Category Archives: Online addictions

Tubular hells: A brief look at ‘addiction’ to watching YouTube videos

 

A few days ago, I unexpectedly found my research on internet addiction being cited in a news article by Paula Gaita on compulsive viewing of YouTube videos (‘Does compulsive YouTube viewing qualify as addiction?‘). The article was actually reporting a case study from a different news article published by PBS NewsHour by science correspondent Lesley McClurg (‘After compulsively watching YouTube, teenage girl lands in rehab for digital addiction’). As Gaita reported:

“The story profiles a middle school student whose obsessive viewing of YouTube content led to extreme behavior changes and eventually, depression and a suicide attempt. The student finds support through therapy at an addiction recovery center…The student in question is a young girl named Olivia who felt at odds with the ‘popular’ kids at her Oakland area school. She began watching YouTube videos after hearing that it was a socially acceptable thing to do… Her viewing habits soon took the place of sleep, which impacted her energy and mood. Her grades began to falter, and external problems within her house – arguments between her parents and the death of her grandmother – led to depression and an admission of wanting to hang herself. Her parents took her to a psychiatric hospital, where she stayed for a week under suicide watch, but her self-harming compulsion continued after her release. She began viewing videos about how to commit suicide, which led to an attempt to overdose on Tylenol[Note: The name of the woman – Olivia – was a pseudonym].

McClurg interviewed Olivia’s mother for the PBS article and it was reported that Olivia went from being a “bubbly daughter…hanging out with a few close friends after school” to “isolating in her room for hours at a time”. Olivia’s mother also claimed that her daughter had always been kind of a nerd, a straight. A student who sang in a competitive choir. But she desperately wanted to be popular, and the cool kids talked a lot about their latest YouTube favorites”. According to news reports, all Olivia would do was to watch video after video for hours and hours on end and developed sleeping problems. Over time, the videos being watched focused on fighting girls and other videos featuring violence.

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The news story claimed that Olivia was “diagnosed with depression that led to compulsive internet use”. When Olivia went back home she was still feeling suicidal and then spent hours watching YouTube videos on how to commit suicide (and it’s where she got the idea for overdosing on Tylenol tablets).

After a couple of spells in hospital, Olivia’s parents took her to a Californian centre specialising in addiction recovery (called ‘Paradigm’ in San Rafael). The psychologist running the Paradigm clinic (Jeff Nalin) claimed Olivia’s problem was “not uncommon” among clients attending the clinic. Nalin believes (as I do and have pointed out in my own writings) that treating online addictions is not about abstinence but about getting the behaviour under control but developing skills to deal with the problematic behaviour. He was quoted as saying:

“I describe a lot of the kids that we see as having just stuck a cork in the volcano. Underneath there’s this rumbling going on, but it just rumbles and rumbles until it blows. And it blows with the emergence of a depression or it emerges with a suicide attempt…The best analogy is when you have something like an eating disorder. You cannot be clean and sober from food. So, you have to learn the skills to deal with it”.

The story by Gaita asked the question of whether compulsive use of watching YouTube could be called a genuine addiction (and that’s where my views based on my own research were used). I noted that addiction to the internet may be a symptom of another addiction, rather than an addiction unto itself. For instance, people addicted to online gambling are gambling addicts, not internet addicts. An individual addicted to online gaming or online shopping are addicted to gaming or shopping not to the internet.

An individual may be addicted to the activities one can do online and is not unlike saying that an alcoholic is not addicted to a bottle, but to what’s in it. I have gone on record many times saying that I believe anything can be addictive as long there are continuous rewards in place (i.e., constant reinforcement). Therefore, it’s not impossible for someone to become addicted to watching YouTube videos but the number of genuine cases of addiction are likely to be few and far between. Watching video after video is conceptually no different from binge watching specific television series or television addiction itself (topics that I have examined in previous blogs).

I ought to end by saying that some of my own research studies on internet addiction (particularly those co-written with Dr. Attila Szabo and Dr. Halley Pontes and published in the Journal of Behavioral Addictions and Addictive Behaviors Reports – see ‘Further reading’ below) have examined the preferred applications by those addicted to the internet, and that the watching of videos online is one of the activities that has a high association with internet addiction (along with such activities such as social networking and online gaming). Although we never asked participants to specify which channel they watched the videos, it’s fair to assume that many of our participants will have watched them on YouTube), and (as the Camelot lottery advert once said) maybe, just maybe, a few of those participants may have had an addiction to watching YouTube videos.

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

Further reading

Gaita, P. (2017). Does compulsive YouTube viewing qualify as addiction? The Fix, May 19. Located at: https://www.thefix.com/does-compulsive-youtube-viewing-qualify-addiction

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

Griffiths, M.D., Kuss, D.J., Billieux J. & Pontes, H.M. (2016). The evolution of internet addiction: A global perspective. Addictive Behaviors, 53, 193–195.

Griffiths, M.D. & Pontes, H.M. (2014). Internet addiction disorder and internet gaming disorder are not the same. Journal of Addiction Research and Therapy, 5: e124. doi:10.4172/2155-6105.1000e124.

Griffiths M.D. & Szabo, A. (2014). Is excessive online usage a function of medium or activity? An empirical pilot study. Journal of Behavioral Addictions, 3, 74-77.

Kuss, D.J. & Griffiths, M.D. (2015). Internet Addiction in Psychotherapy. Basingstoke: Palgrave Macmillan.

Kuss, D.J., Griffiths, M.D. & Binder, J. (2013). Internet addiction in students: Prevalence and risk factors. Computers in Human Behavior, 29, 959-966.

Kuss, D.J., Griffiths, M.D., Karila, L. & Billieux, J. (2014). Internet addiction: A systematic review of epidemiological research for the last decade. Current Pharmaceutical Design, 20, 4026-4052.

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.

McClurg, L. (2017). After compulsively watching YouTube, teenage girl lands in rehab for ‘digital addiction’. PBS Newshour, May 16. Located at: http://www.pbs.org/newshour/rundown/compulsively-watching-youtube-teenage-girl-lands-rehab-digital-addiction/

Pontes, H.M., Kuss, D.J. & Griffiths, M.D. (2015). The clinical psychology of Internet addiction: A review of its conceptualization, prevalence, neuronal processes, and implications for treatment. Neuroscience and Neuroeconomics, 4, 11-23.

Pontes, H.M., Szabo, A. & Griffiths, M.D. (2015). The impact of Internet-based specific activities on the perceptions of Internet Addiction, Quality of Life, and excessive usage: A cross-sectional study. Addictive Behaviors Reports, 1, 19-25.

Widyanto, L. & Griffiths, M.D. (2006). Internet addiction: A critical review. International Journal of Mental Health and Addiction, 4, 31-51.

