Problem and Pathological Gambling in a Sample
of Casino Patrons
Timothy W. Fong•Michael D. Campos•Mary-Lynn Brecht•
Alice Davis•Adrienne Marco•Viviane Pecanha•Richard J. Rosenthal
Published online: 12 June 2010
? The Author(s) 2010. This article is published with open access at Springerlink.com
a casino setting. The current study sought to examine the prevalence of gambling problems
among a sample of casino patrons and examine alcohol and tobacco use, health status, and
quality of life by gambling problem status. To these ends, 176 casino patrons were
recruited by going to a Southern California casino and requesting that they complete an
anonymous survey. Results indicated the following lifetime rates for at-risk, problem, and
pathological gambling: 29.2, 10.7, and 29.8%. Differences were found with regards to
gambling behavior, and results indicated higher rates of smoking among individuals with
gambling problems, but not higher rates of alcohol use. Self-rated quality of life was lower
among pathological gamblers relative to non-problem gamblers, but did not differ from at-
risk or problem gamblers. Although subject to some limitations, our data support the notion
of higher frequency of gambling problems among casino patrons and may suggest the need
for increased interventions for gambling problems on-site at casinos.
Relatively few studies have examined gambling problems among individuals in
Pathological gambling prevalence ? Casino patrons ? Gambling behavior
Problem and Pathological Gambling in a Sample of Casino Patrons
Whereas there has been significant growth in the amount of prevalence research on
gambling problems in North America (Volberg 2004), to our knowledge, few studies have
examined the prevalence of problem and pathological gambling among patrons at gam-
bling venues. Further, the most recent study in the US using a gambling venue sample was
T. W. Fong (&) ? M. D. Campos ? A. Davis ? A. Marco ? V. Pecanha ? R. J. Rosenthal
UCLA Gambling Studies Program, David Geffen School of Medicine, Los Angeles, USA
UCLA Integrated Substance Abuse Programs, David Geffen School of Medicine, Los Angeles, USA
T. W. Fong ? M. D. Campos ? M.-L. Brecht ? A. Davis ? A. Marco ? V. Pecanha ? R. J. Rosenthal
Semel Institute for Neuroscience and Human Behavior at UCLA, 760 Westwood Plaza, Suite C8-891,
Los Angeles, CA 90095, USA
J Gambl Stud (2011) 27:35–47
reported in the late 1990s (Gerstein et al. 1999) and since that time gambling venues and
opportunities to gamble have become increasingly prevalent throughout the US.
Four studies in the literature (Fisher 2000; Gerstein et al. 1999; Oliveira and Silva 2000,
2001), all published nearly 10 years ago, have examined the prevalence of pathological
gambling among gambling venue patrons in three countries (e.g., the UK, the US, and
Brazil). In summary, these studies indicate that: (a) although more stringent methodology
yields lower estimates, the percentage of problem/pathological gambers among casino
patrons [2.2% in the UK (Fisher 2000); 7.9% in the US (Gerstein et al. 1999); and 43.5% in
Brazil (Oliveira and Silva 2000)] is elevated in these samples relative to the estimates for
pathological gambling among the North American general public (0.42–4.0%) (Gerstein
et al. 1999; Petry et al. 2005; Shaffer and Hall 2001; Shaffer et al. 1999; Stucki and Rihs-
Middel 2007; Welte et al. 2001); (b) many problem/pathological gamblers perceive
themselves to have a problem with gambling; (c) despite some recognition of problems
with gambling, very few individuals in these samples report having sought treatment for
gambling problems, which is consistent with the previous literature on treatment seeking
among individuals with gambling problems in the US (Kessler et al. 2008; Slutske 2006);
and (d) individuals with pathological gambling are more likely to have substance problems,
which is consistent with findings from other studies of gambling and substance abuse
(Cunningham-Williams et al. 1998; Grant and Potenza 2005; Petry and Oncken 2002;
Potenza et al. 2004; Welte et al. 2001; Welte et al. 2004).
In addition to substance-related disorders, previous research on gambling problems has
indicated that suicidality (Ledgerwood et al. 2005), health problems (Larimer et al. 2006;
Meyer et al. 2000), and reduced quality of life (Black et al. 2003) are common among
individuals with pathological gambling disorder. As part of our survey of casino patrons,
we assessed alcohol and tobacco use, health status, and quality of life in order to examine
differences along these dimensions by gambling problem status.
