Gender Differences in Treatment-Seeking British Pathological Gamblers

Abstract

Background and aim
Gambling is a widespread recreational activity in the UK. A significant percentage of gamblers develop subclinical or clinically relevant problem gambling issues, but only a low percentage of them seek treatment. Although characteristics of pathological gamblers from treatment-seeking population have been examined in some research, only a few studies have explored the differences between females and males. This study aimed to examine the gender-related differences in demographics, gambling measures, and clinical variables in an outpatient sample of pathological gamblers seeking treatment.

Methods
A total of 1,178 treatment-seeking individuals with gambling disorder were assessed at the National Problem Gambling Clinic in London. Sociodemographic characteristics, clinical variables, and gambling behavior habits were obtained during the assessment evaluation. Of the total sample, 92.5% were males and 7.5% were females.

Results
Males were more likely to be younger, white, and employed than females. In addition, compared to women, men showed a lower PGSI score, an earlier age of onset of gambling behavior, a higher gambling involvement, and preferred specific forms gambling. Female gamblers were more anxious and depressed, while men were more likely to use alcohol and illicit drugs.

Conclusions
Our findings support the importance of gender differences in a treatment-seeking population of pathological gamblers both in sociodemographic characteristics, gambling behavior variables, and clinical variables. Males and females might benefit from group-specific treatment.

Full text

Gender Differences in Treatment-Seeking British Pathological Gamblers
SILVIA RONZITTI
1,2,3
*, VITTORIO LUTRI
1,2
, NEIL SMITH
1
, MASSIMO CLERICI
1,3
and HENRIETTA BOWDEN-JONES
1,4
1
NPGC, National Problem Gambling Clinic, Central North West London NHS Foundation Trust, London, United Kingdom
2
Department of Surgery and Translational Medicine, University of Milano-Bicocca, Monza, Italy
3
Department of Mental Health, San Gerardo Hospital, Monza, Italy
4
Department of Medicine, Imperial College London, London, United Kingdom
(Received: July 16, 2015; accepted: March 22, 2016)
Background and aim: Gambling is a widespread recreational activity in the UK. A significant percentage of gamblers
develop subclinical or clinically relevant problem gambling issues, but only a low percentage of them seek treatment.
Although characteristics of pathological gamblers from treatment-seeking population have been examined in some
research, only a few studies have explored the differences between females and males. This study aimed to examine
the gender-related differences in demographics, gambling measures, and clinical variables in an outpatient sample of
pathological gamblers seeking treatment. Methods: A total of 1,178 treatment-seeking individuals with gambling
disorder were assessed at the National Problem Gambling Clinic in London. Sociodemographic characteristics,
clinical variables, and gambling behavior habits were obtained during the assessment evaluation. Of the total sample,
92.5% were males and 7.5% were females. Results: Males were more likely to be younger, white, and employed than
females. In addition, compared to women, men showed a lower PGSI score, an earlier age of onset of gambling
behavior, a higher gambling involvement, and preferred specific forms gambling. Female gamblers were more
anxious and depressed, while men were more likely to use alcohol and illicit drugs. Conclusions: Our findings support
the importance of gender differences in a treatment-seeking population of pathological gamblers both in socio-
demographic characteristics, gambling behavior variables, and clinical variables. Males and females might benefit
from group-specific treatment.
Keywords: gambling disorder, pathological gambling, treatment seeking, gender differences
INTRODUCTION
Gambling is a widespread recreational activity in the UK,
with the 2010 British Gambling Prevalence Survey report-
ing that 75% of males and 71% of females had gambled in
the previous year (Wardle et al., 2010). Although most
individuals gamble recreationally and do not develop
gambling-related problems, a smaller, but significant per-
centage of gamblers develop problem gambling issues. It
has been estimated that gambling disorder (GD) has a
prevalence rate that ranged between 0.3% and 5.3% of the
general population worldwide, with an estimated rate of
0.7–0.9 in the UK according to the criteria set by the fourth
edition of the Diagnostic and Statistical Manual of Mental
Disorders (Wardle et al., 2010). GD is characterized by
maladaptive patterns of gambling behavior with a natural
history characterized by chronicity and recurrence.
