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Teaming reign: A brief look at marketing convergence in online sports betting

The marketing cycle of a typical online betting firm aptly illustrates the converging nature of sports and its neighbouring industries. For instance, consider the following football narrative. A betting site buys advertisement space in a national newspaper. The online edition of that newspaper accompanies the advertisement with an active link. If a user clicks on it and access the betting site, the newspaper as an affiliate marketer will get 30% of the money that user has lost betting. In order to boost the number of users clicking on it, the paper publishes next to it a news article featuring Real Madrid on the eve of a match against Manchester United with the following headline: ‘Cristiano Ronaldo scored in 4 of his last 5 visits to Old Trafford’. Now, the journalist shares the link to that piece of news on Twitter, predicting a goal from Ronaldo, with a non-negligible likelihood that he or she is in business with a betting company, according to what was found in a 2014 sample of the ten most followed sports journalists in Spain.

The tweet might be read by someone at home, or even in the stands of a stadium as the game is being played, in which case a betting company might have sponsored the installation of high-speed Wi-Fi connection to facilitate bets. The bet will be preferably made in the proprietary app of the team, who partnered with the betting firm for an amount of money in exchange for adorning the stadium with the brand’s logo, although exclusivity in the electronic banners surrounding the pitch is not possible since the home team must comply with the different betting partners of the league.

Generating-Income-from-Sports-Betting-Affiliate-Programs

Chances are that those at home watching the game on television will hear a litany of statistics about the game delivered by the commentators, provided by a data company like Perform or Dimension Data, who in turn also provide those same data to betting companies, and which are also in a partnership with the league. It is these same data that will inform a fantasy league competition, which also sponsors the league. It might be the case that among the members of the family watching the game at home there are minors who cannot legally gamble for money, for whom a social gaming alternative is also available that can smooth the transition towards real money gambling in the future.

Also, for some demographic groups, sports betting might not be as appealing as eSports, but sport teams have already started sponsoring players in those competitions. When the match has finished, fans can watch further gambling commercials such as ones related to poker, conveniently introduced by sportsmen such as Neymar, Rafael Nadal or Cristiano Ronaldo, or indulge themselves in a little trading in the forex market company Xtrade endorsed by Cristiano Ronaldo himself.

A potential downside of such convergence might be the errors derived by a faulty identification of each product’s category and characteristics. The border between not-for-real-money social gaming on sports and real money gambling might not be obvious, especially when gambling gradually approaches gaming with more gamification attributes being added to the betting experience, and simultaneously, gaming approaches gambling by implementing real or virtual money in-app micro purchases or simulating gambling environments. Blurred lines might impact the understanding of what is information and what is promotion, as has been observed with children having problems distinguishing gambling advertising from non-advertising content (as demonstrated by Helena Sandberg and her colleagues in a 2011 issue of the International Journal of Communication). Another downside could be the transference of positive attributes from sport to other markets (most notably financial trading or poker in the example above), that buy their way into the mental association by, for instance, becoming a named sponsor of a sporting competition.

However, neither the situational and structural characteristics nor the cross-marketing convergence act as singular factors determining online betting behaviour. More likely, they work by aggregation, populating a marketing and advertising ecosystem that far from curtailing other gambling motivating factors – individual factors such as the biological, psychological or social characteristics of the gambler – it facilitates them.

(Please not that this article was co-written with Dr. Hibai Lopez-Gonzalez).

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

Further reading

Deans, E.G., Thomas, S.L,. Derevensky, J. & Daube, M. (2017) The influence of marketing on the sports betting attitudes and consumption behaviours of young men: implications for harm reduction and prevention strategies. Harm Reduction Journal, 14(5). doi:10.1186/s12954-017-0131-8.

Deans, E.G., Thomas, S.L,. Daube, M. & Derevensky J (2016) The role of peer influences on the normalisation of sports wagering: a qualitative study of Australian men. Addiction Research & Theory. doi: 10.1080/16066359.2016.1205042.

Gainsbury, S.M., Delfabbro, P., King, D.L., et al. (2016) An exploratory study of gambling operators’ use of social media and the latent messages conveyed. Journal of Gambling Studies, 32, 125–141.

Gordon, R. & Chapman, M. (2014). Brand community and sports betting in Australia. Victoria, Australia: Victorian Responsible Gambling Foundation.

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

Hing, N., Lamont, M., Vitartas, P., et al. (2015). Sports-embedded gambling promotions: A study of exposure, sports betting intention and problem gambling amongst adults. International Journal of Mental Health and Addiction, 13(1), 115–135..

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., Estevez, A. & Griffiths, M.D. (2017). Marketing and advertising online sports betting: A problem gambling perspective. Journal of Sport and Social Issues, 41, 256-272.

Lopez-Gonzalez, H., Estévez, A. & Griffiths, M.D. (2017). Controlling the illusion of control: A grounded theory of sports betting advertising in the UK. International Gambling Studies, in press.

Lopez-Gonzalez, H. & Griffiths, M.D. (2017). Betting, forex trading, and fantasy gaming sponsorships – A responsible marketing inquiry into the ‘gamblification’ of English football. International Journal of Mental Health and Addiction, in press.

Lopez-Gonzalez,Generating-Income-from-Sports-Betting-Affiliate-Programs 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., Guerrero-Sole, F. & Griffiths, M.D. (2017). A content analysis of how ‘normal’ sports betting behaviour is represented in gambling advertising. Addiction Research and Theory, in press.

Lopez-Gonzalez, H. & Tulloch, C.D. (2015) Enhancing media sport consumption: Online gambling in European football. Media International Australia, 155, 130–139.

Sandberg, H., Gidlof, K. & Holmberg, N. (2011). Children’s exposure to and perceptions of online advertising. International Journal of Communication, 5, 21–50.

Working while lurking: A brief look at participant observation in online forums

In offline situations, many social science researchers have employed ethnographic methods as a means of understanding and describing different culture and behaviours. However, ethnographic methods can also be used online for studying various types of excessive behaviour. For instance, I argued in a 2010 paper in the International Journal of Mental Health and Addiction that by being online, gaming researchers have the capacity to become a part of the phenomenon that is being studied. Recently, I along with a number of my research colleagues at Nottingham Trent University, published a paper in Studia Psychologia that online forums are providing a new and innovative methodology for data collection in the social sciences.

cyberpsychology

For those who don’t know, ethnography focuses on accounting for the actions and intentions of the studied social agents, and outlining how such behaviour is rationalized and understood by the wider group. Traditionally derived from anthropology, ethnography aims at studying people and their behaviours and cultures within their socio-cultural contexts. Behaviours and communications are engulfed with meaning by being situated within the field site. What is needed on behalf of the researcher is what Dr. Clifford Geertz described as the production of a “thick description” of what takes place in these field sites to discern the latter’s contextualized meaning.

When it comes to virtual (i.e., online) ethnography, it is important to notice that while in-person ethnography is constrained by the laws of the physical world where the researcher needs to interact with the participants, online ethnography or as Dr. Robert Kozinets calls it in his 2010 book about online ethnography – “netnography” – can be done in a more unobtrusive way without the need to interact with the participants. Lurking is a possibility that Dr. Kozinets describes as opening a “window into naturally occurring behaviour” without the interference of the researcher.

Virtual ethnography takes the idea of participant observation a step further by challenging the notion of a geographically bound and relatively stagnant field site by replacing it with the virtual sphere that has no set boundaries. In this respect, virtual ethnography is what Dr. Christine Hine says “ethnography in, of and through the virtual”. The Internet is used as place, topic and means of research. It is an important qualitative online methodology and has been used in a variety of different research endeavours, including the studies of people’s explorations of multi-layered identities on the Internet, different levels of online experience, and playing Massively Multiplayer Online Role-Playing Games such as Everquest.

There are a number of principles that underlie virtual ethnography. Ethnographers must immerse themselves in the (virtual) field site in order to gain an in depth insight into why and how interactions take place and what they mean within the context of the respective virtual sphere. However, the relationship of the latter’s agents to their real (embodied) lives cannot be disregarded. The online space is a space ‘in between’ that is connected to the world outside of the Internet. Therefore, virtual ethnography is but a partial study and cannot deliver a full account of what it sets out to study. It can never be a holistic approach. Nevertheless, this is aided by the researchers who must be reflexive about what they experience, and about the method they use. The involvement of the researcher and the researcher’s interpretation of the actions and communications that occur within the virtual field site are integral to this type of research. In addition to this, the technology of the Internet itself is essential because it provides the tools for, the objects and the context of analysis.

Given the wide variety of advantages of and important insights virtual ethnography can offer for the researcher, potential disadvantages also need to be taken into consideration. The researchers’ active participation in the field site offers them the possibility of in-depth insights that would not be possible without their involvement. However, at the same time, they might lose their critical distance towards the object of their study. Sacrificing some critical distance therefore is a trade-off for in the collection of invaluable and profound data. As Dr. Christine Hine notes, these data are necessarily biased by the researchers’ experience and perception of online interactions in the respective realm that, due to their immersion, is knowledgeable and familiar.

Dr. Adrian Parke and I applied online ethnography to the study of poker skill development within online poker forums, and published our findings in a 2011 issue of the International Journal of Cyber Behavior, Psychology and Learning. Our study was a virtual ethnographical research design looking at how poker gamblers utilized computer-mediated communication (CMC) to develop their poker skill and profitability, and to examine the factors associated with problem gambling. The study was a six-month participant observational analysis of two independent online poker forums. Dr. Parke participated in poker gambling during the entire study period and used strategies proposed from forum members to develop poker ability. This approach provided an insider’s perspective into how skill development through CMC affects poker gambling behaviour.

