Psychopathogical status and personality correlates of problem gambling severity in sports bettors undergoing treatment for gambling disorder Journal of Behavioral Addictions  SUSANA JIMENEZ-MURCIA 1,2,3p  , MONICA  GIMENEZ 2 , 10 (2021) 3, 422–434 1,5  ROSER GRANERO , HIBAI LOPEZ-GONZALEZ ,  2  MONICA  GOMEZ-PE ~ 2, LAURA MORAGAS2, NA Special Section on  sports and esports ISABEL BAENAS1,2, AMPARO DEL PINO-GUTIERREZ 1,2,6 , 2 1,2 betting ESTER CODINA , TERESA MENA-MORENO , EDUARDO VALENCIANO-MENDOZA2,4, DOI: BERNAT MORA-MALTAS2, SUSANA VALERO-SOLIS2, 10.1556/2006.2020.00101  SANDRA RIVAS-PEREZ 2 , ELIAS GUILLEN-GUZM   7, AN © 2020 The Author(s) JOSE M. MENCHON 2,3,4 and  FERNANDO FERNANDEZ-ARANDA1,2,3 1 CIBER Fisiopatologıa Obesidad y Nutrici on (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain FULL-LENGTH REPORT 2 Department of Psychiatry, University Hospital of Bellvitge-IDIBELL, Barcelona, Spain 3 Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain 4 CIBER Salud Mental (CIBERSam), Instituto de Salud Carlos III, Madrid, Spain 5 Department of Psychobiology and Methodology, Autonomous University of Barcelona, Barcelona, Spain 6 Department of Public Health, Mental Health and Perinatal Nursing, School of Nursing, University of Barcelona, Barcelona, Spain 7 Departament of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic Barcelona, Barcelona, Spain Received: April 21, 2020 • Revised manuscript received: August 3, 2020; November 30, 2020 • Accepted: December 2, 2020 Published online: March 2, 2021 ABSTRACT Background and aims: Sports betting has been barely explored independently from other gambling behaviors. Little evidence is available regarding the factors affecting its severity in a clinical sample. The current study explores new determinants for sports betting severity in Spain by the inclusion of psy- chopathological distress and personality factors. Methods: A sample of 352 Spanish sports bettors un- dergoing treatment for gambling disorder was recruited. Multiple regression models were used to evaluate the effects of sociodemographic variables, the age of onset of gambling behavior, the global psychopathological distress (SCL-90R GSI) and the personality profile (TCI-R) on sports betting severity and their influence over frequency (bets per episode) and debts due to gambling. Results: We found that older age, higher psychopathological distress, lower self-directedness level, and higher novelty seeking level were predictors of gambling severity in Spanish sports bettors. The highest betting frequency was found in men, with the lowest education levels but the highest social status, the highest psychopatho- logical distress, reward dependence score, and self-transcendence trait and the lowest persistence score. p Debts were also associated to higher score in cooperativeness as well as older age. Discussion and con- Corresponding author. E-mail: sjimenez@bellvitgehospital.cat clusions: Our findings call for further exploration of factors affecting sports betting severity regarded as a separate gambling entity subtype, as some of the traditional factors typically found in gamblers do not apply to sports bettors or apply inversely in our country. Consequently, sports bettors might deserve specific clinical approaches to tackle the singularities of their gambling behavior. Unauthenticated | Downloaded 11/25/22 04:28 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 422–434 423 KEYWORDS recent examples in the literature in Spain. In a sample of gambling, sports betting, multiple regression, personality, psychopatho- young Spanish students, the frequency of participation in logical distress, severity sports betting was high, with 42.6% of the sample having placed sports bets at least once (Labrador & Vallejo-Ach on, 2020). In the same vein, a study by Molinaro et al. (2018) carried out across 33 European countries, showed that un- INTRODUCTION derage gambling behavior was a really alarming issue. They observed that last year gambling of 16 year-old students was Gambling problems emerge in multiple forms depending, 22.6% (16.2% online and 18.5% land-based). Comparing this among other things, on the gambling type gamblers become age to the legal gambling age in whichever country in Europe involved in (Stevens & Young, 2010). The development of (18 years old and up, and even higher in some exceptions gambling disorder (GD) is also sensitive to situational and where the legal age increases up to 21, 23 or 25), it is clear structural factors of gambling products [e.g., game fre- that a large proportion of 16 year olds gambling are likely to quency, accessibility, game duration, reward schedule (Parke be doing so illegally (https://gamblersdailydigest.com/ & Griffiths, 2007)] that might precipitate the onset of gambling-age-around-the-world/). Adolescents and young gambling problems, make it more difficult for gamblers to sports fans are an extremely vulnerable group to develop discontinue gambling, or relapse. gambling problems (Gassman, Emrich, & Pierdzioch, 2012). The expansion of sports betting and gambling advertising Young people are highly exposed to advertising, through during sport-related events is a relatively recent fact various channels, which reduces their perception of risk of compared to other gambling activities. In Western regions this activity (Milner, Hing, Vitartas, & Lamont, 2013). Sports (i.e., North America, Australia, and Europe) sports betting is betting represents important public health concerns, as well quite prevalent, especially due to the increase in online access as serious psychological and psychopathological gambling- (Gainsbury, Russell, Hing et al., 2015). In some countries related harms (Winters & Derevensky, 2019). In summary, sports betting appears to be the fastest-growing form of considering the distinct risk factors involved in sports gambling, doubling in popularity over the last decade betting, a singular approach to this gambling type seems (Gainsbury, Russell, Hing et al., 2015). A British annual appropriate (Wicker & Soebbing, 2013). report from the Gambling Commission stated that sports However, little is known about the potential factors betting participation notably increased during 2016 (Sullivan, predicting, maintaining or worsening sports betting in 2018). In fact, given the global