The Brief Addiction Science Information Source (BASIS)

The WAGER, Vol. 17(1) – Shhh! Keep it a Secret: The Role of Stigma and Culture as Barriers to Gambling Treatment

Recent research suggests that a small minority of people who have gambling problems ever seek treatment for those problems (Slutske, 2006). One reason for failing to seek treatment might be the stigma attached to mental health problems, particularly problems with addiction. This week, The WAGER reviews a study that examined whether culture plays a role in the stigma attached to gambling problems and treatment (Dhillon, Horch, Hodgins, 2011).

Method

• Participants were students of East Asian and Caucasian ancestry recruited from the University of Calgary through the Psychology Department Research Participation System (n=64 and n=50, respectively).
• Researchers gave participants questionnaire packets containing vignettes describing either an East Asian or a Caucasian problem gambler. The vignettes differed only by the depicted individual’s ethnicity.
• The questionnaire packets also contained additional assessments including Attitudinal Social Distance.
  • The social distance measure used in this study indicates willingness to interact with problem gamblers (higher social distance score indicate less willingness) and is a good indicator of stigma. The questions used were modified to relate to gambling issues.

Results

• Mean social distance reported by East Asians was higher than that reported by Caucasians (M = 10.9, SD = 3.6 vs. M = 9.2, SD = 3.1; F[1,106] = 8.46, p < .05).
• Social distance score did not differ significantly by the ethnicity of the problem gambler described in the vignette (F(1,106) = 0.24, p = ns).
• As displayed in Figure 1, there was a significant interaction between participant ethnicity and the ethnicity of the problem gambler described in the vignette (F(1, 106) = 4.20, p   < .05)
  • East Asians participants preferred more social distance from the East Asian problem gambler depicted in the vignette than Caucasian participants, but participants did not differ in terms of the distance they preferred from the Caucasian problem gambler.

Figure 1. Interaction between participant ethnicity and vignette ethnicity on social distancing (adapted from Dhillon et al., 2011).

Limitations

• The sample consisted only of university students
  • East Asian university students might be more acculturated than other East Asian individuals
• Only East Asian cultures and Caucasians were investigated
  • Additionally, individuals of all East Asian cultures were grouped into a single category
• The use of social distance as a measure of stigma can be affected by social desirability bias and it is hard to determine if an individual’s questionnaire responses reflect their actual behavior.
• The study does not examine how stigma affects treatment seeking.

Conclusion

The results from this study indicate that East Asians might experience more stigmatization of problem gambling than Caucasians, particularly from other East Asians. This suggests that culture might pose a significant barrier to treatment. Future research needs to investigate the specific beliefs about gambling and mental health that underlie these cultural differences.

-Jed Jeng

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References

Dhillon, J., Horch, J., & Hodgins, D. C. (2011). Cultural Influences on Stigmatization of Problem Gambling: East Asian and Caucasian Canadians. Journal of Gambling Studies, 27(4), 633-647.

Slutske, W. S. (2006). Natural Recovery and Treatment-Seeking in Pathological Gambling: Results of Two U.S. National Surveys. The American Journal of Psychiatry, 163(2), 297-302.

The WAGER, Vol. 16(11) – Slots and shots: Drinking patterns of pathological gamblers before, during, and after treatment

Gambling-related problems often co-occur with other risky behavior patterns, such as excessive alcohol or substance use (Kessler et al., 2008). However, it is unclear whether efforts to address one behavior (e.g., gambling) will also lead to decreases in other problematic behaviors, or, instead, result in addiction-hopping, substituting one excessive behavior for another (Shaffer et al., 2004). This week, the WAGER reviews a study that examined the weekly alcohol use trajectories of treatment-seeking pathological gamblers to understand more fully the drinking patterns in that population (Rash et al., 2011).

Method

• Participants were 163 individuals taking part in one of two randomized clinical trials of psychotherapy for pathological gambling who reported any alcohol consumption in the 36-week period of data collection (56% of trial participants).
• Participants completed the timeline followback (TLFB) procedure at baseline, 8 weeks post-treatment, and 24 weeks post-treatment to report their alcohol use in the 12 weeks prior to gambling treatment, as well as the 24 weeks post-treatment.
• Based on the alcohol use data, researchers split participants into one of two groups:
  • Ever-risky drinkers (n = 76) drank more than 14 standard drinks per week or four per day for males, and more than seven drinks per week or three per day for females on at least one occasion during the 12 weeks prior to treatment or 24 weeks post-treatment.
  • Non-risky drinkers (n = 87) never drank at the above-specified risky levels during the course of the study. 

Results

• Particularly among risky drinkers, alcohol use decreased prior to treatment entry, but then escalated again post-treatment.
• There were significant changes in at-risk status from the pretreatment period to the period following treatment entry. Fifty-five participants qualified as at-risk drinkers prior to treatment entry; 26 of those (47%) did not drink at risky levels after treatment entry. One hundred eight participants did not qualify as at-risk drinkers prior to treatment; however, 21 of those (19%) exhibited at-risk drinking after treatment entry. 

Figure 1. Drinks per day and drinking days pre-, during, and post-gambling treatment (adapted from Rash et al., 2011).
 

Limitations

• The alcohol use data rely on retrospective self-report. Participants may have under- or over-estimated their alcohol use intake.
• Results are limited to gamblers-seeking treatment and do not provide information about whether the gambling treatment itself influenced alcohol-use patterns.