We generated forum discussions regarding specific behavioural concepts and cognitive processes based on accumulative analysis of emergent data from the online poker players. Forum interaction was observed, monitored and analyzed through traditional content analytic methods. Membership and participation in such online community forums provided poker players the opportunity to benefit from the consequences of reporting gambling experience and acquiring both poker gambling structural knowledge and skill.

One of the key advantages of data collection via online forums is that it can provide a detailed record of events that can be revisited after the event itself has finished. Furthermore, screen captures can be taken and used as examples or related back to the data collected – something that has been used in the gaming studies field (and outlined in a 2007 paper I published with Dr. Richard Wood in the International Journal of Mental Health and Addiction). Study findings can be posted on bulletin boards and participants have the opportunity to comment on their accuracy or comment on any other observations that they may have. This also helps to empower the participant and can prevent misrepresentation.

Given the increase in the number of hours we now spend online every day, carrying out research online is going to become an ever more popular (and useful).

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

Further reading

Geertz, C. (1973). The interpretation of cultures: Selected essays. London: Fontana Press. 

Griffiths, M.D. (2010). The use of online methodologies in data collection for gambling and gaming addictions. International Journal of Mental Health and Addiction, 8, 8-20.

Griffiths, M.D., Lewis, A., Ortiz de Gortari, A.B. & Kuss, D.J. (2016). Online forums and blogs: A new and innovative methodology for data collection. Studia Psychologica, in press.

Hine, C. (Ed.). (2005). Virtual methods. Issues in social research on the Internet. Oxford, UK: Berg.

Hine, C. (2000). Virtual ethnography. London: Sage.

Kozinets, R.V. (2010). Netnography. Doing ethnographic Research Online. Sage: London.

Parke, A., & Griffiths, M.D. (2011). Poker gambling virtual communities: The use of Computer-Mediated Communication to develop cognitive poker gambling skills. International Journal of Cyber Behavior, Psychology and Learning, 1(2), 31-44.

Wood, R.T.A. & Griffiths, M.D. (2007). Online data collection from gamblers: Methodological issues. International Journal of Mental Health and Addiction, 5, 151-163.

Wood, R.T.A., Griffiths, M.D. & Eatough, V. (2004). Online data collection from videogame players: Methodological issues. CyberPsychology and Behavior, 7, 511-518.

Back tracking: A brief look at using big data in gambling research

I’ve been working in the area of gambling for nearly 30 years and over the past 15 years I have carrying out research into both online gambling and responsible gambling. As I have outlined in previous blogs, one of the new methods I have been using in my published papers is online behavioural tracking. The chance to carry out innovative research in both areas using a new methodology was highly appealing – especially as I have used so many other methods in my gambling research (including online and offline surveys, experiments in laboratories and ecologically valid settings, offline focus groups, online and offline case study interviews, participant and non-participation observation, secondary analysis of survey data, and analysis of various forms of online data such as those found in online forums and online diary blogs).

Over the last decade there has been a big push by gambling regulators for gambling operators to be more socially responsible towards its clientele and this has led to the use of many different responsible gambling (RG) tools and initiatives such as voluntary self-exclusion schemes (where gamblers can ban themselves from gambling), limit setting (where gamblers can choose how much time and/or money they want to lose while gambling), personalized feedback (where gamblers can get personal feedback and advice based on their actual gambling behaviour) and pop-up messages (where gamblers receive a pop-up message during play that informs them how long they have been playing or how much money that have spent during the session).

However, very little is known about whether these RG tools and initiatives actually work, and most of the research that has been published relies on laboratory methods and self-reports – both of which have problems as reliable methods when it comes to evaluating whether RG tools work. Laboratory experiments typically contain very few participants and are carried out in non-ecologically valid settings, and self-reports are prone to many biases (including social desirability and recall biases). Additionally, the sample sizes are also relatively small (although bigger than experiments).

The datasets to analyse player behaviour are huge and can include hundreds of thousands of online gamblers. Given that my first empirical paper on gambling published in the Journal of Gambling Studies in 1990 was a participant observational analysis of eight slot machine gamblers at one British amusement arcade, it is extraordinary to think that decades later I have access to datasets beyond anything I could have imagined back in the 1980s when I began my research career. The data analysis is carried with my research colleague Michael Auer who has a specific expertise in data mining and we use traditional statistical tests to analyse the data. However, the hardest part is always trying to work out which parameters to use in assessing whether the RG tool worked or not. The kind of data we have includes how much time and money that players are spending on the gambling website, and using that data we can assess to what extent the amount of time and money decreases as a result of using limit setting measures, or receiving personalized feedback or a pop-up message.

One of the biggest problems in doing this type of research in the gambling studies field is getting access to the data in the first place and the associated issue of whether academics should be working with the gambling industry in the first place. The bottom line is that we would never have been able to undertake this kind of innovative research with participant sizes of hundreds of thousands of real gamblers without working in co-operation with the gambling industry. (It should also be noted that the gambling companies in question did not fund the research but provided simply provided access to their databases and customers). In fact, I would go as far as to say the research would have been impossible without gambling industry co-operation. Data access provided by the gambling industry has to be one of the key ways forward if the field is to progress.

Unlike other consumptive and potentially addictive behaviours (smoking cigarettes, drinking alcohol, etc.), researchers can study real-time gambling (and other potentially addictive behaviours like video gaming and social networking) in a way that just cannot be done in other chemical and behavioural addictions (e.g., sex, exercise, work, etc.) because of online and/or card-based technologies (such as loyalty cards and player cards). There is no equivalent of this is the tobacco or alcohol industry, and is one of the reasons why researchers in the gambling field are beginning to liaise and/or collaborate with gambling operators. As researchers, we should always strive to improve our theories and models and it appears strange to neglect this purely objective information simply because it involves working together with the gambling industry. This is especially important given the recent research by Dr. Julia Braverman and colleagues published in the journal Psychological Assessment using data from gamblers on the bwin website showing that self-recollected information does not match with objective behavioural tracking data.

The great thing about online behavioural tracking data collected from gamblers is that it is totally objective (as it provides a true record of what every gambler does click-by-click), is collected from real world gambling websites (so is ecologically valid), and has large sample sizes (typically tens of thousands of online gamblers). There of course some disadvantages, the main ones being that the sample is unrepresentative of all online gamblers (as the data only comes from gamblers at one website) and nothing is known about the person’s gambling activity at other websites (research has shown that online gamblers typically gamble at a number of different websites and not just one). Despite these limitations, the analysis of behavioural tracking data (so-called ‘big data’) is a reliable and cutting-edge way to assess and evaluate online gambling behaviour and to assess whether RG tools actually work in real world gambling settings with real online gamblers in real time.

To get access to such data you have to cultivate a trusting relationship with the data providers. It took me years to build up trust with the gambling industry because researchers who study problem gambling are often perceived by the gambling industry to be ‘anti-gambling’ but in my case this wasn’t true. I am ‘pro-responsible gambling’ and gamble myself so it would be hypocritical to be anti-gambling. My main aim in my gambling research is to protect players and minimise harm. Problem gambling will never be totally eliminated but it can be minimised. If gambling companies share the same aim and philosophy of not wanting to make money from problem gamblers but to make money from non-problem gamblers, then I would be prepared to help and collaborate.

You also need to be thick-skinned. If you are analysing any behavioural tracking data provided by the gambling industry, then you need to be prepared for others in the field criticizing you for working in collaboration with the industry. Although none of this research is funded by the industry, the fact that you are collaborating is enough for some people to accuse you of not being independent and/or being in the pockets of the gambling industry. Neither of these are true but it won’t stop the criticism. Nor will it stop me from carrying on researching in this area using datasets provided by the gambling industry.

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

Further reading

Auer, M. & Griffiths, M.D. (2013). Behavioral tracking tools, regulation and corporate social responsibility in online gambling. Gaming Law Review and Economics, 17, 579-583.

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. (2014). An empirical investigation of theoretical loss and gambling intensity. Journal of Gambling Studies, 30, 879-887.

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). Theoretical loss and gambling intensity (revisited): A response to Braverman et al (2013). Journal of Gambling Studies, 31, 921-931.

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., 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.

Auer, M., Schneeberger, A. & Griffiths, M.D. (2012). Theoretical loss and gambling intensity: A simulation study. Gaming Law Review and Economics, 16, 269-273.

Braverman, J., Tom, M., & Shaffer, H. J. (2014). Accuracy of self-reported versus actual online gambling wins and losses. Psychological Assessment, 26, 865-877.

Griffiths, M.D. (1990). Addiction to fruit machines: A preliminary study among males. Journal of Gambling Studies, 6, 113-126.

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. & Auer, M. (2015). Research funding in gambling studies: Some further observations. International Gambling Studies, 15, 15-19.

You bet! A brief overview of our recent papers on youth gambling

Following my recent blogs where I outlined some of the papers that my colleagues and I have published on mindfulness, Internet addiction, and gaming addiction, here is a round-up of recent papers that my colleagues and I have published on adolescent gambling.

Calado, F., Alexandre, J. & Griffiths, M.D. (2014). Mom, Dad it’s only a game! Perceived gambling and gaming behaviors among adolescents and young adults: An exploratory study. International Journal of Mental Health and Addiction, 12, 772-794.

  • Gambling and gaming are increasingly popular activities among adolescents. Although gambling is illegal in Portugal for youth under the age of 18 years, gambling opportunities are growing, mainly due to similarity between gambling and other technology-based games. Given the relationship between gambling and gaming, the paucity of research on gambling and gaming behaviors in Portugal, and the potential negative consequences these activities may have in the lives of young people, the goal of this study was to explore and compare the perceptions of these two behaviors between Portuguese adolescents and young adults. Results from six focus groups (comprising 37 participants aged between 13 and 26 years) indicated different perceptions for the two age groups. For adolescents, gaming was associated with addiction whereas for young adults it was perceived as a tool for increasing personal and social skills. With regard to gambling, adolescents associated it with luck and financial rewards, whereas young adults perceived it as an activity with more risks than benefits. These results suggest developmental differences that have implications for intervention programs and future research.

