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Problem gambling and family violence: Prevalence and patterns in treatment-seekers

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  • Australian Centre for Heart Health

Abstract and Figures

The primary aim of this study was to explore the prevalence and patterns of family violence in treatment-seeking problem gamblers. Secondary aims were to identify the prevalence of problem gambling in a family violence victimisation treatment sample and to explore the relationship between problem gambling and family violence in other treatment-seeking samples. Clients from 15 Australian treatment services were systematically screened for problem gambling using the Brief Bio-Social Gambling Screen and for family violence using single victimisation and perpetration items adapted from the Hurt-Insulted-Threatened-Screamed (HITS): gambling services (n=463), family violence services (n=95), alcohol and drug services (n=47), mental health services (n=51), and financial counselling services (n=48). The prevalence of family violence in the gambling sample was 33.9% (11.0% victimisation only, 6.9% perpetration only, and 16.0% both victimisation and perpetration). Female gamblers were significantly more likely to report victimisation only (16.5% cf. 7.8%) and both victimisation and perpetration (21.2% cf. 13.0%) than male gamblers. There were no other demographic differences in family violence prevalence estimates. Gamblers most commonly endorsed their parents as both the perpetrators and victims of family violence, followed by current and former partners. The prevalence of problem gambling in the family violence sample was 2.2%. The alcohol and drug (84.0%) and mental health (61.6%) samples reported significantly higher rates of any family violence than the gambling sample, while the financial counselling sample (10.6%) reported significantly higher rates of problem gambling than the family violence sample. The findings of this study support substantial comorbidity between problem gambling and family violence, although this may be accounted for by a high comorbidity with alcohol and drug use problems and other psychiatric disorders. They highlight the need for routine screening, assessment and management of problem gambling and family violence in a range of services.
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Short Communication
Problem gambling and family violence: Prevalence and patterns
in treatment-seekers
N.A. Dowling
a,b,c,
, A.C. Jackson
b
, A. Suomi
b,d
,T.Lavis
e
,S.A.Thomas
f
,J.Patford
b
,P.Harvey
e
, M. Battersby
e
,
J. Koziol-McLain
g
,M.Abbott
h
, M.E. Bellringer
h
a
School of Psychology, Deakin University, Australia
b
Problem Gambling Research and Treatment Centre, University of Melbourne, Australia
c
School of PsychologicalSciences, Monash University, Australia
d
Centre for Gambling Research, The Australian National University, Australia
e
Flinders Human Behaviour & Health Research Unit, School of Medicine, Flinders University, Australia
f
Problem Gambling Research and Treatment Centre, Monash University, Australia
g
Trauma Research Centre, Auckland University of Technology, New Zealand
h
Gambling and Addictions Research Centre,Faculty of Health and Environmental Sciences, Auckland University of Technology, New Zealand
HIGHLIGHTS
The prevalence of any family violence in treatment-seeking gamblers was 33.9%.
Family violence victimisation prevalence was 27.0% and perpetration was 22.9%.
Parents and current or former partners were the most common perpetrators and victims.
Prevalence was higher in alcohol/drug (84.0%) and mental health (61.6%) services.
The prevalence of problem gambling in the family violence sample was 2.2%.
abstractarticle info
Available online 10 July 2014
Keywords:
Problem gambling
Family violence
Domestic violence
Prevalence
Alcohol
Mental health
The primaryaim of this study was to explore the prevalence and patterns of familyviolence in treatment-seeking
problem gamblers. Secondary aims were to identify the prevalence of problem gambling in a family violence
victimisation treatment sample and to explore the relationship between problem gambling and family violence
in other treatment-seeking samples. Clients from 15 Australian treatment services were systematically screened
for problem gambling using the Brief Bio-Social Gambling Screen and for family violence using single
victimisation and perpetration items adapted from the Hurt-Insulted-Threatened-Screamed (HITS): gambling
services (n= 463), family violence services (n=95),alcoholanddrugservices(n= 47), mental health services
(n=51),andnancial counselling services (n= 48). The prevalence of family violence inthe gamblingsample
was 33.9% (11.0% victimisation only, 6.9% perpetration only, and 16.0% both victimisation and perpetration).
Female gamblers were signicantly more likely to report victimisation only (16.5% cf. 7.8%) and both
victimisation and perpetration (21.2% cf. 13.0%) than male gamblers. There were no other demographic differ-
ences in family violence prevalence estimates. Gamblers most commonly endorsed their parents as both the
perpetrators and victims of familyviolence,followed bycurrent and former partners. The prevalence of problem
gambling in the family violence sample was 2.2%. The alcohol and drug (84.0%) and mental health (61.6%)
samples reported signicantly higher rates of any family violence than the gambling sample, while the nancial
counselling sample (10.6%) reported signicantly higher rates of problem gambling than the family violence
sample. The ndings of this study support substantial comorbidity between problem gambling and family
violence, although this may be accounted for by a high comorbidity with alcohol and drug use problems and
other psychiatric disorders. They highlight the need for routine screening, assessment and management of
problem gambling and family violence in a range of services.
