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
Posted by drmarkgriffiths
In recent years, online gambling has become a more common leisure time activity. Research around the world suggests around 8-16% of adults have gambled online during the past year. Research has also demonstrated that there are a number of situational and structural characteristics that make online gambling potentially risky for susceptible and vulnerable individuals. Such factors include increased accessibility, affordability, anonymity and specific structural features of online games such as high event frequency. In addition, some forms of online gambling may be more problematic than others (e.g., online poker, online casino games).
A number of scientific studies have also shown that there are typically more problematic gamblers among those that gamble on the internet compared to those that only gamble in land-based venues. However, problem gambling severity is associated with overall engagement and that when the volume of gambling is controlled for, Internet gambling is not predictive of problems. Furthermore, most online gamblers are also offline gamblers and gamble on many different activities and across different gambling platforms.
Given the increasing number of people gambling online and issues surrounding problem gambling, many of the more socially responsible gambling companies around the world have started to use responsible gambling tools to help their clientele gamble more safely (such as the option to set time and money spending limits or to temporarily self-exclude from gambling for a day, week, month, or longer). In fact, one of our own studies recently demonstrated that the use of both time and money spending limits are most effective among gamblers that play most frequently, and that the effects are differential. For instance, time spending limits were most useful for online poker players and monetary spending limits were most useful for online casino players.
In addition, gamblers can now access and/or are given general advice on healthy and responsible gambling, as well as information about common misbeliefs and erroneous perceptions concerning gambling. However, findings on the effectiveness of providing gamblers with information in correcting or changing erroneous beliefs have been mixed. Some outcomes support the display of information, while other studies have reported non-significant results.
Studies have also shown that the way information is presented can significantly influence behaviour and thinking. Several studies have investigated the effects of interactive versus static pop-up messages during gambling sessions. Static messages do not appear to be effective, whereas interactive pop-up messages and animated information have been shown to change both irrational belief patterns and behaviour of gamblers. It has also been suggested that informational warning signs should promote the application of self-appraisal and self-regulation skills rather than the simple provision of information.
In one of our more recent studies, we investigated the effect of a pop-up message that appeared after 1,000 consecutive online slot machine games had been played during a single gambling session using behavioural tracking data. Our study analysed 400,000 gambling sessions (200,000 sessions before the pop-up had been introduced and 200,000 after the pop-up had been introduced). We found that the pop-up message had a limited effect on a small percentage of players. Although the study reported nine times as many gamblers stopped after 1000 consecutive plays compared to those gamblers before the introduction of the pop-up message, the number of gamblers that actually stopped after viewing the pop-up message was less than 1%.
In a follow-up study, we investigated the effects of normative and self-appraisal feedback in a slot machine pop-up message compared to a simple (non-enhanced) pop-up message. The study compared two representative random samples of 800,000 gambling sessions (i.e., 1.6 million sessions in total) across two conditions (i.e., simple pop-up message versus an enhanced pop-up message). The results indicated that the additional normative and self-appraisal content doubled the number of gamblers who stopped playing after they received the enhanced pop-up message (1.39%) compared to the simple pop-up message (0.67%). Like our previous study, the findings suggested that pop-up messages influence only a small number of gamblers to cease long playing sessions but that enhanced messages are slightly more effective in helping gamblers to stop playing within-session. Our two studies evaluating pop-up messages are the only published studies that examine the impact of messaging on actual gamblers in a real world online gambling environment.
In order to make individuals gamble more responsibly using behavioural tracking data, we believe that player feedback should also be presented in a motivational way. In practical terms, this means presenting messages in a non-judgmental way alongside normative data so that gamblers can evaluate their actions compared to other like-minded individuals. One of our most recent studies examined personalised feedback and information given to players during real world gambling sessions. We hypothesized that gamblers receiving tailored feedback about their online gambling behaviour would be more likely to change their behaviour (as measured by the amount of time and money spent) compared to those who did not receive tailored feedback.
We were given access to the behavioural tracking data of 1,358 gamblers at a European online gambling website that had voluntarily signed up to a behavioural feedback system that we developed (called mentor) that is offered to all customers on the website. The system is an opt-in system (i.e., gamblers can voluntarily choose to use it and the system is not mandatory). Once gamblers have enrolled to use the system, they can retrieve detailed visual and numerical feedback about their gambling behaviour via a button on the website. Player feedback is displayed in a number of ways (numerical, graphical, and textual) and provides information about wins and losses, playing duration, number of playing days, and games played. The system can also display personal gambling behaviour over time. For instance, Figure 1 shows the playing time information for a hypothetical player in the form of a graph over time.