Delfabbro, P.H., King, D.L. & Griffiths, M.D. (2014). From adolescent to adult gambling: An analysis of longitudinal gambling patterns in South Australia. Journal of Gambling Studies, 30, 547-563.

  • Although there are many cross-sectional studies of adolescent gambling, very few longitudinal investigations have been undertaken. As a result, little is known about the individual stability of gambling behaviour and the extent to which behaviour measured during adolescence is related to adult behaviour. In this paper, we report the results of a 4-wave longitudinal investigation of gambling behaviour in a probability sample of 256 young people (50 % male, 50% female) who were interviewed in 2005 at the age of 16–18 years and then followed through to the age of 20–21 years. The results indicated that young people showed little stability in their gambling. Relatively few reported gambling on the same individual activities consistently over time. Gambling participation rates increased rapidly as young people made the transition from adolescence to adulthood and then were generally more stable. Gambling at 15–16 years was generally not associated with gambling at age 20–21 years. These results highlight the importance of individual-level analyses when examining gambling patterns over time.

Canale, N., Vieno, A., Griffiths, M.D., Rubaltelli, E., Santinello, M. (2015). Trait urgency and gambling problems in young people: the role of decision-making processes. Addictive Behaviors, 46, 39-44.

  • Although the personality trait of urgency has been linked to problem gambling, less is known about psychological mechanisms that mediate the relationship between urgency and problem gambling. One individual variable of potential relevance to impulsivity and addictive disorders is age. The aims of this study were to examine: (i) a theoretical model associating urgency and gambling problems, (ii) the mediating effects of decision-making processes (operationalized as preference for small/immediate rewards and lower levels of deliberative decision-making); and (iii) age differences in these relationships. Participants comprised 986 students (64% male; mean age = 19.51 years; SD = 2.30) divided into three groups: 16–17 years, 18–21 years, and 22–25 years. All participants completed measures of urgency, problem gambling, and a delay-discounting questionnaire involving choices between a smaller amount of money received immediately and a larger amount of money received later. Participants were also asked to reflect on their decision-making process. Compared to those aged 16–17 years and 22–25 years, participants aged 18–21 years had a higher level of gambling problems and decreased scores on lower levels of deliberative decision-making. Higher levels of urgency were associated with higher levels of gambling problems. The association was mediated by a lower level of deliberative decision-making and preference for an immediate/small reward. A distinct pathway was observed for lower levels of deliberative decision-making. Young people who tend to act rashly in response to extreme moods, had lower levels of deliberative decision-making, that in turn were positively related to gambling problems. This study highlights unique decision-making pathways through which urgency trait may operate, suggesting that those developing prevention and/or treatment strategies may want to consider the model’s variables, including urgency, delay discounting, and deliberative decision-making.

Carran, M. & Griffiths, M.D. (2015). Gambling and social gambling: An exploratory study of young people’s perceptions and behavior. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 33(1), 101-113.

  • Background and aims: Gambling-type games that do not involve the spending of money (e.g., social and ‘demo’ [demonstration] gambling games, gambling-like activities within video games) have been accused in both the legal and psychological literature of increasing minors’ propensity towards prohibited forms of gambling thus prompting calls for gambling regulation to capture address such games and subject them to age restrictions. However, there is still a shortage of empirical data that considers how young people experience monetary and non-monetary gambling, and whether they are sufficiently aware of the differences. Methods: Data was collected from 23 qualitative focus groups carried out with 200 young people aged between 14 and 19 years old in schools based in London and Kent. As the study was exploratory in nature, thematic analysis was adopted in order to capture how pupils categorise, construct, and react to gambling-like activities in comparison to monetary forms of gambling without the constrains of a predetermined theoretical framework. Results: Despite many similarities, substantial differences between monetary and non-monetary forms of gambling were revealed in terms of pupils’ engagement, motivating factors, strengths, intensity, and associated emotions. Pupils made clear differentiation between non-monetary and monetary forms of gambling and no inherent transition of interest from one to the other was observed among participants. Only limited evidence emerged of ‘demo’ games being used as a practice ground for future gambling. Conclusion: For the present sample, non-monetary forms of gambling presented a different proposition to the real-money gambling with no inherent overlap between the two. For some the ‘softer’ form minimised the temptation to try other forms of gambling that they were not legally allowed to engage in, but ‘demo’ games may attract those who already want to gamble. Policy implications: Regulators must recognise and balance these two conflicting aspects.

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.

  • Research indicates that compared to the general population, teenagers and students make the most use of social networking sites (SNSs). Although SNSs were originally developed to foster online communication between individuals, they now have the capability for other types of behaviour to be engaged in such as gambling and gaming. The present paper focuses on gambling and the playing of gambling-type games via SNSs and comprises a selective narrative overview of some of the main concerns and issues that have been voiced concerning gambling and gambling-type games played via social network sites. Overall, there is little empirical evidence relating to the psychosocial impact of adolescents engaging in gambling and gambling-type activities on SNSs, and the evidence that does exist does not allow definitive conclusions to be made. However, it is recommended that stricter age verification measures should be adopted for social games via SNSs particularly where children and adolescents are permitted to engage in gambling-related content, even where real money is not involved.

Canale, N., Vieno, A., Griffiths, M.D., Marino, C., Chieco, F., Disperati, F., Andriolo, S., Santinello, M. (2016). The efficacy of a web-based gambling intervention program for high school students: A preliminary randomized study. Computers in Human Behavior, 55, 946-954.

  • Early onset in adolescent gambling involvement can be a precipitator of later gambling problems. The aim of the present study was to test the preliminary efficacy of a web-based gambling intervention program for students within a high school-based setting. Students attending a high school in Italy (N= 168) participated in the present study (58% male – age, M = 15.01; SD = 0.60). Twelve classes were randomly assigned to one of two conditions: intervention (N = 6; 95 students) and control group (N = 6; 73 students). Both groups received personalized feedback and then the intervention group received online training (interactive activities) for three weeks. At a two-month follow-up, students in the intervention group reported a reduction in gambling problems relative to those in the control group. However, there were no differences in gambling frequency, gambling expenditure, and attitudes toward the profitability of gambling between the two groups. In addition, frequent gamblers (i.e., those that gambled at least once a week at baseline) showed reductions in gambling problems and gambling frequency post-intervention. Frequent gamblers that only received personalized feedback showed significantly less realistic attitudes toward the profitability of gambling post-intervention. The present study is the first controlled study to test the preliminary efficacy of a web-based gambling intervention program for students within a high school-based setting. The results indicate that a brief web-based intervention delivered in the school setting may be a potentially promising strategy for a low-threshold, low-cost, preventive tool for at-risk gambling high school students.

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.

  • Aims: The primary aim of the present study was to understand the impact of online gambling on gambling problems in a large-scale nationally representative sample of Italian youth, and to identify and then further examine a subgroup of online gamblers who reported higher rates of gambling problems. Design: Data from the ESPAD®Italia2013 (European School Survey Project on Alcohol and Other Drugs) Study were used for analyses of adolescent Internet gambling. Setting: Self-administered questionnaires were completed by a representative sample of high school students, aged 15–19 years. Participants: A total of 14,778 adolescent students. Measurements: Respondents’ problem gambling severity; gambling behavior (participation in eight different gambling activities, the number of gambling occasions and the number of online gambling occasions, monthly gambling expenditure); Socio-demographics (e.g., family structure and financial status); and control variables were measured individually (i.e., use of the Internet for leisure activities and playing video games). Findings: Rates of problem gambling were five times higher among online gamblers than non-online gamblers. In addition, factors that increased the risk of becoming a problem online gambler included living with non-birth parents, having a higher perception of financial family status, being more involved with gambling, and the medium preferences of remote gamblers (e.g., Internet cafes, digital television, and video game console). Conclusions: The online gambling environment may pose significantly greater risk to vulnerable players. Family characteristics and contextual elements concerning youth Internet gambling (e.g., remote mediums) may play a key role in explaining problem online gambling among adolescents.

Pallesen, S., Hanss, D., Molde, H., Griffiths, M.D. & Mentzoni, R.A. (2016). A longitudinal study of factors explaining attitude change towards gambling among adolescents. Journal of Behavioral Addictions, 5, 59–67

  • Background and aims: No previous study has investigated changes in attitudes toward gambling from under legal gambling age to legal gambling age. The aim of the present study was therefore to investigate attitudinal changes during this transition and to identify predictors of corresponding attitude change. Methods: In all 1239 adolescents from a national representative sample participated in two survey waves (Wave 1; 17.5 years; Wave 2; 18.5 years). Results: From Wave 1 to Wave 2 the sample became more acceptant toward gambling. A regression analysis showed that when controlling for attitudes toward gambling at Wave 1 males developed more acceptant attitudes than females. Neuroticism was inversely related to development of acceptant attitudes toward gambling from Wave 1 to Wave 2, whereas approval of gambling by close others at Wave 1 was positively associated with development of more acceptant attitudes. Continuous or increased participation in gambling was related to development of more acceptant attitudes from Wave 1 to Wave 2. Conclusions: Attitudes toward gambling became more acceptant when reaching legal gambling age. Male gender, approval of gambling by close others and gambling participation predicted development of positive attitudes toward gambling whereas neuroticism was inversely related to development of positive attitudes toward gambling over time.

Ciccarelli, M., Griffiths, M.D., Nigro, G., & Cosenza, M. (2016). Decision-making, cognitive distortions and alcohol use in adolescent problem and non-problem gamblers: An experimental study. Journal of Gambling Studies, in press.

