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Numerous responsible gambling (RG) strategies are promoted to assist consumers to “gamble responsibly”. However, consumer adoption of RG strategies, how this varies by gambler risk group, and whether usage is associated with non-problematic gambling are largely unknown. This study aimed to (1) determine how use of RG-related strategies differs amongst regular gamblers by gambler risk group; and (2) identify RG-related strategies whose usage predicts non-problem/low risk gambling. Regular Australian gamblers on high-risk products ( N  = 860), recruited through gambling venues and an online wagering operator, were surveyed about their use of RG strategies promoted on the website of their jurisdiction’s main RG agency. Knowledge of RG strategies was reasonably high amongst all gambler risk groups, but lower-risk groups were more likely to use RG strategies. A logistic regression correctly predicted 82.1 % of lower-risk gamblers and 77.2 % of higher-risk gamblers. Predictors of lower-risk gambling included: greater confidence in their understanding of RG; endorsement of lower gambling expenditure and frequency limits; fewer erroneous gambling beliefs; being less likely to gamble to win money, challenge their skills/beat the odds, or forget about worries and stresses; and being more likely to gamble for pleasure/entertainment. Lower-risk gamblers were more likely to set a money limit in advance of gambling and to balance their gambling with other activities. These findings contribute to understanding which strategies are favoured by different risk groups, and which are associated with safer levels of gambling. They can guide consumer information aimed at enhancing RG consumption and future research on RG consumption.

Background Both the Problem Gambling Severity Index (PGSI) and the Short Gambling Harms Screen (SGHS) purport to identify individuals harmed by gambling. However, there is dispute as to how much individuals are harmed, conditional on their scores from these instruments. We used an experienced utility framework to estimate the magnitude of implied impacts on health and wellbeing. Methods We measured health utility using the Short Form Six-Dimension (SF-6D), and used this as a benchmark. All 2603 cases were propensity score weighted, to balance the affected group (i.e., SGHS 1+ or PGSI 1+ vs 0) with a reference group of gamblers with respect to risk factors for gambling harm. Weighted regression models estimated decrements to health utility scores attributable to gambling, whilst controlling for key comorbidities. Results We found significant attributable decrements to health utility for all non-zero SGHS scores, as well as moderate-risk and problem gamblers, but not for PGSI low-risk gamblers. Applying these coefficients to population data, we find a similar total burden for both instruments, although the SGHS more specifically identified the subpopulation of harmed individuals. For both screens, outcomes on the SF-6D implies that about two-thirds of the ‘burden of harm’ is attributable to gamblers outside of the most severe categories. Conclusions Gambling screens have hitherto provided nominal category membership, it has been unclear whether moderate or ‘at-risk’ scores imply meaningful impact, and accordingly, population surveys have typically focused on problem gambling prevalence. These results quantify the health utility decrement for each category, allowing for tracking of the aggregate population impact based on all affected gamblers.

A large, integrated survey data set provided by the Ontario Problem Gambling Centre was used to investigate psychometric properties of the Problem Gambling Severity Index (PGSI). This nine-item self-report instrument was designed to measure a single, problem gambling construct. Unlike its nearest competitor—the South Oaks Gambling Screen (SOGS)—the PGSI was designed specifically for use with a general population rather than in a clinical context. The present analyses demonstrated that the PGSI does assess a single, underlying, factor, but that this is complicated by different, multiple factor structures for respondents with differing levels of problem gambling severity. The PGSI also demonstrated small to moderate correlations with measures of gambling frequency and faulty cognitions. Overall, the PGSI presents a viable alternative to the SOGS for assessing degrees of problem gambling severity in a non-clinical context.

Background Many 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. Methods A 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. Results Money 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). Conclusions The 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.

It is well known that many problem gamblers also suffer from other psychiatric conditions. However, knowledge regarding the temporal sequencing of the conditions is lacking, as well as insight in possible gender specific patterns. The aim of this study was to examine the risk for psychiatric comorbidity among problem gamblers compared to non-problem gamblers in the general Swedish population, as well as the age of onset and the temporal sequencing of problem gambling and the comorbid psychiatric conditions among lifetime problem gamblers. A case–control study nested in the Swelogs cohort was used. For both the female and the male problem gamblers, the risk for having had a lifetime psychiatric condition was double or more than double compared to the controls. Having experienced anxiety or depression before gambling onset, constituted a risk for developing problem gambling for the women but not for the men. Further, the female cases initiated gambling after their first period of anxiety, depression and problems with substances, and problem gambling was the last condition to evolve. Opposite this, the male cases initiated gambling before any condition evolved, and depression and suicidal events emerged after problem gambling onset. There were large differences in mean age of onset between the female cases and their controls, this was not the case for the males. Gender specific patterns in the association between problem gambling and psychiatric comorbidity, as well as in the development of problem gambling needs to be considered in treatment planning as well as by the industry in their advertising.