At the top of the screen, players receive information about playing time over the previous 4-week and 24-week period. The white line in Figure 1 indicates that the player shows an upward trend and is steadily increasing the amount of time spent gambling. During the previous 4-week period, the player spent 25.75 hours gambling online. The upper line in Figure 1 is the average playing time for all other comparable online players (depending upon what types of game are typically played) and provides the gambler both normative and comparative feedback. Such feedback has been emphasized as an important aspect in facilitating behavioural change. Players are either assigned to ‘lottery’ type players or ‘casino’ type players based on their playing patterns.
Of the daily active players, 10% (n=1,358) opted into the system. Players could opt-in via a clearly visible button on the post-login website page which appeared immediately after they logged into their account. The personalised information appeared in a new pop-up window. This typically led to a break in play, as gamblers who viewed the information are unlikely to play and view information simultaneously. The system tracks those players who sign up and therefore the opt-in date is known and can also be used for analytical purposes.
All the visual, numerical, and textual information can be accessed by the gambler via a user-friendly on-screen dashboard. Responsiveness means that interactive content automatically adapts to technical environments. The player front end thus looks similar on different devices such as desktops, laptops, mobile phones, or tablets and also across different browsers and operating systems such as Windows, Android or iOS.
We investigated whether players’ behaviour changed after they have registered for the mentor system and saw the personalised feedback for the first time. We then compared their gambling behaviour with over 15,000 online gamblers displaying the same types of gambling behaviour (i.e., matched controls). Our results indicated that the personalised feedback system achieved the hypothesised effect and that the time and money spent gambling was significantly reduced compared to the online gambler control group that did not utilize the mentor system. The results suggest that responsible gambling tools such as mentor may help the clientele of gambling companies gamble more responsibly, and may be of help those who gamble excessively.
To our knowledge, this study was the first real world study investigating the effects of behavioural feedback on actual gambling behaviour within a real online gambling website. However, there were a number of limitations. For instance, all of the players in the target population had voluntarily registered to use the mentor system and were therefore not selected randomly from the population of players (but we tried to overcome this by using a control group of matched pairs). In addition, the reliability of our findings is limited because our data were only collected from one online gambling environment. It may also the case that players who voluntarily signed up to receive personalised messages about their gambling were different in other ways from controls (i.e., gamblers who voluntarily signed up to receive personalised messages may have already been interested in reducing their gambling and would be likely to gamble less).
Another limitation is that we did not know whether any of the gamblers who voluntarily opted to use the mentor system were problem gamblers. Therefore we do not know whether the system captures gamblers most in need of such interventions. Based on the findings, one explanation may be that the tool may simply be curtailing gambling in those who already play responsibly. Although our study was performed in a real world setting utilising objective behavioural data, it is limited because the motivations and thoughts of the players were unknown and can only be inferred.
Online gambling operators have the technical capabilities to introduce behavioural feedback systems such as the one we described in our paper, and our findings suggest that a system like mentor can help players limit the amount of time and money spent gambling can be achieved. However, the findings are preliminary and future research should focus on investigating at which point in time players should receive personalised messages to optimize behavioural change.
Dr Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Auer, M. & Griffiths, M. D. (2013). Voluntary limit setting and player choice in most intense online gamblers: An empirical study of gambling behaviour. Journal of Gambling Studies, 29, 647-660.
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). Testing normative and self-appraisal feedback in an online slot-machine pop-up message in a real-world setting. Frontiers in Psychology, 6, 339. doi: 10.3389/fpsyg.2015.00339.
Auer, M. & Griffiths, M. D. (2015). The use of personalized behavioral feedback for problematic online gamblers: An empirical study. Frontiers in Psychology, 6, 1406. doi: 10.3389/fpsyg.2015.01406.
Auer, M. & Griffiths, M.D. (2016). Personalized behavioral feedback for online gamblers: A real world empirical study. Frontiers in Psychology, 7, 1875. doi: 10.3389/fpsyg.2016.01875.
Auer, M., Littler, A. & Griffiths, M.D. (2015). Legal aspects of responsible gaming pre-commitment and personal feedback initiatives. Gaming Law Review and Economics, 6, 444-456.
Auer, M., Malischnig, D. & Griffiths, M.D. (2014). Is ‘pop-up’ messaging in online slot machine gambling effective? An empirical research note. Journal of Gambling Issues, 29, 1-10.
Posted in Addiction, Compulsion, Cyberpsychology, Gambling, Gambling addiction, Games, I.T., Internet gambling, Online addictions, Online gambling, Poker, Problem gamblng, Psychology, Social responsibility, Technology
Tags: Gambling, Gambling addiction, Gambling feedback, Mentor (RG tool), Online betting, Online casino, Online poker, Personalised feedback, Problem gambling, Responsible gambling, Responsible gambling tools, Social responsibility in gambling