The Effect of Mandatory Play Breaks on Subsequent Gambling Behavior Among Norwegian Online Sports Betting, Slots and Bingo Players: A Large-scale Real World Study

In order to protect gamblers, gambling operators have introduced a wide range of responsible gambling (RG) tools. Mandatory play breaks (i.e., forced termination of a gambling session) and personalized feedback about the gambling expenditure are two RG tools that are frequently used. While the motivation behind mandatory play breaks is simple (i.e., gambling operators expect gamblers to reduce their gambling significantly as a result of an enforced break in play), empirical evidence supporting the efficacy of the mandatory breaks is still limited. The present study comprised a real-world experiment with the clientele of Norwegian gambling operator Norsk Tipping. On the Norsk Tipping gambling website, which offers slots, bingo and sports-betting, forced termination occurs if gamblers have played continuously for a one-hour period. The study tested the effect of different lengths of mandatory play breaks (90 s, 5 min, 15 min) on subsequent gambling behavior, as well as the effect of combined personalized feedback concerning money wagered, won, and net win/loss. In total 21,129 online players (61% male; mean age = 47.4 years) experienced at least one play break between April 17 and May 21 (2020) with 156,989 mandatory play breaks in total. Results indicated that a 15-min mandatory play break led to a disproportionately longer voluntary play pause compared to 5-min and 90-s mandatory play breaks. Personalized feedback appeared to have no additional effect on subsequent gambling and none of the mandatory play breaks appeared to affect the increase or decrease in money wagered once players started to gamble again.

Socio-Demographic Factors, Gambling Behaviour, and the Level of Gambling Expenditure: A Population-Based Study

The aim of this study was to examine the relationship between socio-demographic factors, gambling behaviour, and the level of gambling expenditure. The data were drawn from the population-based Gambling Harms Survey 2016 and 2017 conducted in Finland. The data were linked to register-based variables. Past-year gamblers were included (Wave 1; n = 5 805, both Waves; n = 2 165). The study showed that of the 4.2 % of gamblers that produced 50.0 % of the total GE in 2016, 33.1 % of the GE was produced by those with a gambling problem and 43.3 % by those with at-risk gambling pattern. Compared to gamblers in the lowest GE group, those in the highest GE group were more likely to be men, aged 25 or older, with upper secondary education, have a high income, be on disability pension or sickness allowance, be frequent gamblers, gambling at least six game types, and showing at-risk and problem gambling patterns. Cumulative weekly GE by income tertiles remained fairly stable between the years. The results suggest that GE is highly concentrated. Among the small group of high-intensity consumers, the majority of the revenue comes from at-risk and problem gambling. Participants in the low GE group differ from those in the intermediate and high GE groups in terms of socio-demographics and gambling behaviour.

A scoping review of hard systems and tools that restrict money and cash for gambling

BackgroundGamblers engage in a range of “soft” financial options to limit access to money or cash for gambling (e.g., family looks after cash). Such barriers are easily overturned, resulting in a demand for financial systems and tools that offer “hard” restrictions on access to money and cash in a gambling context. The aim of this scoping review was to determine the attitudes and preferences of gamblers and their families on systems or tools to restrict access to money and cash, as well as the effectiveness of systems and tools that can be used to accomplish that goal.MethodsA systematic search of articles related to financial restrictions and gambling was conducted. Eligibility criteria included samples of gamblers or affected others and interventions targeted at money or cash restrictions in a gambling context. Soft financial barriers such as family involvement were excluded, as were limit-setting systems which focused on gambling expenditure in gambling venues.ResultsNine studies met the eligibility criteria, with three focused on financial systems (e.g., ban on credit betting) and six focused on removal of cash machines from gambling venues. The included literature was generally of low quality, with just two pre-post studies and seven cross-sectional or qualitative ones.ConclusionsThe included studies provided strong support for financial mechanisms to support gamblers and their families. Future studies need to involve multiple stakeholders to provide this type of support as well as to evaluate the holistic impact that such hard barriers can have on gambling and gambling-related harms.

