ORIGINAL RESEARCH published: 13 January 2021 doi: 10.3389/fpsyt.2020.590554 Current Addiction in Youth: Online Sports Betting Núria Aragay 1,2*, Laia Pijuan 3 , Àngela Cabestany 3 , Irene Ramos-Grille 1,2,4 , Gemma Garrido 2,5 , Vicenç Vallès 1,2,3 and Esther Jovell-Fernández 2,6 1 Pathological Gambling Unit, Department of Mental Health, Consorci Sanitari de Terrassa, Terrassa, Spain, 2 Faculty of Medicine and Health Sciences, Universitat Internacional de Catalunya, Barcelona, Spain, 3 Department of Mental Health, Consorci Sanitari de Terrassa, Terrassa, Spain, 4 Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona, Spain, 5 Community Mental Health Service, Department of Mental Health, Consorci Sanitari de Terrassa, Terrassa, Spain, 6 Department of Epidemiology, Consorci Sanitari de Terrassa, Terrassa, Spain 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 Edited by: Susana Jiménez-Murcia, characteristics of OSB compared to slot-machine (SM) gamblers, the most common Bellvitge University Hospital, Spain offline gambling disorder. Reviewed by: Methods: This was a prospective study conducted between October 2005 and Anders Hakansson, Lund University, Sweden September 2019, and included outpatients diagnosed with GD seen in a Pathological Marco Di Nicola, Gambling and Behavioral Addictions referral unit. Only patients with OSB and SM Catholic University of the Sacred Heart, Italy disorders were included. The main objective was to assess the clinical profile of OSB Marta Sancho, compared to SM gamblers, and to define clinical predictors for developing OSB gambling Hospital de la Santa Creu i Sant disorder. Logistic regression was performed to determine the effects of variables on the Pau, Spain likelihood of this disorder. *Correspondence: Núria Aragay Results: Among 1,186 patients attended in our Unit during the study period, 873 naragay@cst.cat patients were included; 32 (3.7%) were OSB gamblers and 841 (96.3%) were SM Specialty section: gamblers. Overall, mean age was 45 ± 13 years and 94.3% were men. Compared to This article was submitted to SM patients, OSB patients were younger (34.9 ± 9.5 vs. 45.3 ±13), more frequently Addictive Disorders, single (43.8 vs. 20.6%) and had a university education level (43.8 vs. 4.5%); they a section of the journal Frontiers in Psychiatry were also more frequently non-smokers (18.7 vs. 66.7%) and had fewer psychiatric Received: 01 August 2020 comorbidities (12.5 vs. 29.4%) than SM gamblers. GD duration before treatment initiation Accepted: 14 December 2020 was shorter in OSB patients than in SM gamblers, most of them (81.3 vs. 42.4%) with ≤5 Published: 13 January 2021 years of GD duration. OSB gamblers showed significant differences in weekly gambling Citation: Aragay N, Pijuan L, Cabestany À, expenditure, spending higher amounts than SM patients. Younger age (OR: 0.919; Ramos-Grille I, Garrido G, Vallès V 95% CI: 0.874–0.966), university education level (OR: 10.658; 95% CI: 3.330–34.119), and Jovell-Fernández E (2021) Current weekly expenditure >100e (OR: 5.811; 95% CI:1.544–21.869), and being a non-smoker Addiction in Youth: Online Sports Betting. Front. Psychiatry 11:590554. (OR:13.248; 95% CI:4.332–40.517) were associated with an increased likelihood of OSB doi: 10.3389/fpsyt.2020.590554 gambling behavior. Frontiers in Psychiatry | www.frontiersin.org 1 January 2021 | Volume 11 | Article 590554 Aragay et al. Online Sports Betting v. Slot Machine 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. Keywords: gambling disorder, online gambling, sports betting, offline gambling, slot machine, predictors INTRODUCTION MATERIALS AND METHODS Gambling disorder (GD) is a gambler’s inability to control Study Design their gambling behavior despite the negative consequences that This was a prospective study conducted from October 2005 this entails. The latest version of the Diagnostic and Statistical to September 2019 among outpatients seen in a Pathological Manual of Mental Disorders, Fifth Edition (DSM-5), includes this Gambling and