Risk of problem gambling among occupational groups: A population and registry study

Problem Gambling and Problem Gaming in Elite Athletes: a Literature Review

Researchers have raised concerns about mental health in elite athletes, including problem gambling, where research hitherto is scarce. While gambling has been assessed in the younger student-athlete population, neither gambling nor the recently recognized behavioral addiction of gaming disorder has been sufficiently addressed in the elite athlete population. The present systematic literature review aimed to summarize research knowledge on the prevalence and correlates of problem gambling and problem gaming in elite athletes. Research papers were searched systematically using the Scopus, PsycINFO, and PubMed/MEDLINE databases and evaluated following a PRISMA paradigm. For the elite athlete population, eight reports on problem gambling and one report on problem gaming were found. While at least five papers indicated an increased risk of problem gambling in elite athletes compared to the general population, one study from Australia indicated the opposite. Problem gambling was generally more common in male athletes. Knowledge of problem gaming prevalence is thus far limited. It is concluded that increased research in problem gambling and problem gaming in elite athletes is warranted.

Socio-Demographics, Gambling Participation, Gambling Settings, and Addictive Behaviors Associated with Gambling Modes: A Population-Based Study

Online and land-based gambling differ in terms of participation and harms. Multimode gambling has also been distinguished as a separate mode. The current study uses the Finnish Gambling 2019 population study sample of 18–74-year-old past-year gamblers (N = 3,077) to evaluate how these gambling modes differ in terms of socio-demographics, gambling participation, gambling settings, and addictive behaviors. We used land-based gambling as the reference group in a multinomial regression model. Male gender (OR 1.48), age between 18 and 54 (OR 1.88), and high income (OR 1.87) were associated with online gambling. The odds of online gambling were higher among those who gambled at least monthly (OR 1.34) and among those with the highest gambling spending (OR 3.62). Younger age (OR 2.31), high income (OR 1.51), gambling at least four game types (OR 2.96), spending the most money on gambling (OR 4.56), and gambling in at least three gambling settings were associated with multimode gambling. Socio-demographics and gambling participation were indicators of gambling modes. Online gambling was more intensive while multimode gambling was more frequent and versatile than land-based gambling. However, this was not reflected as increased addictive behaviors, probably due to the harmful nature of Finnish land-based gambling.

Gambling-Related Harms for Affected Others: A Finnish Population-Based Survey

Aims This study explores the prevalence of being a past-year affected other (AO) of a problem gambler by gender. The aims were to study the amount and type of gambling-related harms (GRHs) for subgroups of AOs and to distinguish GRH profiles for AO subgroups. Methods A total of 7186 adults aged 18 years and over participated in the Gambling Harms Survey evaluating year 2016. The data were analyzed using descriptive statistics and binary logistic regression. Results Of all respondents, 12.9% were defined as past-year AOs (women 13.7%; men 12.1%). The proportion of affected non-family members (ANFs) was 8.4%, and 5.6% were affected family members (AFMs). AFMs were usually women, and ANFs were usually men. Emotional, relationship, and financial harms were the most common types of harm. The odds of experiencing financial harm were highest for the 18- to 34-year-olds (OR 1.82) and for those whose partner/ex-partner had a gambling problem (OR 3.91). Having a parent/step-parent (OR 1.93) and child/stepchild (OR 3.64) increased the odds of experiencing emotional harm, whereas male gender (OR 0.50) and being an ANF (OR 0.58) decreased emotional harm. Relationship harm was evident for partners/ex-partners (OR 1.97-5.07). Conclusions GRH profiles for AO subgroups varied, which emphasizes the need for effective harm minimization strategies for those in need.