Printer Friendly

Gambling behind the walls: a behavior-analytic perspective.

The field of behavior analysis has done an excellent job of not only raising public awareness about certain disorders (e.g., Autism), but also developing the best treatments for those disorders. The field has not yet, however, done so for many behavioral disorders. For instance, pathological gambling is a major societal issue, but little behavior-analytic work has focused on it despite the fact that the disorder occurs at several times the frequency of other, more publicized, disorders such as Autism (Dixon, Marley, & Jacobs, 2003). One possible reason for the dearth of behavior-analytic research could be B.F. Skinner's (1953) conclusion that gambling behavior could be understood in terms of schedules of reinforcement. Subsequent research, however, suggests that multiple factors likely control gambling behavior (e.g., see Weatherly & Dixon, 2007).

According to most prevalence studies, the rate of pathological gambling in the general population likely ranges between 1 -2% (see Petry, 2005, for a review). In terms of absolute numbers, these percentages represent millions of individuals in the United States alone. The numbers do not, however, encapsulate the problem. That is, pathological gamblers are individuals who officially meet diagnostic criteria according to the DSM-IV-TR (American Psychiatric Association, 2000). Other people are labeled as "problem gamblers" because they display some symptoms of pathological gambling, but not enough symptoms to be diagnosed clinically as pathological. The prevalence rates of problem gambling are also difficult to estimate, but it seems reasonable to conclude that the number of problem gamblers exceeds the number of pathological gamblers, possibly another 5% or more of the population (see Petry, 2005).

Pathological gambling is currently classified as an impulse disorder that is not otherwise classified. (1) To meet diagnostic criteria for pathological gambling, an individual must display at least five of the ten possible symptoms. Three of these symptoms are generally considered "cognitive" in nature. The possible cognitive symptoms include a preoccupation with gambling, feeling the need to increase one's betting so as to maintain the original level of excitement or arousal, and feeling restless when one attempts to cease gambling. (2) Six of the remaining seven symptoms are descriptive of behaviors in which the gambler might engage. They are trying to cease gambling but failing, increasing one's betting in an attempt to win back what has been lost (i.e., chasing one's bet), lying to others so as to conceal one's gambling, engaging in illegal behavior to finance one's gambling, putting one's opportunities (e.g., job, personal relationships, etc.) in jeopardy because of continued gambling, and turning to other individuals to finance one's gambling or to address financial issues that have resulted from one's gambling. (3)

Interestingly, only one of the official symptoms for pathological gambling specifically identifies a contingency that might be controlling the person's gambling behavior; that the person gambles as an escape. It will therefore likely come as no surprise to behavior analysts that this particular symptom may have special relevance, which will be addressed later in the paper.

As one might imagine, the research literature on gambling is immense (and beyond the scope of the present paper to review all of it), and many researchers have attempted to identify the factors that lead to pathological gambling. Unfortunately, the vast majority of this research is correlational in nature. As such, associative relationships can be, and have been, identified. However, the causal mechanisms underlying the disorder have not been firmly established. Regardless, research has potentially identified the establishing operations (Michael, 1993) or setting events (Kantor & Smith, 1975) for pathological gambling. As outlined by Petry (2005), there are six major risk factors for pathological gambling, several of which may be intercorrelated. One is gender, with males displaying a greater prevalence rate than females. A second is age, with the prevalence rates of pathological gambling decreasing with age. A third is ethnicity, with ethnic minorities suffering from pathological gambling at a significantly greater frequency than the majority population. For instance, Wardman, el-Geubaly, and Hodgins (2001) estimated that American Indians displayed pathological gambling at up to 15 times the rate as Caucasians. A fourth risk factor is socio-economic status, with those of low socio-economic status displaying the disorder at a significantly greater frequency than those of high status. A fifth factor is marital status. Individuals who are single or divorced are more likely to be pathological gamblers than are individuals who are married.

Last, but certainly not least, is substance use and abuse. People who use or abuse drugs are far more likely to be pathological gamblers than are people who do not use drugs. Petry (2005) highlighted that drug use is the strongest of the six risk factors. So strong, in fact, that she recommended that mental-health providers who work with substance abusers would be wise to also screen for pathological gambling because the comorbidity rate of the two disorders (i.e., substance dependence & pathological gambling) is so high.

In sum, a young male who is an ethnic minority, is not affluent, is single, and uses drugs is at high risk for gambling pathologically. Behaviorally, this description would seem to make sense in terms of establishing operations. For example, such an individual may have a problem getting or maintaining a job, which would set up an establishing operation in terms of money and potentially alter the contingencies that maintain gambling behavior. With that said, finding that such a person is at increased risk for pathological gambling is probably less than surprising. An individual with these characteristics is quite likely to be at increased risk for a number of behavioral disorders or problems.


