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General selection: Is voluntary self-exclusion a good proxy measure for problem gambling?

A couple of months ago, Dr. Michael Auer and I published a short paper in the Journal of Addiction Medicine and Therapy (JAMT) critically addressing a recent approach by researchers that use voluntary self-exclusion (VSE) by gamblers as a proxy measure for problem gambling in their empirical studies. We argued that this approach is flawed and is unlikely to help in developing harm-minimization measures.

For those who don’t know, self-exclusion practices typically refer to the possibility for gamblers to voluntarily ban themselves from playing all (or a selection of) games over a predetermined period. The period of exclusion can typically be chosen by the gambler although some operators have non-negotiable self-exclusion periods. Self-exclusion in both online sites and offline venues has become an important responsible gambling practice that is widely used by socially responsible operators.

There are many reasons why players self-exclude. In a 2011 study in the Journal of Gambling Studies by Dr. Tobias Hayer and Dr. Gerhard Meyer, players frequently reported excluding as a preventive measure and annoyance with the gambling operator as reasons for VSE. Furthermore, only one-fifth of self-excluders reported to be problem gamblers (21.2%). A recent 2016 (conference) paper by Dr. Suzanne Lischer (2016) reported that in a study of three Swiss casinos, 29% of self-excluders were pathological gamblers, 33% were problem gamblers, and 38% were recreational gamblers. Given that many voluntary self-excluders do not exclude themselves for gambling-related problems, Dr. Lischer concluded that self-exclusion is not a good indicator of gambling-related problems. In line with these results, a 2015 study published in International Gambling Studies led by Simo Dragicevic compared self-excluders with other online players and reported no differences in the (i) mean number of gambling hours per month or (ii) minutes per gambling session. The study also reported that 25% of players self-excluded within one day of their registration with the online operator. This could also be due to the fact that online players can self-exclude with just a few mouse-clicks.

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Most studies to date report that the majority of voluntary self-excluders tend to be non-problem gamblers. Additionally, in 2010, the Australian Productivity Commission reported 15,000 active voluntary self-exclusions from 2002 to 2009 and that this represented only 10-20% of the population of problem gamblers. This means that in addition to most self-excluders being non-problem gamblers, that most problem gamblers are not self-excluders. This leads to the conclusion that there is little overlap between problem gambling and self-excluding.

Over the decade, analytical approaches to harm minimization have become popular. This has led to the development of various tracking tools such as PlayScan (developed by Svenska Spel), Observer (developed by 888.com), and mentor (developed by neccton and myself). Furthermore, regulators are increasingly recognizing the importance of early risk detection via behavioural tracking systems. VSE also plays an important role in this context. However, some systems use VSE as a proxy of at-risk or problem gambling.

Based on the findings from empirical research, self-exclusion is a poor proxy measure for categorizing at-risk or problem gamblers and VSE should not be used in early problem gambling detection systems. The reasons for this are evident:

  • There is no evidence of a direct relationship between self-exclusion and problem gambling. As argued above, self-excluders are not necessarily problem gamblers and thus cannot be used for early risk detection.
  • There are various reasons for self-exclusion that have nothing to do with problem gambling. Players exclude for different reasons and one of the most salient appears to be annoyance and frustration with the operator (i.e., VSE is used as a way of venting their unhappiness with the operator). In this case, an early detection model based on self-exclusion would basically identify unhappy players and be more useful to the marketing department than to those interested in harm minimization
  • Problem gamblers who self-exclude are already actively changing their behaviour. The trans-theoretical ‘stages of change’ model (developed by Dr. Carlo DiClemente and Dr. James Prochaska) argues that behavioural change follows stages from pre-contemplation to action and maintenance. One could argue that the segment of players who self-exclude because they believe their gambling to be problematic are the ones who already past the stages where assistance is usually helpful in triggering action to cease gambling. These players are making use of a harm-minimization tool. The ones actually in need of detection and intervention are the ones who have not yet reached this stage of change yet and are not thinking about changing their behaviour at all. This is one more argument for the inappropriateness of self-exclusion as a proxy for problem gambling.

