Abstract and Keywords
Gambling disorder is a significant public health concern. The recent and continued proliferation of land-based and interactive gambling opportunities has increased both accessibility and acceptability of gambling in the United States and abroad, resulting in greater and more varied participation. However, there is currently no designated federal funding for prevention, intervention, treatment, or research, and states are left to adopt varying standards on an ad hoc basis. Social workers receive little or no training in screening or treating problem gamblers, though research suggests that a significant proportion of those with mental health and other addictive disorders also gamble excessively. Raising awareness about the nature and scope of gambling disorder and its devastating implications for families and children is a first-step toward integrating gambling into prevention, assessment and treatment education in social work. This, in turn, will increase the chances of early identification and intervention across settings and insure that social workers can lend a knowledgeable and credible voice to addressing this hidden addiction.
The recent proliferation of gambling opportunities across the United States and abroad has led to increased participation in multiple forms of gambling, both land-based and online. A majority of those who gamble do so for recreation only. However, about 5 million adults and 3 million youth in the United States meet clinical criteria for gambling disorder, and double those numbers have serious gambling problems.
Unlike substance abuse, where individuals begin to manifest obvious symptoms over time, gambling disorder is, essentially, a silent addiction. Disordered gamblers can often hide debts, borrow and steal, and move money among accounts so that unsuspecting family members are caught unaware when the house is in foreclosure, the cars and money are gone, and they learn of impending bankruptcy and, often, criminal charges. Despite these devastating consequences—consequences that often adversely impact the most vulnerable groups and children—gambling is seldom included in routine screenings in schools, mental health centers, health settings, child welfare agencies, senior centers, or other areas where social workers practice. Most schools of social work omit the diagnosis and treatment of gambling disorder from addiction curriculum, opting instead to adhere to teaching materials that feature only substance use disorders. In addition, only a handful of gambling researchers are faculty in schools of social work. This article will familiarize social workers with the nature, course, and scope of this behavioral addiction, including: (a) terminology and history of the disorder; (b) etiology of gambling problems and disordered gambling; (c) the prevalence of disorder, particularly among special populations; (d) comorbidity; (e) individual and societal impacts; (f) screening and clinical interventions; and (g) policy considerations and the role of social workers.
Terminology and History of the Disorder
Defining maladaptive gambling behavior has long been the subject of debate among gamblers, clinicians, and researchers. Historically, gambling has been viewed as a vice, and those with gambling problems labeled “degenerate gamblers” lacking in self-control. To combat this stigma, individuals with gambling problems have long referred to themselves as “compulsive” gamblers, suggesting that excessive gambling is beyond their volitional control. This perspective was shared by psychiatrist Dr. Robert Custer, a pioneer in the field who first brought awareness to the devastating effects of gambling disorder in his book When Luck Runs Out: Help for Compulsive Gamblers and Their Families (Custer & Milt, 1985). The research and larger medical community, however, rejected the notion that excessive gambling is a compulsion, in large part because a majority of gamblers find the activity pleasurable and arousing (i.e., ego-syntonic rather than ego-dystonic) until the money runs out and they are forced to deal with the negative consequences of losses (Moran, 1970).
Confusion regarding the nomenclature is reflected in the evolution of the diagnostic criteria. Sigmund Freud was the first to identify uncontrolled gambling as an illness worthy of treatment (Freud, 1928). However, disordered gambling was not officially recognized until the World Health Organization identified it as a psychiatric illness in the 1979 edition of the International Classification of Diseases (World Health Organization, 1979), followed by recognition in the third edition of the Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association (DSM-III, American Psychiatric Association (APA), 1980). Both criteria use the term “pathological” rather than “compulsive” to identify gamblers who meet diagnostic criteria for disorder, attesting to the volitional nature of the disorder.
Despite use of the term “pathological,” gambling disorder was classified with compulsion-like impulse control disorders that were difficult to place in the diagnostic rubric and shared few other commonalities with gambling: kleptomania, trichotillomania, explosive temper disorder, and pyromania. Based largely on feedback from addiction counselors, who viewed gambling as a behavioral addiction, the DSM-III-R (APA, 1987) included criteria that paralleled those for psychoactive substance dependence: preoccupation, tolerance, and loss of control. But the psychiatric community was still resistant to reclassifying disordered gambling as an addiction.
All versions of the DSM criteria have retained two hallmark characteristics of gambling disorder: (a) the unique notion of “chasing” or repeated attempts by the gambler to continue a winning streak or end a losing streak by gambling more frequently and (b) “bailouts,” in which the gambler seeks money from family, friends, and others to address growing debt. Despite inclusion of additional items, the DSM-III-R met with criticism from the gambling community, who criticized the criteria as vague and repetitive (Rosenthal, 1992), failing to capture the unique nature of a behavior addiction. In particular, the treatment community viewed gambling disorder as a unique mix of addiction and impulsive behavior rather than simply a surrogate for substance abuse. In contrast, the medical community was steadfast in maintaining that addictions should be limited to those that are substance-based. The resulting DSM-IV criteria (APA, 1994) was a hybrid, retaining the “pathological gambling” language, an impulse control classification, and some substance abuse parallel elements while also including common behavioral consequences, such as chasing, lying, illegal acts, social and educational costs, and bail-outs.
In the late 1990s, a congressional committee report and national prevalence study focused on gambling heighted awareness of gambling disorder. Though the classification and criteria remained unchanged in the DSM-IV-TR (APA, 2000), a number of neurobiological researchers began documenting physiological similarities between disordered gamblers and those with substance use disorders (Goudriaan, Oosterlaan, de Beurs, & Van den Brink, 2004, 2006; Potenza, 2001, 2008). These and other empirical findings led leading scholars to conclude that the growing evidence regarding the similarities between gambling and substance use disorders suggest they should be classified together (Grant, Potenza, Weinstein, & Gorelick, 2010; Potenza, 2006).
In 2013, pathological gambling was officially renamed “Gambling Disorder” and classified with substance use disorders as the first behavioral addition in the “Substance-Related and Addictive Disorders” chapter of the DSM 5 (APA, 2013). Explaining the change, the American Psychiatric Association reasoned that the scholarly literature had established that gambling disorder was similar to substance-related disorders in “clinical expression, brain origin, comorbidity, physiology and treatment” (APA, 2013). The criminal acts symptom was dropped from the classification, resulting in nine rather than ten criteria with slightly better classification accuracy than the prior criteria (Petry, Blanco, Stinchfield, & Volberg, 2013). However, the change in classification left unresolved the question of how to categorize sub-threshold problem gamblers, also called “low, moderate, and high-risk” gamblers; cut-scores for these groups differ across research studies, and the DSM provides no guidance beyond the criteria needed to meet diagnosis for gambling disorder.
The development of gambling disorder is complex and multifactorial, rooted in a wide array of bio-psycho-social factors that evolve over time. Researchers have proposed a number of etiological models to explain the development of gambling problems, including social reward (Ocean & Smith, 1993), behavioral (Weatherly & Dixon, 2007), cognitive-behavioral (Sharpe, 2002), neurobiological and genetic (Ibáñez, Blanco, & Saiz-Ruiz, 2002; Ibáñez, Blanco, de Castro, Fernandez-Piqueras, & Sáiz-Ruiz, 2003; Potenza, 2013). The highly cited and multifactorial Pathways Model by Blaszczynski and Nower (2002) asserts that a combination of specific factors creates predisposing, etiological subgroups of individuals who develop gambling problems in response to exposure to ecological stimuli, behavioral conditioning, and erroneous cognitions in a gambling environment.
