Adolescent Gambling in Oregon:
A report to the
Oregon Gambling Addiction Treatment Foundation
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
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
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:
|
Acknowledgements........................................................................ |
i |
|
Executive
Summary....................................................................... |
ii |
|
Table of
Contents........................................................................... |
iv |
|
List of Tables.................................................................................. |
v |
|
|
|
|
Chapter One.
Introduction............................................................. |
1 |
|
Purpose of the
Study............................................................... |
1 |
|
Defining Problem
Gambling.................................................... |
2 |
|
Estimating Problem
Gambling................................................. |
5 |
|
Data and
Methods.................................................................... |
6 |
|
Survey
Methodology................................................................ |
8 |
|
|
|
|
Chapter Two. Adolescent
Gambling............................................... |
10 |
|
The Prevalence of
Gambling.................................................... |
10 |
|
Prevalence of Lottery
Gambling............................................... |
11 |
|
Prevalence of Casino
Gambling............................................... |
13 |
|
Prevalence of Other Gambling
Activities.................................. |
14 |
|
Prevalence of Gambling for Selected
Counties....................... |
15 |
|
Gambling
Frequency................................................................ |
16 |
|
Average Monthly
Expenditures................................................. |
17 |
|
Grade of Onset......................................................................... |
19 |
|
Youth Gambling and Parental
Gambling.................................. |
21 |
|
Gambling Prevalence/Frequency and
Substance Use............. |
23 |
|
Advertising Awareness and
Gambling...................................... |
24 |
|
Adolescent
Attitudes................................................................. |
26 |
|
Chapter
Summary..................................................................... |
27 |
|
|
|
|
Chapter Three. Level 2 and Level 3
Gambling............................... |
29 |
|
Prevalence of Level 2 and Level 3
Gambling........................... |
29 |
|
Age of Onset, Parental Gambling and
Problem Gambling....... |
31 |
|
Substance Abuse and Problem
Gambling................................ |
34 |
|
Comparing Oregon's Rates with Other
States.......................... |
34 |
|
Chapter
Summary..................................................................... |
36 |
|
|
|
|
Chapter Four. Conclusions and
Implications of the Study.............. |
37 |
|
Prevalence of Gambling and Problem
Gambling...................... |
37 |
|
Risk Factors Associated with Problem
Gambling..................... |
38 |
|
Implication for
Policy................................................................. |
39 |
|
Implication for future
Research................................................. |
40 |
|
|
|
|
References...................................................................................... |
41 |
|
Appendix 1. SOGS-RA and Scoring
Rules..................................... |
43 |
|
Appendix 2. Survey
Instrument....................................................... |
45 |
List of Tables
|
Table 1.1 |
Classification of
Adolescent Gambling..................................... |
4 |
|
Table 1.2 |
Sample
Characteristics............................................................. |
7 |
|
Table 2.1 |
Lifetime and
One-Year Gambling Prevalence Rates................ |
10 |
|
Table 2.2 |
Lottery
Gambling...................................................................... |
11 |
|
Table 2.3 |
Lottery Gambling by
Game...................................................... |
12 |
|
Table 2.4 |
Where Lottery
Tickets are Obtained......................................... |
12 |
|
Table 2.5 |
Casino
Gambling...................................................................... |
13 |
|
Table 2.6 |
Other Gambling
Activities......................................................... |
14 |
|
Table 2.7 |
Prevalence Rates
for Other Forms of Gambling...................... |
15 |
|
Table 2.8 |
Gambling Prevalence
by County.............................................. |
16 |
|
Table 2.9 |
Frequency of
Gambling............................................................ |
17 |
|
Table 2.10 |
Average Monthly
Gambling Expenditures................................ |
18 |
|
Table 2.11 |
Average Weekly
Income.......................................................... |
19 |
|
Table 2.12 |
Grade of Onset......................................................................... |
20 |
|
Table 2.13 |
