Gender comparison of online and land-based gamblers from a nationally representative sample: Does gambling online pose elevated risk?

Robert Edgren, Sari Castrén, Hannu Alho, Anne H. Salonen.

The expansion of online gambling opportunities calls for better comprehension of online gambling, including relevant gender specific correlates. This study compared online and land-based gamblers among males and females separately, utilizing a nationally representative Finnish survey sample of 18-74 year olds. Online gamblers were younger than land-based gamblers and had full-time working status more often than land-based gamblers, with partial indication of land-based gamblers’ monthly income being lower. Online gambling was associated with participation in computer or video gaming more strongly than with land-based gambling. Results show that the strongest predictors of online gambling common to both genders were younger age, computer gaming and gambling on multiple gambling types. Risky alcohol consumption and tobacco smoking were not associated to gambling mode when controlling for other factors. Results indicate that particularly for females online gambling may be related to higher relative expenditure and at-risk and problem gambling, providing implications for tailored interventions. The continued study of subgroups of gamblers is necessary to comprehensively understand the altering gambling milieu.


Early risk and protective factors for problem gambling: A systematic review and meta-analysis of longitudinal studies (full text)

Dowling, N. A., Merkouris, S. S., Greenwood, C. J., Oldenhof, E., Toumbourou, J. W., & Youssef, G. J.

This systematic review aimed to identify early risk and protective factors (in childhood, adolescence or young adulthood) longitudinally associated with the subsequent development of gambling problems. A systematic search of peer-reviewed and grey literature from 1990 to 2015 identified 15 studies published in 23 articles. Meta-analyses quantified the effect size of 13 individual risk factors (alcohol use frequency, antisocial behaviours, depression, male gender, cannabis use, illicit drug use, impulsivity, number of gambling activities, problem gambling severity, sensation seeking, tobacco use, violence, undercontrolled temperament), one relationship risk factor (peer antisocial behaviours), one community risk factor (poor academic performance), one individual protective factor (socio-economic status) and two relationship protective factors (parent supervision, social problems). Effect sizes were on average small to medium and sensitivity analyses revealed that the results were generally robust to the quality of methodological approaches of the included articles. These findings highlight the need for global prevention efforts that reduce risk factors and screen young people with high-risk profiles. There is insufficient investigation of protective factors to adequately guide prevention initiatives. Future longitudinal research is required to identify additional risk and protective factors associated with problem gambling, particularly within the relationship, community, and societal levels of the socio-ecological model.

Dowling, N. A., Merkouris, S. S., Greenwood, C. J., Oldenhof, E., Toumbourou, J. W., & Youssef, G. J. (n.d.). Early risk and protective factors for problem gambling: A systematic review and meta-analysis of longitudinal studies. Clinical Psychology Review.

An Ecological Approach to Electronic Gambling Machines and Socioeconomic Deprivation in Germany

Xouridas, S., Jasny, J., & Becker, T.
In Germany, gambling research has primarily focused on the broader population in prevalence studies, neglecting the importance and influence of the local socioeconomic context in the development and maintenance of gambling disorders. To analyze the interplay between contextual and compositional factors in the market for electronic gambling machines (EGMs) in Germany, we assessed the EGM densities and socioeconomic deprivation in 244 local communities within Baden-Wuerttemberg. Our results suggest that EGM density is statistically associated with 3 socioeconomic determinants: The shares of migrants, unemployed, and high-school-educated people in the communities are statistically significant variables in our linear regression model, whereas younger age, male gender, and marital status exhibit no statistical associations with EGM density. The share of unemployed people is the only variable of statistical and practical significance. Our analysis advocates area-based policy measures to minimize gambling-related harm. By decreasing EGM densities in communities with high levels of unemployment, we expect to protect at-risk population strata that are most vulnerable to gambling exposure.

Gambling Disorder and Minority Populations: Prevalence and Risk Factors

Okuda, M., Liu, W., Cisewski, J. A., Segura, L., Storr, C. L., & Martins, S. S.

