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.

Women with compulsive buying or gambling disorder: Similar profiles for different behavioural addictions.

The aim of the present study was to examine the differences in sociodemographic and clinical characteristics of 104 women diagnosed with compulsive buying behaviour (CBB = 55) or gambling disorder (GD = 49) treated at three public hospitals unit specialized in behavioural addictions from January 2004 to December 2015. Significant between-group differences in sociodemographic variables were observed for cohabitation status (living with a partner or not) and educational level, with a higher percentage of women in the GD group cohabiting (х2 (1), p = .029). By contrast, the CBB group had a significantly higher educational level (х2 (1) = 7.4, p = .007). There were no significant differences between the groups in age of onset, age at treatment initiation, age at the onset of behavioural problems, or in the years elapsed until presenting addiction problems. However, there were significant between-group differences in the amount of money spent weekly (F (1.100) = 4.9, p = .028), with women in the CBB group spending on average €289.4/week (SD, 412.4) versus €151/week (SD, 141.23) in the GD group. The CBB group had significantly more depressive disorders compared to the GD group (х2(1) = 5.4, p = .020). In contrast, the GD group presented significantly more tobacco use than the CBB group (х2(1) = 1.19, p = .000). This study suggests that women with CBB or GD share more characteristics than differences and the treatment approaches must take into account gender related factors.