Consumer perspectives of a multi-venue gambling self-exclusion program: A qualitative process analysis

Available online – from the Journal of Gambling Studies

Abstract: Self-exclusion is an important harm minimization strategy implemented by gambling operators to restrict a problem gambler’s access to gambling opportunities. Aspects of self-exclusion, including low uptake and non-compliance, limit the effectiveness of programs. Research that considers the consumer perspective is needed to enhance the perceived utility of self-exclusion in the target audience. Twenty interviews were conducted with current (n = 13) and former (n = 7) participants of a multi-venue self-exclusion program for land-based gaming machine venues in New South Wales, Australia. Participants were asked open-ended questions about their experiences and opinions of the program, including its strengths and weaknesses, and suggested improvements for future consumers. Overall, participants found self-exclusion beneficial. However, several shortcomings of the program were expressed, including lack of available public information and overly complicated registration processes. Participants lacked confidence in venues’ willingness and ability to identify non-compliant gamblers and highlighted the need for vastly improved detection systems. The quality of interactions with venue staff in relation to self-exclusion were mixed; counsellor support, however, was perceived as important from beginning to end of a self-exclusion period. Results suggest that gambling operators should increase marketing efforts to promote the availability and benefits of self-exclusion. Investigation of strategies to streamline registration processes and to augment detection systems with new technologies was supported. Venue staff may benefit from training in appropriate self-exclusion facilitation procedures. Gambling operators should aim to foster strong links between self-exclusion programs and professional gambling counselling services. Access full article

Reference: Pickering, D., Nong, Z., Gainsbury, S.M. & Blaszczynski, A. (2019). Consumer perspectives of a multi-venue gambling self-exclusion program: A qualitative process analysis. Journal of Gambling Studies, 41.


The Relationship Between Exclusions from Gambling Arcades and Accessibility: Evidence from a Newly Introduced Exclusion Program in Hesse, Germany [subscription access article]

Strohäker, T. & Becker, T. (2018). Journal of Gambling Studies:

Abstract: An exclusion system for gambling arcades has been introduced recently in the state of Hesse. The aim of this paper is to identify significant predictors that are useful in explaining the variation of exclusions between different Hessian communities. Next to socio-demographic factors, we control for three different accessibility variables in two models: the number of electronic gambling machines (EGMs) in model I, and the number of locations and density of gambling machines at a location in model II. We disentangle the association between EGMs and exclusions of model I into a location and a clustering effect. Considering the socio-demographic variables, the explanatory power of our cross-sectional models is rather low. Only the age group of the 30–39 years old and those who are not in a partnership (in model I) yield significant results. As self-exclusion systems reduce availability for the group of vulnerable players, this analysis provides evidence for the assumption that the two groups—pathological gamblers and vulnerable players—seem to have little overlap concerning sociodemographic characteristics. The accessibility variables, on the other hand, turn out to be significantly associated with the number of exclusions. All three of them are statistically significant and their association is positive. The results of model II show that the location effect is more pronounced then the clustering effect of EGMs, i.e. the effect of an additional single-licensed arcade on the number of exclusions is stronger than the increase in the number of license at one location. Article details and access options

Predicting online gambling self-exclusion: an analysis of the performance of supervised machine learning models

As gambling operators become increasingly sophisticated in their analysis of individual gambling behaviour, this study evaluates the potential for using machine learning techniques to identify individuals who used self-exclusion tools out of a sample of 845 online gamblers, based on analysing trends in their gambling behaviour. Being able to identify other gamblers whose behaviour is similar to those who decided to use self-exclusion tools could, for instance, be used to share responsible gaming messages or other information that aids self-aware gambling and reduces the risk of adverse outcomes. However, operators need to understand how accurate models can be and which techniques work well. The purpose of the article is to identify the most accurate technique out of four highly diverse techniques and to discuss how to deal analytically and practically with a rare event like self-exclusion, which was used by fewer than 1% of gamblers in our data-set. We conclude that balanced training data-sets are necessary for creating effective models and that, on our data-set, the most effective method is the random forest technique which achieves an accuracy improvement of 35 percentage points versus baseline estimates.