It is certainly true that the risk factors for pathological gambling are not isolated to that particular disorder. That is, the same characteristics are also risk factors for incarceration. For instance, of the over 1.5 million individuals in the United States in 2009 who were incarcerated, 93% were male (Bureau of Justice Statistics, 2009a). Overall, this population is relatively young, with 56% of the male inmate population less than 40 years old. Similarly, for females, 66% of the inmates were less than 40 years old (Bureau of Justice Statistics, 2009b). Furthermore, ethnic minorities are overrepresented in the prison population. In terms of ethnicity, only one third of the male, and slightly less than half of the female, prisoners were Caucasian (Bureau of Justice Statistics, 2009b). In other words, non-majority ethnicities constitute the majority of the individuals incarcerated in the United States.

Given the overlap between the risk factors for pathological gambling and incarceration, one could reasonably predict that the rate of pathological gambling among the inmate population might be high. That prediction turns out to be accurate (e.g., Anderson, 1999). Whereas the prevalence rate of pathological gambling in the general population likely ranges between 1-2% (Petry, 2005), research on inmate populations suggests that the prevalence rate of pathological gambling is 30% or higher (Lahn, 2005; Nixon, Leigh, & Nowatzki, 2006; Williams, Royston, & Hagen, 2005; Zorland, Mooss, & Perkins, 2008). Williams et al. (2005) assert that inmates display the highest frequency of pathological gambling of any population. These data would seem to argue that behavior-analytic research is needed not only on this population, but also so that preventative practices can also be identified.

Although there is an extremely high rate of pathological gambling in the prison population, one might be tempted to discount the issue because these individuals are segregated from society. In other words, why worry about what goes on in prisons? The answer to that question is straightforward. People in prison do not necessarily remain there indefinitely. For instance, research (e.g., Erisman & Contardo, 2005; Harlow, 2003; Harrison & Beck, 2006, Petersilia, 2003) suggests that up to 95% of all incarcerated prisoners will ultimately be released. U.S. Department of Justice figures suggest that approximately 750,000 prisoners are released each year from state and federal prisons. These individuals return to communities and bring their problematic behaviors with them.

Furthermore, if the problematic behavior leads to illegal activities, (4) then not only do those activities have the potential to disrupt the community, they can also lead to reincarceration of the individual. Research suggests that approximately 40% of released offenders will return to prison within three years of their release (Pew Center on the States, 2011). Furthermore, states spend an amazingly large amount of money, estimated at a collective $50 billion per year, in an attempt to decrease the rate of recidivism. However, such attempts have been largely unsuccessful (Pew Center on the States, 2011). Having successful treatment programs for pathological gambling in the prison environment could therefore have multiple benefits.


Given that the risk factors between pathological gambling and being incarcerated overlap substantially, finding high rates of pathological gambling among prison populations should not be shocking. However, the risk factors do not cause pathological gambling or, if they do, they do not do so directly. Thus, a reasonable follow-up question is why are rates of pathological gambling astronomically higher in inmate populations than in the general population (Lahn, 2005; Nixon et al., 2006; Williams et al., 2005; Zorland et al., 2008)?

One potential reason lies in the current symptoms of pathological gambling itself, namely engaging in illegal activity to finance one's gambling. For instance, Williams et al. (2005) reported that, for inmates who qualified as pathological gamblers, half of the crimes that had been committed were related to the individuals' gambling. Zorland et al. (2008) suggested that the percentage of gambling-related crimes was in fact much higher than 50%, approaching 90%. Data from Lahn (2005), on the other hand, indicate that although nearly half of the incarcerated respondents report having stolen money to pay off their gambling debts, only a quarter of the respondents indicated that gambling-related offenses were the reason for their incarceration. Regardless of the reason for incarceration, most criminals who qualify as pathological gamblers report that they have committed crimes related to their gambling (Blaszczynski, McConaghy, & Frankova, 1989).

A second potential reason for the high prevalence of pathological gambling among the inmate population may be the prison environment itself. That is, although gambling is illegal in the prison environment, such a highly controlled environment limits the number of other activities in which the inmates can engage. In other words, gambling may be reinforced by escape, however temporarily, from the many different aspects of the prison environment that inmates find aversive. If so, then one can speculate that the prison environment itself may be producing or facilitating pathological gambling. Unfortunately, so few studies have been conducted on pathological and problem gambling in prison populations (5) that it is not possible to estimate with much confidence how many pathological and problem gamblers who are incarcerated qualified under those labels prior to being incarcerated versus how many developed the symptoms after incarceration. However, it can be said that some researchers assume that gambling within the prison system may be maintained because of the aversive or uncomfortable conditions in prison (e.g., to alleviate boredom; Oregon Department of Human Services, 2007).