The model proposes there are three subtypes of gamblers, distinguished by the presence or absence of specific premorbid psychopathology and biological vulnerabilities. All three groups share the commonalities of gambling opportunities that lead to the habituation of gambling and foster irrational and erroneous cognitions regarding winning and randomness (Blaszczynski & Nower, 2002). For Pathway 1 or “behaviorally conditioned” problem gamblers, those factors alone are enough to move them along the spectrum toward disorder; they lack evidence of mood, personality, or other pathology before the development of their gambling problems. In contrast, the model asserts that Pathway 2 “emotionally vulnerable” problem gamblers have a history of mood disorders, comorbid addictions, poor coping and problem-solving skills, problematic family backgrounds, and/or child abuse or neglect. As a result, these gamblers initiate gambling to escape aversive mood states and ultimately develop gambling problems in response to the ecological, conditioning, and cognitive factors outlined previously. Finally, the Pathways Model theorizes that Pathway 3 “antisocial-impulsivist” gamblers possess all the vulnerabilities of the previous pathway; however, in addition, these gamblers manifest high levels of impulsivity and antisocial personality traits and behaviors and a history of comorbid addiction and attention deficits. For this group, gambling is one of many pleasure-seeking behaviors.
A number of studies have attempted to explore or validate the Pathways Model in a variety of settings and populations (Balodis, Thomas, & Moore, 2014; Gupta, Nower, Derevensky, Blaszczynski, Faregh, & Temcheff, 2013; Ledgerwood & Petry, 2010; Tirachaimongkol, Jackson, & Tomnay, 2010; Turner, Jain, Spence, & Zangeneh, 2008; Valleur et al., 2015). A latent class analysis of gamblers using data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) identified three subtypes of disordered gamblers that corresponded roughly to the Pathways subtypes, ranging from a group with low levels of gambling severity and psychopathology to one with high levels of problem severity and comorbid psychiatric disorders (Nower, Martins, Lin, & Blanco, 2013).
As theorized by the Pathways Model, a growing number of empirical studies suggest that some proportion of problem and disordered gamblers have genetic and/or biological vulnerabilities that predispose them to sensation seeking and risk taking, which can lead to problem gambling. Early genetic studies found associations between dopamine-related gene sequences and disordered gambling (Comings et al., 1996, 1997, 2001); these gene sequences typically predispose individuals to engage in activities like gambling, which stimulate the release of dopamine, a chemical that mediates pleasure responses in the brain. As further evidence of this phenomenon, Parkinson’s disease medication, which supplements depleted dopamine, can induce disordered gambling behavior (Clark & Dagher, 2014; Ray et al., 2012).
Recently, Slutske and her colleagues undertook several related investigations of the genetic, familial transmission of disordered gambling behavior using data from more than 3,500 same-sex twins from the Australian Twin Registry. In one study, the researchers found that one-half to two-thirds of those with gambling disorder, particularly males, also shared a genetic vulnerability for alcohol use disorder (Slutske, Ellingson, Richmond-Rakerd, Zhu, & Martin, 2013). Other studies reported that sharing genetic or environmental factors with family members, especially personality traits of negative emotionality, were key predictors of gambling frequency and disorder in later adulthood (Slutske et al., 2014; Slutske, Cho, Piasecki, & Martin, 2013). Notably, difficulty controlling emotion at age three significantly predicted gambling problems in young adulthood, even when controlling for IQ and family socio-economic status (Slutske, Moffitt, Poulton, & Caspi, 2012). Mood-related impulsivity is also associated with disordered gambling in genetic studies (Clark et al., 2012). Taken together, these findings suggest there are strong, genetic familial factors (mood dysregulation, impulsivity, comorbidity) that are correlated with developing gambling problems. It is likely that these factors interact with ecological factors, conditioning effects, and cognitions that lead to disordered gambling.
These findings are supported by psychosocial research, reporting that early exposure to gambling, primarily with family members, is positively associated with disordered gambling. In one study, adolescent males who believed their fathers gambled too much were more than 3 times as likely than others to develop serious gambling problems, while girls who believed their fathers abused substances were at 2.5 times greater risk for disordered gambling (Nower, Derevensky, & Gupta, 2004). For adolescents, receiving lottery tickets as gifts during childhood has been associated with problem gambling and the continued purchase of tickets (Kundu et al., 2013). King and colleagues (2010) noted that parental substance use problems, combined with negative emotions and impulsivity, predicted gambling-related cognitive distortions, time spent gambling, and gambling problems, particularly in males. Most notably, it was the youth’s perception, whether or not true, that proved to be the most influential factor. Another study confirmed that parental gambling participation alone, even without demonstrating problems, predicted early gambling for boys and girls (Vitaro &Wanner, 2011). These findings support research that has established that perceived parental permissiveness toward gambling and other risky behaviors was significantly related to gambling, drug, and alcohol problems (Leeman et al., 2014) This is particularly troubling in light of the fact that gambling is typically viewed by parents and teachers as harmless activity (Campbell, Derevensky, Meerkamper, & Cutajar, 2011; Derevensky, St. Pierre, Temcheff, & Gupta, 2014). Indeed, teachers in one study reported that gambling in school can constitute a good learning experience (Derevensky et al., 2014), and a growing number of schools and districts feature casino nights, poker tournaments, and classes in stock investing without providing any prevention programs for problem gambling.
Traumatic experiences in childhood have also been linked to disordered gambling later in life. Specifically, several studies have reported that disordered gamblers are significantly more likely than their peers to report childhood sexual, physical, and emotional abuse (Black, Shaw, McCormick, & Allen, 2012; Felsher, Derevensky, & Gupta, 2010; Hodgins et al., 2010; Jacobs et al., 1989; Scherrer et al., 2007). In addition, the severity of childhood maltreatment has been linked to earlier onset of gambling behavior (Petry & Steinberg, 2005), mainly in female disordered gamblers who are more likely than males to report childhood victimization (Boughton & Brewster, 2002; Dowling et al., 2014; Petry & Steinberg, 2005). Not all studies have identified linkages between childhood trauma and disordered gambling (Leppink & Grant, 2015), though experiencing trauma has been linked to higher rates of comorbid disorders (Leppink & Grant, 2015) and negative impacts on functioning in those with preexisting comorbidity (Kausch, Rugle, & Rowland, 2006).
