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
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.
Over the last decade, I have been asked by the mass media on countless occasions about the increasing popularity of online gambling. The two biggest successes appear to be the use of betting exchanges and online poker. Gamblers clearly feel these types of gambling provide value and an opportunity to exercise their skill. This is coupled with increasingly sophisticated gaming software, integrated e-cash systems, increased realism (in the shape of “real” gambling via webcams, or player and dealer avatars) are all inter-linked facilitating factors. However, another factor that I feel is really important in the rise of online gambling 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.
I’m sure many people’s view of psychology is that it is little more than common sense (and to be honest, some of it is). For instance, psychologists claim that male gamblers are attracted to sports betting because they love competitiveness. There has also been North American research examining the high participation in US college basketball. The researchers found that above anything else, males were attracted to the competitiveness of betting on teams and games. 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, my own research unit published some research into this area in the journal Addiction Research and Theory. Dr. Adrian Parke and myself speculated that a gambler who is highly competitive would experience more arousal and stimulation, and be drawn to gambling as an outlet to release competitive instincts and drives. We also speculated that competitiveness may be linked to problem gambling. For instance, being highly competitive may help in explaining why in the face of negative and damaging consequences, problem gamblers persist in their potentially self-destructive 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.
Psychology is not the only discipline to suggest that competitiveness levels can be associated with problem gambling. 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.
In the published research study that we carried out, we hypothesised that problem gamblers would possess higher levels of competitiveness than non-problem gamblers. Using a competitiveness scale, gamblers were asked to rate statements about competitive reasons for gambling (such as ‘I like to gamble to show others how good I am at it’, ‘I like to gamble to beat the system’, ‘I like to gamble to see how good I am at it’) and general competitive tendencies (such as ‘I am competitive’, ‘I enjoy taking risks’, ‘I am abitious’). We found that problem gamblers scored significantly higher on the competitiveness scale. Put simply, we concluded that having a highly competitive streak may in fact be a potential risk factor for problem gambling.
It is not hard to see how a highly competitive person would be attracted to gambling by the competitive and challenging nature of the behaviour. However, why are competitive people at particular risk of developing pathological gambling behaviour? It could be the case that highly competitive gamblers are less inclined to ‘throw the towel in’ or accept a loss, and, as a result are more prone to chasing behaviour. Chasing behaviour – that is, increasing frequency and stake of bets in an attempt to recoup losses – is self-perpetuating. When gamblers chase losses it is highly probable they will lose more and the need to recoup losses increases as time passes. What’s more, chasing losses has been shown to be a major risk factor in the development of gambling problems. At the other end of spectrum, winning is potentially more rewarding for a competitive gambler as they are more inclined to perceive gambling as an internal and external challenge than a non-competitive gambler. In addition, winning will be much more rewarding after incurring losses. Put very simply, the competitive person feels greater triumph by defeating unlikely odds and emerging from what appeared a hopeless situation.
Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
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.
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. (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.D. & Irwing, P. (2004). Personality traits in pathological gambling: Sensation seeking, deferment of gratification and competitiveness as risk factors, Addiction Research and Theory, 12, 201-212.
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. (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.
Match-fixing is nothing new. There’s always been big money to make on the outcome of sporting events. However, spot-fixing (i.e., the action or practice of dishonestly determining the outcome of a specific part of a match or game before it is played) is a more recent phenomenon. The situation escalated in December 2013 when six men (including Blackburn Rovers’ DJ Campbell) were arrested after an investigation into spot-fixing in football by the National Crime Agency. According to the British newspaper The Sun On Sunday, one of their undercover investigators reported that ex-Portsmouth footballer Sam Sodje could arrange for professional football league players to get themselves yellow cards in return for large amounts of money (i.e., tens of thousands of pounds). Consequently, the UK Government is believed to be considering whether match-fixing should be a criminal offence.
