Better data access can lead to better collaborative conclusions: Results of a discussion with Heirene

Proposed financial risk checks are more usefully evaluated by directly estimating the impact of £150 monthly thresholds on different risk groups. Re-analysis shows the typical ‘unharmed’ [Problem Gambling Severity Index (PGSI) = 0] gambler in our data is flagged 0.28 times per annum by these, whereas the average ‘at-risk’ gambler (PGSI > 0) is flagged 1.94 times. Heirene [1] raises a series of valid points. We agree that our inferences provide stronger evidence for a general relationship between gambling spend and risk; but importantly, weaker evidence for proposed specific monthly financial risk checks. Based on discussion with Heirene, we agreed that a better way of evaluating risk checks would be to determine how many times each person in each risk group would have reached the now £150 net-deposit threshold with a single operator in a given month. We performed these analyses, finding that the typical ‘unharmed’ [Problem Gambling Severity Index (PGSI) = 0; n = 229] gambler would be flagged 0.28 times [95% confidence interval (CI) = 0.14, 0.54] during the calendar year, whereas the average ‘at-risk’ gambler (PGSI > 0; n = 195) would be flagged 1.94 times (95% CI = 1.42, 2.66). Code and analysis output are available on-line [2]. We hope that this analysis addresses Heirene’s [1] concerns and supports the target article in suggesting the potential utility of financial risk checks at the now £150 monthly net-deposit threshold [3]. Regulation in technology-focused domains such as gambling must be fast-moving if it is to be effective. When we began writing [3], public language centred around ‘affordability checks’; now stakeholder discussions have moved forward to ‘financial risk checks’ [4]. When we published [3], checks were proposed for £125 monthly net loss [5]; now proposed thresholds are at £150 in net deposits [6]. To provide timely guidance in dynamic environments, researchers need rapid access to naturalistic data. Without this, agile academic responses become intractable and the ability of the research community to inform policy becomes limited. We hope that this constructive and collaborative debate with Heirene provides a test case in the ability for better data access to unlock better, data-driven ways of making policy. Crucially, this open exchange of views is facilitated by our reliance upon data infrastructure, rather than data sharing. There are typically significant barriers to the repeated sharing of naturalistic datasets with the research community by third parties [7]. This point is demonstrated by two impactful projects using naturalistic data [8, 9]. These projects have been transformative in terms of obtaining insights, but have faced barriers in terms of translating ongoing data access to the wider community. An understated strength of Zendle & Newall [3] is that the implementation of novel data infrastructure allowed us to crowd-source naturalistic data directly from gamblers via a process of data donation [10]. This means that such data remain accessible for iterative and incremental research: this is the process by which science becomes self-correcting. All evidence in the gambling policy space is inherently limited. Open debate and critique are needed to gradually chip away at these limitations. However, the limitations that remain unavoidable at any one time should not prevent policy stakeholders from taking action [11, 12]. Policy stakeholders can also take action by supporting the research community in obtaining naturalistic data, combining these data with other relevant data sets and enabling naturalistic field studies [13]. Access to such infrastructure should be as equitable and inclusive as possible, both for pace of change and to assuage any concerns about potential conflicts of interest [14]. Overall, the new outcomes presented here provide clearer evidence for financial risk checks in the United Kingdom at the proposed thresholds. This response aimed to show the benefits from a collaborative, non-adversarial approach to knowledge generation and academic debate. We wish to thank Dr Robert Heirene for working with us to help create the analyses reported here. D.Z. is a member of the Advisory Board for Safer Gambling, a statutory body whose remit is to provide independent advice to the UK Gambling Commission. D.Z. is the recipient of an Academic Forum for the Study of Gambling Major Exploratory Grant that is derived from ‘regulatory settlements applied for socially responsible purposes’ received by the UK Gambling Commission and administered by Gambling Research Exchange Ontario (GREO). D.Z. has worked as a paid consultant for governments seeking to understand the effects of video games and gambling. He has worked as an expert witness in cases relating to the video game industry but has never represented the games industry legally or been formally affiliated with any games industry body in any way. D.Z. has been involved in brokering data-sharing agreements with video games industry stakeholders. He acknowledges that such data-sharing agreements constitute a conflict of interest as important as financial awards and wishes to highlight that he has used such data brokerage in ways that are likely to give him indirect financial advantage. P.N. is a member of the Advisory Board for Safer Gambling—an advisory group of the Gambling Commission in Great Britain. In the last 3 years, P.N. has contributed to research projects funded by the Academic Forum for the Study of Gambling, Clean Up Gambling, Gambling Research Australia, NSW Responsible Gambling Fund and the Victorian Responsible Gambling Foundation. P.N. has received honoraria for reviewing from the Academic Forum for the Study of Gambling and the Belgium Ministry of Justice, travel and accommodation funding from the Alberta Gambling Research Institute and the Economic and Social Research Institute and open access fee funding from Gambling Research Exchange Ontario.

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