© 2014 Elsevier Ltd. All rights reserved.
Addictive Behaviors 39 (2014) 17131717
Corresponding authorat: Deakin University, School of Psychology, Faculty of Health, MelbourneBurwood Campus, Building W, 221 Burwood Highway,Burwood, VIC 3125, Australia.
Tel.: +61 3 9244 5610; fax: +61 3 9244 6858.
E-mail address: nicki.dowling@deakin.edu.au (N.A. Dowling).
http://dx.doi.org/10.1016/j.addbeh.2014.07.006
0306-4603/© 2014 Elsevier Ltd. All rights reserved.
Contents lists available at ScienceDirect
Addictive Behaviors
1. Introduction
Despitesomeequivocalndings (Schluter, Bellringer, & Abbott,
2007; Schluter, Abbott, & Bellringer, 2008), there is growing evi-
dence that suggests a signicant association between problem gam-
bling and family violence. Much of this evidence is derived from
studies estimating the prevalence of intimate partner violence
(IPV) in problem gambling samples. Despite considerable methodo-
logical differences, most of the studies in this area report past year or
lifetime IPV victimisation estimates ranging from 60% to 69%
(Echeburua, Gonzalez-Ortega, De Corral, & Polo-Lopez, 2011;
Kausch, Rugle, & Rowland, 2006; Korman et al., 2008). In contrast,
Raylu and Oei (2009) found that 7% of 440 treatment-seeking
problem gamblers in Australia reported spouse assaultand 20%
reported recent experience of family violence and intimidationin
clinical interviews. There is also limited evidence that a signicant
proportion (56%) of problem gamblers report past year IPV perpetra-
tion (Korman et al., 2008). Findings relating to gender differences in
these studies are mixed, with some indicating that women (100%)
are more likely to report lifetime abuse victimisation than men
(69%) (Kausch et al., 2006) and others indicating higher rates of inju-
ry perpetration by women (49%) than men (22%) (Korman et al.,
2008). Echeburua et al. (2011) also found that retirement and
prolonged lowemployment were independently related to IPV
victimisation in female pathological gamblers.
Other evidence is derived from studies investigating rates of
problem gambling in IPV offender samples from batterer interven-
tion programs in the US. These studies have identied rates of prob-
lem or pathological gambling ranging from 1 to 24% (Braseld,
Shorey, Febres, Strong, & Stuart, 2011; Braseld et al., 2012;
Rothman, Johnson, & Hemenway, 2006). Although these ndings
suggest that problem gambling is likely over-represented in sam-
ples of IPV offenders, there are currently no prevalence estimates
of problem gambling in samples of individuals presenting to treat-
ment services for IPV or family violence victimisation experiences.
Given that alcohol and substance use disorders and psychiatric
disorders are highly comorbid with both problem gambling (Dowling
et al., in press; Lorains, Cowlishaw, & Thomas, 2011) and family violence
(Krug, Dahlberg, Mercy, Zwi, & Lorenzo, 2002), there are surprisingly
few studies that explore their relationship in other treatment-
seeking samples. In a sample of 605 out-of-treatment female sub-
stance abusers, Cunningham-Williams, Abdallah, Callahan, and
Cottler (2007) found that problem gamblers were more likely to re-
port experiencing parental abuse in their childhoods than non-
problem gamblers.
Although this literature suggests that problem gambling and family
violence are highly comorbid, it is difcult to validly compare the rates
from the available studies as they are generally limited to IPV, employ
US samples, and fail to employ validated instruments. The primary
aim of the present study was to explore the prevalence and patterns
of family violence in an Australian sample of treatment-seeking
problem gamblers. Secondary aims were to identify the prevalence of
problem gambling in a family violence victimisation treatment sample
and explore the relationship between problem gambling and family
violence in other treatment-seeking samples.
2. Method
2.1. Participants and procedure
In this cross-sectional study, clients from 15 treatment services across
14 Australian agencies were systematically screened for problem gam-
bling and family violence: 8 gambling services (clients seeking treatment
for their own gambling problems) (n= 463), 2 family violence services
(clients seeking treatment for family violence victimisation) (n=95),2
alcohol and drug services (n= 47), 1 mental health services (n=51),
and 2 nancial counselling services (n= 48). Most services were located
in Victoria (n= 11), with smaller numbers from Tasmania (n=3)and
South Australia (n= 1). Participating agencies administered the screen-
ing questions to all new clients at intake. Agencies screened for between
1 and 19 months (median = 4.0 months) and the number of clients
screened at each agency ranged from 9 to 199 (M= 47.2, SD = 52.7,
median = 24). Data were collected from August 2009 to March 2012.
The resulting sample comprised 704 clients (364 men, 320 women, 20
unspecied) ranging in age from 18 to 79 (Table 1). The project was
approved by the University of Melbourne Human Research Ethics Com-
mittee (0838146) and the Victorian Department of Justice Human Re-
search Ethics Committees (1119644).
2.2. Measures
The Brief Bio-Social Gambling Screen (BBGS; Gebauer, LaBrie, &
Shaffer, 2010) was employed to measure past year problem gambling.