nature of online sports betting, particular. Most of the literature evaluates gambling prob- combined with the pervasiveness of gambling advertising, lems in general, rather than those specifically related to sponsorships, with exposure to promotions everywhere and sports betting. The few papers focused on risk factors of from a young age (Nyemcsok et al., 2018; Pitt, Thomas, sport betting showed that bettors were mainly young people, Bestman, Stoneham, & Daube, 2016), sports betting has more engaged sports bettors and gamblers in general, with a arguably become an inherently normal component of sport. money-oriented motivation, higher erroneous cognitions Consequently, a very recent study based on interviews found and gambling urges, alcohol abuse and lower self-control that 78% of young people under the age of 17 and 86% of levels (Russell, Hing, & Browne, 2019). Some authors have adults thought that betting had become a normal part of suggested that singular risk factors such as the combination sport (Djohari, Weston, Cassidy, Wemyss, & Thomas, 2019). of skill, knowledge and chance in sports betting products It is not surprising, then, that betting on sports constitutes a might influence the minimization of risks by society and its huge global business that generates a large volume of money. widespread acceptance (Cantinotti, Ladouceur, & Jacques, The 34th edition of the Australian Gambling Statistics re- 2004; Lopez-Gonzalez, Griffiths, & Estevez, 2020a). The ported an increase of 15% in total sports betting disburse- evaluation of the predictors of impulsive sports betting ment in 2016–2017 («Gambling : Australian gambling behavior showed that higher trait impulsiveness was related statistics | Queensland Government Statistician’s Office», to higher problem gambling severity (Hing, Lamont, Vitar- 2018). Similar statistics from Europe estimated the global tas, & Fink, 2015; Hing, Li, Vitartas, & Russell, 2018; Hing, online gambling gross revenue reaching approximately 25 Russell, Vitartas, & Lamont, 2016). Also, a relationship be- billion euros from 2017 to 2020, mostly generated by sports tween sports betting severity and a higher approval of all betting, lottery and casinos («Gambling industry in Europe: gambling promotional techniques has been reported (Hing Statistics & Facts | Statista», 2019). et al., 2015). Although the scientific literature regarding sports betting In conclusion, having in mind the social acceleration of is incipient, there is a consistent idea that sports betting, sports betting, and its direct link with an increase in other especially the online form, is rapidly surpassing other forms gambling behaviors, the potential factors affecting sports of gambling in terms of participation (European Gaming & betting severity warrant specific attention, especially given Betting Association, 2018). In this sense, it is a matter of the relationship between bettors’ impulsiveness response growing concern how sports betting might become ‘a and severity of gambling (Deans, Thomas, Daube, & Der- gateway drug’ causing younger generations to familiarize evensky, 2017; Hing, Russell, Tolchard, , & Nower, 2016; with gambling and transition from there to other forms of Russell, Hing, Browne, Li, & Vitartas, 2018; Thomas, Lewis, gambling and/or gaming (Zendle & Cairns, 2018). We have McLeod, & Haycock, 2012). Severity of online sports bettors Unauthenticated | Downloaded 11/25/22 04:28 PM UTC 424 Journal of Behavioral Addictions 10 (2021) 3, 422–434 has been related to a more positive response, attitude and Measures disposition to sports gambling advertising, demonstrating a greater likelihood of using the sponsored products (Hing, Diagnostic Questionnaire for Pathological Gambling (ac- Russell, Lamont, & Vitartas, 2017). Internet-based sports cording to the Diagnostic and Statistical Manual of Mental gambling severity has been directly associated with the Disorders [DSM] criteria) (Stinchfield, 2003). This diag- amount of time dedicated to discuss betting before placing nostic questionnaire allows to assess the presence of GD bets, and the use of other sports betting-specific online through 19-items based on the DSM taxonomy [for the gambling features (Lopez-Gonzalez, Estevez, & Griffiths, DSM-IV-TR, text revision (APA, 2000), and the DSM-5 2019). A very recent study of in-play bettors showed that versions (APA, 2013)]. The Spanish adaptation of the scale this condition was strongly associated to problem gambling achieved good psychometric properties (Cronbach alpha severity (Lopez-Gonzalez, Griffiths, & Estevez, 2020b). A a 5 0.81 calculated for the general population and a 5 0.77 previous study that found that the severity of sport bettors in for the clinical sample; Jimenez-Murcia et al., 2009). In this general (not only online) was directly related to being male, study, the total number of DSM-5 criteria for GD was of a young age, unmarried, with higher education levels, analyzed as a dimensional variable of severity level. Cron- working or studying full-time, engaging in different forms of bach’s alpha in the present sample was 0.797. gambling, with a less planned approach to betting, and Temperament and Character Inventory-Revised (TCI-R) frequently watching both live and televised sporting events (Cloninger, Przybeck, Svrakic, & Wetzel, 1994). This ques- (Hing, Russell, Vitartas et al., 2016). tionnaire contains 240 items for measuring personality traits While more data is available concerning how severity structured in 7 personality dimensions: 4 are dimensions strongly predicts greater intended frequency of sports related to temperament (novelty seeking, harm avoidance, betting (Hing, Lamont, Vitartas, & Fink, 2014), little is reward dependence and persistence; consistency for each known about the factors affecting such severity. More spe- dimension in our sample was a 5 0.750, a 5 0.841, a 5 cifically, is there any psychopathological and/or personality 0.795, a 5 0.900, respectively) and 3 were character di- aspect that may be affecting sports betting severity? mensions (self-directedness, cooperativeness and self-tran- Furthermore, most of the aforementioned studies rely on scendence; consistency for each dimension in our sample community level samples and problem gambling screening was a 5 0.899, a 5 0.863, a 5 