Finally, a key component in the etiology of problem gambling that is common across groups is the role of cognitive distortions during play. Gamblers erroneously perceive the nature of randomness, luck, and skill and believe they can somehow control the uncontrollable (Ladouceur & Walker, 1996; Clark, 2010). Four types of distortions are common to most disordered gamblers: the illusion of control, the gambler’s fallacy, biased evaluation, and the “near win.” The “illusion of control” (Langer, 1975) is the belief that a gambler can somehow control the gambling outcome through luck, skill, or a winning system. A preference for picking lottery numbers over those that are computer generated, using lucky daubers or troll dolls at a bingo game, or engaging in rituals before throwing dice demonstrate this erroneous cognition. Similarly, the “gambler’s fallacy” (Tversky & Kahneman, 1971) suggests that, as losses increase, the chances of winning big increase as well. By example, if “tails” comes up three times in a coin toss, a gambler might bet on “heads” because it is “due”; in reality, however, the chance of either heads or tails is exactly 50%, because each toss is independent of the one that came before. Gilovich (1983) first proposed that gamblers engage in “biased evaluation,” tending to accept wins at face value but explain away or discount their losses. This practice, in turn, results in characterizing a loss as a “near win” or in failing to identify losses disguised as wins, that is, where the win was smaller than the spin wager (Dixon, Harrigan, Sandhu, Collins, & Fugelsang, 2010). While these erroneous cognitions are common, to some extent, among all gamblers, it is reasonable to theorize that beliefs about luck, superstition, and winning also possess a transgenerational component, with caregivers modeling these misperceptions for their children who, in turn, adopt them as well. Combined with other etiological risk factors, these cognitions can fuel play and the development of disorder.
Between 78% and 86% of adults in the U.S. will gamble in their lifetimes, 63% to 82% in the past year (Kessler et al., 2008; National Opinion Research Center, 1999; Welte, Barnes, Wieczorek, Tidwell, & Parker, 2002). A majority of these adults will gamble occasionally and for recreation only. However, a proportion of those who gamble will do so to excess, resulting in serious adverse social, psychological, physical, familial, and legal consequences.
The prevalence of disordered and sub-threshold problem gambling varies widely among jurisdictions, many of which assess “problem gambling,” which includes disordered and sub-threshold gamblers, rather than adopting the stricter DSM-based clinical classification. In a comprehensive worldwide review of prevalence studies, Williams, Volberg, and Stevens (2012) reported that the standardized past year rate of problem gambling ranges from 0.5% to 7.6%, with a mean of 2.3%. Lower than average rates have been reported in Great Britain, South Korea, Iceland, Hungary, Norway, France, and New Zealand. The United States, Canada, Australia, Sweden, Switzerland, Estonia, Finland, and Italy report average rates. Above average rates were found in Belgium and Northern Ireland with the highest prevalence rates observed in Singapore, Macau, Hong Kong, and South Africa (Williams et al., 2012). Disparities in prevalence rates are due to a number of factors, including differences in: (a) assessment tools and differing scoring thresholds; (b) assessment time frames (e.g., lifetime versus past year); (c) survey administration (e.g., in-person interviews versus telephone surveys, mail surveys, etc.); (d) survey description (e.g., gambling survey versus health and recreation survey); and (e) time frame used for each question (e.g., weekly gambling, any past year gambling, etc.) (Williams et al., 2012).
In the United States, general population surveys have reported rates of past year problem gambling of around 2% and lifetime rates approaching 3% (Kessler et al., 2008; National Opinion Research Center (NORC), 1999; Welte et al., 2002). Studies have also noted a relationship between higher prevalence rates and closer proximity to gambling venues. For example, individuals living within 50 miles of a casino in one study had double the rate of disordered gambling (NORC, 1999). Another study found that living within 10 miles of a casino increased the odds of being a problem gambler by 90% (Welte et al., 2004), although subsequent regression analyses found that residential proximity was predictive only for men over 29 years but not for other demographic groups (Welte et al., 2007). Nevada, where gambling has long been legal and accessible, has slightly higher rates of problem gambling, particularly in counties closest to casinos (Shaffer, LaBrie, & LaPlante, 2004); those rates, however, are still modest, considering the amount of gambling available relative to other jurisdictions.
Williams et al. (2012) reported that rates of problem gambling have stabilized in recent years, despite a steady increase in availability. Those authors suggest this phenomenon could be due to a number of factors, including: (a) increased awareness of the potential harms, (b) decreased overall population participation in gambling after the novelty wore off, (c) problem gamblers leaving the population pool due to severe adverse consequences of their gambling (e.g., bankruptcy, suicide), (d) increased industry and/or government efforts at harm reduction and informed choice, and (e) increasing age of the population (Williams et al., 2012).
Despite this relative stability, there are sub-groups who experience significantly higher rates of problem gambling than other groups. Notably, these groups are also of particular interest to social workers, because they may be at risk for exploitation or abuse in society and/or be particularly susceptible to marketing ploys or gambling machines that typically result in greater losses.
Men report two to three times the rate of gambling pathology when compared to women (Petry, Stinson, & Grant, 2005). Men who develop gambling problems typically begin gambling at a younger age than women, who characteristically begin gambling later in life (Black et al., 2015; Ibanez, Blanco, Moreryra, & Saiz-Ruiz, 2003; Gonzalez-Ortega, Echeburua, Corral, Polo-Lopez, & Alberich, 2013; Nower & Blaszczynski, 2006; Tang, Wu, & Tang, 2007). Despite the later onset, however, women typically prefer gaming machines like video poker and slots (Nower & Blaszczynski, 2006), which have been called the “crack cocaine” of gambling because they rapidly generate losses and lead to serious gambling problems (Dowling, Smith, & Thomas, 2005). Irrespective of gender, frequent gambling and engaging in multiple forms of play lead to increases in problem severity (Ellenbogen, Derevensky, & Gupta, 2007).
Specific demographic profiles vary by jurisdiction and sampling strategy. For example, in a study of 2,670 gamblers who self-excluded from casinos in Missouri, the women were more likely to be older at the time of application, African American, and either retired, unemployed, or otherwise outside the traditional workforce (Nower & Blaszczynski, 2006). Women in that study were also more likely to report a prior bankruptcy (Nower & Blaszczynski, 2006), though Grant and Kim (2002) found equal rates of bankruptcy by gender, with women writing more bad checks and men more likely to lose significant savings. An Australian study found that female problem gamblers were more likely than males to be older and prefer machine gambling,;however, they were also more likely to be married, living with family and dependent children, and to report less than half the debt owed by males (Crisp et al., 2004). Several studies have reported that women prefer gaming machines and bingo while men opt for cards and sports betting (Grant & Kim, 2002; Odlaug, Marsh, Kim, & Grant, 2011; Potenza et al., 2001). In contrast, a recent large-scale Australian prevalence study found that younger age, low education, unemployment, non-English speaking, and playing gaming machines, table games, and lotteries were significant predictors of both male and female problem gamblers (Hing, Russell, Tolchard, & Nower, 2015). These findings suggest that jurisdictional differences may play a role in the gambling preferences of men and women.