  • In the psychological literature, many studies have investigated the neuropsychological and behavioral changes that occur developmentally during adolescence. These studies have consistently observed a deficit in the decision-making ability of children and adolescents. This deficit has been ascribed to incomplete brain development. The same deficit has also been observed in adult problem and pathological gamblers. However, to date, no study has examined decision-making in adolescents with and without gambling problems. Furthermore, no study has ever examined associations between problem gambling, decision-making, cognitive distortions and alcohol use in youth. To address these issues, 104 male adolescents participated in this study. They were equally divided in two groups, problem gamblers and non-problem gamblers, based on South Oaks Gambling Screen Revised for Adolescents scores. All participants performed the Iowa gambling task and completed the Gambling Related Cognitions Scale and the alcohol use disorders identification test. Adolescent problem gamblers displayed impaired decision-making, reported high cognitive distortions, and had more problematic alcohol use compared to non-problem gamblers. Strong correlations between problem gambling, alcohol use, and cognitive distortions were observed. Decision-making correlated with interpretative bias. This study demonstrated that adolescent problem gamblers appear to have the same psychological profile as adult problem gamblers and that gambling involvement can negatively impact on decision-making ability that, in adolescence, is still developing. The correlations between interpretative bias and decision-making suggested that the beliefs in the ability to influence gambling outcomes may facilitate decision-making impairment.

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

Further reading

Griffiths, M.D. (1995). Adolescent Gambling. London: Routledge.

Griffiths, M.D. (2002). Gambling and Gaming Addictions in Adolescence. Leicester: British Psychological Society/Blackwells.

Griffiths, M.D. (2003). Adolescent gambling: Risk factors and implications for prevention, intervention, and treatment. In D. Romer (Ed.), Reducing Adolescent Risk: Toward An Integrated Approach (pp. 223-238). London: Sage.

Griffiths, M.D. (2010). Asian national adolescent gambling surveys: Methodological issues, protocols, and advice. Asian Journal of Gambling Issues and Public Health, 1, 4-18.

Griffiths, M.D. (2011). Adolescent gambling. In B. Bradford Brown & Mitch Prinstein (Eds.), Encyclopedia of Adolescence (Volume 3) (pp.11-20). San Diego: Academic Press.

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

Griffiths, M.D. & Linsey, A. (2006). Adolescent gambling: Still a cause for concern? Education and Health, 24, 9-11.

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

Hayer, T. & Griffiths, M.D. (2015). The prevention and treatment of problem gambling in adolescence. In T.P. Gullotta & G. Adams (Eds). Handbook of Adolescent Behavioral Problems: Evidence-based Approaches to Prevention and Treatment (Second Edition) (pp. 539-558). New York: Kluwer.

Are you ‘intexticated’?: Another look at excessive smartphone use

Yesterday, I received a copy of a new book called Too Much Of A Good Thing: Are You Addicted To Your Smartphone? by Dr. James Roberts (a Professor of Marketing at Baylor University in Waco, Texas). It’s a populist and easy-to-read book that you can read from cover to cover inside two hours. It’s not an academic book but there’s lots of input from various academics around the world (including me – which is why I was sent a copy of the book). It’s a fun read and is written by someone (who like myself) loves technology and all the great benefits it brings us.

The main thrust of the book doesn’t concern addiction per se, but is more concerned with how smartphones take us away from or compromises other things in our lives like our friends, our loved ones, our hobbies and (in extreme cases) our jobs. Roberts describes this as ‘cellularitis’ – “a Socially Transmitted Disease (STD) that results in habitual use of one’s cell phone to the detriment of his or her psychological and physical health and well-being”. In the second chapter, Dr. Roberts uses my addiction components model to describe his ‘Six Signs of Cell Phone Addiction Scale’ (although uses an older version of the components model taken from a paper I published on internet addiction back in 1999 in The Psychologist).

One of the chapters on the phenomena of ‘phubbing’ (i.e., phone snubbing – where someone you are socially interacting with would rather be on their smartphone, rather than talking to you). One recent paper by Dr. Roberts published in the journal Computers in Human Behavior even had the title ‘My life has become a major distraction from my cell phone’. The chapter also contains a 9-item ‘Phubbing Scale’ that Roberts developed with his colleague Dr. Meredith David (and a later chapter also includes the ‘Partner Phubbing Scale’). Academic research into phubbing has already started (see ‘Further reading below) and I’ll hopefully write a blog on that in the future. I also liked the concept of being ‘intexticated’ defined as being “distracted by the act of texting to such a degree that one seems intoxicated”.

In previous blogs I have examined the concept of mobile phone addiction, the most recent of which argued that there was nowhere near enough empirical evidence to be able to confirm whether addiction to smartphones exists. Dr. Roberts asked me about the topic for his book and here are the answers to the questions he asked me.

Can someone be addicted to their cell phone? Why or why not?

That depends on how ‘addiction’ is defined. I believe that anything can be potentially addictive if constant rewards and reinforcement are present. Some people may confuse habitual use of such technology as an addictive behaviour (when in reality it may not be). For instance, some people may consider themselves cell phone addicts because they never go out of the house without their cell phone, do not turn their cell phone off at night, are always expecting calls from family members or friends, and/or over-utilise cell phones in their work and/or social life. There is also the importance of economic and/or life costs. The crucial difference between some forms of cell phone use and pathological cell phone use is that some applications involve a financial cost. If a person is using the application more and is spending more money, there may be negative consequences as a result of not being able to afford the activity (e.g., negative economic, job-related, and/or family consequences). High expenditure may also be indicative of cell phone addiction but the phone bills of adolescents are often paid for by parents, therefore the financial problems may not impact on the users themselves.

It is very difficult to determine at what point cell phone use becomes an addiction. The cautiousness of researchers suggests that we are not yet in a position to confirm the existence of a serious and persistent psychopathological addictive disorder related to cell phone addiction on the basis of population survey data alone. This cautiousness is aided and supported by other factors including: (a) the absence of any clinical demand in accordance with the percentages of problematic users identified by these investigations, (b) the fact that the psychometric instruments used could be measuring ‘concern’ or ‘preoccupation’ rather than ‘addiction, (c) the normalisation of behaviour and/or absence of any concern as users grow older; and (d) the importance of distinguishing between excessive use and addictive use.

What signs or symptoms would you look for when deciding if someone is addicted to their cell phone?

You could argue that a person is no more addicted to their phone than an alcoholic is addicted to the bottle. Individuals tend to have addictions on their mobile phone rather than to their phone. For me to class someone as addicted to their mobile phone they would have to fulfill the following six criteria:

  • Salience – This occurs when the mobile phone use 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 socialised behaviour). For instance, even if the person is not actually on their phone they will be constantly thinking about the next time that they will be (i.e., a total preoccupation with their mobile phone).
  • Mood modification – This refers to the subjective experiences that people report as a consequence of mobile phone use 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 on the phone.
  • Tolerance – This is the process whereby increasing amounts of mobile phone use are mobile phone users gradually build up the amount of the time they spend on their phone every day.
  • Withdrawal symptoms – These are the unpleasant feeling states and/or physical effects (e.g., the shakes, moodiness, irritability, etc.) that occur when the person is unable to use their phone because there is no signal, mislaid or broken phone, 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 on their mobile phone.
  • Relapse – This is the tendency for repeated reversions to earlier patterns of excessive mobile phone use to recur and for even the most extreme patterns typical of the height of excessive mobile phone use to be quickly restored after periods of control.

What is one suggestion you could offer to help someone better control their cell phone use?

I don’t have a single suggestion. If there was a single suggestion to overcome or better control problematic phone use then I could give up my whole research career. However, my tips on digital detox can be found here.

 

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

Further reading

Bianchi, A. & Phillips, J.G. (2005). Psychological predictors of problem mobile phone use. Cyberpsychology and Behavior, 8, 39–51.

Billieux, J. (2012). Problematic use of the mobile phone: A literature review and a pathways model. Current Psychiatry Reviews, 8, 299–307.

Billieux, J., Maurage, P., Lopez-Fernandez, O., Kuss, D.J. & Griffiths, M.D. (2015). Can disordered mobile phone use be considered a behavioural addiction? An update on current evidence and a comprehensive model for future research. Current Addiction Reports, DOI 10.1007/s40429-015-0054-y

Carbonell, X., Chamarro, A., Beranuy, M., Griffiths, M.D. Obert, U., Cladellas, R. & Talarn, A. (2012). Problematic Internet and cell phone use in Spanish teenagers and young students. Anales de Psicologia, 28, 789-796.

Chóliz M. (2010). Mobile phone addiction: a point of issue. Addiction. 105, 373-374.

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

Griffiths, M.D. (2007). Mobile phone gambling. In D. Taniar (Ed.), Encyclopedia of Mobile Computing and Commerce (pp.553-556). Pennsylvania: Information Science Reference.

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

Karadağ, E., Tosuntaş, Ş. B., Erzen, E., Duru, P., Bostan, N., Şahin, B. M., … & Babadağ, B. (2015). Determinants of phubbing, which is the sum of many virtual addictions: A structural equation model. Journal of Behavioral Addictions, 4, 60-74.

Lopez-Fernandez, O., Honrubia-Serrano, L., Freixa-Blanxart, M., & Gibson, W. (2014). Prevalence of problematic mobile phone use in British adolescents. Cyberpsychology, Behavior and Social Networking, 17, 91-98.

Lopez-Fernandez, O., Kuss, D.J., Griffiths, M.D., & Billieux, J. (in press). The conceptualization and assessment of problematic mobile phone use. In Z. Yan (Ed.), Encyclopedia of Mobile Phone Behavior (Volumes 1, 2, & 3). Hershey, PA: IGI Global.

Roberts, J.A. (2016). Too Much Of A Good Thing: Are You Addicted To Your Smartphone? Austin: Sentia Publishing.