0.859, respectively). For the tools but do not explore sports betting severity in the context current study, the Spanish version of TCI-R was used of a clinical setting. The current study seeks to address the (Gutierrez-Zotes et al., 2004). lack of research in Spain concerning factors directly affecting Symptom Checklist-Revised (SCL-90-R) (Derogatis, 1975). sports betting severity, by a multiple regression approach. The SCL-90-R is a 90-item test that evaluates different psy- More purposely, the present study aims to examine the as- chological problems and psychopathological symptoms. The sociation of different sociodemographic and clinical vari- test measures different primary symptom dimensions: so- ables, including global psychopathological distress and the matization, obsession-compulsion, interpersonal sensitivity, personality profile, with sports betting severity. In addition, depression, anxiety, hostility, phobic anxiety, paranoid idea- models exploring the statistical predictors of debts related to tion, and psychoticism. This instrument also includes three gambling were also carried out. With this, we provide a global indices: (1) a global severity index (GSI), aimed to comprehensive approach to variables affecting sports betting measure global psychological distress, (2) a positive symptom severity in a large sample of Spanish bettors undergoing distress index (PSDI), to evaluate the intensity of symptoms, treatment for gambling disorder, assessing for the first time and (3) a positive symptom total (PST). For the current in literature which and how psychopathological distress and study, the scale validated in a Spanish population (Derogatis, personality aspects may predict sports betting severity. 2002) was used. The GSI, PSDI and PST present an excellent internal consistency (a 5 0.979). The primary symptoms present an internal consistency a ≥ 0.800 in all cases. South Oaks Gambling Screen (SOGS) (Lesieur & Blume, METHODS 1987). Gambling behavior was measured with this self- report gambling questionnaire. It contains 20 items (the Participants total score ranges from 0 to 20) based on DSM-III (APA, This study examines treatment-seeking Spanish adult pa- 1980) and DSM-III-R (APA, 1987) criteria. We used the tients (n 5 352) whose reported primary gambling activity is Spanish validation of this questionnaire (Echebur ua, Baez, sports betting. The sample was recruited at the Pathological Fernandez-Montalvo, & Paez, 1994), which showed a good Gambling Unit of Bellvitge University Hospital of Bellvitge internal consistency (0.717) in the current sample. from 2005 until now. Patients were consecutively included Statistical analysis in the study, excluding those who did not have an adequate educational level or some kind of cognitive disability that Statistical analysis was carried out with Stata16 for Windows made them unable to complete the self-report measures of (Stata-Corp, 2019). Multiple regression models estimated the the study. Only patients who sought treatment for sports specific capacity of the sociodemographic variables, the age of betting as their primary health concern were admitted to this onset of the sports betting activity, the global psychopatho- study. logical distress (SCL-90R GSI) and the personality profile Unauthenticated | Downloaded 11/25/22 04:28 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 422–434 425 (TCI-R) on the criteria measuring the gambling severity. analyzed in this work. Access to sports betting was through Logistic regression was used for the dependent variable Internet platform. The sample comprised 339 men (96.3%) “presence of debts related with the gambling behavior” and 13 women (3.7%), and the mean age was 32.1 years-old [defined as a binary variable (yes versus no)], and negative (standard deviation [SD] 5 9.6, range 14–70 years). Most binomial regression was used for the dependent variables participants achieved secondary or less education levels defined as count variables (DSM-5 total criteria for GD, (82.4%), were single (61.4%) or married (30.1%), employed SOGS total, bets per episode and debts due to the gambling). (66.8%), and were into mean-low to low social position So, the presence of debt was explored in two ways: as a indexes (72.1%). The mean age for the onset of sports dichotomous variable (yes/no) and as a quantitative variable betting problems was 25 (SD 5 7.6) years-old and the (level of debt in euros). In addition, and due to the high mean duration of the addictive behavior was 3.8 (SD 5 3.9) likelihood of comorbid forms of gambling in GD patients, years. The number of patients who reported debts due to the “presence of other forms of gambling” (different to sports the sports betting activity was 226 (64.2%). A total of n 5 betting) was also collected and included within the analysis to 130 (36.9%) participants presented other forms of avoid bias due to the potential confounding effect of this gambling engaged as a secondary addiction problem. The variable. The negative binomial regression is a type of most common form of comorbid gambling was slot-ma- generalized linear model, similar to multiple regressions in chines (n 5 78, 22.2%), followed by casinos (n 5 58, which the dependent variable is an observed count that fol- 16.5%), lotteries (n 5 22, 6.3%), bingo (n 5 14, 4.0%) and lows the negative binomial distribution (that is, the possible market stock (n 5 2, 0.6%). values for the criterion are nonnegative integers: 0,1,2,3, and so on). It can be considered an extension of the Poisson Multiple regression: variables related to sports betting regression for over-dispersed outcomes (Dupont, 2009). severity Table 2 includes the multiple regression models exploring Ethics the variables related to sports betting severity between This work was performed in accordance with the Helsinki sociodemographic, age of onset of the sports betting ac- Declaration of 1975 as revised in 1983, and it was approved tivity, psychopathological distress and personality traits. by the Ethics Committee of University Hospital of Bellvitge. The number of DSM-5 total criteria was predicted for An informed consent was obtained from all the included patients with worse psychopathological state and lower participants. Parental consent was sought for those younger self-directedness level. Higher SOGS scores