Search of the poisoned mind? A brief look at ‘internet search dependence’

Despite being a controversial topic, research into a wide variety of online addictions has grown substantially over the last decade. My own research into online addictions has been wide ranging and has included online social networking, online sex addiction, online gaming addiction, online shopping addiction, and online gambling addiction. As early as the late 1990s/early 2000s, I constantly argued that when it came to online addictions, most of those displaying problematic behaviour had addictions on the internet rather than addictions to the internet (i.e., they were not addicted to the medium of the internet but addicted to applications and activities that could be engaged in via the internet).

A recent 2016 paper by Dr. Yifan Wang and colleagues in the journal Frontiers in Public Health described the development of the Questionnaire of Internet Search Dependence (QISD), a tool developed to assess individuals who may be displaying a dependence on using online search engines (such as Google and Baidu). The notion of individuals being addicted to using search engines is not new and was one of five types of internet addiction outlined in a 1999 typology in a paper in the Student British Medical Journal by Dr. Kimberley Young (and what she termed ‘information overload’ and referred to compulsive database searching). Although I criticized the typology on the grounds that most of the types of online addict were not actually internet addicts but were individuals using the medium of the internet to fuel other addictive behaviours (e.g., gambling, gaming, day trading, etc.), I did implicitly acknowledge that activities such as internet database searching could theoretically exist, even if I did not think it was a type of internet addiction.

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As far as I am aware, the new scale developed by Wang et al. (2016) is the first to create and psychometrically evaluate an instrument to assess ‘internet search dependence’. As noted by the authors:

Subsequently, we compiled 16 items to represent psychological characteristics associated with Internet search dependence, based on the literature review and a follow-up interview with 50 randomly selected university students…We adopted the six criteria for behavioral addiction formulated by Griffiths (i.e., salience, mood modification, tolerance, withdrawal, conflict, and relapse) [Griffiths, 1999b]”.

Given the authors claimed they used an early version of my addiction components model (i.e., one from 1999 rather than my most recent 2005 formulation) to help inform item construction, I was obviously interested to see the scale’s formulated items. I have to admit that I had a lot of misgivings about the paper so I wrote a commentary on it that has just been published in the same journal (Frontiers in Public Health). More specifically, I noted in my paper that if an individual was genuinely addicted to searching online databases I would have expected to see all of my six criteria applied as follows:

  • Salience – This occurs when searching internet databases becomes the single most important activity in the person’s life and dominates their thinking (preoccupations and cognitive distortions), feelings (cravings) and behaviour (deterioration of socialized behaviour). For instance, even if the person is not actually searching the internet they will be constantly thinking about the next time that they will be (i.e., a total preoccupation with internet database searching).
  • Mood modification – This refers to the subjective experiences that people report as a consequence of internet database searching and can be seen as a coping strategy (i.e., they experience an arousing ‘buzz’ or a ‘high’ or paradoxically a tranquilizing feel of ‘escape’ or ‘numbing’ when searching internet databases).
  • Tolerance – This is the process whereby increasing amounts of time searching internet databases are required to achieve the former mood modifying effects. This basically means that for someone engaged in internet database searching, they gradually build up the amount of the time they spend searching internet databases every day.
  • Withdrawal symptoms – These are the unpleasant feeling states and/or physical effects (e.g., the shakes, moodiness, irritability, etc.), that occur when an individual is unable to search internet databases because they are ill, the internet is unavailable, or there is no Wi-Fi on holiday, etc.
  • Conflict – This refers to the conflicts between the person and those around them (interpersonal conflict), conflicts with other activities (social life, hobbies and interests) or from within the individual themselves (intra-psychic conflict and/or subjective feelings of loss of control) that are concerned with spending too much time searching internet databases.
  • Relapse – This is the tendency for repeated reversions to earlier patterns of excessive internet database searching to recur and for even the most extreme patterns typical of the height of excessive internet database searching to be quickly restored after periods of control.

Of the 12 QISD items constructed in the new scale, very few appeared to have anything to do with addiction and/or dependence but this is most likely due to the fact that the authors also used data collected from 50 participants to inform their items and not just the criteria in the addiction components model. However, relying heavily on input from their participants resulted in a number of key features in addiction/dependence not even being assessed (i.e., no assessment of salience, mood modification, conflict, relapse or tolerance). A couple of items may peripherally assess withdrawal symptoms (e.g., ‘I will be upset if I cannot find an answer to a complex question through Internet search’) but not in any way that is directly associated with addiction or dependence. This may be because the authors’ conceptualization of ‘dependence’ was more akin to ‘over-reliance’ rather than traditional definitions of dependence.

While the QISD may be psychometrically robust I argued that it appears to have little face validity and does not appear to assess problematic engagement in internet database searching (irrespective of how addiction or dependence is defined). Based on the addiction components model, I concluded my paper by creating my own scale to assess internet search dependence based directly on the addiction components model and which I argued would have much greater face validity than any item currently found in the QISD:

  • Internet database searching is the most important thing in my life.
  • Conflicts have arisen between me and my family and/or my partner about the amount of time I spend searching internet databases.
  • I engage in internet database searching as a way of changing my mood.
  • Over time I have increased the amount of internet database searching I do in a day.
  • If I am unable to engage in internet database searching I feel moody and irritable.
  • If I cut down the amount of internet database searching I do, and then start again, I always end up searching internet databases as often as I did before.

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Andreassen, C.S., Griffiths, M.D., Pallesen, S., Bilder, R.M., Torsheim, T. Aboujaoude, E.N. (2015). The Bergen Shopping Addiction Scale: Reliability and validity of a brief screening test. Frontiers in Psychology, 6:1374. doi: 10.3389/fpsyg.2015.01374.

Andreassen, C.S., Pallesen, S., Griffiths, M.D. (2017). The relationship between excessive online social networking, narcissism, and self-esteem: Findings from a large national survey. Addictive Behaviors, 64, 287-293.

Canale, N., Griffiths, M.D., Vieno, A., Siciliano, V. & Molinaro, S. (2016). Impact of internet gambling on problem gambling among adolescents in Italy: Findings from a large-scale nationally representative survey. Computers in Human Behavior, 57, 99-106.

Griffiths, M.D. (1998). Internet addiction: Does it really exist? In J. Gackenbach (Ed.), Psychology and the Internet: Intrapersonal, Interpersonal and Transpersonal Applications (pp. 61-75). New York: Academic Press.

Griffiths, M.D. (1999a). Internet addiction: Internet fuels other addictions. Student British Medical Journal, 7, 428-429.

Griffiths, M.D. (1999b). Internet addiction: Fact or fiction? The Psychologist: Bulletin of the British Psychological Society, 12, 246-250.

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, 191-197.

Griffiths, M.D. (2012). Internet sex addiction: A review of empirical research. Addiction Research and Theory, 20, 111-124.

Griffiths, M.D. (2017). Commentary: Development and validation of a self-reported Questionnaire for Measuring Internet Search Dependence. Frontiers in Public Health, in press.

