Gambling and Problem Gambling in Victoria, Australia: Changes over 5 years

Abbott, Max; Stone, Christine; Billi, Rosa; Yeung, Kristal

doi:10.1007/s10899-015-9542-1

Cited by 56 publications

(41 citation statements)

References 18 publications

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“…Males, young adults, low‐income and non‐married people are almost universally at elevated risk . Problem gamblers’ socio‐demographic profile has changed somewhat over time . In jurisdictions where electronic gaming machines (EGMs) have been distributed widely, gender differences have often diminished .…”

Section: Introductionmentioning

confidence: 99%

The prevalence, incidence, and gender and age‐specific incidence of problem gambling: results of the Swedish longitudinal gambling study (Swelogs)

2017

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Section: Introductionmentioning

confidence: 99%

The prevalence, incidence, and gender and age‐specific incidence of problem gambling: results of the Swedish longitudinal gambling study (Swelogs)

2017

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“…This is equivalent to the recent practice that has been applied to compare prevalence estimates between studies e.g. [8, 13], where prevalence estimates are normalised by multiplying them by fixed adjustment factors. Fixing coefficients is advantageous as it forces control variables to be set at plausible values and reduces the effective degrees of freedom of the models.…”

Section: Methodsmentioning

confidence: 99%

“…Consequently, in a series of studies [10–13], Abbott proposed an alternative hypothesis of ‘adaptation’, in which the prevalence of problem gambling tends to fall over time. The reasons for adaptation may include a decline in gambling participation as the novelty of a new gambling activity dwindles, decreased average duration of gambling problems through destigmatisation and improved treatment, changing cultural norms, increased knowledge of gambling-related harms, and the introduction of regulations such as in-venue smoking bans and caps on EGM numbers.…”

Section: Introductionmentioning

confidence: 99%

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A meta-regression analysis of 41 Australian problem gambling prevalence estimates and their relationship to total spending on electronic gaming machines

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BackgroundMany jurisdictions regularly conduct surveys to estimate the prevalence of problem gambling in their adult populations. However, the comparison of such estimates is problematic due to methodological variations between studies. Total consumption theory suggests that an association between mean electronic gaming machine (EGM) and casino gambling losses and problem gambling prevalence estimates may exist. If this is the case, then changes in EGM losses may be used as a proxy indicator for changes in problem gambling prevalence. To test for this association this study examines the relationship between aggregated losses on electronic gaming machines (EGMs) and problem gambling prevalence estimates for Australian states and territories between 1994 and 2016.MethodsA Bayesian meta-regression analysis of 41 cross-sectional problem gambling prevalence estimates was undertaken using EGM gambling losses, year of survey and methodological variations as predictor variables. General population studies of adults in Australian states and territory published before 1 July 2016 were considered in scope. 41 studies were identified, with a total of 267,367 participants. Problem gambling prevalence, moderate-risk problem gambling prevalence, problem gambling screen, administration mode and frequency threshold were extracted from surveys. Administrative data on EGM and casino gambling loss data were extracted from government reports and expressed as the proportion of household disposable income lost.ResultsMoney lost on EGMs is correlated with problem gambling prevalence. An increase of 1% of household disposable income lost on EGMs and in casinos was associated with problem gambling prevalence estimates that were 1.33 times higher [95% credible interval 1.04, 1.71]. There was no clear association between EGM losses and moderate-risk problem gambling prevalence estimates. Moderate-risk problem gambling prevalence estimates were not explained by the models (I 2 ≥ 0.97; R 2 ≤ 0.01).ConclusionsThe present study adds to the weight of evidence that EGM losses are associated with the prevalence of problem gambling. No patterns were evident among moderate-risk problem gambling prevalence estimates, suggesting that this measure is either subject to pronounced measurement error or lacks construct validity. The high degree of residual heterogeneity raises questions about the validity of comparing problem gambling prevalence estimates, even after adjusting for methodological variations between studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-017-4413-6) contains supplementary material, which is available to authorized users.

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“…[12][13][14]). This downward trajectory may be artefactual, a spurious trend resulting from temporal confounding with the shift to mobile telephones, everdiminishing response rates and demographic change.…”

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confidence: 99%

Commentary on Dowling et al. (2016): Is it time to stop conducting problem gambling prevalence studies?

Markham

Young

2016

Addiction

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Gambling and Problem Gambling in Victoria, Australia: Changes over 5 years

Cited by 56 publications

References 18 publications

The prevalence, incidence, and gender and age‐specific incidence of problem gambling: results of the Swedish longitudinal gambling study (Swelogs)

The prevalence, incidence, and gender and age‐specific incidence of problem gambling: results of the Swedish longitudinal gambling study (Swelogs)

A meta-regression analysis of 41 Australian problem gambling prevalence estimates and their relationship to total spending on electronic gaming machines

Commentary on Dowling et al. (2016): Is it time to stop conducting problem gambling prevalence studies?

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