But what could be done to prevent the development of gambling-related problems in the first place? For the reasons outlined above, we would argue that the attempt to identify problem gambling via playing patterns that are derived from self-excluders does not assist harm minimization. Firstly, this approach does not target problem gamblers, and secondly it does not provide any insights into the prevention of such problems.

It is evident that any gambling environment should strive to minimize gambling-related harm and reduce the amount of gambling among vulnerable groups. It is also known that information that is given to individuals to enable behavioural change should encourage reflection because research has shown that self-monitoring can enable behavioural change in the desired direction. Dr. Jim Orford has also stated that attempts to explain such disparate gambling types from a single theoretical perspective are essentially a fool’s errand. This also complements the notion that problem gambling is not a homogenous phenomenon and there is not a single type of problem gambler (as I argued in my first book on gambling back in 1995). This also goes in line with the belief of Dr. Auer and myself that gambling sites have to personalize communication and offer the right player the right assistance based on their individual playing history. Recent research that Dr. Auer and I have carried out supports this line of thinking.

Studies have also shown that dynamic feedback in the form of pop-up messages has a positive effect on gambling behaviour and gambling-related thoughts. For instance, research from Dr. Michael Wohl’s team in Canada have found that animation-based information enhanced the effectiveness of a pop-up message related to gambling time limits. Our own research has found that an enhanced pop-up message (that included self-appraisal and normative feedback) led to significantly greater number of players ending their session than a simple pop-up message. In a real-world study of online gamblers, we also found that personalized feedback had a significant effect in reducing the time and money spent gambling.

Personalized feedback is a player-centric approach and in addition to gambling-specific research, there is evidence from many other areas that shows the beneficial effects on behavioural change. For instance, personalized messages have shown to enable behavioural change in areas such as smoking cessation, diabetes management, and fitness activity. Contrary to the self-exclusion oriented detection approach, we concluded in our recent JAMT paper that personalized feedback aims to prevent and minimize harm in the first place and is a much better approach to the prevention of problem gambling than using data from those that self-exclude from gambling.

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

 Further reading

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

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

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

Auer, M., Littler, A., Griffiths, M. D. (2015). Legal Aspects of Responsible Gaming Pre-commitment and Personal Feedback Initiatives. Gaming Law Review and Economics. 19, 444-456.

DiClemente, C. C., Prochaska, J. O., Fairhurst, S. K., Velicer, W. F., Velasquez, M. M., & Rossi, J. S. (1991). The process of smoking cessation: an analysis of precontemplation, contemplation, and preparation stages of change. Journal of Consulting and Clinical Psychology, 59, 295-304.

Dragicevic, S., Percy, C., Kudic, A., Parke, J. (2015). A descriptive analysis of demographic and behavioral data from Internet gamblers and those who self-exclude from online gambling platforms. Journal of Gambling Studies. 31, 105-132.

Gainsbury, S. (2013). Review of self-exclusion from gambling venues as an intervention for problem gambling. Journal of Gambling Studies, 30, 229-251.

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

Griffiths, M.D. & Auer, M. (2016). Should voluntary self-exclusion by gamblers be used as a proxy measure for problem gambling? Journal of Addiction Medicine and Therapy, 2(2), 00019.

Hayer, T., & Meyer, G. (2011). Self-exclusion as a harm-minimization strategy: Evidence for the casino sector from selected European countries. Journal of Gambling Studies, 27, 685-700

Kim, H. S., Wohl, M. J., Stewart, M. K., Sztainert, T., Gainsbury, S. M. (2014). Limit your time, gamble responsibly: setting a time limit (via pop-up message) on an electronic gaming machine reduces time on device. International Gambling Studies, 14, 266-278.

Lischer, S. (2016, June). Gambling-related problems of self-excluders in Swiss casinos. Paper presented at the 16th International Conference on Gambling & Risk Taking, Las Vegas, USA.

Suurvali, H., Hodgins, D. C., Cunningham, J. A. (2010). Motivators for resolving or seeking help for gambling problems: A review of the empirical literature. Journal of Gambling Studies, 26, 1-33

Time out: Are voluntary self-exclusion services about responsible gambling or problem gambling?