Griffiths, M.D., Kuss, D.J., Billieux J. & Pontes, H.M. (2016). The evolution of internet addiction: A global perspective. Addictive Behaviors, 53, 193–195.

Kuss, D. J., Griffiths, M. D., Karila, L. & Billieux, J. (2014). Internet addiction: A systematic review of epidemiological research for the last decade. Current Pharmaceutical Design, 20, 4026-4052.

Pontes, H. & Griffiths, M.D. (2015). Measuring DSM-5 Internet Gaming Disorder: Development and validation of a short psychometric scale. Computers in Human Behavior, 45, 137-143.

Wang, Y., Wu, L., Zhou, H., Xu, J. & Dong, G. (2016). Development and validation of a self-reported Questionnaire for Measuring Internet Search Dependence. Frontiers in Public Health, 4, 274. doi: 10.3389/fpubh.2016.00274

Young, K. S. (1999). Internet addiction: evaluation and treatment. Student British Medical Journal, 7, 351-352.

It takes all sports: A brief look at sport-related betting

Over the past year I have been carrying out research with my Spanish colleague – Dr. Hibai Lopez-Gonzalez – into problematic sports betting and sports betting advertising which has already produced a number of papers (see ‘Further reading’ below) and with many more to come. One of the issues we have faced in contextualising our work is that there is no such concept as sport-related problem gambling in prevalence surveys because problem gambling is assessed on the totality of gambling experiences rather than a single activity. For instance, in the three British Gambling Prevalence Surveys (BGPSs) conducted since 1999, sport-related gambling is subsumed within a number of different gambling forms: ‘football pools and fixed odds coupons’, ‘private betting’, and ‘other events with a bookmaker’. The 2010 BGPS (which I co-authored) included ‘sports betting’ as a category, along with ‘football pools’ (no coupons), ‘private betting’, ‘spread betting’ (which can include both sports or financial trading). In addition, the 2010 BGPS added a new category under online gambling activities to include ‘any online betting’. More recently, the Health Survey for England also introduced a new category: ‘gambling on sports events (not online)’.

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Despite these limitations, some evidence can be inferred from gambling activity by gambling type. In 2014, Heather Wardle and her colleagues combined the gambling data from the Health Survey for England and the Scottish Health Survey. They reported that among adult males aged 16 years and over during a 12-month period, 5% participated in offline football pools, 8% engaged in online betting (although no indication was made about whether this only involved sport), and 8% engaged in sports events (not online). The categories were not mutually exclusive so an overlapping of respondents across categories was very likely. A similar rate was found in South Australia in a 2013 report the Social Research Centre with those betting on sports over the past year accounting for 6.1% of the adult population, an increase from the 4.2% reported in 2005.

In Spain, the Spanish Gambling Commission (Direccion General de Ordenacion del Juego [DGOJ] reported that 1.5% of the adult (male and female) population had gambled online on sports in 2015. This is a significantly lower proportion compared with the British data, although the methodological variations cannot be underestimated. Spanish data also shows that, among those who have gambled online on a single gambling type only, betting on sports is the more prevalent form with up to 66% of those adults.

In France, the data on the topic only focuses on those who gamble rather than examining the general population of gamblers and non-gamblers. Among online gamblers, Dr. Jean-Michel Costes and colleagues reported in a 2011 issue of the journal Tendances that 35.1% had bet on sports during the last 12 months. In another French study by Costes and colleagues published in a 2016 issue of the Journal of Gambling Studies, sports betting represented 16.4% of the gambling cohort, although again, the representativeness of sports betting behaviour among the general gambling and non-gambling population could not be determined.

Due to the aforementioned shortcomings in the definition of sport-related gambling, there is only fragmented empirical evidence concerning the impact of sports-related problem gambling behaviour. For instance, in 2014, Dr. Nerilee Hing noted that clinical reports indicate that treatment seeking for sports-related problem gambling had grown in Australia. In British Columbia (Canada), a 2014 survey by Malatests & Associates for the Ministry of Finance reported that 23.6% of at-risk or problem gamblers had gambled on sports either offline or online. A smaller proportion (16.2%) was found in the Spanish population screened in the national gambling DGOJ survey, except this subgroup was entirely composed of online bettors.

In a 2011 study published in International Gambling Studies with patients from a pathological gambling unit within a community hospital in Barcelona, Dr. Susana Jiménez-Murcia and her colleagues found that among those who had developed the disorder gambling online only (as opposed to those who gamble both online/offline or offline only), just over half (50.8%) were sport bettors. Those who gambled online only (on any activity) and those that only gambled online on sports events represented a small minority of the total number of problem gamblers. Overall, there is relatively little research on this sub-group of gamblers therefore I and others will be monitoring the evolution of this trend as the online gambling population grows.

(Note: This blog was co-written with input from Dr. Hibai Lopez-Gonzalez).

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Costes, J-M, Kairouz, S., Eroukmanoff, V., et al. (2016) Gambling patterns and problems of gamblers on licensed and unlicensed sites in France. Journal of Gambling Studies 32(1), 79–91.

Costes, J., Pousset, M., Eroukmanoff, V., et al. (2010). Gambling prevalence and practices in France in 2010. Tendances, 77, 1–8.

DGOJ (2016a) Análisis del perfil del jugador online. Madrid: Ministerio de Hacienda y Administraciones Públicas.

DGOJ (2016b) Estudio sobre prevalencia, comportamiento y características de los usuarios de juegos de azar en España 2015. Madrid: Ministerio de Hacienda y Administraciones Públicas.

Hing, N. (2014) Sports betting and advertising (AGRC Discussion Paper No. 4). Melbourne: Australian Gambling Research Centre.

Jiménez-Murcia S, Stinchfield R, Fernández-Aranda F, et al. (2011) Are online pathological gamblers different from non-online pathological gamblers on demographics, gambling problem severity, psychopathology and personality characteristics? International Gambling Studies 11(3), 325–337.

Lopez-Gonzalez, H., Estevez, A. & Griffiths, M.D. (2017). Marketing and advertising online sports betting: A problem gambling perspective. Journal of Sport and Social Issues, in press.

Lopez-Gonzalez, H. & Griffiths, M.D. (2016). Is European online gambling regulation adequately addressing in-play betting advertising? Gaming Law Review and Economics, 20, 495-503.

Lopez-Gonzalez, H. & Griffiths, M.D. (2017). Understanding the convergence of online sports betting markets. International Review for the Sociology of Sport, in press.

Lopez-Gonzalez, H. & Griffiths, M.D. (2017). ‘Cashing out’ in sports betting: Implications for problem gambling and regulation. Gaming Law Review and Economics, in press.

Malatests & Associates Ltd (2014). 2014 British Columbia Problem Gambling Prevalence Study. Victoria, Canada: Gaming policy and enforcement branch, Ministry of Finance.