Behavioral Addictions Unit from a referral disorder within the “Addictive and substance-related disorders,” population of 1.3 million. Most patients are referred from and describes it as “a maladaptive, persistent and recurrent primary care physicians within the public healthcare system. behavior that disrupts personal, family and/or work” (1). All patients were diagnosed with GD according to the DSM- In a systematic review of 69 studies from different countries, IV-TR, or DSM-5 when appropriate (1, 15). For this study, adult gambling prevalence was between 0.7 and 6.5% (2). only patients with OSB and SM disorders were included. All However, most of these epidemiological studies were based on participants provided written or oral informed consent. The offline gambling samples. Evidence on online gambling practices study was conducted in accordance with the Declaration of is scarce, but prevalence is estimated to range from 1 to 13% of the Helsinki and was approved by the Ethics Committee of Consorci general population (3, 4). In a study conducted in Spain, Choliz Sanitari de Terrassa (Barcelona, Spain). All patients were treated et al. found a prevalence of 0.56% in adults, and 1.04% in young and followed-up by a team of psychologists, supervised by a people (5). senior clinical psychologist with more than 15 years’ experience Gambling was legalized in Spain in 1977. Slot-machines in the diagnosis and treatment of GD. (SM) appeared in 1981, and rapidly became one of the most The therapeutic program has been described elsewhere widely used forms of gambling, and the cause of most gambling and consists of individualized outpatient cognitive-behavioral problems (6). therapy for PG, aimed at achieving abstinence from gambling. The gambling market has changed in recent years due to the Treatment was protocolized, and the main techniques used were emergence of new technologies and online gambling (OG) (6, 7). psychoeducation, motivational interviewing, stimulus control, The possibility of gambling from home and betting with “virtual cognitive restructuring and relapse prevention (16, 17). money” has increased the accessibility, frequency, disinhibition, The main objective was to assess the clinical profile of OSB and lack of control of OG (8). All these features, as well as the gamblers compared with SM gamblers, and to define clinical diversification in different types of online games, can increase predictors for developing OSB. the risk of developing problems derived from OG (9). There are different types of OG, such as sports betting, poker, casino games, Variables bingo, and gambling machines, but online sports betting (OSB) is Gambling Variables currently the most common OG modality. We recorded the type of game (OSB or SM), age of gambling The advertising and marketing strategies used by the online behavior onset, duration of GD, frequency of gambling, and gaming sector provide an unreal image of OSB as a lucrative weekly gambling expenditure. leisure activity that can bring economic and social success to the gambler. It establishes a relationship between fun, Sociodemographic and Clinical Variables sports, competition, friendship, and other values associated with We recorded age, gender, marital status, education level, and adolescence and youth. All these characteristics have contributed employment status. Psychiatric comorbidities were assessed to a better positive social perception of OSB (9, 10). according to DSM-IV-TR or DMS-5 (affective disorder, psychotic Some previous studies have compared general samples of disorder, anxiety disorder, adaptive disorder, attention deficit online and offline gamblers (11–13). However, little is known disorder, and substance use disorder). about specific comparisons between OSB and land-based SM gamblers. In fact, these were the most common gambling modes Statistical Analysis in 2019 in Spain (31 and 21%, respectively) (14). Because of A descriptive statistical analysis was performed for all categorical their high prevalence, particularly