There are also gender differences in physical and mental health comorbidity. Female problem gamblers report more mental and physical health problems than their same-age peers. A variety of studies have found that poorer overall general and mental health (Afifi, Cox, Martens, Sareen, & Enns, 2010), depressed mood (Blanco, Petry, Stinson, & Grant, 2006), suicidal thoughts and somatic complaints (Tang, Wu, & Tang, 2007), anxiety, and eating disorders (Dannon et al., 2006) are particularly characteristic of female problem gamblers and that those associations may begin in childhood and adolescence (Nower, Gupta et al., 2004). Women gamblers are much more likely than controls to be victims of intimate partner violence (Echeburua, Gonzalez-Ortega, Decorral, & Polo-Lopez, 2013) and physical abuse (Ibanez et al., 2003), to report a family history of alcoholism (Ledgerwood, Wiedemann, Moore, & Arfken, 2012) and to suffer from poor self-esteem (Echeburua, Gonzalez-Ortega, de Corral, & Polo-Lopez, 2011).
Compared to women, men who gamble problematically are much more likely to smoke excessively, be classified as heavy drinkers (Martins, Tavares, da Silva Lobo, Galetti, & Gentil, 2004), receive lifetime diagnoses of alcohol and drug use disorders (Blanco et al., 2006; Dannon et al., 2006; Desai, Maciejewski, Pantalon, & Potenza, 2006; Desai & Potenza, 2008), report incarceration (Potenza, Maciejewski, & Mazure, 2006), and engage in more sexual risk taking behavior (Martins et al., 2004). However, gambling problems are associated with increased odds of most past year mood and personality disorders, regardless of gender (Martins et al., 2004).
Higher rates of disordered gambling occur among racial and ethnic minorities, particularly Native Americans (Volberg & Abbott, 1997; Zitzow, 1996a, b), Asians (Marshall, Elliott, & Schell, 2009; Petry, Armentano, Kuoch, Norinth, & Smith, 2003; Toyama et al., 2014), Latinos (Barry, Stefanovics, Desai, & Potenza, 2011a; Welte, Barnes, Wieczorek, Tidwell, & Parker, 2001) and blacks (Barnes, Welte, Hoffman, & Tidwell, 2009; Barry, Stefanovics, Desai, & Potenza, 2011b; Cunningham-Williams, Cottler, Compton, & Spitznagel, 1998; Petry, Stinson, & Grant, 2005; Welte et al., 2001; Welte, Barnes, Wieczorek, Tidwell, & Parker, 2002; Welte, Barnes, Tidwell, & Hoffman, 2008). Analysis of the National Epidemiologic Survey on Alcohol and Related Conditions data found that Native Americans and Asians had the highest rates of disordered gambling, 2.3%; followed by blacks, 2.2%; whites, 1.2%; and Latinos, 1.0% (Alegria et al., 2009). That general population survey found that groups also differed significantly on socioeconomic indicators, comorbid psychopathology, and health conditions. Few studies have specifically investigated gambling disorder in particular minority groups in a large sample; rather, a majority of the studies have small, non-representative samples. Nevertheless, rates of disorder in most investigations are higher than those found in the white population.
Among Native Americans, both men and women have high prevalence rates for problem and disordered gambling, primarily because of low socio-economic status, unemployment, increased alcohol use, depression, historical trauma, and lack of social alternatives (Zitzow, 1996b). In studies comparing Native and non-Native Americans, Native American adults began gambling later in life than other adults but quickly developed problems (Zitzow, 1996b), whereas Native American adolescents report an earlier age of onset and higher levels of involvement than their peers (Zitzow, 1996a). However, much more research is needed to understand the nature and course of disorder in this group.
It is widely known that certain Asian groups, particularly Chinese, gamble at much higher rates than other gamblers. The insular nature of many Asian communities, combined with potential for stigma and language barriers, has limited research in this ethnic group. Petry et al. (2003) surveyed Southeast Asian refugees in community service organizations in the United States and found extraordinarily high rates of disordered gambling; about 59% of those surveyed met criteria for gambling disorder. In addition, more than half of all respondents had gambled within two weeks of the interview and 42% wagered more than $500 in the previous two months. A study of Cambodian refugees in the United States noted similar, though less severe, rates of disordered gambling, with 13.9% of participants meeting criteria for lifetime disordered gambling; traumatic exposure emerged as one significant predictor of higher rates of disorder (Marshall, Elliott, & Schell, 2009). In Japan, Toyama and colleagues (2014) reported very high rates of gambling disorder among men (9.0%), compared to women, who had average rates of pathology (1.6%). The findings, which controlled for socioeconomic and other demographic factors, noted that a majority of gamblers played Pachinko machines, highlighting the culturally specific facets of gambling preference and the severity of losses on machines, irrespective of type or location.
There are few studies of gambling among Latinos, and a majority of those are small-scale investigations of specific sub-groups. One general population survey that examined gambling problem severity and psychiatric disorders found that Latinos with sub-threshold gambling problems were more likely to have comorbid mood, anxiety, substance use, and personality disorders than white participants. In another study of Latino American veterans, Westermeyer and colleagues (2005) reported the lifetime prevalence rate for disordered gambling was 4.3%, significantly higher than rates in the general population; gambling disorder was also accompanied by high rates of major depressive (14.1%), alcohol (22.9%), and posttraumatic stress (12.2%) disorders.
A small study of undocumented Mexican immigrants in New York City found that more than half of those surveyed reported lifetime gambling and a majority of gamblers played scratch and win tickets or the lottery (Momper, Nandi, Ompad, Delva, & Galea, 2009). Those who sent money home to their families or had lived in the United States more than 12 years and those who reported one to five days of poor mental health in the past 30 days were most likely to gamble. As Latinos become a larger proportion of the population with increasing access to gambling opportunities, these findings suggest it will be imperative to ensure the availability of adequate screening and specialized gambling treatment in Spanish. Currently, few if any states have Spanish-speaking certified gambling counselors, and the few who are practicing are often geographically inconvenient for many Latino gamblers.
Similar needs exist with regard to black gamblers, including African Americans. Large-scale prevalence studies have long identified higher rates of disordered gambling among blacks, though blacks traditionally have lower rates of overall gambling participation (Cunningham-Williams, Cottler, Compton, & Spitznagel, 1998; Welte et al., 2001). Compared to whites in the epidemiologic NESARC study, for example, blacks had twice the rate (2.2%) of disordered gambling and lower scores on general health measures; they were also more likely to be women in the lowest income brackets (Alegria et al., 2009). Black youth are significantly more likely than whites to engage in heavy gambling (Barnes, Welte, Hoffman, & Tidwell, 2009). Being young, male, and non-Hispanic black was associated with high rates of gambling disorder in the U.S. National Comorbidity Survey Replication (NCS-R) data (Kessler et al., 2008). These findings generally mirror sociodemographic characteristics and comorbidity patterns found in earlier studies (Petry et al., 2005; Welte et al., 2001). Controlling for gender, age, and socioeconomic status, one study reported that blacks had 1.6 times the odds of being frequent gamblers, 3.7 times the odds of being disordered or problem gamblers, and 5.8 the odds of being disordered gamblers when compared to whites (Welte et al., 2001).
