The UK Online Gambling ‘Self-Exclusion Puzzle’: Putting the Pieces Together
Author: Patroklos Androulakis-Korakakis, Research Officer, Gamban
Highlighting the Importance of a Multi-Layered Approach to Self-Exclusion
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Aims & Objectives
- To better define online gambling self-exclusion in the UK
- To briefly examine each piece of the self-exclusion puzzle, weighing up strengths and
- weaknesses in an attempt to highlight the importance of a multi-layered approach to self-exclusion from online gambling
- To briefly review the evidence on the effectiveness of self-exclusion tools and strategies
Despite some of the article’s terminology resembling the terminology used in academic texts (eg: systematic reviews etc), this is not an academic document nor does it aim to be. This is an article expressing some of Gamban’s views on self-exclusion while briefly looking at some of the available evidence to highlight the need for more data around online gambling blocking software.
Overview: Access, time and money
Online gambling is more accessible than ever especially given the increase in computer, smartphone and tablet use over the past decade. A report published by iovation found that online gambling transactions have increased more than tenfold from 6% in 2012 to 70% in 2018 (iovation, 2019). In their report, iovation stated that “to attract and retain players, a mobile-first approach is needed” and emphasized on how a good mobile experience can make a significant difference revenue-wise for an online operator. They used the example of the operator DraftKings, an operator that demonstrated the effectiveness of mobile gambling with over 90% activity through their mobile app, averaging 53,000 bets each day (iovation, 2019). Mobile gambling apps are widely available for the majority of mobile devices and mobile operating systems allowing users to register, deposit and place bets without requiring computer access. In a semi-structured interview study, Drakeford & Hudson Smith (2015) found that 3mobile gambling was more accessible than both desktop and offline gambling, highlighting the importance and growth rate of mobile gambling as a significant “if not separate form of internet gambling”.
Online gambling activity has grown significantly over the past decade with operators’ yield from online and mobile gambling increasing from £1bn to £5.3bn in the 10 years leading up to 2019 (Financial Times, 2020).
In the UK, active online banking accounts have doubled from approximately 16m in 2008 to over 30m in 2019 (UK Gambling Commission, 2019).
In a research overview paper by Gainsbury (2015) titled “Online Gambling Addiction: the Relationship Between Internet Gambling and Disordered Gambling”, one of the author’s conclusions was despite Internet Gambling being under-researched, “use of Internet gambling is more common among highly involved gamblers, and for some Internet gamblers, this medium appears to significantly contribute to gambling problems” (Gainsbury 2015). As mentioned above, since the publication of the study by Gainsbury (2015), online gambling has not only become more popular but also more accessible as smartphones and tablets are being used more than ever before. A study by Kim et al (2017) examined the motivations of young adults to transition from online social network casino games to online gambling and found that social games were often used as “avenues” to online gambling websites. Peer pressure, sign-up bonuses, advertisements and inflated payout rates were all factors that led to young adults migrating from social casino games towards online gambling. The results of the study by Kim et al (2017) further highlight how easily accessible online gambling is and how vulnerable populations may find themselves on online gambling platforms “by accident”. Hing et al (2017) examined the relationship between gambling promotions and gambling severity amongst Australian Internet sports bettors and found that “young male Internet sports bettors are especially vulnerable to gambling problems, particularly if they hold positive attitudes to gambling sponsors who embed promotions into sports broadcasts and to the promotional techniques they use and this heightens the risk that alluring messages contribute to excessive gambling. As problem gambling severity increased, so too did the recognition that these promotions have impacted negatively on their sports betting behaviour”. Aside from the above factors, online gambling communities, like Facebook groups, are also a significant predictor for excessive gambling in 15-25-year-old at-risk and pathological gamblers (Sirola et al., 2018). Choliz (2015) investigated the effect of legalisation of online gambling in Spain and found that there was a significant increase in young pathological gamblers post legalisation. The potential increase in gambling activity observed in young adults is something numerous researchers 4 have encouraged further research as well as protective measures to be developed (Choliz, 2015).