Although GD was traditionally classified as an impulse-
control disorder, the DSM-5 reclassified it into the “addic-
tion and related disorders”category, underlining multiple
similarities with substance use disorders (American Psychi-
atric Association, 2013).
Gender differences in problem gamblers among the
general population have been increasingly explored. Preva-
lence rates of GD among females were found to be less than
half, when compared to males (Blanco, Hasin, Petry,
Stinson, & Grant, 2006); however, figures on female prob-
lematic gambling are currently increasing as changes in the
gambling market, i.e., the availability of online, more
“tailored,”games, and in the cultural framework, are con-
tributing to increasing female gambling participation
(Griffiths, Wardle, Orford, Sproston, & Erens, 2009;
LaPlante, Nelson, LaBrie, & Shaffer, 2006). Female gam-
blers had a later initiation of problematic gambling, and a
two-fold faster development of GD (Nelson, LaPlante,
LaBrie, & Shaffer, 2006;Tavares, Zilberman, Beites, &
Gentil, 2001). Moreover, women were found to have a
preference for pure chance, “non-strategic”types of gam-
bling (Potenza et al., 2001). When examining psychopath-
ological correlates of GD, it was found that associations
between GD and substance abuse, major depressive epi-
sodes, and generalized anxiety disorder were stronger
among women (Petry, Stinson, & Grant, 2005).
Although characteristics of pathological gamblers from
the general population have been examined on a satisfactory
sample, a few studies, to our knowledge, have examined the
treatment-seeking population, reporting significant inter-
gender differences. Among the difficulties of studying
this population are the relatively low percentage of indivi-
duals who seek treatment for GD, 9.9% according to one
study (Slutske, 2006), and the high rate of dropouts
* Corresponding author: Silvia Ronzitti; Department of Surgery
and Translational Medicine, University of Milano-Bicocca, Via
Cadore 48, 20900 Monza (MB), Italy; Phone: +39 346 0045094;
E-mail: silvia.ronzitti@gmail.com
© 2016 The Author(s)
FULL-LENGTH REPORT Epub ahead of print: June 27, 2016
Journal of Behavioral Addictions 5(2), pp. 231–238 (2016)
DOI: 10.1556/2006.5.2016.032

(Melville, Casey, & Kavanagh, 2007). A consistently
reported result was that women were older in age, and had
initiated problematic gambling behavior at an older age
than men (Echeburúa, González-Ortega, de Corral, & Polo-
L´opez, 2011;Granero et al., 2009;Tang, Wu, & Tang,
2007). Men, in turn, reported more debt and more money
spent on gambling (Granero et al., 2009;Lahti, Halme,
Pankakoski, Sinclair, & Alho, 2013) as well as more
relational difficulties due to gambling (Granero et al., 2009).
The psychopathological profile of women was found to
be poorer than that of males, with higher scores for depres-
sion and anxiety; moreover, women were more likely to
report the use of gambling to regulate negative affect
(Granero et al., 2009). Due to the scarcity of data on this
specific population, and the absence of treatment-seeking
related data in the UK, we aimed to explore sociodemo-
graphic, gambling, and clinical correlates of GD, with a
particular attention to gender differences, in a British sample
of treatment-seeking pathological gamblers.
METHODS
Participants
Data were collected from clients who were voluntarily
seeking treatment at the National Problem Gambling Clinic
(NPGC) between January 2011 and December 2013. Over
the course of the present study, we received 1,741 referral
forms. From this initial sample, there were a number of
clients excluded from the study because of not attending or
not completing assessments (n=563). The final sample
therefore consisted of 1,178 clients.
Procedure
The NPGC is the first and only National Health Service
clinic in the UK that provides treatment for pathological
gamblers. Cognitive behavioral therapy is the main type of
treatment offered, and is delivered in three different ways; in
a group setting, individually, and remotely over the phone
for those who are unable to travel weekly to the clinic. On
their first visit, clients are assessed thoroughly to gain
information about the clients’gambling behavior and related
information, including clinical variables (e.g., patient health
questionnaire and generalized anxiety disorder). Sociode-
mographic variables were obtained from the referral form in
which each client is required to fill in prior to assessment.
During the assessment, clients were informed that informa-
tion collected from the referral and assessment forms would
be analyzed by researchers to increase the understanding
about GD. Oral consent was obtained from clients before
filling in the assessment form.
