Today Ekaterina Ivanova will defend her PhD-thesis entitled ”Responsible provision of online gambling: Effects, usability and gamblers’ experiences of protective measures implemented in online gambling environments”. Professor Mark Griffiths from Nottingham Trent University will be the opponent during the public defense.
From the abstract of the thesis:
Problem gambling is considered a public health problem in many countries and is associated with serious financial and health-related harms for both problem gamblers and significant others. It is possible to create gambling environments that would promote sustainable gambling behaviors and prevent excessive gambling. However, research on the effectiveness of tools for responsible provision of gambling is scarce and the quality of the research is low. Also, there exists a conflict of interest between making a profit when providing gambling and protecting vulnerable customers. The general aim of the project was to study the effects, usability and gamblers’ experiences of tools for responsible provision of online gambling.
Study I evaluated the effects of a prompt to set voluntary deposit-limit of optional size among 4,328 customers of an online gambling platform. During the data collection period, all customers from Finland registering an account on the gambling platform were randomized into being prompted to set a deposit-limit either 1) at-registration, 2) before their first deposit, 3) after their first deposit or 4) to an unprompted control group. Gambling intensity, measured with aggregated net loss, was tracked during 90 days after registration. No differences in gambling intensity between the intervention and control groups were found neither on the whole-group level (B (95% CI) =-0.080 (-0.229-0.069), p=.291), nor in the subgroup of the most involved gamblers (B (95% CI) =0.042(-0.359-0.442), p=.838).
Study II aimed at predicting gaming freeze (as a proxy parameter for problem gambling) in online gamblers. For the sample of N=2,618 (N=1,309 freezers), a total of 105 predictors were created based on the data tracked by the gambling platform. The analysis was carried out using the machine learning method Random Forest. The predictive accuracy of the model applied to the dataset was 0.615, with a specificity of 0.686 and a sensitivity of 0.543.
Study III aimed at investigating non-problem gamblers’ experiences of protective measures. A total of N=10,200 active customers of an online gambling platform were asked to rate their previous experiences of protective tools, their inclination to abandon a gambling service due to perceived overexposure to protective measures and answer questions on their symptoms of problem gambling. N=1,223 responded to the questionnaire, with the majority of the sample being moderate-risk gamblers (38.5%), followed by low-risk gamblers (26.8%), non-problem gamblers (18.9%) and problem gamblers (15.8%). In general, non-problem gamblers were not more disturbed by protective measures than other categories of gamblers. More problem gamblers have previously abandoned a gambling service due to perceived overexposure to protective measures compared to non-problem gamblers (OR(95% CI)= 7.17(3.61-14.23), p<.001). In conclusion, a prompt to set a voluntary deposit-limit of optional size did not appear to be effective in decreasing gambling intensity in online gamblers, indicating the need of evaluating alternative designs. Predicting gaming freezes in the current project resulted in a low accuracy, indicating that gaming freeze is not suitable as a proxy measurement for problem gambling and suggesting the need for collecting subjective data on symptoms of problem gambling. The results of Study III suggest that protective measures can be tested and implemented without the risk of disturbing recreational gamblers.