Conclusions

The reviewed study suggests that entry into gambling treatment might be associated with reductions in alcohol use. According to the syndrome model of addiction (Shaffer et al., 2004), various risky behavior patterns like excessive drinking or gambling may indicate an underlying addiction syndrome. However, the behaviors associated with that syndrome often follow different trajectories. Most risky gamblers who also drank reduced their drinking behavior post-treatment, but a small subset of the population persisted and actually worsened, suggesting that efforts to address one behavior may sometimes result in addiction-hopping.

- Kat Belkin

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References

Kessler, R. C., Hwang, I., LaBrie, R., Petukhova, M., Sampson, N. A., Winters, K. C., & Shaffer, H. J. (2008). DSM–IV pathological gambling in the National Comorbidity Survey Replication. Psychological Medicine, 38, 1351–1360. doi:10.1017/S0033291708002900

Rash, C. J., Weinstock, J., & Petry, N. M. (2011). Drinking patterns of pathological gamblers before, during, and after gambling treatment. Psychology Of Addictive Behaviors, 25(4), 664-674.

Shaffer, H., LaPlante, D., LaBrie, R., Kidman, R., Donato, A., & Stanton, M. (2004) Toward a syndrome model of addiction: Multiple expressions, common etiology. Harvard Review of Psychiatry, 12(6), 367-374.

The WAGER, Vol. 16(10) – Warm Turkey: Considering whether abstinence ought to be the goal of gambling treatment

The goal of most gambling treatment is abstinence from gambling. Though not everyone who engages in treatment achieves this “cold turkey” goal, it is possible that the goal itself deters some individuals from seeking treatment. This week’s WAGER reports results of a study that examined how common abstinence versus controlled gambling are among problem gamblers in recovery (Slutske, Piasecki, Blaszczynski, & Martin, 2010). 

Method

• Participants were 104 individuals who qualified for DSM-IV pathological gambling (PG) among a general population sample of 2,382 twin pairs drawn from the Australian twin registry.¹
• Researchers classified these life-time PG gamblers into three groups according to their symptoms during the past year: 
  • Past-year PG (N = 28): Gamblers who qualified for PG within the past year
  • Some problems (N = 32): Gamblers who met 1 - 4 PG criteria within the past year
  • Recovery group (N = 44): Gamblers who had no symptoms of PG within the past year. 
• Researchers assessed the following indicators of gambling involvement during the heaviest gambling period and during the past year: 
  • Number of days spent gambling 
  • Number of hours spent on a typical gambling day
  • Percentage of yearly income spent on gambling 
  • Number of different gambling activities –gambling versatility (e.g., horse and dog betting, casino table games, keno, bingo etc.).

Results

• Almost all of the recovered gamblers (90%) gambled in the past year, and less than 20% received any formal treatment.
• As Figure 1 shows, recovered gamblers demonstrated greatly reduced gambling activity, compared both to other non-recovered participants and to their own previous activity. 

Figure 1. Gambling involvement of recovered, partially recovered, and symptomatic PGs

PY=past year; PG=pathological gambling 

Limitation

• This is a correlational study, based on a cross-sectional survey about past behavior. Therefore we cannot conclude that controlled gambling caused PG recovery.
• Measures of gambling activity are based on retrospective self-report and may not reflect actual gambling.

Conclusion

This study does not support the assumption that abstinence is required for PG recovery. Only 10% of those who recovered from gambling-related problems did not gamble during the past year. However, the recovery group demonstrated substantial decreases in gambling involvement compared to non-recovery groups. As with any correlational study, this study does not conclude causality. Future controlled experiments or longitudinal studies are required to examine if abstinence or controlled gambling lead more effectively to PG recovery.  However, this study does suggest that allowing for the possibility of a controlled gambling, or “warm turkey”² goal within treatment might increase treatment engagement

-Julia Braverman & Sarah Nelson

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References

Miller, W. R., & Page, A. C. (1991). Warm turkey: other routes to abstinence. Journal of Substance Abuse Treat, 8(4), 227-232.

Slutske, W. S., Piasecki, T. M., Blaszczynski, A., & Martin, N. G. (2010). Pathological gambling recovery in the absence of abstinence. Addiction, 105(12), 2169-2175.

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¹ The 104 participants in this study were derived from 102 different twin pairs: only two pairs of related twins were included in the sample.

² Slutske and colleagues (2010) refer to the goal of engaging in controlled gambling as a “warm turkey” approach. The term was first used by Miller & Page (1991) to describe controlled drinking.

The WAGER, Vol. 16(9) – Help!… maybe: Facilitating treatment engagement among helpline callers

Few people who experience gambling problems seek help for those problems (Slutske, 2006). Some of these untreated individuals recover on their own. Others who might benefit from treatment avoid it due to ambivalence or barriers. For this second group, first points of contact might serve as important opportunities to promote treatment engagement. This week, the WAGER reviews a study that investigated factors that predict treatment engagement among individuals calling a gambling problem helpline (Weinstock et al., 2011).

Method

• Participants were 2,912 individuals who called the West Virginia gambling problem helpline and were offered in-person assessments; 82% of these participants qualified as pathological gamblers (PGs).
• Helpline staff conducted interviews with each caller, collecting information about demographics, gambling activity, gambling problems, other mental health issues, and previous treatment.
• Researchers recorded whether callers accepted the offer of an in-person assessment, whether they attended the assessment, and how soon after the helpline call the assessment was scheduled to occur.