The definitive answer for why the rate of pathological gambling is so high in the prison setting is not known. However, it may be informative to look at rates of pathological gambling in a different population that is also in a highly controlled setting; military personnel. Research on gambling on the military population suggests that rates of pathological gambling may exceed that observed within the civilian population (Kindt, 2007). However, when the demographic risk factors for pathological gambling are controlled for statistically, the rate of the disorder may not exceed that of the civilian population (Polich, 1981). This comparison suggests that at least part of the answer for the high rate of pathological gambling in the prison population lies with the behavioral repertoires of criminals prior to their entry into the prison system. That argument can be made because, if the high rate was solely the outcome of the prison environment, one would also expect to see an extremely high rate of pathological gambling on military bases where the range of extracurricular activities might also be limited. But that seems to not be the case. On the other hand, military personnel may have opportunity to leave the military base to socialize, which is not an option for prison inmates. Thus, these contingencies may also explain the difference between the populations.


No specific data exist to support the contention that escape contingencies might be facilitating pathological gambling in the prison environment. However, there are several pieces of evidence that suggest escape plays a unique role in pathological gambling. As noted above, gambling as an escape is an official symptom of pathological gambling and is also the only one of the ten potential symptoms that outlines a contingency that may be maintaining the person's gambling behavior. Likewise, research utilizing non-inmate populations suggest that this contingency is unique relative to positive reinforcement contingencies (i.e., gambling for money, excitement, social attention, etc.).

That research started when Dixon and Johnson (2007) introduced the Gambling Functional Assessment (GFA) survey, which was originally designed to assess four possible maintaining contingencies for the respondent's gambling behavior. The original GFA consists of 20 self-report items, endorsed on a seven-point Likert-like scale, with the four potential categories being gambling for tangible outcomes (i.e., money), for the social aspects of gambling, for the sensory experience, and as an escape. The category that receives the highest score is theoretically the primary maintaining contingency for that respondent's gambling behavior.

Although originally designed to measure four contingencies, the results from Miller, Meier, Muehlenkamp, and Weatherly (2009) suggested that the GFA was likely only measuring two. In their study, 949 undergraduate university students completed the GFA. An exploratory factor analysis conducted on data from half of the respondents suggested a two-factor solution. A confirmatory factor analysis on the data from the other half of the respondents was consistent with a two-factor model. In both cases, the items that were designed to identify the contingencies of tangible, social attention, and sensory experience tended to load onto one factor and the items designed to identify the contingency of escape loaded onto the second factor. Miller et al. (2009) therefore labeled the two factors positive and negative reinforcement, respectively.

One very intriguing aspect of the data from Miller et al. (2009) was how scores on Factor 2 (i.e., escape) varied with respondents' total score on the GFA (i.e., summing across all 20 items). Specifically, very few respondents endorsed items related to escape. However, when they did, those individuals also tended to score very high overall on the GFA. This finding led Miller et al. to speculate that individuals gambling as an escape were potentially the individuals in the sample who were likely pathological gamblers.

To test this speculation, Miller, Dixon, Parker, Kulland, and Weatherly (2010) had individuals contacted on the streets of Las Vegas and Wendover, NV and in sports bars in Rockford, IL complete the GFA and the South Oaks Gambling Screen (SOGS; Lesieur & Blume, 1987), which is the most widely used diagnostic screening tool for the potential presence of pathological gambling. Scores on the escape factor for the GFA were significantly correlated with scores on the SOGS in the samples from both locations. Likewise, a score of 7 or more in the escape category on the GFA identified 30-50%, depending on which sample was used, of the respondents who scored 5 or more on the SOGS, which is indicative of the potential presence of pathology. Phrased differently, although the GFA was designed to determine the contingencies maintaining gambling behavior, the measure of escape appears to also provide some information as to whether or not the respondent is a pathological gambler.

Due to the strong link between pathological gambling and gambling as an escape, as well as the finding that the original GFA (Dixon & Johnson, 2007) was not parsing the different potential positive reinforcement contingencies for gambling behavior, Weatherly, Miller, and Terrell (2011) revised the GFA (GFA-R). The GFA-R contains 16 items, eight each designed to measure gambling maintained by positive reinforcement and escape. Research to date suggests that escape scores on the GFA-R are even more highly correlated with SOGS scores than were the escape scores on the original GFA (Weatherly & Derenne, 2012).

