An ongoing challenge for the development and implementation of responsible gambling (RG) programming is determining how to evaluate the program’s effectiveness. Moreover, RG strategies are often multi-faceted and target a diverse array of players. As such, any determination of effectiveness necessitates a means to assess what is working well, what needs attention, and whether player segmentation is required.
Typically, evaluating an RG strategy has been undertaken in three ways:
Assessing behaviors among players experiencing problems, or measuring the rate of problem gambling (PG) in a population: PG rates are typically very low (0.1 to 5.8 percent of the general population). With such a low base-rate, the number of problem gamblers in any one sample may be low, which undermines the reliability of any findings. That is, drawing generalized conclusions from very small sample sizes of atypical players may be tenuous. Moreover, a focus on problem gamblers ignores the majority of players who may or may not be gambling responsibly, and how RG strategy may help them, or how responsible their playing behavior is.
Measuring the effectiveness of different RG features: There are many components to an RG strategy (e.g., player education, game design, player tools). Measuring each feature can be helpful, but it is time consuming and does not provide information about the effectiveness of the overall RG strategy. Also, because there is no standardized way to measure the effectiveness of an RG strategy, determining whether changes to that strategy help or hinder the extent to which players gamble responsibly is difficult, if not impossible.
Adherence to RG frameworks: Various organizations offer accreditation for meeting agreed upon RG standards (e.g., WLA, NASPL RG frameworks). These have been useful for ensuring that an RG strategy contains essential features. However, these frameworks do not tend to measure the effectiveness of those features or suggest how they might be improved.
Recently, a team of Canadian researchers developed an alternative approach to optimize RG strategy: focus on those in a gambling population that are not experiencing problems (they term this group “positive players”) and identify what it is that they have in common as a basis for developing effective RG programming.
Dr. Wood and his colleagues, Drs. Wohl, Tabri and Philander, conducted an extensive 3-part research project in British Columbia, which resulted in the development of the Positive Play Scale (PPS). The PPS is the first validated scale that reliably defines and assesses the extent to which a consumer base has positive beliefs about gambling and gambles in a positive manner. Critically, among other things, the PPS can be used to measure the outcome of an RG strategy.
In 2017/18 Wood and colleagues, undertook a larger validation study with approximately 8,000 players from across Canada. The results of this study—funded by the Canadian Responsible Gambling Association—allows us to identify the extent to which players within and between Canadian jurisdictions engage in positive play.
In addition to the Canada national study, the PPS has now been used by four US state lotteries, a large nationwide US casino operator, three organizations in the UK and by Lotto New Zealand. Gathering all this data has not only helped to inform RG strategy in those jurisdictions, it has allowed the PPS team to gather useful knowledge on what works and what works best for different players. “The biggest revelation for us is that the one-size-fits-all approach to responsible gambling is far from optimal and can be greatly improved upon by considering the specific needs of different player segments” reports Dr. Wood. “For example, there are some big differences being measured according to the players age and the types of games they play. We are seeing that RG resources can be much more effectively applied when we know who needs to be targeted and in specific ways that meet those particular players’ needs.
The PPS is a 14-item scale, which is assesses 4 key components of positive play:
Personal responsibility: Items measure the extent to which players believe that they should take personal responsibility for their gambling behavior.
Gambling literacy: Items measure players’ beliefs understanding about the nature of gambling and the likelihood of winning.
Honesty and control: Items measure the extent to which players’ are open and honest about gambling with friends and family.
Pre-commitment: Items measure whether players determine how much money and time they want to gamble before they begin playing.
Typically, the PPS is administered to players in a short online survey together with items that assess gambling frequency and player demographics. Data analysis allows for the determination of whether a player-base scores high, medium, or low in each of the four positive play components. These scores can then provide benchmark data from which possible changes in positive play can be examined over time.
Put another way, should the the PPS be administered over several time points, it can be possible to observe if levels of positive play are improving, and in which specific areas. This is a useful way to measure the impact of various changes such as the introduction of new RG features (e.g., does a player education campaign increase gambling literacy scores?) or in response to the introduction of new gambling opportunities (e.g., a new game or gambling venue is launched).
Overall, the PPS aims to increase the focus and cost effectiveness of RG programming by providing an operator with a better understanding of which player segments are scoring higher, medium or lower, and in what specific ways. For example, if 18-24 year old electonic gaming machine (EGM) players are scoring low on pre-commitment, then messaging encouraging those players to reflect on and determine how much they want to spend before playing could be introduced. Such messages can be communicated in a number of ways, including via tailored pop-up messages on EGMs that resonate with younger players.
Understanding whether there is a compenent of positive play that needs attention may be a useful compass for impoving an RG strategy. However, to implement effective changes it is necessary to develop and test strategies that are tailored toward particualr player segements. In this sense, the PPS team have integrated the science of behavioural economics to gently nudge players in more positive directions. As noted by Dr. Wood, “gambling is an entertainment option and players are likely to respond better to nudges that are encouraging, rather than messages that are essentially a warning”. Examples of this includes reducing the “friction” of finding and engaging with RG features (e.g., provide online limit setting tools directly on the wallet loading page) and through communicating the social norms of other players (e.g., “95% of players consider how much they want to spend before they begin playing”). These gentle encouragements help players to gamble more responsibly without invoking the spectre of problem gambling that many players associate with traditional RG approaches, and which may be deemed irellevant to their own gambling beliefs and behaviors.
According to Dr. Wood, the research conducted this far on positive play has shown that efforts to improve the overall satisfaction levels of players through RG are not in vain. “When we conduct an evaulation of positive play, we also include an assessment of player satisfaction. Results suggest that players with high PPS scores (i.e., most responsible) are also those with the highest levels of player satisfaction”. Therefore it seems that not only does an effective RG strategy minimize harms for some players it is also associated with more satisfied customers.