Like land-based gamblers, online gamblers attempting to reduce their online gambling activity have the option to self-exclude. Self-exclusion is one of the main, if not the main, tools that make up “safer gambling” (BeGambleAware, 2020). Gamblers have the option to self-exclude for one website, or both online websites and offline venues (i.e, casino venues) (Luquiens et al., 2018). Aside from self-excluding independently from each gambling website, online gamblers also have the option to sign-up to multi-operator self-exclusion schemes that allow them to self-exclude from multiple websites with a single-sign up. For example, in the UK a problem gambler wishing to go down the route of self-exclusion can sign-up to GAMSTOP, provide their details be excluded from “gambling with online gambling companies licensed in Great Britain” (GAMSTOP, 2020). Being part of the GAMSTOP self-exclusion scheme will become a licensing condition as of April 2020 and any gambling operator that wishes to operate within the UK will be required to work with GAMSTOP. In the UK, searching for “self-exclusion from online gambling” points the users at different responsible gambling websites directing them towards GAMSTOP.
This is where one of the main issues with the currently available guidelines for self-exclusion lies. Self-excluding from a single website or even multiple websites through a self-exclusion scheme like GAMSTOP comes with a few limitations that unfortunately fail the reality test of problem gambling. Allow me to note that the idea behind GAMSTOP is not completely flawed and in a theory should be the way forward. Unfortunately at the moment, a self-exclusion scheme like GAMSTOP cannot be regarded as a complete approach to self-exclusion from online gambling but rather as another piece of the self-exclusion puzzle. Self-excluding from an operator comes with the obvious limitation of being able to simply sign-up on a different online gambling website. Using a service like GAMSTOP may allow users to self-exclude from multiple websites but that will only cover the operators that have agreed to sign-up to schemes like GAMSTOP. As mentioned above, in the UK any operator that wants to operate within the UK must sign-up to the GAMSTOP self-exclusion scheme from April 2020. GAMSTOP works by using the user’s personal details to prevent them from signing up to gambling websites. An individual can sign-up to a gambling website with the help of a friend/family member that has not self-excluded allowing them to gamble again. Aside from the above, there are a few gambling websites that have not agreed to join the GAMSTOP program, allowing self-excluded users to still gamble on gambling websites licensed in Great Britain. People are taking advantage of 5 the above and have even created websites dedicated to providing users with access to non-GAMSTOP registered gambling websites.
Aside from regulated websites that have decided to not join the GAMSTOP, something that will not be an option following April 2020, program, there are thousands of unregulated gambling websites and social games that are accessible at all times regardless of self-excluding through GAMSTOP or not. Now, despite the limitations presented, a service like GAMSTOP is still a very useful and necessary piece of the self-exclusion puzzle. Ensuring that a person will not be able to use their personal information to register on some of the major licensed online gambling websites is one of the necessary protection layers to ensure the process of self-exclusion is as effective as possible.
Notice the words “pieces” and “puzzle”. Self-exclusion from online gambling is a multi-layered process that cannot be fully successful unless all the “pieces” are put together. The other two pieces are transaction blocking and blocking software. The self-exclusion puzzle aims to create a complete approach towards online gambling self-exclusion with its main aim being to provide gamblers with a multitude of protection layers making it harder to relapse after selecting to self-exclude. Figure 1 below shows what the self-exclusion puzzle should ideally look like.
Figure 1 – The Online Gambling Self-Exclusion Puzzle
Transaction blocking is a “toggle-on” option offered by many banks, blocking gambling-related transactions. In certain countries, aside from the toggle-on option, transactions to unlicensed online gambling operators are blocked – eg: in Norway (Gainsbury, 2012). Despite the potential for transaction blocking to further increase player protection, most online gambling operators accept other forms of payment besides credit/debit cards (eg: PayPal), allowing users to easily bypass any transaction blocking. Gainsbury (2012) also noted that online gambling transactions are often difficult to identify and can sometimes be “masked by gambling providers to avoid detection”. In the “Policy and Regulatory Options” chapter of the “Internet Gambling: Current Research Findings and Implications” book, Gainsbury (2012) also commented on how customers may use third-party payment methods to easily bypass transaction blocking. Similarly to self-exclusion schemes like GAMSTOP, transaction blocking alone is not enough to represent a complete approach to self-exclusion but still plays an important role as one of the key puzzle pieces acting as yet another layer of protection.