were related than 18 years of age. to older age, higher psychological distress and higher novelty seeking level. The highest bets per betting episode were registered among men, patients with the lowest ed- RESULTS ucation levels but the highest social status, patients with the highest psychopathological distress and gamblers with the highest reward dependence score and the lowest Characteristics of the sample persistence score. Higher bets per betting episode were Table 1 includes the descriptive characteristics for the also related to higher scores in the self-transcendence sociodemographic and the sports betting related variables trait. Table 1. Characteristics of the patients in the study (n 5 352) Sociodemographics n % Age, onset and evolution Mean SD Sex Women 13 3.7% Chronological age (yrs-old) 32.1 9.62 Men 339 96.3% Onset of the addiction (yrs-old) 25.0 7.64 Education Primary or less 120 34.1% Duration of the addiction (yrs) 3.82 3.91 Secondary 170 48.3% Gambling disorder severity Mean SD University 62 17.6% DSM-5 total criteria 7.22 1.78 Marital status Single 216 61.4% SOGS total score 11.12 3.19 Married-couple 106 30.1% Bets (euros/episode, maximum) 1,744 2,640 Divorced-Separated 30 8.5% Bets (euros/episode, mean) 132 213 Employment Unemployed 117 33.2% Debts due to gambling; n – % 226 64.2% Employed 235 66.8% a Debts (euros); mean – SD 16,209 16,526 Social status High 10 2.8% Mean-high 35 9.9% Mean 53 15.1% Mean-low 136 38.6% Low 118 33.5% Note. OSB: online sports betting. SD: standard deviation. a Calculated for patients who reported bets due to the gambling activity. Unauthenticated | Downloaded 11/25/22 04:28 PM UTC 426 Journal of Behavioral Addictions 10 (2021) 3, 422–434 Table 2. Variables associated to the gambling severity: multiple negative binomial DSM-5 total criteria SOGS total score Bets (episode, max) Bets (episode, mean) B SE P B SE P B SE P B SE P Sex (men) 0.092 0.1118 0.412 0.046 0.0880 0.598 0.933 0.3461 0.007* 0.310 0.3205 0.334 Education (lower) 0.015 0.0393 0.694 0.024 0.0317 0.450 0.313 0.1058 0.003* 0.061 0.1128 0.590 Marital status (not 0.016 0.0469 0.725 0.021 0.0380 0.572 0.128 0.1258 0.309 0.080 0.1281 0.534 married) Employed 0.083 0.0477 0.083 0.055 0.0385 0.152 0.219 0.1297 0.092 0.142 0.1334 0.288 (unemployed) Social status (lower 0.002 0.0281 0.957 0.010 0.0225 0.650 0.350 0.0791 0.001* 0.078 0.0780 0.319 indexes) Other forms of 0.006 0.0441 0.892 0.053 0.0357 0.140 0.181 0.1225 0.138 0.035 0.1294 0.786 gambling engaged Age (years-old) 0.000 0.0031 0.888 0.006 0.0024 0.020* 0.005 0.0089 0.596 0.004 0.0088 0.654 Onset of GD (years-old) 0.000 0.0037 0.986 0.004 0.0029 0.231 0.002 0.0103 0.837 0.015 0.0110 0.181 SCL-90R GSI 0.102 0.0444 0.022* 0.140 0.0359 0.001* 0.410 0.1267 0.001* 0.110 0.1407 0.433 TCI-R Novelty seeking 0.001 0.0018 0.403 0.005 0.0014 0.001* 0.007 0.0053 0.215 0.006 0.0049 0.236 TCI-R Harm avoidance 0.001 0.0018 0.604 0.001 0.0015 0.345 0.009 0.0049 0.082 0.006 0.0057 0.285 TCI-R Reward 0.002 0.0017 0.146 0.002 0.0013 0.163 0.013 0.0050 0.013* 0.009 0.0050 0.085 dependence TCI-R Persistence 0.001 0.0012 0.401 0.000 0.0010 0.884 0.010 0.0036 0.007* 0.000 0.0035 0.992 TCI-R Self-directedness 0.003 0.0014 0.048* 0.002 0.0011 0.116 0.000 0.0043 0.954 0.002 0.0044 0.592 TCI-R Cooperativeness 0.002 0.0016 0.172 0.001 0.0013 0.535 0.004 0.0044 0.377 0.003 0.0051 0.547 TCI-R Self- 0.000 0.0017 0.880 0.002 0.0014 0.137 0.007 0.0051 0.169 0.012 0.0048 0.017* transcendence Note. SE: standard error. *Bold: significant parameter. Sample size: n 5 352. Multiple regression: predictors of the debts cumulative debts was related to male sex, being employed, Table 3 includes the results of the models exploring the older age, worse psychopathological state, and higher levels statistical predictors of the debts [as a binary variable in novelty seeking and cooperativeness. The amount of euros (presence of debt) and a quantitative variable (cumulative cumulated as debts due to sports betting was also higher for euros)] related to the betting activity. The risk for having men, with lower education levels but higher social status, Table 3. Variables associated to the debts related to the gambling activity a b Presence of debts Debts (euros) B SE P OR B SE P Sex (men) 1.313 0.655 0.045* 3.718 0.546 0.326 0.045* Education (lower) 0.226 0.241 0.348 1.253 0.272 0.112 0.015* Marital status (not married) 0.040 0.285 0.888 1.041 0.029 0.129 0.820 Employed (unemployed) 0.599 0.276 0.030* 0.549 0.149 0.127 0.240 Social status (lower indexes) 0.299 0.176 0.088 0.741 0.383 0.080 <0.001* Other forms of gambling engaged 0.073 0.265 0.782 1.076 0.076 0.125 0.545 Age (years-old) 0.037 0.019 0.053 1.037 0.062 0.009 0.000 Onset of GD (years-old) 0.004 0.023 0.877 1.004 0.008 0.010 0.452 SCL-90R GSI 0.498 0.278 0.048* 1.646 0.328 0.129 0.011* TCI-R Novelty seeking 0.023 0.011 0.032* 1.023 0.005 0.005 0.287 TCI-R Harm avoidance 0.000 0.011 0.999 1.000 0.004 0.005 0.373 TCI-R Reward dependence 0.012 0.010 0.229 0.988 0.009 0.005 0.079 TCI-R Persistence 0.005 0.007 0.525 0.995 0.004 0.003 0.243 TCI-R Self-directedness 0.008 0.009 0.371 0.992 0.001 0.004 0.814 TCI-R Cooperativeness 0.029 0.010 0.004* 1.029 0.017 0.005 0.001* TCI-R Self-transcendence 0.004 0.010 0.665 0.996 0.007 0.005 0.156 Note. SE: standard error. OR: odds ratio. *Bold: significant parameter. Sample size: n 5 352. a Logistic regression. b Negative binomial regression. Unauthenticated | Downloaded 11/25/22 04:28 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 422–434 427 older age, worse psychopathological state and higher score in Browne, 2019), but also in previous samples from our hos- cooperativeness. pital (Jimenez-Murcia et al., 2020), shows that the current sample shows a mean age younger than previous studies (a difference of at least 10 years), so the current sample is in a DISCUSSION lower age range compared to previous studies, with a short average disease duration. In this sense, online gambling has To the best of our knowledge, this is the first study in a been associated with a shorter disease course (Hubert & Spanish sample evaluating the factors affecting the severity Griffiths, 2018; Landreat et al., 2020). of gambling problems in a large clinical sample of sports Similar to other studies (Black et al., 2015; Jimenez- bettors. In addition, the