Measures
Clinical interview. During the interview, clients were asked
to describe their gambling behavior (type of gambling,
frequency, money spent, age noted gambling became prob-
lematic, history of gambling behavior, debts, total amount
lost on gambling, and previous treatment) psychiatric,
medical and forensic histories, family psychiatric history,
family structure, and impact of gambling on family and
personal histories.
Assessment forms
Self-administered questionnaires
•Problem Gambling Severity Index (PGSI). Validated
by a number of studies (Holtgraves, 2009), the PGSI is
a nine-item questionnaire, which measures gambling
severity. It consists of four questions that assess prob-
lematic gambling behavior and five questions that
assess adverse consequences of gambling. The score
that can be obtained from the PGSI ranges from 0 to
27. A score of 8 and above indicates a “problem”
gambler (Ferris & Wynne, 2001).
•Patient Health Questionnaire (PHQ-9). The PHQ-9 is a
nine-item instrument, which is widely used to measure
the severity of depression. The questionnaire evaluates
each of the nine DMS-IV criteria for depression
(Kroenke, Spitzer, & Williams, 2001). Scores of 5,
10, 15, and 20 are used as the cutoff points for mild,
moderate, moderately severe, and severe depression.
The PHQ-9 has been commended for its high sensitiv-
ity and specificity for diagnosing depression, good
internal consistency, convergent and discriminant
validity, robustness of factor structure, and responsive-
ness to change (Kroenke, Spitzer, Williams, & Löwe,
2010).
•Generalized Anxiety Disorder (GAD-7). The widely
used seven-item GAD-7 measures anxiety over the
previous two weeks. Scores range from 0 to 27; Scores
of 5, 10, and 15 are taken as the cutoff points for mild,
moderate, and severe anxiety (Kroenke, Spitzer,
Williams, Monahan, & Löwe, 2007). The GAD-7 has
been credited with having good convergent validity
with other measures of anxiety (Kroenke et al., 2010)
and described as having good sensitivity and specifici-
ty for GAD-7 (Spitzer, Kroenke, Williams, & Löwe,
2006).
•Alcohol Use Disorders Identification Test-Consump-
tion Questions (AUDIT-C). The AUDIT-C consists of
three questions, two of which assess regular drinking in
terms of frequency and quantity, the third assessing
binge drinking, which is defined as six or more alcoholic
drinks in one sitting, at least once a month in the
preceding three months (Bush, Kivlahan, McDonell,
Fihn, & Bradley, 1998). Answers are ranked from 0 to 4,
and the final score is the sum of each question. A score of
5 or more indicates hazardous drinking. The AUDIT-C
is a validated and well-established screening tool
(Meneses-Gaya et al., 2010).
•Tobacco behavior. All subjects were questioned about
their tobacco use [frequency (i.e., daily) and amount,
i.e., 20].
•Drug use. To determine other drug use, we adminis-
tered a specific questionnaire that asked about individ-
ual drugs (marijuana, cocaine, crack cocaine, opiates,
opiate substitutes, and ecstasy). For each drug, we
assessed lifetime use, current use, and number of days
in the past month in which the drug was used.
•Type of gambling. To determine the gambling
behavior, we administered a specific questionnaire
232 |Journal of Behavioral Addictions 5(2), pp. 231–238 (2016)
Ronzitti et al.

evaluating the specific forms of gambling in which the
client was involved. For each type of gambling activi-
ty, we asked if the client had ever practiced it, if she
had gambled on it in the past year and in the last 30
days, the number of gambling days in the past 30 days
and the total time spent per typical day. The specific
forms of gambling we inquired about were lottery or
scratch cards, internet gambling on computer or mobile
phone, and interactive TV or telephone; betting sports
at bookmaker or sports events, gaming machines,
Fixed Odd Betting Terminal (FOBT), casino table
games, bingo, and other forms of gambling.