The Social Research Centre (2013) Gambling prevalence in South Australia. Adelaide, Australia: Office for problem gambling. Available from: http://phys.org/news/2012-03-lung-doctors-respiratory-diseases-worsen.html.

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

Wardle H, Seabury C, Ahmed H, et al. (2014) Gambling behaviour in England & Scotland. Findings from the health survey for England 2012 and Scottish health survey 2012. London: NatCen Social Research.

Wardle, H., Sproston, K., Orford, J., Erens, B., Griffiths, M.D., Constantine, R. & Pigott, S. (2007). The British Gambling Prevalence Survey 2007. London: The Stationery Office.

A diction for addiction: A brief overview of our papers at the 2017 International Conference on Behavioral Addictions

This week I attended (and gave one of the keynote papers at) the fourth International Conference on Behavioral Addictions in Haifa (Israel). It was a great conference and I was accompanied by five of my colleagues from Nottingham Trent University all of who were also giving papers. All of the conference abstracts have just been published in the latest issue of the Journal of Behavioral Addictions (reprinted below in today’s blog) and if you would like copies of the presentations then do get in touch with me.

mark-haifa-keynote-2017

Griffiths, M.D. (2017). Behavioural tracking in gambling: Implications for responsible gambling, player protection, and harm minimization. Journal of Behavioral Addictions, 6 (Supplement 1), 2.

  • Social responsibility, responsible gambling, player protection, and harm minimization in gambling have become major issues for both researchers in the gambling studies field and the gaming industry. This has been coupled with the rise of behavioural tracking technologies that allow companies to track every behavioural decision and action made by gamblers on online gambling sites, slot machines, and/or any type of gambling that utilizes player cards. This paper has a number of distinct but related aims including: (i) a brief overview of behavioural tracking technologies accompanied by a critique of both advantages and disadvantages of such technologies for both the gaming industry and researchers; (ii) results from a series of studies carried out using behavioural tracking (particularly in relation to data concerning the use of social responsibility initiatives such as limit setting, pop-up messaging, and behavioural feedback); and (c) a brief overview of the behavioural tracking tool mentor that provides detailed help and feedback to players based on their actual gambling behaviour.

Calado, F., Alexandre, J. & Griffiths, M.D. (2017). Youth problem gambling: A cross-cultural study between Portuguese and English youth. Journal of Behavioral Addictions, 6 (Supplement 1), 7.

  • Background and aims: In spite of age prohibitions, most re- search suggests that a large proportion of adolescents engage in gambling, with a rate of problem gambling significantly higher than adults. There is some evidence suggesting that there are some cultural variables that might explain the development of gambling behaviours among this age group. However, cross­cultural studies on this field are generally lacking. This study aimed to test a model in which individual and family variables are integrated into a single perspective as predictors of youth gambling behaviour, in two different contexts (i.e., Portugal and England). Methods: A total of 1,137 adolescents and young adults (552 Portuguese and 585 English) were surveyed on the measures of problem gambling, gambling frequency, sensation seeking, parental attachment, and cognitive distortions. Results: The results of this study revealed that in both Portuguese and English youth, the most played gambling activities were scratch cards, sports betting, and lotteries. With regard to problem gambling prevalence, English youth showed a higher prevalence of problem gambling. The findings of this study also revealed that sensation seeking was a common predictor in both samples. However, there were some differences on the other predictors be- tween the two samples. Conclusions: The findings of this study suggest that youth problem gambling and its risk factors appear to be influenced by the cultural context and highlights the need to conduct more cross-cultural studies on this field.

Demetrovics, Z., Richman, M., Hende, B., Blum, K., Griffiths,
M.D, Magi, A., Király, O., Barta, C. & Urbán, R. (2017). Reward Deficiency Syndrome Questionnaire (RDSQ):
A new tool to assess the psychological features of reward deficiency. Journal of Behavioral Addictions, 6 (Supplement 1), 11.

  • ‘Reward Deficiency Syndrome’ (RDS) is a theory assuming that specific individuals do not reach a satisfactory state of reward due to the functioning of their hypodopaminergic reward system. For this reason, these people search for further rewarding stimuli in order to stimulate their central reward system (i.e., extreme sports, hypersexuality, substance use and/or other addictive behaviors such as gambling, gaming, etc.). Beside the growing genetic and neurobiological evidence regarding the existence of RDS little re- search has been done over the past two decades on the psychological processes behind this phenomenon. The aim of the present paper is to provide a psychological description of RDS as well as to present the development of the Reward Deficiency Syndrome Questionnaire (developed using a sample of 1,726 participants), a new four-factor instrument assessing the different aspects of reward deficiency. The results indicate that four specific factors contribute to RDS comprise “lack of satisfaction”, “risk seeking behaviors”, “need for being in action”, and “search for overstimulation”. The paper also provides psychological evidence of the association between reward deficiency and addictive disorders. The findings demonstrate that the concept of RDS provides a meaningful and theoretical useful context to the understanding of behavioral addictions.

Demetrovics, Z., Bothe, B., Diaz, J.R., Rahimi­Movaghar, A., Lukavska, K., Hrabec, O., Miovsky, M., Billieux, J., Deleuze,
J., Nuyens, P. Karila, L., Nagygyörgy, K., Griffiths, M.D. & Király, O. (2017). Ten-Item Internet Gaming Disorder Test (IGDT-10): Psychometric properties across seven language-based samples. Journal of Behavioral Addictions, 6 (Supplement 1), 11.

  • Background and aims: The Ten-Item Internet Gaming Disorder Test (IGDT-10) is a brief instrument developed to assess Internet Gaming Disorder as proposed in the DSM­5. The first psychometric analyses carried out among a large sample of Hungarian online gamers demonstrated that the IGDT-10 is a valid and reliable instrument. The present study aimed to test the psychometric properties in a large cross-cultural sample. Methods: Data were collected among Hungarian (n = 5222), Iranian (n = 791), Norwegian (n = 195), Czech (n = 503), Peruvian (n = 804), French­speaking (n = 425) and English­ speaking (n = 769) online gamers through gaming­related websites and gaming-related social networking site groups. Results: Confirmatory factor analysis was applied to test the dimensionality of the IGDT-10. Results showed that the theoretically chosen one-factor structure yielded appropriate to the data in all language­based subsamples. In addition, results indicated measurement invariance across all language-based subgroups and across gen- der in the total sample. Reliability indicators (i.e., Cronbach’s alpha, Guttman’s Lambda-2, and composite reliability) were acceptable in all subgroups. The IGDT- 10 had a strong positive association with the Problematic Online Gaming Questionnaire and was positively and moderately related to psychopathological symptoms, impulsivity and weekly game time supporting the construct validity of the instrument. Conclusions: Due to its satisfactory psychometric characteristics, the IGDT-10 appears to be an adequate tool for the assessment of internet gam- ing disorder as proposed in the DSM-5.