Smaller-scale studies support these findings as well. Comparing black and white callers to a gambling hotline, Barry et al. (2008) found that black problem gamblers were more likely to be female with less education who reported a longer history of problem gambling. A comparison of casino self-excluders found that women who self-excluded as problem gamblers were more likely to be black, older, separated, divorced, or widowed, report low personal income, and not be employed full-time (Nower & Blaszczynski, 2006). Most alarming, in a study of 275 predominantly black homeless individuals, nearly half reported gambling problems and 12% met clinical criteria for disordered gambling (Nower, Eyrich-Garg, Pollio, & North, 2015). Despite these findings, few social workers who work on hotlines or in homeless shelters, community agencies, or hospitals have familiarity with these statistics nor are they trained to conduct routine screening for symptoms, pathology, or adverse consequences of problem gambling. Ironically, diversity courses in master’s programs in social work that include content on addictive disorders also uniformly fail to address gambling problems as well.
In the United States and Canada, between 70% and 85% of adolescents report having gambled and 4% to 6% experience serious gambling problems—double the rate for adults (Blinn-Pike, Worthy, & Jonkman, 2010; Chalmers & Willoughby, 2006; Volberg, Gupta, Griffiths, Ólason, & Delfabbro, 2010). Gambling typically begins at home, and early gambling experiences appear to predict later onset of gambling problems (Kundu et al., 2013; Nower, Derevensky, & Gupta, 2004).
As discussed in the section on etiology, gambling is typically viewed as a benign activity by parents and teachers, who either tacitly condone or actively participate in gambling with minors (Campbell, Derevensky, Meerkamper, & Cutajar, 2011; Derevensky, St-Pierre, Temcheff, & Gupta, 2014).
This is particularly troubling since a significant body of research indicates that youth who begin gambling at a young age are more likely to experience later gambling problems (Rahman et al., 2012), have sex before age 18 (Martins et al., 2014), use and abuse substances (Nower et al., 2004), and engage in delinquent behaviors (Vitaro, Brendgen, Ladouceur, & Tremblay, 2001).
Youth who begin gambling with family or who have parents with addictions are most likely to develop gambling problems (Nower et al, 2004; Pagani, Derevensky, & Japel, 2009), particularly those who also experience impulsivity and emotional lability (Slutske, Moffitt, Poulton, & Caspi, 2012), anxiety and/or depression (Ste-Marie, Gupta, & Derevensky, 2006; Nower et al., 2004), and poor parental monitoring and disciplinary tactics (Vachon, Vitaro, Wanner, & Tremblay, 2004).
In the United States, card play and casino gambling have been frequently associated with disordered gambling symptoms in adolescents and young adults (Welte, Barnes, Tidwell, & Hoffman, 2009). The most troubling risk for youth, however, appears to be the increasing availability of Internet gambling. Despite attempts to monitor and limit online gambling to those over 18 in the three states where it is legal (New Jersey, Delaware, and Nevada), youth can still gamble on off-shore sites and, sometimes, gamble using their parents’ accounts with their permission. A growing number of free sites and social media outlets like Facebook offer gambling games that may serve as a gateway to high stakes gambling sites. A recent study of adolescents between 12 and 17 years found that 31.5% of participants engaged in simulated gambling activities on free gambling sites, social media, smartphone applications, and video-games (King, Delfabbro, Kaptsis, & Zwaans, 2014). The study found that adolescents with a history of gambling in simulated activities are at highest risk of endorsing symptoms of disordered gambling. Studies have also identified a significant association between online gambling, Internet addiction, psychopathology, and lower school achievement (Floros et al., 2013). These studies suggest that youth raised in an era with wide access to video and online games are at risk to move from free to pay sites over time. Studies of Internet gamblers have reported higher rates of gambling problems, greater gambling frequency, and gambling on a greater variety of games than non-Internet gamblers (Gainsbury, Russell, Hing, Wood, & Blaszczynski, 2013; Wood & Williams, 2007). This is likely amplified by the current legal status of daily fantasy sports betting as a non-gambling activity.
Historically, older adults reported lower rates of gambling participation (Kallick, Suits, Dielman, & Hybels, 1976; Mok & Hraba, 1991). However, rates began increasing with the widespread legalization of casino gambling in the 1990s (NORC, 1999; Welte et al., 2001). In 1975, only 35% of adults 65 and over reported lifetime gambling (Kallick, Suits, Dielman, & Hybels, 1976) as compared with 69% of those 61 and older in a 2001 survey (Welte et al., 2001).
Older adult gamblers typically begin gambling later in life but may develop problems more quickly than some of their younger peers (Nower & Blaszczynski, 2008; Petry, 2002). Studies have identified higher rates of older adult problem gambling among women (Nower & Blaszczynski, 2008; Petry, 2002); patrons of casino bus-trips (Bazargan, Bazargan, & Akanda, 2000), residents of senior centers and/or those attending bingo halls (Erickson, Molina, Ladd, Pietrzak, & Petry, 2005); ethnic minorities and veterans (Bazargan et al., 2000; Levens, Dyer, Zubritsky, Knott, & Oslin, 2005), and individuals with disabilities (Southwell, Boreham, & Laffan, 2008).
The typical older adult gambler reports a lower income and fewer gambling-related problems, arrests, illegal behavior, and debt than younger gamblers (Potenza, Steinberg, Rounsaville, & O’Malley, 2006). Those who frequent casinos are also more likely to be widowed, less educated with lower incomes, lack transportation, and report poorer mental health status and less social support than non-casino patrons (Zaranek & Chapleski, 2005). Among recreational gamblers, older adults are more likely than younger gamblers to gamble daily or multiple times per week and to report big wins (Desai et al., 2004). One study of self-excluded casino problem gamblers found that older adults began gambling in mid-life, experienced gambling problems around age 60, reported preferences for non-strategic forms of gambling like slot machines, and self-excluded due, in part, to fear of suicide (Nower & Blaszczynski, 2008). For comprehensive reviews of the literature on older adult gambling, see Subramaniam et al. (2015), Ariyabuddhiphongs (2012), and Tse, Hong, Wang, & Cunningham-Williams (2012).
The National Research Council of the National Academies first highlighted the relationship between chronic illness and disability more than a decade ago, reporting that about 6% of problem gamblers received disability services (National Research Council, 1999). Prevalence and other studies have also found higher levels of gambling pathology among the underemployed, those with chronic health problems, and those with lower incomes (Nower & Blaszczynski, 2006, 2008). Despite these mentions, there has been little research in these areas. One of the only studies reported that 26% of individuals receiving disability services met criteria for disordered or problem gambling (Morasco & Petry, 2006). In addition, those receiving disability services self-reported more gambling-related problems and lower levels of mental and physical health than those who did not receive disability services.
Individuals with lower levels of cognitive functioning may also be at higher risk of developing gambling problems (Lubinski, 2009; Rai et al., 2014; Shamosh et al., 2008). Wachter (2008) reported that adults with intellectual disability have nearly double the rate of gambling disorder compared to the general population. In a large population survey in England, researchers found that individuals with estimated verbal IQ scores below 85 were five times more likely than those with verbal IQ scores over 100 to be problem gamblers even when controlling for various sociodemographic factors (Rai et al., 2014).