Statistical analysis
Analysis was carried out using SPSS version 20.0 for
Windows. All the hypothesis tests were performed using
two-sided significance level (α=0.05). First, differences
between the genders were tested for the significance with
chi-square and Fisher’s exact testing for categorical vari-
ables, and two-tailed t-test for continuous variables, and we
calculated the odd ratio for significant variables. For con-
tinuous variables, we also used a non-parametric alternative
to the t-test (Mann–Whitney U) as a control test, which is
usually used when there was a reason to believe that data
were not normally distributed. Since the results were iden-
tical, we have only reported the t-test results. Finally,
variables were entered into a logistic regression to determine
whether gender was related to categorical- and continuous-
independent variables, using Nagelkerke’sR
2
(Nagelkerke,
1991). Since the previous research in this field is limited, we
used stepwise methods to include all variables in the
analysis as predictors, independently from the significance
shown at bivariate level. We used gender as dependent
variable.
Ethics
Ethical approval was not needed as the collected data were a
part of the clinic’s standard battery of assessment forms.
RESULTS
Sociodemographic characteristics
Of the 1,178 pathological gamblers assessed, 1,090 (92.5%)
were males and 88 (7.5%) were females. The subjects were
adults (18 years or older) with an average age of 36 years
old. Most of the subjects were white (74.8%), single
(53.7%), had at least a secondary educational degree
(77.8%), and were employed (66.6%). Males were younger
than females (average age of 35 versus 41, p<.001) and
were more likely to be white (p=.016; OR =1.75, 95% CI:
1.11; 2.79) and employed (p<.001; OR =2.06, 95% CI:
1.32; 3.23) (Table 1).
Gambling behavior
In terms of GD severity, there were significant differences in
PGSI scores between males and females (average 19.67
versus 21.61, p=.001). Furthermore, men presented earlier
onset of gambling than women (average 22.97 versus 30.68,
p<.001), and longer duration of GD before contacting the
clinic (mean 12.23 versus 9.52, p=.048). Information about
the type of gambling activity over the last year was available
Table 1. Sociodemographic characteristics of the sample by gender (n=1,178)
Variable
Male
(n=1,090)
N(%)
Female
(n=88)
N(%)
Total
(n=1,178)
N(%) OR (CI 95%)
Age
Mean (SD) 35.34 (10.72) 41.09 (9.95) 35.77 t=–4.839
(p<.001)
Ethnicity
White 791 (75.7%) 55 (64.0%) 846 (74.8%) 1.75 (1.11; 2.79) X
2
=5.811
(p=.016)Not white 254 (24.3%) 31 (36.0%) 285 (25.2%) 1.00
Marital status
Married or cohabitant 385 (38.2%) 25 (32.0%) 410 (37.7%) X
2
=7.259
(p=.064)Divorced or separated 79 (7.8%) 11 (14.1%) 90 (8.3%)
Widowed 2 (0.2%) 1 (1.3%) 3 (0.3%)
Single 543 (53.8%) 41 (52.6%) 584 (53.7%)
Employment
Employed 718 (67.9%) 42 (50.6%) 760 (66.6%) 2.06 (1.32; 3.23) X
2
=41.957
(p<0.001)Unemployed 117 (16.7%) 10 (12.1%) 187 (16.4%) 1.00
Student 39 (3.7%) 1 (1.2%) 40 (3.5%)
Retired 16 (1.5%) 2 (2.4%) 18 (1.6%)
Other 108 (10.2%) 28 (33.7%) 136 (11.9%)
Educational level
None 141 (15.6%) 7 (10.3%) 148 (15.2%) X
2
=8.701
(p=.034)CGSE or equivalent 429 (47.3%) 35 (51.5%) 464 (47.6%)
Degree or more 278 (30.7%) 16 (23.5%) 294 (30.2%)
Other 58 (6.4%) 10 (14.7%) 68 (7.0%)
Journal of Behavioral Addictions 5(2), pp. 231–238 (2016) |233
Treatment-Seeking Pathological Gamblers

for 1087 patients. The most popular gambling activities in
the year prior to the assessment were lottery/scratch cards
(77.9%), betting at bookmakers or at sports events (65.8%)
and FOBT gambling (64.8%). Data about the type of
gambling in the past month were available for 903 subjects.
