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A Comparison of Gambling Behavior, Problem Gambling Indices, and Reasons for Gambling Among Smokers and Nonsmokers Who Gamble: Evidence from a Provincial Gambling Prevalence Study

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Abstract

Numerous epidemiological and clinical studies have found that tobacco use and gambling frequently cooccur. Despite high rates of smoking among regular gamblers, the extent to which tobacco potentially influences gambling behavior and vice versa is poorly understood. The current study aimed to provide more insight into this relationship by directly comparing nonsmoking and smoking gamblers on gambling behavior, problem gambling indices, and reasons for gambling. The data for this study came from the 2005 Newfoundland and Labrador Gambling Prevalence Study. Gamblers identified as nonsmokers (N = 997) were compared with gamblers who smoke (N = 622) on numerous gambling-related variables. Chi-square analyses were used to compare groups on demographic variables. Associations between smoking status and gambling criteria were assessed with a series of binary logistic regressions. The regression analyses revealed several significant associations between smoking status and past 12-month gambling. Higher problem gambling severity scores, use of alcohol/drugs while gambling, amount of money spent gambling, use of video lottery terminals, and reasons for gambling which focused on positive reinforcement/reward and negative reinforcement/relief were all associated with smoking. The findings suggest an association between smoking and potentially problematic gambling in a population-based sample. More research focused on the potential reinforcing properties of tobacco on the development and treatment of problematic gambling is needed.
Nicotine & Tobacco Research
1
doi: 10.1093/ntr/ntr294
© The Author 2012. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.
All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Introduction
A sizable body of evidence suggests that tobacco use often cooccurs
with problem gambling ( McGrath & Barrett, 2009 ; Petry,
2007 ) with smoking prevalence rates ranging from 41% ( Smart &
Ferris, 1996 ) to 60% ( Cunningham-Williams, Cottler, Compton, &
Spitznagel, 1998 ; Lorains, Cowlishaw, & Thomas, 2011 ) among
problem gamblers. In particular, epidemiological studies indi-
cate that tobacco dependence is frequently associated with prob-
lem gambling. Indeed, one investigation found that tobacco
dependence (60%) is second only to alcohol dependence (73%)
as the most prevalent substance use disorder that is comorbid
with problem gambling ( Petry, Stinson, & Grant, 2005 ). In
addition, recent epidemiological evidence also indicates that ciga-
rette smokers are three times more likely to be problem gam-
blers than nonsmokers ( Griffi ths, Wardle, Orford, Sproston, &
Erens, 2010 ). Despite the substantial degree of cooccurrence
between smoking and gambling disorders, little research has
focused on disentangling the exact dynamics of the smoking
gambling relationship.
Beyond prevalence rates, relatively few studies have directly
compared smoking and nonsmoking gamblers. Each study that
has done so focused on problem gamblers seeking treatment for
their gambling. Their fi ndings suggest that problem gamblers
who smoke have higher problem gambling severity scores ( Grant,
Kim, Odlaug, & Potenza, 2008 ; Petry & Oncken, 2002 ), experi-
ence more psychiatric symptoms ( Grant et al., 2008 ; Petry &
Oncken, 2002 ; Potenza et al., 2004 ), are more likely to have other
substance use disorders ( Petry & Oncken, 2002 ; Potenza et al.,
2004 ), report stronger urges/cravings to gamble ( Grant & Potenza,
2005 ; Petry & Oncken, 2002 ), spend more time gambling ( Petry &
Oncken, 2002 ), spend/lose more money gambling ( Grant et al.,
Abstract
Introduction: Numerous epidemiological and clinical studies
have found that tobacco use and gambling frequently cooccur.
Despite high rates of smoking among regular gamblers, the
extent to which tobacco potentially infl uences gambling behavior
and vice versa is poorly understood. The current study aimed to
provide more insight into this relationship by directly compar-
ing nonsmoking and smoking gamblers on gambling behavior,
problem gambling indices, and reasons for gambling.
Methods: The data for this study came from the 2005
Newfoundland and Labrador Gambling Prevalence Study.
Gamblers identifi ed as nonsmokers ( N = 997) were compared
with gamblers who smoke ( N = 622) on numerous gambling-
related variables. Chi-square analyses were used to compare groups
on demographic variables. Associations between smoking status
and gambling criteria were assessed with a series of binary logistic
regressions.
Results: The regression analyses revealed several significant
associations between smoking status and past 12-month
gambling. Higher problem gambling severity scores, use of
alcohol/drugs while gambling, amount of money spent gam-
bling, use of video lottery terminals, and reasons for gambling
which focused on positive reinforcement/reward and negative
reinforcement/relief were all associated with smoking.
Conclusions: The findings suggest an association between
smoking and potentially problematic gambling in a population-
based sample. More research focused on the potential reinforc-
ing properties of tobacco on the development and treatment of
problematic gambling is needed.
Original Investigation
A Comparison of Gambling Behavior,
Problem Gambling Indices, and Reasons
for Gambling Among Smokers and
Nonsmokers Who Gamble: Evidence
from a Provincial Gambling Prevalence
Study
Daniel S. McGrath , Ph.D. , 1 Sean P. Barrett , Ph.D. , 1 , 2 Sherry H. Stewart , Ph.D. , 1 , 2 & Pauwlina R. McGrath , B.Sc. (Pharm) 3
1 Department of Psychology, Life Sciences Centre, Dalhousie University, Halifax, Nova Scotia, Canada
2 Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
3 College of Pharmacy, Dalhousie University, Halifax, Nova Scotia, Canada
Corresponding Author : Sean P. Barrett, Ph.D., Department of Psychology, Dalhousie University, Life Sciences Centre, 1355 Oxford Street,
Halifax, Nova Scotia, Canada B3H 4R2. Telephone: 902-494-2956; Fax: 902-494-6585; E-mail: sean.barrett@dal.ca
Received July 8 , 2011 ; accepted November 10 , 2011
doi:10.1093/ntr/ntr294
Advance Access Published on January 16, 2012
© e Author 2012. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.
All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Nicotine & Tobacco Research, Volume 14, Number 7 (July 2012) 833839
833
at Dalhousie University on July 25, 2012http://ntr.oxfordjournals.org/Downloaded from
Smoking and gambling
2
Smoking and gambling
2008 ; Petry & Oncken, 2002 ), experience more fi nancial problems
( Grant et al., 2008 ; Potenza et al., 2004 ), and more often choose
nonstrategic/riskier forms of gambling such as electronic gam-
ing ( Grant et al., 2008 ; Potenza et al., 2004 ). The aggregate of
these studies indicates that tobacco use is associated with a host
of psychosocial diffi culties among problem gamblers.
To date, however, no known studies have specifi cally addressed
tobacco use within a general population sample which encom-
passes the entire continuum of gamblers (i.e., from non-problem
to severe problem gamblers). Outside of clinical samples, much
remains unknown regarding how smoking and nonsmoking
gamblers might potentially differ in their gambling behavior or
level of risk for problematic gambling. In addition, an increas-
ing emphasis in the gambling literature has been placed on
identifying underlying reasons or motives for gambling as
a means for differentiating gambler subtypes ( Milosevic &
Ledgerwood, 2010 ; Neighbors, Lostutter, Cronce, & Larimer,
2002 ). Studies on motives for drinking (e.g., Cooper, 1994 ) and
gambling (e.g., Stewart & Zack, 2008 ) indicate that both posi-
tive and negative reinforcement processes underlie motivation
to drink or gamble. Other research suggests that smokers may
also be driven to smoke by similar underlying motives ( Battista
et al., 2008 ; Pomerleau, Fagerström, Marks, Tate, & Pomerleau,
2003 ). However, no known research has acknowledged potential
differences between smokers and nonsmokers in their reasons
for gambling. Identifying potential patterns in gambling in-
volvement, problem gambling risk, and motivation for gam-
bling among smokers may have implications for the prevention
and treatment of problem gambling in this population.
In the current investigation, we attempted to address impor-
tant gaps in the existing literature on tobacco use and gambling.
Specifi cally we explored differences in gambling behavior, problem
gambling indices, and reasons for gambling among gamblers
who are smokers and nonsmokers in a representative Canadian
population-based sample. In line with previous clinical and
epidemiological evidence (e.g., Grant et al., 2008 ; Petry & Oncken,
2002 ; Potenza et al., 2004 ), we hypothesized that smoking among
gamblers would be associated with ( a ) greater gambling
involvement, ( b ) higher problem gambling severity scores, and
( c ) participation in riskier forms of gambling (e.g., electronic
gaming). Based on previous motives research (e.g., Battista et al.,
2008 ; Stewart & Zack, 2008 ), it was also predicted that tobacco
use would be associated with ( d ) reasons for gambling that
either increase positive affect or decrease negative affect.