Throuvala, M.A., Kuss, D.J., Rennoldson, M. & Griffiths, M.D. (2017). Delivering school-based prevention regarding digital use for adolescents: A systematic review in the UK. Journal of Behavioral Addictions, 6 (Supplement 1), 54.

  • Background: To date, the evidence base for school-delivered prevention programs for positive digital citizenship for adolescents is limited to internet safety programs. Despite the inclusion of Internet Gaming Disorder (IGD) as a pro- visional disorder in the DSM-5, with arguable worrying prevalence rates for problematic gaming across countries, and a growing societal concern over adolescents’ digital use, no scientifically designed digital citizenship programs have been delivered yet, addressing positive internet use among adolescents. Methods: A systematic database search of quantitative and qualitative research evidence followed by a search for governmental initiatives and policies, as well as, non­profit organizations’ websites and reports was conducted to evaluate if any systematic needs assessment and/or evidence-based, school delivered prevention or intervention programs have been conducted in the UK, targeting positive internet use in adolescent populations. Results: Limited evidence was found for school-based digital citizenship awareness programs and those that were identified mainly focused on the areas of internet safety and cyber bullying. To the authors’ knowledge, no systematic needs assessment has been conducted to assess the needs of relevant stakeholders (e.g., students, parents, schools), and no prevention program has taken place within UK school context to address mindful and positive digital consumption, with the exception of few nascent efforts by non­profit organizations that require systematic evaluation. Conclusions: There is a lack of systematic research in the design and delivery of school-delivered, evidence-based prevention and intervention programs in the UK that endorse more mindful, reflective attitudes that will aid adolescents in adopting healthier internet use habits across their lifetime. Research suggests that adolescence is the highest risk group for the development of internet addictions, with the highest internet usage rates of all age groups. Additionally, the inclusion of IGD in the DSM-5 as provisional disorder, the debatable alarming prevalence rates for problematic gaming and the growing societal focus on adolescents’ internet misuse, renders the review of relevant grey and published research timely, contributing to the development of digital citizenship programs that might effectively promote healthy internet use amongst adolescents.

Bányai, F., Zsila, A., Király, O., Maraz, A., Elekes, Z., Griffiths, M.D., Andreassen, C.S. & Demetrovics, Z. (2017). Problematic social networking sites use among adolescents: A national representative study. Journal of Behavioral Addictions, 6 (Supplement 1), 62.

  • Despite being one of the most popular activities among adolescents nowadays, robust measures of Social Media use and representative prevalence estimates are lacking in the field. N = 5961 adolescents (49.2% male; mean age 16.6 years) completed our survey. Results showed that the one-factor Bergen Social Media Addiction Scale (BSMAS) has appropriate psychometric properties. Based on latent pro le analysis, 4.5% of the adolescents belonged to the at-risk group, who reported low self-esteem, high level of depression and the elevated social media use (34+ hours a week). Conclusively, BSMAS is an adequate measure to identify those adolescents who are at risk of problematic Social Media use and should therefore be targeted by school-based prevention and intervention programs.

Bothe, B., Toth-Király, I. Zsila, A., Griffiths, M.D., Demetrovics, Z. & Orosz, G. (2017). The six-component problematic pornography consumption scale. Journal of Behavioral Addictions, 6 (Supplement 1), 62.

  • Background and aims: To our best knowledge, no scale ex- ists with strong psychometric properties assessing problematic pornography consumption which is based on an over- arching theoretical background. The goal of the present study was to develop a short scale (Problematic Pornography Consumption Scale; PPCS) on the basis of Griffiths` (2005) six-component addiction model that can assess problematic pornography consumption. Methods: The sample comprised 772 respondents (390 females; Mage = 22.56, SD = 4.98 years). Items creation was based on the definitions of the components of Griffiths’ model. Results: A confirmatory factor analysis was carried out leading to an 18­item second­order factor structure. The reliability of the PPCS was good and measurement invariance was established. Considering the sensitivity and specificity values, we identified an optimal cut­off to distinguish between problematic and non-problematic pornography users. In the present sample, 3.6% of the pornography consumers be- longed to the at-risk group. Discussion and Conclusion: The PPCS is a multidimensional scale of problematic pornography consumption with strong theoretical background that also has strong psychometric properties.

Dr Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Don’t blame the game: Parents, videogame content, and age ratings

Back in March 2015, BBC News reported that parents of children in 16 Cheshire county schools had been sent a letter saying that head teachers would report them to the authorities if they allowed their children to play videogames that are rated for adults (i.e., games that have an ‘18’ rating). The teachers claimed that popular games like Grand Theft Auto and Call of Duty are too violent to be played by those under the age of 18 years. They also stated that such games increased sexualised behaviour and left children vulnerable to sexual grooming. The schools also threatened to report parents who let their children play such games because it was a form of parental neglect. The author of the letter, Mary Hennessy Jones, was quoted as saying that:

“We are trying to help parents to keep their children as safe as possible in this digital era. It is so easy for children to end up in the wrong place and parents find it helpful to have some very clear guidelines”.

I’m sure the letter to parents was written with the best of intentions but as a parent of three ‘screenagers’ and someone that has spent almost three decades researching the effects of video games on human behaviour, this appears to be a very heavy-handed way to deal with the issue. Although it is illegal for any retailer to sell ‘18’ rated games to minors, it is not illegal for children to play such games, or illegal for parents to allow their children to play such games. Many parents need to be educated about the positives and negatives of playing video games but reporting them to the “authorities” is not the right way forward.

pegi_ratings_system

Back in the early 1990s I was probably the only academic in the UK carrying out scientific research on children’s video game playing. In fact, I was proud of my role in getting age ratings onto all video games in the first place, and for writing the text for educational information leaflets for parents (outlining the effects of excessive playing of such games) sponsored by the National Council for Educational Technology. There are many positive benefits of playing video games (something that I wrote about in a previous article for The Conversation).

I know from first-hand experience that children often play games that are age-inappropriate. Two years ago, my (then) 13-year old son said he was the only boy in his class that did not play or own the Call of Duty video game. This is also borne out by research evidence. One study that I was involved in found that almost two-thirds of children aged 11- to 13-years of age (63%) had played an 18+ video game. Unsurprisingly, boys (76%) were more likely than girls (49%) to have played an 18+ video game. Children were also asked about how often they played 18+ video games. Of the two-thirds who had played them, 8% reported playing them “all the time”, 22% reported playing them “most of the time”, 50% reported playing them “sometimes”, 18% reported playing them “hardly ever”. Again, boys were more likely than girls to play 18+ video games more frequently. Children were asked how they got access to 18+ plus video games. The majority had the games bought for them by family or friends (58%), played them at a friend’s house (35%), swapped them with friends (27%), or bought games themselves (5%). This research certainly appears to suggest that parents and siblings are complicit in the playing of age-inappropriate games.

