Short CommunicationAssociations between sensitivity to punishment, sensitivity to reward, and gambling
Introduction
Gambling is an activity that most individuals will participate in over the course of their life, however, only a few of these individuals develop pathological gambling (Griffiths, 2006). Pathological gambling, or gambling disorder, is a psychiatric condition characterized by persistent maladaptive gambling behavior (American Psychiatric Association [APA], 2013). Excessive gambling is associated with a wider range of negative consequences such as discord in interpersonal relationships, legal problems, financial loss, poor physical health, and other mental disorders (American Psychiatric Association, 2013, Clark, 2010, Morasco et al., 2006). In the United States, the prevalence of lifetime gambling problems and pathological gambling is approximately 2–5% (Griffiths, 2006, Pallesen et al., 2005, Potenza, 2008). In addition, according to the National Comorbidity Survey, 96.3% of individuals with history of pathological gambling have one or more diagnoses of other mental illnesses, such as substance use disorders, anxiety disorders, and major depressive disorders (Kessler et al., 2008). As gambling is becoming more accessible through the Internet (Griffiths, 2006), it is expected that more people will develop problems with gambling. Due to the severity of consequences, popularity of gambling, and increasing avenues of gambling, understanding risk and resiliency mechanisms underlying problem gambling is an important area of focus.
Gray's Reinforcement Sensitivity Theory (RST; Gray, 1991) may be relevant to understanding the development of gambling problems (Balodis et al., 2013, Jacobsen et al., 2007). The RST ascertains that differences in neurobiological levels on sensitivity to punishments and rewards can influence an individual's affect and behavior. Moreover, the RST discusses two systems: behavioral activation system (BAS) and behavioral inhibition system (BIS; Gray, 1991). BAS is hypothesized to be sensitive to reward (SR), and thus leads individuals to attain goals (Gray, 1991). More recent developments have conceptualized BIS as mediating between BAS and Fight–Flight–Freezing system (FFFS) that controls avoidance and generating risk assessment (Gray & McNaughton, 2003). Since winning in gambling is a reward, individuals with high BAS (SR) are likely to engage in betting more. A limited amount of previous literature has examined relationships between BAS and gambling decision-making (Brunborg et al., 2011, Demaree et al., 2008, Kim and Lee, 2011). Brunborg and colleagues (2011) and Demaree et al. (2008) found a positive associated between BAS and the size of average bet on a laboratory slot machine task. Similarly, Kim and Lee (2011) found that individuals with a high BAS bet larger amounts and exhibit greater confidence even in situations with high likelihood of losing. The aforementioned findings demonstrate a significant association between BAS and gambling, further supporting the idea that high SR may act as a risk factor for problematic gambling.
There is a limited amount of literature investigating BIS and gambling behavior. BIS is hypothesized to be sensitive to punishment (SP) or nonreward, resulting in anxiety or fear, and thus stops individuals' actions or resolves approach–avoidance situations (Corr, 2001, Gray, 1991), and may act as a protective factor for problematic gambling. As losing in gambling is often punishing or nonrewarding, individuals with high sensitivity to punishment are expected to abstain from betting. In fact, Demaree et al. (2008) found that SP (BIS) is associated with less risk-taking while SR (BAS) is associated with greater risk-taking. Moreover, in that study, the influence of high SP (BIS) on risk-taking was greater than high SR (BAS). Similarly, Kim and Lee (2011) found that BAS, or SR, was positively associated with greater risky gambling decisions after a winning experience while BIS, or SP, was negatively associated with risky gambling decisions after the same experience. Alternatively, individuals who might be high in the anxiety associated with sensitivity to punishment engage in a variety of risk taking behaviors, including gambling, in an effort to alleviate negative affect and escape reality. If so, this might suggest a positive association between sensitivity to punishment and gambling (Hudson et al., 2013, Hundt et al., 2013). These opposing mechanisms might explain the null findings in recent literature on associations between BIS and gambling (Brunborg et al., 2011).
In addition, the two systems of the RST are orthogonal; thus, we hypothesized that SR and SP influence each other's effect on gambling problems. Such interaction effects of SR and SP were found in addiction research. For example, Simons and Arens (2007) found that sensitivity to punishment moderated the relationship between SR and marijuana use among college students. Similarly, Genovese and Wallace (2007) found the highest rates of substance use among adolescents with high SR and low SP. Given the established addictive nature of gambling, substance use studies such as those previously mentioned may provide important theoretical framework for the relationships between SR, SP, and gambling.
Although gambling is a behavior that the majority of people engage in during the course of their lifetime, many will not experience gambling problems. Additionally, one can only experience gambling problems if they are currently gambling. Thus, a large number of zero-values are expected within a mixed distribution of reported gambling problems. Some individuals who gamble may report no gambling-related problems while others may report a broad range of problems. It is expected, however, that individuals who do not gamble do not experience gambling problems. Thus, it is of interest to identify variables that predict non-gamblers as well as predictors of gambling problems. The current study examines associations between sensitivity to punishment, sensitivity to reward, and gambling problems among college students. It is hypothesized that sensitivity to reward will be positively associated with gambling problems, sensitivity to punishment will be negatively associated with gambling problems, and sensitivity to punishment will weaken the relationship between sensitivity to reward and the likelihood of having gambling problems.