The BBGS displays high sensitivity (0.96) and high specicity (0.99) in
identifying pathological gamblers assessed using the DSM-IV-TR diag-
nostic criteria in the AUDADIS-IV in a survey of a nationally representa-
tive US sample (Gebauer et al., 2010). The BBGS was selected due to its
brevity, psychometric properties, and ability to measure problem
gambling using few items over a 12-month timeframe. The 4-item
Hurt-Insulted-Threaten-Screamed (HITS; Sherin, Sinacore, Li, Zitter, &
Shakil, 1998)wasmodied into single items measuring past year family
violence victimisation (In the past twelve months, has a family member
physically hurt you, insulted or talked down to you, threatened you with
harm,orscreamedorcursedatyou?) and perpetration (In the past twelve
months, have you physically hurt a family member, insulted or talked down
to a family member, threatened a family member with harm, or screamed or
cursed at a family member?). Participants were provided with a deni-
tion of family members and those endorsing either item were asked
to specify their relationship to the relevant immediate or extended
family member(s). The original HITS displays high internal consis-
tency (α= .80) and good concurrent and construct validity
(Sherin et al., 1998). The HITS was selected due to its brevity, psy-
chometric properties, and its ability to be converted into a brief
screening tool that measures violence extending beyond intimate
partners and for perpetration experiences (see Rabin, Jennings,
Campbell,&Bair-Merritt,2009;Thompson,Basile,Hertz,&Sitterle,
2006). The items were modied into single items to reduce partici-
pant burden during the screening process.
2.3. Data analysis
Past year point prevalence estimates were calculated for the propor-
tion of each sample completing each screening instrument. Although
only one participant failed to complete the BBGS (0.1%), there was more
missing data for the HITS victimisation (8.4%) and perpetration (9.0%)
screens. Victimisation data was missing from 43.8% of the participants
from the nancial counselling service sample, 22.1% of the participants
from the family violence services, 19.1% of participants from the alcohol
and drug services, 17.7% of participants from the mental health services,
and 1.2% of participants from the gambling services. Similarly, perpetra-
tion data was missing from 43.8% of the participants from the nancial
counselling services, 25.3% of participants from the family violence
services, 21.6% of participants from the mental health services, 21.3% of
participants from the alcohol and drug services, and 1.2% of participants
from the gambling services. More women than expected were missing
data for both victimisation (χ
2
(2, 688) = 11.53, p= .004) and per-
petration (χ
2
(2, 688) = 14.70, p= .006), but there were no other
demographic markers for missing data. Demographic differences in
family violence estimates in the problem gambling sample were
compared using chi-square analyses (with follow-up adjusted
standardised residuals [ASRs N2]) and independent samples t-tests.
Chi-square analyses were employed to examine any signicant group
1714 N.A. Dowling et al. / Addictive Behaviors 39 (2014) 17131717
differences on family violence and problem gambling between different
treatment-seeking samples.
3. Results
3.1. Gambling sample
The prevalence of family violence in the gambling sample was 27.0%
for victimisation, 22.9% for perpetration, and 33.9% for any form of fam-
ily violence (Table 2). Women were signicantly more likely to report
victimisation than men (RR = 1.8, χ
2
(2,463) = 15.52, pb.001).
When mutually exclusive family violence groups were explored
(Table 2), there was a signicant sex difference across the groups (χ
2
(6,463) = 19.38, p=.007),withsignicantly more women than men
reporting victimisation only (RR = 2.1) and both forms of violence
(RR = 1.6). The remaining demographic variables (age, country of
birth, relationship status, and household status) were not signicantly
associated with either victimisation or perpetration. Participants
endorsing victimisation identied between 1 and 7 of their family
members as perpetrators of that violence (median = 1). They were
their parents (31.9%), current partners (21.8%), former partners
(15.1%), siblings (11.2%), children (10.2%), in-laws (5.9%), and extended
family members (4.2%). Participants endorsing perpetration identied
between 1 and 6 of their family members as victims of that violence
(median = 1). They were their parents (31.9%), current partners
(27.3%), former partners (12.1%), siblings (10.2%), children (17.4%),
in-laws (3.3%), and extended family members (0.9%).
3.2. Other treatment-seeking samples
The prevalence of problem gambling in the family violence services
was 2.2% (Table 2). It was not possible to explore the relationships be-
tween problem gambling and family violence in the other three services
due to the small numbers of screened problem gamblers in these ser-
vices (Table 2). However, examinationof Ta ble 2 reveals thatthe alcohol
and drug sample reported signicantly higher rates of family violence
victimisation (RR = 2.0, χ
2
(1,495) = 22.84, pb.001), perpetration
(RR = 2.2, χ
2
(1,495) = 36.78, pb.001), and any form of family vio-
lence (RR = 2.5, χ
2
(1,494) = 36.74, pb.001) than the gambling sam-
ple. The mental health sample also reported signicantly higher rates of
family violence victimisation (RR = 2.3, χ
2
(1,499) = 23.19, pb.001)
and any form of family violence (RR = 1.8, χ
2
(1,496) = 12.13, p=
.004) than the gambling sample. In contrast, the nancial counselling
sample reported signicantly higher rates of problem gambling than the
family violence sample (RR = 4.8, χ
2
(1,141) = 5.05, p= .04).
