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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.
Net advantage: Another brief look at the psychology of online poker
From everything that I’ve observed over the last decade in the gambling world, the one thing that has caught my eye more than anything else is the number of online gambling stories – particularly about the rise of online poker. Clearly, online poker and traditional poker are not synonymous. As I outlined in one of my previous blogs, a very useful psychological tool in poker is to ‘read’ a player through their body language and their verbalisations. When playing online poker, a gambler is denied this advantage. Poker players must therefore seek to manipulate their poker-playing opponents by using the psychological tools at their disposal. One of my colleagues who has researched this area (Dr. Adrian Parke), believes that in a ‘SunTzu’-type way, an online poker player must take their weakness (in this case, not being able to physically see other players) and turn it into a positive strength. Put simply, a player must use the non-transparency inherent in the situation to their advantage.
Online poker permits players to create a false identity. As a player you could portray the façade of being a young attractive novice female player when in fact you are actually a very experienced recognised pro. On a psychological level, the key to a ‘hustle’ or manipulating other players in poker is by projecting a character and hiding your identity. Essentially it is about representing a façade, whether it is for one hand or the whole of the game. While playing poker online, a player can adapt any ‘character’ they wish to suit any game in which they engage in. For instance, if you are playing with novices it may be profitable to portray an experienced professional in order to intimidate players into submission.
Using the messaging systems provided, it is easier for online poker players to develop their persona(s). The tone and pitch of what a player “says” is not revealed in the text on the screen. At a fundamental level all players are acting with their most unemotional ‘poker face’. In these situations, players can exude confidence as they go all in on a psychological bluff, when in reality they may have shaking hands and be sweating like a pig. The key to winning on a psychological level is by inducing emotional reactions from other players, so with knowledge of the opponent, it is possible to ‘tailor’ interactions to induce the desired response.
Social interaction at the online poker table is not confined to adversarial chastising. It is also possible to develop amiable relationships between players. Online poker – particularly at low stakes tables – is often more about entertainment than making profits. In poker it is not necessary to reveal your hand if nobody calls (i.e., pays to see it). Without seeing cards it is more difficult to understand player behaviour. However, at more sociable tables, players will reveal what they had to opposing players, if nothing else but to indulge the observers. Creating false ‘alliances’ is a way of ascertaining more information about your opponents and improving your ability to ‘read’ them.
From a psychological perspective, there are also some things to be aware of in the online gambling world. At a basic level, what separates professional gamblers and novice (or problem) gamblers is the factor of self-control. The rule of thumb is to avoid becoming emotionally involved in the game. Inducing emotional rather than logical reactions from gamblers is what makes the gambling industry so profitable. By remaining unemotional gamblers can protect themselves from recklessly chasing losses and avoid going on ‘tilt’. People gambling online are particularly at risk from engaging in chasing losses for the simple reason that they have 24-hour convenient access from their home or workplace and have the potential to be constantly subjected to temptation. What’s more, in this asocial world, they often lack friends acting as a “social safety net” to give objective appraisals of the player’s behaviour.
The best ways of avoiding becoming emotionally engaged online is to have (i) reflective time outs and (ii) an objective attribution of outcomes. Having reflective time-outs simply refers to playing slowly, making gambling decisions with accrued knowledge (for example, knowledge of probability and of opponents). It is advisable after a ‘bad beat’ to be disciplined enough sit out one or two hands to regain composure before playing again. Determining objective attributions of outcomes occurs at a psychological level and concerns the gambler’s locus of control. For the gambler, this means having an external locus of control when assessing the cards they have and an internal locus of control regarding what they do with the cards available.
The mantra of poker players is that ‘You can only play the hand you were dealt’. All players will experience streaks of both desirable and poor hands, and it is how a player responds to these streaks that will determine their success. It is very easy to become frustrated while in a negative streak. Likewise, it is easy in a positive streak to become narcissistic and complacent. It is the knowledgeable player that understands probability and who realises that over a continuous playing period, positive and negative streaks are inevitable and transient.
Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Further reading
Biolcati, R., Passini, S. & Griffiths, M.D. (2015). All-in and bad beat: Professional poker players and pathological gambling. International Journal of Mental Health and Addiction, in press.
Griffiths, M.D., Parke, J., Wood, R.T.A. & Rigbye, J. (2010). Online poker gambling in university students: Further findings from an online survey. International Journal of Mental Health and Addiction, 8, 82-89.