The most popular gambling activities in the 30 days prior to
assessment were lottery and scratch cards (56.4%) FOBT
gambling (52.0%) and betting at bookmakers or at sports
events (47.4%). There were significant sex differences:
males were more likely to be involved in casino table games
(p=.002, OR =2.30, 95% CI: 1.35; 3.91), FOBT (p<.001,
OR =4.97, 95% CI: 3.00; 8.22), sports betting (p<.001,
OR =15.77, 95% CI: 8.01; 31.04), and other forms of
gambling (p=.004, OR =6.28, 95% CI: 1.52; 25.83), while
women were more likely to play bingo (p<.001, OR =
0.13, 95% CI: 0.08; 0.23). The analysis of the gambling
behavior in the 30 days prior to assessment confirmed one-
year results for FOBT (p<.001, OR =3.40, 95% CI: 1.93;
6.00), sports betting (p<.001, OR =10.17, 95% CI: 4.35;
23.79), and bingo (p<.001, OR =0.12, 95% CI: 0.05;
0.28). Furthermore, males were more likely to be involved
in multiple types of gambling both in last-year data (average
3.93 versus 3.01; p<.001) and in data from the last 30 days
(average 2.59 versus 2.13; p=.002), as reported in Table 2.
Clinical variables
Female gamblers were more anxious and depressed with a
higher mean score in GAD-7 (12.64 versus 10.10, p<.001)
and PHQ-9 scales (16.63 versus 12.56, p<.001), while men
had a higher mean score in the AUDIT-C scale (4.78 versus
3.41, p<.001). Furthermore, men were more likely to use
drugs (p<.007, OR =3.75, 95% CI: 1.35; 10.40) and
alcohol (p<.001, OR =2.35, 95% CI: 1.45; 3.81) in the
30 days prior to assessment. No significant gender-related
differences were found in smoking behavior (Table 3).
Logistic regression analysis
Variables with significant gender results (p<0.01) were
considered together in a multivariate analysis; the most
salient correlates of gender were: male are more likely to
be engage in FOBT (p<.001, AOR 0.09, 95% CI: 0.03;
0.34) and sports betting gambling (p=0.011, AOR 0.06,
95% CI: 0.01; 0.55), while women are more likely to be
older (p=.001, AOR 1.08, 95% CI: 1.03; 1.13), report an
higher PHQ-9 score (p=.004, AOR 1.12, 95% CI: 1.04;
1.21), and to engage in bingo (p=.006, AOR 113.71, 95%
CI: 3.94; 3,284.83) (Table 4).
DISCUSSION
The present study aimed to examine sociodemographic, gam-
bling-related, and clinical variables in a treatment-seeking
sample of pathological gamblers as well as to analyze gen-
der-related characteristics. The data suggest relevant differ-
ences between male and female treatment-seeking gamblers.
Our sociodemographic findings were partially in accor-
dance with the few similar studies in the literature as the
majority of the treatment seekers had at least a secondary
degree, were employed, and belonged to the country’s
ethnic majority (Braun, Ludwig, Sleczka, Bühringer, &
Kraus, 2014;Volberg, 1994). There were mixed findings
as to how marital status influences the odds of attending
treatment (Braun et al., 2014;Granero et al., 2009;
Weinstock, Burton, & Rash, 2011), with one similar study
finding that female gamblers were more likely to be di-
vorced/widowed (Echeburúa et al., 2011). These results
might be partially explained by the fact that, as shown by
Evans and Delfabbro (2005), the primary motivations of
help seeking among problem gamblers were crisis driven,
and therefore the loss of a relationship, or a job, would be a
motivator for seeking professional help. However, in the
present study, a majority of male and female subjects were
employed, as was the case in one of the previous study
(Lahti et al., 2013), and more than half of male and female
subjects were never married, and not currently in a relation-
ship. We can also hypothesize that differing levels of
availability and perception of professional help seeking for
problematic gambling might influence treatment-seeking
rates, regardless of family status. In keeping with previous
findings (Echeburúa et al., 2011), a significant difference in
age between male and female participants was found in our
sample as treatment-seeking females were significantly
older than their male counterparts.
Another important result in the present study was that
males were more likely than females to be employed, and to
belong to the majority ethnic group. To our knowledge, this
is the first such finding on a large sample. Although many
research studies have shown that GD prevalence is higher
among minority ethnicity groups; only a small percentage
from this group has sought help from the clinic (25.2%).
Females from ethnic minorities are more likely to seek
treatment compared to men (36.0% versus 24.3%), con-
firming that they may be a particular group at risk of
developing GD.