4. Discussion
The rate of family violence victimisation in the current sample of
problem gamblers (27.0%) was half than those of most previous IPV
studies (6069%) (Echeburua et al., 2011; Kausch et al., 2006; Korman
et al., 2008). It is, however, more consistent with the rates identied in
the only available Australian study (Raylu & Oei, 2009).Therateoffamily
violence perpetration in the current sample of problem gamblers
(22.9%) was also half that identied in previous IPV research (56%)
Table 1
Summary of demographic characteristics of the study treatment-seeking samples.
Demographic characteristic Gambling services
(n= 463)
Family violence services
(n= 95)
Alcohol and drug services
(n= 47)
Mental health services
(n= 51)
Financial counselling
services (n= 48)
Total sample
(n= 704)
Male (%) 63.1 35.6 40.4 26.7 22.9 52.9
Age (M, SD) 40.8 (12.6) 38.4 (11.4) 41.6 (12.0) 38.3 (11.7) 41.7 (14.0) 40.5 (12.5)
Australian born (%) 73.3 91.8 83.0 86.7 70.8 77.0
Relationship status (%)
Single, not in a relationship 46.6 25.6 55.3 28.9 60.5 44.0
Living with partner 39.8 41.0 36.8 44.4 15.8 17.3
Not living with partner 13.6 33.3 7.9 26.7 23.7 38.6
Household status (%)
Couple with children 27.1 25.6 25.6 40.0 13.5 26.9
One parent family 9.5 26.9 20.5 22.2 51.4 16.4
Couple with no children 14.1 11.5 10.3 13.3 8.1 13.0
Single person household 24.7 16.7 41.0 13.3 18.9 23.4
Group/share household 24.7 19.2 2.6 11.1 8.1 20.2
Table 2
Prevalence of past year problem gambling and family violence (FV) across treatment services.
Screen
a
Gambling services (%; CI 95%) Family violence
services
(%; CI 95%)
Alcohol & drug
services
(%; CI 95%)
Mental health
services
(%; CI 95%)
Financial
counselling
services (%; CI 95%)
Men Women Total
FV victimisation 20.8 (15.624.9) 37.6
d
(29.344.2) 27.0 (22.130.2)
c
54.1
e
(36.265.9) 61.9
e
(46.677.2) 37.0 (17.856.5)
FV perpetration 20.8 (15.624.9) 26.5 (18.632.0) 22.9 (18.225.8)
c
49.3
e
(38.468.0) 32.5 (17.345.2) 33.3 (14.350.2)
Any form of FV 28.7 (23.033.4) 43.0 (34.649.8) 33.9 (29.037.6)
c
84.0
e
(68.995.9) 61.6
e
(45.677.5) 48.1 (28.168.3)
Problem gambling
bb b
2.2 (0.15.1) 4.3 (0.210.3) 2.0 (0.25.9) 10.6
f
(1.520.2)
Mutually exclusive FV
groups
FV victimisation only 7.8 (4.811.1) 16.5
d
(11.122.6) 11.0 (8.314.1)
c
16.2 (3.828.9) 28.2 (13.443.0) 14.8 (4.929.1)
FV perpetration only 7.8 (4.811.1) 5.3 (1.98.9) 6.9 (4.89.5)
c
18.9 (5.732.2) 2.6 (2.67.8) 11.1 (1.623.8)
FV victimisation &
perpetration
13.0 (3.612.2) 21.2
d
(13.826.1) 16.0 (11.718.2)
c
48.9 (31.865.5) 30.8 (15.645.9) 22.2 (5.539.0)
a
Base sample sizes vary due to missing data (see data analysis section).
b
Gambling programs did not administer the BBGS.
c
Family violence programs did not administer the HITS.
d
Signicant gender difference in problem gambling sample (pb.05).
e
Signicant difference with family violence estimates in comparison to problem gambling sample (pb.05).
f
Signicant difference between problem gambling estimate in comparison to family violence sample (pb.05).
1715N.A. Dowling et al. / Addictive Behaviors 39 (2014) 17131717
(Korman et al., 2008). While the rates may reect lower prevalence in
Australia relative to other jurisdictions, they may also reect the use of
the adapted HITS items that measured multiple forms of violence in
single items and did not measure some forms of violence, such as sexual
violence. Because the complexity of family violence presentations is
poorly captured by current screening instruments that tend to comprise
too many items to be usefully employed in screening or focus on
intimate partner victimisation experiences (see Rabin et al., 2009;
Thompson et al., 2006), future research may benet from the further
development and validation of brief screens for violence extending
beyond intimate partners and for perpetration experiences. Finally,
this study is the rst to examine the prevalence of problem gambling
in individuals seeking assistance related to familyviolence victimisation
(2.2%).