Methods
The sample in this report was compiled from the 2005
Newfoundland and Labrador Gambling Prevalence Study ( Market
Quest Research Group, 2005 ). The questionnaire consisted of
65 questions organized into four major sections: demographic
variables, gambling involvement (including reasons for gam-
bling), problem gambling behavior and adverse consequences,
and correlates of gambling. Data were collected province-wide
via telephone between September 7 and October 20, 2005. All
respondents were 19 years or older. The sample included 2,154
respondents who reported gambling during the past 12 months
with smoking status data available for 1,619 gamblers (only these
respondents were included in our analyses). Sampling was strat-
ifi ed by gender and region but was otherwise random. The total
response rate was unavailable. A demographic comparison of
smokers ( N = 622) and nonsmokers ( N = 997) is provided in
Table 1 .
Respondents were asked several questions regarding their
gambling involvement and behavior during the past 12 months.
These included: types of gambling activities they had participated
in, total number of activities participated in, and total dollar
amount spent gambling. In the present investigation, amount
spent gambling underwent a square root transformation as a
result of a non-normal distribution and the presence of outliers.
Table 1. Chi-Square Analyses for Demographic Characteristics of Nonsmokers Versus
Smokers
Demographic characteristic Nonsmokers ( N = 997) Smokers ( N = 622) χ 2 df p value
Gender: n (%) 0.63 1 0.44
Male 496 (49.7) 322 (51.8)
Female 501 (50.3) 300 (48.2)
Age group: n (%) 97.26 3 0.01*
19 – 34 years 188 (18.9) 206 (33.1)
35 – 54 years 459 (46.0) 321 (51.6)
55 – 64 years 168 (16.9) 64 (10.3)
65+ years 182 (18.3) 31 (5.0)
Marital status: n (%) 48.82 2 0.01*
Married/common law 796 (80.0) 418 (67.4)
Widowed/separated/divorced 114 (11.5) 76 (12.3)
Single 85 (8.5) 126 (20.3)
Household income: n (%) 8.65 3 0.03*
$20,000 or less 96 (13.1) 69 (14.3)
$20,001 to $40,000 240 (32.7) 191 (39.5)
$40,001 to $80,000 276 (37.6) 163 (33.7)
$80,000 or more 123 (16.6) 61 (12.5)
Note . * p .05 .
834
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Nicotine & Tobacco Research, Volume 14, Number 7 (July 2012)
2
Smoking and gambling
2008 ; Petry & Oncken, 2002 ), experience more fi nancial problems
( Grant et al., 2008 ; Potenza et al., 2004 ), and more often choose
nonstrategic/riskier forms of gambling such as electronic gam-
ing ( Grant et al., 2008 ; Potenza et al., 2004 ). The aggregate of
these studies indicates that tobacco use is associated with a host
of psychosocial diffi culties among problem gamblers.
To date, however, no known studies have specifi cally addressed
tobacco use within a general population sample which encom-
passes the entire continuum of gamblers (i.e., from non-problem
to severe problem gamblers). Outside of clinical samples, much
remains unknown regarding how smoking and nonsmoking
gamblers might potentially differ in their gambling behavior or
level of risk for problematic gambling. In addition, an increas-
ing emphasis in the gambling literature has been placed on
identifying underlying reasons or motives for gambling as
a means for differentiating gambler subtypes ( Milosevic &
Ledgerwood, 2010 ; Neighbors, Lostutter, Cronce, & Larimer,
2002 ). Studies on motives for drinking (e.g., Cooper, 1994 ) and
gambling (e.g., Stewart & Zack, 2008 ) indicate that both posi-
tive and negative reinforcement processes underlie motivation
to drink or gamble. Other research suggests that smokers may
also be driven to smoke by similar underlying motives ( Battista
et al., 2008 ; Pomerleau, Fagerström, Marks, Tate, & Pomerleau,
2003 ). However, no known research has acknowledged potential
differences between smokers and nonsmokers in their reasons
for gambling. Identifying potential patterns in gambling in-
volvement, problem gambling risk, and motivation for gam-
bling among smokers may have implications for the prevention
and treatment of problem gambling in this population.
In the current investigation, we attempted to address impor-
tant gaps in the existing literature on tobacco use and gambling.
Specifi cally we explored differences in gambling behavior, problem
gambling indices, and reasons for gambling among gamblers
who are smokers and nonsmokers in a representative Canadian
population-based sample. In line with previous clinical and
epidemiological evidence (e.g., Grant et al., 2008 ; Petry & Oncken,
2002 ; Potenza et al., 2004 ), we hypothesized that smoking among
gamblers would be associated with ( a ) greater gambling
involvement, ( b ) higher problem gambling severity scores, and
( c ) participation in riskier forms of gambling (e.g., electronic
gaming). Based on previous motives research (e.g., Battista et al.,
2008 ; Stewart & Zack, 2008 ), it was also predicted that tobacco
use would be associated with ( d ) reasons for gambling that
either increase positive affect or decrease negative affect.
Methods
The sample in this report was compiled from the 2005
Newfoundland and Labrador Gambling Prevalence Study ( Market
Quest Research Group, 2005 ). The questionnaire consisted of
65 questions organized into four major sections: demographic
variables, gambling involvement (including reasons for gam-
bling), problem gambling behavior and adverse consequences,
and correlates of gambling. Data were collected province-wide
via telephone between September 7 and October 20, 2005. All
respondents were 19 years or older. The sample included 2,154
respondents who reported gambling during the past 12 months
with smoking status data available for 1,619 gamblers (only these
respondents were included in our analyses). Sampling was strat-
ifi ed by gender and region but was otherwise random. The total
response rate was unavailable. A demographic comparison of
smokers ( N = 622) and nonsmokers ( N = 997) is provided in
Table 1 .
Respondents were asked several questions regarding their
gambling involvement and behavior during the past 12 months.
These included: types of gambling activities they had participated
in, total number of activities participated in, and total dollar
amount spent gambling. In the present investigation, amount
spent gambling underwent a square root transformation as a
result of a non-normal distribution and the presence of outliers.
Table 1. Chi-Square Analyses for Demographic Characteristics of Nonsmokers Versus
Smokers
Demographic characteristic Nonsmokers ( N = 997) Smokers ( N = 622) χ 2 df p value
Gender: n (%) 0.63 1 0.44
Male 496 (49.7) 322 (51.8)
Female 501 (50.3) 300 (48.2)
Age group: n (%) 97.26 3 0.01*
19 – 34 years 188 (18.9) 206 (33.1)
35 – 54 years 459 (46.0) 321 (51.6)
55 – 64 years 168 (16.9) 64 (10.3)
65+ years 182 (18.3) 31 (5.0)
Marital status: n (%) 48.82 2 0.01*
Married/common law 796 (80.0) 418 (67.4)
Widowed/separated/divorced 114 (11.5) 76 (12.3)
Single 85 (8.5) 126 (20.3)
Household income: n (%) 8.65 3 0.03*
$20,000 or less 96 (13.1) 69 (14.3)
$20,001 to $40,000 240 (32.7) 191 (39.5)
$40,001 to $80,000 276 (37.6) 163 (33.7)
$80,000 or more 123 (16.6) 61 (12.5)
Note . * p .05 .
3
Nicotine & Tobacco Research
Three gambling activities (i.e., internet gambling, arcade or
video games, and short - term stock) were excluded due to low
rates of endorsement (<5%).
The questionnaire also included Problem Gambling Severity
Index (PGSI) scores from the Canadian Problem Gambling
Index (CPGI; Ferris & Wynne, 2001 ) to determine past 12-month
problem gambling severity (higher scores denote increased
risk for problem gambling). The CPGI displays strong psycho-
metric properties including good internal consistency ( α =
.84), test retest reliability ( r = 0.78), and high convergent
validity ( r = 0.83) ( Ferris & Wynne, 2001 ) with the South Oaks
Gambling Screen (SOGS; Lesieur & Blume, 1987 ). In the cur-
rent study, the PGSI displayed a high degree of internal consis-
tency ( α = .93). In addition, questions on known correlates
of problem gambling were included such as age fi rst gambled,
remembering first big win, agreement with the gambler s
fallacy, ” use of a “ certain system or strategy while gambling, ”
using alcohol or drugs while gambling, and gambling while
drunk or high.