Previous studies demonstrate disparities in health and health services including gambling disorders (GD) among ethnic and racial minority groups. In this review, we summarize studies examining the prevalence of GD across different ethnic and racial minorities. We describe the sociodemographic subgroup variations at heightened risk for GD and factors associated with GD in racial and ethnic minority groups including gambling availability, comorbid substance use, psychiatric conditions, stress, acculturation, and differences in cultural values and cognitions. We found that research of GD among minority groups is scant, and the prevalence of GD among these groups is at a magnitude of concern. Racial and ethnic minority status in it of itself is not a risk factor for GD but may be a proxy for underlying potential risk factors. The need for prevention and treatment programs for different cultural group remains unmet.

Okuda, M., Liu, W., Cisewski, J. A., Segura, L., Storr, C. L., & Martins, S. S. (2016). Gambling Disorder and Minority Populations: Prevalence and Risk Factors. Current Addiction Reports, 1–13.

Changes in risky gambling prevalence among a New Zealand population cohort

Evidence suggests that problem gambling is an unstable state where gamblers move into and out of risk over time. This article looks at longitudinal changes in risky gambling and the factors associated with an increased risk (measured by the Problem Gambling Severity Index [PGSI]) in the current New Zealand context, which has experienced a doubling of the electronic gaming machine (EGM) market over the last two decades. Respondents from a nationally representative baseline sample (n = 2672) were recontacted two years later to assess changes in gambling behaviours. Among the 901 respondents reached at follow-up, average gambling risk increased over time, and the prevalence of those who had at least some level of gambling risk (i.e. low-risk or greater) more than doubled (from 4.7% to 12.4%). The majority (80.2%) of those who were at risk at follow-up had not been at risk at baseline. Multivariate linear regression analyses show that the predictors of low to moderate increased risk include Pacific ethnicity; high neighbourhood deprivation status; baseline frequent, continuous gambler type; baseline PGSI status; and playing EGMs. These findings highlight the need to develop theories of gambling addiction trajectories and to identify the earliest point along the trajectory where public health interventions should occur.

Kruse, K., White, J., Walton, D. K., & Tu, D. (2016). Changes in risky gambling prevalence among a New Zealand population cohort. International Gambling Studies, 0(0), 1–19.

The association between pathological gambling and suicidality in treatment-seeking pathological gamblers in South Africa

BACKGROUND: A number of studies have noted a significant association between suicidality and pathological gambling (PG), but the exact relationship has not been extensively characterized. It is unclear whether gambling precipitates suicidality, or whether underlying psychiatric problems, such as mood disturbances, lead to both gambling and suicidality. Furthermore, all published data on the association between suicidality and gambling is from high-income countries, and the nature of this relationship in low- and middle-income countries, such as South Africa, has not been explored.

METHODS: The relationship between gambling and suicidality was investigated in individuals who had called the South African National Responsible Gambling Programme’s helpline. Associations between sociodemographic factors, severity of gambling symptoms, comorbid psychiatric disorders, family history of psychiatric disorders, and suicidality were assessed…

Source: Stein, G. N., Pretorius, A., Stein, D. J., & Sinclair, H. (2016). The association between pathological gambling and suicidality in treatment-seeking pathological gamblers in South Africa. Annals of Clinical Psychiatry: Official Journal of the American Academy of Clinical Psychiatrists, 28(1), 43–50.

Is all Internet gambling equally problematic? Considering the relationship between mode of access and gambling problems

Concerns exist that Internet gambling may increase rates of gambling harms, yet research to date has found inconsistent results. Internet gamblers are a heterogeneous group and considering this population as a whole may miss important differences between gamblers. The differential relationship of using mobile and other devices for gambling online has not been considered as compared to the use of computers. The true relationship of Internet gambling on related problems and differences between preferred modes for accessing online gambling may be obscured by confounding personal and behavioural factors. This paper thus uses the innovative approach of propensity score matching to estimate the consequence of gambling offline, or online through a computer, as compared to mobile or other supplementary devices by accounting for confounding effects of difference among groups of Australian gamblers…

Source: Gainsbury, S., Liu, Y., Russell, A. M. T., & Teichert, T. (2016). Is all Internet gambling equally problematic? Considering the relationship between mode of access and gambling problems. Computers in Human Behavior, 55, Part B, 717–728.