Grade of Onset and
Frequency of Gambling........................... |
21 |
|
Table 2.14 |
Youth Gambling and
Parental Gambling.................................. |
22 |
|
Table 2.15 |
Grade of Onset and
Parental Gambling................................... |
22 |
|
Table 2.16 |
Drug Use and
Gambling........................................................... |
23 |
|
Table 2.17 |
Correlation Between
Frequency of Gambling and Frequency of Substance Use..................................................................... |
24 |
|
Table 2.18 |
Frequency of
Lottery Gambling and Advertising Recall........... |
25 |
|
Table 2.19 |
Frequency of Casino
Gambling and Advertising Recall........... |
25 |
|
Table 2.20 |
Frequency of Advertising
Recall by Type................................. |
26 |
|
Table 2.21 |
Responses to the
Question: To what extent, in general, do you feel gambling is a good way to
make money?................... |
26 |
|
Table 2.22 |
Responses to the
Question: Some say that people get ahead by their own hard work; others say
that lucky breaks or help from other people are more important. Which do you think is most
important?........................................................................ |
27 |
|
Table 3.1 |
Prevalence of Level
2 and Level 3 Gambling........................... |
29 |
|
Table 3.2 |
Prevalence of Level
2 and Level 3 Gambling for At-Risk
Population................................................................................ |
30 |
|
Table 3.3 |
Gender, Age, Race
Distribution of At-Risk Level 2 and Level 3
Gamblers.............................................................................. |
30 |
|
Table 3.4 |
Grade of Onset and
Problem Gambling................................... |
31 |
|
Table 3.5 |
Parental Gambling
and Problem Gambling.............................. |
32 |
|
Table 3.6a |
Grade of Onset and
Problem Gambling................................... |
32 |
|
Table 3.6b |
Children of
Gambling Parents.................................................. |
33 |
|
Table 3.6c |
Children of
Non-Gambling Parents.......................................... |
33 |
|
Table 3.7 |
Correlation of
Substance Use and Level of Gambling............. |
34 |
|
Table 3.8 |
Comparing Oregon
With Other States...................................... |
35 |
|
|
|
|
Gambling is an increasingly popular
leisure activity enjoyed in the United States by a majority of adults and
youth. Most adolescents gamble, and
most of those who do so experience few problems associated with gambling. According to a recent review of 22 studies
of adolescent gambling which were conducted in the U.S. and Canada, between 86%
and 93% of youth have gambled at least once in their life, and between 3% and
8% of adolescents are problem gamblers (Shaffer, Hall and Vander Bilt, 1997). However, it is also clear that youth may
have more trouble controlling their gambling behavior than adults (Derevensky
and Gupta, 1996, Lesieur and Klein, 1987; Stinchfield, Cassuto, Winters and
Latimer,1997). Rates of problem
gambling among youth are considerably higher than the rates for adult problem
gambling. The findings of this study
and those of the Oregon Adult Gambling Prevalence Study (Volberg, 1997) completed in August, 1997
show this tendency to be true in Oregon.
Not only are youth at greater risk of
experiencing problems associated with gambling behavior, those who do may be at
greater risk of experiencing gambling related problems as adults. Recent research suggests that early onset of
gambling may be associated with the development of problem gambling later in
life (Volberg, 1994). Thus, not only
does adolescent gambling behavior carry the potential for serious negative
consequences for youth, if left unchecked, frequent gambling in adolescence may
develop into problem gambling in adulthood.
Because of this, understanding adolescent gambling is of crucial
importance not only to reduce negative consequences associated with youth
gambling, but also to arrest the development of gambling problems which may be
carried into adulthood. Understanding
the prevalence and risk-factors for adolescent problem gambling is an important
issue which ultimately may help reduce the social cost associated with both
adolescent and adult gambling problems.
The purpose of this study is to
estimate the prevalence of gambling behavior and problem gambling by analyzing
a survey of 1000 Oregon adolescents ages 13 to 17 about the nature and extent
of their gambling behavior. This survey
is also intended to be used as a baseline from which future studies can
evaluate changes in adolescent gambling over time. Additionally, this report identifies various factors that may be
associated with increased risk of pathological gambling. Finally, this study was designed to estimate
the number of youth that may benefit from prevention or treatment
interventions.
This study addresses
the following questions:
·
How many of Oregon’s
adolescents gamble?
·
In what forms of
gambling do adolescents participate?