Lastly, respondents were asked to provide the main reasons
why they gamble. They were free to list as many reasons for
gambling as they wished. Each verbatim response was then
placed by the interviewer into one of the following categories:
“ it ’ s an opportunity to socialize, ” “ it is exciting/fun, ” “ I can win
money, ” “ it ’ s a hobby, ” “ out of curiosity, ” “ because I am good
at it , ” and “ to support worthy causes/charities. ” The answer
choices also included: “ I can forget about my problems, ” “ it de-
creases my boredom, ” and “ to be alone. ” Individual motives
were then combined for the current report into three motives
groups based on their conceptual similarity: (1) positive rein-
forcement/reward [socialize, exciting/fun, win money, hobby,
curiosity, and being good at it] ( N = 1,375), (2) negative re-
inforcement/relief [forget problems, boredom, & to be alone]
( N = 151), and (3) charitable motives [support causes/charities]
( N = 456). All reasons for gambling provided by respondents
were included with some providing more than one motive.
Previous research suggests that conceptually similar items load
onto broader gambling motive constructs and usefully differen-
tiate gambler subtypes (e.g., Stewart & Zack, 2008 ).
Statistical Analysis
Data analyses for this study were performed with SPSS software.
Hypotheses were tested by comparing nonsmokers and smokers
across criterion variables. Categorical demographic measures
were examined with individual chi-square analyses. Three binary
logistic regressions were conducted in an effort to identify which
(1) gambling involvement variables, (2) problem gambling
correlates, and (3) reasons for gambling differentially distinguish
nonsmokers and smokers. No violations of the assumptions of
linearity or multicollinearity were detected.
Results
Nonsmoking and smoking gamblers differed on several demo-
graphic variables (see Table 1 ). While no differences in gender
composition were noted, gamblers who smoke were on average
found to be younger, more likely to be single/not married, and
to have lower incomes than gamblers who don t smoke.
The regression model for gambling involvement was signif-
icant, Cox and Snell Pseudo R 2 = .06, χ 2 (10) = 88.92, p < .001.
Amount of money spent gambling ( odds ratio [ OR ] = 1.01) and
use of VLTs (OR = 1.77) in the past 12 months both predicted
smoking over nonsmoking (see Table 2 ). Only raffl e ticket (OR =
0.66) participation predicted nonsmoking group member-
ship. The remaining gambling involvement variables were not
signifi cant.
For problem gambling correlates, the regression analysis
revealed several signifi cant associations with smoking status,
Cox and Snell Pseudo R 2 = .04, χ 2 (7) = 52.68, p < .001. The OR
for average score on the PGSI ( Ferris & Wynne, 2001 ) (OR = 1.08)
and use of alcohol/drugs while gambling (OR = 1.58) signifi-
cantly predicted smoker group membership (see Table 3 ). The
remaining problem gambling correlates were not signifi cant.
Finally, the reasons for gambling regression model were also
signifi cant, Cox and Snell Pseudo R 2 = .02, χ 2 (3) = 23.50, p <
.001. “ Positive reinforcement/reward motives ” (OR = 1.53)
and “ negative reinforcement/relief motives ” (OR = 2.22), each
Table 2. Binary Logistic Regression for Gambling Involvement Among Nonsmokers and
Smokers
Gambling involvement Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
Number of activities: M ( SE ) a 2.7 (0.05) 3.2 (0.07) 0.66 1.43 0.60 3.40
Amount spent gambling (dollars): M ( SE ) a 336.5 (53.1) 724.7 (133.8) 5.93 1.01* 1.00 1.02
Type of gambling
Lottery tickets: n (%) 881 (88.5) 532 (85.7) 3.17 0.67 0.43 1.04
Scratch tickets: n (%) 489 (49.0) 388 (62.6) 0.36 1.14 0.74 1.78
Raffl e tickets: n (%) 565 (56.7) 320 (51.5) 4.89 0.66* 0.46 0.95
Cards and poker: n (%) 142 (14.2) 146 (23.5) 0.81 1.21 0.80 1.84
Sports, horses, and games of skill: n (%) 79 (7.9) 73 (11.7) 0.01 1.02 0.62 1.69
Bingo: n (%) 112 (11.2) 123 (19.8) 2.52 1.39 0.93 2.09
Video lottery terminals: n (%) 92 (9.2) 142 (22.8) 6.84 1.77* 1.15 2.71
Casino games: n (%) 49 (4.9) 33 (5.3) 2.52 0.63 0.35 1.12
Not e. * p .05
a Original means and SE s reported .
835
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Smoking and gambling
4
Smoking and gambling
predicted smoker group membership (see Table 4 ). “ Charitable ”
motives were not found to be signifi cant.
Discussion
The purpose of this study was to investigate potential differ-
ences between nonsmokers and smokers on several gambling-
related criteria. Consistent with our predictions, smoking
gamblers were differentiated from nonsmoking gamblers across
numerous gambling behaviors, problem gambling indices, and
gambling motives.
Tobacco use in this study was associated with increased odds
of elevated PGSI scores, using alcohol/drugs while gambling
and spending more money gambling in the previous 12 months.
Additionally, VLT participation was the only gambling activity
that signifi cantly predicted smoker group membership with an
increase of 1.77 in the log odds. These fi ndings from a population-
based sample are generally consistent with the profi le of tobacco-
using gamblers derived from clinical studies ( Grant & Potenza,
2005 ; Grant et al., 2008 ; Petry & Oncken, 2002 ; Potenza
et al., 2004 ). Our results also suggest that motivation to gamble
for smokers and nonsmokers may be uniquely different. Motives
centered on positive reinforcement/reward as well as negative
reinforcement/relief were strongly associated with tobacco use.
These two groups of motives closely correspond to previous
reports of “ enhancement ” and “ coping ” motives for alcohol
use ( Cooper, 1994 ) and for problematic gambling ( Stewart &
Zack, 2008 ; Stewart, Zack, Collins, & Klein, 2008 ), respectively.
This trend toward gambling for riskier reasons that decrease
negative affect (i.e., “ escape ” ) and increase positive affect
(i.e., “ excitement ” ) among smokers in our sample appears
to parallel their increased association with problem gambling
severity, substance use while gambling, and choice of riskier
types of gambling.
Overall, these results suggest that tobacco use is associated
with potentially problematic gambling outcomes and motives.
It is conceivable that smoking and gambling share a number of
common underlying mechanisms which may help to explain
their association. For instance, evidence indicates that both
nicotine ( Pontieri, Tanda, Orzi, & Di Chiara, 1996 ) and problem
gambling ( Lader, 2008 ; Linnet, Peterson, Doudet, Gjedde, &
Møller, 2010 ) are reinforced via neurochemical processes
including increased dopamine neurotransmission. Theoretically,
it is conceivable that tobacco use during gambling may augment
reinforcement through dopamine mediation. The relationship
between smoking and gambling may also be behaviorally condi-
tioned. For example, evidence indicates that the presence of
environmental cues can elicit cravings in a number of substance
use disorders ( Carter & Tiffany, 1999 ) as well as problem gam-
bling ( Sodano & Wulfert, 2010 ). In animal models, nicotine has
been found to facilitate the release of dopamine in response to
other reinforcing stimuli (e.g., Chaudhri et al., 2007 ). In humans,
nicotine has been shown to increase sensitivity to cocaine-related
cues ( Reid, Mickalian, Delucchi, Hall, & Berger, 1998 ) as well as
increase other addictive behaviors such as alcohol consumption
( Barrett, Tichauer, Leyton, & Pihl, 2006 ). While as yet to be tested,
it is feasible that cue reactivity or the reinforcement-enhancing
properties of nicotine contribute to the problematic gambling
behavior exhibited by smokers who gamble. It is also possible
that cooccurring tobacco use and gambling is infl uenced through
cognitive factors. For instance, a recent laboratory study found
Table 3. Binary Logistic Regression for Problem Gambling Correlates Among
Nonsmokers and Smokers
Problem gambling correlates Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
PGSI score, M ( SE ) 0.33 (0.06) 1.02 (0.14) 8.54 1.08* 1.03 1.13
Age fi rst gambled (years), M ( SE ) 23.3 (0.36) 22.3 (0.39) 0.32 0.99 0.99 1.01
Remember fi rst big win, n (%) 38 (3.9) 37 (6.0) 1.66 1.22 0.90 1.64
Endorse gambler ’ s fallacy, n (%) 45 (4.7) 40 (6.6) 0.18 1.11 0.68 1.82
Use system or strategy, n (%) 90 (9.7) 76 (12.9) 0.56 1.15 0.80 1.65
Use alcohol/drugs while gambling, n (%) 120 (12.3) 146 (23.7) 6.98 1.58* 1.13 2.22
Gambled while drunk/high, n (%) 37 (3.8) 63 (10.3) 3.04 1.61 0.94 2.74
Not e.