Data for the analyses presented in this paper come from a casino located in Southern
California. The casino is open 24 h a day, 7 days a week, 365 days a year. The casino is
open to the public, with no membership requirements. Data were collected with the
knowledge and authorization of the casino management. The casino offers only un-banked
table games with cards.
Data from gambling venues in the US are of interest because documenting high
prevalence rates of pathological or problem gambling among casino patrons would argue
for the systematic implementation of primary, secondary, or tertiary prevention approaches
in gambling settings (e.g., training casino employees to identify problem/pathological
gamblers, providing information regarding problem/pathological gambling to patrons, and
implementing formal treatment referral procedures for identified problem/pathological
gamblers). Alternatively, equal prevalence of problem or pathological gambling among
casino patrons relative to individuals in other settings would suggest that settings other
than casinos (e.g., bankruptcy courts, substance abuse treatment programs, etc.) may be
better locations for prevention and treatment outreach programs for gambling problems.
Based on prior work, our primary hypotheses were that rates of problem and patho-
logical gambling would be higher among casino patrons relative to rates for these disorders
found in general population samples; individuals with gambling problems would report
more tobacco and alcohol use; and, individuals with gambling problems would report
lower ratings for health and quality of life. Our primary focus on the prevalence of
gambling problems among casino patrons provides data bearing on the potential need for
casino-based problem gambling interventions. Our analyses of substance use, self-reported
health, and quality of life provide some context for our data on gambling problem
36 J Gambl Stud (2011) 27:35–47
frequency by examining commonly co-occurring problems which are important in the
treatment of gambling problems.
Participants and Procedures
The current analyses are based on a total of 178 individuals surveyed inside a Southern
California casino. The mean age for the sample was 37 (SD = 12.6). Roughly 78% of
participants were male, 40% were Asian Pacific Islander, 28.5% were Latino/a, and 31.5%
were White. Over 80% had at least some college education, and 38% were married.
Seventy percent were employed and nearly 45% had an income range between 25 and 50
thousand per year. Table 1 presents sample demographics and background characteristics.
Prior to data collection, all instruments and procedures were approved by the UCLA
General Campus Institutional Review Board. In order to obtain study participants, research
M (SD) or N (%) for sample demographics and background characteristics by problem gambling
NPGAR PrG PaG
N (%)54 (30.3) 52 (29.2)19 (10.7)53 (29.8)
Age 36.6 (13.3)36.7 (13.5) 41.8 (14.9) 39.3 (13.3)
Male33 (61.1) 43 (82.7)17 (89.5) 47 (88.7)
Female21 (38.9) 9 (17.3)2 (10.5) 6 (11.3)
API 20 (37.0) 15 (28.8)9 (47.4) 29 (54.7)
Latino/a 17 (31.5)14 (26.9)8 (42.1) 11 (20.8)
White17 (31.5) 23 (44.2)2 (10.5) 13 (24.5)
H.S. or less9 (16.7) 9 (17.3)0 (0.0)9 (17.0)
Some College16 (29.6)24 (46.2)10 (52.6) 23 (43.4)
College Grad 29 (53.7)19 (36.5) 9 (47.4)21 (39.6)
Married 23 (42.6) 20 (38.5) 10 (52.6)17 (32.1)
Unmarried 31 (57.4) 32 (61.5) 9 (47.4)36 (67.9)
Employed full time42 (77.8) 34 (65.4)13 (68.4) 37 (69.8)
Income range (in thousands)
0–$25 10 (19.2) 12 (23.1)3 (15.8) 12 (23.5)
$25–50 25 (48.1)23 (44.2) 10 (52.6) 20 (39.2)
12 (23.1)11 (21.2) 5 (26.3) 14 (27.5)
5 (9.6) 6 (11.5)1 (5.3) 5 (9.8)
Groupings for table based on NODS score
Ns differ due to missing data
NPG non-problem gamblers, AR at-risk gamblers, PrG problem gamblers, PaG pathological gamblers
* p\0.05; ** p\0.01
J Gambl Stud (2011) 27:35–4737
staff went to a casino in Southern California and set up a table in the casino with a sign
reading ‘‘gamblers wanted to fill out a survey’’. Data were collected in eight-hour blocks
spanning all hours of the day across three business days (Monday, Tuesday, and
Wednesday). After providing informed consent, participants completed a study question-
naire. Although basic demographics were collected, no identifying information was
included on the questionnaire in order to maintain anonymity. Participants were given a
five dollar gift card for a coffee house in compensation for their time. Thus our sample is
one of convenience, rather than one systematically selected.