·
At what age do
adolescents begin gambling?
·
What is the
prevalence of problem gambling among adolescents in Oregon?
·
Is gambling related
to substance abuse?
·
Does gambling by
parents influence the likelihood of gambling and problem gambling in
adolescents?
·
Are gamblers more
aware of lottery and/or casino advertising than non-
gamblers?
For most individuals, gambling is a
social activity enjoyed in moderation.
Social gambling is defined by the American Psychiatric Association as
“gambling which lasts for a limited amount of time with predetermined
acceptable losses” (APA, 1994, p. 617).
However, for some, gambling becomes a compulsion, an activity which is
carried out in the face of negative consequences. The official definition of pathological gambling, as defined in
the American Psychiatric Association’s Diagnostic and Statistical Manual of
Mental Disorders, 4th Edition (APA, 1994) is as follows:
Pathological
Gambling: Persistent and recurrent maladaptive gambling
behavior that disrupts personal, family, or vocational pursuits[1].
For the purposes of this study we
will use the term “problem gambling” rather than pathological gambling. The estimates of problem gambling derived
from this survey are not based on clinical examinations, rather, they are
estimates derived from surveys. Thus,
we will use non-clinical terminology to describe persistent gambling behavior
which results in self-reported problems such as truancy or conflict with family
and friends.
Current research suggests that youth
gambling occurs on a continuum of involvement from no gambling at all to
occasional gambling, to over-involvement (Stinchfield and Winters, 1998). In order to describe the range of problems
associated with gambling we use the South Oaks Gambling Screen Revised for
Adolescents (SOGS-RA) developed at the University of Minnesota (Winters,
Stinchfield and Fulkerson, 1993a). We
then classify adolescents based on their SOGS-RA score using the level system
as proposed by Shaffer and Hall (1996).
We
use the level system for at least two reasons.
First, the level system offers a common sense approach to describing the
continuum of gambling pathology.
Historically, there has been no consensus about how to define pathological
gambling in adolescents. However, since the publication of Shaffer and Hall’s
proposed level system, other researchers have begun to adopt this approach to
classifying problem gambling (Westphal, Rush, Stevens, Horswell & Johnson,
1998). Second, the level system is the
only classification scheme which directly links various degrees of problem
gambling with levels of intervention.
Thus, the level system not only provides a straight forward approach to
classifying gambling behavior, but links various levels of gambling with
appropriate intervention. Table 1.1,
below, describes the level system.
Because
youth experience a wide range of problems associated with gambling, it is not
useful to simply describe young gamblers as “problem gamblers” or “non-problem
gamblers.” The level system used in
this report classifies young gamblers in terms of the degree of problems
associated with gambling. As described
in Table 1.1 below, level 1 gambling is “social gambling” or gambling which is
not associated with any problems.
Level two gambling, or in-transition
gambling, refers to gambling behavior which does not meet the diagnostic
criteria for pathological gambling, but which does, nonetheless, appear to be
somewhat problematic. Because the adult
rates of problem gambling are lower than the adolescent rates, there is reason
to believe that many adolescents who are classified as problem gamblers may not
go on to become adult problem gamblers.
Thus, a youth described as an in-transition gambler may be moving toward
problem gambling, or may be moving away from problem gambling (Shaffer, Hall
and Vander Bilt, 1997).
Finally, level three gambling refers
to problem gambling. Adolescents
described as level three gamblers report heavy gambling in the face of adverse
consequences. This population is the
target population for which treatment for pathological gambling may be
necessary. Because the survey used for
this report did not ask respondents to identify whether or not they wanted
treatment we do not use the level 4 classification in the report.
Table 1.1.