There is a growing amount of scientific literature that has examined the content of video games designed for adults. For instance, a study led by Dr. Kimberley Thompson and published in the Archives of Pediatric and Adolescent Medicine attempted to quantify the depiction of violence, blood, sexual themes, profanity, substances, and gambling in adult (18+) video games and to assess whether the actual game content matched the content descriptor on the packaging. Although content descriptors for violence and blood provided a good indication of content in the 36 games examined, the authors concluded that 81% of the games studied (n=29) lacked content descriptors of other adult content. Other studies carried out by the same research team have found that adult content can be found in lots of games aimed at young children and teenagers.

Another study led by Dr. David Walsh published in Minerva Pediatrica tested the validity of media rating systems (including video games). Results showed that when the entertainment industry rated a product as inappropriate for children, parents also agreed that it was inappropriate. However, parents disagreed with many industry ratings that were designated as containing material as suitable for children. The products rated as appropriate for adolescents by the industry were of the greatest concern to parents.

The issue of children and adolescents playing 18+ games is no different from the debates about children and adolescents watching 18+ films. However, based on anecdotal evidence appears that parents are more likely to adhere to age ratings on films than they are on video games. This is one area that both media researchers and media educators need to inform parents to be more socially responsible in how they monitor their children’s leisure activity. A school sending out a threatening letter to parents is unlikely to change parental behaviour. Education and informed debate is likely to have a much greater effect in protecting our children from the potential harms of video game playing.

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

 Further reading

Anderson, C.A., Gentile, D.A., & Dill, K.E. (2012). Prosocial, antisocial and other effects of recreational video games. In D.G. Singer, & J.L. Singer (Eds), Handbook of Children and the Media, Second Edition, (pp. 249-272). Thousand Oaks, CA: Sage.

Anderson, C. A., Shibuya, A., Ihori, N., Swing, E. L., Bushman, B.J., Sakamoto, A., Rothstein, H.R., & Saleem, M. (2010). Violent video game effects on aggression, empathy, and prosocial behavior in eastern and western countries: a meta-analytic review. Psychological Bulletin, 136, 151-173.

Bartlett, C. P., Anderson, C.A. & Swing, E.L. (2009). Video game effects confirmed, suspected and speculative: A review of the evidence. Simulation and Gaming, 40, 377-403.

Ferguson, C. J. (2007). Evidence for publication bias in video game violence effects literature: A meta analytic review. Aggression and Violent Behavior, 12, 470-482.

Ferguson, C. J. (2013). Violent video games and the supreme court: Lessons for the scientific community in the wake of Brown v. Entertainment Merchants Association. American Psychologists, 68, 57-74.

Ferguson, C. J., San Miguel, S. & Hartley, T. (2009).  Multivariate analysis of youth violence and aggression: The influence of family, peers, depression and media violence. Journal of Paediatrics, 155, 904-908.

Gentile, D. A. & Stone, W. (2005). Violent video game effects in children and adolescents: A review of the literature. Minerva Pediatrics, 57, 337-358.

Griffiths, M.D. (1998). Video games and aggression: A review of the literature. Aggression and Violent Behavior, 4, 203-212.

Griffiths, M.D. (2000). Video game violence and aggression: Comments on ‘Video game playing and its relations with aggressive and prosocial behaviour’ by O. Weigman and E.G.M. van Schie. British Journal of Social Psychology, 39, 147-149.

Griffiths, M.D. (2010). Age ratings on video games: Are the effective? Education and Health, 28, 65-67.

Griffiths, M.D. & McLean, L. (in press). Content effects: Online and offline games. In P. Roessler (Ed.), International Encyclopedia of Media Effects. Chichester: Wiley.

Grüsser, S.M., Thalemann, R. & Griffiths, M.D. (2007). Excessive computer game playing: Evidence for addiction and aggression?  CyberPsychology and Behavior, 10, 290-292.

Ivory, J.D., Colwell, J., Elson, M., Ferguson, C.J., Griffiths, M.D., Markey, P.M., Savage, J. & Williams, K.D. (2015). Manufacturing consensus in a divided field and blurring the line between the aggression concept and violent crime. Psychology of Popular Media Culture, 4, 222–229.

McLean, L. & Griffiths, M.D. (2013). The psychological effects of videogames on young people. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 31(1), 119-133.

McLean, L. & Griffiths, M.D. (2013). Violent video games and attitudes towards victims of crime: An empirical study among youth. International Journal of Cyber Behavior, Psychology and Learning, 2(3), 1-16.

Mehroof, M. & Griffiths, M.D. (2010). Online gaming addiction: The role of sensation seeking, self-control, neuroticism, aggression, state anxiety and trait anxiety. Cyberpsychology, Behavior, and Social Networking, 13, 313-316.

Aid and a bet: Can personalised feedback help online gamblers play more responsibly?

In recent years, online gambling has become a more common leisure time activity. Research around the world suggests around 8-16% of adults have gambled online during the past year. Research has also demonstrated that there are a number of situational and structural characteristics that make online gambling potentially risky for susceptible and vulnerable individuals. Such factors include increased accessibility, affordability, anonymity and specific structural features of online games such as high event frequency. In addition, some forms of online gambling may be more problematic than others (e.g., online poker, online casino games).

A number of scientific studies have also shown that there are typically more problematic gamblers among those that gamble on the internet compared to those that only gamble in land-based venues. However, problem gambling severity is associated with overall engagement and that when the volume of gambling is controlled for, Internet gambling is not predictive of problems. Furthermore, most online gamblers are also offline gamblers and gamble on many different activities and across different gambling platforms.

Given the increasing number of people gambling online and issues surrounding problem gambling, many of the more socially responsible gambling companies around the world have started to use responsible gambling tools to help their clientele gamble more safely (such as the option to set time and money spending limits or to temporarily self-exclude from gambling for a day, week, month, or longer). In fact, one of our own studies recently demonstrated that the use of both time and money spending limits are most effective among gamblers that play most frequently, and that the effects are differential. For instance, time spending limits were most useful for online poker players and monetary spending limits were most useful for online casino players.

In addition, gamblers can now access and/or are given general advice on healthy and responsible gambling, as well as information about common misbeliefs and erroneous perceptions concerning gambling. However, findings on the effectiveness of providing gamblers with information in correcting or changing erroneous beliefs have been mixed. Some outcomes support the display of information, while other studies have reported non-significant results.

Studies have also shown that the way information is presented can significantly influence behaviour and thinking. Several studies have investigated the effects of interactive versus static pop-up messages during gambling sessions. Static messages do not appear to be effective, whereas interactive pop-up messages and animated information have been shown to change both irrational belief patterns and behaviour of gamblers. It has also been suggested that informational warning signs should promote the application of self-appraisal and self-regulation skills rather than the simple provision of information.