current approach evaluates for the Murcia et al., 2010), we did not find a direct relationship first time how psychopathological distress and different between sports betting severity and onset of disease. How- personality aspects are influencing sports betting severity. ever, having in mind that gambling initiation age of onset We found that older age, higher psychopathological may condition severity of gambling at older ages specifically, distress, lower self-directedness level, and higher novelty it may be plausible that in our sample, with an early onset, seeking level were predictors of gambling severity (under- older adult problem gamblers who began gambling earlier in stood as higher number of DSM-5 criteria) in sports bet- life showed higher severity (they gambled more often) than tors. did their counterparts who began gambling as adults. In this A previous study in an Australian sample (Hing, Russell, sense, previous research has shown that pathological Vitartas et al., 2016) found that the severity of sports betting gambling in general seems to have an age at onset between in general was directly related to being male, of a young age, the mid-twenties to the late thirties (Black et al., 2015; Black, unmarried, with higher education levels, working or study- Monahan, Temkit, & Shaw, 2006; Black, Shaw, Forbush, & ing full-time, engaging in different forms of gambling, with a Allen, 2007; Bland, Newman, Orn, & Stebelsky, 1993; Grant less planned approach to betting, and watching both live and & Kim, 2001). Interestingly, the study from Bland et al. televised sporting events. Both studies are not totally com- (1993) coincides with our age at onset at 25 years, relating parable as the Hing and colleagues’s model did not evaluate the range from 25 to 29 years at age of onset to heavy betting psychopathological distress or personality factors. In addi- behavior. More recent data also puts the onset closer to 25 tion, their sample was not a treatment-seeking population. years (23 years) (Kessler et al., 2008). This threshold of 25 Contrary to literature from Australian bettors, where years has been previously reported as an early-onset with younger age appears as a risk factor of sport betting behavior clear implications for prevention and treatment strategies (Russell, Hing, & Browne, 2019) and is normally related to (Grant, Kim, Odlaug, Buchanan, & Potenza, 2009). At this higher problem gambling severity (Hing et al., 2017; Hing, point, we cannot avoid the phenomenon of the impact of Russell, Vitartas et al., 2016), we found that “older” age was gambling advertising and marketing during sporting events more related to higher levels of severity. One plausible hy- (mainly in televised matches) especially in adolescent and pothesis is that for some gambling behavior typologies and/ young people, which has been recognized by the scientific or samples older age could be related to higher economic community as a health and social problem (Djohari et al., incomes which allow gambling more often, betting more 2019; Pitt, Thomas, & Bestman, 2016) that can contribute to money per episode and consequently having more losses and the development of gambling-related problems (Hing et al., more accumulated debts. Another potential source of 2017; Pitt, Thomas, & Bestman, 2016). disagreement is that our sample is clinical, which might yield In addition, with respect to the age of gambling onset per different results as compared to non-clinical samples from se, the fact that sports betting may be shaped by different other studies. In this vein, several studies indicate that the factors, not only personality-related, including socioeco- fact of requesting professional treatment is usually associ- nomic status, allows us to speculate about the cultural dif- ated with higher severity (Braun, Ludwing, Sleczka, ferences between countries that may condition the access to B€uhringer, & Kraus, 2014; Pulford et al., 2009) because sports betting in youths and the apparent discrepancies mostly only individuals with more severe gambling prob- about age and severity between studies. The International lems actively seek treatment. Therefore, apart from different Monetary Fund points out how youth unemployment in legislative jurisdictions where different environmental fac- Spain is a persistent phenomenon, consistently being among tors and availability of gambling may influence disorder the highest in the European Union, with young people development trajectory, these differences related to the na- working and earning less («Spain: Time to Strengthen ture and characteristics of the samples studied can partially Resilience, Promote Inclusive Growth», 2018). These factors explain these apparently contradictory results. In addition, may help to explain the age-related results presented here as the age characteristics of the current sample (mean age the Spanish sample may have a later access to play, resulting around 32), mean age of onset (25 years) and mean duration in younger ages being partially underrepresented. In the of the disease (4 years) may also account for the apparent past, country–related differences regarding younger ages discrepancies among the Australian study and ours. The accessing to sports betting has been reported (Humphreys & comparison of the mean age of our sample with previous Perez, 2012). We additionally found that older age was a studies, not only in Australian samples (Russell, Hing, & predictor of gambling-related debts, reinforcing the idea that Unauthenticated | Downloaded 11/25/22 04:28 PM UTC 428 Journal of Behavioral Addictions 10 (2021) 3, 422–434 in our sample older ages are consistent with more severe Therefore, economic consequences are also related to sports betting trajectories. emotional distress (Oksanen, Savolainen, Sirola, & Kaaki- Most of the participants were men, coinciding with what nen, 2018), which should be addressed primarily to avoid has been reported in previous literature for sports betting gambling harm affecting all the life spheres of sports bettors. (Granero et al., 2020). Being a man has been considered a With regards to the personality aspects, we found only risk factor for gambling behavior (Hing, Russell, Vitartas et two particular factors related to sports betting severity: lower al., 2016; Hing, Russell, Tolchard