Roberts, J. A., & David, M. E. (2016). My life has become a major distraction from my cell phone: Partner phubbing and relationship satisfaction among romantic partners. Computers in Human Behavior, 54, 134-141

Smetaniuk, P. (2014). A preliminary investigation into the prevalence and prediction of problematic cell phone use. Journal of Behavioral Addictions, 3(1), 41-53.

Ugur, N. G., & Koc, T. (2015). Time for digital detox: Misuse of mobile technology and phubbing. Procedia-Social and Behavioral Sciences, 195, 1022-1031.

Against all odds: The rise and rise of gambling

In many areas of the world, gambling has become a popular activity. Almost all national surveys into gambling have concluded that most people have gambled at some point in their lives, there are more gamblers than non-gamblers, but that most participants gamble infrequently. Commissions and official government reviews in a number of countries including the United States, United Kingdom, Australia and New Zealand have all concluded that increased gambling availability has led to an increase in problem gambling. Estimates of the number of problem gamblers vary from country to country but most countries that have carried out national prevalence surveys suggest around 0.5%-2% of individuals have a gambling problem.

In May 2013, the new criteria for problem gambling (now called ‘Gambling Disorder’) were published in the fifth edition of the American Psychiatric Association’s Diagnostic and Statistical Manual for Mental Disorders (DSM-5), and for the very first time, problem gambling was included in the section ‘Substance-related and Addiction Disorders’ (rather than in the section on impulse control disorders). Also included in the Appendix of the DSM-5 as a potential addiction was Internet Gaming Disorder (i.e., online video game addiction). Although most of us in the field had been conceptualizing problematic gambling and video gaming as addictions for many years, this was arguably the first time that an established medical body had described them as such. For me, gambling and gaming addictions should not be considered any differently from other more traditional chemical addictions (e.g., alcohol addiction, nicotine addiction). Consequently, there is no theoretical reason why other problematic and excessive activities that do not involve the ingestion of a psychoactive substance cannot be deemed as legitimate behavioural addictions in the years to come (e.g., shopping addiction, sex addiction, work addiction, exercise addiction, etc.).

Gambling is a multifaceted rather than unitary phenomenon. Consequently, many factors are involved in the acquisition, development and maintenance of gambling behaviour. Such factors include an individual’s biological and genetic predisposition, their social environment, psychological variables (personality characteristics, attitudes, expectations, beliefs, etc.), macro-situational characteristics (how much gambling is marketed and advertised, the number of gambling venues within a jurisdiction, where the gambling venue is located), micro-situational characteristics of the gambling environment (on-site cash machine, provision of free alcohol, floor layout etc.), and the structural characteristics of the gambling activity itself (jackpot size, stake size, the number of times a individual can gamble in a given time frame, etc.). Most research has tended to concentrate on individual characteristics (personality, genetics, family and peer influence) rather than situational and structural characteristics.

The introduction of national lotteries, the proliferation of slot machines, the expansion of casinos, and the introduction of new media in which to gamble (e.g., Internet gambling, mobile phone gambling, interactive television gambling, gambling via social networking sites), has greatly increased the accessibility and popularity of gambling worldwide, and as a result, the number of people seeking assistance for gambling-related problems. In addition, the rise of remote gambling via the internet and mobile phones has arguably changed the psychosocial nature of gambling. I have also published a number of studies showing that to vulnerable and susceptible individuals (e.g., problem gamblers, minors, the intoxicated, etc.), the medium of the internet may facilitate and fuel problematic and addictive behaviours.

There are many known factors that make online activity potentially problematic to a minority of individuals. This includes factors such as easy accessibility, affordability, anonymity, convenience, escape, and disinhibition. Some of these factors can change the psychological experience of gambling. For instance, gambling with virtual representations of money online lower the psychological value of the money and people tend to spend more with virtual representations of money than if they were gambling with physical money. Also, when people lose money online it is a different psychological experience because no-one can see anyone losing face-to-face. As a result, there is less guilt and embarrassment about losing and vulnerable individuals may be tempted to spend more time and money than they had originally intended.

One very salient trend that has implications for gambling (and arguably problem gambling) is that technology hardware is becoming increasingly convergent (e.g., internet access via smartphones and interactive television) and there is increasing multi-media integration such as gambling and video gaming via social networking sites. As a consequence, people of all ages are spending more time interacting with technology in the form of internet use, playing videogames, watching interactive television, mobile phone use, social networking, etc. In addition to convergent hardware, there is also convergent content. This includes some forms of gambling including video game elements, video games including gambling elements, online penny auctions that have gambling elements, and television programming with gambling-like elements.

One of the key drivers behind the increased numbers of people gambling online and using social networking sites is the rise of mobile gambling and gaming. Compared to internet gambling, mobile gambling is still a relatively untapped area but the functional capabilities of mobile phones and other mobile devices are improving all the time. There are now hundreds of gambling companies that provide casino-style games to be downloaded onto the gambler’s smartphone or mobile device (e.g., tablet or laptop). This will have implications for the psychosocial impact of gambling and will need monitoring. Like online gambling, mobile gaming has the capacity to completely change the way people think about gambling and betting. Mobile phones provide the convenience of making bets or gambling from wherever the person is, even if they are on the move.

One of the most noticeable changes in gambling over the last few years – and inextricably linked to the rise of mobile gaming – has been the large increase of in-play sports betting. Gamblers can now typically bet on over 60 ‘in-play’ markets while watching a sports event (such as a soccer match). For instance, during a soccer game, gamblers can bet on who is going to score the first goal, what the score will be after 30 minutes of play, how many yellow cards will be given during them game and/or in what minute of the second half will the first free kick be awarded. Live betting is going to become a critical activity in the success of the future online and mobile gambling markets.

The most salient implication of ‘in-play’ sports betting is that it has taken what was traditionally a discontinuous form of gambling – where an individual makes one bet every Saturday on the result of the game – to one where an individual can gamble again and again and again. Gaming operators have quickly capitalized on the increasing amount of televised sport. In contemporary society, where there is a live sporting event, there will always be a betting consumer. ‘In-play’ betting companies have both catered for the natural betting demand but introduced new gamblers in the process. If the reward for gambling only happens once or twice a week, it is completely impossible to develop problems and/or become addicted. ‘In-play’ has changed that because there are soccer matches on almost every day of the week making a daily two-hour plus period of betting seven days a week.

New technologies in the form of behavioural tracking have helped online gambling companies keep track of players by noting (among many other things) what games they are playing, the time spent playing, the denomination of the gambles made, and their wins and losses. Although such technologies can potentially be used to exploit gamblers (e.g., targeting the heaviest spenders with direct marketing promotions to gamble even more), such technologies can also be used to help gamblers that may have difficulties stopping and/or limiting their gambling behaviour. Over the past few years, innovative social responsibility tools that track player behaviour with the aim of preventing problem gambling have been developed. These new tools are providing insights about problematic gambling behaviour. A number of European jurisdictions (such as Germany and The Netherlands) are now considering whether such tools should be mandatory for gaming operators to use especially as such tools are already being used in Sweden, Norway, Finland and Austria.

Although gamblers are ultimately responsible for their own behaviour, gambling can be minimised via both governmental policy initiatives (age restrictions, marketing and advertising restrictions, no gaming licenses unless operators display the highest standards of social responsibility to their clientele, etc.) and gaming operator initiatives (self-exclusion programs, information about games so gamblers can make informed choices, limit-setting tools that allow gamblers to set time and money loss limits, staff training on responsible gambling, referral to gambling treatment providers, etc.). Problem gambling can never be totally eliminated but harm minimisation practices can be put in place to keep the problem to a minimum. Treatment for gambling addiction should be free and paid for by gambling industry profits (either in the form of voluntary donations to a charitable trust or – if that doesn’t work – a statutory levy). In short, any jurisdiction that has legalised and liberalised gambling has a duty of care to put a national social responsibility infrastructure in place to prevent, minimise, and treat problem gambling as they would with any other consumptive and potentially addictive behaviour (e.g., drinking alcohol, smoking cigarettes, etc.)

Please note: A version of this article first appeared in Science and Technology (Pan European Networks) magazine (Volume 15, pages 153-155).

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

Further reading

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

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

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

Griffiths, M.D. (2012). Mind games (A brief psychosocial overview of in-play betting). i-Gaming Business Affiliate, June/July, 44.

Griffiths, M.D. (2012). Internet gambling, player protection and social responsibility. In R. Williams, R. Wood & J. Parke (Ed.), Routledge Handbook of Internet Gambling (pp.227-249). London: Routledge.

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. & Parke, J. (2003). The environmental psychology of gambling. In G. Reith (Ed.), Gambling: Who wins? Who Loses? (pp. 277-292). New York: Prometheus Books.

Kuss, D.J. & Griffiths, M.D. (2012).  Internet gambling behavior. In Z. Yan (Ed.), Encyclopedia of Cyber Behavior (pp.735-753). Pennsylvania: IGI Global.

McCormack, A. & Griffiths, M.D. (2013). A scoping study of the structural and situational characteristics of internet gambling. International Journal of Cyber Behavior, Psychology and Learning, 3(1), 29-49.

Meyer, G., Hayer, T. & Griffiths, M.D. (2009). Problem Gaming in Europe: Challenges, Prevention, and Interventions. New York: Springer.

Parke, J. & Griffiths, M.D. (2007). The role of structural characteristics in gambling. In G. Smith, D. Hodgins & R. Williams (Eds.), Research and Measurement Issues in Gambling Studies (pp.211-243). New York: Elsevier.

Pontes, H. & Griffiths, M.D. (2014). The assessment of internet gaming disorder in clinical research. Clinical Research and Regulatory Affairs, 31(2-4), 35-48.

Zangeneh, M., Griffiths, M.D. & Parke, J. (2008). The marketing of gambling. In Zangeneh, M., Blaszczynski, A., and Turner, N. (Eds.), In The Pursuit Of Winning (pp. 135-153). New York: Springer.