Results

• 76% of the helpline callers agreed to participate in an in-person assessment, and 72% of those (55% of the full sample) actually attended the assessment. Table 1 displays the significant predictors of assessment acceptance and attendance.
• In a logistic regression model predicting in-person assessment acceptance:
  • being single and having received previous treatment predicted refusal of the in-person assessment offer;
  • high gambling debt, calling due to spousal pressure or legal problems, gambling problem severity, and other mental health problems all predicted accepting the in-person assessment.
• In another logistic regression model, predicting assessment attendance among those who had accepted the in-person assessment offer:
  • being female and being younger predicted failure to attend the in-person assessment;
  • having a higher education level, calling due to spousal/familial pressure or legal problems, having received previous treatment, and gambling problem severity all predicted attending the in-person assessment;
  • receiving an appointment within 72 hours of calling the helpline, accomplished for 57% of the sample, was also strongly predictive of assessment attendance.
• Employment, income, suicidal ideation, and gambling patterns and frequency did not have discernable effects on assessment acceptance or attendance.

Table 1. Significant predictors of assessment acceptance and attendance among gambling problem helpline callers.

Limitations

• Though this study tells us what predicts treatment engagement, it does not tell us about the efficacy of that treatment or participants’ receptiveness to the session, once there.
• We do not know whether those who refused or failed to attend the assessment got worse or better without treatment.

Conclusion

This study provides information about personal and situational characteristics that influence not only willingness to pursue treatment, but also ability to follow through. Though demographics did not have a strong influence on whether helpline callers accepted an offer of in-person assessment, they did affect whether callers attended that assessment. This suggests that certain demographic factors, such as being female, younger, and having a lower education, might be associated with barriers to treatment. These potential barriers, such as family burden, deserve further attention. At the same time, efforts to make treatment immediately available (i.e., within 72 hours) appear to facilitate treatment engagement. In addition, family involvement had a positive effect on treatment-seeking and attendance in this study; it remains to be seen whether such coerced entry into treatment has a positive or negative effect on treatment outcome.

-Sarah Nelson

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References

Slutske, W. S. (2006). Natural recovery and treatment-seeking in pathological gambling: results of two U.S. national surveys. Am J Psychiatry, 163(2), 297-302.

Weinstock, J., Burton, S., Rash, C. J., Moran, S., Biller, W., Krudelbach, N., et al. (2011). Predictors of engaging in problem gambling treatment: data from the West Virginia Problem Gamblers Help Network. Psychol Addict Behav, 25(2), 372-379.

The WAGER, Vol. 16(8) – Impaired decision making among at-risk young gamblers

Researchers are investigating the neurological factors that might play a role in the development of pathological gambling. For example, cognitive deficits, such as dementia and reduced executive functioning are well-known correlates of pathological gambling (PG; Manes, Torralva, Roca, Gleichgerrcht, Bekinschtein, & Hodges, 2011). Grant and colleagues suggested that cognitive deficits create risk because they lead to impaired decision-making, which in turn leads to PG (Grant, Brewer, & Potenza, 2006). Today’s WAGER reviews a study that explores whether young adults with decision-making impairments are also more likely to be at-risk for the development of PG (Grant, Chamberlain, Schreiber, Odlaug, & Kim, 2011).

Methods

• One hundred eighty-six participants who responded to media advertisements met criteria (i.e., 18-29 year olds who gambled at least 5 times during the past year, but did not meet criteria for PG) for the study.
  • One hundred and twelve did not affirm any DSM-IV-TR criteria for PG (i.e., low-risk) and 74 participants met one or two criteria for PG (i.e., at-risk). Researchers excluded participants meeting three or more PG criteria.
  • Researchers administered of tests to assess PG and decision-making impairments.
    • Of specific relevance to this summary, the Cambridge Gamble Task (CGT) is a computerized measure that assesses participant’s rational decision-making abilities in an ambiguous gambling scenario (Grant, et al., 2011).
      • The program presents a series of 10 red or blue boxes to the participants, along with instructions that one box contains a ‘token’.
      • The ratio of red to blue boxes changes with each trial. This box-ratio varies from 10:0 to 6:4, with each condition introducing more ambiguity.
      • Participants choose whether the token is in a red or blue box. A ‘rational decision’ is choosing the color with the majority of boxes (e.g., choosing red when there are seven red and three blue boxes).
      • The program initially assigns participants 100 points; each round, participants bet a proportion of their points.

Results

• There was a significant effect of box-ratio (F = 27.80, p < .001) and a significant group x box-ratio interaction (F = 3.63, p = .013).
  • All participants made fewer rational decisions as the box-ratio decreased. This tendency was more pronounced among the at-risk group than the low-risk group (see Figure 1).
  • The at-risk group also wagered a significantly greater number of points regardless of box-ratio (F = 7.34, p < .01).

Figure 1: Proportion of rational decisions for each box-ratio (From Grant, et al., 2011, reprinted with permission).

Limitations

• These data cannot determine causality. In other words, we cannot conclude whether participants are at-risk because of decision-making deficits, or whether another factor causes both.
• The current study does not determine whether the at-risk participants eventually develop PG. A longitudinal extension to this study is in progress, however, and will remediate this issue.
• The CGT only assesses a specific area of cognition. There are many other tests that assess other aspects of cognition and decision-making.