* p .05
Table 4. Binary Logistic Regression for Reasons for Gambling Among Nonsmokers and
Smokers
Reasons for gambling Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
Positive reinforcement/reward, n (%) 837 (87.9) 538 (90.3) 4.88 1.53* 1.05 2.22
Negative reinforcement/relief, n (%) 70 (7.4) 81 (13.6) 18.88 2.22* 1.55 3.19
Charitable, n (%) 297 (31.2) 159 (26.7) 0.72 0.90 0.71 1.15
Note . Gambling reasons are not mutually exclusive with participants free to endorse more than one reason.
* p .05.
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Nicotine & Tobacco Research, Volume 14, Number 7 (July 2012)
4
Smoking and gambling
predicted smoker group membership (see Table 4 ). “ Charitable ”
motives were not found to be signifi cant.
Discussion
The purpose of this study was to investigate potential differ-
ences between nonsmokers and smokers on several gambling-
related criteria. Consistent with our predictions, smoking
gamblers were differentiated from nonsmoking gamblers across
numerous gambling behaviors, problem gambling indices, and
gambling motives.
Tobacco use in this study was associated with increased odds
of elevated PGSI scores, using alcohol/drugs while gambling
and spending more money gambling in the previous 12 months.
Additionally, VLT participation was the only gambling activity
that signifi cantly predicted smoker group membership with an
increase of 1.77 in the log odds. These fi ndings from a population-
based sample are generally consistent with the profi le of tobacco-
using gamblers derived from clinical studies ( Grant & Potenza,
2005 ; Grant et al., 2008 ; Petry & Oncken, 2002 ; Potenza
et al., 2004 ). Our results also suggest that motivation to gamble
for smokers and nonsmokers may be uniquely different. Motives
centered on positive reinforcement/reward as well as negative
reinforcement/relief were strongly associated with tobacco use.
These two groups of motives closely correspond to previous
reports of “ enhancement ” and “ coping ” motives for alcohol
use ( Cooper, 1994 ) and for problematic gambling ( Stewart &
Zack, 2008 ; Stewart, Zack, Collins, & Klein, 2008 ), respectively.
This trend toward gambling for riskier reasons that decrease
negative affect (i.e., “ escape ” ) and increase positive affect
(i.e., “ excitement ” ) among smokers in our sample appears
to parallel their increased association with problem gambling
severity, substance use while gambling, and choice of riskier
types of gambling.
Overall, these results suggest that tobacco use is associated
with potentially problematic gambling outcomes and motives.
It is conceivable that smoking and gambling share a number of
common underlying mechanisms which may help to explain
their association. For instance, evidence indicates that both
nicotine ( Pontieri, Tanda, Orzi, & Di Chiara, 1996 ) and problem
gambling ( Lader, 2008 ; Linnet, Peterson, Doudet, Gjedde, &
Møller, 2010 ) are reinforced via neurochemical processes
including increased dopamine neurotransmission. Theoretically,
it is conceivable that tobacco use during gambling may augment
reinforcement through dopamine mediation. The relationship
between smoking and gambling may also be behaviorally condi-
tioned. For example, evidence indicates that the presence of
environmental cues can elicit cravings in a number of substance
use disorders ( Carter & Tiffany, 1999 ) as well as problem gam-
bling ( Sodano & Wulfert, 2010 ). In animal models, nicotine has
been found to facilitate the release of dopamine in response to
other reinforcing stimuli (e.g., Chaudhri et al., 2007 ). In humans,
nicotine has been shown to increase sensitivity to cocaine-related
cues ( Reid, Mickalian, Delucchi, Hall, & Berger, 1998 ) as well as
increase other addictive behaviors such as alcohol consumption
( Barrett, Tichauer, Leyton, & Pihl, 2006 ). While as yet to be tested,
it is feasible that cue reactivity or the reinforcement-enhancing
properties of nicotine contribute to the problematic gambling
behavior exhibited by smokers who gamble. It is also possible
that cooccurring tobacco use and gambling is infl uenced through
cognitive factors. For instance, a recent laboratory study found
Table 3. Binary Logistic Regression for Problem Gambling Correlates Among
Nonsmokers and Smokers
Problem gambling correlates Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
PGSI score, M ( SE ) 0.33 (0.06) 1.02 (0.14) 8.54 1.08* 1.03 1.13
Age fi rst gambled (years), M ( SE ) 23.3 (0.36) 22.3 (0.39) 0.32 0.99 0.99 1.01
Remember fi rst big win, n (%) 38 (3.9) 37 (6.0) 1.66 1.22 0.90 1.64
Endorse gambler ’ s fallacy, n (%) 45 (4.7) 40 (6.6) 0.18 1.11 0.68 1.82
Use system or strategy, n (%) 90 (9.7) 76 (12.9) 0.56 1.15 0.80 1.65
Use alcohol/drugs while gambling, n (%) 120 (12.3) 146 (23.7) 6.98 1.58* 1.13 2.22
Gambled while drunk/high, n (%) 37 (3.8) 63 (10.3) 3.04 1.61 0.94 2.74
Not e.
* p .05
Table 4. Binary Logistic Regression for Reasons for Gambling Among Nonsmokers and
Smokers
Reasons for gambling Nonsmokers ( N = 997) Smokers ( N = 622) Wald Exp (B)
95% CI
Lower Upper
Positive reinforcement/reward, n (%) 837 (87.9) 538 (90.3) 4.88 1.53* 1.05 2.22
Negative reinforcement/relief, n (%) 70 (7.4) 81 (13.6) 18.88 2.22* 1.55 3.19
Charitable, n (%) 297 (31.2) 159 (26.7) 0.72 0.90 0.71 1.15
Note . Gambling reasons are not mutually exclusive with participants free to endorse more than one reason.
* p .05.
5
Nicotine & Tobacco Research
that pathological gamblers who were heavy smokers made fewer
errors on tests of cognitive flexibility than lighter smokers
( Mooney, Odlaug, Kim, & Grant, 2011 ). The authors suggest
that nicotine may serve as a putative cognitive enhancer for
pathological gamblers. Finally , there is evidence to indicate that
smokers and gamblers share common personality characteristics.
In particular, higher levels of impulsivity have been reported
among smokers (e.g., Mitchell, 2004 ), pathological/problem
gamblers (e.g., Alessi & Petry, 2003 ; Nower, Derevensky, &
Gupta, 2004 ), and pathological gamblers with substance-use
disorders ( Verdejo-García, Lawrence, & Clark, 2008 ). It is con-
ceivable that certain personality characteristics differentially
infl uence the genesis and maintenance of cooccurring tobacco
use and gambling. These possible underlying mechanisms warrant
further experimental exploration.
This study contains a number of limitations. First, as the
questions were not designed for this investigation, additional
information that would have been desirable (e.g., co-use of
tobacco while gambling) was not available. Second, demographic
differences (i.e., age, marital status, income) were found be-
tween smokers and nonsmokers. It would have been preferable
to control for these differences; however, continuous informa-
tion was unavailable. Third, the cross-sectional design of the
survey did not allow for an examination of cause and effect. The
present study highlights a number of associations between
smoking and gambling but the directionally or causality of these
effects cannot be inferred. Fourth, while respondents provided
information on their motives for gambling, the construction of
the survey did not allow for the isolation of the primary rea-
son they gambled during the past year. It is feasible that these
primary motives for gambling are associated with problematic
gambling behavior to a greater extent than the other more sec-
ondary motives provided. Another potential limitation is that
only one Canadian province was included at one point in time.
Laws surrounding gambling and smoking vary; it is possible
that our results do not extrapolate to other jurisdictions. Finally,
results may have been impacted by the timing of data collection.
On July 1, 2005, Newfoundland and Labrador amended the
Smoke- Free Environment Act (2002), prohibiting smoking in
all public places including establishments which host gaming.
The gambling prevalence survey was administered in September
and October, 2005. As such, the smoking ban had been in effect
for 2 months prior to the start of data collection. It is unclear
how this could affect responses, especially for those questions
surrounding smoking. However, most of the gambling-related
questions focused on the past 12 months, with the majority of
those months occurring prior to the amendment.
The current study may have important implications for
both researchers and clinicians. First, pathological gambling
may soon be reclassifi ed as an addictive disorder in the upcoming
fth edition of the American Psychiatric Association Diagnostic
and Statistical Manual of Mental Disorders ( Grant, Potenza,
Weinstein, & Gorelick, 2010 ; Holden, 2010 ). If the diagnostic
classifi cation of pathological gambling changes to more closely
resemble that of substance-use disorders, including tobacco
dependence, an opportunity exists for researchers to further
investigate common features (e.g., genetics, personality, neuro-
biology) associated with both gambling and other substance
dependence including smoking. A strength of the methodology
employed in the current investigation is that it allows for the
identifi cation of important associations between gambling and
other addictive behaviors. Also, in addition to previous work
that examined clinical samples of gamblers (e.g., Grant et al.,
2008 ; Petry & Oncken, 2002 ), the present study indicates that
smoking is also commonly associated with gambling-related
problems in the general population. For clinicians, these results
provide awareness of potentially problematic gambling motives,
correlates , and activities associated with tobacco use and may
ultimately lead to better prevention efforts for smokers at risk
for problem gambling.