Together, these findings support other studies and high-
light the need to make the clinic services more available or
attractive to minority groups. Language difficulties and
cultural barriers could negatively impact on treatment entry
and utilization among a non-British population (Braun
et al., 2014;Potenza et al., 2001). Lower socioeconomic
class and an ethnic minority status have already been
recognized as probable obstacles to treatment access (Braun
et al., 2014;Weinstock et al., 2011); although the results in
the present study must be interpreted with caution, as
neither employment status nor ethnicity can be considered
as a direct measure of the socioeconomic status, they might
suggest that the negative effects of socioeconomic vulner-
ability factors on treatment access can be even greater on
women.
In relation to gambling behavior variables, and unlike
previous studies (Echeburúa et al., 2011;Lahti et al., 2013),
we found that women had higher gambling severity scores.
This difference was statistically significant, although small,
when considering the effect size. One possible explanation
could be that the increased gambling severity among treat-
ment-seeking women may reflect the fact that women are
less likely than men to seek treatment, and therefore the
severity of the cases that reach clinical attention might be
higher. Another possible explanation is the fact that, in the
234 |Journal of Behavioral Addictions 5(2), pp. 231–238 (2016)
Ronzitti et al.

Table 2. Comparison of gambling behavior by sex
Variable Male Female OR (CI 95%)
Problem Gambling Severity Index mean (SD) 19.67 (5.07) 21.61 (4.80) t=–3.345 (p=.001)
Age of onset (years) mean (SD) 22.97 (9.07) 30.68 (11.98) t=–4.996 (p<.001)
Duration of GD (years) mean (SD) 12.23 (10.53) 9.52 (8.43) t=1.977 (p<.048)
Lottery or
scratch cards
Last year Yes N(%) 783 (77.6%) 64 (82.1%) X
2
=0.833 (p=.361)
Past 30 days Yes N(%) 469 (56.0%) 40 (60.6%) X
2
=0.520 (p=.471)
Internet on computer/
mobile phone,
interactive TV or
telephone
Last year Yes N(%) 627 (62.1%) 45 (57.7%) X
2
=0.607 (p=.436)
Past 30 days Yes N(%) 315 (37.6%) 31 (47.0%) X
2
=2.256 (p=.133)
Casino table games Last year Yes N(%) 429 (42.5%) 19 (24.4) 2.30 (1.35; 3.91) X
2
=9.853 (p=.002)
Past 30 days Yes N(%) 145 (17.3%) 7 (10.6%) X
2
=1.972 (p=.160)
Gaming machine Last year Yes N(%) 536 (53.1%) 48 (61.5%) X
2
=2.063 (p=.151)
Past 30 days Yes N(%) 295 (35.2%) 29 (43.9%) X
2
=2.010 (p=.156)
FOBT Last year Yes N(%) 681 (67.5%) 23 (29.5%) 4.97 (3.00; 8.22) X
2
=45.828 (p<.001)
Past 30 days Yes N(%) 453 (54.1%) 17 (25.8%) 3.40 (1.93; 6.00) X
2
=19.720 (p<.001)
Sports at bookmaker
or sports event
Last year Yes N(%) 705 (69.9%) 10 (12.8%) 15.77 (8.01; 31.04) X
2
=104.686 (p<.001)
Past 30 days Yes N(%) 422 (50.4%) 6 (9.1%) 10.17 (4.35; 23.79) X
2
=41.908 (p<.001)
Bingo Last year Yes N(%) 57 (5.6%) 24 (30.8%) 0.13 (0.08; 0.23) X
2
=66.248 (p<.001)
Past 30 days Yes N(%) 15 (1.8%) 9 (13.6%) 0.12 (0.05; 0.28) X
2
=33.172 (p<.001)
Others Last year Yes N(%) 143 (14.2%) 2 (2.6%) 6.28 (1.52; 25.83) X
2
=8.440 (p=.004)
Past 30 days Yes N(%) 53 (6.3%) 2 (3.0%) X
2
=1.166 (p=.280)
Involvement mean (SD)
(number of different
gambling activities played)
Last year 3.92 (1.52) 3.01 (1.20) t=6.330 (p<.001)
Past 30 days 2.58 (1.36) 2.13 (1.09) t=3.173 (p<.002)
Note. FOBT =Fixed Odd Betting Terminal.
Journal of Behavioral Addictions 5(2), pp. 231–238 (2016) |235
Treatment-Seeking Pathological Gamblers

literature, women reported quicker development of prob-
lematic gambling, compared to men (Nelson et al., 2006).