Although the failure to employ a community-based control group
precludes denitive conclusions about these estimates relative to the
general population, the past year family violence victimisation rate in
gambling treatment services (27.0%) was 25 times higher than the
past year physical and/or sexual IPV victimisation rate (1.1%), and 7
times higher than the past year emotional IPV victimisation rate
(3.8%), in the Australian population (Australian Bureau of Statistics,
2013). Similarly, the rate of past year problem gambling in family
violencevictimisation treatment services (2.2%) was 2 to 4 times higher
than in the Australian population (0.51.0%) (Jackson, Wynne, Dowling,
Tomnay, & Thomas, 2010). Although these comparisons are not entirely
valid as different denitions and measures of problem gambling and
family violence were employed, they suggest that further investigation
of the relationship between problem gambling and family violence is
warranted.
The highest proportion of the gambling sample reported both
family violence victimisation and perpetration, raising the possibili-
ty of reciprocal violence occurring in problem gambling families
(Suomi et al., 2013). Consistent with Kausch et al. (2006),women
were 2.1 times more likely to report victimisation only and 1.6
times more likely to report both victimisation and perpetration
than men. Although this study provides an acontextual acts-based
measurement of family violence (Taft, Hegarty, & Flood, 2001), the
nding that nearly half of female problem gamblers report some
form of family violence suggest that this group of service users
should be specically targeted for screening, assessment and man-
agement. Finally, the parents, partners, and former partners of the
gamblers were most commonly endorsed as both perpetrators and
victims of family violence. Evidence of high rates of family violence
victimisation and perpetration by the parents of problem gamblers
has also been noted in a study investigating the prevalence of family
violence in a small sample of the family members of problem gam-
blers (Suomi et al., 2013). Moreover, there are ndings to suggest
that parents of problem gamblers report equivalent nancial, emo-
tional, social life, employment, and physical health impacts to
partners (Dowling, Rodda, Lubman, & Jackson, 2014). Although the
precise nature of the relationship between problem gambling and
family violence remains unknown, preliminary ndings have sug-
gested that problem gambling precedes both victimisation and per-
petration of family violence (Suomi et al., 2013). This implies that
gambling-related stressors, such as the loss of family nancial re-
sources, abdication of family role responsibilities, mistrust, and
poor communication may result in chronic family stress, domestic
conict, and the perpetration of violence by parents and partners
(Echeburua et al., 2011; Korman et al., 2008) and that gambling
losses and other problems may result in the manifestation of stress,
anger, and nancial crisis within the home and lead to the perpetra-
tion of violence by the proble mgambler against parents and partners
(Afifi, Brownridge, MacMillan, & Sareen, 2010; Korman et al., 2008;
Muelleman, DenOtter, Wadman, Tran, & Anderson, 2002). Regard-
less of the nature of the relationship, the ndings that parents are in-
volved highlights the importance of studying violence that extends
into problem gambling families beyond intimate partners and chil-
dren (Jackson, 2003; Ulman & Straus, 2003).
The ndings of this study underscore the need that other services,
such alcohol and drug services, mental health services, and nancial
counselling services, should develop screening, referral and manage-
ment protocols for problem gambling and family violence. The rate of
problem gambling in the nancial counselling sample was 4.8 times
higher than that in the family violence sample while the rates of family
violence in the alcohol and drug and mental health samples were 1.8 to
2.5 times higher than those in the problem gambling sample. The high
rates of family violence in clients attending alcohol and drug services
and mental health services are not unexpected, given there is substan-
tial evidence that family violence is highly comorbid with alcohol and
drug use problems and mental health issues (Krug et al., 2002). Howev-
er, problem gamblingis also highly comorbid with alcohol and drug use
problems and psychiatric comorbidities (Dowling et al., in press; Lorains
et al., 2011). It is therefore possible that the rates of family violence
observed in the problem gambling treatment sample may reect an
association of family violence with alcohol and substance use problems
or psychiatric comorbidity, rather than any specic association with
gambling problems. There is evidence that alcohol and substance use
problems and psychiatric comorbidity exacerbate the relationship
between problem gambling and family violence (Afifi et al., 2010;
Braseld et al., 2011, 2012; Goldstein, Walton, Cunningham, Resko,
& Duan, 2009; Kausch et al., 2006; Leiseur & Rothschild, 1989;
Muelleman et al., 2002). However, there are some conicting ndings
with some studies failing to report these associations (Echeburua
et al., 2011; Korman et al., 2008; Schluter, Abbott, & Bellringer, 2008).
Moreover, approximately two-thirds ofthe family members of problem
gamblers report there is an association between problem gambling and
family violence (Muelleman et al., 2002; Suomi et al., 2013). The
ndings of this study therefore highlight the need for further research
investigating the role of alcohol and substance use problems and mental
health problems in the relationship between problem gambling and
family violence.
The ndings of this study support substantial comorbidity between
problem gambling and family violence, although this may be accounted
for by a high comorbidity with alcohol and drug use problems and other
psychiatric disorders. Further research, including prospective studies,
are needed to advance our understanding of the relationships between
problem gambling, family violence, and these psychiatric comorbidities.