Classification of Adolescent Gambling[2]
|
Levels of Gambling Involvement |
Definition |
Possible Education, Prevention,
Treatment Interventions |
SOGS-RA Score (narrow criteria) |
|
Level 0: Non-
Gambling |
Has
never gambled |
Ø Educational
awareness Ø Primary prevention |
0 |
|
Level 1:
Non-Problem Gambling |
Gambles
recreationally and does not experience any signs or symptoms of
gambling-related disorder |
Ø
Secondary Prevention |
£ 1 |
|
Level 2:
In-Transition Gambling |
Gambler
who experiences subclinical symptoms or displays signs of gambling problems,
may be progressing either toward more serious symptoms (i.e.,
progression) or away from these
symptoms (i.e., during recovery) |
Ø Tertiary
prevention Ø Early
treatment to arrest progression Ø Relapse
prevention activities to facilitate and sustain recovery |
2-3 |
|
Level 3:
Gambling-Related Disorder with Impairment |
Gambler
who meets diagnostic criteria as assessed by the SOGS-RA as impaired in
psychological or sociological domains. |
Ø Tertiary
prevention to minimize harm Ø Treatment |
³ 4 |
|
Level 4: Impaired
Gambler who Displays Willingness to Enter Treatment |
Gambler
who satisfies level 3 requirements and, in addition, displays interest in
entering treatment |
Ø Treatment |
N/A |
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.
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 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)
|
|
Sample
Characteristics (n=997) |
Oregon Census |
|
|
|
|
|
Age[3] |
|
|
|
14 |
24.3 |
25.4 |
|
15 |
26.1 |
25.2 |
|
16 |
26.0 |
24.6 |
|
17 |
23.6 |
24.8 |
|
Total |
100.0 |
100.0 |
|
|
|
|
|
|
|
|
|
White |
90.1 |
90.7 |
|
Hispanic |
1.7 |
NA |
|
Native American |
2.0 |
2.0 |
|
Asian |
1.6 |
2.9 |
|
Black |
0.2 |
2.1 |
|
Other |
3.7 |
2.3 |
|
Total |
99.1 |
100.0 |
|
|
|
|
|
|
|
|
|
46.0 |
48.5 |
|
|
54.0 |
51.5 |
|
|
Total |
100.0 |
100.0 |
|
|
|
|
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%.
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).
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 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)
|
Group (N) |
Gambled Lifetime |
Gambled Past 12 Months |
|
|
|
|
|
Total
(997) |
75.9 |
66.0 |
|
|
|
|
|
Gender
[5] |
|
|
|
Boys (539) |
81.3 |
74.0 |
|
Girls (459) |
73.7 |
57.1 |
|
|
|
|
|
Age [6] |
|
|
|
13 (151) |
69.3 |
58.9 |
|
14 (205) |
74.6 |
65.4 |
|
15 (221) |
76.9 |
66.1 |
|
16 (220) |
76.4 |
69.1 |
|
17 (200) |
80.4 |
68.5 |
|
|
|
|
|
Race |
|
|
|
Anglo (898) |
76.7 |
66.9 |
|
Non-Anglo (99) |
68.7 |
58.2 |
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.
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)
|
Group (N) |
Gambled Lifetime |
Gambled Past 12 Months |
|
|
|
|
|
Total
(997) |
38.9 |
29.6 |
|
|
|
|
|
Gender [8] |
|
|
|
Boys (539) |
42.3 |
33.3 |
|
Girls (459) |
34.9 |
25.3 |
|
|
|
|
|
Age [9] |
|
|
|
13 (151) |
35.1 |
25.8 |
|
14 (205) |
38.5 |
27.3 |
|
15 (221) |
39.5 |
29.5 |
|
16 (220) |
37.3 |
27.3 |
|
17 (200) |
43.2 |
37.7 |
|
|
|
|
|
Race |
|
|
|
Anglo (898) |
39.5 |
30.1 |
|
Non-Anglo (99) |
32.7 |
25.3 |
|
|
|
|
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)
|
Lottery Game |
Percent |
|
|
|
|
Scratch-its |
22.6 |
|
Sports
Action |
7.8 |
|
Keno |
5.3 |
|
Pull-tabs |
4.6 |
|
Powerball |
4.6 |
|
Video
Poker |
4.3 |
|
Megabucks |
3.3 |
|
Daily
four |
0.8 |
|
|
|
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)
|
Access Type |
Percent |
|
|
|
|
Buy
them myself at a convenience store |
12.9 |
|
Buy
them myself at a grocery store |
18.6 |
|
Buy
them myself at a vending machine |
1.3 |
|
Buy
them myself at a deli, restaurant, tavern, or bar |
2.4 |
|
A
parent, sibling, or other relative buys them for me |
50.0 |
|
Other |
15.0 |
|
|
|
|
Total
(379) |
100.0 |
|
|
|
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)
|
Group (N) |
Gambled Lifetime |
Gambled Past 12 Months |
|
|
|
|
|
Total
(997) |
18.6 |
12.1 |
|
|
|
|
|
Gender |
|
|
|
Boys (539) |
18.6 |
13.4 |
|
Girls (459) |
18.6 |
10.5 |
|
|
|
|
|
Age |
|
|
|
13 (151) |
13.9 |
7.3 |
|
14 (205) |
19.0 |
11.7 |
|
15 (221) |
22.7 |
15.0 |
|
16 (220) |
14.5 |
10.5 |
|
17 (200) |
21.6 |
15.0 |
|
|
|
|
|
Race[10] |
|
|
|
Anglo (898) |
17.6 |
11.8 |
|
Non-Anglo (99) |
28.3 |
15.2 |
|
|
|
|
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.
