Digital gambling is the fastest growing form of gambling in the world (Reilly & Smith, 2013a). Technological advancements continually increase access to gambling, which has led to increased social acceptance and uptake (Dragicevic & Tsogas, 2014) with Roulette being among the most popular games played both online and on Electronic Gaming Machines. In response, gambling stakeholders have drawn on the structural characteristics of gambling platforms to develop and improve Responsible Gambling (RG) devices for casual gamblers. Many RG data-tracking systems employ intuitive ‘traffic-light’ metaphors that enable gamblers to monitor their gambling (e.g. Wood & Griffiths, 2008), though uptake of voluntary RG devices is low (Schellinck & Schrans, 2011), leading to calls for mandatory RG systems. Another area that has received considerable RG research focus involves the use of pop-up messages (Auer & Griffiths, 2014). Studies have examined various message content, such as correcting erroneous beliefs, encouraging self-appraisal, gambling cessation, and the provision of personalised feedback. To date, findings have been inconsistent but promising. A shift towards the use of personalised information has become the preferred RG strategy, though message content and timing/frequency requires improvement (Griffiths, 2014). Moreover, warning messages are unable to provide continuous feedback to gamblers. In response to this, and calls for a ‘risk meter’ to improve monitoring of gambling behaviours (Wiebe & Philander, 2013), this thesis tested the impact of a risk meter alongside improved pop-up warning messages as RG devices for within-session roulette gambling. The thesis aimed to establish the optimal application of these devices for facilitating safer gambling behaviours. In support of the aims of RG research to evaluate the impact of devices on gambling attitudes and behaviours, the Elaboration Likelihood Model was identified as a suitable framework to test the proposed RG devices (Petty & Cacioppo, 1986). Both the interactive risk meter and pop-up messages were developed based on existing methods and recommendations in the RG literature, and examined via a series of laboratory-based roulette simulation experiments. Overall, results found the risk meter to be most effective when used as an interactive probability meter. Self-appraisal/Informative pop-up warnings were examined alongside expenditure-specific and hyrbid warnings. Findings showed that hybrid messages containing both types of information to be most effective, with optimal display points at 75%, 50%, 25% and 10% of remaining gambling credit. The final study tested both optimised devices (probability meter and hybrid messages). Results showed that using both RG devices in combination was most effective in facilitating reduced gambling risk and early within-session gambling cessation. Findings support the use of personalised, interactive RG devices using accurate context-specific information for the facilitation of safer gambling. The ELM was shown to be an effective model for testing RG devices, though findings suggested only temporary shifts in attitude change and a lack of impact on future gambling intentions. Overall, support for the implementation of RG devices that facilitate positive, temporary behaviour change that do not negatively impact on broader gambling attitudes or gambling enjoyment. Implications for theory, implementation, and RG frameworks are discussed, alongside recommendations for future research.
|Qualification||Doctor of Philosophy|
|Award date||22 Oct 2017|
|Publication status||Unpublished - Oct 2017|