Ringing the changes: Can disordered mobile phone use be considered a behavioural addiction?

Over the last decade, I have published various papers on excessive mobile phone use both in general and related to particular aspects of mobile phone use (such as gambling and gaming via mobile phones (see ‘Further reading’ below). Recently, some colleagues and I (and led by Dr. Joël Billieux) published a new review in the journal Current Addiction Reports examining disordered mobile phone use.

I don’t think many people would say that their lives are worse because of mobile phones as the positives appear to greatly outweigh the negatives. However, in the scientific literature, excessive mobile phone use has been linked with self-reported dependence and addiction-like symptoms, sleep interference, financial problems, dangerous use (phoning while driving), prohibited use (phoning in banned areas), and mobile phone-based aggressive behaviours (e.g., cyberbullying).

Despite accumulating evidence that mobile phone use can become problematic and lead to negative consequences, its incidence, prevalence, and symptomatology remain a matter of much debate. For instance, our recent review noted that prevalence studies conducted within the last decade have reported highly variable rates of problematic use ranging from just above 0% to more than 35%. This is mainly due to the fact most studies in the field have been conducted in the absence of a theoretical rationale.

Too often, excessive mobile phone use has simply been conceptualized as a behavioural addiction and subsequently develop screening tools using items adapted from the substance use and pathological gambling literature, without taking into account either the specificities of mobile phone “addiction” (e.g., dysfunctional mobile phone use may often be related to interpersonal processes) or the fact that the most recent generation of mobile phones (i.e., smartphones) are tools that – like the internet – allow the involvement in a wide range of activities going far beyond traditional oral and written (SMS) communication between individuals (e.g., gaming, gambling, social networking, shopping, etc.).

The first scientific studies examining problematic mobile phone use (PMPU) were published a decade ago. Since then, the number of published studies on the topic has grown substantially. At present, several terms are frequently used to describe the phenomenon, the more popular being ‘mobile phone (or smartphone) addiction’, ‘mobile phone (or smartphone) dependence’ or ‘nomophobia’ (that refers to the fear of not being able to use the mobile phone).

PMPU is generally conceptualized as a behavioural addiction including the core components of addictive behaviours, such as cognitive salience, loss of control, mood modification, tolerance, withdrawal, conflict and relapse. Accordingly, the criteria (and screening tools developed using such criteria) that have been proposed to diagnose an addiction to the mobile phone have been directly transposed from those classifying and diagnosing other addictive behaviours, i.e., the criteria for substance use and pathological gambling. For example, in a recent study published in the Journal of Behavioral Addictions, Dr. Peter Smetaniuk reported a prevalence of PMPU around 20% in U.S. undergraduate students using adapted survey items that were initially developed to diagnose disordered gambling.

Although many scholars believe that PMPU is a behavioural addiction, evidence is still lacking that either confirms or rejects such conceptualization. Indeed, the fact that this condition can be considered as an addiction is to date only supported by exploratory studies relying on self-report data collected via convenience samples. More specifically, there is a crucial lack of evidence that similar neurobiological and psychological mechanisms are involved in the aetiology of mobile phone addiction compared to other chemical and behavioural addictions. Such types of evidence played a major role in the recent recognition of Gambling Disorder and Internet Gaming Disorder as addictive disorders in the latest (fifth) addiction of the DSM (i.e., DSM-5) In particular, three key features of addictive behaviours, namely loss of control, tolerance and withdrawal, have – to date – received very limited empirical support in the field of mobile phone addiction research.

Given these concerns, it appears that the empirical evidence supporting the conceptualization of PMPU as a genuine addictive behaviour is currently scarce. However, this does not mean that PMPU is not a genuine addictive behaviour (at least for a subgroup of individuals displaying PMPU symptoms), but rather that the nature and amount of the available data at the present time are not sufficient to draw definitive and valid conclusions. Therefore, further studies are required. In particular, longitudinal and experimental research is needed to obtain behavioural and neurobiological correlates of PMPU. In the absence of such types of data, all attempts to consider PMPU within the framework of behavioural addictions will remain tentative. It is worth noting here that it took decades of empirical research before disordered gambling was officially recognized as an addiction (as opposed to a disorder of impulse control) in the DSM-5.

The current conceptual chaos surrounding PMPU research can also be related to the fact that while the number of empirical studies is growing quickly, these studies have (to date) primarily been based on concepts borrowed from other disorders (e.g., problematic Internet use, pathological gambling, substance abuse, etc.). This approach is atheoretical and lacks specificity with regard to the phenomenon under investigation. In fact, by adopting such a ‘confirmatory approach’ relying on deductive quantitative studies, important findings that are unique to the experience of PMPU have been neglected. As an illustration, no qualitative analyses of PMPU exist, and only a few models have been proposed. This implies that most studies have been conducted without a theoretical rationale that goes beyond transposing what is known about addictions in the analysis of PMPU.

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

Additional input: Joël Billieux, Pierre Maurage, Olatz Lopez-Fernandez and Daria J. Kuss

Further reading

Bianchi, A. & Phillips, J.G. (2005). Psychological predictors of problem mobile phone use. Cyberpsychology and Behavior, 8, 39–51.

Billieux, J. (2012). Problematic use of the mobile phone: A literature review and a pathways model. Current Psychiatry Reviews, 8, 299–307.

Billieux, J., Maurage, P., Lopez-Fernandez, O., Kuss, D.J. & Griffiths, M.D. (2015). Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research. Current Addiction Reports, 2, 154-162.

Carbonell, X., Chamarro, A., Beranuy, M., Griffiths, M.D. Obert, U., Cladellas, R. & Talarn, A. (2012). Problematic Internet and cell phone use in Spanish teenagers and young students. Anales de Psicologia, 28, 789-796.

Chóliz M. (2010). Mobile phone addiction: a point of issue. Addiction. 105, 373-374.

Griffiths, M.D. (2007). Mobile phone gambling. In D. Taniar (Ed.), Encyclopedia of Mobile Computing and Commerce (pp.553-556). Pennsylvania: Information Science Reference.

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

Lopez-Fernandez, O., Honrubia-Serrano, L., Freixa-Blanxart, M., & Gibson, W. (2014). Prevalence of problematic mobile phone use in British adolescents. Cyberpsychology, Behavior and Social Networking, 17, 91-98.

Lopez-Fernandez, O., Kuss, D.J., Griffiths, M.D., & Billieux, J. (2015). The conceptualization and assessment of problematic mobile phone use. In Z. Yan (Ed.), Encyclopedia of Mobile Phone Behavior (Volumes 1, 2, & 3) (pp. 591-606). Hershey, PA: IGI Global.

Smetaniuk, P. (2014). A preliminary investigation into the prevalence and prediction of problematic cell phone use. Journal of Behavioral Addictions, 3(1), 41-53.

Cell growth: A brief look at mobile sports betting

It is often claimed by marketeers that remote gambling makes commercial sense (i.e., the combining of gambling and remote technologies such as the internet and mobile phones into one convenient package). Mobile phone betting and gambling not only provides convenience and flexibility, but perhaps more importantly from a gaming operator’s perspective, provides gambling on the move, whenever and wherever. Since it is somewhat unnatural to always be near a computer, it could be argued that mobile phones are an ideal medium for betting and gambling. Whenever gamblers have a few minutes to spare (at the airport, commuting to work, waiting in a queue, etc.), they can occupy themselves by gambling.

Conventional wisdom says that two things have the power to drive any new consumer technology – pornography and gambling. These activities helped satellite and cable television, video, and the Internet and provide adult entertainment in a convenient and guilt-free environment. Betting via mobile phone is no different. Along with pornography, gambling should have little trouble reaching profitability – especially if this is combined with sports events. Sports interest is huge. There are thousands of communities (including those online). The most successful of those communities will look to ‘mobilize’ and then ‘monetize’.

The mobile phone industry has grown rapidly in the last decade. Market research highlights that mobile phone revenues from mobile gambling and gaming is increasingly rapidly. Although mobile gaming revenues are increasing, it is estimated that less than 2% of mobile industry revenue is generated by gaming and gambling. It is generally thought that lottery gambling will make most money for mobile gambling operators because governments are generally less censorious about lotteries than other forms of gambling. They are also easy to play and relatively low cost compared to other types of gambling.

To some extent, the majority of gamblers are risk-takers to begin with. Therefore, they may be less cautious with new forms of technology. For every day gamblers, mobile phones are ideal for bet placing, and gamblers will be able to check on their bets, and place new ones. Furthermore, it is anonymous, and can provide immediate gratification, anytime, anywhere. Anonymity and secrecy may be potential benefits of mobile gambling as for a lot of people there is still stigma attached to gambling in places like betting shops and casinos. Mobile sports betting is also well suited to personal (i.e., one-to-one) gambling, where users bet against each other rather than bookies. Online betting exchanges demonstrate that people bet on anything and everything to do with sport (with each other).

Although mobile phone technology has improved exponentially over the last decade, it is unlikely that mobile phone graphics and technology will ever truly compete with Internet web browsers (although I am happy to be proved wrong). Intuitively, mobile phone gambling is best suited for sports and event betting. With mobile phone betting, all that is required is real-time access to data about the event to be bet on (e.g., a horse race, a football match), and the ability to make a bet in a timely fashion.

These basic requirements are, of course, easily be provided by the current generation of mobile phones, and the appropriate software. The placing of the bet is not the driving motivation in event wagering. Since being the spectator is what sports fans are really interested in, the sports gambler does not need fulfillment from the process of gambling. People betting on sports will use mobile phones because they are easy, convenient and take no time to boot up. Once they have their sports book registered as a bookmark on their phone, they can access it and place a bet within a very short space of time.

