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Online Gambling Addiction: the Relationship Between Internet Gambling and Disordered Gambling

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Abstract

One of the most significant changes to the gambling environment in the past 15 years has been the increased availability of Internet gambling Internet, including mobile, gambling is the fastest growing mode of gambling and is changing the way that gamblers engage with this activity. Due to the high level of accessibility, immersive interface, and ease at which money can be spent, concerns have been expressed that Internet gambling may increase rates of disordered gambling. The current paper aimed to provide an overview of the research to date as well as highlight new and interesting findings relevant to Internet gambling addiction. A comprehensive review was conducted of existing literature to provide an overview of significant trends and developments in research that relates to disordered Internet gambling. This paper presents research to inform a greater understanding of adult participation in Internet gambling, features of this interface that may impact problem severity, the relationship between Internet gambling and related problems, as well as considering the role of the wider spectrum of gambling behaviour and relevant individual factors that moderate this relationship.
Online Gambling Addiction: The relationship between Internet gambling and
disordered gambling
Sally M. Gainsbury, PhD, Doc.Clin.Psych, BPsych(Hons)
Senior Lecturer, Centre for Gambling Education & Research, Southern Cross University
Address: PO Box 157, Lismore NSW 2480, Australia
Email: sally.gainsbury@scu.edu.au
Cite as: Gainsbury, S.M. (2015). Online Gambling Addiction: the Relationship Between
Internet Gambling and Disordered Gambling. Current Addiction Reports, 2(2), 185-193.
DOI: 10.1007/s40429-015-0057-8
Available at: http://download-v2.springer.com/static/pdf/25/art%253A10.1007%252Fs40429-
015-0057-
8.pdf?token2=exp=1430955014~acl=%2Fstatic%2Fpdf%2F25%2Fart%25253A10.1007%25
252Fs40429-015-0057-
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Keywords: Addiction; disordered gambling; problem gambling; gambling harm; protective
factors; risk factors; Internet gambling; interactive gambling; online gambling; mental health;
causation; determinants
Abstract
One of the most significant changes to the gambling environment in the past 15 years has
been the increased availability of Internet gambling Internet, including mobile, gambling is
the fastest growing mode of gambling and is changing the way that gamblers engage with this
activity. Due to the high level of accessibility, immersive interface, and ease at which money
can be spent, concerns have been expressed that Internet gambling may increase rates of
disordered gambling. The current paper aimed to provide an overview of the research to date
as well as highlight new and interesting findings relevant to Internet gambling addiction. A
comprehensive review was conducted of existing literature to provide an overview of
significant trends and developments in research that relates to disordered Internet gambling.
This paper presents research to inform a greater understanding of adult participation in
Internet gambling, features of this interface that may impact problem severity, the
relationship between Internet gambling and related problems, as well as considering the role
of the wider spectrum of gambling behaviour and relevant individual factors that moderate
this relationship.
Gainsbury Online Gambling Addiction 2
Introduction
Internet gambling (a term largely interchangeable with interactive remote, and online
gambling) refers to the range of wagering and gaming activities offered through Internet-
enabled devices, including computers, mobile and smart phones, tablets, and digital
television. This mode of gambling, facilitated by technological advances, increased Internet
availability and ownership of Internet-enabled devices, is not a separate type of gambling
activity. Rather it is a mode of access that is distinct from gambling in-person at terrestrial or
land-based retail outlets and placing wagers over the telephone. As such, it is a largely
automated activity that be conducted in private, at any time and location, using high-speed
Internet connections enabling rapid placement of bets and notification of outcomes. The
ability for large wagers, continuous gambling, rapid feedback, and instant, easy access to a
vast number of betting options has resulted in concerns that Internet gambling could
contribute to excessive gambling [1, 2].
As a result of the empirical comparisons demonstrating the fundamental parallels between
gambling problems and substance use, the fifth edition of the Diagnostic and Statistical
Manual of Mental Disorders (DSM-5) includes a new category of Non-Substance
Behavioural Addiction within the substance addictions category [3]. Disordered gambling is
classified as the first behavioural addiction and will serve as a ‘blueprint’ for research on
other syndromes and arguably set a precedent for the compilation of evidence on other
similarly excessive behaviours [4] such as ‘Internet gaming disorder’ (currently in Section 3
of the DSM-5). Mounting evidence of distress and dysfunction related to excessive and
problematic Internet use and specifically Internet gaming led the DSM-5 Taskforce to
officially call for further research on this behaviour [5]. Given the similarities in the
experience and excessive use of Internet gambling and gaming and the potential for harm
based on excessive Internet use, pathological use of Internet gambling also warrants specific
consideration [4]. The current paper aims to provide an overview of the research to date as
well as highlighting new and interesting findings relevant to adult Internet gambling
addiction. A comprehensive review was conducted of existing literature to provide an
overview of significant trends and developments in research that relates to disordered Internet
gambling.
Participation
Internet gambling is growing rapidly in terms of popularity, market share, and products
offered. The online global gambling market was valued at 6.1bn in 2013, with expected
annual growth of 10.1% to 2018 [6]. Online gambling accounted for an estimated 8-10% of
the total global gambling market in 2012, and this proportion appears to be increasing -[7-9].