Finally, the other piece of the puzzle is blocking software. Blocking software prevents users from accessing gambling-related websites altogether. Blocking software, like gamban, completely prevents access to any websites, and in certain cases mobile applications, that are considered online gambling. Aside from traditional gambling websites, blocking software often also prevents access to content that is not widely considered gambling, ie: Skin gambling in online video games. Wardle (2019) explored the convergence of skin gambling and other Gambling among children. They found that 39% of children who engaged in skin betting in the span of a month had also gambled on other platforms. They also found that the gamblers that engaged in skin betting “had higher rates of at-risk problem gambling” than those who did not (Wardle, 2019). Wardle (2019) noted that “skin betting and gambling on other activities cluster together, especially where the medium underpinning the behaviours is the same”. The above example demonstrates how a more complete approach to self-exclusion, incorporating blocking software, may help prevent access to other platforms that are not officially considered gambling but can result in increased gambling related activity, especially in vulnerable populations.
For blocking software to be effective certain criteria must be met. Blocking software must be: cross-platform, effective in preventing access to most online gambling websites, non-intrusive, easy to install, affordable as well as relatively difficult to circumvent. It is also important to note that due to online gambling technology advancing at a fast pace, blocking software companies must be able to stay ahead of the curve and ensure that they are constantly adapting to ensure players are protected. Despite blocking software being a powerful piece of the self-exclusion puzzle it also comes with limitations that cannot be ignored. Aside from being able to bypass protection altogether, something that depends on the technical proficiency of the user and will always be a limitation, cross-platform blocking software can sometimes be less effective on certain platforms (eg: Apple mobile devices). Restrictions by certain operating systems as well as unexpected updates can sometimes cause issues with how gambling software functions requiring the software company to update their methodology to keep the user protected. Ensuring that the software is functioning as it is supposed to across both desktop and mobile platforms can be especially challenging especially since blocking methodology can sometimes require adapting to each specific platform. Nevertheless, blocking software may be effective in reducing gambling-related activity thus aiding in the process of self-exclusion.
“May”? How can a blocking software company be unsure of whether the type of software they produce is effective or not? Because at the moment, the only evidence available regarding the effectiveness of blocking software and online gambling prevention is reviews from our users, general user feedback and a non-peer reviewed report by GambleAware (Winning Moves-GambleAware, 2018). This brings us to the next points/questions: What scientific evidence do we currently have regarding self-exclusion from online gambling? Is there anything on blocking software? Has anyone directly investigated the effect of blocking software on online gambling-related activity? The above questions are of particular interest to us as they can potentially allow us to improve our software functionality as well as explore different methodological avenues for increasing its effectiveness. Thus, we tried to locate any available scientific evidence around online gambling blocking software while also looking at some of the available scientific evidence on online gambling self-exclusion as a whole.
We searched through PubMed, Google Scholar as well as through the reference lists of any online-gambling research articles and to our surprise found that currently, no studies have directly investigated blocking software and its effects on online gambling-related activity. PubMed and Google Scholar were searched using the following terms and Boolean operators: “online gambling” AND “software” OR “program”, “online gambling” AND “self-exclusion” or “exclusion”, “block” AND “online gambling”, “self-exclusion” AND “software” or “tools”. To ensure we did not miss any articles, PubMed searches were exported and imported on the Systematic Review management website Covidence.org, allowing us to better review all the available studies on self-exclusion from online gambling. From the 1014 articles reviewed, 8 peer-reviewed studies were deemed remotely appropriate and analysed further. A few non-peer reviewed articles and reports were also analysed given the very limited available evidence that we were able to locate around the subject area. The studies and articles that were deemed remotely appropriate, despite not directly assessing blocking software and its effectiveness on reducing gambling-related harm, can be found in Table 1. Table 1 also includes other nonacademic reports as well as peer-reviewed articles that were located during our searches and may be of interest to readers.