Furthermore, gambling as an escape is not only associated with the reporting of gambling problems, it also appears to predict gambling behavior, at least in a laboratory environment. Weatherly, Montes, and Christopher (2010) recruited 48 university students to complete the GFA and then play video poker. Results demonstrated that participants' endorsement of gambling as a means of escape on the GFA was significantly correlated with how many credits they risked when playing video poker. Interestingly, scores in the escape category were not correlated with how many hands the participants played nor with the number of errors they made while playing the game. Together, these results suggest that gambling for escape may be linked to the amount of risk the gambler will take, not necessarily to the persistence of gambling or to making good (or bad) decisions while gambling.

Thus, if the inmate population turns to gambling as a means of escape from the aversive nature of the prison environment, then there is reason to believe that rates of pathological gambling would increase after incarceration. The same would not necessarily be expected if gambling was maintained by positive reinforcement contingencies, such as gambling for money, cigarettes, or other amenities. (6) Regardless, if pathological gambling in the prison population is going to be treated, it would seem to be wise for practitioners to focus on gambling as being a function of escape (i.e., negative reinforcement).


Disordered gambling often goes undetected or unaddressed for long periods of time (Potenza, Steinberg, McLaughlin, Wu, Rounsaville, & O'Malley, 2001). As a result, between 2-3% of gamblers will seek treatment (Potenza et al., 2001), while 50% of treatment seekers will drop out by the first or second session (Ladouceur, Grosselin, Laberge, & Blasczynski, 2001; Ladouceur, Lachance, & Fournier, 2009).

A major concern for gambling-treatment providers is identifying and engaging pathological gamblers in treatment during early onset stages (Potenza et al., 2001). One popular intervention for gambling is Gamblers Anonymous (GA), and when combined with outpatient or inpatient treatment, GA has a 50% success rate. However, only 8% of GA members discontinue gambling after two years of treatment (Dunstan, 1997).

Alternative treatment strategies have begun to assess differences in treatment content, goals, and duration of treatment. For example, early gambling treatments focused on behavioral principles including aversive respondent conditioning paradigms with gambling-related stimuli (i.e., pairing gambling stimuli with aversive unconditioned stimuli in an attempt to counter condition any positive excitatory conditioned responses that these stimuli may evoke prior to treatment; Seager, Pkorny, & Black, 1966) and cue exposure (i.e., a form of extinction treatment; Symes & Nicki, 1997). More recently, identifying triggers for gambling and replacement behaviors have been used to replace gambling with other behaviors that contact similar reinforcement (Hodgins & Petry, 2004; Petry, 2005). Treatment goals tend to use a universal approach by using abstinence from gambling behaviors altogether. However, these programs have yielded only minimally effective outcomes (Ladouceur, Lachance, & Fournier, 2009). Duration of treatment can range from brief therapies (lasting anywhere from 10 minutes to 4 hours; Petry, Weinstock, Ledgerwood, & Morasco, 2008) to full interventions (50-minute sessions over the course of 8-12 weeks; Petry, 2005).

A relatively new behavioral treatment, Acceptance and Commitment Therapy (ACT; Hayes, Strosahl, & Wilson, 1999), has been recently implemented for gamblers. Similar to a cognitive-behavioral model, ACT focuses on six core components to train individuals to actively contact their experiences in the present moment and to continue to make values-based actions (Sandoz, Wilson, & Dufrene, 2010). Preliminary evidence suggests that specific components of ACT may assist gamblers in reducing persistence of play (Wilson & Dixon, submitted) and may alter brain activation following exposure to 8 weeks of therapy (Dixon & Wilson, 2011). Additionally, when targeting the near-miss effect (7), brief exposure to ACT may also affect subjective win ratings (Nastally & Dixon, 2012). Evidence to date suggests ACT may be an effective treatment strategy for pathological gamblers, and may be a viable option for gamblers in prison. Perhaps equally important, ACT is an escape-based treatment. That is, the gambler learns alternative response strategies to escape the conditions that previously led to gambling.


Overall, treatment of inmates in United States prisons can take, and has taken, a variety of forms. Consistent with the philosophy that underlies behavior analysis, many psychologists and other mental-health professionals have adopted the stance that treatment can play a key role in the rehabilitation of offenders and ultimately the successful transition of offenders back into the community. The past decade or more has seen a shift away from the goals of punishment and segregation back to the goal of treatment and rehabilitation of the offender (Ward & Stewart, 2003). Historically, treatment within prisons has generally referred to administering psychological services to an inmate who had been diagnosed with a mental disorder and the goal was to improve functioning so that this person could successfully return to society. However, treatment or rehabilitation as currently applied in prisons is not directed as much toward the treatment of a mental illness as it is in changing behavior patterns (Cronin, 2009).