UCLA Gambling Survey
A 19-item self-report survey was administered that included questions on demographics,
country of origin, gambling related behaviors (e.g., age first gambled, typical frequency of
gambling, reasons for gambling, days gambled in the last 30, money spent on gambling in
the last 30 days), family history of gambling problems, cigarettes smoked per day, drinks
per week, health, and quality of life. Questionnaire items were chosen to balance com-
prehensiveness with the amount of time necessary for instrument completion. Items were
analyzed individually, with no composite scores generated from these data.
South Oaks Gambling Screen (SOGS)
The SOGS (Lesieur and Blume 1987) consists of 20 scored items and four un-scored items
assessing gambling-related behavior. In our study, we used only the items assessing types
of gambling (e.g., cards, betting on animal races, slot machines, etc.) and one item
assessing whether or not respondents felt that they had ever had a gambling problem. Items
assessing types of gambling could be endorsed as either ‘not at all’ (scored 0), ‘less than
once a week’ (scored 1), or ‘once a week or more’ (scored 2). The gambling problem item
was assessed as ‘Yes’ or ‘No’.
NORC DSM-IV Screen for Gambling Problems (NODS)
Questions from the 17-Item NORC DSM-IV Screen for Gambling Problems (Gerstein
et al. 1999), for which good psychometric properties have been established, were adapted
for self-report administration, resulting in a 10-item, yes–no response format, screening
questionnaire for problem and pathological gambling. The 10-items correspond with DSM-
IV criteria for pathological gambling. Internal consistency for our adapted version of the
NODS was excellent for this sample (Cronbach’s alpha = 0.90). Based on the work of
Gerstein et al. (1999), the following taxonomy was used to categorize respondents:
0 = non-problem gamblers; 1 or 2 = at-risk gamblers; 3 or 4 = problem gamblers; and
individuals scoring 5 or more were considered pathological gamblers.
Reasons for Gambling
An open-ended question asked respondents to write in their reason for gambling. These
answers were manually reviewed and categorized by the second author (MDC), then
reviewed by the first author (TWF). Results of this categorization indicated that the majority
38 J Gambl Stud (2011) 27:35–47
of responses (126 of 141 responses) could be categorized as either gambling to make money
or gambling for fun/pleasure. A single, dichotomous variable was created using these 126
responses. A value of 1 was coded as ‘gambling for money’ and a value of 2 was coded for
‘gambling for fun/pleasure’. Other responses were not coded due to low frequency.
One item asked respondents ‘how many drinks they have per week’. Possible responses
were ‘none at all’, ‘1–5’, ‘6–10’, ‘11–15’, and ‘more than 15’.
One item asked respondents ‘how much they smoked per day’. Possible responses were
‘don’t smoke’, ‘less than 10 cigarettes’, ‘10 cigarettes’, or ‘more than 20 cigarettes’. Due to
a typo, the third category was listed on the instrument as ‘10 cigarettes’.
One item, phrased ‘How would you rate your health?’, was used to operationalize health
status. This item was scored on a 5-point Likert-type scale ranging from 1 (poor) to 5
Missing data were dealt with in two ways. First, in the case where an individual had
missing items for the NODS, we multiplied the total score for all present items by the
following formula: 1 ? (items endorsed positive/number of items endorsed). In cases
where the entire scale was missing (n = 2), we dropped those cases from analysis.
We first obtained the unweighted percentage of individuals in our sample who scored in the
non-problem, at-risk, problem, and pathological gambling range. In order to test for differ-
ences in demographics, background characteristics, tobacco use, alcohol use, self-reported
we conducted v2analyses for categorical variables, Kruskal–Wallis tests for ordinal vari-
ables, and t tests or one-way ANOVAs with post-hoc Tukey tests for continuous variables.
Prevalence of Gambling Problems Among Casino Patrons
Using the NODS as our measure of gambling problem severity, we found that 54 (30.3%)
of respondents were non-problem gamblers, 52 (29.2%) were at-risk gamblers, 19 (10.7%)
were problem gamblers, and 53 (29.8%) were pathological gamblers. Thus, just over 40%
J Gambl Stud (2011) 27:35–4739
of our sample of casino patrons reported experiencing at least 3 serious gambling-related
symptoms in their lifetime.