Table 1 – List of identified studies & possibly relevant documents
None of the above studies directly investigated blocking software and its effects on gambling activity or gambling behavior. Blocking software was only mentioned in the context of “concrete requirements for improvement in internet exclusion practices” (Hayer and Meyer, 2010). Hayer and Meyer (2010) mention how links to “software programs designed to prevent access to online gambling sites” should be promoted more as part of self-exclusion strategies. The only attempt at evaluating blocking software was done by Francis et al (2012) during a presentation at the Responsible Gambling Council Discovery Conference in 2012. What is interesting about the above is that Francis et al (2012) presented the different Governance Options for Collective Self-Exclusion assessing the following: a regulator-driven system, an operator-driven system, 10 a player-driven system, and computer blocking. The table, Table 2, adapted from Parke et al (2014), can be found below.
Table 2 - Governance Options for Collective Self-Exclusion
(Parke et al., 2014 adopted from Francis et al., 2012)
Blocking software scored the lowest among the proposed options, scoring 7/24 for the Functional Scope Potential criteria and 9 for the Adoption Potential criteria. Francis et al (2012) concluded that “player-driven and software blocking approaches were considered inferior due to significant limitations as identified in the table”. Parke et al (2014) added that if the criteria “simplicity” and “barriers to implementation” were considered then a plater-driven system could have potentially carried more weight especially if it “initiated a process which would eventually lead to a more robust approach in due course”. Blocking software has greatly evolved since 2012 and we hypothesise that it would score much higher, especially on the Functional Score Potential section, on the above table if it was re-evaluated. We present a hypothetical assessment / possible score range of our software Gamban based on the above criteria. Given the obvious bias of us evaluating our own software, we are completely open to an official evaluation by any given third-party based on the above, or any criteria.
With the advancements in blocking technology in the last 8 years, we hypothesise that our blocking software and the infrastructure behind would allow it to score much higher than presented by Francis et al (2012) on a grading list with the same or similar criteria. Regarding the Adoption Potential category and its criteria, it is difficult to effectively grade blocking software due to the multi-factorial nature of adoption and the degree to which it is heavily operator-dependent. At the moment, a plethora of operators as well as other organisations (eg: Lloyds Bank) offer Gamban free of charge for their respective user base. Making blocking software a licensing condition, as previously proposed by the UK Gambling Commission, would be an effective first step towards increasing its Adoption Potential score.
It is important to note that Francis et al (2012) was a conference presentation and not an actual paper published on a peer-reviewed Journal, further highlighting the absence of scientific evidence around blocking software and its effect on gambling-related activity.
In terms of non-scientific evidence, a report funded by GambleAware titled “Evaluating online blocking software” was prepared by a third-party organisation called “WinningMoves” and was published in 2018 (Winning Moves-GambleAware, 2018). Despite being the only report of its kind, it was published independently by GambleAware and not in a peer-reviewed Journal. Some of the report’s main aims were the following:
1.) Review the current literature around the effectiveness of blocking software and its influence on the participation of problem gamblers in remote gambling.
2.) Test different gambling blocking software and compare with general content-blocking software against 2417 websites associated with active Gambling Commission licences (on desktop-based operating systems).
3.) Interviews with stakeholders, “exploring the views and experiences of treatment providers, gambling operators, academics, and software developers regarding whether, how and in what circumstances blocking software was a useful tool in reducing gambling-related harm”. 12 stakeholders were interviewed.
4.) Survey/Interviews existing/potential users of blocking software to better understand their experience with blocking software as well as investigate its effectiveness in helping them Self-exclude.
The report found that blocking software appears to be generally effective in restricting access to online gambling and that it also managed to block 80-90% of unregulated/illegal gambling sites that were accessed during testing. Respondents to the survey and interviews reported that installing gambling blocking software was sometimes enough to prevent them from gambling online. The authors of the report also concluded that “The evaluation identified a number of instances that demonstrate software can be helpful in reducing the accessibility of gambling and, in doing so, play a role in reducing gambling-related harm. Benefits derived from the use of blocking software were evident in feedback from users and all types of stakeholders interviewed” (Winning Moves-GambleAware, 2018).