Section snippets
Participants
Participants were 2254 undergraduate students aged 18 to 25. Women comprised 64.15% of the sample. Racial composition of the sample was 94.59% White, 1.16% Hispanic, 1.06% Asian, 0.8% Black, 0.8% Native American, 0.8% multiracial, and 1.82% were of other races. All participants were treated in accordance with APA ethical guidelines for research (Sales & Folkman, 2000) and all study procedures were reviewed by the institutional review board. Three articles have been published from this dataset (
Descriptive statistics
Descriptive statistics and the correlation matrix for the variables are presented in Table 1. The mean of participants' SOGS score was 0.43 (SD = 1.32) with a range of 0 to 19. Further analyses revealed that 18.63% of participants scored 1 or higher, suggesting some risk for gambling problems, and 5.06% scored 3 or higher, indicating a greater likelihood of being a problem gambler (Cox et al., 2004, Volberg and Steadman, 1988). These rates are consistent with previous research in college
Discussion
The current study examined associations between sensitivity to punishment, sensitivity to reward, and gambling problems. Consistent with hypothesis, sensitivity to reward was positively associated with gambling problems. This effect was observed in both the bivariate and multivariate analyses and held for both the likelihood of any gambling problems as well as the number of problems among potential problem gamblers. This is consistent with research on a wide range of risk behaviors including
Role of Funding Sources
Preparation of this manuscript was supported, in part, by the National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health, under Award Number R01AA017433 (J.S. Simons, PI). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Contributors
All authors have contributed to and have approved the final manuscript.
Conflict of interest
All participants were treated in accordance with APA ethical guide lines for research and all study procedures were reviewed by the institutional review board. Three articles have been published from this dataset (Simons, Carey and Wills, 2009, Simons et al., 2008, Wray et al., 2011). The current paper is theoretically and conceptually distinct.
References (43)
- et al.
Individual differences in evaluative conditioning and reinforcement sensitivity affect bet-sizes during gambling
Personality and Individual Differences
(2011) - et al.
The relations of trait anxiety, anxiety sensitivity, and sensation seeking to adolescents' motivations for alcohol, cigarette, and marijuana use
Addictive Behaviors
(2001) Testing problems in J. A. Gray's personality theory: A commentary on Matthews and Gilliland (1999)
Personality and Individual Differences
(2001)- et al.
The role of impulsivity in the development of substance use and eating disorders
Neuroscience & Biobehavioral Reviews
(2004) - et al.
You bet: How personality differences affect risk-taking preferences
Personality and Individual Differences
(2008) - et al.
Dependent heroin use and associated risky behaviour: The role of rash impulsiveness and reward sensitivity
Addictive Behaviors
(2014) - et al.
Reward/punishment sensitivities among internet addicts: Implications for their addictive behaviors
Progress in Neuro-Psychopharmacology and Biological Psychiatry
(2013) - et al.
Reinforcement sensitivity theory predicts positive and negative affect in daily life
Personality and Individual Differences
(2013) - et al.
Negative urgency, distress tolerance, and substance abuse among college students
Addictive Behaviors
(2012) - et al.
Effects of the BAS and BIS on decision-making in a gambling task
Personality and Individual Differences
(2011)
Curiosity killed the cocktail? Curiosity, sensation seeking, and alcohol-related problems in college women
Addictive Behaviors
Confirmatory factor analysis of the Sensitivity to Punishment and Sensitivity to Reward Questionnaire
Personality and Individual Differences
Reliability, validity, and classification accuracy of the South Oaks Gambling Screen (SOGS)
Addictive Behaviors
Internet addiction: Hours spent online, behaviors and psychological symptoms
General Hospital Psychiatry
The Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) as a measure of Gray's anxiety and impulsivity dimensions
Personality and Individual Differences
Diagnostic and statistical manual of mental disorders
Sensitivity to reward and punishment: Horse race and EGM gamblers compared
Personality and Individual Differences
Decision-making during gambling: An integration of cognitive and psychobiological approaches
Philosophical Transactions of the Royal Society of London Series B, Biological Sciences
Comparisons between the South Oaks Gambling Screen and a DSM-IV-based interview in a community survey of problem gambling
The Canadian Journal Of Psychiatry
Reward sensitivity and substance abuse in middle school and high school students
The Journal of Genetic Psychology
The neuropsychology of temperament
Cited by (28)
Do attention-deficit/hyperactivity symptoms influence treatment outcome in gambling disorder?
2024, Comprehensive PsychiatryImpulsivity and loot box engagement
2023, Telematics and InformaticsReinforcement sensitivity theory may predict COVID-19 infection outcome and vulnerability
2023, Personality and Individual DifferencesGambling and gaming during COVID-19: The role of mental health and social motives in gambling and gaming problems
2022, Comprehensive PsychiatryCitation Excerpt :Although our sample size was relatively large, the distributions of the variables measuring gambling problems and gaming problems were skewed, as they contained a large number of zeros and a long right tail with small values [59]. ZINB regression models produce good estimates in these types of models containing excess zeros, which are common in addiction research [60,61]. In the models, we estimated gambling and online gaming problems using incidence rate ratios (IRRs) and excessive zeros using odds ratios (ORs).
Trans-diagnostic measurement of impulsivity and compulsivity: A review of self-report tools
2021, Neuroscience and Biobehavioral ReviewsTrends and sociodemographic disparities in sugary drink consumption among adults in New York City, 2009–2017
2020, Preventive Medicine ReportsCitation Excerpt :We then created weight-adjusted multiple zero-inflated negative binomial regression (ZINB) models to identify the association between different sociodemographic and neighborhood factors (i.e., neighborhood poverty level) and sugary drink consumption. The zero-inflated negative binomial regression was used because the dependent variable was count data, contained an excessive number of zeros, and was non-normally distributed (Gaher et al., 2015; Rehder and Bowen, 2019). Year as a fixed effect was controlled in all estimations because data from multiple years were combined.