Over the past few years, allegations and convictions relating to spot-fixing have been made in many different sports including football, cricket, snooker and horse-racing. In all honesty, this doesn’t surprise me in the least – particularly because sport and gambling have always been inextricably linked. Matt Scott made a number of interesting observations on the issue in a December 2013 article for Inside World Football:
“Betting has a tradition of accompanying football in England in the same way custard goes with English puddings. It just adds a bit of flavour to the proceedings. It is a guilty pleasure, nothing more. No harm done…[However] now is the time to reappraise the complicated English relationship with the ‘harmless’ flutter. The ubiquity of the betting companies whose advertisements fill the half-time breaks of every match covered on television has been very lucrative for football. Figures from the website sportingintelligence.com suggest that in title sponsorships alone, Premier League clubs earn £13m a year from betting companies…Investigations by the ‘Sun on Sunday’ and the ‘Daily Telegraph’ have shown how professional footballers appear to be fixing events in matches…Whether they know it or not, players who fix matches or events within them are the foot soldiers of international match-fixing rings who, according to sports anticorruption experts, have links with serious organised crime. The fixers do not place the bulk of their bets with onshore UK bookmakers but in Asian markets where the liquidity is deeper and where the regulatory scrutiny is much lighter…As the National Crime Agency’s arrests have shown, it is high time for law makers and enforcers to act. For if not, it will be easier to deliver yellow cards to order on the football pitch than for miscreant bookmakers to be issued with cautions about their activities”.
Personally, I think the rise of match-fixing and spot-fixing has mirrored the rise in the use of betting exchanges like Betfair, and the rise of in-play betting. Back in 2005, I published an article on betting exchanges and argued that they had radically altered the shape of gambling particularly because – for the first time – gamblers could bet on individuals and/or teams losing (in contrast to traditional bookmakers that would only take bets on who was going to win). Betting shop operators got worried because their clientele could use betting exchanges to become bookmakers themselves. As a consequence, I argued that betting exchanges had potentially opened the door to fraud, corruption, and crime. As Matt Scott reported:
“In 2006 a whistleblower who had previously worked for the bookmaker Victor Chandler claimed to have data from accounts belonging to Premier League players and managers. The account holders had allegedly bet on matches in their own competitions, in breach of football’s regulations. But Victor Chandler International [VCI] obtained a high-court injunction preventing the release of information about the accounts…There is no way of knowing if the alleged breaches of regulations relating to the VCI accountholders amounted to anything more sinister. (And it is fair to say that Chandler would be unlikely to have exposed himself repeatedly to bets on matches involving account holders’ teams, given the substantial risk of manipulation)”.
More recently, in-play betting has become very popular among sports bettors and plays into the hands of the spot-fixers. As the CEO of OpenBet commented:
“The periodic ritual of predicting a daily or weekly series of events is no longer the mainstay. Today’s punter wants to be able to turn on their gadget of choice and instantly be offered an array of real-time betting opportunities with immediate results…Sports betting is growing in what is offered, how it is offered, when it is offered, where it is offered, and to whom it is offered…Like the financial markets, volatile events produce increased liquidity and increased liquidity produces greater revenue to the operator”.
We can now bet on dozens of ‘in-play’ markets while watching almost any sporting event. Should I wish to, during any football match I can bet on everything from 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, who will get a red card, and/or in what minute of the second half will the first free kick be awarded. Money talks – and there is big money to be made. Paying sports men and women relatively large amounts of money to lose a point (in tennis), get a yellow card (in football), go down in the ninth round (in boxing), or lose a frame (in snooker) can result in even more money for those paying the sports players in the first place.
But maybe technological advance will be the solution to the problem. Technology makes it easier to spot betting cheats and criminal activity. Betting exchange and in-play betting technology means that every bet made through their systems can be tracked and leave an audit trail. Unusual betting patterns can be identified and shared with the relevant sporting and criminal authorities. While prevention is better than detection, betting audit trails do at least give us the chance to crack down on the cheats – even if it’s after the fact. The more sports cheats that are caught, the bigger the deterrent. While we would never want to stop people having an enjoyable punt on their favourite team, we do need to make sure that gambling is as fraud-free as possible. In Matt Scott’s article, the English football Premier League’s general secretary, Nic Coward, summarized what is required of the UK government.
“It [is] true of any regulated sector that there need to be clear regulations in place so that the sector and stakeholders with an interest in the sector understand what they are…That they are monitored; that there is an effective compliance regime; and that there are real enforcement provisions behind it”.
Note: This blog is a much extended version of an article that first appeared in Nottingham Trent University’s Expert Opinion column
Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Griffiths, M.D. (2006). All in the game. Inside Edge: The Gambling Magazine, July (Issue 28), p. 67.
Griffiths, M.D. (2010). Gambling addiction among footballers: causes and consequences. World Sports Law Report, 8(3), 14-16.
Scott, M. (2013). Time to overhaul football’s betting relationship. Inside World Football. December 12. Located at: http://www.insideworldfootball.com/matt-scott/13779-matt-scott-time-to-overhaul-football-s-betting-relationship