Globally, the largest online gambling product is wagering, accounting for 53% of the online
gambling market, followed by casino games (including slot machines/pokies/electronic
gaming machines, 25.4%), poker (14.2%), and bingo (7.4%) [8].
Gainsbury Online Gambling Addiction 3
Internationally, an increasing number of jurisdictions are legalizing and regulating Internet
gambling [10]. This follows recognition of the difficulties of enforcing prohibition and the
benefits of regulation, including requiring harm minimization measures to enhance consumer
protection, and generating taxation revenue [1]. Although the prevalence of Internet gambling
appears to be relatively low, participation is increasing rapidly, particularly in jurisdictions
that permit access to regulated sites [11, 12]. For example, in Australia following the
legalisation of Internet wagering and lottery playing, prevalence rates in Internet gambling
rose from less than one percent in 1999 to 8.1% in 2011 [13]. Similarly in the UK, an average
of 16% of respondents had participated in at least on form of online gambling in the previous
four weeks [11]. In comparison, only 6% of the British population used the Internet to
gamble in the past year in 2007, although this figure does not include purchasing lottery
tickets online, which may have increased the participation rate [14].
Internet gambling use is likely to continue to grow as online platforms become increasingly
used to engage in entertainment and recreational activities, including through phones and
other wireless devices. Research suggests that the most commonly reported motivators and
advantages of Internet gambling are the convenience and accessibility of this mode [15-17].
Other commonly stated advantages of Internet gambling include greater value for money,
including payout rates and bonuses, the speed and ease of online gambling, greater number of
betting products and options, and the physical comfort of being able to gamble from home.
Internet gambling represents a fundamental shift in how consumers engage in gambling and
concerns have been expressed by various stakeholders about these changes. Disadvantages
cited by Internet gamblers include that it is easier to spend money online, it is too convenient,
and concerns about account safety [15-20]. Other concerns include that the high accessibility
to Internet gambling may increase gambling, particularly among technology-savvy youth, and
lead to an increase in the incidence and prevalence of disordered gambling [1, 21]. These
concerns have led to recommendations for Internet gambling to be prohibited, or conversely
regulated, in an attempt to institute policies to minimise harms [1, 12, 18, 22-24].
Internet gambling and problem gambling
Features of Internet gambling that may impact problem severity
Evidence suggests that there is a relationship, albeit complex, between the availability of
gambling opportunities and increased levels of related problems [25-30]. Consequently, it has
been asserted that the easy access to gambling provided by Internet modes may lead to the
development or exacerbation of gambling problems [1, 22, 24, 31].
Gainsbury Online Gambling Addiction 4
Internet gambling also has some unique features that may pose additional risks for harm,
particularly for vulnerable populations. Internet gambling differs from land-based gambling
primarily in terms of its constant availability, easy access, and ability to bet for uninterrupted
periods in private, facilitated by the interactive and immersive Internet environment [2, 18,
32-35]. The use of digital forms of money (e.g., credit cards, electronic bank transfers, and e-
wallets) appears to lead to increased gambling and losses, particularly for problem gamblers,
as people feel that they are not spending ‘real’ money [16, 32, 36, 38, 39]. Surveys indicate
that 19-28% of online gamblers report it is easier to spend more money online [20, 39], while
15% consider this form to be more addictive than land-based gambling [15].
The immersive nature of Internet gambling is also clear through reports that online gamblers,
particularly those experiencing problems are more likely to report disruption to their sleep
and eating patterns than land-based gamblers [18, 36, 37]. Data collected by gambling
treatment services suggest that Internet gambling currently makes a small, but growing
contribution to gambling problems among those seeking formal help [37, 40, 41]. Surveys
have found that online problem gamblers are significantly less likely to have sought formal
help as compared to land-based problem gamblers; [20, 42, 43]. This suggests that problems
related to Internet gambling may be underrepresented in treatment-seeking samples and are
likely to increase over time as more people participate in this mode and problem severity
increases.
The relationships between Internet gambling and gambling problems
Initial concerns over the harmful effects of Internet gambling are sensible as numerous
studies have found greater levels of problem gambling severity amongst samples of Internet
as compared to non-Internet gamblers [13, 31, 41, 43-48]. For example, in an Australian
nationally representative prevalence survey, the overall problem gambling rate among
Australian non-Internet gamblers was 0.9%. In comparison, the rate among Internet gamblers
was three times higher at 2.7% [13]. Fewer than 60% of Internet gamblers were classified as
non-problem gamblers, compared to more than 80% of non-Internet gamblers, which was a
significant difference. Furthermore, the average PGSI score of Internet gamblers was
significantly higher than that of non-Internet gamblers. Similarly, a total of 16.4% of Internet
gamblers were classified as either moderate or problem gamblers, compared to a rate of 5.7%
among non-Internet gamblers [43]. However, there is little evidence available that would
enable the causation of Internet-related gambling problems to be determined and most
longitudinal studies contain too few Internet gamblers to provide meaningful analyses.