As I have noted in previous blogs, all forms of gambling lie on a chance-skill dimension. Neither games of pure skill nor games of pure chance are particularly attractive to sports bettors. Games of chance (like lotteries) offer no significant edge to sports bettors and are unlikely to be gambled upon. Serious punters gravitate towards types of gambling that provide an appropriate mix of chance and skill. This is one of the reasons why sports betting – and in particular activities like horse race betting – is so popular for gamblers. The edge available in horse race gambling can be sufficient to fully support professional gamblers as they bring their wide range of knowledge to the activity. There is the complex interplay of factors that contributes to the final outcome of the race. However, in the mobile sports betting market, it is likely to be football that will make the big money for sports betting agencies.

Consider the following scenario. A betting service that knows where you are and/or what you are doing has the capacity to suggest something context-related to the mobile user to bet on. For instance, if the mobile phone user bought a ticket for a soccer match using an electronic service, this service may share this information with a betting company. If in that match the referee gives a penalty for one team, a person’s mobile could ring and give the user an opportunity (on screen) to bet whether or not the penalty will be scored. On this type of service, the mobile phone user will only have to decide if they want to bet, and if they do, the amount of money. Two clicks and the bet will be placed. Context, timeliness, simplicity, and above all user involvement look like enough to convince also people that never entered a bet-shop.

Many football clubs are turning themselves into powerful media companies. They have their own digital TV channel and signed up a host of big-name technology partners. Such companies will get the chance to develop co-branded mobile services with the club. This offers users access to content similar to their website (receiving real-time scores and team news via SMS). While watching matches, users will be able to view statistics, player biographies, and order merchandise. Such mobility will facilitate an increase in ‘personalized’ gambling where bettors gamble against each other, rather than the house.

Gambling will (if it is not already) become part of the match day experience. A typical scenario might involve a £10 bet with a friend on a weekend football match. The gambler can text their friend via SMS and log on to the betting service to make their gamble. If the friend accepts, the gambler has got the chance to win (or lose). Football clubs will get a share of the profits from the service. Clubs are keen to get fans using branded mobile devices where they can simply hit a ‘bet’ button and place a wager with the club’s mobile phone partner.

As with all new forms of technological gambling, ease of use is paramount to success. Mobile phones have become more user-friendly. Pricing structures are also important. Internet access and mobile phone use that is paid for by the minute produces very different customer behavior to those that have one off payment fees (e.g., unlimited use and access for a monthly rental fee). The latter payment structure facilitates leisure use, as punters would not be worried that for every extra minute they are online, they are increasing the size of their phone bills. For me, mobile sports betting is where the future of mobile gambling is likely to be.

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

Further reading

Griffiths, M.D. (2004). Mobile phone gambling: preparing for take off. World Online Gambling Law Report, 8(3), 6-7.

Griffiths, M.D. (2005). The psychosocial impact of mobile phone gambling. World Online Gambling Law Report, 4 (10), 14-15.

Griffiths, M.D. (2010). The psychology of sports betting: What should affiliates know? i-Gaming Business Affiliate, August/September, 46-47.

Griffiths, M.D. (2011). Mobile sportsbetting: A view from the social sciences. i-Gaming Business, 69, 64-65.

Griffiths, M.D. (2011). Technological trends remote gambling: A psychological perspective. i-Gaming Business, 71, 39-40.

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

Griffiths, M.D. (2007). Mobile phone gambling. In D. Taniar (Ed.), Encyclopedia of Mobile Computing and Commerce (pp.553-556). Pennsylvania: Information Science Reference.

Place your bets: Has problem gambling in Great Britain decreased?

In the summer of 2014 I was commissioned to review problem gambling in Great Britain (the fall out of which I wrote about in detail in a previous blog). Earlier last year, a detailed report by Heather Wardle and her colleagues examined gambling behaviour in England and Scotland by combining the 2012 data from the Health Survey for England (HSE; n=8,291 aged 16 years and over) and the 2012 Scottish Health Survey (SHeS; n=4,815). To be included in the final data analysis, participants had to have completed at least one of the gambling participation questions. This resulted in a total sample of 11,774 participants. So what did the research find? Here is a brief summary of the main results:

  • Two-thirds of the sample (65%) had gambled in the past year, with men (68%) gambling more than women (62%). As with the British Gambling Prevalence Survey (BGPS), past year participation was greatly influenced by the playing of the bi-weekly National Lottery (lotto) game. Removal of those individuals that only played the National Lottery meant that 43% had gambled during the past year (46% males and 40% females).
  • Gambling was more likely to be carried out by younger people (50% among those aged 16-24 years and 52% among those aged 25-34 years).
  • The findings were similar to the previous BGPS reports and showed that the most popular forms of gambling were playing the National Lottery (52%; 56% males and 49% females), scratchcards (19%; 19% males and 20% females), other lottery games (14%; 14% both males and females), horse race betting (10%; 12% males and 8% females), machines in a bookmaker (3%; 5% males and 1% females), slot machines (7%; 10% males and 4% females), online betting with a bookmaker (5%; 8% males and 2% females), offline sports betting (5%; 8% males and 1% females), private betting (5%; 8% males and 2% females), casino table games (3%; 5% males and 1% females), offline dog race betting (3%; 4% males and 2% females), online casino, slots and/or bing (3%; 4% males and 2% females), betting exchanges (1%; males 2% and females 0%), poker in pubs and clubs (1%; 2% males and 0% females), spread betting (1%; 1% males and 0% females).
  • The only form of gambling (excluding lottery games) where females were more likely to gamble was playing bingo (5%; 7% females and 3% males).
  • Most participants gambled on one or two different activities a year (1.7 mean average across the total sample).
  • Problem gambling assessed using the Problem Gambling Severity (PGSI) criteria was reported to be 0.4%, with males (0.7%) being significantly more likely to be problem gamblers than females (0.1%). This equates to approximately 180,200 British adults aged 16 years and over.
  • Problem gambling assessed using the criteria of the fourth Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) was reported to be 0.5%, with males (0.8%) being significantly more likely to be problem gamblers than females (0.1%). This equates to approximately 224,100 British adults aged 16 years and over.
  • Using the PGSI screen, problem gambling rates were highest among young men aged 16-24 years (1.7%) and lowest among men aged 65-74 years (0.4%). Using the DSM-IV screen, problem gambling rates were highest among young men aged 16-24 years (2.1%) and lowest among men aged over 74 years (0.4%).
  • Problem gambling rates were also examined by type of gambling activity. Results showed that among past year gamblers, problem gambling was highest among spread betting (20.9%), played poker in pubs or clubs (13.2%), bet on other events with a bookmaker (12.9%), bet with a betting exchange (10.6%) and played machines in bookmakers (7.2%).
  • The activities with the lowest rates of problem gambling were playing the National Lottery (0.9%) and scratchcards (1.7%).
  • Problem gambling rates were highest among individuals that had participated in seven or more activities in the past year (8.6%) and lowest among those that had participated in a single activity (0.1%).

The authors also carried out a latent class analysis and identified seven different types of gambler among both males and females. The male groups comprised:

  • Cluster A: non-gamblers (33%)
  • Cluster B: National Lottery only gamblers (22%)
  • Cluster C: National Lottery and scratchcard gamblers only (20%)
  • Cluster D: Minimal, no National Lottery [gambling on 1-2 activities] (9%)
  • Cluster E: Moderate [gambling on 3-6 activities] (12%)
  • Cluster F: Multiple [gambling on 6-10 activities] (3%)
  • Cluster G: multiple, high [gambling on at least 11 activities] (1%).

The female groups comprised:

  • Cluster A: non-gamblers (40%)
  • Cluster B: National Lottery only gamblers (21%)
  • Cluster C: National Lottery and scratchcard gamblers only (7%)
  • Cluster D: Minimal, no National Lottery (8%)
  • Cluster E: moderate, less varied [2-3 gambling activities, mainly lottery-related] (8%)
  • Cluster F: moderate, more varied [2-3 gambling activities but wider range of activities] (6%)
  • Cluster G: multiple [gambling on at least four activities] (6%)

Using these groupings, the prevalence of male problem gambling was highest among those in Cluster G: multiple high group (25.0%) followed by Cluster F: multiple group (3.3%) and Cluster E: moderate group (2.6%). The prevalence of problem gambling was lowest among those in the Cluster B; National Lottery Draw only group (0.1%) followed by Cluster C: minimal – lotteries and scratchcards group (0.7%). The prevalence of female problem gambling was highest among those in the Cluster G: multiple group (1.8%) followed by those in Cluster F: moderate – more varied group (0.6%). The number of female gamblers was too low to carry out any further analysis. The report also examined problem gambling (either DSM-IV or PGSI) by gambling activity type.

  • The prevalence of problem gambling was highest among spread-bettors (20.9%), poker players in pubs or clubs (13.2%), bettors on events other than sports or horse/dog races (12.9%), betting exchange users (10.6%) and those that played machines in bookmakers (7.2%).
  • The lowest problem gambling prevalence rates were among those that played the National Lottery (0.9%) and scratchcards (1.7%).
  • These figures are very similar to those found in the 2010 BGPS study although problem gambling among those that played machines in bookmakers was lower (7.2%) than in the 2010 BGPS study (8.8%).
  • As with the BGPS 2010 study, the prevalence of problem gambling was highest among those who had participated in seven or more activities in the past year (8.6%) and lowest among those who had taken part in just one activity (0.1%). Furthermore, problem gamblers participated in an average 6.6 activities in the past year.