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)
|
Group (N) |
Gambled Lifetime |
Gambled Past 12 Months |
|
|
|
|
|
Total
(997) |
73.2 |
62.9 |
|
|
|
|
|
Gender [11] |
|
|
|
Boys (539) |
79.7 |
71.2 |
|
Girls (459) |
65.6 |
53.2 |
|
|
|
|
|
Age [12] |
|
|
|
13 (151) |
66.2 |
56.0 |
|
14 (205) |
72.2 |
59.7 |
|
15 (221) |
74.5 |
65.0 |
|
16 (220) |
73.2 |
66.4 |
|
17 (200) |
77.9 |
65.3 |
|
|
|
|
|
Race |
|
|
|
Anglo (898) |
73.8 |
63.6 |
|
Non-Anglo (99) |
67.7 |
56.6 |
|
|
|
|
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)
|
Forms of Gambling |
Percent |
|
|
|
|
Purchased
raffle tickets for a charitable organization |
40.5 |
|
Bet
on sports teams with friends/relatives |
31.6 |
|
Played
cards at someplace other than a casino |
30.9 |
|
Bet
on games of skill |
25.4 |
|
Played
bingo other than at a casino |
14.8 |
|
Played
dice games not at a casino |
10.1 |
|
Flipped
coins for money |
6.9 |
|
Bet
on horse or dogs |
3.3 |
|
Bet
on sports teams with bookies |
3.3 |
|
Gambled
on the Internet |
0.3 |
|
Other |
4.0 |
|
|
|
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.
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)
|
County (N) |
Any Gambling |
Casino Gambling |
Lottery Gambling |
|
|
|
|
|
|
Multnomah
(198) |
67.7 |
8.1 |
38.2 |
|
Washington
(120) |
66.7 |
10.8 |
20.8 |
|
Clackamas
(99) |
70.7 |
6.1 |
32.3 |
|
Lane
(95) |
66.7 |
18.9 |
31.3 |
|
Marion
(83) |
53.7 |
12.0 |
30.1 |
|
All
Others (402) |
66.4 |
14.4 |
26.9 |
|
|
|
|
|
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].
