Analyses of multiple types of online gambling within one provider: an extended evaluation framework of actual online gambling behaviour

Abstract

The aim of this article is to extend previous publications of actual online gambling behaviour that neglected involvement across multiple types of gambling and did not provide levels of at-risk involvement. Behavioural data from 27,653 subscribers of an online gambling provider (bwin) in February 2005 were reanalysed across eight products over seven months. Established involvement levels of offline gambling segregated possible online at-risk gamblers. Forty-seven percent of the sample exceeded at least one of the two most conservative thresholds. Each additionally used gambling product increased the risk of transgressing involvement cut-offs by 3.06 to 4.27 times, but type-specific risks decreased strongly after adjusting for involvement in multiple gambling types. Only Poker and Live-action betting remained significant risk factors after adjustment. Taken together, cross-product analyses of gambling patterns lay the groundwork for an extended understanding of individual online gambling behaviour and overcome the methodological artefacts of isolated analyses.

Keywords:

• gambling
• Internet
• behaviour
• frameworks
• risk assessment

Acknowledgements

This paper utilized data from the Transparency Project (www.thetransparencyproject.org), Division on Addictions, Cambridge Health Alliance, a teaching affiliate of Harvard Medical School. We thank the Division on Addictions for launching the Transparency Project and making this unique dataset of online gamblers publicly available for secondary analyses.

Notes

1. In an additional series of logistic regressions we controlled for the fact that not playing different types of gambling but, rather, the associated greater gambling frequency was the true predictor of transgressing thresholds. To dispel the doubts about circular reasoning we additionally adjusted the previous two-factor prediction models (type and multiple involvement) for the sum of all active days. Even after this adjustment each additionally used type of gambling significantly increased the risk of transgressing both thresholds by about two to three times. These findings confirm our suggestion that the number of regularly used types of gambling is significantly associated with at-risk gambling.