The present study was the first to systematically compare
a population-based sample of nonsmokers and smokers who
smoke on gambling behavior, problem gambling indices, and
motives for gambling. Our results indicate that tobacco use
among gamblers was associated with increased participation in
riskier forms of gambling, increased problem gambling severity,
and endorsement of motives linked to problematic gambling.
Future work should address the potential impact of nicotine on
the development, reinforcement, and treatment of problematic
gambling. Of particular importance, more controlled laboratory
studies are needed to accurately elucidate the role that smoking
plays in gambling behavior, craving, and motivation.
Funding
The data for this study w ere generously provided by the Ontario
Problem Gambling Research Centre. Portions of this study were
completed by Daniel McGrath in partial fulfi llment of a Ph . D .
in experimental psychology at Dalhousie University. Daniel was
supported through doctorate student research awards from the
Nova Scotia Health Research Foundation, Gambling Awareness
Nova Scotia, and a doctorate fellowship from the Ontario Problem
Gambling Research Centre during the completion of this
research.
Declaration of Interests
None declared.
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16500
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youth gamblers . Psychology of Addictive Behaviors , 18 , 49 – 55 .
doi:10.1037/0893-164X.18.1.49
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Current status and future directions . The American Journal on
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with increased severity of gambling problems in treatment-seeking
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00163.x
Petry , N. M. , Stinson , F. S. , & Grant , B. F. ( 2005 ). Comorbidity
of DSM-IV pathological gambling and other psychiatric disorders:
Results from the National Epidemiologic Survey on Alcohol and
Related Conditions . Journal of Clinical Psychiatry , 66 , 564 – 574 .
doi:10.4088/JCP.v66n0504
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Pomerleau , C. S. ( 2003 ). Development and validation of a self-
rating scale for positive- and negative-reinforcement smoking:
The Michigan Nicotine Reinforcement Questionnaire . Nicotine &
Tobacco Research , 5 , 711 – 718 . doi:10.1080/146222003100015
8627
Pontieri , F. E. , Tanda , G. , Orzi , F. , & Di Chiara , G. ( 1996 ).
Effects of nicotine on the nucleus accumbens and similarity to
those of addictive drugs . Nature , 382 , 255 – 257 . doi: 10.1038/
382255a0
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Rounsaville , B. J. , Krishnan-Sarin , S. , et al. ( 2004 ). Characteristics
F
838
at Dalhousie University on July 25, 2012http://ntr.oxfordjournals.org/Downloaded from
Nicotine & Tobacco Research, Volume 14, Number 7 (July 2012)
6
Smoking and gambling
Chaudhri , N. , Caggiula , A. R. , Donny , E. C. , Booth , S. , Gharib , M. ,
Craven , L. , et al. ( 2007 ). Self-administered and noncontingent
nicotine enhance reinforced operant responding in rats: Impact
of nicotine dose and reinforcement schedule . Psychopharmacology ,
190 , 353 – 362 . doi:10.1007/s00213-006-0454-8
Cooper , M. ( 1994 ). Motivations for alcohol use among adoles-
cents: Development and validation of a four-factor model .
Psychological Assessment , 6 , 117 – 128 . doi:10.1037/1040-3590.6.
2.117
Cunningham-Williams , R. M. , Cottler , L. B. , Compton , W. , &
Spitznagel , E. L. ( 1998 ). Taking chances: Problem gamblers and
mental health disorders: Results from the St. Louis Epidemiologic
Catchment Area study . American Journal of Public Health , 88 ,
1093 – 1096 . doi:10.2105/AJPH.88.7.1093
Ferris , J. , & Wynne , H. ( 2001 ). The Canadian Problem Gambling
Index: Final report . Canadian Centre on Substance Abuse , Ottawa,
Ontario: CCSA .
Grant , J. E. , Kim , S. , Odlaug , B. L. , & Potenza , M. N. ( 2008 ).
Daily tobacco smoking in treatment-seeking pathological gam-
blers: Clinical correlates and co-occurring psychiatric disorders .
Journal of Addiction Medicine , 2 , 178 – 184 . doi:10.1097/ADM.
0b013e3181878673
Grant , J. E. , & Potenza , M. N. ( 2005 ). Tobacco use and pathological
gambling . Annals of Clinical Psychiatry , 17 , 237 – 241 . doi:10.1080/
10401230500295370
Grant , J. E. , Potenza , M. N. , Weinstein , A. , & Gorelick , D. A.
( 2010 ). Introduction to behavioral addictions . The American
Journal of Drug and Alcohol Abuse , 36 , 233 – 241 . doi:10.3109/
00952990.2010.491884
Griffi ths , M. , Wardle , H. , Orford , J. , Sproston , K. , & Erens , B.
( 2010 ). Gambling, alcohol, consumption, cigarette smoking and
health: Findings from the 2007 British Gambling Prevalence
Survey . Addiction Research & Theory , 18 , 208 – 223 . doi:10.3109/
16066350902928569
Holden , C. ( 2010 ). Behavioral addictions debut in proposed
DSM-V . Science , 327 , 935 . doi: 10.1126/science.327.5968.935
Lader , M. ( 2008 ). Antiparkinsonian medication and pathological
gambling . CNS Drugs , 22 , 407 – 416 . doi:10.2165/00023210-
200822050-00004
Lesieur , H. R. , & Blume , S. B. ( 1987 ). The South Oaks Gambling
Screen (SOGS): A new instrument for the identification of
pathological gamblers . The American Journal of Psychiatry , 144 ,
1184 – 1188 .
Linnet , J. J. , Peterson , E. E. , Doudet , D. J. , Gjedde , A. A. , &
Møller , A. A. ( 2010 ). Dopamine release in ventral striatum of
pathological gamblers losing money . Acta Psychiatrica Scandinavica ,
122 , 326 – 333 . doi: 10.1111/j.1600-0447.2010.01591.x
Lorains , F. K. , Cowlishaw , S. , & Thomas , S. A. ( 2011 ). Preva-
lence of comorbid disorders in problem and pathological
gambling: Systematic review and meta-analysis of population
surveys . Addiction , 106 , 490 – 498 . doi:10.1111/j.1360-0443.2010.
03300.x
Market Quest Research Group . ( 2005 ). 2005 Newfoundland and
Labrador Gambling Prevalence Study . St. John ’ s, NL : Department of
Health and Community Services, Government of Newfoundland
and Labrador .
McGrath , D. S. , & Barrett , S. P. ( 2009 ). The comorbidity of
tobacco smoking and gambling: A review of the literature . Drug
and Alcohol Review , 28 , 676 – 681 . doi: 10.1111/j.1465-3362.2009.
00097.x
Milosevic , A. , & Ledgerwood , D. M. ( 2010 ). The subtyping
of pathological gambling: A comprehensive review . Clinical
Psychology Review , 30 , 988 – 998 . doi:10.1016/j.cpr.2010.06.013
Mitchell , S. H. ( 2004 ). Measuring impulsivity and modeling its
association with cigarette smoking . Behavioral and Cognitive
Neuroscience Reviews , 3 , 261 – 275 . doi:10.1177/15345823052
76838
Mooney , M. E. , Odlaug , B. L. , Kim , S. , & Grant , J. E. ( 2011 ).
Cigarette smoking status in pathological gamblers: Associa-
tion with impulsivity and cognitive flexibility . Drug and
Alcohol Dependence , 117 , 74 – 77 . doi:10.1016/j.drugalcdep.
2010.12.017
Neighbors , C. , Lostutter , T. W. , Cronce , J. M. , & Larimer , M. E.
( 2002 ). Exploring college student gambling motivation . Journal
of Gambling Studies , 18 , 361 – 370 . doi:10.1023/A:10210651
16500
Nower , L. , Derevensky , J. L. , & Gupta , R. ( 2004 ). The relationship
of impulsivity, sensation seeking, coping, and substance use in
youth gamblers . Psychology of Addictive Behaviors , 18 , 49 – 55 .
doi:10.1037/0893-164X.18.1.49
Petry , N. M. ( 2007 ). Gambling and substance use disorders:
Current status and future directions . The American Journal on
Addictions , 16 , 1 – 9 . doi:10.1080/10550490601077668
Petry , N. M. , & Oncken , C. ( 2002 ). Cigarette smoking is associated
with increased severity of gambling problems in treatment-seeking
gamblers . Addiction , 97 , 745 – 753 . doi:10.1046/j.1360-0443.2002.
