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. 2024 May 14;13(2):635-649.
doi: 10.1556/2006.2024.00025. Print 2024 Jun 26.

Harm-to-self from gambling: A national study of Australian adults

Affiliations

Harm-to-self from gambling: A national study of Australian adults

Catherine Tulloch et al. J Behav Addict. .

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.

Keywords: gambling harm; gambling products; health-related quality of life (HRQoL) population study; health inequity; risk factors.

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Conflict of interest statement

Funding sources: Funding for this study was provided by Gambling Research Australia, a partnership between the Commonwealth, State and Territory Governments to initiate and manage a national gambling research program.

Authors' contribution: NH led the study on which the current paper is based. All authors except CT helped to design the overall study and the survey instrument. CT, MB and AR drafted the methods section. CT conducted the statistical analyses, compiled the results tables, and drafted the results section. NH completed the remainder of the first draft of the manuscript. All authors refined and approved the submitted version of the manuscript.

Conflicts of interest: The authors declare no conflicts of interest in relation to this manuscript.

Figures

Fig. 1.
Fig. 1.
Proportion of people who experience each number of harms or more by gamblers and Australian adult population Note: Gamblers reporting harm only, proportion of zero harms are 85.27% (gamblers), 91.62% (population), population weighting used. See Appendix (Table A1) for further information.
Fig. 2.
Fig. 2.
Proportion of people in each PGSI risk category who experience each number of harms or more Note: Gamblers reporting harm only. Proportion of zero harms for gamblers are 94.88% (NP), 61.96% (LR), 24.22% (MR), 3.60% (PG). Subsample weight used. See Appendix (Table A2) for further information.
Fig. 3.
Fig. 3.
Proportion of harm in the population by PGSI category
Fig. 4.
Fig. 4.
Burden of harm in the population by PGSI and GHS-10 category Note: Sample N = 5,224; Population N = 19,931,221 (Adult population of Australia in 2019); No harm includes non-gambling; No harm and non-gambling are 0 harm by definition, included for clarity.

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