BY:

Matthew J. Carlson, Ph.D.
 Institute of Health, Health Care Policy, and Aging Research
Rutgers University
New Brunswick, New Jersey
AND
Thomas L. Moore, Ph.D.
Herbert & Louis Wilsonville, Oregon
December 1, 1998
Funded by the Oregon Gambling Addiction Treatment Foundation Salem, Oregon

Table of Contents  

Acknowledgements
 
In August of 1998, the Oregon Gambling Addiction Treatment Foundation commissioned a study with the purpose of estimating the prevalence of gambling behavior and pathological gambling among Oregon youth ages thirteen to seventeen.  Although this survey was conducted and carried out by Matthew Carlson and Thomas Moore, it would not have been possible without the help of many individuals and organizations who assisted with the project.  The authors would like to thank Mr. Michael McCracken for his untiring assistance in making this study a reality.  Without the gracious support of the Spirit Mountain Community Fund and the Oregon Lottery this study would not have been possible.
 
The authors would also like to thank Rina Gupta, Sue Fisher, Henry Lesieur, Randy Stinchfield, Ken Winters, Norval Glenn, and Dan Mears for their collegial support and suggestions during the process.

Copies of this report can be obtained by contacting:
 
Oregon Gambling Addiction Treatment Foundation
PO Box 866
Salem, Oregon 97308
(503) 399-7201
www.gamblingaddiction.org


Executive Summary
The Oregon Gambling Addiction Treatment Foundation commissioned this independent study to measure the estimated prevalence of gambling and problem gambling among Oregon youth ages 13 to 17.   This telephone survey of 1000 randomly selected youth in Oregon was conducted in September and October of 1998.  The Key findings of this study are as follows:

• Seventy-five percent ( ± 3) of the respondents surveyed reported gambling for money at least once in their lives and 66% ( ± 3) reported gambling last year.  As with prevalence studies done in other states, this study found that boys and older adolescents were more likely to gamble than girls and younger adolescents (Volberg, 1993; Westphal, 1998; Winters, Stinchfield and Fulkerson, 1993b).  This study found that between 140,777 to 154,185 adolescents gambled for money in the last 12 month

• The rate of level 2  (in-transition) gambling is estimated by this study at 11.2% ( ± 2%).  The rate of level 3 (problem) gambling is estimated at 4.1% ( ± 2). These rates appear to be slightly lower than rates of the few states which have conducted studies and used similar techniques for estimating problem gambling including Washington State, Minnesota and Louisiana.

• The study findings recommend the development of treatment opportunities for youth with problems associated with gambling.  It is estimated that between 20,558 and 29,496 adolescents are level 2 gamblers while between 4,693 and 13,631 are level 3 gamblers.

• It is estimated that between 94 and 272 adolescents should access treatment each year.

• Of those adolescents who reported gambling, 4.0 percent reported daily gambling while 13.3 percent reported weekly gambling for money.  Boys were more likely to be frequent gamblers than girls.

• Among 13 to 17 year-olds, 39% ( ± 3) have played the Oregon Lottery at least once in their life, and 30% ( ± 3) reported playing last year.  At least 50% of the young lottery players obtain the tickets from family members, and 35% buy them illegally, primarily at grocery stores and convenience stores.  This finding was similar to those in other states (Shaffer, H.J., Hall, M.N. and Vander Bilt, J., 1997)

• Approximately 19% ( ± 2) of the respondents reported gambling in a casino at least once in their lives, and 12% ( ± 2) reported gambling in a casino last year.  This finding was similar to those in other states (Shaffer, H.J., Hall, M.N. and Vander Bilt, J., 1997).  Approximately 50% of those reporting casino gambling reported doing so out of State.

• Of the other forms of gambling, purchasing raffle tickets (41%) was the most frequently cited, followed by betting on sports with friends or relatives (32%); playing cards (31%) and betting on games of skill, such as pool or bowling, (25%).