$14.5-Billion Per Year and Counting: Canadian Gambling Statistics

Ask any gambler how much money they spend on gambling in a typical year and you’ll almost certainly see a quizzical look appear on their face. Individuals are frequently reluctant to disclose such information and those that do typically find it difficult to recall the specifics of their gambling spending. Gamblers who are willing and able to answer might also need some clarification since the question could be referring to either the cumulative amount of dollars gambled or the net dollar figure gambled after accounting for wins and losses[1]. But what if, instead of asking individual gamblers about their spending, one was attempting to determine gambling spending for the entire country of Canada including provinces and territories… are these figures even available? Are provincial and territorial gambling regulators and operators forthcoming with this information? The short answer is that, yes, it is indeed possible to determine a figure for Canada’s net commercial gambling revenue using available data[2]. In this article, I’ll describe my rationale for documenting available Canadian gambling statistics, methods employed, and challenges encountered. A selection of charts is interspersed throughout to illustrate key gambling statistics using examples from the Canadian Gambling Statistics (1970-2020) online database which was created to house these collected statistics and make them publicly accessible. [1] To learn about these intricacies, see Wood & Williams (2007) ‘How Much Money Do You Spend on Gambling?’ The Comparative Validity of Question Wordings Used to Assess Gambling Expenditure and Auer & Griffiths (2017) Self-Reported Losses Versus Actual Losses in Online Gambling: An Empirical Study. [2] Calculate at $14.51-billion in 2019 or about $500 per Canadian adult (18+ years of age) – for details, see Figure 1.

A speed-of-play limit reduces gambling expenditure in an online roulette game

UK online casino games are presently not subject to any limitations on stakes or speed-of-play. Two policy recommendations have been recently put forward: One proposal is to limit the maximum bet to £2, and another is to ensure that no online casino game can be played faster than its in-person equivalent. However, any policy proposal may be ineffective or have unintended consequences. This research experimentally investigated the speed-of-play proposal, in an experiment with 1,002 UK online roulette players, incentivized payouts, and £4 endowments. Participants played on a commercial online roulette game, which was slowed-down in one condition to enforce a speed-of-play limit of one spin every 60 seconds. The preregistered analysis plan showed no effect of the speed-of-play limit on participants’ choice to gamble at all, a marginal reduction in participants’ probability to gamble everything, and a credible reduction in the proportion of endowments gambled amongst participants who gambled some of their money. Expenditure reductions occurred via a credible reduction in the number of spins played that outweighed a marginal increase in per-spin bet sizes. This research shows how speed-of-play limits for online casino games may be effective in reducing gambling expenditure, and how the structural characteristics of online gambling games can be explored via ecologically-valid online experiments.

Gambling Self-Control Strategies: A Qualitative Analysis

There is limited research exploring the perceptions of people who gamble on the self-control strategies used to limit their gambling. This qualitative study examines self-control strategies used to limit money spent gambling, frequency of gambling, and time spent gambling. A total of 56 people who gamble (27 males and 29 females) participated in nine focus groups and five individual interviews in Montreal, Calgary, and Toronto (Canada). Self-control strategies used to limit their gambling expenditure were more common than frequency or time limiting strategies. Strategies to limit expenditure included: restricting access to money; keeping track of money allocated to gambling activities; and avoiding certain types of gambling activities. Various contextual factors were identified to influence those strategies, including social influences; winning or losing; using substances. Findings from this study emphasize the importance of communicating clear gambling limits to people who gamble, as well as the value of developing individual self-control strategies to limit frequency, time and money spent gambling.

The Development of Empirically Derived Australian Low-Risk Gambling Limits

This study derived a set of Australian low-risk gambling limits and explored the relative and absolute risk associated with exceeding these limits. Secondary analysis of population-representative Tasmanian and Australian Capital Territory (ACT) cross-sectional (11,597 respondents) and longitudinal studies (2027 respondents) was conducted. Balancing sensitivity and specificity, the limits were: gambling frequency of 20–30 times per year; gambling expenditure of AUD $380–$615 per year (USD $240–$388 per year); gambling expenditure comprising 0.83–1.68% of gross personal income; and two types of gambling activities per year. All limits, except number of activities, predicted subsequent harm, with limits related to gambling expenditure consistently the best-performing. Exceeding the limits generally conferred a higher degree of relative and absolute risk, with gamblers exceeding the limits being 3–20 times more likely to experience harm than those who do not, and having a 5–17% risk of experiencing harm. Only 7–12% of gamblers exceeding the limits actually experienced harm. Gambling consumption lower than the limits also conferred a considerable amount of harm. Using a relative risk method, this study derived similar limits from disparate Australian states and territories. These limits can serve as working guidelines for the consideration of researchers, clinicians, and policy makers, but need to be subject to further rigorous empirical investigation.