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.
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., & Parke, J. (2005) Can playing poker be good for you? Poker as a transferable skill. Journal of Gambling Issues, 14.
Recher, J. & Griffiths, M.D. (2012). An exploratory qualitative study of online poker professional players. Social Psychological Review, 14(2), 13-25.
Wood, R.T.A., Griffiths, M.D. & Parke, J. (2007). The acquisition, development, and maintenance of online poker playing in a student sample. CyberPsychology and Behavior, 10, 354-361.
Wood, R.T.A. & Griffiths. M.D. (2008). Why Swedish people play online poker and factors that can increase or decrease trust in poker websites: A qualitative investigation. Journal of Gambling Issues, 21, 80-97.
Gamblers anonymous: The psychology of live online casino gambling
Over the last decade, my research unit has carried out an increasing amount of research into the psychology of online gambling. In some of our recent research interviewing online gamblers, offline gamblers and non-gamblers, we found that people who gambled online did so because of its (i) convenience, (ii) greater value for money, (iii) the greater variety of games, and (iv) anonymity. Perhaps more interestingly, were the inhibiting reasons that stopped people from wanting to gamble online in the first place. The main inhibiting reason that stopped people gambling online was that offline gamblers and non-gamblers said the authenticity of gambling was significantly reduced when gambling online. We also found a number of other inhibitors of online gambling including (i) the reduced realism, (ii) the asocial nature of the internet, (iii) the use of electronic money, and (iv) concerns about the safety of online gambling websites. The reduced authenticity and realism may help to explain why online live action casino games are seen as increasingly popular among some types of gamblers.
This empirical research also chimes with my own personal psychology of online gambling. One of the main reasons I don’t like gambling at Internet casinos is that I believe the majority of game outcome are likely to be pre-programmed and/or predetermined. To me, this is somewhat akin to playing with imaginary dice! Our empirical research findings also help explain the rise of live online casino gambling. Players not only want increased realism and authenticity, but still have the added advantages of online anonymity while playing.
In online live casino gaming, the anonymity of the Internet allows players to privately engage in gambling without the fear of stigma. This anonymity may also provide the gambler with a greater sense of perceived control over the content, tone, and nature of the online experience. Anonymity may also increase feelings of comfort since there is a decreased ability to look for, and thus detect, signs of insincerity, disapproval, or judgment in facial expression, as would be typical in face-to-face interactions. For activities such as gambling, this may be a positive benefit particularly when losing as no-one will actually see the face of the loser. Anonymity may reduce social barriers to engaging in gambling, particularly those activities thought to be more skill-based gambling activities (such as poker or blackjack) that are relatively complex and often possess tacit social etiquette. The potential discomfort of committing a structural or social faux-pas in the gambling environment because of inexperience is minimized because the player’s identity remains concealed.
Furthermore, one of the main reasons why behaviour online is very different from offline is because it provides a ‘disinhibiting’ experience. One of the main consequences of disinhibition is that on the internet people lower their emotional guard and become much less restricted and inhibited in their actions.
The increase in online live casino gambling has happened alongside the rise of online betting exchanges – the type of online gambling where it could be argued that skill can – to some extent – be exercised. For gamblers, having a punt on live sporting events via betting exchanges is a psychologically safer option because punters know (or can check) who won a particular football or horse race. The playing of live action casino games via the Internet shares some of the psychological similarities of online betting exchanges.
The rise of live online gambling has been coupled with increasingly sophisticated gaming software, integrated e-cash systems, and increased realism (in the shape of “real” gambling via webcams, live remote wagering, and/or player and dealer avatars). These are all inter-linked facilitating factors. Another factor that I feel is really important in the rise of online gambling (including online live action casino games) is the inter-gambler competition. Obviously there is an overlap between competitiveness and skill but they are certainly not the same. What’s more recent research has suggested that being highly competitive may not necessarily be good for the gambler. For instance, Professor Howard Shaffer, a psychologist at Harvard University, claims that men are more likely to develop problematic gambling behaviour because of their conventionally high levels of aggression, impulsivity and competitiveness. Clearly, the idea of the competitiveness of the activity being one of the primary motivations to gamble is well supported.