A significant gender difference in the age of onset of
problematic gambling behavior was also found, with
females beginning gambling much later than males and
reporting shorter of problematic gambling before contacting
the clinic. Possible explanations for this difference have
been grouped into two main conjectures: a direct effect of
gender on problematic gambling, and a concomitance of
gender, sociodemographic, and clinical factors (the “gender-
as-proxy”theory; Nelson et al., 2006). The empirical evi-
dence supporting a “telescoping effect”in the course of GD
among women is consistent, suggesting that women are
more likely than men to move rapidly through the multiple
landmark events associated with the development and pro-
gression of GD (Grant, Oldaug, & Mooney et al., 2012;
Potenza et al., 2001). However, a recent study among a non-
treatment population did not support this theory, and sug-
gested that the use of treatment-seeking samples may lead to
incorrect conclusion about gender differences (Slutske,
Piasecki, Deutsch, Statham, & Martin, 2015).
Bivariate and multivariate analysis on preferred gambling
types showed that male gamblers had a preference for
gambling on fixed-odds-betting-terminals, and sports bet-
ting, whereas gambling on bingo was strongly correlated with
female gender. The distinction between FOBTs and regular
gaming machines is another new finding of the present study.
Contrary to the previous studies (Petry, 2003), we did not
find significant inter-gender difference concerning lower
stakes, regular gambling machines otherwise known as “fruit
machines.”However, in our analysis, males were shown to
have a preference for higher stakes gambling machines
(FOBT). It is possible to mention that, as a partial explana-
tion, the effect of structural and situational characteristics,
such as the size of bets and wins, payout schedule, and venues
in which these forms of gambling are available, namely,
authorized betting shops for FOBT, as opposed to pubs,
clubs, and arcades, as is the case for regular gaming machines
(Griffiths, 1993), as well as different impulsivity profiles
between men and women (Echeburúa et al., 2011); a similar
explanation might be applied, on the other hand, to preference
for bingo among women in our sample (Ledgerwood & Petry,
2006). Political, social, and cultural determinants, e.g., the
perceived acceptability/unacceptability of male and female
gamblers in different gambling settings, might also play a
very important role in gender-based preference for specific
gambling types (LaPlante et al., 2006).
We found a small, although significant, difference in
gambling involvement, in which male gamblers participated
to more gambling activities than females, although they had
lower gambling severity. The role of gambling involvement
in treatment-seeking individuals has not yet been satisfac-
torily explored; however, it would appear that, in the general
population, gambling involvement is a better predictor of
problematic gambling development than any individual
form of gambling, with the notable exception of FOBT
machines, the usage of which had a strong association with
problematic gambling behavior (LaPlante, Nelson, LaBrie,
& Shaffer, 2011); this finding might partially explain the
high rates of FOBT players in our sample.
Analysis of psychopathological variables showed that
women had higher rates of anxious and depressive symp-
toms with respect to men. These results reflect previous
findings on the GD population (Granero et al., 2009), and
might suggest that women are more inclined to utilize
gambling in an escape-oriented paradigm, a result that is
compatible with the pathways model of problem gambling
initiation, as postulated by Blaszczynski and Nower (2002).
Similar to the previous research (Grant & Potenza, 2005),
we found no significant difference between males and
females for tobacco smoking. However, in contrast with
the previous results (Granero et al., 2009), we found that
Table 3. Comparison of clinical variables by sex
Variable Male Female OR (CI 95%)
Patient Health Questionnaire score mean (SD) 12.56 (7.12) 16.63 (7.19) t=–4.941 (p<.001)
Generalized Anxiety Disorder score mean (SD) 10.10 (6.11) 12.64 (6.12) t=–3.609 (p<.001)
Alcohol Use Disorders Identification Test
consumption score mean (SD)
4.78 (2.87) 3.41 (2.83) t=4.091(p<.001)
Use of drugs in
pre-assessment month
Yes N(%) 171 (17.0%) 4 (5.2%) 3.75 (1.35; 10.40) X
2
=7.401 (p=.007)
Use of alcohol in
pre-assessment month
Yes N(%) 789 (78.7%) 47 (61.0%) 2.35 (1.45; 3.81) X
2
=12.702 (p<.001)
Smokers Yes N(%) 463 (63.5%) 40 (65.6%) X
2
=0.103 (p=.748)
Table 4. Significant results of logistic regression analysis
BSE Exp (B) 95% CI p
Age of onset 0.079 0.023 1.04 1.03; 1.13 .001
PHQ-9 score 0.112 0.039 1.12 1.04; 1.21 .004
Engaging in FOBT gambling −2.368 0.654 0.09 0.02; 0.34 <.001
Engaging in sports betting −2.796 1.106 0.06 0.01; 0.55 .011
Engaging in bingo 4.734 1.716 113.71 3.93; 3,284.83 .006
Note. PHQ-9 =Patient Health Questionnaire; FOBT =Fixed Odd Betting Terminal. Adjusted odd ratio [i.e., Exp (B)] greater than 1 imply
that variables are more likely to be present in females than males. Number of observations =380, X
2
=82.229, R
2
=.476, and p<0.001.
