Prevalence of gambling-related harm provides evidence for the prevention paradox - PubMed (original) (raw)
Prevalence of gambling-related harm provides evidence for the prevention paradox
Matthew Browne et al. J Behav Addict. 2018.
Abstract
Background The prevention paradox (PP) describes a situation in which a greater number of cases of a disease-state come from low-risk members of a population, because they are more prevalent than high-risk members. Past research has provided only tangential and disputed evidence to support the application of the PP to gambling-related harm. Aims To assess whether the PP applies to gambling, the prevalence of a large set (72) of diverse harmful consequences from gambling was examined across four risk categories for problem gambling, including no-risk, low-risk, moderate-risk, and problem-gambling. Methods Respondents who had gambled on non-lottery forms in the past 6 months completed an online survey (N = 1,524, 49.4% male). The data were weighted to the known prevalence of gambling problems in the Victorian community. Results The prevalence of gambling harms, including severe harms, was generally higher in the combined categories of lower risk categories compared to the high-risk problem-gambling category. There were some notable exceptions, however, for some severe and rare harms. Nevertheless, the majority of harms in the 72-item list, including serious harms such as needing temporary accommodation, emergency welfare assistance, experiencing separation or end of a relationship, loss of a job, needing to sell personal items, and experiencing domestic violence from gambling, were more commonly associated with lower risk gamblers. Conclusion Many significant harms are concentrated outside the ranks of gamblers with a severe mental health condition, which supports a public-health approach to ameliorating gambling-related harm.
Keywords: gambling harm; prevention paradox; public health.
Figures
Figure 1.
(a) Prevalence of PGSI categories, (b) average number of harms per person within PGSI categories, and (c) number of harms per 1,000 people arising from each PGSI category
Figure 2.
Mosaic plot of the estimated number of individuals in the population with at least one harm, by PGSI category
Figure 3.
Stacked bar chart of the estimated prevalence of individuals reporting differing numbers of harm by PGSI category
Figure 4.
Mosaic plot of the proportion of harms arising from PGSI categories, by harm domain
Figure 5.
Mosaic plot of the proportion of specific financial harms arising from PGSI categories
Figure 6.
Mosaic plot of the proportion of specific health harms arising from PGSI categories
Figure 7.
Mosaic plot of the proportion of specific relationship harms arising from PGSI categories
Figure 8.
Mosaic plot of the proportion of specific work/study harms arising from PGSI categories
Figure 9.
Mosaic plot of the proportion of specific emotional/psychological harms arising from PGSI categories
Figure 10.
Mosaic plot of the proportion of specific social deviance harms arising from PGSI categories
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References
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Funding sources:
Data collection for this study was funded by the Victorian Responsible Gambling Foundation (VRGF). MB has received funding from the NZ Ministry of Health, VRGF, the Queensland Department of Health, the Tasmanian Department of Treasury and Finance, the Alberta Gambling Research Institute, the First Nations Foundation and Gambling Research Australia. MJR has additionally received funding from the Department of Social Services (Federal), the Queensland Treasury, and the Victorian Department of Justice.
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