Based on the fact that so little research has systematically examined the links between gambling and competitiveness, our research unit did some research into this area. We speculated that a gambler who is highly competitive will experience more arousal and stimulation, and be drawn to gambling as an outlet to release competitive instincts and drives. This is likely to occur more in activities like online poker and online live action casino games. Our research did indeed show that problem gamblers were significantly more likely than non-problem gamblers to be competitive.
Being highly competitive may help in explaining why in the face of sometimes negative and damaging financial consequences, gamblers persist in their habit. Psychological research in other areas has consistently shown that highly competitive individuals are more sensitive to social comparison with peers regarding their task performance. Applying this to a gambling situation, it is reasonable to suggest that competitive gamblers may be reluctant to stop gambling until they are in a positive state in relation to opposing gamblers, perhaps explaining why excessive gambling can sometimes occur.
Sociologists have speculated that factors of the human instinctual expressive needs, such as competition, can be temporarily satisfied when engaging in gambling activities. Evidence exists supporting gambling as an instrumental outlet for expressing competitive instinctual urges. The US sociologist Erving Goffman developed what he called the ‘deprivation-compensation’ theory to explain the relationship between gambling and competitiveness. He suggested that the stability of modern society no longer creates situations where competitive instincts are tested. Therefore, gambling is an artificial, self-imposed situation of instability that can be instrumental in creating an opportunity to test competitive capabilities. Again, online live action casino gambling is another gambling form that can facilitate such instinctive needs.
Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Further reading
Goffman, I. (1972). Where the action is. In: Interaction Ritual (pp. 149–270). Allen Lane, London.
Griffiths, M.D. (2010). Gambling addiction on the Internet. In K. Young & C. Nabuco de Abreu (Eds.), Internet Addiction: A Handbook for Evaluation and Treatment. pp. 91-111. New York: 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.
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.
Kuss, D. & 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. (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. (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.
Wardle, H. & Griffiths, M.D. (2011). Defining the ‘online gambler’: The British perspective. World Online Gambling Law Report, 10(2), 12-13.
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.
The weighting game: Gambling with the nation’s health (revisited)
A couple of weeks ago I wrote a blog on why problem gambling should be considered a health issue. Earlier this week, I came across an interesting study carried out by jackpot.co.uk who surveyed 2,131 online gamblers (58% males and 42% female) about their health. After the self-reported data had been collected, the gamblers were classed into one of nine categories based on the casino game type that the gambler played most often (i.e., slot machines, video poker, blackjack, roulette, dice/craps, baccarat, poker, pai gow, and ‘other’). The data were then tabulated so that all the health variables (including obesity) corresponded to the gambler’s preferred casino game.
I was interested in the findings not only because I am a Professor of Gambling Studies, but also because I was a member of the Department of Health’s ‘Expert Working Group on Sedentary Behaviour, Screen Time and Obesity’ (a reference to our final report to the British government can be found in the ‘Further Reading’ section below). The study took an objective measurement of physical condition by asking each gambler their height (centimetres) and their weight (kilograms) to calculate each person’s Body Mass Index (BMI) by dividing the gamblers’ weight by height (metres) and dividing by height again (for example, someone who weighs 80kg and is 180cm tall, the BMI is 24.1 as this is 80/1.80)/1.80). The survey then asked s few general health and lifestyle questions (similar to ones that we have used in the last few British Gambling Prevalence Surveys:
- Do you normally drink more than the recommended limit for weekly alcohol consumption (21 units of alcohol for men and 14 for women)? (Yes/No)
- Do you smoke regularly? (Yes/No)
- Do you normally engage in at least 30 minutes of physical activity, 5 times per week? (Yes/No)
Overall, the survey found that British casino gamblers as a group were no less healthy than the rest of the British population, with an average Body Mass index (BMI) of 27 (which is the same as the UK national average). However, the survey also reported that the average BMIs, health, and lifestyle choices (such as smoking cigarettes, engaging in exercise, and drinking alcohol varied considerably depending on the casino games that the respondents played. Here are some of the main findings:
- Slots players were the least healthy. They took less exercise and had an average BMI of 31, pushing them into the category of obese (which is linked to increased chance of developing illnesses such as Type 2 diabetes and reduced life expectancy)
- Roulette, blackjack, video poker and craps/dice players were not far behind slots players, each having BMI levels higher than the national average.
- Those that played poker, baccarat and Pai Gow had an average BMI of 25 or under (well within the normal range recommended by the World Health Organisation.