Although the achieved rates of screening in these samples are superior
to average rates of clinician-administered screening for alcohol, drug,
and mental health problems (Edlund, Unutzer, & Wells, 2004; Groves
et al., 2010), it is unlikely that agencies screened every client and
there was a considerable amount of missing family violence data. This
indicates future replication with researcher-administered screening is
warranted. The ndings of this study can, however, inform specic
approaches to prevention and intervention efforts and responsible
gambling and violence prevention policies. They highlight the need for
routine screening, assessment and management of family violence in
problem gambling services and gambling problems in family violence
services.
Role of funding sources
This research was funded by the Aust ralian Research Council (Linka ge Grant LP
0989331) with the Ofce for Problem Gambling, South Australia and Drummond Street
Services, Vict oria as industry partners; and the Problem Gambling Re search and
Treatment Centre at the University of Melbourne.
Contributors
AJ, ND and ST designed the study; ND wrote the rst draft of the manuscript; AS, TL,
and JP wereinvolved in data collection; andAS project managedand led the data analysis.
All authorscontributed to and approved the nal manuscript and all meet the NH & MRC
guidelines for authorship.
Conict of interest
The authors declare that they have no competing interests.
1716 N.A. Dowling et al. / Addictive Behaviors 39 (2014) 17131717
Acknowledgements
This research wa s funded by the Australian Research Council (Linkag e Grant LP
0989331) with the Ofce for Problem Gambling, South Australia and Drummond Street
Services, Victoria as industry partne rs; and the Problem Gamb ling Research and
Treatment Centr e at the University of Melbour ne. The research te am would like to
acknowledge th e effort of the parti cipating agenci es in Victoria, Sou th Australia and
Tasmania, and the clients who participated in the study.
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... One harm associated with gambling is domestic and family violence, with higher rates of perpetration and victimization found among individuals with a gambling problem (Afifi et al., 2010;Dowling et al., 2018;Roberts et al., 2018). Intimate partners are most commonly the victims and perpetrators of this violence, although violence related to gambling also occurs amongst other family members (Dowling et al., 2014;Bellringer et al., 2017;Palmer du Preez et al., 2018). Gambling research has sought to understand the prevalence of this violence, characteristics of perpetrators and victims, why this violence occurs, and how it is linked to gambling. ...
... DFV/IPV linked to a perpetrator's gambling Prevalence of DFV/IPV by perpetrators with a gambling problem Several studies provide insights into the prevalence of DFV and IPV perpetrated by individuals with a gambling problem, but results vary across countries, samples and types of abuse examined. In convenience samples of treatment-seekers experiencing problem gambling, DFV perpetration rates in Australia have ranged from 19% (Dowling et al., 2021), to 23% (Dowling et al., 2014) to 49% (Lavis et al., 2015). New Zealand studies have found rates of 42% (Palmer du Preez et al., 2018) and 43% (Bellringer et al., 2017). ...
... Heightened rates of problem gambling are also apparent amongst DFV and IPV perpetrators (Korman et al., 2007; Frontiers in Psychology 04 frontiersin.org Afifi et al., 2010;Brasfield et al., 2011Brasfield et al., , 2012Dowling et al., 2014;Izmirli et al., 2014). A meta-analysis estimated that 11% of perpetrators of physical IPV report problem gambling , compared to an average of 2.3% of the general adult population who report problem gambling across numerous countries (Williams et al., 2012). ...
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... Conceptual frameworks identify gambling harm to CSOs as most commonly extending across financial, relationship, emotional, physical health and vocational domains (Browne et al., 2016;Dowling et al., 2014Dowling et al., , 2021Kourgiantakis, Saint-Jacques, & Tremblay, 2013;Riley et al., 2018). Financial harms to CSOs can range from eroded savings, to more severe and less prevalent harms such as inability to afford necessities, the sale of family assets, and bankruptcy (Browne et al., 2016;Dowling et al., 2021;Holdsworth, Nuske, Tiyce, & Hing, 2013;Li et al., 2017). ...
... Lies and deception about gambling lead to mistrust and blame between CSOs and gamblers, along with loss of faith in a shared commitment to the family's wellbeing Holdsworth et al., 2013;Patford, 2007bPatford, , 2009). These tensions can give rise to conflict, including family violence, to manipulate and control others to support the gambling (Dowling et al., 2014;Hing et al., 2021aHing et al., , 2021dPalmer du Preez et al., 2018;Suomi et al., 2013). Strains from gambling can lead to relationship breakdown and estrangement between CSOs and gamblers, as well as CSOs' social isolation from family and friends (Dickson-Swift, James, & Kippen, 2005;Patford, 2007aPatford, , 2007b. ...
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... Although there is an increase in the number of empirical studies proving that familial factors as well as individual factors can influence gambling problem, few studies have conducted research on how childhood experience interplay with familial factors in adulthood and influence gambling problem. Most studies related to gambling so far have inferred the connection between individual and familial factors of gambling problem by conducting correlation or regression analysis of variables [16], t-test or ANOVA [16] and chi-square test [34]. However, the intervention with regard to gambling problem requires identification of specific path between variables of gambling problem. ...