among young people, these and continuous variables and expressed as proportions or forms of gambling are an important health problem that must be means with standard deviations (SD), respectively. We used addressed and prevented (7). So we aimed to compare gambling chi-square or Fisher’s exact tests to compare categorical data behavior characteristics between OSB and SM gamblers, and to between groups. Continuous variables were compared using the define clinical predictors for OSB. Student t-test. We used two-tailed unpaired t-tests to compare Frontiers in Psychiatry | www.frontiersin.org 2 January 2021 | Volume 11 | Article 590554 Aragay et al. Online Sports Betting v. Slot Machine normally distributed continuous data between two groups, performed a post-hoc analysis including gamblers who started and the Mann-Whitney U test for non-normally distributed gambling at ≤25 years of age. P-values < 0.05 were considered continuous data comparisons. To control the effect of age statistically significant. on the differences found between OSB and SM gamblers, we Logistic regression analyses were performed to identify associated risk factors for OSB gambling and presented as odds ratios (OR) with 95% confidence intervals (95% CI). For the manual backward stepwise multivariate logistic regression TABLE 1 | Bivariate analysis comparing online sports betting and slot machine model, we assessed variables that had a significant p level <0.05 in gamblers. univariate analyses. The Hosmer and Lemeshow test was applied; Variable Online sports Slot machine p-value betting gamblers gamblers (n = 32) (n = 841) TABLE 2 | Bivariate analysis comparing online sports betting and slot machine Age, mean (SD) 34.9 ± 9.5 45.3 ± 13.0 0.000 gamblers with gambling onset before 25 years of age. Gender, n (%) Male 31 (96.9%) 792 (94.2%) 1.000 Variable Online sports Slot machine p-value betting gamblers gamblers Female 1 (3.1) 49 (5.8%) (n = 18) (n = 438) Marital status, n (%) Single 14 (43.8%) 173 (20.6%) 0.002 Age, mean (SD) 29.72 ± 7.6 40.07 ± 10.9 0.000 With partner 18 (56.3%) 668 (79.4%) Gender, n (%) Stable partner 14 (43.8%) 462 (54.9%) Male 17 (94.4%) 426 (97.2%) 0.412 Separated 2 (6.3%) 129 (15.3%) Female 1 (5.5%) 12 (2.7%) Divorced 2 (6.3%) 64 (7.6%) Marital status, n (%) Widowed 0 13 (1.5%) Single 13 (72.2%) 114 (26%) 0.000 Education level, n (%) With partner 5 (27.7%) 324 (74%) University 14 (43.8%) 38 (4.5%) 0.000 Stable partner 5 (27.7%) 218 (49.8%) Non-university 18 (56.3%) 776 (92.3%) Separated 0 88 (20.1%) Primary/Secondary 18(56.3%) 708 (84.2%) Divorced 0 18 (4.1%) Illiterate 0 68 (8.1%) Widowed 0 0 Employment status, n (%) Education level, n (%) Employed 22 (68.8%) 441 (52.4%) 0.077 University 9 (50%) 21 (4.8%) 0.000 Unemployed 10 (31.3%) 393 (46.7%) Non-university 9 (50%) 405 (92.5%) Student 5 (15.6%) 2 (0.2%) Primary/Secondary 9 (50%) 378 (86.3%) Age at gambling onset, mean (SD) 26.41 ± 9.5 26.52 ± 11 0.956 Illiterate 0 27 (6.2%) Duration of GD before treatment, n (%) Employment status, n (%) ≤5 years 26 (81.3%) 357 (42.4%) 0.000 Employed 11 (61.1%) 269 (61.4%) 0.950 >5 years 6 (18.8%) 477 (56.7%) Unemployed 7 (38.9%) 166 (37.9%) 6–10 years 5 (15.6%) 178 (21.2%) Student 5 (27.8%) 2 (0.5%) >10 years 1 (3.1%) 299 (35.6%) Age at gambling onset 19.72 ± 3.4 19.28 ± 3.1 0.559 Daily frequency of gambling, n (%) 16 (50%) 344 (41%) 0.204 Length of GD before treatment, n (%) Gambling expenditure per week, n (%) ≤5 years 16 (88.9%) 176 (41.2%) 0.000 ≤100e/week 6 (18.8%) 377 (44.8%) 0.003 >5 years 2 (11.1%) 261 (59.6%) >100e/week 22 (68.8%) 372 (44.2%) 6–10 years 1 (5.6%) 99 (22.6%) >500e/week 8 (25%) 82 (9.8%) >10 years 1 (5.6%) 162 (37%) Psychiatric comorbidity, n (%) 4 (12.5%) 247 (29.4%) 0.039 Daily frequency of gambling, n (%) 9 (50%) 180 (41.09%) 0.630 Affective disorder 0 (0%) 44 (5.2%) 0.400 Gambling expenditure per week, n (%) Psychotic disorder 0 (0%) 48 (5.7%) 0.251 ≤100e/week 3 (16.7%) 190 (43.4%) 0.013 Anxiety disorder 1 (3.1%) 24 (2.9%) 0.612 >100e/week 15 (83.3%) 204 (46.6%) Adaptive disorder 1 (3.1%) 40 (4.8%) 1.000 >500e/week 5 (27.7%) 48 (11%) Attention deficit disorder 1 (3.1%) 17 (2%) 0.493 Psychiatric comorbidity, n (%) 2 (11.1%) 123 (28.1%) 0.175 Substance use disorder, n (%) Substance use disorder, n (%) Alcohol dependence 3 (9.4%) 186 (22.1%) 0.200 Alcohol dependence 1 (5.6%) 113 (25.8%) 0.192 Tobacco dependence 6 (18.8%) 561 (66.7%) 0.000 Tobacco dependence 4 (22.2%) 307 (70.1%) 0.000 Cannabis dependence 0 56 (6.7%) 0.400 Cannabis dependence 0 41 (9.4%) 0.625 Cocaine dependence 0 42 (5%) 0.629 Cocaine dependence 0 25(5.7%) 1 The blod values means “statistically significant values”. The blod values means “statistically significant values”. Frontiers in Psychiatry | www.frontiersin.org 3 January 2021 | Volume 11 | Article 590554 Aragay et al. Online Sports Betting v. Slot Machine a p-value of 0.05 or higher indicated that the model fitted well a Nagelkerke R2 of 55.6%. Younger age (OR: 0.919; 95% CI: with the data. The variance inflation factors (VIF) of each variable 0.874–0.966), university education level (OR: 10.658; 95% CI: included in the final model were computed, and a VIF of >10 3.330–34.119), weekly expenditure >100e (OR: 5.811; 95% CI: indicated that multicollinearity of the corresponding variable was 1.544–21.869) and being a non-smoker (OR: 13.248; 95% CI: high. Analyses were performed using SPSS, version 25 for PC 4.332–40.517) were associated with an increased likelihood of (SPSS Inc., Chicago, IL, USA). OSB gambling behavior (Table 3). RESULTS DISCUSSION Among 1,186 patients attended in our Unit during the study This is the first study comparing OSB with SM gamblers, in which period, 172 patients were excluded due to other behavioral we aimed to define clinical predictors for OSB. The results of our addictions and 141 patients due to other types of gambling. study reveal a different profile between OSB and SM gamblers. Finally, 873 patients were included: 32 (3.7%) were OSB gamblers We also found that younger age, university education level, and 841 (96.3%) were SM gamblers. Overall, mean age was 45 ± gambling expenditure of more than 100e per week and being a 13 years and 94.3% were men. Most patients had a stable partner non-smoker increases the likelihood of being an OSB gambler. (54.5%), had completed primary or secondary education (83.2%), In accordance with previous studies, almost all OSB gamblers were employed (53%) and were smokers (65%). Mean age for from our study were male, single and had a higher education level gambling onset was 26.5 ± 10.9 years. Most patients (55.3%) had (9, 12). We also found lower tobacco use and fewer psychiatric a gambling history of >5 years. comorbidities in OSB compared to SM gamblers. The smoking Compared to SM patients, OSB patients were younger (34.9 ± prevalence in our OSB sample is slightly lower than in previous 9.5 vs. 45.3 ± 13), more frequently single (43.8 vs. 20.6%) and studies among online gamblers (18–20). This could be because with university education level (43.8 vs. 4.5%); they were also almost half of OSB gamblers from our study have reached a more frequently non-smokers (18.8 vs. 66.7%) and had fewer university education level that has shown a negative association psychiatric comorbidities (12.5 vs. 29.4%) than SM gamblers. with smoking prevalence (21). The presence of psychiatric Duration of the GD was shorter in OSB patients than in SM comorbidities has a negative effect on offline gambling outcomes gamblers, most of them (81.3 vs. 42.4%) with ≤5 years of (16, 22). However, the influence of this variable on OSB gambling GD duration before treatment initiation. OSB gamblers showed is controversial (23, 24). In fact, although OSB gamblers in our significant differences in their weekly gambling expenditure, study exhibit severe gambling behavior (spending more money spending higher amounts than SM patients. Comparison on gambling and developing GD faster than SM gamblers), they between OSB and SM gamblers is shown in Table 1. presented a lower prevalence