* All times are based on Canada/Eastern EDT.

  • 10:00


    10:00 - 10:30 EDT

    Opening Remarks



    10:30 - 11:15 EDT

    Keynote Presentation - Thomas B. Sama

    Gambling industry strategies to influence the reform of state online monopolies: The case of the gambling industry in Sweden and Finland The aim of this qualitative study was to investigate the strategies used by the gambling industry to influence the reform of state online monopoly into a licensing system in Sweden in 2019, and to weaken state online monopoly in Finland. The study has answered two research questions: (1) what strategies were used by the gambling industry to influence the reform of state online monopoly into a licensing system in Sweden in 2019? and (2) what strategies are used by the gambling industry to weaken state online monopoly in Finland? Methodologically, this study utilized primary data from interviews and secondary data from prior literature, journal articles and Google databases. Primary data was collected through 9 expert interviews in both countries with informants who had expertise knowledge in gambling research and policy making. The results identified five main political strategies used by the gambling industry: (1) ‘information’, through lobbying politicians; (2) ‘constituency building’, under which the gambling industry formed alliances with interest groups; (3) ‘policy substitution’, under which the gambling industry promoted alternative policies and self-regulation; (4) ‘legal infringements’, under which the gambling industry argued that the monopoly violated EU law, but not in Finland; and (5) ‘regulatory redundancy’, under which the gambling industry argued that the monopoly was redundant. The study concluded that the involvement of the gambling industry in policy making, influenced the change of the state online monopoly into a licensing system in Sweden in 2019, and is influencing the weakening of the of state online monopoly in Finland.



    11:15 - 11:30 EDT




    11:30 - 12:15 EDT

    Keynote Presentation - Elena Gomis-Vicent

    Physiological mechanisms associated with non-invasive brain stimulation during gambling-related task performance Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that has been investigated as a tool to improve current treatment approaches for gambling disorder (GD). In this study, tDCS effects over the autonomous nervous system (ANS) were examined during different reward conditions. Participants consisted of 17 low-risk and high-risk gamblers who were grouped by their self-reported impulsivity levels. Electroencephalogram (EEG), electrodermal activity (EDA) and electrocardiogram (ECG) were measured during gambling-related cognitive task performance while receiving two tDCS sessions (real stimulation and sham). Results revealed tDCS effects over the ANS, associated with an increase of skin conductance level and changes of cortical excitability. Furthermore, the EEG outcomes showed participants intra-individual variability between sessions. Different autonomic arousal was found between groups of low and high impulsive gamblers, and between different reward phases. Specifically, high impulsive gamblers showed higher sympathetic activation (increased EDA and heart rate variability) compared with low impulsive gamblers during wins compared to losses. Lastly, gambling severity correlated positively with cravings, and with EDA and heart rate during cognitive task-performance. Neuromodulation outcomes showed evidence of the capability of tDCS to modulate the ANS, however, due to the lack of effectiveness of blinding during real stimulation, these results should be carefully interpreted. Notably, the correlations between baseline EDA and reward response variables might indicate that EDA could be a potential biomarker to investigate GD. Employing more realistic experimental gambling scenarios in future studies will be essential to improve ecological validity and to better understand problematic gambling behaviour.



    12:15 - 13:15 EDT

    Break - Lunch



    13:15 - 14:00 EDT

    Keynote Presentation - Jenny Blythe

    Levers and barriers to addressing gambling harms using public health approaches in London local government- a mixed methods approach. Under the Gambling Act 2005 in Great Britain, so-called ‘land-based’ gambling premises (such as betting shops, bingo, arcades and casinos) require three licenses to operate, the premises licence being authorised by local government licensing authorities. Unlike premises that sell alcohol, however, local public health teams are not what is called Responsible Authorities: that is, there is no mandatory requirement in primary legislation to involve them in the decision-making process. Furthermore, certain gambling products (such as National Lottery and online gambling) fall outside local licensing powers. My research aims to identify levers and barriers that support local government adopting public health strategies to address gambling harms, with a focus upon London local authorities, as approximately a quarter of all land-based gambling premises in the UK are within the Greater London area. The research adopts a mixed methods approach underpinned by a critical realist philosophy. The mixture of quantative and qualitative outputs will be analysed in their entirety with the aim of identifying the underlying mechanisms that have generated these findings. The five individual outputs are a survey of London Directors of Public health, a time series analysis of gambling premises by type, number borough-level deprivation ranking, a scoping review of population-level strategies to address gambling harms in local government settings, a critical discourse analysis of UK gambling policy, and a thematic analysis of interviews with public health licensing teams representatives from London’s local authorities. Findings of the individual outputs will be discussed, as well as the underlying mechanisms hypothesised from the research.