... Treatment-seeking men more often engage in sports betting (19)(20)(21). In treatment-seeking individuals, it has also been reported that female gamblers often report being victims of family violence (21,34,39) and that they, to a larger extent than men, had been exposed to childhood maltreatment (40). ...
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... Youth who report problem gambling in the family also endorse indicators of harm or other negative consequences: dysphoric mood states (Gupta & Derevensky, 1998), impulsive decision-making and avoidant stress-coping styles (Nower et al., 2004), higher levels of stress and psychological distress (Tulloch et al., 2021), comorbid addictive behaviors (Molinaro et al., 2018;Zhai et al., 2017), and feelings of 'pervasive loss' that encompass relationships, trust, security, sense of home, and material goods (Darbyshire et al., 2001). Adverse outcomes later manifest in adulthood (Forrest & McHale, 2021) and are further exacerbated by comorbidity with alcohol and drug use problems and psychiatric disorders (Dowling et al, 2014). For example, a recent review of 35 studies concluded there are both direct and indirect effects of perceived parental gambling on child wellbeing across multiple domains, with child distress and family dysfunction demonstrating the most pronounced negative effects (Suomi et al., 2022b). ...
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We evaluated treatment effects for continuous and dichotomous outcomes using standardised mean difference (SMD) and risk ratios (RR), respectively, employing random-effects meta-analyses. A minimum of two independent treatment effects were required for a meta-analysis to be conducted (with only meta-analytic findings reported in this abstract). Main results: We included 17 studies in the review (n = 1193 randomised) that reported outcome data scheduled for end of treatment. Length of treatment ranged from 7 to 96 weeks. Antidepressants: Six studies (n = 268) evaluated antidepressants, with very low to low certainty evidence suggesting that antidepressants were no more effective than placebo at post-treatment: gambling symptom severity (SMD -0.32, 95% CI -0.74 to 0.09, n = 225), gambling expenditure (SMD -0.27, 95% CI -0.60 to 0.06, n = 144), depressive symptoms (SMD -0.19, 95% CI -0.60 to 0.23, n = 90), functional impairment (SMD -0.15, 95% CI -0.53 to 0.22, n = 110), and responder status (RR 1.24, 95% CI 0.93 to 1.66, n = 268). Opioid antagonists: Four studies (n = 562) evaluated opioid antagonists, with very low to low certainty evidence showing a medium beneficial effect of treatment on gambling symptom severity relative to placebo at post-treatment (SMD -0.46, 95% CI -0.74 to -0.19, n = 259), but no difference between groups in responder status (RR 1.65, 95% CI 0.86 to 3.14, n = 562). Mood stabilisers: Two studies (n = 71) evaluated mood stabilisers (including anticonvulsants), with very low certainty evidence suggesting that mood stabilisers were no more effective than placebo at post-treatment: gambling symptom severity (SMD -0.92, 95% CI -2.24 to 0.39, n = 71), depressive symptoms (SMD -0.15, 95% CI -1.14 to 0.83, n = 71), and anxiety symptoms (SMD -0.17, 95% CI -0.64 to 0.30, n = 71). Atypical antipsychotics:Two studies (n = 63) evaluated the atypical antipsychotic olanzapine, with very low certainty evidence showing a medium beneficial effect of treatment on gambling symptom severity relative to placebo at post-treatment (SMD -0.59, 95% CI -1.10 to -0.08, n = 63). Comparative effectiveness: Two studies (n = 62) compared antidepressants with opioid antagonists, with very low certainty evidence indicating that antidepressants were no more effective than opioid antagonists on depressive symptoms (SMD 0.22, 95% CI -0.29 to 0.72, n = 62) or anxiety symptoms (SMD 0.21, 95% CI -0.29 to 0.72, n = 62) at post-treatment. Two studies (n = 58) compared antidepressants with mood stabilisers (including anticonvulsants), with very low certainty evidence indicating that antidepressants were no more effective than mood stabilisers on depressive symptoms (SMD 0.02, 95% CI -0.53 to 0.56, n = 58) or anxiety symptoms (SMD 0.16, 95% CI -0.39 to 0.70, n = 58) at post-treatment. Tolerability and adverse events: Several common adverse effects were reported by participants receiving antidepressants (e.g. headaches, nausea, diarrhoea/gastrointestinal issues) and opioid antagonists (e.g. nausea, dry mouth, constipation). There was little consistency in the types of adverse effects experienced by participants receiving mood stabilisers (e.g. tiredness, headaches, concentration difficulties) or atypical antipsychotics (e.g. pneumonia, sedation, increased hypomania). Discontinuation of treatment due to these adverse events was highest for opioid antagonists (10% to 32%), followed by antidepressants (4% to 31%), atypical antipsychotics (14%), and mood stabilisers (13%). Authors' conclusions: This review provides preliminary support for the use of opioid antagonists (naltrexone, nalmefene) and atypical antipsychotics (olanzapine) to produce short-term improvements in gambling symptom severity, although a lack of available evidence precludes a conclusion regarding the degree to which these pharmacological agents can improve other gambling or psychological functioning indices. In contrast, the findings are inconclusive with regard to the effects of mood stabilisers (including anticonvulsants) in the treatment of disordered or problem gambling, and there is limited evidence to support the efficacy of antidepressants. However, these conclusions are based on very low to low certainty evidence characterised by a small number of included studies, high risk of bias, modest pooled sample sizes, imprecise estimates, moderate between-study heterogeneity, and exclusion of participants with psychiatric comorbidities. Moreover, there were insufficient studies to conduct meta-analyses on many outcome measures; to compare efficacy across and within major categories of interventions; to explore dosage effects; or to examine effects beyond post-treatment. These limitations suggest that, despite recommendations related to the administration of opioid antagonists in the treatment of disordered or problem gambling, pharmacological interventions should be administered with caution and with careful consideration of patient needs. A larger and more methodologically rigorous evidence base with longer-term evaluation periods is required before definitive conclusions can be drawn about the effectiveness and durability of pharmacological treatments for disordered or problem gambling.