Analyses of demographic and background characteristics indicated that at-risk, prob-
lem, and pathological gambling were more frequent among males (v2
and that pathological gambling was more frequent among individuals of Asian Pacific
Islander descent (v2
income were unrelated to the frequency of problem or pathological gambling in this sample
(see Table 1). The groups did not differ in age.
½3?¼ 14:9, p\0.01)
½6?¼ 13:5, p\0.05). Education, marital status, employment status, and
Pathological gamblers were more likely to have had a family member with a history of
problem gambling (v2
vious month ðv2
30 days (v2
money rather than for fun or pleasure (v2
pathological gamblers were younger at age of first gambling experience, the age difference
was not significant. Fully 73.6% (n = 39) of those classified as pathological gamblers
reported that they have (or have ever had) a gambling problem (v2
whereas 15.4% (n = 8) and 26.3% (n = 5) of at-risk or problem gamblers reported that
they have (or have ever had) a gambling problem. These data are presented in Table 2.
With regards to specific gambling activities, results of Kruskal–Wallis tests indicated that
individuals with pathological gambling were more likely to report frequently playing cards
for money (p\0.01), betting on animals (p\0.05), sports betting (p\0.01), going to a
casino (p\0.01), and playing lotto/numbers (p\0.01).
½3?¼ 20:1, p\0.01), to have gambled 10 or more days in the pre-
½3?¼ 17:0, p\0.01), to have gambled more than $400.00 in the previous
½3?¼ 33:7, p\0.01), and were more likely to report that they gambled to make
½3?¼ 25:3, p\0.01). Although problem and
½3?¼ 77:6, p\0.01);
Alcohol and Tobacco Use
Results for the tobacco use and alcohol use variable analyses are presented in Table 3.
Although there was no difference with regards to level of alcohol use between groups,
pathological gamblers reported smoking more cigarettes per day relative to other groups as
tested using a Kruskal–Wallis test (p = 0.02). Moreover, self-identified smokers had
significantly higher mean NODS scores than those who reported not smoking [M = 3.9,
(SD = 3.5) vs. M = 2.5, (SD = 3.0); t[77.7]= -2.5, p\0.05].
Self-Rated Health and Quality of Life
Self-rated health and quality of life data are presented in Table 3. There was a trend for
lower self-rated health among pathological gamblers (F[2,175]= 3.9, p\0.06) relative to
non-problem gamblers. Self-rated quality of life was lower among pathological gamblers
relative to non-problem gamblers (F[3,174]= 4.1, p\0.01), but did not differ between at-
risk, problem, and pathological gamblers.
A number of large scale epidemiological studies have been conducted internationally and
in the US to determine the prevalence of problem/pathological gambling in the general
40J Gambl Stud (2011) 27:35–47
population; however, less work has examined the prevalence of pathological gambling
among gambling venue patrons. The current study, using data from a sample of individuals
surveyed in a casino setting, sought to determine the frequency of gambling problems in a
sample of gambling venue patrons. Further, the current study sought to examine alcohol
and tobacco use, health status, and quality of life differences by gambling problem status in
Based on prior work, our primary hypotheses were as follows: (a) rates of problem and
pathological gambling would be higher among casino patrons relative to rates for these
disorders found in general population samples; (b) individuals with gambling problems
would report higher quantities of tobacco and alcohol use; (c) individuals with gambling
problems would report lower ratings for health and quality of life.