To this end, a wide range of modern psychological training programs have been introduced into many correctional settings with the specific purpose of helping the offender succeed as a law-abiding and healthy functioning citizen upon release. The treatment approaches have been representative of approaches found across psychology in general (e.g., self-help groups, individual therapy sessions, group counseling). Likewise, efforts have been made in certain prisons to address specific behavioral disorders via targeted treatment programs (e.g., drug-abuse education, sex-offender management, impulsive-aggressive behaviors; Office of the Inspector General, 2004). Although the results are not unequivocal, researchers suggest that such treatments and programs have had at least some positive impact in reducing post-release recidivism, especially when targeted at certain inmates (e.g., those with low skills; e.g., O'Neill, MacKenzie, & Bierie, 2007; Wilson, Gallagher, & MacKenzie, 2000). As noted above, however, overall recidivism rates remain high.

Germane to the present topic, treatment programs directed at pathological gambling for the prison population are rare (e.g., Reynolds, 1999, as cited by Oregon Department of Human Services, 2007) and, when they are instituted, they have been linked to substance-abuse programs (e.g., Bond, 1998). Unfortunately, there are little to no outcome data available to validate the efficacy of these programs. Researchers have certainly voiced the need for (more) gambling-specific treatment programs in prison settings (e.g., Abbott, McKenna, & Giles, 2005), but at present those voices have not been heeded.

Our literature search did not identify any behavior-analytic treatment programs, either proposed or attempted, for pathological gambling in a prison setting. However, the absence of such programs in the literature cannot be considered surprising. For one, the GFA (Dixon & Johnson, 2007) was the first overtly behavior-analytic measure of gambling behavior to be proposed for treatment purposes. Secondly, to our knowledge, ACT is the first strictly behavioral treatment program that has been proposed for the treatment of pathological or problem gambling in any setting, let alone for a specific population (e.g., prisoners) or a certain environment (e.g., prisons).

Thus, perhaps a reasonable first suggestion for behavior analysts attempting to treat pathological gambling in the prison setting would be to make use of the GFA-R (Weatherly et al., 2011). (8) As noted above, the GFA-R measures whether the respondent's gambling behavior is potentially maintained by positive reinforcement or escape. That information alone may be crucial because, as also noted above, gambling as a means of escape may play a special role in pathological gambling.

Next, it should be possible to establish a behavioral treatment plan that incorporates the principles of ACT. ACT may lead to more efficacious outcomes than traditional treatments with pathological gamblers in prison settings, than traditional treatments, especially if the prisoners' gambling is escape-based. An ACT program for prison gamblers could be arranged by incorporating sessions as a choice during daily activities or by granting prisoners access to individual or group ACT sessions. ACT sessions focused on gambling can be developed to identify large, overarching value systems for the prisoners in hopes of creating values-based choice making. Additionally, ACT sessions can be developed in brief format, where sessions can be delivered on a computer, without removing the gambler from the prison environment.


As noted above, there is a dearth of research on gambling among the prison population, so one easily made recommendation is to call for additional research. With that said, although prevalence studies are informative and should be done periodically, additional studies on the prevalence rates of pathological gambling among prisoners are likely not needed. Of the research that has been conducted to date, the results are clear that pathological gambling is a major problem among this population and the prevalence of the problem is significantly greater than found in the general population. It is also possible that gambling problems that develop in prison may generalize when the individual is released and could promote a cycle of recidivism, which also needs study.

What would potentially be highly informative is the difference between the prevalence of pathological gambling of inmates upon their incarceration and the rate of pathological gambling in the general prison population. That is, what we do not know at this point in time is whether the high rates of pathological gambling in the prison population is produced by pathological gamblers having a high rate of incarceration, the prison environment promoting pathological gambling, or both. If incoming prisoners were screened for the potential presence of pathological gambling, perhaps using a measure such as the SOGS (Lesieur & Blume, 1987), one could then compare that rate to the overall prison population at that particular facility. If one consistently observed higher rates of pathology in the prison population than observed for incoming inmates, then one would become more confident that the prison environment is promoting pathological gambling. (9) If it is, then changes could potentially be made to the environment to counteract that influence.

If the prison environment is in fact promoting gambling as a means of escape from things such as boredom, monotony, etc., then one would predict that gambling treatment programs would be somewhat successful in the prison environment regardless of the theoretical orientation of the program. That is, activities that compete against gambling (i.e., that also provide an escape) should help decrease the frequency of gambling. Inasmuch as therapy provides that escape, one should see a decrease in gambling when therapy is provided (i.e., functional equivalence). In fact, such an effect might be expected even if the therapy program focused on something other than gambling.

