Playscan 3 helps at-risk players to reduce their spending on gambling.
A previous evaluation determined that players found Playscan to be a useful tool (Griffiths, Wood & Parke, 2009), but a systematic investigation of whether the tool influences players’ gambling behaviours had yet to be conducted. To address this gap we, Dr Richard Wood from GamRes Limited, Canada and Dr Michael Wohl from Carleton University, Canada, undertook an independent evaluation study the previous version, Playscan 3.
Specifically, we set out to empirically test the hypothesis that ‘The gambling behavior of players who use Playscan, will show a significant observable change, following the presentation of a negative change in risk category (i.e. Green to Yellow or Yellow to Red). In other words, we tested the idea that using Playscan can help players maintain, or return to, less risky patterns of play.
How was the study conducted?
Player data was examined for 1558 Swedish Internet players (n = 1388 male; n = 170 female). More males were present in the sample due to the data being drawn from a population that had a predominance of online poker players. Poker is a game that has a higher proportion of male versus female players. Six hundred and ninety four Playscan subscribers were compared to the same number of non-Playscan subscribers. The two groups of players were matched in terms of age, gender, gambling intensity, types of games played and current Playscan risk rating.
All players in the study were rated by Playscan, but only Playscan subscribers received feedback about their playing behaviour. This meant that everything else being equal, any changes in behaviour following feedback from Playscan would suggest that it was having an impact.
What did the evaluation study conclude?
It was found that Playscan subscribers who were informed that their rating was ‘Yellow’ (at-risk for gambling problems) showed a significant reduction in the amount of money deposited and wagered, compared to those players who did not use Playscan. This reduction in spending for at-risk players, was seen one week after enrolment with Playscan and was also evident 24 weeks after enrolment.
Based on the results, Wood and Wohl concluded that there is evidence to suggest Playscan is particularly helpful for Yellow players (those who show signs of risky play). That is, the feedback provided by Playscan, to those who show signs of risky play, was shown to reduce their levels of spending on gambling games tracked by Playscan. As such, Playscan appears to have responsible gambling utility – at least for those who are most at-risk for developing problematic patterns of play. Importantly, Red players (those who show signs of problematic play) enrolled in Playscan also reduced their expenditure on play, but so did Red players not enrolled in Playscan.
One explanation for this is that Red players, in both groups, may be more aware of a need to reduce their spending on games, as their playing is more obviously risky. Nevertheless, Red players who were using Playscan would have benefitted additionally from being given information to help them seek out the treatment or support that they may have required.