Conclusions

This study shows that at-risk young adult gamblers tend to have impaired decision-making, as assessed by ratio of rational decisions on the CGT. This study is particularly interesting as it is the first to explore cognitive impairment as a PG risk factor among at-risk, but otherwise healthy gamblers. Previous studies have examined cognitive impairment among participants who already had a diagnosis of PG. Although further study is necessary to establish a causal linkage between impaired decision-making and PG, this study provides a starting point for additional studies that might provide important insights into the etiology and underlying mechanisms of PG. Such research may eventually lead to advances in the detection, prevention and treatment of pathological gambling.

-Daniel Tao

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References

Grant, J.E., Brewer, J.A., Potenza, M.N. (2006). The neurobiology of substance and behavioral addictions. CNS Spectrums, 11, 924–930.

Grant, J.E., Chamberlain, S.R., Schreiber, L.R., Odlaug, B.L., Kim, S.W. (2011). Selective decision-making deficits in at-risk gamblers. Psychiatry Research, 189, 115-120.

Mares, F.F., Torralva, T., Roca, M., Gleichgerrcht, E., Bekinschtein, T.A., Hodges, J.R. (2011). Frontotemporal dementia presenting as pathological gambling. Nature Reviews Neurology, 6, 347-352.

Welte, J.W., Barnes, G.M., Wieczorek, W.F., Tidwell, M-C.O., Parker, J.C. (2004). Risk factors for pathological gambling. Addictive Behaviors, 29(2), 232-335. 

The WAGER, Vol. 16(7) – Guesstimates: Can venue staff accurately identify patrons with gambling-related problems?

Although some researchers suggest that there are visible indicators (e.g., gambling for long periods of time, using ATMs, placing high risk bets, avoiding social contact) associated with problem gambling, they also recognize that, in real-time, it might be difficult for gambling venue staff to correctly identify these indicators (Delfabbro, Osborn, Nevile, Skelt, & McMillen, 2007; Schellinck & Schrans, 2004). This week, The WAGER reviews a study that compares patrons’ self-reported gambling status with gambling venue staffs’ estimation of their gambling status (Delfabbro, Borgas, & King, 2011). 

Methods

• The researchers interviewed patrons and staff from seven gambling venues in South Australia during different times of the day and week.
• Patron survey: A small number of all patrons approached by the researchers agreed to participate in the survey and (n=303) completed the past year Problem Gambling Severity Index (PGSI).^[I]
• Staff survey: The staff rated patrons’ gambling status on a 4-point scale (1 = No problems, 2 = Might have some problems, 3 = Suspect patron is a problem gambler, 4 = Confident patron has severe gambling-related problems) for patrons they recognized (i.e., patrons they had seen at least once or twice at the venue). All staff in South Australia receives responsible gambling training, which purportedly includes visual indicators for problem gambling. 

Results

• Self-report (n = 303) PGSI indicated that 40% were not at risk for problem gambling, 29% at low risk, 22% at moderate risk, and 9% were classified as problem gamblers.
• The staff recognized 76% (n = 230) of the patrons. Table 1 compares the patrons’ PGSI scores with staff’s rating of patron gambling among these 230 patrons.
  • Staff members made many false negative ratings for individuals who identified themselves as having problems (i.e., 64%) and were even more inaccurate for those who identified as having low or moderate problems (i.e., 83%).
  • Staff made a number of false positive ratings for individuals who identified themselves as being problem-free (i.e., 6%).

Table 1: Patron PGSI Classifications Compared to Staff Ratings (adapted from Delfabbro, et al., 2011)

Limitations

• Using the PGSI, the patrons self-reported their gambling status. The researchers could use more than one screen to identify problem gambling.
• The researchers approached only patrons using machines in small or medium-sized venues. Therefore, patrons did not come from larger venues and/or venues that offer other forms of gambling.
• Only a small percentage of the people approached agreed to participate. Therefore, the results might not be representative of the Southern Australian gambling population.

Discussion

The results indicate that staff ratings were not a reliable indicator of problem gambling among patrons. It is unclear whether these low ratings are the result of the training, or the difficulty of completing this task in real-time. Perhaps future research will lead to the ability to better train staff to identify patrons’ problematic gambling. Similarly, bartenders also have difficulty correctly identifying which customers are intoxicated (Brick & Erickson, 2009), and this phenomenon is likely even more difficult for identifying problem gambling. These results suggest that staff might be unable to identify customers with a problem using visible indicators.

References

Brick, J., & Erickson, C. K. (2009). Intoxication is not always visible: An unrecognized prevention challenge. Alcoholism: Clinical and Experimental Research, 33(9), 1489–1507. doi: 10.1111/j.1530-0277.2009.00979.x

Delfabbro, P., Borgas, M., & King, D. (2011). Venue staff knowledge of their patrons' gambling and problem gambling. Journal of Gambling Studies, Online First. doi: 10.1007/s10899-011-9252-2

Delfabbro, P., Osborn, A., Nevile, M., Skelt, & McMillen, J. (2007). Identifying Problem Gamblers in Gaming Venues: Final Report. Melbourne, AU: Gambling Research Australia.

Schellinck, T., & Schrans, T. (2004). Identifying problem gamblers at the gambling venue: Finding combnations of high confident. Gambling Research, 16(1), 8-24.

