Posted by drmarkgriffiths
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.
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
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
Tags: Gambling, Harm minimisation in gambling, Personalised feedback, Problem gambling, Problem gambling proxy measures, Responsible gambling, Self-exclusion, Social Responsibility, Stages of change model, Voluntary self-exclusion