236 |Journal of Behavioral Addictions 5(2), pp. 231–238 (2016)
Ronzitti et al.

males had higher levels of alcohol abuse, and higher rates of
consumption of illicit drugs. It was proposed that, in the
general population, social gender roles and biological dif-
ferences in relation to alcohol might mediate a higher level
of alcohol consumption for males. This explanation would
also be in concordance with previous findings among
treatment-seeking pathological gamblers, showing that pa-
rental history of alcohol abuse did not significantly differ
between genders (Grant & Kim, 2002).
It is to be mentioned that 32% of the original sample did
not complete the assessment procedure and was therefore
excluded from our analysis; one possible hypothesis on how
these assessment dropout rates might have affected our
results is that subjects who did not complete the assessment
procedures might have been patients with less severe symp-
toms who did not perceive the treatment of their gambling
behavior as essential; another hypothesis is that subjects who
did not complete the assessment were, on the other hand,
more severe gamblers, e.g., the “antisocial impulsivist”
gamblers, as described by Blaszczynski and Nower (2002).
The present study presented some limitations. First, we
only considered a treatment-seeking population, which was
shown to differ from the general gambling population, with
lower proportions of women, people from ethnic minorities,
and less severe problematic gamblers (Braun et al., 2014);
moreover, the clinic’s geographical location in the heart of a
densely populated and ethnically diverse city, as well as the
clinic’s own referral process and ethnic preferences in terms
of gambling behavior and gambling treatment seeking might
have further influenced the results in terms of our sample’s
ethnic composition (Forrest & Wardle, 2011). Therefore, the
findings in the present study cannot be generalized to all
pathological gamblers. A further limitation was the fact that
the measures we used were self-reported, and therefore
might suffer from recall biases. Moreover, the cross-
sectional nature of the study does not allow to verify clinical
and sociodemographic variables over time in their relation
to gambling behavior; therefore, longitudinal studies on
gender differences among treatment-seeking gamblers, in-
cluding the evolution of gambling-related, and clinical
variables would help shed more light on how gender
differences influence the natural history of GD. Among the
strengths of this study, we cite its large sample, the fact this
is the first study of its kind in the UK and the large number
of gambling-related variables gathered.
In conclusion, our findings support the importance of
bearing in mind gender differences in a treatment-seeking
population of pathological gamblers, not only in terms of
sociodemographic characteristics, but also in terms of dif-
ferent gambling behaviors and clinical variables. On the
grounds of this work, we highlight the need for new
methods of empowerment and involvement in treatment,
particularly for women, to improve the access and retention
in treatment. An even greater deal of attention is suggested
in the treatment of women from minority ethnic groups and
lower socioeconomic classes.
Second, we suggest that the differences between higher
and lower stakes machines should be considered in further
studies on GD. A third implication of this study is that, due
to different gambling behavior patterns, gambling motives,
and psychiatric comorbidities, male and female gamblers
might benefit from group-specific treatment offers.
Founding sources: No financial support was received for
this study.
Authors’contribution: SR: study concept and design, anal-
ysis and interpretation of data, drafting of manuscript; VL:
interpretation of data, drafting of manuscript; NS: acquisi-
tion of data; MC: study supervision; HBJ: interpretation of
data, study supervision, critical revision.
Conflict of interest: The authors declare no conflict of
interest.
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