• The youth in this survey were significantly more likely to gamble and were also more likely to begin gambling earlier (in grade school) if one or both of their parents gamble. 

• Age of onset may be decreasing in Oregon.  Younger respondents (13 and 14 years old) were significantly more likely to report gambling in grade school than older respondents (15 to 17 years old).  In addition, respondents who reported gambling in grade school were significantly more likely to be problem gamblers. 

• As found in other studies, there is a moderate correlation between gambling and alcohol, drug, and tobacco use (Westphal et al., 1998).

• Less than one percent reported gambling with money on the Internet.
  
  
• Prevention efforts, targeting grade and middle school aged children, are indicated.  The association of problem gambling with other risk behaviors such as smoking and alcohol and drug use would indicate these prevention efforts could be blended with existing efforts formally integrated into the private and public school curricula.

List of Tables
 

 

 
            For the reader not familiar with the prevention literature, primary prevention is defined as those efforts that delay or prevent the onset of activities that can lead to harmful gambling (Shaffer, H.J. & Hall, M.N., 1996, p. 207). Secondary prevention is defined as efforts aimed at minimizing the likelihood that level 1 gamblers will develop problems related to gambling (Shaffer, H.J. & Hall, M.N., 1996, p. 209).  Tertiary prevention is then defined as those efforts that are taken with youth in order to minimize problems that exist with level 2 and level 3 gambling.  This level of prevention could be associated with early treatment for level 2 and treatment for level 3 gamblers and defined as relapse prevention (Shaffer, J.J. & Hall, M.N., 1996, p. 209-210).  Treatment would be defined as those activities associated with arresting the problem gambling behavior and minimizing the harm caused by that behavior.
 
Estimating Problem Gambling
 
            In this study we estimate the prevalence of problem gambling using the SOGS-RA for several reasons.  First, it allows comparison with several other states including Washington, Minnesota, and Louisiana.  Second, it has been found to be a valid and reliable instrument which is based on extensive testing (see Winters et al., 1993a).  Finally, the SOGS-RA has been tested using telephone interviews, which is the methodology employed in the current study.
 
            Both the SOGS-RA and the adult version on which it is based, the SOGS (Lesieur and Blume, 1987) were created using the DSM-IIIR classification for pathological gambling (APA, 1987).  In order to develop the adolescent version of the SOGS, a research team at the University of Minnesota revised the original SOGS items, with the help of an adolescent focus group, in order to “accommodate adolescent experiences and reading levels” (Winters et al., 1993a, p. 67).  A psychometric evaluation of the instrument reported that the SOGS-RA was both a reliable and valid measure of problem gambling for adolescents.
 
            The SOGS-RA consists of a two-part questionnaire which measures a) the frequency and type of gambling activities engaged in by respondents and b) a checklist of 12 signs and symptoms of pathological gambling as described in the DSM-IIIR.  In order to estimate the prevalence of pathological gambling, the number of symptoms that a respondent reports are summed to create an overall score which can range from 0 (no symptoms at all) to 12 (respondent experiences all 12 symptoms). 
 
            There is not currently a single agreed-upon method for defining level three gambling, no gold standard so to speak.  In order to accommodate reasonable variation in definitions of problem gambling and comparisons to other studies,   we provide two different estimates of problem gambling.  Nonetheless, because the broad method combines frequency of gambling with number of symptoms,  we feel it is better than the narrow method for planning preventative and treatment interventions.  Both of these classification techniques have been previously used by the developers of the SOGS-RA instrument, and both are reasonably valid and reliable (Winters et al., 1993b; Winters, Stinchfield and Kim, 1995).
 
            The first estimate based on "narrow criteria," uses only the score on the SOGS-RA items to estimate problem gambling. Using this method results in a relatively low estimate primarily because it does not include the frequency of gambling as a criteria.  In this method, a SOGS-RA score of four or more identifies an adolescent as a problem gambler.  While this ensures a conservative estimate of problem gambling, it is possible that it underreports the number of youth that many would consider problem gamblers.  For example, a respondent with a SOGS score of three will not be classified as a problem gambler, even if she gambles every day and reports having trouble in school and with her parents (scored two) as a result of gambling using the narrow criteria.   
 