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^[I]The researchers did not obtain an exact record of the number of patrons who refused to participate because the environment and patrons made it difficult to capture this information. The researchers aimed to report about a working sample/convenient sample of PGSI scores rather than a fully representative sample of South Australian gamblers.

The WAGER, Vol. 16(6) – What is the worst gambling strategy? A study about preferred forms of gambling among pathological gamblers

It is important to understand clinical characteristics (e.g., betting pattern, emotional states, gambling preferences) of pathological gambling to provide insight for developing effective prediction, prevention and treatment initiatives. This week’s WAGER reports results of a study that examined how gambling preferences (i.e., strategic versus non-strategic) relate to clinical characteristics among people who suffer with gambling disorder (Odlaug, Marsh, Kim, & Grant, 2011).

Method

• Participants (N = 440, age >=18, 54% females) were patients with a current DSM-IV diagnosis of pathological gambling (PG) and no psychotic or bipolar disorders. The researchers recruited participants who were enrolled to one of several clinical trials that investigated PG treatment during 2000 through 2008.
• Investigators assessed participants using the following measures:
• Psychiatric assessment – The Structured Clinical Interview for DSM-IV Axis Disorders (SCID-I; Williams et al., 1992) and the Structured Clinical Interview for Pathological Gambling (SCI-PG; Grant, Steinberg, Kim, Rounsaville, & Potenza, 2004). 
•  Demographics and features of PG – The researchers assessed participants’ gender and age. The semi-structured clinical interview asked for the preferred types of gambling.  
•  PG symptoms severity – The Yale-Brown Obsessive Compulsive Scale Modified for Pathological Gambling (PG-YBOCS; Pallanti, DeCaria, Grant, Urpe, & Hollander, 2005) and the Clinical Global Impression Severity scale (CGI-S; Guy, 1976). 
• Based on the participants’ reported preferred gambling type, the researchers assigned participants to one of three groups: strategic gamblers (e.g., those who prefer poker, blackjack, dog and horse racing, sports betting, and craps/dice games; N =56); nonstrategic gamblers (e.g., those who prefer slot machines, pull tabs, bingo, and keno; N = 200); and, both (those who reported no preference; N = 184).  

 Results

• Table 1 shows that the nonstrategic gamblers reported no more relationship, financial or work-related problems than strategic gamblers.
• The nonstrategic gamblers were older than strategic gamblers when they started gambling (mean age 34.1 vs. 22.5) and when gambling became a problem (mean age 42.6 vs. 30.6). Nonstrategic gamblers were also less educated (60.4% with at least some college education vs. 79.6%) and more likely to be women (71.5% vs. 30%) than strategic gamblers. All differences are statistically significant at p < .01.
• There were no differences between the groups in terms of PG symptoms severity and psychiatric comorbidity.

Table 1. Self-reported gambling related problems among gamblers who prefer strategic, nonstrategic and both types of gambling  -- N (%)

Group Problems due to gambling	Nonstrategic N = 200	Strategic N = 56	Both N = 184
Financial	151 (75.5)	40 (71.4)	153 (83.2)
Relationship	37 (18.5)	4 (7.1)	23 (12.5)
Work-related	92 (46.0)	20 (35.7)	79 (42.9)

Note: These are the measures with no significant difference between groups. 

Limitations

• This is a self-reported study. The self-reported preference to play a specific type of game might not identify the game type that is associated with problems or is actually the most often played game.
• The study included only treatment seeking gamblers.

Conclusion

The study found that gambling type preference is confounded with age, education, and gender differences. Specifically, gamblers that prefer nonstrategic games are older, less educated, and more likely to be women than those that prefer strategic games.  However, because female gamblers tend to be older than male gamblers (Nelson, LaPlante, LaBrie, & Shaffer, 2006) further studies should examine if the age and education differences remain when the gender is controlled. The study did not find differences in the severity of PG symptoms among the groups. However, using treatment-seeking PGs as participants necessarily reduces the variance in symptom severity, and might work against finding differences in associated measures.

-Julia Braverman

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References

Grant, J. E., Steinberg, M. A., Kim, S. W., Rounsaville, B. J., & Potenza, M. N. (2004). Preliminary validity and reliability testing of a structured clinical interview for pathological gambling. Psychiatry Res, 128(1), 79-88.

Guy, W. (1976). ECDEU assessment manual for psychopharmacology. Rockville, MD: US Department of Health, Education and Welfare publication (ADM).

Nelson, S. E., LaPlante, D. A., LaBrie, R. A., & Shaffer, H. J. (2006). The Proxy Effect: Gender and Gambling Problem Trajectories of Iowa Gambling Treatment Program Participants. Journal of Gambling Studies, 22(2), 221-240.

Odlaug, B. L., Marsh, P. J., Kim, S. W., & Grant, J. E. (2011). Strategic vs nonstrategic gambling: characteristics of pathological gamblers based on gambling preference. Ann Clin Psychiatry, 23(2), 105-112.

Pallanti, S., DeCaria, C. M., Grant, J. E., Urpe, M., & Hollander, E. (2005). Reliability and validity of the pathological gambling adaptation of the Yale-Brown Obsessive-Compulsive Scale (PG-YBOCS). J Gambl Stud, 21(4), 431-443.