This association between cognitive functioning and problem gambling has also been reported with adolescents. Studies have found higher rates of gambling disorder in adolescents with learning disorders (Parker et al., 2013), even after controlling for negative affectivity and ADHD symptoms. A key determinant in this relationship may be the role of cognitive distortions. In the general population, erroneous cognitions regarding luck, the possibility of winning, and the nature of randomness have been found to fuel excessive gambling. However, researchers have found that youth with special educational needs hold more erroneous beliefs about gambling and, therefore, have a higher risk of developing problematic gambling patterns than their peers (Taylor, Parker, Keefer, Kloosterman, & Summerfeldt, 2015).
It is well established that a majority of disordered gamblers have comorbid mental health and substance use disorders. In a national study in the United States, more than 73% of disordered gamblers met criteria for an alcohol use disorder, 38% for a drug use disorder, 60% for nicotine dependence, 50% for a mood disorder, 41% for an anxiety disorder, and 61% for a personality disorder, even after controlling for gender, race, marital status, age, geographic location, and socioeconomic status (Petry, Stinson, & Grant, 2005). A number of other studies have likewise reported significantly higher levels of mood, bipolar, generalized anxiety, posttraumatic stress, and substance use disorders in disordered gamblers as compared to the general population (Chou & Afifi, 2011; Kessler et al., 2008; Ledgerwood & Petry, 2006. For a review, see Dowling et al., 2015) Those figures are higher in the homeless population, which reported very high rates of problem (46%) and disordered (12%) gambling as well as personality, bipolar, and post-traumatic stress disorder (PTSD) and drug, alcohol, and nicotine abuse and dependence (Nower, Eyrich-Garg, Pollio, & North, 2015).
A growing number of studies investigate the relationship of disordered gambling to PTSD (Ledgerwood & Milosevic, 2015; Ledgerwood & Petry, 2006; McCormick, Taber, & Kruedelbach, 1989; Specker, Carlson, Edmonson, Johnson, & Marcotte, 1996; Taber, McCormick, & Ramirez, 1987). For example, Ledgerwood and Petry (2006) found that 34% of treatment-seeking gamblers reported a high frequency of PTSD symptoms, which were further correlated with gambling and psychiatric symptom severity, impulsivity, and dissociation. This association is particularly notable among veterans. Westermeyer and colleagues (2005) reported that 10% of Native American veterans met lifetime criteria for gambling disorder and had a high prevalence of comorbid substance, mood, and antisocial personality disorder. Higher rates of gambling disorder have been identified in veterans with history of gambling in the family (Daghestani, Elenz, & Crayton, 1996) and those with poor coping skills (Castallani et al., 1996).
Societal and Individual Costs
Increasingly limited options often compel disordered gamblers to resort to criminal behavior. In fact, the behavior is so common that it was removed as a criterion in the DSM-5 (APA, 2013). In addition, mounting debts can also lead to bankruptcy and its attendant societal costs.
There is a significant relationship between crime and disordered gambling (Blaszczynski & McConaghy, 1994; Folino & Abait, 2009; Meyer & Fabian, 2005; Potenza, Steinberg, McLaughlin, Rounsaville, & O’Malley, 2000; Turner, Preston, Saunders, McAvoy, & Jain, 2009). For a comprehensive summary of this topic, see Nower and Blaszczynski, 2013). In a national survey of gambling in the United States, more than 30% of disordered gamblers and 36% of sub-clinical problem gamblers reported arrests, compared to around 12% of low-risk and 5% of non-gamblers (National Opinion Research Center [NORC], 1999). The study also reported that 31% of disordered and problem gamblers go to jail, compared to just over 4% of low-risk and non-gamblers, costing the criminal justice system around $2,000 per gambler. Those rates are consistent with findings in other studies (see e.g., [Australia] Blaszczynski & McConaghy, 1994; [Argentina] Folino & Abait, 2009; [Germany] Meyer & Fabian; 2005; [Canada] Turner et al., 2007) as well as in treatment (Ledgerwood, Weinstock, Morasco, & Petry, 2007), Gamblers Anonymous (Abait & Folino, 2008), and hotline caller populations (Potenza et al., 2000).
High rates of gambling pathology have, likewise, been identified among prisoners, probationers, and parolees (Templer, Kaiser, & Siscoe, 1993; Turner et al., 2007, 2009). One study reported that 34% of non-imprisoned participants who were on remand, probation, or parole at the time of the study met criteria for disordered gambling, and 38% did so for problem gambling (Lahn, 2005). About 25% of those surveyed endorsed gambling as a key contributor to their offense, and nearly 50% of respondents reported obtaining money illegally to gamble. Another study reported that about 20% of newly sentenced inmates claimed their crime was gambling-related, 21% met criteria for gambling disorder at the time of assessment, and 16% did so in the six months before going to prison (Abbott, McKenna, & Giles, 2005).
Despite these findings, there is still limited understanding regarding the relationship of disordered gambling and crime. A majority of existing studies consist of self-report with a small, self-selected group of volunteer participants who may be subject to recall and social desirability biases. It is also generally unknown which offenses were motivated by the desire to generate funds for gambling or cover up the consequences of gambling and which were related to other causes, including a penchant for antisocial and impulsive behavior. Few arrest, pre-sentence, probation, or other court reports and documents detail the reason the crime was committed; rather, reports typically state the nature of the offense and the evidence for believing the defendant committed it. For that reason, there is no way to independently verify whether crimes are, in fact, gambling-related in the vast majority of cases.
Debt and Bankruptcy
The main reason gamblers initiate gambling is to win money. As habitual, excessive gambling proceeds toward disorder, gamblers typically accumulate significant amounts of debt, file for bankruptcy, and suffer personal and familial consequences like divorce and suicide (Downs & Woolrych, 2010; Edwards, 2003; Ladouceur, Boisvert, Pepin, Loranger, & Sylvain, 1994; NORC, 1999; Nower & Blaszczynski, 2008).
Research has yet to clearly establish whether legalized gambling opportunities have led to overall increases in rates of personal bankruptcy, primarily because most governments fail to require debtors to detail precipitators of debt. Several studies have found statistical correlations between the introduction of casino gambling and overall increases in per-capita bankruptcy filings (Nichols, Stitt, & Giacopassi, 2000). For example, Nichols and colleagues (2000) reported that filings rose significantly in five of eight counties studied; however, the analysis failed to control for unemployment rate, percentage of males in population, and other variables that may significantly impact rates. Another study reported that bankruptcy filing in a gambler’s home state increased 10% following visits to casinos in other states (Garrett & Nichols, 2008) in all but one state studied. Modeling the association of bankruptcy filing rates around casinos, Barron, Staten, and Wilshusen (2002) found that removing casinos would result in a 5% decrease in bankruptcy filing locally and a 1% decrease in the national bankruptcy rate. However, other studies have identified unemployment rates (de la Vina & Bernstein, 2002) and socio-demographic factors (Thalheimer & Ali, 2004) as the most significant determinants of personal bankruptcies, not access to gambling.
Such conflicting research findings mirror the lack of consensus in court decisions regarding guidelines for treating gambling-related credit card debt. In general, courts consider a number of factors, including the length of time (pattern) between the charges and the filing of the bankruptcy, the number and amount of charges, and the financial condition and employment of the gambler at the time of the charges (see In re Dougherty, 1988; In re Troutman, 1994). Whether or not gamblers meet the discharge threshold, there are social cost implications. Destitute gamblers and their families utilize public assistance and services at a cost to the community; discharged credit card debt is also passed on to other customers and businesses in the form of fees and interest, further increasing the societal cost associated with this disorder.