Along the same lines, one would also predict that other, non-therapy-related activities would also produce a decrease in gambling in the prison environment. This possibility could potentially be tested by measuring prevalence of gambling problems in facilities that provide inmates with numerous possible activities versus facilities that have few structured activities for inmates. This prediction would not, however, extend to every kind of activity. Activities that promote competition (e.g., sports) might facilitate, rather than inhibit, gambling because the inmates might wager on the outcome of the competition. One could therefore alter the above prediction and postulate that gambling problems might be observed at higher rates at facilities that have structured activities that involve competition between inmates than at facilities that do not.

Of course, the ideal scenario would be to create a treatment program or environment that not only decreases the rate of gambling problems within the prison environment, but that also serves to decrease the frequency of pathological gambling once offenders reenter society. ACT may represent such a program, but future research is needed to determine how effective it will be in a prison environment. Next, if negative reinforcement (i.e., escape) is the primary contingency maintaining gambling behavior in pathological gamblers, then programs, ACT or otherwise, designed to provide alternative means of escape should prove successful. If these alternative forms of escape should require skills training, then a successful program might also involve shaping behaviors not currently displayed by the pathological gambler.

In conclusion, more research is certainly needed to understand the gambling behavior of those who are incarcerated, especially gambling maintained by negative reinforcement. At this point, we do know that this population warrants extra attention given its significantly higher prevalence rate of pathological gambling than observed in the general population. Unfortunately, until further advances occur in behavior-analytic treatments for problem and pathological gambling, one can only speculate on what a successful treatment program might look like in a prison setting.


Abbott, M.W., McKenna, B.G., & Giles, L.C. (2005). Gambling and problem gambling among recently sentenced male prisoners in four New Zealand prisons. Journal of Gambling Studies, 21, 537-558.

American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders (4"1 ed., text revision). Washington, D.C.: Author.

American Psychiatric Association (2010). DSM-V: The Future of Psyciatric Diagnosis. Retrieved February 28, 2012 from

Anderson, D. (1999). Problem gambling among incarcerated male felons. Journal of Offender/Rehabilitation, 29, 113-127."

Blaszczynski, A., McConaghy, N., & Frankova, A. (1989). Crime, antisocial personality and pathological gambling. Journal of Gambling Behavior 5, 137-152.

Bond, P (1998). The development of good practices and treatment in the rehabilitation of alcoholic and drug-addicted inmates in her majesty's prisons. Alcohol & Alcoholism, 33, 83-88.

Bureau of Justice Statistics. (2009a, December). Correctional populations in the U.S. Washington, DC: U.S. Department of Justice, Bureau of Justice Statistics NCJ231681.

Bureau of Justice Statistics. (2009b, December). Prisoners in 2009. Washington, DC U.S. Department of Justice, Bureau of Justice Statistics, NCJ231675.

Cronin, C. (2009). Forensic Psychology: An Applied Approach (3rd ed.). Dubuque Kendall Hunt

Dixon, M.R., & Johnson, T.E. (2007). The gambling functional assessment (GFA): An assessment device for identification of the maintaining variables of pathological gambling. Analysis of Gambling Behavior 1, 44-49.

Dixon, M.R., Marley, J., & Jacobs, E.A. (2003). Delay discounting by pathological gamblers. Journal of Applied Behavior Analysis, 36, 449-458.

Dixon, M.R., & Wilson, A.N. (February 24, 2011). How to behaviorally treat the pathological gambler. Symposium presented at the Behaviorist Interested in Gambling Special Interest Group conference, Ft Lauderdale, FL.

Dunstan, R. (1997). Gambling in California. Retrieved from: crb/97/03/crb97003.htm1#toc.

Erisman, W., & Contardo, J.B. (2005) Learning to reduce recidivism: A 50-state analysis of postsecondary correctional education policy. Washington, DC: Institute for Higher Education Policy.

Harlow, C.W. (2003). Education and correctional populations. Washington, DC: Bureau of Justice Statistics.

Harrison, P.M., & Beck, A.J. (2006). Prison and jail inmates at midyear 2005. Washington, DC: Bureau of Justice Statistics.

Hayes, S.C., Strosahl, K.D., & Wilson, K.G. (1999). Acceptance and commitment therapy: An experiential approach to behavior change. New York: Guilford Press.

Hodgins, D. C., & Petry, N. M. (2004). Cognitive and behavioral treatments. In J.E.

Grant & M.N. Potenza (Eds.). Pathological gambling a clinical guide to treatment (pp 169-187). Washington D.C.: American Psychiatric Publishing.

Holden, C. (2010). Behavior addictions debut in proposed DSM-V. Science, 327 935.

Kantor, J. R. & Smith, N. W. (1975). The science of psychology: An interbehavioral survey. Principia Press, Inc: Chicago, IL.

Kindt, J.W. (2003). Gambling with terrorism and US military readiness: Time to ban video gambling devices on US military bases and facilities. Northern Illinois University Law Review, 24, 1-31.