et al., 2016; Jimenez- self-directness and higher novelty seeking levels. These are Murcia et al., 2020; Kim, von Ranson, Hodgins, McGrath, & very common personality aspects describing gamblers Tavares, 2018; Valero-Solıs et al., 2018). Our data supports (Alvarez-Moya et al., 2010; Estevez et al., 2017; Janiri, this idea, emphasizing the weight of being a man in sports Martinotti, Dario, Schifano, & Bria, 2007). Both components betting as a predictor for debts, as well as the direct rela- of personality are related to risky behaviors, impulsivity and tionship between being a man and the presence of worse the capacity to regulate behaviors (Abassi & Abolghasemi, economic harmful consequences, with an increase in the 2015), and considered relevant for impulsivity-related dis- amount of debt accumulated and the highest bets per betting orders (Del Pino-Gutierrez et al., 2017), so we can argue in episode. this case that sports bettors present specific temperamental With regards to marital status, problem gambling often factors directly related to impulsivity, and not related to results in separation and divorce (Jimenez-Murcia, Trem- harm avoidance, as we did not find an association between blay et al., 2017; Shaw, Forbush, Schlinder, Rosenman, & this latter factor and sports betting severity. Coincidentally, Black, 2007). The prevalence of separated or divorced par- Hing et al. (2018) suggest a dysfunctional self-regulatory ticipants was low in the current sample (8.5%), with most capacity in many highly-involved sports bettors who may people being single (61%) (here, there is a clear influence of fail to exercise self-control (Hing, Li, Vitartas et al., 2018). In age, as this is a “young sample”). The short mean duration of this sense, lack of self-control has been widely accepted as a the disorder reported here is probably explained because key problem in gambling (Bergen, Newby-Clark, & Brown, marriages lacked time to break up. 2014). Having in mind that sports bettors are more impul- The current work incorporates psychopathological and sive in general (Russell, Hing, Li, & Vitartas, 2019), and personality factors in categorizing sports betting, aligning considering the presence of more opportunities to bet with the idea that different and complex pathways models impulsively (Hing, Russell, Li, & Vitartas, 2018; Hing, Rus- for describing different gambling behaviors should be sell, Vitartas et al., 2016), an impaired self-control is likely to considered (Blaszczynski & Nower, 2002). We found that be happen amongst problem sports bettors. Russell et al. sports betting severity was related to higher psychopatho- (2019) report that higher-risk sports bettors were also more logical distress. This relationship has been widely reported in likely to have lower self-control, but that this lack of control general gambling behavior (Ciccarelli, Griffiths, Nigro, & should be contextualized as a general gambling behavior Cosenza, 2017; Nigro, D’Olimpio, Ciccarelli, & Cosenza, characteristic, not as a predictor of sports betting specifically. 2019), with some therapies especially focused on the For this, they used a penalized model that allowed for amelioration of this emotional distress in gamblers collinearity amongst predictors (Russell, Hing, & Browne, (Mench on, Mestre-Bach, Steward, Fernandez-Aranda, & 2019). Different from us, that study did not explore per- Jimenez-Murcia, 2018). Considering gambling might be sonality factors. Interestingly, in terms of risk factors for understood as a behavioral pattern to relieve emotional sports betting problems, these authors postulate that there distress, the more the stress, the more the severity of the are some variables relevant to all levels of problem gambling behavior. As a consequence, distress has been also postulated severity (i.e., gambling expenditure, number of accounts as a moderator between gambling severity and psycho- with different operators, impulsiveness), whereas others are pathological problems (Ronzitti, Kraus, Hoff, & Potenza, only relevant to those with the highest level of gambling- 2018). A previous study from our research group based on a related problems (i.e., normative data such as age, gender, or clustering by a psychopathological state showed how there is being in a single marital status, or number of different types a type of gamblers who present the highest gambling dis- of promotions used [which despite appearing in all levels of order severity and the most severe levels of emotional gambling are more important in high levels]) (Russell, Hing, distress (Jimenez-Murcia et al., 2019). In that study, severity Li, et al., 2019). The authors, however, pointed out the need was related to psychopathological distress, coincidental with to identify subtypes of gambling severity within sports our present results. betting in order to provide a more personalized therapeutic Our results expand previous findings in gamblers approach. concluding that sports bettors in Spain specifically show a We found a paradoxical result. The highest bets per direct relationship between emotional distress and the betting episode and the debts were mostly registered in severity of this subtype of gambling. This is important in patients with the lowest education levels but the highest order to tackle sports betting and its idiosyncratic charac- social status. In other words, the less the education sports teristics in therapy. In this sense, the highest bets per betting bettors have, the more likely they will gamble. With regards episode, the risk of having accumulated debts and the to the apparently surprising result in reference to the social amount of money accumulated as gambling-related debts status, a possible explanation might be the particularity of were also related to a worse psychopathological state. the social status distribution in the current sample. While a Unauthenticated | Downloaded 11/25/22 04:28 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 422–434 429 very high percentage of patients are in the low and medium- impulsive and excessive behavior. Some sports with less low groups, less than 3% are actually in a high level. microevents are, theoretically, less attractive for bettors in Therefore, when we refer to “higher values” we do not mean this regard, meaning that perseverance