Williams, J. B., Gibbon, M., First, M. B., Spitzer, R. L., Davies, M., Borus, J., et al. (1992). The Structured Clinical Interview for DSM-III-R (SCID). II. Multisite test-retest reliability. Arch Gen Psychiatry, 49(8), 630-636.

The WAGER, Vol. 16(5) – Lifetime patterns of gambling and alcohol prevalence

Research suggests that youth are at increased-risk for problem behaviors (e.g., problem gambling and excessive drinking) – See The DRAM, Vol. 7(4) and The WAGER, Vol. 14(7). Although evidence suggests that the phenomenological histories (e.g., use, misuse, and seeking help) that people experience with various expressions of addiction are similar (Shaffer et al., 2004), it is unclear whether the developmental trajectories for problem behaviors are similar. This week, The WAGER reviews an article that compares patterns of gambling and alcohol use to determine prevalence trends across the lifespan (Welte, Barnes, Tidwell, & Hoffman, 2011).

Methods

• Welte et al conducted two US national telephone interviews among randomly recruited adults ages 18+ (n=2,631; 65.2% response rate) during 1999-2000 and adolescents ages 14-21 (n=2,274; 55.0% response rate) during 2005-2007.
• The surveys for both studies assessed various aspects of alcohol and gambling behavior, among other topics. This study examined:
  • Alcohol - past year drinking, drinking more than one drink/day in the past year, and DSM-IV-based measures (i.e., DIS for adults, Adolescent Diagnostic Interview for adolescents) for alcohol dependence;
  • Gambling - past year gambling on a multitude of gambling types for any gambling, frequent gambling (past year 52+ times), and Diagnostic Interview Schedule (DIS-IV) criteria for problem or pathological gambling. The adolescent group’s interview included an additional item about missing school because of gambling.

Results

• As Figure 1 shows, past year gambling and alcohol prevalence varied among the age groups, but the overall pattern for both measures was a rise in prevalence during teenage years, with a peak during adulthood and decline during late adulthood.
  • The first graph in Figure 1 indicates a parallel pattern of change in the prevalence of gambling and alcohol use across age.
  • The other graph plots frequent and problematic use. Frequent alcohol use and dependence peak for respondents 18 to 21 years old whereas for gambling these measures show muted peaks delayed to later ages.
  • Except for the brief alcohol peaks, gambling measures of use and abuse exceed those of alcohol for the younger and older age groups.

Figure 1: Mean prevalence for past year gambling and alcohol use by age (adapted from Welte, et al., 2011)

  

Limitations

• This study used retrospective self report.
• The researchers used different dependence measuring instruments for the adolescent and adult surveys. However, the researchers designed the studies to yield comparable outcome measures.
• The adult gambling data is more than 10 years old and predates the recent proliferation in the number of land-based and Internet-based gambling sites. The gap between interviews and the associated different milieus extant at the interview period might confound results.

Discussion

The report did not examine the overlapping age group for both surveys (i.e., 18-21), which could account for potential confounding or provide important insights. However, the results indicate that past year alcohol use and gambling peak around the same age, whereas frequent drinking and alcohol dependence peak at a younger age than disordered gambling. However, alcohol use tends to taper off more quickly with age than gambling. The prevalence patterns for alcohol and gambling suggest that people might be at risk for developing problems during adolescence and into early adulthood. 

-Tasha Chandler

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References

Shaffer, H. J., LaPlante, D. A., LaBrie, R. A., Kidman, R. C., Donato, A. N., & Stanton, M. V. (2004). Toward a Syndrome Model of addiction: Multiple expressions, common etiology. Harvard Review of Psychiatry, 12, 367-374. doi: 10.1080/10673220490905705

Welte, J. W., Barnes, G. M., Tidwell, M.-C. O., & Hoffman, J. (2011). Gambling and problem gambling across the lifespan. Journal of Gambling Studies, 27, 49-61. doi: 10.1007/s10899-010-9195-z

The WAGER, Vol. 16(4) – Winning? Perspectives on problem gambling

Research tells us that few people with gambling problems seek treatment (Shaffer & Martin, 2011). Perhaps people’s views of addiction, gambling in particular, create barriers that deter disordered gamblers from seeking formal treatment. This week The WAGER reviews a study of beliefs about gambling addiction (Cunningham, Cordingley, Hodgins, & Toneatto, 2011).

Methods

• Cunningham et al. conducted a random digit dialing telephone interview among adults residents living in Ontario (n=8,467) to:
  • Assess their agreement with different views of gambling abuse (strongly agree to disagree): Gambling abuse is a disease or illness; a wrongdoing; a habit, not a disease; or an addiction similar to drug addiction.
  • Assess agreement with different views of the ability to change gambling behavior (yes or no) – People with gambling problems can: fix it on their own without getting any treatment?; reduce their gambling to that of a social gambler or do they need to quit altogether?
  • Report their current (past year) and lifetime gambling problems – Participants who spent more than $100 gambling during their lifetime were asked past year and lifetime NODS-CLiP questions; and if they endorsed one or more items, they also completed the NORC DSM Screen for Gambling Problems.
• The researchers used logistic regression analyses to identify significant predictors of participants’ perceptions of the levels of treatment and curbing use necessary to fix gambling problems. 

