Differences in the Gambling Behavior of Online and Non-online Student Gamblers in a Controlled Laboratory Environment

Delay Discounting in Established and Proposed Behavioral Addictions: A Systematic Review and Meta-Analysis

Steep delay discounting, or a greater preference for smaller-immediate rewards over larger-delayed rewards, is a common phenomenon across a range of substance use and psychiatric disorders. Non-substance behavioral addictions (e.g., gambling disorder, internet gaming disorder, food addiction) are of increasing interest in delay discounting research. Individual studies have reported steeper discounting in people exhibiting various behavioral addictions compared to controls or significant correlations between discounting and behavioral addiction scales; however, not all studies have found significant effects. To synthesize the published research in this area and identify priorities for future research, we conducted a pre-registered systematic review and meta-analysis (following PRISMA guidelines) of delay discounting studies across a range of behavioral addiction categories. The final sample included 78 studies, yielding 87 effect sizes for the meta-analysis. For studies with categorical designs, we found statistically significant, medium-to-large effect sizes for gambling disorder (Cohen’s d = 0.82) and IGD (d = 0.89), although the IGD effect size was disproportionately influenced by a single study (adjusted d = 0.53 after removal). Categorical internet/smartphone studies were non-significant (d = 0.16, p = 0.06). Aggregate correlations in dimensional studies were statistically significant, but generally small magnitude for gambling (r = 0.22), internet/smartphone (r = 0.13) and food addiction (r = 0.12). Heterogeneity statistics suggested substantial variability across studies, and publication bias indices indicated moderate impact of unpublished or small sample studies. These findings generally suggest that some behavioral addictions are associated with steeper discounting, with the most robust evidence for gambling disorder. Importantly, this review also highlighted several categories with notably smaller effect sizes or categories with too few studies to be included (e.g., compulsive buying, exercise addiction). Further research on delay discounting in behavioral addictions is warranted, particularly for categories with relatively few studies.

Parental Acceptance/Rejection Perceptions and Attachment Styles of Men With Online Gambling Disorder

Online gambling disorder has recently emerged as a significant public health issue. Family dynamics play an important role in the development of online gambling disorder. In this research, the aimed to compare the parental acceptance/rejection and attachment styles of individuals with online gambling disorder with a healthy control group. Also, the relationship between parental acceptance/rejection and attachment styles was examined in individuals with online gambling disorder. The study group consisted of 53 male patients with online gambling disorder and 57 healthy controls. The individuals with online gambling disorder perceived more rejection from mothers but especially from fathers than the individuals in the control group. Paternal hostility/aggression and indifference/neglect are determinants of online gambling behavior. The individuals with online gambling disorder had lower levels of secure attachment and higher levels of dismissive and fearful attachment than the individuals in the control group. Both secure attachment style and dismissive attachment style are thought to be determinants of gambling behavior. Mother-father rejection and insecure attachment are important in terms of creating risk for online gambling. Assessment of the effects of maternal and especially paternal rejection in online gambling disorder will be beneficial within the scope of preventive mental health.

A Literature Review and Gap Analysis of Emerging Technologies and New Trends in Gambling

There have been significant changes in the gambling landscape particularly relating to gambling in the digital age. As the gambling landscape changes, regulation of gambling also needs to change. In 2018, the Office of Responsible Gambling in New South Wales, Australia, commissioned a gap analysis to inform their research objectives and priority focus areas. This included an identification of gaps in our understanding of emerging technologies and new trends in gambling. A gap analysis of the peer-reviewed literature published since 2015 was undertaken, identifying 116 articles. The main area of focus was Internet gambling, followed by articles exploring the relationship between video gaming and gambling, the expansion of the sports betting market, Electronic Gambling Machines characteristics and articles exploring new technologies and trends in advertising and inducements. Key gaps related to the need for more research in general, as well as research focusing on subpopulations such as those using different gambling formats, those with varying levels of problem gambling, and vulnerable populations. From a methods perspective, researchers saw the need for longitudinal studies, more qualitative research and improved outcome measures. The development and testing of a public health approach to addressing the harms associated with gambling in these areas is needed.