of bettors may be being in high social classes, but in higher percentiles but conditioned by the type of sport. always within the most unfavorable social groups. In this The participants of this study were recruited during a respect, it would not be surprising if the highest bets were long period of time, between January 2005 until January linked to people with a slightly higher level of purchasing 2020, and we might suspect the contribution of a potential power. moderator effect of the assessment time on the gambling A higher number of bets per episode occurred in sports phenotypes. In this regard, the frequency of participants bettors with a high reward dependence score, the lowest with sports betting as the main reason for treatment seeking persistence score, and higher scores in the self-transcen- showed a increasing trend in this work: n 5 43 between dence trait, while debts were also dependent on high levels 2005 and 2010, n 5 130 between 2010 and 2015 and n 5 of cooperativeness. High levels of reward dependence, 179 between 2016 until now. This increase is strongly related strongly associated with extraversion (De Fruyt, Wiele, & with advances in technology and the universalization of van Heeringen, 2000; Smillie, 2013), have been previously Internet access (which have facilitated fast and easy access to reported in some gamblers as a trait (Hodgins & Holub, almost all traditional manners of gambling globally) and the 2015; Jimenez-Murcia, Fernandez-Aranda et al., 2017; changes in the Gambling Law. Regarding online gambling, Mestre-Bach et al., 2016). However, different to some of should it really be considered a new gambling modality, or a this literature, these levels are not in consonance with the simple mode to access to the different gambling activities apparent contradictory low persistence scores found for and platforms? It could be suspected that the structural sports bettors. Within the gambling behavior, rewards may features of Internet gambling, its interactive and immersive acquire different forms (e.g., immediate, delayed, in-play, specificities, should affect gambling related harms, but re- by chance, strategic or non-strategic, accumulated) (Grant, sults are yet scarce and differences between online and off- Odlaug, Chamberlain, & Schreiber, 2012; Ledgerwood & site gambling outcomes are controversial (Baggio et al., 2017; Petry, 2010; Odlaug, Marsh, Kim, & Grant, 2011), and this Gainsbury, Liu, Russell, & Teichert, 2016; Gainsbury, Rus- is especially relevant for sports bets. Depending on the sell, Wood, Hing, & Blaszczynski, 2015). On the other hand, reward, this may condition the persistence levels of sport studies carried out across different European countries, with bettors in the number of bets per episode, and sports different jurisdictions regarding the legal status of Internet betting products include multiple reward types as gambling (ranging from prohibition to broad legal access), compared to other gambling activities. This explanation have found no relevant differences in the prevalence rates of aligns well with the psychobiological model of tempera- GD depending on the mode of access (Planzer, Gray, & ment of Cloninger (Cloninger, Svrakic, & Przybeck, 1993) Shaffer, 2014). In our study, we have assessed potential by which low persistence is an adaptive strategy when differences in key variables related to the gambling profile reward contingencies change rapidly. For that reason, in for the groups defined by the recruitment time for the main the specific case of sports bettors, persistence does not seem variables of the study: P 5 0.809 for the progression/dura- to be a common characteristic, and may be a strategy tion of the problematic gambling, P 5 0.217 for the number adopted attending the demands of the subtype of gambling. of DSM criteria, P 5 0.644 for the gambling severity level A previous study pointed out that high levels in reward according to the SOGS total score and P 5 0.581 for the dependence and cooperativeness did not have an effect on global psychopathological distress measured through the gambling severity, arguing that maybe those were effective SCL-90R GSI. protective factors (Moragas et al., 2015), in concordance This study has some limitations that should be with the lower levels of persistence found here. Current mentioned in order to better interpret the results. First, the results about perseverance in sports bettors led us to argue sample comprised treatment-seeking sports bettors, and about an evaluation of different subtypes of gambling be- consequently the results might not be generalizable to haviors, not only among gamblers in general, but also sports bettors who do not seek treatment (and by extension within sports bettors in particular. Future studies in to pathological gamblers in general). In this sense, it should different countries should establish groups of comparison also be considered that although our gamblers were path- according to the type of sport one bets on (i.e, football, ological, considering the mean obtained in the SOGS tennis), in order to consider different types of potential (around 11) they scored at the ‘lower limit’ of the gambling rewards. In this sense, we have a clear example in tennis harm spectrum, but still pathological. However, the Span- which appears as one of the most “addictive” sports. In ish version of the test validation (Echebur ua et al., 1994) tennis, bettors can bet on multiple microevents within a places the diagnostic efficacy threshold slightly below what single game (Russell et al., 2019), many more than in Eu- the original version of the test placed, achieving the same ropean football, for instance, because of the characteristics diagnostic efficacy and even increasing the sensitivity. This of each type of sport. The key is the frequency and duration goes in line with the scores obtained in other Spanish of the event, compartimentalized in quick points and pathological gamblers samples, but it should be framed in games in tennis, which increase the bettors’ ability to bet the characteristics of the sample size, as other studies in and re-bet in continuous, short-lived cycles that facilitate sports betting gamblers are larger. In this sense, Unauthenticated | Downloaded 11/25/22 04:28 PM UTC 430 Journal of Behavioral Addictions 