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Petry , N. M. , Stinson , F. S. , & Grant , B. F. ( 2005 ). Comorbidity
of DSM-IV pathological gambling and other psychiatric disorders:
Results from the National Epidemiologic Survey on Alcohol and
Related Conditions . Journal of Clinical Psychiatry , 66 , 564 – 574 .
doi:10.4088/JCP.v66n0504
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rating scale for positive- and negative-reinforcement smoking:
The Michigan Nicotine Reinforcement Questionnaire . Nicotine &
Tobacco Research , 5 , 711 – 718 . doi:10.1080/146222003100015
8627
Pontieri , F. E. , Tanda , G. , Orzi , F. , & Di Chiara , G. ( 1996 ).
Effects of nicotine on the nucleus accumbens and similarity to
those of addictive drugs . Nature , 382 , 255 – 257 . doi: 10.1038/
382255a0
Potenza , M. N. , Steinberg , M. A. , Mclaughlin , S. D. , Wu , R. ,
Rounsaville , B. J. , Krishnan-Sarin , S. , et al. ( 2004 ). Characteristics
7
Nicotine & Tobacco Research
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839
at Dalhousie University on July 25, 2012http://ntr.oxfordjournals.org/Downloaded from
... Registered on August 3, 2019 Keywords: Problem gambling, Tobacco smoking, Integrated treatment, Cognitive behavioural therapy, Motivational interviewing, Online, Self-help Background Significance Problem gambling [1,2] and tobacco smoking [3,4] are highly comorbid [5,6] in North America. Indeed, studies show that tobacco dependence is the most common comorbid disorder among problem gamblers, with prevalence rates ranging from 41 to 60% [7][8][9][10][11]. According to the World Health Organization, tobacco use kills up to 50% of its users-translating into nearly six million deaths annually [12]. ...
... Tobacco use is also linked to several chronic health conditions, including cancers, respiratory problems, and cardiovascular diseases [12]. Given their high rates of smoking (relative to the general population) [7][8][9], problem gamblers are thus disproportionately affected by the increased morbidity and mortality from tobacco use. Moreover, research to date shows that co-occurring tobacco use compounds gamblingrelated harms. ...
... This open-label pilot study will address a notable gap in the literature on problem gambling treatment. It has been known for a long time that a high proportion of gamblers smoke cigarettes [7,8] and that daily smoking compounds gambling severity [13][14][15][16]. However, very little work has been done to systematically address the problem of smoking in treatment for problem gambling. ...
Article
Full-text available
Background Gambling and tobacco smoking are highly comorbid among North American adults. However, there is a paucity of treatment options that are integrated (i.e. targeting both gambling and tobacco smoking simultaneously), accessible, and evidence based. Methods The aim of this two-arm open-label randomized controlled trial is to examine the effectiveness of an online, self-guided integrated treatment for problem gambling and tobacco smoking. A target sample of 214 participants will be recruited and be randomized into either an 8-week integrated or gambling only control condition. Both conditions will consist of seven online modules following cognitive behavioural therapy and motivational interviewing principles. Our three primary outcomes are (1) the number of days gambled, (2) money spent on gambling activities, and (3) time spent in gambling activities. Secondary outcomes include gambling disorder symptoms, cigarette use, and nicotine dependence symptoms. Assessments will be completed at baseline, at completion (i.e. 8 weeks from baseline), and at follow-up (i.e. 24 weeks from baseline). Generalized linear mixed modelling will be used to evaluate our primary and secondary outcomes. We expect that participants receiving online integrated treatment will show larger reductions in gambling relative to those receiving a control gambling only intervention. We further hypothesize that reductions in smoking will mediate these group differences. Discussion The rates of problem gambling and tobacco smoking are high in North America; yet, the treatment options for both are limited, with no integrated treatments available. If supported, our pilot study will be a cost-effective and accessible way to improve treatments for co-occurring problem gambling and tobacco use. Trial registration ClinicalTrials.gov NCT03614884. Registered on August 3, 2019
... This open label pilot study will address a notable gap in the literature on problem gambling treatment. It has been known for a long time that a high proportion of gamblers smoke cigarettes, 7,8 and that daily smoking compounds gambling severity. [13][14][15][16] However, very little work has been done to systematically address the problem of smoking in treatment for problem gambling. ...
... Dr. Keough will recruit from cities across Canada and the United States using online ads (e.g., Google Ads, Craigslist, Kijiji, and local news websites), local avenues (i.e., newspapers), and governmental organizations (i.e., Manitoba Liquor and Lotteries). Given the high rates of problem gambling and tobacco smoking in Canada and the United States, 7,8,9,12 it should be feasible to recruit the required sample size. ...
... In fact, statistics suggest that people living in remote communities are at a signi cant disadvantage. 7,8 They seem to be struggling most with addiction and related problems, but have limited access to treatment facilities. Thus, the proposed study has the potential to substantially improve the health and well-being of adults living across the continent. ...
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Background: Gambling and tobacco smoking are highly comorbid among North American adults. However, there is a paucity of treatment options that are integrated (i.e., targeting both gambling and tobacco smoking simultaneously), accessible, and evidence based. Methods: The aim of this two-arm open label randomized controlled trial is to examine the effectiveness of an online, self-guided integrated treatment for problem gambling and tobacco smoking. A target sample of 214 participants will be recruited and be randomized into either an eight-week integrated or gambling-only control condition. Both conditions will consist of seven online modules following cognitive behavioral therapy and motivational interviewing principles. Our three primary outcomes are (1) number of days gambled, (2) money spent on gambling activities, and (3) time spent in gambling activities. Secondary outcomes include gambling disorder symptoms, cigarette use, and nicotine dependence symptoms. Assessments will be completed at baseline, at completion (i.e., eight-weeks from baseline), and follow-up (i.e., 24-weeks from baseline). Generalized linear mixed modelling will be used to evaluate our primary and secondary outcomes. We expect that participants receiving online integrated treatment will show larger reductions in gambling relative to those receiving a control gambling only intervention. We further hypothesize that reductions in smoking will mediate these group differences. Discussion: The rates of problem gambling and tobacco smoking are high in North America; yet, the treatment options for both are limited, with no integrated treatments available. If supported, our pilot study will be a cost-effective and accessible way to improve treatments for co-occurring problem gambling and tobacco use. Trial registration: Clinicaltrials.gov; ID NCT03614884. Registered August 3, 2019; https://clinicaltrials.gov/ct2/show/NCT03614884?term=keough&rank=1
... 49,71 Accordingly, in the rst module, participants in the integrated treatment arm will be provided with an extensive fact sheet on NRT use -including the strong evidence supporting its use in conjunction with psychosocial treatment for smoking cessation. Participants will be (1) encouraged to use NRT patches for the eight weeks of active treatment, (2) advised that NRT patches are available over the counter at any local pharmacy, (3) provided with NRT patches for the duration of treatment, and (4) advised to consult with their family physician should they have any medical questions related to NRT patches. As noted in best practice guidelines 71 , the dosage schedule of NRT patches will be the following: 24 mg for four weeks then 14 mg for two weeks and nally 7 mg for remaining two weeks. ...
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Background: Gambling and tobacco smoking are highly comorbid among North American adults. However, there is a paucity of treatment options that are integrated (i.e., targeting both gambling and tobacco smoking simultaneously), accessible, and evidence based. Methods: The aim of this two-arm randomized controlled trial is to examine the effectiveness of an online, self-guided integrated treatment for problem gambling and tobacco smoking. A target sample of 214 participants will be recruited and be randomized into either an eight-week integrated or gambling-only control condition. Both conditions will consist of seven online modules following cognitive behavioral therapy and motivational interviewing principles. Our three primary outcomes are (1) number of days gambled, (2) money spent on gambling activities, and (3) time spent in gambling activities. Secondary outcomes include gambling disorder symptoms, cigarette use, and nicotine dependence symptoms. Assessments will be completed at baseline, at completion (i.e., eight-weeks from baseline), and follow-up (i.e., 24-weeks from baseline). Generalized linear mixed modelling will be used to evaluate our primary and secondary outcomes. We expect that participants receiving online integrated treatment will show larger reductions in gambling relative to those receiving a control gambling only intervention. We further hypothesize that reductions in smoking will mediate these group differences. Discussion: The rates of problem gambling and tobacco smoking are high in North America; yet, the treatment options for both are limited, with no integrated treatments available. If supported, our intervention will be a cost-effective and accessible way to improve treatments for co-occurring problem gambling and tobacco use. Trial registration: Clinicaltrials.gov; ID NCT03614884. Registered August 3, 2019;
... These included lottery tickets, daily lottery, instant-win/scratch tickets, raffles, bingo, video lottery terminals, slot machines, video games for money, Internet gambling, sport select, sports pools, outcome of sporting events, horse races, casino games (in province), casino games (outside of the province), short-term stock, games of skill, and non-regulated card games. A similar question has been employed by our group in the past to assess recent gambling behavior (e.g., McGrath, Barrett, Stewart, & McGrath, 2012). This information was used to dichotomize the gamblers (0 = nongambler, 1 = gambler). ...