Current Addiction in Youth: Online Sports Betting

Background: Gambling landscape has changed in recent years with the emergence of online gambling (OG). Greater accessibility and availability of this betting modality can increase the risk of developing a gambling disorder (GD). Online sports betting (OSB) is currently the most common type of OG, but little is known about the clinical characteristics of OSB compared to slot-machine (SM) gamblers, the most common offline gambling disorder. Methods: This was a prospective study conducted between October 2005 and September 2019, and included outpatients diagnosed with GD seen in a Pathological Gambling and Behavioral Addictions referral unit. Only patients with OSB and SM disorders were included. The main objective was to assess the clinical profile of OSB compared to SM gamblers, and to define clinical predictors for developing OSB gambling disorder. Logistic regression was performed to determine the effects of variables on the likelihood of this disorder. Results: Among 1,186 patients attended in our Unit during the study period, 873 patients were included; 32 (3.7%) were OSB gamblers and 841 (96.3%) were SM gamblers. Overall, mean age was 45 ± 13 years and 94.3% were men. Compared to SM patients, OSB patients were younger (34.9 ± 9.5 vs. 45.3 ±13), more frequently single (43.8 vs. 20.6%) and had a university education level (43.8 vs. 4.5%); they were also more frequently non-smokers (18.7 vs. 66.7%) and had fewer psychiatric comorbidities (12.5 vs. 29.4%) than SM gamblers. GD duration before treatment initiation was shorter in OSB patients than in SM gamblers, most of them (81.3 vs. 42.4%) with ≤ 5 years of GD duration. OSB gamblers showed significant differences in weekly gambling expenditure, spending higher amounts than SM patients. Younger age (OR: 0.919; 95% CI: 0.874-0.966), university education level (OR: 10.658; 95% CI: 3.330-34.119), weekly expenditure >100€ (OR: 5.811; 95% CI:1.544-21.869), and being a non-smoker (OR:13.248; 95% CI:4.332-40.517) were associated with an increased likelihood of OSB gambling behavior. Conclusions: We identified different profiles for OSB and SM gamblers. Younger age, university education level, higher weekly expenditure, and non-smoking habit were associated with OSB compared to SM disorders. Prevention strategies should help young people become aware of the severe risks of OSB.

Behavior analysis of virtual-item gambling

From the gambling logs of an online lottery game we extract the probability distribution of various quantities (e.g., bet value, total pool size, waiting time between successive gambles) as well as related correlation coefficients. We view the net change of income of each player as a random walk. The mean-squared displacement of these net income random walks exhibits a transition between a superdiffusive and a normal diffusive regime. We discuss different random-walk models with truncated power-law step lengths distributions that allow us to reproduce some of the properties extracted from the gambling logs. Analyzing the mean-squared displacement and the first-passage time distribution for these models allows us to identify the key features needed for observing this crossover from superdiffusion to normal diffusion.

Self-Reported Losses Versus Actual Losses in Online Gambling: An Empirical Study

Many research findings in the gambling studies field rely on self-report data. A very small body of empirical research also suggests that when using self-report, players report their gambling losses inaccurately. The aim of the present study was to evaluate the differences between objective and subjective gambling spent data by comparing gambler’s actual behavioral tracking data with their self-report data over a 1-month period. A total of 17,742 Norwegian online gamblers were asked to participate in an online survey. Of those surveyed, 1335 gamblers answered questions relating to gambling expenditure that could be compared with their actual gambling behavior. The study found that the estimated loss self-reported by gamblers was correlated with the actual objective loss and that players with higher losses tended to have more difficulty estimating their gambling expenditure (i.e., players who spent more money gambling also appeared to have more trouble estimating their expenses accurately). Overall, the findings demonstrate that caution is warranted when using self-report data relating to amount of money spent gambling in any studies that are totally reliant on self-report data.