10 (2021) 3, 422–434 particularities of the current sample may also account for characteristic contributing to good generalizability (many some of the discrepancies found. Second, the study did not different types of patients and situations plus large sample cover all possible sociodemographic and clinical factors sizes are the keys of how useful the results of a concrete affecting severity. Third, the type of sports betting was not research are for the target populations). available for the participants of this study, and therefore it was not possible to test the contribution of this variable on the gambling severity. Attending to the multiple forms of CONCLUSION sports betting, future research should assess the potential moderator or mediational role of the gambling preference To sum up, there are studies evaluating how gambling on the gambling related harms. In this sense, the results of severity in sports bettors influences gambling behavior our study should be interpreted carefully as aspects such as (Hing et al., 2014), arguing that severity is a strong pre- in-play betting, which is directly related to severity (Hing, dictor to greater intended frequency of sports betting, but Russell, et al., 2018), has not been evaluated here specif- there is a lack of literature evaluating factors affecting ically. sports betting severity. The findings in the present study Some strengths of this work must also be listed. First, characterize, beyond the sociodemographic and clinical the inclusion of a relatively large sample of sports betting factors, the psychopathological and personality traits in gambling patients, treatment seeking for the problems Spanish sports bettors associated with the severity of related to their addiction behavior. Second, this study used gambling disorder. These factors and traits, in some cases, two instruments to measure gambling related variables, even seem to contradict some of the results found in other which provide complementary information regarding the worldwide samples. These results permit us to flag sports gambling profile. While the questionnaire based on the bettors as a subtype of gamblers that should merit tailored DSM-5 is a diagnostic tool to assess the number of criteria therapeutic approaches in response to their singular char- for GD based on the operational definition of this taxon- acteristics. omy, the SOGS is a screening tool which covers cognitive, emotional and other behaviors related to problem gambling. The SOGS includes a set of items measuring Funding sources: Financial support was received through lying about gambling activity, losses and debts, taking time the Ministerio de Ciencia, Innovacion y Universidades off work, arguments with family or close friends, feeling (grant RTI2018-101837-B-100). FIS PI14/00290, FIS PI17/ guilty, borrowing money to gamble, and performing illegal 01167 received aid from the Ministerio de Sanidad, Servi- acts to finance gambling. This questionnaire is used to cios Sociales e Igualdad. The research was also funded by examine both the gambling behavior (symptom level) and the Delegacion del Gobierno para el Plan Nacional sobre the consequences of gambling. The use of both measures, Drogas (2017I067 and 2019I47), CIBER Fisiologıa Obesi- based on the DSM-5 criteria and the SOGS contribute to dad y Nutricion (CIBERobn) and CIBER Salud Mental increase the generalization capacity of the study, and allow (CIBERSAM), both of which are initiatives of ISCIII. We to external researchers to compare our evidences with the thank CERCA Programme/Generalitat de Catalunya for results obtained in their studies. Related with this charac- institutional support. Fondo Europeo de Desarrollo teristic, we would like to outline that use of multiple Regional (FEDER) “Una manera de hacer Europa”/“a way measurement tools provides a complete picture of the to build Europe”. Grant research by the Spanish “Dele- disordered gambling. gacion del Gobierno para el Plan Nacional sobre Drogas” This work analyzed a sample of sports betting gamblers (2017I067). IB was partially supported by a Post-Residency recruited from a treatment unit at the Bellvitge University Grant from Research the Committee of the University Hospital, which oversees the outpatient treatment of cases Hospital of Bellvitge (HUB; Barcelona, Spain) 2019–2020. with behavioral addictions related problems (mainly GD). TMM is supported by a predoctoral grant awarded by the This unit has obtained the recognition of tertiary care Ministerio de Educacion, Cultura y Deporte (FPU16/ center, which in Spain consist in a level of health care 02087). carried out by highly specialized equipment and experts in large hospitals. Patients are referred from the providers of Authors’ contribution: Study concept and design: SJM, RG, primary or secondary care centers from a catchment area FFA, MG, JM. Analysis and interpretation of data: MGP, that includes over two million people in the metropolitan LM, IB, APG, EC, TMM, EVM, BMM, HLG, SVS, SRP, area of Barcelona. Therefore, our sample can be considered EGG. Statistical analysis: RG. Obtained funding: SJM, RG, highly representative of the general public who need JM, FFA. Study supervision: SJM, RG, JM, FFA. All authors treatment due the problematic gambling behavior. The had full access to all data in the study and take responsibility long period of recruitment in this work also facilitates for the integrity of the data and the accuracy of the data variations due to the own cultural progress and the regu- analysis. latory/legalization structures (values and beliefs regarding gambling, as well as help-seeking attitudes), and this het- Conflicts of interest: The authors declare no conflict of in- erogeneity in the participants should be interpreted as a terest Unauthenticated | Downloaded 11/25/22 04:28 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 422–434 431 REFERENCES Cantinotti, M., Ladouceur, R., & Jacques, C. (2004). Sports betting: Can gamblers beat randomness? Psychology of Addictive Be- haviors, 18(2), 143–147. https://doi.org/10.1037/0893-164X.18. Abassi, M., & Abolghasemi, A. (2015). Temperament and character 2.143. dimensions: Correlates of impulsivity in morphine addicts. Ciccarelli, M., Griffiths, M. D., Nigro, G., & Cosenza, M. 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