Lahn, J. (2005). Gambling among offenders: Results from an Australian survey International Journal of Offender Therapy and Comparative Criminology, 49, 343-355.

Ladouceur, R., Grosselin, P., Laberge, M., & Blasczynski, A. (2001). Dropouts in clinical research: Do results reported in the field of addiction reflect clinical reality? The Behavior Therapist, 24, 44-46.

Ladouceur, R., Lachance, S., & Fournier, P M. (2009). Is control a viable goal in the treatment of pathological gambling? Behavior Research and Therapy, 47, 189-197.

Lesieur, H.R., & Blume, S.B. (1987). The South Oaks Gambling Screen (SOGS): a new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144, 1184-1188.

Michael, J. (1993). Establishing operations. The Behavior Analyst, 16, 191-206.

Miller, J.C., Dixon, M.R., Parker, A., Kulland, A.M., & Weatherly, J.N. (2010) Concurrent validity of the gambling function assessment (GFA): Correlations with the South Oaks Gambling Screen (SOGS) and indicators of diagnostic efficiency. Analysis of Gambling Behavior, 4, 61-75.

Miller, J.C., Meier, E., Muehlenkamp, J., & Weatherly, J.N. (2009). Testing the validity of Dixon & Johnson's (2007) gambling functional assessment. Behavior Modification, 33, 156-174.

Montes, K.S., & Weatherly, J.N. (2012). Gambling Behavior and Temporal Discounting Among Military-Affiliated and Civilian Students. Analysis of Gambling Behavior 6, 67-76.

Nastally, B.L., & Dixon, M.R. (2012). The effect of a brief acceptance and commitment therapy (ACT) intervention on the near miss effect in problem gamblers. The Psychological Record, 62, 677-690.

Nixon, G., Leigh, G., & Nowatzki, N. (2006). Impacting attitudes towards gambling: A prison gambling awareness and prevention program. Journal of Gambling Issues, 17.

Office of the Inspector General. (2004, March). The Federal Bureau of Prisons inmate release preparation and transition reentry programs. Report No. 04-16.

O'Neill, L, MacKenzie, D.L., & Bierie, D.M. (2007). Educational opportunities within correctional institutions: Does facility type matter? The Prison Journal, 87, 311-327.

Oregon Department of Human Services (2007, September). Literature review for gambling among the corrections population. Retrieved from http://www.oregon. gov/DHS/addiction/gambling/corrections-pop-gambling.pdf?ga=t

Petersilia, J. (2003). When prisoners come home: Parole and prisoner reentry. Oxford Oxford University Press.

Petry, N.M. (2005). Pathological gambling: Etiology, comorbidity, and treatment Washington, D.C.: American Psychological Association

Petry, N.M., Weinstock, J., Ledgerwood, D., & Morasco, B. (2008). A randomized trial of brief interventions for problem and pathological gamblers. Journal of Consulting Clinical Psychology, 76, 318-328.

Pew Center on the States (April, 2011). State of Recidivism: The Revolving Door of America's Prisons. Washington, DC: The Pew Charitable Trusts.

Polich, M.J. (1981). Epidemiology of alcohol abuse in military and civilian populations American Journal of Public Health, 71, 1125-1132.

Potenza, M.N., Steinberg, M.A., McLaughlin, S.D., Wu, R., Rounsaville, B.J., &

O'Malley, S.S. (2001). Gender-related differences in the characteristics of problem gamblers using a gambling helpline. American Journal of Psychiatry, 158, 1500-1505.

Sandoz, E.K., Wilson, K.G., & Dufrene, T. (2010). Acceptance and commitment therapy for eating disorders. Oakland, CA: New Harbinger Publications.

Seager, C.P, Pkorny, M.R., & Black, D. (1966). Aversion therapy for compulsive gambling. The Lancet, 1(7436), 546.

Skinner, B.F. (1953). Science and human behavior. New York: Free Press.

Symes, B.A., & Nicki, R.A. (1997). A preliminary consideration of cue-exposure response-prevention treatment for pathological gambling behavior: Two case studies. Journal of Gambling Studies, 13, 145-157.

Ward, T. & Stewart, C. (2003). Criminogenic needs and human needs: A theoretical model. Psychology, Crime, & Law, 9, 124-143.

Wardman, D., el-Guebaly, N., & Hodgins, D. (2001). Problem and pathological gambling in North American Aboriginal populations: A review of the empirical literature. Journal of Gambling Studies, 17, 81-100.

Weatherly, J.N., & Derenne, A. (2012). Investigating the relationship between the contingences that maintain gambling and probability discounting of gains and losses. European Journal of Behavior Analysis, 13, 39-46.