Results

• Most participants (56%) strongly agreed that gambling abuse should be categorized as an addiction similar to drug addiction, followed by 38% as a disease or illness, 32% as a habit, not a disease, and 17% as a wrongdoing.
• 53% of participants felt that (a) treatment was needed to fix a gambling problem, and 71% felt that (b) people needed to remain abstinent to completely fix their gambling problem.
• 50.2% of participants (n = 4,250) reported spending less than $100 on gambling during their lifetime (i.e., non-gamblers). Of those who spent at least $100 (n = 4,217):
  • 71.4% (n = 3,012) did not endorse experiencing any gambling problems according to NODS CliP (i.e., social gamblers).
  • 28.6% (n = 1,205) endorsed one or more problem(s) and were assessed as possible or probable pathological gamblers (PG) by the NORC CLiP (i.e., possible PGs).
  • Of those, 12.4% (n = 150) met criteria for lifetime PG and half (n = 75) also met criteria for past year PG by the NORC DSM Screen (i.e., PGs).
• As Table 1 shows:
  • Compared to possible PGs and PGs, non-gamblers and social gamblers were significantly more likely to believe that treatment and abstinence were needed to completely fix a gambling problem.
  • Those who strongly agreed that gambling problems are a disease, a habit or an addiction were significantly more likely to believe treatment was necessary to fix gambling problems. The disease and addiction groups and those who viewed disordered gambling as a wrongdoing were significantly more likely to believe that abstinence was necessary.
  • Those who strongly agreed that disordered gambling was a habit were significantly less likely to believe treatment was necessary.

Table 1 – Logistic regression analyses of participants’ perceptions of gambling (adapted from Cunningham, et al., 2011)

 
* P < 0.05, ** P < 0.01, *** P < 0.001

Limitations

• This study uses retrospective self-report to identify both respondents with gambling disorders and the attitudes of those with disorders, and the reported attitudes and behaviors might not be credible (Baumeister, Vohs, & Funder, 2007).
• The results might not be generalizable to other adult populations, especially given the high prevalence rates for possible PG and PG among the participants.

Discussion

The results suggest that most possible PGs and PGs do not feel that treatment and abstinence are essential to recovering from gambling problems. This might relate to how they understand their problems with gambling and potentially be a barrier to treatment. However, those without gambling problems appear to believe that both treatment and abstinence are necessary for recovery. These findings are consistent with the fundamental attribution error (Ross, 1977): people think their behavior is the result of external influences (e.g., social pressure), but the behavior of others is due to internal states (e.g., mental illness).

Perhaps treatment providers can improve their programs by making it clear what treatment entails, educate the general public and potential treatment seekers about rational gambling beliefs, and also promote alternative treatment methods in an effort to dissipate the negative perceptions surrounding gambling addiction. Most of all, treatment providers might consider how to make treatment more attractive to all who might need it.

-Tasha Chandler

What do you think? Please use the comment link below to provide feedback on this article.

References

Baumeister, R. F., Vohs, K. D., & Funder, D. C. (2007). Psychology as the science of self-reports and finger movements: Whatever happened to actual behavior? Perspectives on Psychological Science, 2(4), 396-403. doi: DOI: 10.1111/j.1745-6916.2007.00051.x

Cunningham, J. A., Cordingley, J., Hodgins, D. C., & Toneatto, T. (2011). Beliefs about gambling problems and recovery: Results from a general population telephone survey. Journal of Gambling Studies, Online first. doi: 10.1007/s10899-010-9231-z

Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology (Vol. 10, pp. 173-220). New York: Academic Press.

Shaffer, H. J., & Martin, R. (2011). Disordered gambling: Etiology, trajectory, and clinical considerations. Annual Review of Clinical Psychology, 7, 483-510. doi: 10.1146/annurev-clinpsy-040510-143928

The WAGER, Vol. 16(3) - Pleasure and Pain: The reinforcing role of dopamine and excitement level for pathological gambling

There is reason to believe that feelings of excitement while gambling reinforce maladaptive gambling behavior among a subtype of pathological gamblers (PGs). These individuals crave excitement to a greater extent than other PGs and recreational gamblers and, for them, gambling might be especially rewarding because it offers excitement (Vachon & Bagby, 2009). Though the neurotransmitter dopamine is linked to behavior reinforcement and feelings of “sustained interest and approach” (Marco, 2010), the role of dopamine and excitement among pathological gamblers is unclear.  This week, the WAGER reviews a study that examined the association between dopamine release and feelings of excitement during gambling to explore the potentially reinforcing role of dopamine in pathological gamblers’ maladaptive behavior in comparison to healthy controls (Linnet, Møller, Peterson, Gjedde, & Doudet, 2011).