In one of our more recent studies, we investigated the effect of a pop-up message that appeared after 1,000 consecutive online slot machine games had been played during a single gambling session using behavioural tracking data. Our study analysed 400,000 gambling sessions (200,000 sessions before the pop-up had been introduced and 200,000 after the pop-up had been introduced). We found that the pop-up message had a limited effect on a small percentage of players. Although the study reported nine times as many gamblers stopped after 1000 consecutive plays compared to those gamblers before the introduction of the pop-up message, the number of gamblers that actually stopped after viewing the pop-up message was less than 1%.

In a follow-up study, we investigated the effects of normative and self-appraisal feedback in a slot machine pop-up message compared to a simple (non-enhanced) pop-up message. The study compared two representative random samples of 800,000 gambling sessions (i.e., 1.6 million sessions in total) across two conditions (i.e., simple pop-up message versus an enhanced pop-up message). The results indicated that the additional normative and self-appraisal content doubled the number of gamblers who stopped playing after they received the enhanced pop-up message (1.39%) compared to the simple pop-up message (0.67%). Like our previous study, the findings suggested that pop-up messages influence only a small number of gamblers to cease long playing sessions but that enhanced messages are slightly more effective in helping gamblers to stop playing within-session. Our two studies evaluating pop-up messages are the only published studies that examine the impact of messaging on actual gamblers in a real world online gambling environment.

In order to make individuals gamble more responsibly using behavioural tracking data, we believe that player feedback should also be presented in a motivational way. In practical terms, this means presenting messages in a non-judgmental way alongside normative data so that gamblers can evaluate their actions compared to other like-minded individuals. One of our most recent studies examined personalised feedback and information given to players during real world gambling sessions. We hypothesized that gamblers receiving tailored feedback about their online gambling behaviour would be more likely to change their behaviour (as measured by the amount of time and money spent) compared to those who did not receive tailored feedback.

We were given access to the behavioural tracking data of 1,358 gamblers at a European online gambling website that had voluntarily signed up to a behavioural feedback system that we developed (called mentor) that is offered to all customers on the website. The system is an opt-in system (i.e., gamblers can voluntarily choose to use it and the system is not mandatory). Once gamblers have enrolled to use the system, they can retrieve detailed visual and numerical feedback about their gambling behaviour via a button on the website. Player feedback is displayed in a number of ways (numerical, graphical, and textual) and provides information about wins and losses, playing duration, number of playing days, and games played. The system can also display personal gambling behaviour over time. For instance, Figure 1 shows the playing time information for a hypothetical player in the form of a graph over time.

At the top of the screen, players receive information about playing time over the previous 4-week and 24-week period. The white line in Figure 1 indicates that the player shows an upward trend and is steadily increasing the amount of time spent gambling. During the previous 4-week period, the player spent 25.75 hours gambling online. The upper line in Figure 1 is the average playing time for all other comparable online players (depending upon what types of game are typically played) and provides the gambler both normative and comparative feedback. Such feedback has been emphasized as an important aspect in facilitating behavioural change. Players are either assigned to ‘lottery’ type players or ‘casino’ type players based on their playing patterns.

Of the daily active players, 10% (n=1,358) opted into the system. Players could opt-in via a clearly visible button on the post-login website page which appeared immediately after they logged into their account. The personalised information appeared in a new pop-up window. This typically led to a break in play, as gamblers who viewed the information are unlikely to play and view information simultaneously. The system tracks those players who sign up and therefore the opt-in date is known and can also be used for analytical purposes.

All the visual, numerical, and textual information can be accessed by the gambler via a user-friendly on-screen dashboard. Responsiveness means that interactive content automatically adapts to technical environments. The player front end thus looks similar on different devices such as desktops, laptops, mobile phones, or tablets and also across different browsers and operating systems such as Windows, Android or iOS.

We investigated whether players’ behaviour changed after they have registered for the mentor system and saw the personalised feedback for the first time. We then compared their gambling behaviour with over 15,000 online gamblers displaying the same types of gambling behaviour (i.e., matched controls). Our results indicated that the personalised feedback system achieved the hypothesised effect and that the time and money spent gambling was significantly reduced compared to the online gambler control group that did not utilize the mentor system. The results suggest that responsible gambling tools such as mentor may help the clientele of gambling companies gamble more responsibly, and may be of help those who gamble excessively.

To our knowledge, this study was the first real world study investigating the effects of behavioural feedback on actual gambling behaviour within a real online gambling website. However, there were a number of limitations. For instance, all of the players in the target population had voluntarily registered to use the mentor system and were therefore not selected randomly from the population of players (but we tried to overcome this by using a control group of matched pairs). In addition, the reliability of our findings is limited because our data were only collected from one online gambling environment. It may also the case that players who voluntarily signed up to receive personalised messages about their gambling were different in other ways from controls (i.e., gamblers who voluntarily signed up to receive personalised messages may have already been interested in reducing their gambling and would be likely to gamble less).

Another limitation is that we did not know whether any of the gamblers who voluntarily opted to use the mentor system were problem gamblers. Therefore we do not know whether the system captures gamblers most in need of such interventions. Based on the findings, one explanation may be that the tool may simply be curtailing gambling in those who already play responsibly. Although our study was performed in a real world setting utilising objective behavioural data, it is limited because the motivations and thoughts of the players were unknown and can only be inferred.

Online gambling operators have the technical capabilities to introduce behavioural feedback systems such as the one we described in our paper, and our findings suggest that a system like mentor can help players limit the amount of time and money spent gambling can be achieved. However, the findings are preliminary and future research should focus on investigating at which point in time players should receive personalised messages to optimize behavioural change.

Dr Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Auer, M. & Griffiths, M. D. (2013). Voluntary limit setting and player choice in most intense online gamblers: An empirical study of gambling behaviour. Journal of Gambling Studies, 29, 647-660.

Auer, M. & Griffiths, M. D. (2014). Personalised feedback in the promotion of responsible gambling: A brief overview. Responsible Gambling Review, 1, 27-36.

Auer, M. & Griffiths, M. D. (2015). Testing normative and self-appraisal feedback in an online slot-machine pop-up message in a real-world setting. Frontiers in Psychology, 6, 339. doi: 10.3389/fpsyg.2015.00339.

Auer, M. & Griffiths, M. D. (2015). The use of personalized behavioral feedback for problematic online gamblers: An empirical study. Frontiers in Psychology, 6, 1406. doi: 10.3389/fpsyg.2015.01406.

Auer, M. & Griffiths, M.D. (2016). Personalized behavioral feedback for online gamblers: A real world empirical study. Frontiers in Psychology, 7, 1875. doi: 10.3389/fpsyg.2016.01875. 

Auer, M., Littler, A. & Griffiths, M.D. (2015). Legal aspects of responsible gaming pre-commitment and personal feedback initiatives. Gaming Law Review and Economics, 6, 444-456.