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Background and aims Substantial research has examined the role of personality in disordered gambling. The predominant model in this work has been the five-factor model (FFM) of personality. In this study, we examined the personality correlates of gambling engagement and gambling severity using a six-dimensional framework known as the HEXACO model of personality, which incorporates FFM characteristics with the addition of honesty–humility. In addition, the potential mediating role of gambling motives in the personality and gambling severity relationship was explored. Methods A sample of undergraduate gamblers (n = 183) and non-gamblers (n = 143) completed self-report measures of the Problem Gambling Severity Index (PGSI) and the Gambling Motives Questionnaire-Financial, as well as self- and observer report forms of the HEXACO-100. Results Logistic regression results revealed that scores on honesty–humility were positively associated with non-gambling over gambling status. Furthermore, it was also found that honesty–humility, agreeableness, and conscientiousness were each uniquely associated with PGSI severity scores. The results of the mediational analyses suggest that each personality factor has different gambling motivational paths leading to PGSI gambling severity. Discussion and conclusions The findings of this study contribute to the literature on behavioral addictions by providing an increased understanding of individual personality factors associated with likelihood of gambling, overall gambling severity, and gambling motives. Ultimately, these findings suggest that the honesty–humility dimension may be a target for the prevention efforts against problematic gambling outcomes.
... Current smoking status was assessed with the following question: "At the present time, do you smoke cigarettes daily, occasionally, or not at all?". This question format has been used in previous investigations of gambling behavior to identify current smokers and non-smokers (e.g., McGrath, Barrett, Stewart, & McGrath, 2012). ...
Article
Background: Co-morbidity with other addictive behaviors is common in disordered gambling (DG). In particular, tobacco dependence has been found to be among the most prevalent disorders co-morbid with DG. While the extant literature has firmly established the co-occurrence of DG and smoking, there is a paucity of research examining factors that differentiate DGs who smoke from those who do not. Objectives: To address this empirical gap, the current study tested whether dimensions of trait impulsivity as measured by the UPPS-P Impulsive Behavior Scale (positive urgency, negative urgency, lack of premeditation, lack of perseverance, and sensation seeking), discriminated between non-DGs and DGs based on their present smoking status: non-smoker, occasional smoker, and daily smoker. Methods: To this end, 564 community gamblers were recruited through a crowdsourcing platform (Amazon's Mechanical Turk) and completed an online survey, assessing problem gambling severity, tobacco use, and trait impulsivity. Results: MANOVA analyses revealed significant main effects for both gambling severity and smoking status groups. Importantly, a significant gambling by smoking interaction was also found. Pairwise comparisons revealed that DGs who were daily smokers scored higher on negative urgency than those who smoked occasionally or not all. Furthermore, among non-DGs, smoking status failed to discriminate between mean scores on negative urgency. No other significant interaction effects were found for the remaining UPPS-P impulsivity facets. Conclusions: Results suggest that individual components of trait impulsivity, and more specifically negative urgency, successfully differentiate DGs who do not smoke, or just smoke occasionally, from DGs who smoke daily. These findings suggest that the degree of trait impulsivity may potentially distinguish between DGs and DGs who are dually addicted to other substances such as tobacco.
... Smoking was assessed with the following question: BAt the present time, do you smoke cigarettes daily, occasionally, or not at all?^. This question has been used in previous investigations of smoking behaviour by our team (e.g.,McGrath et al. 2012). Several e-cigarette questions were included, with three being of primary interest: BHave you ever used e-cigarettes, electronic, or vapor cigarettes?^; BHave you used e-cigarettes, electronic, or vapor cigarettes in the past 30 days?^; and BIn the past 12 months, have you used e-cigarettes, electronic, or vapor cigarettes while gambling?^. ...
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Many smokers are replacing tobacco with electronic cigarettes (e-cigarettes) or are engaging in dual-use. Evidence indicates that smoking rates are higher amongst gamblers; however, the extent to which gamblers use e-cigarettes is unknown. The current study examined rates of e-cigarette use in gamblers, identified associations between e-cigarette use and gambling, and assessed motives for e-cigarette use during gambling. A community-recruited sample of gamblers (N = 564) completed questionnaires on e-cigarettes, smoking, and gambling. ‘Ever use’ of e-cigarettes was 38.7% with 17.6% reporting ‘past 30-day use’. Furthermore, 11.9% used e-cigarettes while gambling in the past 12 months. Regression analyses for ‘past 30-day use’ revealed that occasional smoking, gambling severity, and number of gambling activities were associated with the highest odds of use. Reasons for use while gambling included: relaxation/stress, nicotine dependence and legal in casinos. These findings suggest e-cigarette use is common in gamblers and may be used to circumvent casino smoking bans.
... Insofar as smoking status is frequently omitted in studies of SUDs, a focus on the relationship between tobacco use disorders and hypersexual behavior is warranted. Similar research exploring smoking status and problem gambling has yielded important findings noting tobacco use disorders constitute a precipitating and perpetuating risk factor in gambling disorder, relapse, and gambling severity [45][46][47]. Given the field is in its infancy, future research should also investigate possible differences for gender, socio-economic status, ethnicity, physical/intellectual disabilities, and sexual orientation among hypersexual populations. ...
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Purpose of Review Understanding the relationship between hypersexual behavior and substance use disorders (SUDs) has implications for assessment, diagnosis, treatment, and case conceptualization among individuals seeking help. This article reviews existing literature linking hypersexual behavior and SUDs, offers possible explanations for associations, and concludes by offering perspectives and suggestions for future research. Recent Findings SUDs are common in hypersexual populations and research is slowly beginning to highlight more complex relationships such as some of the mediating and moderating variables implicated in this comorbid condition. Summary Despite several studies investigating comorbid associations of SUDs among hypersexual patients, relationships between these phenomena are poorly understood. Additional research is needed to clarify the relationship between SUDs and hypersexual behavior including greater clarity about possible pathways including mediating and moderating models to explain associations between SUDs and hypersexuality. Outcome research delineating interventions that can successfully attenuate symptoms of hypersexual behavior and SUDs are also needed.
Chapter
Research has firmly established that smoking and gambling frequently co-occur. However, the exact mechanisms of this relationship are not completely understood. Studies pointing to the effects of conditioning and reinforcement have posited that the high rate of smoking among individuals with gambling disorder is due, in part, to these activities being paired together repeatedly. In addition, nicotine has been shown to strengthen the reinforcement of rewarding stimuli that are not related to smoking. Some research indicates that nicotine may directly influence gambling behavior through reinforcement-enhancing properties. Furthermore, there is some recent research that suggests that gambling may elicit cravings for smoking and may increase the likelihood of smoking during a gambling session. In sum, while smoking and gambling are clearly associated with each other, the exact mechanisms that influence the gambling-smoking link remain in need of further exploration.
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Chapter contains broad review of state of art in one of the best known behavioral addicions - since DSM-5 renamed as gambling disorder.
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Despite availability of treatments for gamblers, few at-risk and pathological gamblers seek help. Self-help treatments offer a private and personalized alternative that may appeal to gamblers who need help. Objective: This study examines the impact of the self-help treatment JEu me questionne (JMQ) on gambling behavior and severity, and reports participants' satisfaction. Method: Forty-seven at-risk and pathological gamblers entered the program that involved a self-help treatment workbook and two motivational phone interviews. Results: Among the 32 gamblers who completed the program, results indicated a significant reduction in the number of pathological gambling diagnostic criteria. This gain was maintained at the one- and six-month follow-ups. Time gambling and money spent were also significantly lower post-treatment, but only a reduction in time spent gambling was maintained at follow-up. Participants reported high satisfaction with the program. The discussion raises clinical and theoretical implications of these findings.