            Estimates reported based on "broad criteria" include measures of gambling frequency in the criteria of problem gambling.  Thus, a respondent who gambles every day, and has experienced some problems, is defined as a problem gambler.  The broad method is perhaps more instructive in identifying problem gambling because it would identify a heavy gambler who is experiencing some difficulty as a problem gambler, even if the number of symptoms experienced is fewer than four (Winters et al., 1995).  This report provides both estimates in order to acknowledge the current variability in defining level three gambling in gambling research.  Scoring rules for both narrow and broad criteria are included in Appendix 1.
 
Data and Methods
 
            Data for this report come from surveys gathered from a random sample of 1000 adolescents between the ages of 13 to 17 who were selected from a targeted list of households.  The list of eligible households was created by examining drivers license applications and voter registration lists which indicate households with a higher than usual likelihood of containing an adolescent in the target age group.  Although respondents are randomly selected, the sampling frame is not, strictly speaking, a random sample.  Nevertheless, in previous research this sampling methodology yielded representative samples which are generalizable to the target population (Volberg, 1993; Winters et al., 1995). 
 
            Sample characteristics for the current study are listed below in Table 1.2.  For most characteristics, the sample is representative.  Some caution should be exercised when generalizing the results of this sample to the non-white population.  The proportion of this sample which is Anglo matches census estimates almost exactly.  However, the study sample underrepresents certain minority groups, and overrepresents the “other" category.  For this reason, and because the percentages of various minority groups are rather small, analyses in this report compare Anglos with non-Anglos (including the “other” category) and should be considered as tentative for the non-Anglos.  
 

Table 1.2. Sample Characteristics (In Percent)
   
In order to test the representativeness of the sample, t-tests for proportions were done to determine whether or not the study sample was significantly different by age, gender, and percent white, from the population estimates provided by the Center for Population Research and Census, 1996; no significant differences were found.  However, because gambling was significantly different by county, and not all counties were proportionally represented in this survey, data were weighted by county in order to reflect the actual distribution of population by county.  Analyses in this report are based on the weighted data.  Additionally, because the rates of gambling participation were based on a sample, they should be considered as estimates and are subject to a margin of error of ± 3% (95% confidence level) for the population as a whole.  Subgroup analyses are subject to a somewhat higher margin of error due to smaller sample sizes.  Estimates of level 2 and level 3 gambling are subject to a sampling error of ± 2%.  
 
            Of the original sample of 1000 respondents, three interviews were dropped from the final sample for failing to complete all SOGS items, or for obvious exaggerations of gambling frequency.  Thus, the final sample consists of 997 participants.  The response rate for the sample was 38%; the refusal rate was 48%.
 
Survey Methodology
 
            The survey for this report was developed in two-stages.  First, a review of current literature was conducted to determine what surveys were currently being used, and what risk factors should be examined.  Second, a survey was created which incorporated information about gambling (based on the SOGS-RA instrument) as well as information about other risky behaviors including drug and alcohol use, smoking, and criminal behavior as well as attitudinal information.  A copy of the survey instrument is provided in Appendix 2.  In order to be sure that reliable and valid estimates of problem gambling are provided by this report, there were no modifications made to the scored items of the SOGS-RA either in appearance or order.  Both past-year and lifetime estimates are included in the analyses, however, the estimates of problem gambling were based on past-year gambling behavior only.
 
            Second, the survey was reviewed by an outside reviewer and pilot-tested on approximately 40 older adolescents in an introductory course (composed almost entirely of freshman) at a medium sized university in Washington State.  Results of both the outside review and pilot test indicated that the survey was of appropriate length and readability.
 
            The telephone interviews were conducted by Gilmore Research Group of Seattle, WA.  Consent was obtained both from the parents and the adolescents prior to the interview.  The average length of the interview was approximately twelve minutes.
 