Health, Mental Health, and Familial Consequences
Studies have found that a lifetime diagnosis of disordered gambling is associated with medical disorders and increased medical utilization (Morasco & Petry, 2006). Specifically, one national study in the United States reported that disordered gamblers were more likely than low-risk gamblers to have been diagnosed with tachycardia, angina, cirrhosis, and other liver diseases; they were also more likely to have been treated in an emergency room in the past year (Morasco & Petry, 2006). These health problems often coexist with psychiatric conditions reported in “Comorbidity.”
A number of studies have also investigated the impact of problem gambling on families: anger, emotional distress, depression (Hodgins, Toneatto, & Makarchuk, 2007; Lorenz & Shuttleworth, 1983; Lorenz & Yaffee, 1986; see Kourgiantakis, Saint-Jacques, & Tremblay, 2013 for a review). Female partners of problem gamblers report higher rates of suicidal ideation and attempts, somatic complaints, substance abuse, and impulsive spending in response to the stress caused by gambling losses (Lesieur & Rothschild, 1989; Lorenz & Shuttleworth, 1983; Lorenz & Yaffee, 1986). In addition to an increased likelihood of developing addictions, children of problem gamblers report disrupted relationships, financial difficulties, diminished need fulfillment and higher levels of stress, anxiety, and depression than youth with no parental gambling problems (Hsu, Lam, & Wong, 2014). They are more likely than their peers to experience parental physical violence and abuse, to feel sad, shameful, helpless, and isolated (Jacobs et al., 1989; Lesieur & Rothschild, 1989). News reports have documented children found abandoned on casino premises while their parents gambled. Notably, the U.S. National Gambling Impact Study Commission (1999) underscored that cases of child abandonment at one large casino were so common that authorities posted signs in parking lots warning parents not to leave their children unattended.
Excessive gambling is also related to family violence and child maltreatment. Afifi and colleagues (2010) found that gambling disorder was associated with increased odds of the perpetration of dating violence, severe marital violence, and severe child abuse victimization. An in-depth study of family violence and gambling in Australia, New Zealand, and Hong Kong reported that more than half of help-seeking family members of problem gamblers had experienced some form of family violence in the past year (Suomi et al., 2013). The research concluded that family violence was more likely to evolve from deep-seated anger and mistrust and that victimization was typically an outcome of the gambler’s anger and frustration.
In extreme cases, gambling disorder can lead to suicide and familicide (Anderson, Sisack, & Varnik, 2011). Studies have reported that problem gamblers are more than three times as likely as the general population to attempt suicide (Newman & Thompson, 2007). Of treatment-seeking disordered gamblers, more than 81% in one study expressed suicidal ideation and 30% reported one or more attempts in the past year (Battersby, Tolchard, Scurrah, & Thomas, 2006). In a large study in Hong Kong, 20% of treatment-seeking gamblers reported suicidal ideation and 0.6% indicated they were thinking of killing their families (Wong, Kwok, Tang, Blaszczynski, & Tse, 2014). Another study of completed suicides found that nearly 20% showed evidence of gambling prior to death and 47% involved individuals with gambling-related debts (Wong, Chan, Conwell, Conner, & Yip, 2010). Rates are similar in youth and young adults. Stuhldreher and colleagues (2007) noted that college students who gambled were twice as likely as other students to consider or to attempt suicide; problem and disordered gambling also proved the most significant predictor of suicidality in teenagers, irrespective of level of depression (Nower, Gupta, Blaszczynski, & Derevensky, 2004).
Diagnosis and Treatment
Since the early 21st century, researchers have developed a number of screening tools for disordered gambling. Most of these tools are hampered by a lack of conceptual clarity over how to identify and classify sub-threshold problem gamblers and by the every-shifting criteria in new iterations of the DSM.
The South Oaks Gambling Screen (Lesieur & Blume, 1987), a 20-item screen based on the DSM-III-R, was developed for use in clinical settings but subsequently used for population surveys as well. While reliability of the tool is satisfactory, the SOGS yields high rates of false positives in some populations (Stinchfield, 2013). A majority of prevalence surveys no longer use the tool, which has also been replaced in a majority of clinical settings by measures based on the current version of the DSM or with more robust psychometric properties.
The Canadian Problem Gambling Index (Ferris & Wynne, 2001) was developed in response to the need for a psychometrically sound measure for use in general population surveys. The CPGI is a 31-item instrument, which includes the nine-item Problem Gambling Severity Index (PGSI). The PGSI was based on the most predictive items of the SOGS as well as DSM core items so as to be useful to non-clinical samples and generalizable across populations, including countries that do not use the DSM system of classification. The PGSI has demonstrated high internal consistency and validity (Stinchfield, 2013) and is currently the “gold standard” instrument used in both clinical settings and prevalence studies worldwide. The instrument scores respondents in categories: non-problem, low-risk, moderate-risk, and problem gambling. Currie, Hodgins, and Casey (2013) have proposed an alternate scoring that better discriminates the low- and moderate-risk categories.
Stinchfield (2013) has summarized the uses, strengths, and limitations of a majority of available brief and extended problem severity screening tools in his comprehensive review. In addition to tools that measure gambling problem severity, a number of authors have published instruments that assess aspects of gambling, including motives (Stewart & Zack, 2008), craving (Young & Wohl, 2009), and cognitions (Raylu & Oei, 2004). An etiological screening instrument, based on the Pathways Model (Blaszczynski & Nower, 2002), is currently under review. That tool will allow clinicians to assign clients to pathways and tailor treatment to include relevant etiological risk factors.
Behavioral interventions, particularly those with a cognitive component, are the standard treatments for gambling disorder. A meta-analysis of behavioral therapies reported a large effect size of 2.01 at the end of treatment and an effect size of 1.59 at 17-month average follow-up (Pallesen, Mitsem, Kvale, Johnsen, & Molde, 2005). Despite neurobiological features of the disorder outlined previously, a similar meta-analysis of pharmacological treatment failed to strongly support the use of any specific medication to treat gambling disorder (Bartley & Bloch, 2013), though individual cases may warrant tailored drug therapy.
A key feature in cognitive-behavioral therapy is addressing cognitive distortions that fuel play, habituation, and, ultimately, the cycle toward disorder. Treatment primarily attempts to restructure cognitions through education on the concepts of randomness and the independence of events, the odds of winning, and the futility of common cognitive fallacies (Gaboury & Ladouceur, 1990; Ladouceur, Sylvain, Letarte, Giroux, & Jacques, 1998). Studies that also incorporate problem solving and relapse-prevention are the most successful at decreasing gambling severity and urges and increasing the perception of control over time (Bujold, Ladouceur, Sylvain, & Boisvert, 1994; Ladouceur et al., 1998; Sylvain, Ladouceur, & Boisvert, 1997). See Blaszczynski and Nower (2013) and Fortune and Goodie (2012) for reviews of cognitive-based treatment studies and techniques. To date, even successful manualized treatments are largely homogenous “one-size-fits-all” programs that disregard the possibility that etiological sub-groups, ethnic minorities, and others may require individualized treatment to be successful and prevent relapse.