- Whilst drinking levels might be reasonably high among poker players, they were very exercise conscious, with 58% engaging in physical activity for at least 30 minutes, five times a week. For slots players the figure was 27% meeting this government recommended target.
- Overall slots players drink the most, with 24.1% drinking over the recommended weekly limit. Poker players are not far behind on 23%. Female slots players were the biggest drinking subgroup, closely followed by male poker players.
- Slots players also smoked more, with 24% being regular smokers (compared to the UK national average of 20%). Blackjack and roulette players smoked slightly more than average, on 21% and 22% respectively, while poker players smoked slightly less than average, on 19.5%.
None of these results is overly surprising as there are many studies (including my own) showing comorbidity between gambling and other potentially addictive behaviours. However, very few academic studies have ever looked at these health variables by game type. Although this was not an academic study, the results will likely be of interest to those in the gambling studies field.
The survey also examined the most common platform on which the gamblers played casino games. The most common was the desktop computer (65%), followed by mobiles and tablets (20%) and land-based casinos (14%). This is not surprising given the survey was completed by online gamblers. Interestingly, desktop use was linked to higher levels of obesity, drinking and smoking. This is something that I would expect given that online gambling is the most sedentary of these activities.
There are (of course) some limitations with the data collected particularly as it comprised a self-selected sample of online gamblers that played via jackpot.co.uk websites. We have no idea as to whether the sample is representative of all online gamblers but as I noted above, it is no surprise that online gamblers preferred playing casino games online compared to offline (i.e., land-based casinos). The data were also self-report and are therefore open to any number of individual biases including recall biases and social desirability biases. Also, we have no geographical breakdown of the sample as the internet (by definition) is global. However, the sample size is good in comparison to many published studies on gambling and the sample included individuals that were actually gamblers (as opposed to university undergraduates or members of the general public). According to Sam Marsden (editor of jackpot.co.uk and author of the report):
“There’s an undeniable link connecting passive games like slots and video poker to unhealthy, sedentary lifestyles. On the other hand, games that require concentration, strategy and some physical stamina like poker and blackjack seem to fare much better in the health stakes. It seems it’s less a case of ‘you are what you eat’ and more ‘you are what you play’.”
Although such a conclusion could be argued to be PR spin on the findings, the results suggest that more rigorous studies could be carried out in the area including secondary analyses of the robust datasets that already exist including the British Gambling Prevalence Surveys, the English Health Surveys, and the Scottish health Surveys.
Dr. Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Further reading
Biddle, S., Cavill, N., Ekelund, U., Gorely, T., Griffiths, M.D., Jago, R., et al. (2010). Sedentary Behaviour and Obesity: Review of the Current Scientific Evidence. London: Department of Health/Department For Children, Schools and Families (126pp).
Griffiths, M.D. (2001). Gambling – An emerging area of concern for health psychologists. Journal of Health Psychology, 6, 477-479.
Griffiths, M.D. (2004). Betting your life on it: Problem gambling has clear health related consequences. British Medical Journal, 329, 1055-1056.
Griffiths, M.D. (2007). Gambling Addiction and its Treatment Within the NHS. London: British Medical Association (ISBN 1-905545-11-8).
Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2010). Gambling, alcohol consumption, cigarette smoking and health: findings from the 2007 British Gambling Prevalence Survey. Addiction Research and Theory, 18, 208-223.
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.
Marsden, S. (2014). Booze, bets, and BMI. Jackpot.co.uk, October 6. Located at: http://www.jackpot.co.uk/online-casino-articles/booze-bets-bmi
Rigbye, J. & Griffiths, M.D. (2011). Problem gambling treatment within the British National Health Service. International Journal of Mental Health and Addiction, 9, 276-281.
Wardle, H., Griffiths, M.D., Orford, J., Moody, A. & Volberg, R. (2012). Gambling in Britain: A time of change? Health implications from the British Gambling Prevalence Survey 2010. International Journal of Mental Health and Addiction, 10, 273-277.
Wardle, H., Moody. A., Spence, S., Orford, J., Volberg, R., Jotangia, D., Griffiths, M.D., Hussey, D. & Dobbie, F. (2011). British Gambling Prevalence Survey 2010. London: The Stationery Office.
Wardle, H., Seabury, C., Ahmed, H., 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.
