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combinations of winning symbols. Such games can be based on mechanical reels, be offered online, or through complex electronic gaming machines (EGMs) or video-lottery terminals. With most modern machines, players are given opportunities to bet on different play
Electronic gaming machines: Are they the crack-cocaine of gambling? Addiction 100 33 45 . M. Griffiths
, Mentzoni, Molde, & Pallesen, 2013 ). For example, a recent study reported that individuals who gamble on electronic gaming machine (EGMs) preferentially attend to EGM stimuli compared to non-EGM stimuli, unlike non-EGM players ( Kim et al., 2021 ). The
Introduction Problem gambling is recognised as a public health concern ( Latvala, Lintonen, & Konu, 2019 ; The Lancet, 2017 ). Research has consistently found that electronic gaming machines (EGMs) are the gambling product most frequently
://doi.org/10.1016/j.neuroimage.2012.06.067 . 22776462 Delfabbro , P. , Falzon , K. , & Imgram , T. ( 2005 ). The effects of parameter variations in Electronic Gaming Machine simulations: Results of a laboratory-based pilot investigation . Gambling
. , & Pallesen , S. ( 2017 ). Gambling behavior in alcohol-serving and non-alcohol-serving-venues: A study of electronic gaming machine players using account records . Addiction Research & Theory, 25 ( 3 ), 201 – 207 . doi: 10
identified some activity-specific limits in a representative dual-frame German dataset: electronic gaming machines (EGMs) (gambling no more than 3 days in the last year and no more than 10-days ever) and poker (nor more than 1–10 days ever). These previous
Abstract
Aims
Understanding how gambling harm is distributed is essential to inform effective harm reduction measures. This first national Australian study of gambling harm-to-self examined the extent, distribution, risk factors, and health related quality of life (HRQoL) impacts of this harm.
Methods
A Random Digit Dialling sample of 15,000 Australian adults was weighted to key population variables. Key measures included the Gambling Harms Scale-10 (GHS-10), PGSI, SF-6D, gambling behaviours, and demographics. Analyses included ordinal logistic regression.
Results
Amongst gamblers, 14.7% reported harm on the GHS-10, including 1.9% reporting high-level harm. While high-level harm occurred mainly in the problem gambling group (77.3%), other PGSI groups accounted for most of the more prevalent low (98.5%) and moderate (87.2%) harms reported. Proximal predictors of greater harm were use of online gambling and more frequent gambling on electronic gaming machines (EGMs), race betting sports betting, poker, skin gambling, scratchies, and loot box purchasing. Distal predictors were being younger, male, single, Aboriginal or Torres Strait Islander, and speaking a non-English language at home. At the population level, the greatest aggregate HRQoL impacts were amongst lower-risk gamblers, confirming the results of other studies regarding the ‘prevention paradox’.
Conclusions
The distribution of harm across gambler risk groups indicates the need for preventive measures, not just interventions for problem gambling. Reducing harm requires modifying product features that amplify their risk, especially for EGMs, race betting and sports betting that are both inherently risky and widely used. Gambling harm exacerbates health disparities for disadvantaged and vulnerable groups, requiring targeted resources and support.
The assessment of the impact of the reconfiguration on electronic gaming machines as harm minimisation strategies for problem gambling Report for the Gaming Industry Operators Group University of Sydney Sydney
near miss . Journal of Gambling Behavior , 2 ( 1 ), 32 – 39 . 19. Sharpe , L. , Blazczynski , A. , Walker , M. ( 2004 ): The identification of near misses in electronic gaming