Despite not being published on a peer-review Journal and having certain methodological limitations, the above report acts as a useful pilot study for the possible effectiveness of blocking software in reducing gambling-related activity and therefore gambling-related harm.
Another potential piece of the self-exclusion puzzle is Internet Service Provider (ISP) level blocking. ISP providers offer parental-control services/toggle-on addons that sometimes block certain gambling-related websites. In certain countries (eg: Greece) ISPs block offshore gambling sites under government schemes. At the moment, blocking gambling-related activity on the ISP level, despite having great potential, has not been fully explored or attempted. ISP blocking could potentially become a key piece of the self-exclusion puzzle given that it collaborates with the self-exclusion schemes, banks as well as blocking software providers to ensure it can have a constantly updated list of gambling websites (legal and illegal).
When it comes to self-exclusion from online gambling regardless of blocking software or transaction blocking the evidence is also limited with only a few studies directly exploring the subject. Hayer and Meyer (2010) investigated self-excluded internet gamblers from the online gambling platform win2day.at. The 20 participants of the study were surveyed 1, 6 and 12 months after the beginning of the self-exclusion and found that temporary restriction of access to “one single online gambling site can indeed have favourable psycho-social effects”. The authors concluded that due to the limitations and the small sample size of the study, “the long-term effectiveness of self-exclusion in this sector can only be viewed as preliminary” (Hayer and Meyer, 2010). In a more recent study, Luquiens et al (2018) investigated the effect of self-exclusion in online poker gambling as compared to matched controls following the end of self-exclusion from poker website Winamax. They found that self-exclusion seemed to be efficient in the long term but concluded that the effects of self-exclusion on money spent needs to be further investigated among the more heavily involved gamblers (Luquiens et al., 2018). Motka et al (2018) performed a systematic review titled “Who uses self-exclusion to regulate problem gambling?”. They found that in order for the true potential of self-exclusion to be exploited, its acceptance and utilisation need to be increased and that self-exclusion must be used during the early stages of problematic gambling behaviour. They also concluded that “barriers to self-exclusion need to be reduced” (Motka et al., 2018). The proceeded to state, that the simplification of self-exclusion should include the ability to self-exclude from multiple venues/operators. Despite the few studies on the topic presented above, the overall evidence around self-exclusion from online gambling and its effectiveness remains limited and does not fully address the subject.
It is evident that self-exclusion from online gambling must be further researched especially in the context of the self-exclusion puzzle. As mentioned above, the self-exclusion puzzle is a concept that has the potential to provide online-gamblers with a more complete and robust approach to self-exclusion and thus potentially reduce gambling-related activity. This brief review aims to act as a “nudge” for future research around the “self-exclusion puzzle” and its components. It also aims to act as the first official “introduction” to the concept of the self-exclusion puzzle. As a company that makes online gambling blocking software, we understand that our software alone is not enough to provide a complete approach to self-exclusion from online gambling and wish to promote the concept of a combined approach towards online-gambling self-exclusion. Future research in blocking software will also help us better understand possible areas for improvement as well as provide useful insight on how effective our software is in different gambling populations (eg: habitual gamblers vs at-risk gamblers). It is also important for cross-platform research to take place to better understand how mobile gambling activity can be effectively reduced in the context of self-exclusion, as it is currently an area that is on the rise.