Responsible gambling practices have now become the norm within the gaming industry. One of the first types of responsible gambling practice introduced by gaming companies was the introduction of self-exclusion schemes for problem gamblers, particularly in offline casinos. More recently, online gaming companies have begun to introduce self-exclusion schemes. This blog briefly examines the question of whether such schemes should be underpinned by concerns around problem gambling or whether they should be about responsible gambling more generally. This is a particularly important issue for accreditation agencies who typically recommend to online gaming companies very specific periods that online gamblers should be excluded for.

Self-exclusion initiatives are now very common and although these contracts have some value in containing the harms to established problem gamblers, they could certainly be a lot more effective. There is little research demonstrating whether they stop gambling in either the short-term or long-term as exclusion from one or more venues still leaves opportunities to gamble elsewhere. However, a small proportion of problem gamblers appreciate the opportunity to self-exclude and this is clearly a valuable service for them.

In a 2007 report by Dr. Robert Williams and his Canadian colleagues, they noted that the effectiveness of offline self-exclusion programs can be measured in three ways. These are the: (i) utilization rate, (ii) percentage of self-excluders who successfully refrain from entering the gaming venue during the self-exclusion period, and (iii) impact self-exclusion has on overall gambling behaviour. Utilization rates are typically very low across most jurisdictions (0.5% to 7%) although countries with a proactive self-exclusion program (e.g., Holland) are typically much higher.

There has been only a limited amount of research examining how many self-excluders refrain from gambling at a venue where they have excluded themselves. According to researchers like Dr. Robert Ladouceur, typical rates suggest around 20-25% of self-excluders attempt to re-gain access to the gambling venue they excluded themselves from, although higher compliance rates have been reported in Holland. There have been very few empirical reports of whether self-excluders curtail their gambling behaviour. Some studies report that when gamblers have self-excluded from one venue, they simply go and gamble elsewhere.

The most positive evaluation was a 2007 Canadian study published in the Journal of Gambling Studies led by Dr. Ladouceur and colleagues who examined 161 self-excluders. A year later, researchers from the same university (including Dr. Ladouceur) also reported in the Journal of Gambling Studies some success with an ‘improved’ self-exclusion program but the number of self-excluders in the data set (n=39) was very small. After two-year follow-up, most had significant reductions in urge to gamble, the intensity of negative consequences, and pathological gambling scores using the criteria of the American psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders. Research examining offline self-exclusion has almost exclusively viewed self-exclusion schemes as being about protecting problem gamblers. However, this is not the necessarily the case with online gambling.

Compared to offline self-exclusion, there has been even less research on online self-exclusion schemes. Here, most of the research has examined what online gamblers actually think about self-exclusion schemes and/or their use of them. The Global Online Gambler Survey (led by Dr. Jonathan Parke and published by my International Gaming Research Unit, 2007) collected data from 10,865 online gamblers. The survey specifically asked about the use of online social responsibility tools. Although no single feature stood out as critically important, 58% stated that they considered self-exclusion as ‘quite useful’ (with 23% saying it was ‘very’ or ‘extremely’ useful).

In a 2009 survey of 2,348 online gamblers published in the journal CyberPsychology and Behavior that I and my colleagues carried out (all clientele of the Swedish gaming operator Svenska Spel) examining online social responsibility tools via the PlayScan behavioural tracking system, we reported that a quarter of our sample used PlayScan. Over one-third of respondents (42%) reported the self-exclusion features to be ‘quite useful’ or ‘very useful’. Just under one in five PlayScan users (17%) had actually used one of the self-exclusion features. In a 2010 study of online gamblers published in the International Journal of Mental Health and Addiction, Dr. Tobias Hayer and Gerhard Meyer carried out a follow-up survey one year after the initiation of self-exclusion with a small sub-sample (n=20). They reported that the restriction of access to a single online gambling site had favourable psychosocial effects.

Despite the limited empirical evidence showing whether self-exclusion schemes are effective, gamblers (particularly those online) appear to appreciate short-term self-exclusion facilities even if they do not have a problem with gambling. For instance, in the 2009 study we carried out, online gamblers reported that the most useful self-exclusion feature was the 7-day self-exclusion rated as ‘quite/very useful’ by just under half of respondents (46%). This was followed by 1-month self-exclusion (24%), 24-hour self-exclusion (24%), and permanent self-exclusion (16%). These types of self-exclusion are likely to be associated with non-problem gamblers who may want to restrict their gambling behaviour to a very specific instance.