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)
|
Group (N) |
Daily |
Weekly |
Monthly |
Less Than Monthly |
|
|
|
|
|
|
|
Total
(658) |
4.0 |
13.3 |
28.1 |
54.5 |
|
|
|
|
|
|
|
Gender [15] |
|
|
|
|
|
Boys (396) |
5.1 |
16.7 |
29.8 |
48.5 |
|
Girls (262) |
2.7 |
8.4 |
25.6 |
63.4 |
|
|
|
|
|
|
|
Age |
|
|
|
|
|
13 (89) |
3.4 |
13.5 |
18.0 |
65.2 |
|
14 (133) |
0.8 |
19.5 |
30.8 |
48.9 |
|
15 (147) |
7.5 |
12.9 |
25.9 |
53.7 |
|
16 (152) |
3.9 |
10.5 |
27.0 |
58.6 |
|
17 (137) |
3.6 |
10.9 |
35.8 |
49.6 |
|
|
|
|
|
|
|
Race |
|
|
|
|
|
Anglo (600) |
3.7 |
13.0 |
28.3 |
55.2 |
|
Non-Anglo (57) |
7.0 |
15.8 |
28.1 |
49.1 |
|
|
|
|
|
|
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)
|
Group (N) |
$0.00- $9.00 |
$10.00- $49.00 |
More Than $49.00 |
|
|
|
|
|
|
Total
(647) |
87.9 |
8.6 |
1.9 |
|
|
|
|
|
|
Gender [16] |
|
|
|
|
Boys (393) |
76.3 |
11.3 |
2.3 |
|
Girls (254) |
94.5 |
4.3 |
1.2 |
|
|
|
|
|
|
Age |
|
|
|
|
13 (84) |
91.6 |
8.3 |
0.0 |
|
14 (134) |
91.8 |
6.7 |
1.5 |
|
15 (143) |
86.1 |
11.2 |
2.8 |
|
16 (153) |
92.8 |
5.3 |
2.0 |
|
17 (136) |
84.6 |
12.5 |
2.9 |
|
|
|
|
|
|
Race |
|
|
|
|
Anglo (593) |
90.3 |
8.1 |
1.7 |
|
Non-Anglo (54) |
79.6 |
14.8 |
5.6 |
|
|
|
|
|
Table 2.11 Average
Weekly Income
(In Percent)
|
Group (N) |
$0.00- $19.00 |
$20.00- $49.00 |
$50.00- $99.00 |
More Than $99.00 |
|
|
|
|
|
|
|
Total
(609) |
36.2 |
20.2 |
13.3 |
30.3 |
|
|
|
|
|
|
|
Gender |
|
|
|
|
|
Boys (362) |
36.2 |
18.8 |
13.0 |
32.0 |
|
Girls (247) |
36.5 |
22.3 |
13.4 |
27.9 |
|
|
|
|
|
|
|
Age |
|
|
|
|
|
13 (79) |
57.0 |
34.2 |
2.5 |
6.3 |
|
14 (117) |
70.1 |
19.7 |
5.1 |
5.1 |
|
15 (135) |
37.8 |
27.4 |
14.1 |
20.7 |
|
16 (143) |
19.6 |
16.8 |
24.5 |
39.2 |
|
17 (131) |
10.7 |
7.6 |
15.3 |
66.4 |
|
|
|
|
|
|
|
Race |
|
|
|
|
|
Anglo (560) |
35.4 |
20.5 |
13.8 |
30.4 |
|
Non-Anglo (48) |
45.8 |
16.7 |
8.3 |
29.2 |
|
|
|
|
|
|
Younger gamblers are
significantly more likely to have begun gambling in grade school (compared to
junior or high school) than their older counterparts. The left-hand column in Table 2.12 reveals that only 25% of 17
year olds reported gambling in grade school compared to nearly 77% of 13 year
olds. However, many respondents did not
report a specific grade at which they began gambling--only 632 of the 757
respondents answered the question "In what age grade did you first
gamble." Several analyses were
undertaken to be sure that the differences in grade of onset weren't affected
by the missing data. The analyses of
missing data revealed that nearly all of the respondents who failed to specify
the grade in which they began gambling were those that gambled infrequently and
were primarily younger gamblers. In
order to provide a better estimate for group differences in age of onset, only
youth who reported gambling at least monthly were compared to reduce the number
of missing responses.
The right-hand column in Table 2.12
shows that when excluding infrequent gamblers, the estimated relationship
between age and grade of onset is still significant. These two analyses, taken together, strongly suggest that,
compared to their older counterparts, the youngest adolescents in the sample
began their gambling at a younger age.