- Online gambling is growing exponentially
- Mobile gambling is also growing exponentially and in certain cases it makes up a significant percentage of the revenue of some online gambling operators
- Self-exclusion from online gambling is currently wrongfully presented as a one-component process with focus placed around self-exclusion schemes
- A self-exclusion scheme approach is an incomplete approach to self-exclusion and fails the “reality test” of problem gambling behaviour
- A multi-component approach, ie: the self-exclusion puzzle, is proposed as a more complete and robust approach to self-exclusion from online gambling
- Self-exclusion schemes, online gambling transaction blocking and online gambling blocking software are proposed as the main components of the self-exclusion puzzle
- There are currently no peer-reviewed studies examining the effect of blocking software and transaction blocking on reducing online gambling activity or their effect on online gambling self-exclusion
- The current available evidence around self-exclusion from online gambling is limited
- Research is needed around the concept of the self-exclusion puzzle as well as for each of its components
It is time that we adopt a complete approach towards online-gambling self-exclusion, time to start putting the pieces together!
BeGambleAware. 2020. Self Exclusion From Gambling - How To Self Exclude | Begambleaware | Begambleaware. [online] Available at: <https://www.begambleaware.org/safer-gambling/howto-self-exclude/> [Accessed 10 March 2020].
Chóliz, M., 2015. The Challenge of Online Gambling: The Effect of Legalization on the Increase in Online Gambling Addiction. Journal of Gambling Studies, 32(2), pp.749-756.
Drakeford, B. and Hudson Smith, M., 2015. Mobile Gambling: Implications of Accessibility. Journal of Research Studies in Business & Management, 1, pp.3-28.
Financial Times. 2020. Online Gambling Spikes In Britain. [online] Available at: <https://www.ft.com/content/6ca1d9c9-9d13-49c6-96fd-38cd47bcaad2> [Accessed 7 March 2020].
Francis, M., 2012. Multi-Operator Self-Exclusion Theory, Evidence And Future Directions.
Gainsbury, S., 2012. Internet Gambling: Current Research Findings And Implications. 1st ed. NewYork: Springer-Verlag.
GAMSTOP. 2020. Gamstop - Gambling Self-Exclusion Scheme. [online] Available at: <https://www.gamstop.co.uk/> [Accessed 15 January 2020].
Hayer, T. and 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(3), pp.296-307.
Hing, N., Russell, A., Lamont, M. and Vitartas, P., 2017. Bet Anywhere, Anytime: An Analysis of Internet Sports Bettors’ Responses to Gambling Promotions During Sports Broadcasts by Problem Gambling Severity. Journal of Gambling Studies, 33(4), pp.1051-1065.
iovation, 2019. 2019 Iovation Gambling Industry Report. [online] iovation. Available at: <https://gambling.iovation.com/2019-iovation-gambling-industry-report> [Accessed 4 February 2020].
Kim, H., Wohl, M., Gupta, R. and Derevensky, J., 2017. Why do young adults gamble online? A qualitative study of motivations to transition from social casino games to online gambling. Asian Journal of Gambling Issues and Public Health, 7(1).
Luquiens, A., Vendryes, D., Aubin, H., Benyamina, A., Gaiffas, S. and Bacry, E., 2018. Description and assessment of trustability of motives for self-exclusion reported by online poker gamblers in a cohort using account-based gambling data. BMJ Open, 8(12), p.e022541.
Motka, F., Grüne, B., Sleczka, P., Braun, B., Örnberg, J. and Kraus, L., 2018. Who uses self-exclusion to regulate problem gambling? A systematic literature review. Journal of Behavioral Addictions, 7(4), pp.903-916.
Parke, J., Parke, A., Harris, A., Rigbye, J. and Blaszczysnki, A., 2014. Restricting Access: Self-Exclusion as a Gambling Harm Minimisation Measure in Great Britain. The Journal of Gambling Business and Economics, 8(3), pp.52-92.
Sirola, A., Kaakinen, M. and Oksanen, A., 2018. Excessive Gambling and Online Gambling Communities. Journal of Gambling Studies, 34(4), pp.1313-1325.
Wardle, H., 2019. The Same or Different? Convergence of Skin Gambling and Other Gambling Among Children. Journal of Gambling Studies, 35(4), pp.1109-1125.
Winning Moves-GambleAware, 2018. Evaluating Online Blocking Software. [online]
GambleAware. Available at: <https://about.gambleaware.org/media/1813/blocking-softwareevaluation-findings-report.pdf> [Accessed 13 January 2020].