Prevalence of Gambling Problems
The results of our analyses supported our first hypothesis related to increased rates of
gambling problems among casino patrons relative to the general public. Based on the
NODS score classification described above, 30.3% of respondents were non-problem
gamblers, 10.7% were problem gamblers, 29.2% were at-risk gamblers, and 29.8% were
Table 2 Mean (SD) or N (%) for gambling-related variables by problem gambling status
NODS score0.0 (0.0) 1.3 (0.5) 3.4 (0.5)7.3 (1.6)
Age first gambled 22.7 (9.5)20.2 (8.4) 18.9 (9.8)18.9 (8.3)
Family Hx of PG**16 (29.6) 17 (32.7)10 (52.6) 36 (67.9)
Days gambled (Last month)**
0 days 26 (49.1) 12 (23.5)3 (16.7) 0 (0.0)
1–10 days23 (43.4) 30 (58.8)11 (61.1) 33 (61.1)
10–20 days 3 (5.7) 4 (7.8) 2 (11.1)15 (27.8)
Gambled[$400 (Last month)**
1 (1.9)5 (9.8) 2 (11.1)6 (11.1)
36 (70.6) 22 (43.1)5 (27.8) 5 (9.3)
100–200 6 (11.8)12 (23.5)5 (27.8) 6 (11.1)
200–3003 (5.9) 7 (13.7) 2 (11.1) 5 (9.3)
Reason for gambling**
1 (2.0) 2 (3.9) 0 (0.0) 8 (14.8)
5 (9.8) 8 (15.7)6 (3.4) 30 (55.6)
To make money 2 (5.7)14 (31.1) 3 (25.0) 21 (61.8)
For fun/pleasure 33 (94.3)31 (68.9) 9 (75.0)13 (38.2)
Ever had a gambling problem**
No54 (100)44 (84.6) 14 (73.7) 14 (26.4)
Yes 0 (0) 8 (15.4)5 (26.3) 39 (73.6)
Groupings for table based on NODS score
Ns differ due to missing data
Mean with different superscripts significantly different by post hoc Tukey test
NPG non-problem gamblers, AR at-risk gamblers, PrG problem gamblers, PaG pathological gamblers
J Gambl Stud (2011) 27:35–47 41
pathological gamblers. The NODS questions assessed lifetime gambling-related problems,
therefore, these categories reflect lifetime rates of gambling disorders and not necessarily
frequency of current gambling disorders.
The prevalence rates obtained in our sample were higher than those obtained in a
nationwide casino sample (Gerstein et al. 1999) and in a study of casino patrons in the UK
(Fisher 2000). Gerstein and associates found that nationwide, 17.9% of casino patrons were
at-risk gamblers, 5.3% were problem gamblers, and 7.9% were pathological gamblers.
Fisher (2000) and Gerstein et al. (1999) present weighted prevalence estimates that con-
trolled for the likelihood of being sampled. We did not weight our prevalence estimates
because we had no measure of the frequency of casino attendance. Had we weighted our
data we may have obtained lower rates of pathological gambling than those we observed
using un-weighted data.
Conversely, the rate of pathological gamblers found in the current study was lower than
that obtained in a study of problem/pathological gambling done in Brazil (43.5%) (Oliveira
and Silva 2000). Oliveira and Silva (2000, 2001) used the SOGS scores to classify path-
ological gamblers and found a higher rate of probable pathological gamblers than we found
in our data. In the current study, we employed the NODS, which has been shown to more
strictly define gambling problems (Hodgins 2004); further, the SOGS has been shown to
have good agreement with DSM-IV criteria for pathological gambling, but may overes-
timate gambling problems in non-clinical, general population samples (Stinchfield 2002).
The obtained high rate of pathological gambling in our study may be due to the fact that
we had a primarily male sample (78.7% male), and that our sample was primarily non-
Caucasian (69.1%). Male gender and non-Caucasian ethnicity have been associated with
higher rates of problem gambling (Fisher 2000; Gerstein et al. 1999; Volberg 1996).
Table 3 Mean (SD) or N (%) health-related variables by problem gambling status
NPG ARPrG PaG
Do not smoke
43 (81.1)38 (73.1)15 (83.3) 31 (57.4)
7 (13.0) 7 (13.2)3 (5.8)1 (5.6)
0 (0.0) 7 (13.5)0 (0.0)6 (11.1)
3 (5.7)4 (7.7)2 (11.1)10 (18.5)
None at all27 (50.0)27 (51.9) 7 (38.9)19 (35.2)
1–5 Drinks23 (42.6) 19 (36.5) 8 (44.4)28 (51.9)
6–10 Drinks 1 (1.9) 2 (3.8) 2 (11.1)6 (11.1)
11–15 Drinks 2 (3.7) 3 (5.8)0 (0.0) 0 (0.0)
1 (1.9)1 (1.9)1 (5.6) 1 (1.9)
Self-rated quality of life**
Groupings for table based on NODS score
Ns differ due to missing data
Means with different superscripts significantly different by post-hoc Tukey test
NPG non-problem gamblers, AR at-risk gamblers, PrG problem gamblers, PaG probable pathological
?p\0.10; * p\0.05; ** p\0.01
42 J Gambl Stud (2011) 27:35–47
Although in our sample we found that problem gamblers were more likely to be male, just
under 16% of women surveyed in this study were pathological gamblers.