A number of new and promising variations on traditional therapy are generating research interest: mindfulness-enhanced cognitive therapy (Toneatto, Pillai, & Courtice, 2014), meditation awareness training (Shonin, VanGordon, & Griffiths, 2014), imaginal desensitization (Blaszczynski & Nower, 2013), motivational enhancement (Hodgins, Currie, & el-Guebaly, 2001; Ledgerwood et al., 2013), and brief, motivational treatments (Hodgins, Currie, el-Guebaly, & Peden, 2004; Hodgins, Currie, Currie, & Fick, 2009). A majority of these techniques focus on enhancing motivation, a key strategy in engaging gamblers in treatment and limiting drop-out rates.
Researchers have yet to clearly understand why gamblers fail to attend treatment at rates comparable to those with substance use disorders; however, studies have consistently found that gamblers are reticent to present for treatment. Aside from 1-800 numbers and occasional billboards, there is little promotion of problem gambling services. As a result, studies have found there is low awareness of the availability of services (Gainsbury, Hing, & Suhonen, 2014). Gamblers have also reported being concerned about cost, effectiveness of treatment, and stigma (Rockloff & Schofield, 2004). Insurance programs do not always cover gambling disorder absent a co-occurring mood disorder, and not all states in the United States provide subsidized treatment. Excessive gambling has long been seen as a vice rather than a disease, leading some gamblers to hide their problems even when circumstances are dire. Other gamblers, sometimes the most severe, deny they have a gambling problem and see no reason to attend treatment (Suurvali, Hodgins, Toneatto, & Cunningham, 2012).
Motivating clients to attend treatment does not necessarily result in treatment completion. Studies employing different methodologies have estimated that 30% to 50% of treatment seekers drop out after assessment or a few initial sessions (Robson, Edwards, Smith, & Colman, 2002; Ladouceur, Gosselin, Laberge, & Blaszczynski, 2001; Sylvain et al., 1997). Those who drop out are characterized by high levels of impulsivity (Leblond, Ladouceur, & Blaszczynski, 2003) and sensation-seeking traits (Smith et al., 2010), mood disorders, high levels of guilt and shame, gambling for escape, and a lack of readiness for change (Dunn, Delfabbro, & Harvey, 2012). Notably, being male and having a low income job, longer course of gambling problems, higher frequency of play, and higher levels of anxiety and depression were correlated in one study with early drop-outs (Tolchard & Battersby, 2013). That study noted that females, once engaged in therapy, were likely to continue despite endorsing some of the same risk factors as the male drop-outs. Perhaps this is due to the fact that women gamblers are more likely than men to report having received non-gambling-related mental health treatment prior to seeking help for gambling (Potenza et al., 2001) and to express a greater readiness for change (Ledgerwood, Wiedemann, Moore, & Arfken, 2012). Incorporating problem-solving and support-seeking strategies into therapy appears to correlate with more positive attitudes to treatment for both men and women (Matheson, Wohl, & Anisman, 2009). However, at 6-months post treatment, one study found that men had improved significantly more on gambling severity and rates of abstinence than women, who found specific components of the gambling intervention targeting identification of high-risk situations, gambling beliefs, and attitudes to be unhelpful (Toneatto & Wang, 2009). These findings suggest that treatment is highly individualized and dependent, in large part, on the underlying motives for gambling which, in turn, are likely related to etiological risk factors. The lack of public awareness about gambling disorder and its effects, combined with limited treatment availability and intervention strategies, makes it difficult to provide effective treatment, motivate attendance, and sustain participation over time.
Policy Implications and the Role of Social Workers
This overview of a very complex and understudied disorder clearly demonstrates that social workers are critical to improving the understanding of gambling disorder and ensuring that screening, intervention, and treatment are afforded to everyone, particularly those at risk. On a macro level, there is currently no federal funding for gambling treatment or research. Insurance companies and employee-assistance programs are mixed as to whether they will fund gambling treatment independent of another recognized mental health disorder. Accordingly, gambling treatment is usually funded on a state-by-state basis, out of taxes on casinos and other gambling operators. Some states have no formalized treatment infrastructure while others fund hotlines, treatment networks, and residential facilities. Tax revenue generated in a state typically resides in the general revenue fund rather than receiving a specific earmark for gambling treatment only. As a result, in times of economic shortfall, monies are cut back, eliminated, or reapportioned to substance abuse treatment. This continually impacts the most vulnerable members of our society—those who are typically championed by social workers: older adults, ethnic minorities, individuals with disabilities, youth, veterans, and those with low socioeconomic status and levels of education.
However, to date, social work has been silent on these issues. There is currently little expressed interest or awareness in the social work community about problem and disordered gambling. Gambling is conspicuously absent from the National Association of Social Workers advocacy, publications, and special practice sections, which still use the outdated terminology “Alcohol, Tobacco, and Other Drugs” as the only addiction offerings.
This lack of awareness in the profession is reflected in bachelor’s and master’s level curricula in schools of social work nationwide. A majority of schools offer no addiction training at the bachelor’s level. At the master’s level, addiction offerings are generally limited to one or two courses in substance use disorders, despite the grudging recognition by the psychiatric community that behavioral addictions have real and debilitating consequences that parallel those of substance use disorders. As educators, then, we are graduating practicing social workers and agency administrators who have no familiarity with gambling disorder in an era of continued expansion of gambling opportunities. Because of the complex nature of the disorder, the National Council on Problem Gambling recommends counselors receive at least 30 hours of specialized training in screening and treatment, leading to national certification. Yet few schools make this training available in the curriculum or continuing education programs offered to post-graduate practitioners. As a result, there are few social workers who are trained to identify gambling problems in the settings in which they work and are most likely to encounter a high prevalence of problem gamblers: child welfare agencies, mental health settings, emergency rooms, schools, family violence shelters, human service organizations, community agencies, homeless shelters, and the criminal justice system.
Given that social workers are the primary, initial points of contact in these settings, it is imperative that they be educated in the symptoms, consequences, screening, and treatment of the disorder. Schools of social work should adopt an addiction curriculum that includes the prevalence, etiology, and treatment of gambling disorder and awareness of other behavioral addictions, particularly “Internet gaming disorder,” which is a condition for further study in the DSM-5. In addition, it is important for diversity and oppression courses to include information on gambling and its disproportionate impact on ethnic minorities; gambling screenings should accompany other routine assessments in treatment courses. Most important, social work programs should foster relationships with state gambling councils to train students and post-grads in treating problem gamblers.
In community and legislative arenas on both the state and federal levels, social workers could lead efforts to establish funding and infrastructure support for prevention, school education programs, and diagnosis and treatment of problem gambling. Specifically, in the coming years it will be increasingly important to ensure that gambling is included in standardized screens used in health and mental health settings, particularly those that deal with vulnerable groups and children who are typically left to fend for themselves in unpredictable, impoverished, and emotionally volatile environments. As more gambling opportunities become available through interactive media such as mobile phones, televisions, and the Internet, social workers have a critical role to play in educating and protecting those we have served throughout history.
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