Background Problem gambling can lead to health-related harms, such as poor mental health and suicide. In the UK there is interest in introducing guidance around effective and cost-effective interventions to prevent harm from gambling. There are no estimates of the health state utilities associated with problem gambling severity from the general population in the UK. These are required to determine the cost-effectiveness of interventions. This study aims to use an indirect elicitation method to estimate health state utilities, using the EQ-5D, for various levels of problem gambling and gambling-related harm. Methods We used the Health Survey for England to estimate EQ-5D-derived health state utilities associated with the different categories of the Problem Gambling Severity Index (PGSI), PGSI score and a 7-item PGSI-derived harms variable. Propensity score matching was used to create a matched dataset with respect to risk factors for problem gambling and regression models were used to estimate the EQ-5D-derived utility score and the EQ-5D domain score whilst controlling for key comorbidities. Further exploratory analysis was performed to look at the relationship between problem gambling and the individual domains of the EQ-5D. Results We did not find any significant attributable decrements to health state utility for any of the PGSI variables (categories, score and 7-item PGSI derived harms variable) when key comorbidities were controlled for. However, we did find a significant association between the 7-item PGSI derived harms variable and having a higher score (worse health) in the anxiety/depression domain of the EQ-5D, when comorbidities were controlled for. Conclusions This study found no significant association between problem gambling severity and HRQoL measured by the EQ-5D when controlling for comorbidities. There might be several reasons for this including that this might reflect the true relationship between problem gambling and HRQoL, the sample size in this study was insufficient to detect a significant association, the PGSI is insufficient for measuring gambling harm, or the EQ-5D is not sensitive enough to detect the changes in HRQoL caused by gambling. Further research into each of these possibilities is needed to understand more about the relationship between problem gambling severity and HRQoL.

Actual and perceptual measures of gambling exposure are important predictors of problem gambling. This study used Zero-Inflated Poisson regression analyses to assess the relative and interactive effects of actual and perceived exposure on problem gambling risk and severity. Data from the 2008 and 2009 Social and Economic Impacts of Gambling in Alberta surveys indicated actual exposure was significantly associated with problem gambling risk while perceived exposure was significantly associated with problem gambling severity. These associations differ for gamblers from emerging and mature areas. Further, actual and perceived exposure had significant interaction effects on problem gambling severity but not on risk. Implications from these findings suggest that the prevalence of problem gambling could be reduced by restrictions on gambling opportunities.

Purpose Harms due to excessive gambling can be experienced by gamblers and those close to them. Family gambling problems (FGPs) are currently under-researched, particularly in population-representative samples. This study aimed to identify prevalence, risk factors, and the complex of stressors and health-related consequences associated with FGPs, as well as isolating the impact of FGPs on physical and psychological health problems. Methods We analysed data from the National Health Survey 2011–13, a large ( N  = 15,475) nationally representative sample of Australian adults. Participants reported on the presence of 14 family stressors (including FGPs), self-assessed health status, and risky health behaviours. Psychological impact was measured by the Kessler Psychological Distress Scale-10, as well as several indicators of the presence of mental health problems. Results Overall, 1.7% of households reported a FGP. Interviewees in these households reported three times the number of other stressors than those without a FGP. In addition, they were around eight times more likely to be experiencing other addictions (drug and alcohol related problems) and stressors associated with socially deviant behaviours (trouble with police, abuse or violent crime, and witness to violence). Once age, gender, socioeconomic disadvantage, and other stressors were controlled for, FGPs significantly predicted lower self-assessed health and higher psychological distress. Conclusions FGPs occur within a complex of other addictions and stressors, impacting the quality of life of people close to problem gambling. The findings are discussed in relation to their support for General Strain Theory (Agnew, Criminology 30:47–87, 1992).

Previous research has shown that gambling is a popular activity among adolescents. Following a rapid expansion of legalized gambling opportunities and the emergence of new forms of gambling, many researchers have carried out studies on adolescent gambling and problem gambling. The present paper reviews studies that have been conducted worldwide since 2000, and then presents a more detailed picture of adolescent gambling research in Europe, by providing a country-by country analysis. After an extensive search on academic databases and following an exclusion process, 44 studies were identified. The findings showed that 0.2–12.3 % of youth meet criteria for problem gambling, notwithstanding differences among assessment instruments, cut-offs, and timeframes. However, despite this variability, several demographic characteristics were associated with adolescent gambling involvement and problem gambling. It is concluded that a small but significant minority of adolescents have gambling-related problems. Such findings will hopefully encourage more research into youth gambling to further understand the determinants of this phenomenon.

This study aimed to investigate, from a gender perspective, how different features of problem gambling present in men and women who gamble regularly in Sweden were distributed in four domains based on gambling type (chance or strategy) and setting (public or domestic). Problem gambling features were based on the nine items in the Problem Gambling Severity Index (PGSI). It was hypothesized that men and women gamble in different domains. Further, it was hypothesized that male gamblers overall experienced more problems with gambling than female gamblers, although in the same domains they would report the same level of problems. A further hypothesis predicted that regular female gamblers would experience more health and social problems and men would experience more financial difficulties. Interviews with a subsample of gamblers ( n  = 3191) from a Swedish nationally representative sample ( n  = 8179) was used to examine how features of problem gambling correspond with gender and the domains. Only the first hypothesis was fully supported. Men were more likely to participate in forms of gambling requiring strategy in a public setting, and women were more likely to participate in chance-based gambling in a domestic setting. Male and female gamblers had similar levels of problem gambling in the bi-variate analysis, but if controlling for age and gambling in multiple domains, women were more at risk than men. Additionally, men and women presented similar health and economic situations. The differences between male and female gamblers in Sweden have implications for research and prevention.