Auer, M., Malischnig, D. & Griffiths, M.D. (2014). Is ‘pop-up’ messaging in online slot machine gambling effective? An empirical research note. Journal of Gambling Issues, 29, 1-10.

Leisure pleasure treasure: A brief look at gambling within videogames

Over the last decade, gambling and gaming technologies have begun to converge with video games featuring gambling-like elements, and gambling games featuring video gaming-like elements. Many of the newer convergent gambling-gaming convergent forms include such activities as online penny auctions and gambling-type activities on social networking sites, so-called ‘social gaming’. With regard to video gaming including gambling-like elements, a paper that I co-wrote in 2012 with Dr. Daniel King in the journal International Gambling Studies noted that simulated gambling activities and gambling themes have a substantial presence in many modern video games. We noted that gambling content in video games can be categorized according to the following three categories:

  • Standard gambling simulation, a digitally simulated interactive gambling activity that is structurally identical to the standard format of an established gambling activity, such as blackjack or roulette;
  • Non-standard gambling simulation, an interactive gambling activity that involves the intentional wagering of in-game credits or other items on an uncertain outcome, in an activity that may be partially modelled on a standard gambling activity but which contains distinct player rules or other structural components that differ from established gambling games;
  • Gambling references, the appearance of non-interactive gambling material or gambling-related paraphernalia/materials within the context of the video game.

In regard to the second of these categories, it could be argued that some online video games feature mini-games that are non-standard gambling simulations. For instance, in February 2014, the mini-game Treasure Hunter (TH) was introduced into the online video game Runescape. To get in-game prizes, players have to get keys to open chests. Originally, to participate in TH, players had to play in a members’ world. Players that tried to play TH in a free world are given the message: “As a member, you are eligible for improved prizes, so please play Treasure Hunter on a members’ world instead.” However, in April 2014, TH was reformulated and for the first time, members’ prizes could be claimed by those playing in a free world also.

treasurehunterbanner

In TH, five chests can be opened, each containing one of five different gems (going from most common to least common – white, yellow, orange, red, or purple gem – with white being the most common and purple being the rarest). After obtaining a key, players select a chest (not knowing what gem is inside the chest), and open it. The player is then given the option of storing the prize in the bank, discarding the prize, collecting the prize later, or cashing out for a small number of coins. There are a number of different ways to gain TH keys (free daily keys, keys obtained through skilful gameplay, and buying keys). Members get two free keys a day and those playing in free worlds only get one free key a day. Those players paying to be in the silver or gold Premier Club get three free keys a day.

It should also be noted that (i) TH is reset every night at midnight, (ii) free keys have to be used on the day, (iii) one monthly free key can be earned by playing ‘Troll Invasion’, (iv) players can buy bonds for gold coins or money, and (v) a random number generator is used to determine the winners. After completing any daily challenge, players receive an extra key, and after completing any in-game quest, players receive two additional keys. Keys can be bought in bundles of 15 (€3.99), 35 (€8.00), 75 (€16.00), 200 (€39.99) or 450 keys (€79.99). The maximum number of keys that could be bought is $200 (US) a day and $500 (US) a week. Keys can also be earned by watching advertisements, buying products, and completing surveys (and accessed via the ‘Earn keys’ option). TH prizes include in-game skilling items, weapons, bonus experience stars, etc. or can be converted to coins.

The legal definition of gambling in Great Britain is contained in the Gambling Act 2005. It notes that gambling includes “gaming”, “betting” or “participating in lottery”. Gaming is defined in the 2005 Act as “playing a game of a chance for a prize” while betting involves the process of placing or accepting a bet on anything other than financial services that remains uncertain to at least one party of the transaction at the time of the bet. By this definition alone, it would appear that Treasure Hunter is a form of gambling if purchases to participate are made (rather than being given free spins or keys, or earning them through skilful gameplay).

In 2015, the UK Gambling Commission highlighted that they believe the mini-games within Runescape to be ‘social gaming’ and not a game of chance and therefore out of their jurisdiction in relation to the regulation of the game. They have also claim that RuneScape bonds have no intrinsic value outside of Runescape under the terms of the British Gambling Act and therefore is not gambling. The Gambling Commission also note on their website that:

“We are not saying there are no risks in social gaming, nor are we saying that this ends our interest in the issue. We are simply saying that our current assessment of the available evidence is that there is no persuasive reason for us to take regulatory action, in effect to change from maintaining a watching brief. We will continue to monitor emerging evidence, and we are prepared to change this position if the evidence warrants it”.

However, there are instances when the bonds and prizes won do have value outside of the game. Bonds that are purchased with real life currency can be sold to another player for an in-game sum of money. Bonds and prizes can also be redeemed within the game for real-life services. These services are not just limited to the buying of game-related merchandise, such as the buying of card games like Top Trumps, but also includes attendance at offline RuneScape events, such as RuneFest, hotel rooms, and even plane tickets. The bonds can also be used to pay for postage and packing of items bought outside the game. Players can also donate the bonds to charity (in which Jagex contributes the full value of the bond to the charity chosen by the player). These examples clearly demonstrate that the bonds do have specific financial value outside the game in some circumstances, and an impact on real-world activities. More specifically, they demonstrate that the financial value of the bonds and prizes can be used outside the game itself.

Mini-games like Treasure Hunter within the online game RuneScape are not uncommon and are another example of convergence between gambling and video gaming. These games appear to meet the criteria for gambling found in the gambling studies literature and should be regulated as such.

Dr. Mark Griffiths, Professor of Behavioural Addictions, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Gambling Commission (2015). Explaining our approach to social gaming. Located at: http://www.gamblingcommission.gov.uk/Gambling-data-analysis/Social-media/Explaining-our-approach-to-social-gaming.aspx

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

Griffiths, M.D. (2015). Adolescent gambling and gambling-type games on social networking sites: Issues, concerns, and recommendations. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 33(2), 31-37.

Griffiths, M.D. & Carran, M. (2015). Are online penny auctions a form of gambling? Gaming Law Review and Economics, 19, 190-196.

Griffiths, M.D., King, D.L. & Delfabbro, P.H. (2009). Adolescent gambling-like experiences: Are they a cause for concern? Education and Health, 27, 27-30.

Griffiths, M.D., King, D.L. & Delfabbro, P.H. (2014). The technological convergence of gambling and gaming practices. In Richard, D.C.S., Blaszczynski, A. & Nower, L. (Eds.). The Wiley-Blackwell Handbook of Disordered Gambling (pp. 327-346). Chichester: Wiley.

Griffiths, M.D. & King, R. (2015). Are mini-games within RuneScape gambling or gaming? Gaming Law Review and Economics, 19, 64-643.

King, D.L., Delfabbro, P.H., Derevensky, J. & Griffiths, M.D. (2012). A review of Australian classification practices for commercial video games featuring simulated gambling. International Gambling Studies, 12, 231-242.