Given that the same instruments were used to assess problem gambling, the results of the most recent surveys using data combined from the Health Survey for England (HSE) and Scottish Health Survey (SHeS) compared with the most recent British Gambling Prevalence Survey (BGPS) do seem to suggest that problem gambling in Great Britain has decreased over the last few years (from 0.9% to 0.5%). However, Seabury and Wardle again urged caution and noted:

“Comparisons of the combined HSE/SHeS data with the BGPS estimates should be made with caution. While the methods and questions used in each survey were the same, the survey vehicle was not. HSE and SHeS are general population health surveys, whereas the BGPS series was specifically designed to understand gambling behaviour and attitudes to gambling in greater detail. It is widely acknowledged that different survey vehicles can generate different estimates using the same measures because they can appeal to different types of people, with varying patterns of behaviour…Overall, problem gambling rates in Britain appear to be relatively stable, though we caution readers against viewing the combined health survey results as a continuation of the BGPS time series”.

There are other important caveats to take into account including the differences between the two screen tools used in the BGPS, HSE and SHeS studies. Although highly correlated, evidence from all the British surveys suggests that the PGSI and DSM-IV screens capture slightly different groups of problem gamblers. For instance, a 2010 study that I co-authored with Jim Orford, Heather Wardle, and others (in the journal International Gambling Studies) using data from the 2007 BGPS showed that the PGSI may under-estimate certain forms of gambling-related harm (particularly by women) that are more likely to be picked up by some of the DSM-IV items. Our analysis also suggested that the DSM-IV appears to measure two different factors (i.e., gambling-related harm and gambling dependence) rather than a single one. Another important distinction is that the two screens were developed for very different purposes (even though they are attempting to assess the same construct). The PGSI was specifically developed for use in population surveys whereas the DSM-IV was developed with clinical populations in mind. Given these differences, it is therefore unsurprising that national surveys that utilize the screens end up with slightly different results comprising slightly different groups of people.

It also needs stressing (as noted by the authors of most of the national gambling surveys in Great Britain) that the absolute number of problem gamblers identified in any of the surveys published to date has equated to approximately 60 people. To detect any significant differences statistically between any of the studies carried out to date requires very large sample sizes. Given the very low numbers of problem gamblers and the tiny number of pathological gamblers, it is hard to assess with complete accuracy whether there have been any significant changes in problem and pathological gambling between all the published studies over time. Wardle and her colleagues concluded that:

“Overall, based on this evidence, it appears that problem gambling rates in England and Scotland are broadly stable. Whilst problem gambling rates according to either the DSM-IV or the PGSI were higher in 2010, the estimate between 2007 and the health surveys data were similar. Likewise, problem gambling rates according to the DSM-IV and the PGSI individually did not vary statistically between surveys, meaning that they were relatively similar” (p.130).

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

Further reading

Griffiths, M.D. (2014). Problem gambling in Great Britain: A brief review. London: Association of British Bookmakers.

Orford, J., Wardle, H., Griffiths, M.D., Sproston, K. & Erens, B. (2010). PGSI and DSM-IV in the 2007 British Gambling Prevalence Survey: Reliability, item response, factor structure and inter-scale agreement. International Gambling Studies, 10, 31-44.

Seabury, C. & Wardle, H. (2014). Gambling behaviour in England and Scotland. Birmingham: Gambling Commission.

Wardle, H. (2013). Gambling Behaviour. In Rutherford, L., Hinchliffe S., Sharp, C. (Eds.), The Scottish Health Survey: Vol 1: Main report. Edinburgh.

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. (2013). Gambling Behaviour. In Craig, R., Mindell, J. (Eds.) Health Survey for England 2012 [Vol 1]. Health, social care and lifestyles. Leeds: Health and Social Care Information Centre.

Wardle, H., Seabury, C., Ahmed, H., Payne, C., Byron, C., Corbett, J. & Sutton, R. (2014). Gambling behaviour in England and Scotland: Findings from the Health Survey for England 2012 and Scottish Health Survey 2012. London: NatCen.

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

Wardle, H., Sutton, R., Philo, D., Hussey, D. & Nass, L. (2013). Examining Machine Gambling in the British Gambling Prevalence Survey. Report by NatCen to the Gambling Commission, Birmingham.

Net calls: Is online gambling regulation a help or hindrance?

Online gambling regulation is a hot topic and many online gambling operators are wondering what the effect of increased (and arguably stricter) legislative measures will have on the online gambling market. Based on the studies that our research unit has carried out, I would guess that overall it is good news for the industry as I believe this will lead to an increased uptake by those people who are somewhat sceptical or agnostic about online gaming. So why do I think this?

Despite the increase in online gambling research over the last ten years, there has been very little empirical research examining why people gamble online or – just as importantly – why they don’t gamble online. Because there is so little research in this area, Dr Abby McCormack and I published a study in the International Journal of Mental Health and Addiction with adult online and offline gamblers examining the motivating and inhibiting factors in online gambling.

Our findings on the inhibiting factors of online gambling identified one major overarching theme as to what people don’t like about gambling online. In a nutshell, gamblers said that the authenticity of gambling was reduced when gambling online. However, many online gaming operators have now introduced more ‘realistic’ live gaming experiences (e.g., via webcams) so this may diminish over time. However, we also identified other online gaming inhibitors (i.e., the asocial nature and characteristics of the internet, the reduced psychological value of gambling with virtual money, and concerns about the safety of online gambling websites and their trustworthiness). These factors all contributed to the reduced authenticity of the online gambling experience.

Issues around website security, safety and trust, were all major inhibitors that decreased the likelihood of punters gambling online. Predictably, we found that online gamblers were much more likely than the offline gamblers and non-gamblers to believe that the gambling websites were secure. However, there was a perception that some websites were considered more trustworthy than others, and consequently the gamblers generally played on well known sites (e.g., companies that were well established offline).

So what are the implications of these findings for stricter online gaming regulation? From a psychological perspective, research on how and why people access commercial websites indicates that one of the most important factors is trust. If people know and trust the name, they are more likely to use that service. Reliability of the service provider is also a related key factor. Stricter regulation is likely to increase consumer confidence if they feel more protected when they perceive the service to be unfair and/or goes wrong. It is likely to change sceptical gamblers’ perceptions about the reliability and trustworthiness of online gaming operators for the better (no pun intended!).

Even with increased protective legislation, research shows that some punters will always have concerns about Internet security and may never be happy about putting their personal details online. But this mistrust will diminish over the long-term as the ‘screenagers’ of today (the so-called ‘digital natives’) are the potential gamblers of tomorrow. Digital natives generally have more positive attitudes towards online commercial operations. Today’s children and younger adolescents have never known a world without the Internet, mobile phones and interactive television, and are therefore tech-savvy, have no techno-phobia, and are very trusting of these new technologies. For many ‘screenagers’, their first gambling experiences may come not in a traditional offline environment but via the Internet, mobile phone or interactive television. Stricter regulation may not even be an issue for tomorrow’s gamblers as they are already accessing a myriad of online services and are highly trusting of such services.

Despite the lack of trust by some players, the online gaming industry shouldn’t be too worried about stricter regulation. The prevalence of online gambling is steadily increasing and there are lots of reasons why some punters prefer online to offline gambling. Our research findings indicate that those who prefer online (to offline) gambling like the increased convenience, the greater value for money, the greater variety of games, and the anonymity.

Furthermore, online gambling has many advantages for punters as it saves time because they don’t have to travel anywhere, they are not restricted by opening hours, and they can gamble from the comfort of their own home. The removal of unnecessary time consumption (e.g., travelling to a gambling venue) through online gambling is another barrier to gambling participation that had been removed. Increased regulation is highly unlikely to change any of these important motivating factors for gambling online.

Finally, compared to offline gamblers, our research also indicates that online gamblers are more likely to be male, young adults, single, have good qualifications, and in professional and managerial employment. Given this particular demographic profile, this group appears to be highly educated, and are likely to make well informed decisions to gamble online based on due consideration of the facts at hand. Again, stricter regulation is something that is likely to strengthen the decision to gamble rather than inhibit it.

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

Further reading

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2009). Socio-demographic correlates of internet gambling: findings from the 2007 British Gambling Prevalence Survey. CyberPsychology and Behavior, 12, 199-202.

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2011). Internet gambling, health. Smoking and alcohol use: Findings from the 2007 British Gambling Prevalence Survey. International Journal of Mental Health and Addiction, 9, 1-11.

McCormack. A. & Griffiths, M.D. (2012). Motivating and inhibiting factors in online gambling behaviour: A grounded theory study. International Journal of Mental Health and Addiction, 10, 39-53.

McCormack. A. & Griffiths, M.D. (2012). What differentiates professional poker players from recreational poker players? A qualitative interview study. International Journal of Mental Health and Addiction, 10, 243-257.

McCormack, A. & Griffiths, M.D. (2013). A scoping study of the structural and situational characteristics of internet gambling. International Journal of Cyber Behavior, Psychology and Learning, 3(1), 29-49.

McCormack, A., Shorter, G. & Griffiths, M.D. (2013). An examination of participation in online gambling activities and the relationship with problem gambling. Journal of Behavioral Addictions, 2(1), 31-41.

McCormack, A., Shorter, G. & Griffiths, M.D. (2013). Characteristics and predictors of problem gambling on the internet. International Journal of Mental Health and Addiction, 11, 634-657.

Parke, A. & Griffiths, M.D. (2011). Poker gambling virtual communities: The use of Computer-Mediated Communication to develop cognitive poker gambling skills. International Journal of Cyber Behavior, Psychology and Learning, 1(2), 31-44.

Parke, A. & Griffiths, M.D. (2011). Effects on gambling behaviour of developments in information technology: A grounded theoretical framework. International Journal of Cyber Behaviour, Psychology and Learning, 1(4), 36-48.

Parke, A. & Griffiths, M.D. (2012). Beyond illusion of control: An interpretative phenomenological analysis of gambling in the context of information technology. Addiction Research and Theory, 20, 250-260.

Wardle, H., Moody, A., Griffiths, M.D., Orford, J. & and Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: Evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11, 339-356.