                Most recently, there have been efforts to establish an instrument based on the American Psychiatric Association's diagnostic criteria for pathological gambling (American Psychiatric Association, 1994) for adolescents (Fisher, S.E, 1998; Gupta, R., & Derevensky, J.L., 1998).  In an effort to contribute to the knowledge base, this study was also designed to compare the SOGS-RA with the DSM-IV-JR (See Fisher, S.E., 1998).  (The findings from this analysis will be published in a forthcoming paper by the authors.)
 
            In order to prevent any potential question order bias, the SOGS-RA and the DSM-IV-JR questions were alternated.  (See Appendix 2, questions 21, 22, and 23 were alternated with question 44.)  Additionally, the lottery participation questions (7, 8, and 9) were alternated with the casino questions (11 and 12) as well as the lottery advertising recall questions (32 - 37) with the casino advertising recall questions (38 - 42).

CHAPTER TWO. ADOLESCENT GAMBLING
 
            This chapter describes the prevalence of gambling, including the differences in prevalence among various segments of the population and for various forms of gambling including the lottery, casino, and other forms of gambling.  Additionally, this chapter examines factors associated with gambling including age of onset, influence of parental gambling, gambling and substance use, advertising recall, and attitudes about gambling.  The overall prevalence rates for gambling presented in this chapter are estimates derived from a probability sample, and as such are subject to a margin of error of ± 3%.  Some rates for subgroups may be associated with a slightly higher margin of error due to the smaller sample sizes.
 
The Prevalence of Gambling
 
            The majority of adolescents gamble.  Table 2.1. shows that three-quarters of Oregon adolescents have gambled at least once in their lives and 66% gambled within the last 12 months.
 
Table 2.1. Lifetime and One-year Gambling Prevalence Rates In Percent)
   
            Boys are significantly more likely to gamble than girls, and older youth are significantly more likely to gamble than younger youth.  Percentages reported are row percentages.  Thus, 74% of the 539 boys in the sample reported gambling last year compared to 57.1% of the 459 girls in the sample [7] .  Although previous studies have shown a relationship between race and gambling (Wallisch, 1996) our sample does not bear this out.
 
Prevalence of Lottery Gambling
 
            Although most youth gamble, only one-third of the sample reported gambling on the lottery in the 12 months prior to the survey.  Table 2.2 shows the rates of lottery playing.  The patterns of lottery play are similar to gambling overall: Boys and older adolescents are more likely to play the lottery than are girls and younger adolescents.
 
Table 2.2. Lottery Gambling (In Percent)
   
            Table 2.3 identifies the most popular lottery games for 13 to 17 year olds.  Nearly 23% of the sample reported playing scratch-off tickets; Sports Action and Keno, respectively, are the next most popular lottery games, however, less the 10% of the sampled played either of these games.
 
Table 2.3. Lottery Gambling by Game (In Percent)
   
            Although minors are not legally allowed to purchase lottery tickets, approximately 35% of those who had gambled on the lottery indicated they had done so in the 12 months preceding the survey (see Table 2.4).  Most of the illegally purchased lottery tickets were purchased in grocery stores.  The majority of young lottery players, however, obtain the tickets from family members (50%).
 
Table 2.4. Where Lottery Tickets are Obtained (In Percent)
 
   
   
Prevalence of Casino Gambling
 
            Table 2.5 shows the rates of reported illegal casino gambling.  Approximately 19% of the sample reported betting money at a casino at least once in their life and approximately 12% ( ± 2) of the sample did so last year.
 
Table 2.5. Casino Gambling (In Percent)
   
            The pattern of casino gambling is somewhat different than other forms of gambling.  For example, teenage girls reported gambling in casinos as often as did boys.  Although there is a trend towards older youth gambling in casinos more often that their younger counterparts, it is not statistically significant.  Non-Anglos were significantly more likely to have gambled at a casino at least once in their lives, however, the one-year rates were not significantly higher.  Surprisingly, about half of the casino gambling is done outside of Oregon.  Of those who reported gambling in a casino at least once in the last 12 months, 51% reported doing so outside Oregon.  The remaining 49% reported gambling in a casino in Oregon.
 