    14:00 - 14:15 EDT




    14:15 - 15:00 EDT

    Keynote Presentation - Viktorija Kesaite

    Gambling consumption and gambling harm: evidence from three British surveys Population level interventions have been used by policymakers to normalise healthy choices, thuslowering the overall harm in the population. The justification for this type of intervention has beenconceptualised in the total consumption model (TCM), which suggests that there is a close linkbetween mean population consumption and the harm that arises from consumption. In this studywe assess the relationship between gambling consumption measures and gambling related harm. We use three British cross-sectional datasets from 2015 to 2020, covering approximately 50,000individuals across the three datasets. This study firstly presents new evidence on application of theTCM to gambling in Britain. Secondly, we explore the shape of the risk curves, examining the natureof the relationship between consumption and harms and we also conduct moderation analysis to assess if and how the relationship between consumption and harm varies across sub-groups of the population. Results examining the application of the TCM were mixed. One dataset showed a strong correlationbetween population gambling mean and prevalence of excessive gambling. However, similarpatterns were not observed in the other two datasets analysed. The risk curves for the threedatasets suggest that gambling harm increases with levels of consumption, showing a broadly linear relationship. Moderation analyses on the relationship between gambling consumption and harm suggest that younger age groups, and non-white ethnic groups are more likely to experience greater levels of harm. In conclusion, given the scant research on this, more evidence is required to better understand these inter-relationships.



    15:00 - 16:00 EDT
    Virtual Poster Session

    Virtual Poster Session



    16:00 - 16:45 EDT

    Keynote Presentation - Stephanie Merkouris

    Exploring the experiences and perceptions of individuals who use online gambling support forums: A natural language processing approach There is limited research examining the relationship between gambling problems and psychiatric disorders from the perspective of people with gambling problems. The few qualitative studies exploring individuals’ experiences of these complex relationships have been limited by small and unrepresentative samples. However, the emergence of large textual datasets (i.e., online forums) and advances in machine learning methodologies provide an unprecedented opportunity to explore individual experiences and perceptions of these complex relationships from large naturalistic samples. The present study is one of the first to explore the experiences and perceptions of the relationship between gambling and comorbid mental health and alcohol and other drug (AOD) use problems in Australian, UK and US gambling forum users, using various Natural Language Processing analytic techniques, including Latent Dirichlet Analyses and sentiment analysis. The data revealed seven-topic (Gambling Help Online), six-topic (GamCare) and two-topic (PsychForums) models best represented the data in each forum. These topics were subsumed across three overarching categories relating to: (1) the relationship between gambling and mental health issues; (2) the relationship between gambling and AOD issues; and (3) other emotion-related topics. The findings highlight that the complex reciprocal relationship between gambling problems and mental health/AOD issues are universal, and that forum users more commonly discussed issues relating to comorbid mental health issues with fewer topics relating to comorbid AOD issues. Jurisdictional differences in the directional nature of these co-occurring issues and the context in which these co-occurring issues are experienced suggest the need for screening and treatment efforts tailored to each jurisdiction.



    16:45 - 17:00 EDT




    17:00 - 17:45 EDT

    Keynote Presentation - W. Spencer Murch

    A Pre-Registered Analysis to Develop Fairer Machine Learning Models for Detecting At-Risk Online Gamblers Researchers have worked to develop machine learning models capable of detecting at-risk online gamblers to enable personalized harm prevention tools. However, existing research has not evaluated these models’ potential for sociodemographic bias leading to treatment disparity. Given the tendency of machine learning models to produce biased predictions, we sought to develop and compare three examples of potentially more-equitable models. In two large samples of transaction data from a state-owned gambling website (N1 =9,145, N2 =10,716), we developed three machine learning models based on competing concepts of fairness: fairness via unawareness, classification parity, and outcome calibration. We hypothesized that significant covariance existed between the dependent variable - high-risk status indicated by the Problem Gambling Severity Index - and participants’ age and sex. Further, we hypothesized that the three ‘fair’ models would show differing levels of classification performance both in aggregate and within sociodemographic groups. Significant age and sex effects were found, refuting the fairness via unawareness modelling strategy. Superiority across all performance metrics was not present for either of the remaining models. For the fairest practices in any jurisdiction, classification parity and outcome calibration models should be tested in situ, and incorporate the perspectives and preferences of end users who will be affected.



    17:45 - 18:00 EDT

    Closing Address

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