The objective of this study was to evaluate the effectiveness of an exclusion in reducing gambling participation (frequency, duration, expenditure on gambling), using both an experimental and a control group, and differentiating gambling behavior by game type. A secondary objective was to assess the effect of exclusion upon the severity of gambling problems. Regarding the characteristics of the excluded gamblers, no significant discrepancies can be reported in comparison with other studies. In terms of gender, the percentage of males was slightly higher among excluded gamblers. The average age of the excluded gamblers was 33.7 years (median: 30 years). This is slightly lower than the age range found in other studies, which report an average exclusion age in the early or mid-forties (Kotter et al.,
2018). 82.6% of the excluded gamblers were employed. This result is congruent with other studies. For instance, one review reports that the majority of self-excluders (73-90%) were either in full-time or part-time employment (Motka et al.,
2018). 67.5% of the excluded respondents stated that they were of Swiss nationality. The actual proportion of Swiss citizens within the general population, however, may be somewhat lower (Lischer et al.,
2014). In line with a recent review (Drawson et al.,
2017), this study found that improvements related to a decrease in gambling frequency, duration and expenditure were all observed and maintained 12 months later, among the excluded gamblers. However, gambling despite exclusion was still relatively common. Due to entry controls, gambling in land-based casinos was almost non-existent among excluded gamblers. In the online sector, some gamblers bypass the registration controls that have been put in place for licensed online gambling. Overall, however, participation in licensed online games also fell significantly. With respect to online lottery and sports betting, game participation decreased less markedly, however, the interaction of gambler type and time of survey is still significant. The greatest levels of exclusion circumvention were seen in unlicensed online gambling. This observation has also been found in other studies (Håkansson & Widinghoff,
2020). 29.3% of the excluded gamblers continued to circumvent exclusion by gambling through unlicensed online providers. Interestingly, only a few excluded gamblers reported that they circumvented the ban in foreign casinos and gambling arcades. These results differ from previous studies, which found that some of the excluded gamblers continued to gamble abroad. The deviation may be due to methodological reasons: for example, in a previous study, transcripts of the exclusion lifting interviews were evaluated (Lischer & Schwarz,
2018). However, the extent to which gamblers circumvented their exclusions also becomes particularly apparent when one considers the monthly expenditures of the excluded individuals for gambling, which in some cases were still considerable in the third wave of the survey. For example, 21.2% of the excluded gamblers still reported gambling expenditures between 1,000 and 2,499 Swiss Francs in the third survey wave. Overall, 12.1% percent of excluded gamblers stopped gambling altogether. This result is lower than the value from a previous study, in which 20.5% of those excluded ceased all gambling activities (Kotter et al.,
2017). However, from early on, it was pointed out that exclusion is an effective measure for individuals who have difficulty controlling their gambling behavior, and thus exclusion does not necessarily imply complete abstinence (Townshend,
2007).
According to the SOGS-R, 48.3% of the excluded respondents met the criteria for pathological gambling, 43,7% were considered at-risk gamblers and 8.0% reported having no gambling problems. This score is lower than that reported in previous studies, which have found that individuals who were self-excluded from land-based gambling were between 51% and 95% classified as persons experiencing gambling-related problems (Hayer & Mayer,
2011; Kotter
2017; Ladouceur
2000;
2007; Nelson
2010). It is likely that the lower value in this study is due to preventive measures such as early detection processes applied by land-based and online casinos, but also by lotteries. Across the three survey waves, the median of the SOGS-R score of the excluded gamblers decreased from 5 (T1), to 4 (T2) and finally to 1 (T3). The SOGS-R score of the so-called short-term excluded gamblers also decreased, but less markedly. These findings are consistent with a previous study, which found that those who were excluded for only six months reported a significantly smaller reduction in Problem Gambling Severity Index (PGSI) scores compared with those who were excluded for longer than six months (McCormick et al.,
2018). In the context of the SOGS-R, the other striking aspects are as follows; that at the time of the first wave of the survey, 10.8% of non-excluded gamblers were classified as probable pathological gamblers. Overall, the mean scores across the three measurement points are 1.26 and 1.27, respectively, and the medians are 0 and 1 (range 0–10). Thus, there seem to be a few outliers in the group of non-excluded gamblers. Either the non-excluded gamblers with a high SOGS-R score had not yet been detected within the early detection process, or they had been able to prove by means of an affordability check that they did not have any debts and had sufficient financial means to participate in the game. Overall, it can be stated that excluded gamblers differed significantly from non-excluded gamblers in terms of problem gambling behavior. The preventive measures, and the early detection processes seem thus to be proving their worth.
Finally, it should be emphasized that in addition to the use of the preventive measure of exclusion, there are other factors that may have an influence on gambling behavior, such as the uptake of professional help. At the second measurement time point T2, a total of
n = 23 individuals who had a SOGS-R score of
\(\ge\)1, stated, to have sought help in the past six months. Of these,
n = 14 individuals were excluded. A statistical analysis with repeated measures ANOVA revealed that among these gamblers, however, help-seeking had no significant effect on gambling behavior (duration, frequency, expenditure on gambling). A study with the same sample, however, found that exclusion has indeed a motivating effect on help-seeking (Lischer et al.,
2023).
Limitations
Several limitations that may have influenced the results should be identified. Firstly, there may have been a selection bias. For example, the proportion of gamblers with high incomes is likely to be disproportionate. Also, the required sample size of excluded gamblers could not be achieved due to limitations in recruitment. However, an analysis of the achieved effect sizes (Cohen’s
f) shows that an effect worth reporting can also be obtained with a smaller sample size. Namely, the effect sizes vary between medium and large for the ANOVA with repeated measures of self-reported gambling behavior (frequency and duration) for the leading game types (
Casino land-based and
License Online Games). Furthermore, since there were gamblers who were only excluded for one or two waves or whose exclusion was revoked at least once, the gambling behavior of these participants was considered separately (see Fig.
1). The gambling behavior, as well as the SOGS-R score in this group varied, sometimes considerably. Given that the sample sizes of these individual variations (
n = exclusions provoked per wave) were too small for a statistical analysis, the different variations were considered in a combined manner (short-term excluded). This procedure allowed a conclusive comparison between the gamblers who were excluded over all measurement time points with those who were excluded for a short term. Nevertheless, the results on the influence of short-term exclusions on gambling behavior must be interpreted with caution. In Addition, it is likely that the Covid pandemic influenced the results. During the survey period, land-based casinos were closed from March to June 2020 and from November 2020 to January 2021. This was taken into account by asking gamblers to consider only the time outside the lockdown in terms of game participation. Finally, as recruitment of respondents took place in the land-based and online casino environment, which may be one reason that individuals participating in online lotteries and sports betting were underrepresented in the sample.