Weatherly, J.N., & Dixon, M.R. (2007). Toward an integrative behavioral model of gambling. Analysis of Gambling Behavior, 1, 4-18.

Weatherly, J.N., Miller, J.C., & Terrell, H.K. (2011). Testing the construct validity of the Gambling Functional Assessment--Revised (GFA-R). Behavior Modification, 35 553-569.

Weatherly, J.N., Montes, K.S., & Christopher, D.M. (2010). Investigating the relationship between escape and gambling behavior. Analysis of Gambling Behavior, 4, 79-87.

Williams, R. J., Royston, J., & Hagen, B. F. (2005) Gambling and problem gambling within forensic populations: A review of the literature. Criminal Justice and Behavior: An International Journal 32, 665-689.

Wilson, A.N. & Dixon, M.R. Defusing consequences of simulated slot machine play. Manuscript submitted for publication.

Wilson, D., Gallagher, C., & MacKenzie, D. (2000). A meta-analysis of corrections-based education, vocation, and work programs for adult offenders. Research in Crime and Delinquency, 37, 347-368.

Zorland, J., Mooss, A., & Perkins, A. (2008). Gambling and offending: An examination of the literature. Georgia State University Gambling Project Retrieved from http://

(1) This classification may change in future editions of the DSM. The American Psychiatric Association (2010) proposed to renaming pathological gambling "disordered gambling" as well as classifying it as an addiction disorder rather than an impulse-control disorder. Such changes would make pathological/disordered gambling the first and only behavioral addiction (Holden, 2010).

(2) Although pathological gambling is defined as an impulse disorder, its symptoms are virtually identical to those of substance dependence. The latter two cognitive symptoms listed here represent the equivalent of tolerance and withdrawal, respectively. Thus although not overtly stated, the underlying theoretical perspective of the DSM-IV-TR is the medical model and the implication of pathological gambling being linked to substance dependence is that both disorders are physical in nature.

(3) Some or all of these symptoms could potentially be recast in behavioral terms (e.g. as establishing operations or as reinforced behaviors, etc.). However, they are not presently framed that way in the DSM, which implies that the writers of the DSM view these as specific behaviors. The DSM does not take into account the contingencies governing the behavior, and therefore the contingencies are not the clinician's focus.

(4) The current DSM lists engaging in illegal activities as an official symptom of pathological gambling. The proposed DSM-V, however, drops this particular symptom (American Psychiatric Association, 2010).

(5) Why so few studies have been conducted on this population is not known, but several factors likely contribute. One is the fact that specific ethical standards apply to this particular population and thus research involving inmates involves meeting additional ethical safeguards. A second likely reason involves access; not all researchers may be in a reasonable proximity to a prison facility. It is also the case that researchers who work with this population must deal with the administrative structure of the prison above and beyond that of their own institution. Despite these difficulties, given the high rate of pathological gambling in the prison environment, more research on the topic in this setting is clearly warranted.

(6) In terms of the previous comparison with military personnel, it should be noted that people intending to join the military may be less likely than people not intending to join the military to gamble as an escape (Montes & Weatherly, 2012). This finding might explain why extremely high rates of pathological gambling are not found in the military population.

(7) The near-miss effect occurs when the gambler comes close to winning, but does not win (e.g., two winning symbols appear on the pay line of a slot machine with the third necessary symbol landing just above or below the pay line). This effect has interested researchers because the near miss appears to serve as a reinforcer for gambling despite the fact that the gambler actually loses.

(8) Ideally, one would want to conduct an experimental functional analysis to determine the contingencies maintaining the person's gambling behavior. To our knowledge however, no experimental functional analysis has ever been published on gambling behavior, let alone in a prison environment.

(9) With that said, treatment programs for pathological gambling are needed regardless of whether the pathological gambling occurs prior or subsequent to incarceration.

Jeffrey N. Weatherly

University of North Dakota

Kevin S. Montes

University of North Dakota

Douglas Peters

University of North Dakota

Alyssa N. Wilson

Southern Illinois University, Carbondale



Department of Psychology

University of North Dakota

Grand Forks, ND 58202-8380

Phone: (701) 777-3470

Fax: (701) 777-3454

COPYRIGHT 2012 Behavior Analyst Online
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2012 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Weatherly, Jeffrey N.; Montes, Kevin S.; Peters, Douglas; Wilson, Alyssa N.
Publication:The Behavior Analyst Today
Article Type:Report
Date:Jun 22, 2012
Previous Article:Editorial: behavioral interventions and considerations.
Next Article:Prisoner reentry and recidivism according to the formerly incarcerated and reentry service providers: a verbal behavior approach.

Terms of use | Privacy policy | Copyright © 2020 Farlex, Inc. | Feedback | For webmasters