Table
2.12. Grade of Onset
(In Percent)
|
Group |
Beginning in Grade School: All Gamblers (n=632) |
Beginning in Grade School: At least Monthly Gambling (n=265) |
|
|
|
|
|
Total |
43.5 |
47.5 |
|
|
|
|
|
Gender [17] |
|
|
|
Boys |
46.4 |
51.4 |
|
Girls |
38.6 |
39.0 |
|
|
|
|
|
Age [18] |
|
|
|
13 |
76.6 |
73.1 |
|
14 |
55.2 |
53.6 |
|
15 |
43.7 |
54.0 |
|
16 |
34.2 |
47.4 |
|
17 |
24.5 |
26.6 |
|
|
|
|
|
Race |
|
|
|
Anglo |
43.3 |
47.5 |
|
Non-Anglo |
44.4 |
48.1 |
|
|
|
|
Those who started gambling in grade
school are significantly more likely to gamble and are more frequent gamblers
than those who abstain until after grade school. Table 2.13 shows the significant estimated relationship between
grade of onset and frequency of gambling.
Of the 276 respondents who began gambling in grade school, slightly less
than 15% abstained from gambling in the last 12 months, compared to a little
more than 20% of those who waited until high school to begin gambling. Furthermore, slightly more than 20% of those
who began gambling in grade school do so on at least a weekly basis compared to
only 11% of those who didn't gamble in grade school.
Table
2.13. Grade of Onset and Frequency of Gambling
(In Percent)
|
Grade of Onset [19] |
Not Gambled |
Less Than Monthly or Monthly |
Weekly or Daily |
|
|
|
|
|
|
1-6
(276) |
14.5 |
65.2 |
20.3 |
|
7-8
(241) |
18.3 |
70.4 |
11.3 |
|
9-12
(116) |
19.8 |
69.0 |
11.2 |
|
|
|
|
|
It is interesting to note the
authors found an increasing age of onset for adults presenting at treatment and
indicating video poker machines as their primary choice of gambling (Moore,
T.L. and Carlson, M.J., 1998)
Previous research suggests that
children are more likely to gamble if their parents gamble (Lesieur,
forthcoming). Evidence from the current
study supports this finding. Table 2.14
shows that the children of parents who gamble are more likely to gamble. They are also likely to gamble more
frequently than children of parents who do not gamble. Children of parents who gamble are nearly
twice as likely to be weekly or daily gamblers than children whose parents do
not gamble. In analyses not shown, it
was found that older adolescents are not more likely than their younger
counterparts to have parents who gamble.
Thus, it is not likely that the relationship between parents' and
children's gambling is spurious.
Table
2.14. Youth Gambling and Parental Gambling
(In Percent)
|
Frequency of Youth Gambling [20] |
Parents Gamble (425) |
Parents Don't Gamble (559) |
|
|
|
|
|
Never |
23.0 |
41.9 |
|
Less
than monthly |
35.8 |
36.3 |
|
Monthly |
25.6 |
13.2 |
|
Weekly/Daily |
15.6 |
8.6 |
|
|
|
|
|
Total |
100.0 |
100.0 |
|
|
|
|
Not only do children of gambling
parents appear to be more likely to gamble, but they also appear to begin
gambling sooner. Table 2.15 describes
the relationship between grade on onset and parental gambling among children
who gamble at least monthly (to reduce bias associated with missing data).
Adolescents whose parents gamble
appear to be more likely to have started in grade school than children of
non-gambling parents. Conversely,
respondents who report that their parents don't gamble are more likely to
abstain from gambling until high school.
Table
2.15. Grade of Onset and Parental Gambling
(In Percent)
|
Grade of Onset [21] |
Parents Gamble (161) |
Parents Don't Gamble (101) |
|
|
|
|
|
Grades
1-6 |
52.2 |
41.6 |
|
Grades
7-8 |
36.6 |
36.6 |
|
Grades
9-12 |
11.2 |
21.8 |
|
|
|
|
|
Total |
100.0 |
100.0 |
|
|
|
|
Previous studies have suggested that
teen gambling is part of a larger set of risky behaviors including smoking,
drinking, and drug use (Westphal, 1998).
The current study indicates this is true in Oregon. Youth in this study who gambled were also
more likely to smoke, drink alcohol, and use drugs. Additionally, the frequency of youth gambling was also related to
the frequency of substance use.
Tables 2.16 and 2.17 show the
patterns of tobacco use (smoking and chewing tobacco), drinking alcohol, and
using marijuana and other drugs (including cocaine, heroin, and LSD). As expected, older youth are more likely to
use tobacco, alcohol, and other drugs.