference between male and female gaming is likely to be content-based (e.g., males may prefer competitive type gaming experiences whereas females may prefer co-operative type gaming experiences).

• Given the increasing number of research teams in the gambling field being given direct access to gambling companies behavioural tracking data, there is likely to be an increasing number of such collaborations in the gaming studies field.

• Given the increased importance of additional research into the structural and situational characteristics of consumptive behaviours (e.g., smoking nicotine, drinking alcohol, gambling, etc.), it is likely that research on design features within games and their psychological impact (including potential addiction) will increase as well. Such research has already begun (including quite a few studies by our gaming research unit).

• As the diagnosis of video game addiction becomes more legitimate in psychiatric and medical circles, it will lead to better randomized control trials on interventions for problematic video game play than the ones already carried out. There is also likely to be an increase in the online medium itself being used as a treatment channel. The reasons that people like to engage in some online leisure activities (i.e., the fact that the online environment is non-face-to-face, convenient, accessible, affordable, anonymous, non-threatening, non-alienating, non-stigmatizing, etc.) may also be the very same reasons why people would want to seek advice, help and treatment online rather than in face-to-face situations.

Based on our review paper there are several noticeable trends that can be drawn from our recent reviews of problematic video game play and video game addiction.

• There has been a significant increase in empirical research decade by decade since the early 1980s.

• There has been a noticeable (and arguably strategic) shift in researching the mode of video game play. In the 1980s, research mainly concerned ‘pay-to-play’ arcade video games. In the 1990s, research mainly concerned stand alone (offline) video games played at home on consoles, PCs or handheld devices. In the 2000s, research mainly concerned online massively multiplayer video games.

• There has been a noticeable shift in how data are collected. Up until the early 2000s, data about video game behaviour was typically collected face-to-face, whereas contemporary studies collect data online, strategically targeting online forums where gamers are known to (virtually) congregate. These samples are typically self-selecting and (by default) unrepresentative of the general population. Therefore, generalization is almost always one of the methodological shortcomings of this data collection approach.

• Survey study sample sizes have generally increased. In the 1980s and 1990s, sample sizes were typically in the low hundreds. In the 2000s, sample sizes in their thousands – even if unrepresentative – are not uncommon.

• There has been a diversification in the way data are collected including experiments, physiological investigations, secondary analysis of existing data (such as that collected from online forums), and behavioural tracking studies.

• There has been increased research on adult (i.e., non-child and non-adolescent) samples reflecting the fact that the demographics of gaming have changed.

• There has been increasing sophistication in relation to issues concerning assessment and measurement of problematic video game play and video game addiction. In the last few years, instruments have been developed that have more robust psychometric properties in terms of reliability and validity. However, there are still some concerns as many of the most widely used screening instruments were adapted from adult screens and much of the video game literature has examined children and adolescents. In other papers I have co-written with Dr. King, we have asserted that to enable future advances in the development and testing of interventions for video game-related problems, there must be some consensus among clinicians and researchers as to the precise classification of these problems. (In fact, we’ve just had a major review paper accepted on assessing video game addiction in Clinical Psychology Review which I examined in a previous blog).

Clearly, there exist a number of gaps in current understanding of problematic video game play and video game addiction. There is a need for epidemiological research to determine the incidence and prevalence of clinically significant problems associated with video game play in the broader population. There are too few clinical studies that describe the unique features and symptoms of problematic video game play and/or video game addiction. While the current empirical base is relatively small, gaming addiction has become a more mainstream area for psychological and psychiatric research and is likely to become an area of significant importance given the widespread popularity of gaming.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Additional input: Daria Kuss and Daniel King

Further reading

Griffiths, M.D. (2010). Online video gaming: What should educational psychologists know? Educational Psychology in Practice, 26(1), 35-40.

Griffiths, M.D. (2011). Technological trends and the psychosocial impact on gambling. Casino and Gaming International, 7(1), 77-80.

Griffiths, M.D., Kuss, D.J. & King, D.L. (2012). Video game addiction: Past, present and future. Current Psychiatry Reviews, 8, 308-318.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2009). The psychological study of video game players: Methodological challenges and practical advice. International Journal of Mental Health and Addiction, 7, 555-562.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2010). Video game structural characteristics: A new psychological taxonomy. International Journal of Mental Health and Addiction, 8, 90-106.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2010). The role of structural characteristics in problem video game playing: A review. Cyberpsychology: Journal of Psychosocial Research on Cyberspace. Located at: http://www.cyberpsychology.eu/view.php?cisloclanku=2010041401&article=6.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2010). The convergence of gambling and digital media: Implications for gambling in young people. Journal of Gambling Studies, 26, 175-187.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2010). Cognitive behavioural therapy for problematic video game players: Conceptual considerations and practice issues. Journal of CyberTherapy and Rehabilitstion, 3, 261-273.

King, D.L., Delfabbro, P.H., Griffiths, M.D. & Gradisar, M. (2011). Assessing clinical trials of Internet addiction treatment: A systematic review and CONSORT evaluation. Clinical Psychology Review, 31, 1110-1116.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2012). Clinical interventions for technology-based problems: Excessive Internet and video game use. Journal of Cognitive Psychotherapy: An International Quarterly, 26, 43-56.

King, D.L., Delfabbro, P.H., Griffiths, M.D. & Gradisar, M. (2012). Cognitive-behavioural approaches to outpatient treatment of Internet addiction in children and adolescents. Journal of Clinical Psychology: In Session, 68, 1185-1195.

King, D.L., Haagsma, M.C.^, Delfabbro, P.H.,Gradisar, M.S. &^, Griffiths, M.D. (2013). Psychometric assessment of pathological video-gaming: A systematic review. Clinical Psychology Review, 33, 331-342.