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The 'concerned significant others' (CSOs) of people with problem gambling frequently seek professional support. However, there is surprisingly little research investigating the characteristics or help-seeking behaviour of these CSOs, particularly for web-based counselling. The aims of this study were to describe the characteristics of CSOs accessing the web-based counselling service (real time chat) offered by the Australian national gambling web-based counselling site, explore the most commonly reported CSO impacts using a new brief scale (the Problem Gambling Significant Other Impact Scale: PG-SOIS), and identify the factors associated with different types of CSO impact. The sample comprised all 366 CSOs accessing the service over a 21month period. The findings revealed that the CSOs were most often the intimate partners of problem gamblers and that they were most often females aged under 30years. All CSOs displayed a similar profile of impact, with emotional distress (97.5%) and impacts on the relationship (95.9%) reported to be the most commonly endorsed impacts, followed by impacts on social life (92.1%) and finances (91.3%). Impacts on employment (83.6%) and physical health (77.3%) were the least commonly endorsed. There were few significant differences in impacts between family members (children, partners, parents, and siblings), but friends consistently reported the lowest impact scores. Only prior counselling experience and Asian cultural background were consistently associated with higher CSO impacts. The findings can serve to inform the development of web-based interventions specifically designed for the CSOs of problem gamblers.
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This qualitative study used feminist insights to explore experiential aspects of the phenomenon of child-to-mother violence from the perspectives of six women survivors. Participants took part in conversational style audiotaped interviews lasting between two and four hours. Feminist analysis revealed that fear and violence had become a feature of mothering for these women. Three themes were identified: It was only a matter of time: feeling intimidated and under threat; He just punched me: physical violence from child to mother; and Other men in the house: violence directed to the mothers by friends and associates of their children. Currently the literature overwhelmingly constructs family violence as elder abuse, spousal/partner violence, or child abuse, and generally fails to acknowledge, or address, violence from children to parents. However, findings from this study suggest that the discourse about family violence needs to be broadened to include child-to-mother violence. Implications of this study for practice and research are discussed.
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Factors (demographics, gambling behaviors and comorbid problems) that may be related to the severity of gambling problems were investigated among 440 problem gamblers seeking treatment in an Australian outpatient treatment agency. The participants were divided into sub-threshold pathological gamblers (SPGs; N = 104) and pathological gamblers (PGs; N = 336) using Diagnostic Statistical Manual (DSM) IV diagnosis of pathological gambling. SPGs were more likely to be separated/divorced, while PGs were more likely to be single. PGs tended to be younger than SPGs. Participation in lottery games was the only form of gambling that could distinguish between the two severity groups. No significant differences were found in participation in more than one gambling session per week and average amount spent per session on various gambling activities between the two groups. PGs were more likely to report financial, relationship, employment, physical, intrapersonal, other excessive behaviors (e.g., substance problems), leisure (e.g., loneliness, boredom) and legal problems than SPGs. Implications and limitations of these findings are discussed.
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Most states and territories in Australia have adopted the Problem Gambling Severity Index (PGSI) of the Canadian Problem Gambling Index as the standard measure of problem gambling in their prevalence studies and research programs. However, notwithstanding this attempted standardisation, differences in sampling and recruitment methodologies and in some cases the modification of the scoring methods used in the PGSI have lead to substantial difficulties in comparison of the prevalence rates obtained in different studies. This paper focuses on how these two actions may significantly underestimate the true prevalence percent of problem gambling in Australian studies of the prevalence of problem gambling. It is recommended that the original and validated version of the PGSI is used in future Australian prevalence studies and that prevalence in community studies is studied across the whole community not arbitrarily restricted sub-samples. The adoption of valid scoring methods and unbiased sampling procedures will lead to more accurate and comparable prevalence studies. KeywordsProblem gambling-Pathological gambling-Prevalence-Canadian Problem Gambling Index-Problem Gambling Severity Index