Given the (presumed) unproblematic nature of internet gambling among respondents, it was unsurprising that only 16% thought permanent self-exclusion would be useful to them personally. If anything, this might appear to be a slightly higher figure than might have been predicted as it could be argued that non-problem gamblers would be unlikely to make use of a permanent self-exclusion.

As noted above, the seven-day exclusion period was the most useful with almost a half of participants endorsing this as their most favoured. This may have been especially useful for those who do not want to gamble for a particular period such as the week before a monthly ‘pay day’. One-month and one-day self-exclusion periods were most popular for around half the participants (approximately 25% each). These types of self-exclusion are more likely to be associated with non-problem gamblers who may want to restrict their gambling behaviour to a very specific instance such as preceding a night of heavy drinking (e.g., 24-hour self-exclusion) or a particular time of the year like the run up to Christmas (e.g., one-month self-exclusion).

Overall, these results suggest that self-exclusion is not a tool for problem gamblers but more generally a tool for responsible gambling This is particularly important point to bear in mind for those agencies that currently accredit online gaming companies in relation to socially responsible practices and procedures. For instance, GamCare will not accredit online gaming companies unless there is a minimum 6-month online exclusion facility. The empirical evidence outlined above clearly shows that short-term self-exclusion options of less than six months are beneficial to online gamblers. Therefore, accreditation agencies need to base their recommendations about self-exclusion on empirical evidence and what is most useful to online gamblers.

Any online gaming company should allow gamblers the opportunity to self-exclude themselves from their gambling site for any period whether it is one day, one week, one month or one year. Compared to offline schemes, online self-exclusion is relatively easy to introduce, and should run for the period requested by the gambler and not an arbitrary limit set by an accreditation agency.

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

Further reading

Griffiths, M.D. (2012). Self-exclusion services for online gamblers: Are they about responsible gambling or problem gambling? World Online Gambling Law Report, 11(6), 9-10.

Griffiths, M.D., Wood, R.T.A. & Parke, J. (2009). Social responsibility tools in online gambling: A survey of attitudes and behaviour among Internet gamblers. CyberPsychology and Behavior, 12, 413-421.

Hayer, T. & Meyer, G. (2010). Internet self-exclusion: Characteristics of self-excluded gamblers and preliminary evidence for its effectiveness. International Journal of Mental Health and Addiction, 9, 296-307

International Gaming Research Unit (2007). The global online gambling report: An exploratory investigation into the attitudes and behaviours of internet casino and poker players. Report for eCOGRA (e-Commerce and Online Gaming Regulation and Assurance).

Ladouceur, R., Jacques, C., Girous, I., Ferland, F., & LeBlond, J. (2000). Analysis of a casino’s self-exclusion program. Journal of Gambling Studies, 16, 453-460.

Ladouceur, R., Sylvain, C., Gosselin, P. (2007). Self-exclusion program: A longitudinal evaluation study. Journal of Gambling Studies, 23, 85-94.

O’Neil, M., Whetton, S., Doman, B., Herbert, M., Giannopolous, V., OíNeil, D., & Wordley, J. (2003). Part A – Evaluation of self-exclusion programs in Victoria and Part B – Summary of self-exclusion programs in Australian States and Territories. Melbourne: Gambling Research Panel.

Steinberg, M., & Velardo, W. (2002). Preliminary evaluation of a casino self-exclusion program. Paper presented at the Responsible Gambling Council of Ontarioís Discovery 2002 Conference, April 2002, Niagara Falls, Canada.

Tremblay, N., Boutin C. & Ladouceur, R. (2008). Improved self-exclusion program: Preliminary results. Journal of Gambling Studies, 24, 505–518

Williams, R.J., Simpson, R.I. and West, B.L. (2007). Prevention of problem gambling. In G. Smith, D. Hodgins & R. Williams (Eds.), Research and Measurement Issues in Gambling Studies. pp.399-435. New York: Elsevier.