of psychiatric comorbidity than SM We aimed to assess the impact of OSB compared to SM among gamblers (12.5 vs. 29.4% respectively). This could be related to those who started gambling when young. We performed a post- the type of gambling, as OG was more addictive than offline hoc analysis in the subgroup of gamblers who started gambling gambling and could induce more deleterious behavior (5). More at ≤25 years old. Compared to SM gamblers, OSB gamblers studies are needed in online gamblers to assess the effect of were more frequently single (72.2 vs. 26%) and with university psychiatric comorbidity on the course of the disorder and on education level (50 vs. 4.8%). In addition, OSB gamblers had response to treatment. higher weekly gambling expenditure and shorter length of GD In our study, being younger and university education level before starting treatment compared to SM gamblers (88.9% of were predictors for OSB. These results are in line with previous OSB vs. 41.2% of SM gamblers reported GD onset ≤5 years) studies (9). Sports betting associate new technologies with (Table 2). an unreal concept of sport, and is becoming a common The regression model used to determine the effects of variables activity amongst sports audiences, especially youth. Furthermore, on the likelihood for OSB or SM gambling included four because knowledge of sports is widespread amongst the general out of the 18 predictor variables (age, education level, weekly population, and young people are “tech-savvy,” OSB gamblers expenditure and tobacco use) with an accuracy of 97.5% and may have a false perception of a higher probability of winning TABLE 3 | Multivariate analysis predicting online sports betting and slot machine gamblers. Variable beta SE Wald P OR 95% CI Lower Upper Age −0.805 0.026 11.036 0.001 0.919 0.874 0.966 University education level 2.366 0.594 15.896 0.000 10.658 3.330 34.119 >100e gambling expenditure per week 1.760 0.676 6.773 0.009 5.811 1.544 21.869 Non-smoker 2.584 0.570 20.525 0.000 13.248 4.332 40.517 OR, odds ratio; CI, confidence interval. Frontiers in Psychiatry | www.frontiersin.org 4 January 2021 | Volume 11 | Article 590554 Aragay et al. Online Sports Betting v. Slot Machine with a lower influence of chance than in other types of games. the gambling landscape has changed, regulation of gambling All these characteristics have contributed to change gambling as also needs to change. Effective public health policies are needed a common leisure activity among young people. Thus, OSB has to develop comprehensive regulatory frameworks that protect been added to other inherent risk behaviors of young people, young people, including university students, from this excessive where there is a higher risk of developing addiction problems exposure to OG (31). (25). Adolescence is a critical period for brain development, Our study has some limitations that should be mentioned. with an imbalance between emotional (reward motivation) Firstly, because of its descriptive nature, our sample groups and cognitive (executive control) processes, and this is why had an unbalanced sample size. This could be attributed to adolescents are sensitive to the effect of alcohol and other the long study period, which started in 2005, while OSB psychoactive substances (26). Furthermore, some studies have gambling disorder developed some years later. Secondly, the lack demonstrated that earlier onset of the disorder is predictive of of a specific comparison between OSB and land-based sports gambling severity (27). These results underscore the need to early bettors. However, the accessibility and availability of gambling recognition and to design preventive interventions focused on on electronic devices make it hard to confirm which patients young people, especially university groups, and also adolescents are exclusively land-based sports bettors, and to compare both in order to raise awareness of the risks of OSB gambling, and groups. Thirdly, other variables such as personality traits were to avoid