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A 4-factor measure of drinking motives based on a conceptual model by M. Cox and E. Klinger (see PA, Vol 75:32975; see also 1990) is presented. Using data from a representative household sample of 1,243 Black and White adolescents, confirmatory factor analyses showed that the hypothesized model provided an excellent fit to the data and that the factor pattern was invariant across gender, race, and age. Each drinking motive was related to a distinct pattern of contextual antecedents and drinking-related outcomes, and these relationships did not generally vary across demographic subgroups. Results support both the conceptual validity of Cox and Klinger's model and the utility of this measure for clinical and research purposes across a diverse range of adolescent populations. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Several behaviors, besides psychoactive substance ingestion, produce short-term reward that may engender persistent behavior, despite knowledge of adverse consequences, i.e., diminished control over the behavior. These disorders have historically been conceptualized in several ways. One view posits these disorders as lying along an impulsive-compulsive spectrum, with some classified as impulse control disorders. An alternate, but not mutually exclusive, conceptualization considers the disorders as non-substance or "behavioral" addictions. Inform the discussion on the relationship between psychoactive substance and behavioral addictions. We review data illustrating similarities and differences between impulse control disorders or behavioral addictions and substance addictions. This topic is particularly relevant to the optimal classification of these disorders in the forthcoming fifth edition of the American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders (DSM-V). Growing evidence suggests that behavioral addictions resemble substance addictions in many domains, including natural history, phenomenology, tolerance, comorbidity, overlapping genetic contribution, neurobiological mechanisms, and response to treatment, supporting the DSM-V Task Force proposed new category of Addiction and Related Disorders encompassing both substance use disorders and non-substance addictions. Current data suggest that this combined category may be appropriate for pathological gambling and a few other better studied behavioral addictions, e.g., Internet addiction. There is currently insufficient data to justify any classification of other proposed behavioral addictions. Proper categorization of behavioral addictions or impulse control disorders has substantial implications for the development of improved prevention and treatment strategies.
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Evidence suggests that tobacco smoking and gambling frequently co-occur. Although high rates of comorbid smoking and gambling have been documented in studies with clinical populations of pathological gamblers in treatment, in studies using samples drawn from the community, and in large-epidemiological surveys, little empirical attention has been directed towards investigating the exact nature of this relationship. In this review, we stress the literature that has examined the epidemiology, aetiology and environmental factors implicated in comorbid smoking and gambling. Publications included in the review were identified through PsycInfo, PubMed and Medline searches. Although conclusive evidence is lacking, a growing body of literature suggests that smoking and gambling might share similar neurobiological, genetic and/or common environmental influences. Comorbid tobacco smoking and gambling are highly prevalent at the event and syndrome levels. However, research investigating how smoking might affect gambling or vice versa is currently lacking. More studies that examine the impact of this comorbidity on rates of tobacco dependence and problem gambling, as well as implications for treatment outcomes, are needed.
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Previous research has shown an association between gambling, alcohol and cigarette smoking. Co-occurrence of problem gambling with other behavioural and psychological disorders can exacerbate, or be exacerbated by, problem gambling. Using participant data from the 2007 British Gambling Prevalence Survey (n = 9003 adults aged 16 years and above), secondary analysis was carried out on the relationship between gambling and three particular areas of co-occurrence. These were general health status, cigarette smoking and alcohol consumption. All analysis was age standardised to allow comparisons between groups after adjusting for the effects of any difference in their age distributions. Results showed that: (i) cigarette smokers were significantly more likely to gamble in the past year compared to non-smokers, (ii) cigarette smokers were over three times more likely than non-smokers to be a problem gambler, (iii) alcohol consumption as measured by the number of units drunk on the person's heaviest drinking day was not significantly associated with having gambled in the past year, (iv) alcohol consumption as measured by the number of units drank on the person's heaviest drinking day in the past year was significantly associated with problem gambling, (v) health status was not significantly associated with past year gambling and (vi) the prevalence rate of problem gambling among those with poor health were over three times as likely to be a problem gambler compared to those with good health. Implications of these results are discussed.
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The present study examined whether the active component in tobacco, nicotine, can modulate cocaine craving in patients with a history of smoking crack cocaine when exposed to crack cocaine related environmental cues. Twenty patients, all cigarette smokers, were randomly assigned to nicotine (two 22 mg transdermal patches) or placebo in a single-dose, placebo-controlled, crossover, double-blind study. Craving and anxiety were measured before and after cocaine cues with visual analog scales for desire to use cocaine and mood. Skin conductance and skin temperature were recorded before and during cocaine cues. Following exposure to cocaine cues, all patients reported an increase in cocaine craving and anxiety relative to the pre-cue measures. Cue exposure also produced an increase in skin conductance and decrease in skin temperature. The cue-induced increase in cocaine craving was strongly enhanced by nicotine, while the increase in anxiety was slightly augmented. Cue-induced skin conductance and temperature responses were unaffected by nicotine. These findings show that cue-induced cocaine craving is enhanced by nicotine. This occurred in the absence of any tobacco smoking-related cues, suggesting that nicotine may have direct psychopharmacological effects on conditioned cocaine craving.
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While the majority of pathological gamblers are current cigarette smokers (CS), some have quit smoking (former smokers, FS) while others never smoked (never smokers, NS). The reasons for elevated smoking rates in pathological gambling are not known, but gamblers may use nicotine as a putative cognitive enhancer. This study evaluated impulsivity and cognitive flexibility in a sample of pathological gamblers with differing smoking status. Fifty-five subjects with pathological gambling (CS, n=34; FS, n=10; NS, n=11) underwent cognitive assessments using the Stop-Signal (SST) and Intradimensional/Extra-dimensional (ID/ED) set-shift tasks. CS reported less severe gambling problems than either FS or NS on the Yale Brown Obsessive Compulsive Scale modified for Pathological Gambling, and CS was associated with significantly fewer directional errors on the SST task, compared to NS. In addition, in CS, higher daily cigarette consumption was associated with fewer total errors on the ID/ED task. The potential role of nicotine as a cognitive enhancer was supported by objective tests of impulsivity and cognitive flexibility. Human laboratory studies using nicotine challenges in pathological gambling will shed further light on this relationship.
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This paper reviews evidence pertaining to the prevalence of common comorbid disorders, including alcohol use disorder, depression, substance use disorders, nicotine dependence, anxiety disorders and antisocial personality disorder, in population-representative samples of problem and pathological gamblers. A systematic search was conducted for peer-reviewed and unpublished articles reported between 1 January 1998 and 20 September 2010. Only studies which examined the prevalence of comorbid conditions in problem and/or pathological gamblers from a general population sample using randomized sampling methods and standardized measurement tools were included. Meta-analysis techniques were then performed to synthesize the included studies and estimate the weighted mean effect size and heterogeneity across studies. Eleven eligible studies were identified from the literature. Results from across the studies indicated that problem and pathological gamblers had high rates of other comorbid disorders. The highest mean prevalence was for nicotine dependence (60.1%), followed by a substance use disorder (57.5%), any type of mood disorder (37.9%) and any type of anxiety disorder (37.4%). However, there was evidence of moderate heterogeneity across studies, suggesting that rate estimates do not necessarily converge around a single population figure, and that weighted means should be interpreted with caution. Problem and pathological gamblers experience high levels of other comorbid mental health disorders and screening for comorbid disorders upon entering treatment for gambling problems is recommended. Further research is required to explore the underlying causes of variability observed in the prevalence estimates.
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To investigate dopaminergic neurotransmission in relation to monetary reward and punishment in pathological gambling. Pathological gamblers (PG) often continue gambling despite losses, known as 'chasing one's losses'. We therefore hypothesized that losing money would be associated with increased dopamine release in the ventral striatum of PG compared with healthy controls (HC). We used Positron Emission Tomography (PET) with [(11)C]raclopride to measure dopamine release in the ventral striatum of 16 PG and 15 HC playing the Iowa Gambling Task (IGT). PG who lost money had significantly increased dopamine release in the left ventral striatum compared with HC. PG and HC who won money did not differ in dopamine release. Our findings suggest a dopaminergic basis of monetary losses in pathological gambling, which might explain loss-chasing behavior. The findings may have implications for the understanding of dopamine dysfunctions and impaired decision-making in pathological gambling and substance-related addictions.
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Pathological gamblers (PGs) present with various forms of psychopathology, maladaptive personality traits, and gambling motivations. Some suggest that this variability supports classification of PGs into distinct subtypes. Subtyping models are thought to have implications for understanding pathological gambling (PG) etiology and treatment outcomes. This review evaluates the existing literature on the subtyping of PGs based on psychopathology, personality, and/or motivation for gambling. We conclude that three PG subtypes consistently emerge from the empirical literature, and should be the focus of future study. These subtypes closely parallel the three types of gamblers presented in Blaszczynski and Nower's (2002) conceptual pathways model. We suggest that future investigations on PG subtypes build upon the theoretical framework of the pathways model, but also address the limitations of prior studies.