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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.

Identity floored: Can gambling addicts be identified in gambling venues?

Although the behavioural characteristics of problem gamblers have been studied for several decades, it has only been the in last decade that there has been interest in studying gambling within the gambling venue itself. Along with my research colleagues Dr. Paul Delfabbro and Dr. Daniel King at the University of Adelaide, we have just published a paper in the journal International Gambling Studies reviewing all the studies that have examined whether problem gamblers and gambling addicts can be identified as having problems based on their gambling within gambling environments.

For instance, a 2004 study published in the journal Gambling Research by Dr. Tony Schellinck and Dr. Tracy Schrans obtained data from a population sample of 927 video lottery terminal (VLT) gamblers in Nova Scotia (Canada) of whom 16.5% were problem gamblers (as measured by the Problem Gambling Severity Index. Based on their analyses, the authors found that the most common experiences or behaviours reported by problem gamblers in terms of frequency were spending three-quarters of their time gambling, gambling for more than 180 minutes in one session, feeling angry, and sweating. Feeling sick or sad or gambling for over 180 minutes in one session were the factors that most strongly differentiated problem gamblers from other gamblers. For example, a person was around three times more likely to be a problem gambler as compared with the base-rate in the sample if they reported feeling sick while gambling. Some indicators (using credit cards, shaking, going out to get cash) were more commonly reported by problem gamblers, but did not occur very often when problem gamblers played VLTs.

A Swiss study carried out by Dr. Jorg Hafeli and Dr. Caroline Schneider in 2006 carried out qualitative interviews with a sample of 28 problem gamblers, 23 casino employees and seven regular gambling patrons in an attempt to develop a range of indicators that might be used to identify problem gamblers within Swiss casinos. Material from these interviews was content analysed and classified into meaningful categories. Only statements that were simple and concise, and which referred to concrete examples of behaviour were included. Problem gamblers were perceived as those who gambled more intensely and frequently, who were compelled to find many different ways to raise funds to defray the costs of gambling, and whose social and emotional responses differed from other gamblers. Problem gamblers were seen to be more socially withdrawn, angry, anxious, depressed, but also more immersed in the activity. Most of these items appeared to have good face validity as indicators of problem gambling.

A similar Australian study undertaken by Dr. Paul Delfabbro and his colleagues in 2007, but which also drew upon material from the two studies outlined above. Unlike the previous studies, attempts were made to develop indicators that were not so specifically focused on particular activities (e.g., casino table games), but which could be applied to venue-based gambling more broadly. Once again, there were items that referred to the statistically unusual frequency or intensity of gambling; evidence concerning gamblers’ need for funding while gambling; variations in social and emotional responses, but also evidence that gamblers had lost control over their gambling urges.

In an initial stage of this research, a list of indicators was provided to both venue staff (n=120) and counsellors (n=20) recruited from several different parts of Australia. Both groups of respondents were asked to indicate whether each item in the checklist was a valid indicator of problem gambling. The main component of the research was a detailed survey of almost 700 regular gamblers recruited either from the general community or from outside gaming venues. Participants were eligible to participate if they gambled at least fortnightly on electronic gaming machines, casino games or sports and race betting, although the principal focus was on gaming because this is largely venue-based. All respondents completed the Problem Gambling Severity Index with 20% classified as problem gamblers.

Their analyses were based on the proportion of problem and non-problem gamblers who reported producing the particular behaviour rarely or more often. There was one group of indicators that occurred relatively quite commonly in problem gamblers, but which were also reported by a moderate proportion of other regular gamblers. A second group were more rarely reported, but typically only by problem gamblers. Some activities, such as using ATMs on several occasions, playing very fast, or try very hard to win on one machine were relatively common amongst problem gamblers (similar to observations reported by an observational study I carried out way back in 1991 and published in the Journal of Community and Applied Social Psychology in his longitudinal study of British amusement arcade players), but also reported by a modest proportion of other gamblers. By contrast, very strong emotional responses or attempts to disguise one’s gambling were rarely reported by non-problem gamblers. The strongest predictors for males appeared to relate to impaired control (i.e., an inability to stop gambling) and emotional responses, whereas strong emotional responses and a preoccupation with gambling appeared most indicative when considering female problem gamblers.

Although these studies found theoretical support for the notion that there are valid indicators available to identify problem gamblers in venues, there are a number of caveats that need to be applied to these findings. The first difficulty is that all of the studies described involved only single samples. For models to be usefully applied to support harm minimisation policies, it would be important to show that models developed in one sample can be replicated using another. A second difficulty is that survey-based responses do not provide a lot of information concerning the practical reality of observing and consolidating information in a venue environment. Even if the same staff members are available in the venue over a protracted period, it does not necessarily follow that they will have the ability to observe the same patrons all the time.

Another potential challenge for the identification process is that studies are based on aggregate results. Although problem gamblers are likely to share many similarities, it is also known that different subgroups of gamblers very likely exist. These views suggest that the significance of particular indicators may, therefore, differ depending upon the type of gambler. For example, in a number of these models or typologies, a distinction is often drawn between gamblers who are emotionally vulnerable and gamble to escape from feelings of anxiety or depression and those who gamble because of the excitement or ‘action’. Those gamblers who are more emotionally vulnerable may be more likely to display emotion when they gamble and be detectable because of these characteristics, whereas there may be others whose behaviour is distinctive because of stronger externalised behaviours (e.g., displays of anger, large bet sizes, histrionics, etc.). At present, based on existing research evidence, it is difficult to determine whether visible indicators cluster according to these subtype models, but it will be important for this possibility to be considered in future research.

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

Additional contributions from Dr. Paul Delfabbro and Dr. Daniel King

Further reading

Delfabbro, P.H., Osborn, A., McMillen, J., Neville, M., & Skelt, L. (2007). The identification of problem gamblers within gaming venues: Final report. Melbourne, Victorian Department of Justice.

Delfabbro, P.H., Borgas, M., & King, D. (2011). Venue staff knowledge of their patrons’ gambling and problem gambling. Journal of Gambling Studies, 27, 1-15.

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

Ferris, J. & Wynne, H. (2001). The Canadian Problem Gambling Index Final Report. Phase II final report to the Canadian Interprovincial Task Force on Problem Gambling.

Griffiths, M.D. (1991). The observational study of adolescent gambling in UK amusement arcades. Journal of Community and Applied Social Psychology, 1, 309-320.

Hafeli, J. & Schneider, C. (2006). The early detection of problem gamblers in casinos: A new screening instrument. Paper presented at the Asian Pacific Gambling Conference, Hong Kong.

Schellinck, T., & Schrans, T. (2004). Identifying problem gamblers at the gambling venue: Finding combinations of high confidence indicators. Gambling Research, 16, 8-24.