Prevalence of Other Gambling Activities
 
            Other gambling activities in which adolescents commonly engaged included purchasing raffle tickets, betting on sports with friends or relatives, and playing cards for money (see Table 2.7).  In fact, as Table 2.6 indicates, youth were more likely to participate in these other forms of gambling than play the lottery or gamble in a casino.
 
Table 2.6. Other Gambling Activities (In Percent)
   
            As table 2.7 shows, purchasing raffle tickets, betting on sports teams with friends and relatives, and playing cards are the most popular forms of gambling among those respondents that reported gambling in the 12 months prior to the survey.
 
Table 2.7 Prevalence Rates for Other Forms of Gambling (In Percent)
   
            Participants in the survey were allowed to respond to more than one answer for this question.
 
            Internet gambling is the least common form of gambling with less than 1% of the sample reporting gambling with money on the internet in the 12 months prior to the survey.
 
Prevalence of Gambling for Select Counties
 
            In order to examine the geographic distribution of gambling, the five largest counties were analyzed separately.  As stated above, the data were weighted to accurately reflect the proportion of the population residing in each county as reported by the Center For Population Research 1996 population estimates.  Table 2.8 shows that there are significant differences in the prevalence of gambling by county.
 
   
Table 2.8. Gambling Prevalence by County (In Percent)
   
            Marion county's prevalence rates, for all gambling activities combined, are significantly lower than for Multnomah County, Washington County, and the Other Counties group, which is composed of all other counties [13] .  As for casino gambling, respondents from Lane County appeared to report higher levels of casino gambling than respondents from any of the other counties, although the differences are not statistically significant.  Multnomah County had the highest rates of lottery gambling.  Rates in Multnomah County were significantly higher than for Washington and the Other counties [14] .
 
Gambling Frequency
 
            Most youth gamble very infrequently.  As Table 2.9 shows, more than half of the 658 adolescents who reported gambling in the last 12 months, did so less than monthly (55%).  Not only are boys more likely to gamble than girls, but boys are also more frequent gamblers than girls.  Although the differences are not statistically significant, it appears that the older respondents are less likely to report gambling "less than monthly" and more likely to report gambling on a monthly basis.  However, the youngest age groups appear just as likely as their older counterparts to gamble on a daily or weekly basis.  Non-Anglos appear to be more likely to gamble daily and weekly and less likely to gamble "less than monthly" than their Anglo counterparts, but the differences are not statistically significant.
 
 
Table 2.9. Frequency of Gambling (In Percent)
 
   
Average Monthly Expenditures
 
            Not only do most youth gamble infrequently, youth report spending very little money gambling.  Most of the respondents who gambled last year reported spending less than $10.00 per month.  However, the expenditure figures reported in Table 2.10 should be considered only with caution.  In analyses not shown here, approximately 80% of the respondents who reported spending no money last year also reported that they gambled at least once in the previous year and 20% reported gambling more than monthly.  One possible explanation of this is that these adolescents considered the amount so trivial that they simply reported spending nothing.  Nonetheless, it is still instructive to examine expenditures to get some sense of the overall spending patterns which confirm other measures of gambling.  On average, older youth and boys tend to spend more than the younger adolescents and girls.
 
            It appears that boys spend significantly more than girls despite the fact that they do not make significantly more.  Table 2.11 shows the reported incomes.  By comparing Tables 2.10 and 2.11, one can see that boys report spending more on gambling than girls, despite the fact they do not report significantly higher incomes.  By the same token, older adolescents report spending more (though the differences are not statistically significant) but they also report higher incomes than their younger counterparts.
 
Table 2.10 Average Monthly Gambling Expenditures (In Percent)