an escalation of GD once they reach the legal age for not included in the study. Finally, our study has an observational betting (9) design, so our results must be confirmed and validated in In our study, although both groups began gambling at a further studies. similar age (26.4 years for OSB gamblers vs. 26.5 years for SM In conclusion, a different profile between OSB and SM gamblers), most OSB gamblers develop GD within the first 5 gamblers has been described. Younger age, university education years of gambling onset (81.3% for OSB gamblers vs. 42.4% level, higher weekly expenditure, and non-smoking habit were for SM gamblers). Moreover, OSB gamblers spend more money associated with OSB compared to SM disorders. These variables than SM gamblers, and amounts of more than 100e per week should be included in prevention strategies designed to raise increase the likelihood of being an OSB gambler. This higher awareness among young people of the severe risks of OSB and expenditure and rapid progression of GD also appeared when we help them avoid this behavior. selected those gamblers who had started gambling at ≤25 years. These findings corroborate the negative effect of the structural DATA AVAILABILITY STATEMENT characteristics of OG. The availability 24/7 for gambling at home or remotely from an electronic device with “virtual money” The raw data supporting the conclusions of this article will be increases accessibility and loss of control during gambling (8, 9, made available by the authors, without undue reservation. 25). Montes et al., in a laboratory environment study on poker, found that online gamblers play more hands and incur higher ETHICS STATEMENT losses than non-online gamblers (28). These results support the finding that OG induces more deleterious behavior, and could The study was conducted in accordance with the Declaration of explain why OSB gamblers seek treatment earlier than other types Helsinki and was approved by the Ethics Committee of Consorci of gamblers, as we found. Sanitari de Terrassa (Barcelona, Spain). The patients/participants Furthermore, current massive marketing of OG, mainly provided their written informed consent to participate in during sport events, is becoming aggressive and contributing this study. to increasing OG problems (29). Advertising of gambling only highlighting an unrealistic ease of winning without the real AUTHOR CONTRIBUTIONS possibilities of losing can contribute to perceiving gambling as a desirable activity among young people. Moreover, this All authors have participated in the preparation of the deceptive image contributes to game incitement among those manuscript and have approved the final version of risky gamblers, especially among youth (30). The focus of OG the manuscript. marketing on young people has contributed to increasing the incidence of OSB gambling disorder in this group, as we found ACKNOWLEDGMENTS when comparing SM gamblers. The impact of OSB advertising and marketing among young The authors thank Dr. Carlos Garcia Forero, from the Faculty people deserves special attention. Although most countries have of Medicine and Health Sciences, Universitat Internacional laws that ban minors from gambling, controlling their access de Catalunya, Barcelona, Spain, for his advice in the to the game is not easy and requires further efforts (25). As Statistical Analysis. REFERENCES 2. Calado F, Griffiths M.D. Problem gambling worldwide: an update and systematic review of empirical research (2000- 1. 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Problem gambling and substance use in patients attending copyright owner(s) are credited and that the original publication in this journal community mental health services. J Behav Addict. (2017) is cited, in accordance with accepted academic practice. No use, distribution or 6:678–688. doi: 10.1556/2006.6.2017.077 reproduction is permitted which does not comply with these terms. Frontiers in Psychiatry | www.frontiersin.org 6 January 2021 | Volume 11 | Article 590554