Method

• Researchers recruited 18 Pathological Gamblers (PG) and 16 age-matched, non-gambling Healthy Controls (HC) (100% male; M age = 33.6, SD = 9.3; M age = 31.7, SD = 8.0, respectively). The researchers recruited the PG group from the Center of Pathological Gambling in Odense, Denmark based on referrals of those who were still considered to be active and pathological gamblers. They recruited the HC group through local newspaper ads.
• Researchers screened all participants before the study using the DSM-IV for Axis I psychopathology; this screen included a section for pathological gambling. They excluded any participants with present psychopathology (including substance abuse disorders) or neurological disorders that disqualified them from brain scanning procedures. Any HC participants who met the criteria for more than one symptom on the pathological gambling section of the DSM-IV were excluded.
• All research participants completed the following assessments:
  • The Iowa Gambling Task (IGT) - a computerized card game consisting of four decks: two “disadvantageous” (i.e., selecting a card from these decks results in high initial gain but also high punishment and overall net loss) and two “advantageous” (i.e., smaller increments of gain but results in overall net gain).  Participants completed three versions of the IGT; it became increasingly difficult for participants to distinguish between the advantageous and disadvantageous decks. Investigators measured performance as the number of cards selected from advantageous decks minus the number of cards selected from disadvantageous decks (calculated across five blocks of 20 trials for each of the three IGT versions, for a total of 300 cards).
  • Self-reported excitement level- Participants rated their excitement levels after each IGT version by responding to the question “How exciting do you think this game is right now?” on a visual scale ranging from 1 (lowest) to 10 (highest).
  • PET/MRI Scans- Participants underwent two 60-minute PET/MRI scans:  one during the baseline condition, in which a computer explicitly told them which cards to choose, and another during the gambling condition, in which they chose cards for themselves.  The researchers measured baseline dopamine binding potentials (BPND) and changes in binding potentials (ΔBPND) between the baseline and gambling scans. Lower binding potentials signify an increase in dopamine release during gambling).
• The researchers were primarily concerned with self-reported excitement levels as a function of group status (i.e., PG versus HC), condition (i.e., baseline versus gambling) and whether participants experienced increased dopamine release during the gambling tasks.

Results

• The researchers classified all participants according to whether they experienced increased dopamine release during the gambling tasks, resulting in four groups: PG with dopamine release (n= 8), HC with dopamine release (n=7), PG with dopamine inhibition (n=10), and HC with dopamine inhibition (n=9). 
• As Figure 1 shows, the PGs with higher dopamine release during the gambling task reported a greater increase in excitement from baseline to gambling than the HC who also evidenced dopamine release t (13) = 3.28, P < 0.01.  These PG also reported more excitement during the gambling task, t (13) = 2.24, P = 0.05. There was no difference at baseline.

Figure 1- Excitement levels in PG and HC during the baseline and gambling conditions. Notes: “Δ BP ND ≥ 0” indicates increased dopamine release during gambling. “Δ BP ND < 0” indicates dopamine inhibition during gambling. (Adapted from Linnet, Møller, Peterson, Gjedde, & Doudet, 2011).

 

• Two-way ANOVAS revealed that PG with more dopamine release had greater excitement levels across all three IGT games, F (2, 12) = 10.69, P < .005.
• Among all PGs, the change in dopamine release from non-gambling to gambling were significantly correlated with changes in excitement level, t (18) = 0.52, P < 0.05. This relationship was not evident among HCs.
• There were no significant correlations between PG or HC’s increased excitement level and performance on the IGT, or between change in dopamine release and their IGT performance, but PG had lower performance than HC overall.

 Limitations

• This study’s all-male, small sample as well as the screening of participants for co-occurring substance abuse disorders limits the generalizability of these findings. A large proportion of PGs in the community also experience co-occurring substance and other disorders.
• This study also restricted its exploration of dopamine transmission to the ventral striatum brain region, which is only one of the possible areas related to dopamine release in pathological gamblers. 
• Finally, because dopamine serves other functions besides reinforcing behavior, such as warning for potentially undesirable events, this study does not conclusively prove that changes in dopamine release indicate behavior reinforcement.  Instead, PGs might experience higher dopamine release because they are expecting a potentially negative outcome from gambling.

Discussion

This study found an association between dopamine release in the ventral striatum and increased excitement levels during a gambling task among some pathological gamblers.  The authors suggest that dopamine release causes a “double deficit” for these PGs, such that dopamine both reinforces gambling (e.g., by increasing feelings of excitement) and promotes risky decision making. The authors speculate about the role of dopamine release in chemical forms of addiction, where people also perform maladaptive behaviors (e.g., repeated drug use) despite negative consequences. In some chemical forms of addiction, however, individuals often show a “blunted” dopamine response (e.g., Volkow, Wang, Fowler, & Logan, 1997).  With regard to dopamine, similarities and differences with chemical addiction warrant further research. Moreover, dopamine might not be the only factor involved in the excitement levels among pathological gamblers, and future studies should explore the reinforcing role of other biological factors.

-Brittany Bannon

What do you think? Please use the comment link below to provide feedback on this article.

References

Linnet, J., Møller, A., Peterson, E., Gjedde, A., & Doudet, D. (2011). Dopamine release in ventral striatum during Iowa Gambling Task performance is associated with increased excitement levels in pathological gambling. Addiction, 106(2), 383-390.

Marco, L., (2010). The neurobiology of desire: Dopamine and the regulation of mood and motivational states in humans. In Kringelbach, M. L., & Berridge, K. C. (Eds.) Pleasures of the Brain (pp. 222-243). New York, NY: Oxford University Press.

Moodie, C., & Finnigan, F. (2005). A comparison of the autonomic arousal of frequent,
infrequent and non-gamblers while playing fruit machines. Addiction, 100, 51-59.

Vachon, D. D., & Bagby, R. M. (2009). Pathological gambling subtypes. Psychological Assessment, 21(4), 608-615.

Volkow, N. D., Wang, G. J., Fowler, J. S., & Logan, J. (1997). Decreased striatal dopaminergic responsiveness in detoxified cocaine-dependent subjects. Nature, 386(6627), 830-833.