Relative to non-problem gamblers, a greater number of pathological gamblers showed
heavy current gambling involvement as indicated by gambling 10 or more days in the last
30 and gambling greater than $400.00 in the last month. The majority of pathological
gamblers (61.8%) reported that they gambled to make money.
In the current sample, pathological gamblers were more likely to report ‘action’ oriented
game play (e.g., cards, betting on animals, betting on sports), with the exception that they
also reported increased frequency of lottery play. This may be due to the nature of the
casino from which data were collected. The casino offers only card games, therefore, it
likely attracts those individuals with a primary interest in more action oriented games. Our
sample may have a bias towards action oriented gamblers for this reason.
Alcohol and Tobacco Use
Our hypotheses regarding alcohol and tobacco use were partially supported. Somewhat
consistent with other studies, we found that pathological gamblers smoked more cigarettes
per day than non-pathological gamblers (Cunningham-Williams et al. 1998; Grant and
Potenza 2005; Petry and Oncken 2002; Potenza et al. 2004). We also found that smokers
had higher NODS scores relative to non-smokers, which is consistent with the report of
more severe gambling pathology among pathological gamblers who smoke (Petry and
Oncken 2002). Unlike past work, we did not find a relationship between alcohol use and
pathological gambling (Cunningham-Williams et al. 1998; Welte et al. 2001; Welte et al.
2004). The failure to find an association between alcohol use and pathological gambling
may be a result of our alcohol use measurement method. Had we employed alcohol abuse
or dependence diagnoses, we may have detected a relationship between pathological
gambling and alcohol abuse/dependence.
Health and Quality of Life
We hypothesized that individuals with gambling problems would report worse health than
non-problem gambling casino patrons and that individuals with gambling problems would
report reduced quality of life relative to non-problem gambling casino patrons. In the case
of self-reported health, our hypothesis was not supported. Although pathological gamblers
reported lower self-rated health than non-pathological gamblers, the difference was not
statistically significant beyond the trend level. But, for self-reported quality of life, our
hypothesis was supported. Pathological gamblers reported lower quality of life than non-
pathological gamblers. Mean self-reported quality of life scores for the at-risk and problem
gambling groups were higher than those reported by the pathological gambling group, but
lower than those reported by the non-problem gambling group.
Evidence from our data suggest that individuals with gambling problems were aware of
family histories of gambling problems and may have insight into their own gambling
J Gambl Stud (2011) 27:35–4743
problems. Significantly more individuals with gambling problems reported that someone in
their family had or has a gambling problem. Approximately 84% of individuals who
reported 3 or more gambling-related problems as assessed by the NODS indicated that they
felt that they either had or currently have a gambling problem.
Despite the fact that a high percentage of individuals who reported 3 or more gambling-
related problems also indicated that they felt they may have a gambling problem, it is
unlikely that these individuals have sought or will seek treatment. In the US lifetime
treatment seeking among individuals with pathological gambling (PG) disorder is low
(Kessler et al. 2008; Slutske 2006) as compared with psychiatric disorders such as sub-
stance-related disorders and major depression (Kessler et al. 1998). Slutske (2006) com-
pared rates of treatment seeking among individuals with PG surveyed as part of two
national studies: the Gambling Impact and Behavior Study (GIBS) and the National
Epidemiologic Survey on Alcohol and Related Conditions (NESARC). In the GIBS data
only 7.1% of the lifetime pathological gamblers reported seeking professional treatment or
participation in self-help groups. In the NESARC data only 9.9% of the lifetime patho-
logical gamblers sought professional treatment or had attended at least one Gamblers
Anonymous meeting. Kessler et al. (2008), in an analysis of data from the National
Comorbidity Survey Replication (NCS-R), found that of study participants meeting life-
time criteria for PG, none reported seeking treatment specifically for gambling problems;
however, 49% of those with a lifetime diagnosis of PG reported treatment for substance
disorders or emotional problems at any point in their life. Comparatively, for addictive
disorders and major depression, roughly 50 and 70%, respectively, make treatment contact
with a physician, mental health professional, or other professional over their lifetime
(Kessler et al. 1998).
Among reasons such as embarrassment regarding gambling behavior, denial of a
gambling problem, social stigma, and concerns about the effectiveness of treatment, the
simple lack of available services has been cited as a barrier to PG treatment utilization
(Rockloff and Schofield 2004).
In order to increase awareness of gambling treatment availability, effectiveness, and
utilization, casino-based interventions for gambling problems may be necessary. Such
interventions could include posting information about available treatment services,
formalized screening, identification, and referral procedures for individuals with gam-
bling problems in casino settings, and/or gambling problem screening kiosks at key
locations within a casino. The incorporation of curricula on the recognition of the signs
and symptoms of problem gambling into standard training practices for casino staff,
coupled with a formal procedure to refer interested individuals to gambling treatment
services could also be implemented. Our examination of alcohol and tobacco use, health
status, and quality of life suggest that interventions for smoking cessation and
improving quality of life are needs identified among casino patrons with gambling
Study Strengths and Limitations
The current research may be characterized as having a number of strengths. First, the data
come from a ‘real-world’ casino setting rather than in a laboratory setting, or a college
population. Second, we employed a three-day round-the-clock sampling method that
increased the likelihood that individuals with varying gambling patterns would be sampled.
Third, we employed a purpose-built measure, the NODS, in order to assess for pathological
gambling. The NODS was designed specifically to operationalize pathological gambling
44 J Gambl Stud (2011) 27:35–47
criteria for community based studies. Finally, all data were collected anonymously, which
may have increased the likelihood that respondents would provide accurate and reliable
information regarding gambling and associated behaviors.
Findings from the current study must be considered in light of a number of limitations.
First, we present data gathered primarily as a convenience sample from a single Los
Angeles County casino. Systematic bias may have been introduced in our sample as a
result of specific aspects of the casino from which data were sampled, by lack of selection
criteria for inclusion in the study, or participant characteristics which may be related to
choosing to participate in research surveys. A second limitation was the fact that our data
are entirely self-report and may be subject to recall bias, social desirability bias, and other
distortions. Finally, the study was limited by the fact that we did not use DSM-based
measures for substance disorders in our survey and used single-item quality of life and
health status measures. More refined measurement techniques would have allowed for
more detailed analysis of group differences within these domains.
Summary and Conclusions
In the current study of casino patrons, we found higher rates of pathological gambling
relative to some previous work (Fisher 2000; Gerstein et al. 1999), but lower rates than
work conducted in Brazilian gambling venues (Oliveira and Silva 2000, 2001). Gambling
related variables were significantly different in that pathological gamblers were more likely
to report a family history of gambling problems, to report more frequent gambling with
larger sums of money, to report engaging in sports betting and skilled gambling, and to
report gambling to make money. A high percentage of pathological gamblers acknowl-
edged having a gambling problem. Individuals with gambling problems reported more
smoking, but not more drinking. Pathological gamblers reported lower quality of life,
which may be due in part to a trend for lower self-reported health.
The larger implications of our findings are that, given the potentially high rate of
gambling problems among casino patrons, there is a need for formal prevention and
intervention measures in casino settings. More data from casino samples may be helpful for
state and county policy makers in that they provide information upon which ‘evidence-
based’ legislation regarding gambling regulations and controls could be based. Legislators
may serve the public interest and prevent untoward consequences resulting from gambling
problems by supporting the implementation of primary, secondary, and tertiary prevention
efforts in casino settings. The current study––as well as the studies mentioned in our
review of the literature––have identified a high frequency of gambling-related problems
among casino patrons. Such problems are associated with poor health, substance use,
reduced quality of life, psychopathology, and family/social problems. Carefully designed
prevention and treatment programs that account for the significant comorbidity present
among individuals with problem/pathological gambling disorders are needed. These pro-
grams, at minimum, should cooperate with gambling venues by providing training in
recognition of gambling problems among patrons, providing casinos with information to
provide treatment referrals for patrons with gambling problems.
National Institute on Drug Abuse (Grant #: K23DA19522-2).
This work was supported by funding from The Annenberg Foundation and the
mercial License which permits any noncommercial use, distribution, and reproduction in any medium,
provided the original author(s) and source are credited.
This article is distributed under the terms of the Creative Commons Attribution Noncom-
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