Despite some indications of a positive correlation, the relationship between Internet gambling
participation and problems has not been confirmed. Some studies have found similar rates of
gambling problems among Internet and land-based gamblers [15, 41]. Research also suggests
Gainsbury Online Gambling Addiction 5
that very few Internet gamblers gamble exclusively online [12, 24, 48, 49]. Further analyses
of prevalence studies that control for factors such as demographic variables and gambling
involvement have found that participation in Internet gambling does not independently
predict problem gambling severity [13, 20, 36, 46, 50-52]. For example, even though Internet
gamblers were more likely to be classified as being at-risk or experiencing gambling
problems in a nationally representative survey, when other variables were controlled for,
Internet gambling participation was not predictive of problem gambling severity [13].
Similarly, using data from the 2007 British Gambling Prevalence Study, LaPlante and
colleagues [50] found that gambling formats (particularly Internet gambling) and problem
gambling were not significantly related when gambling involvement was included in the
model (based on the number of gambling activities used in the past 12 months). This finding
was in contrast to earlier analyses [31] and demonstrates the importance of controlling for
confounding factors.
Further evidence to question the extent to which Internet gambling increases rates of problem
gambling can be taken from prevalence studies. Despite rates of Internet gambling increasing
in several jurisdictions, little evidence has been found to suggest that the prevalence of
problem gambling has increased [13, 53, 54]. An analysis across 30 European jurisdictions
failed to identify any association between prohibitions against online gambling, gambling
licensing systems, the extent of legal gambling opportunities and the prevalence of gambling
disorder [55].
The impact of Internet and land-based gambling on gambling problems
Evidence is emerging that Internet gambling is not only not predictive of gambling problems,
but that when other variables are controlled for individuals who gamble online may have
lower rates of gambling problems. Studies that have isolated Internet-only gamblers have
found that these gamblers have lower rates of gambling problems than gamblers who only
gamble offline, and those who use both online and offline modes [48, 51, 56]. Gamblers who
engage in online as well as offline modes appear to have the greatest risks of harm, which is
likely related to their greater overall gambling involvement [48, 56, 57].
The relationship between Internet and problem gambling is likely mediated by the use of
land-based gambling. A study examining actual Internet gambling account activity combined
with a self-report measure of gambling problems confirmed that gambling involvement, as
indicated by number of games played and days bets placed on in past year, is predictive of
gambling problems amongst the sample of Internet gamblers analysed [58]. These results are
consistent with a wide-body of research which suggests that gambling disorder is related to
high levels of involvement (in terms of expenditure, time, frequency. and variety of gambling
forms used) [13, 36, 52, 59, 60-63]. Therefore, research suggests that highly involved
gamblers are more likely to engage with Internet modes, including those with existing
Gainsbury Online Gambling Addiction 6
gambling problems, than less involved gamblers. However, a study comparing behavioural
data from an online gambling sites with self-report of gambling problems found that not all
highly involved gamblers were at risk for gambling-related problems, and likewise, not all
those with low involvement screened negatively for gambling-related problems [64]. This is
an important finding as it demonstrates (unsurprisingly) that a single gambling index (such as
a frequency of gambling, or expenditure) is not adequate to predict gambling problems.
Involvement in Internet gambling appears to be more likely among gamblers with existing
problems as compared to non-problem gamblers [35]. Studies have found that one-third to
one-half of Internet gamblers experiencing gambling problems attribute these to land-based
forms of gambling, and over half report that they had existing problems before they ever
gambled online [13, 20]. This is consistent with one study reporting that problem Internet
gamblers prefer land-based over Internet gambling [24]. Few studies have investigated the
types of gambling that are most likely to be associated with problems related to Internet
gambling. In an Australian national survey, almost half of all gamblers stated that land-based
electronic gaming machines were the primary cause of their problems, including among
Internet gamblers [13]. Internet gamblers are most likely to associate their problems with
casino games, sports and race wagering, and poker [13, 20].In particular, sports betting
appeared to be associated with moderate risk and problem gambling, a finding not replicated
among land-based only gamblers [13,20]. However, this finding may be specific to the
Australian context as sports wagering is one of the few legal forms of online gambling.
Conversely, for some Internet problem gamblers, this mode of gambling appears to be the
proximal cause of problems, with problem gamblers reporting that their problems started
after they first gambled online and around half specifically attributing problems to this mode
[13,20]. These results are consistent with other research findings [57, 48], suggesting that for
some problem gamblers, Internet gambling played an important causal role, while others had
existing problems, which were likely exacerbated by Internet gambling. However, most
studies examining the relationship between Internet gambling and problems are cross-
sectional, which do not allow for causality to be determined and self-report is subject to bias
and reliant on accuracy of reporting. Longitudinal research will be an important addition to
this field to address these issues. As Internet gambling increases in popularity and use it is
likely that the next generation of gamblers will use Internet modes earlier in their gambling
career, which may increase the proportion of individuals who experience problems that are
attributed to this mode. However, there is a growing recognition that Internet gamblers are a
heterogeneous group and research needs to consider how Internet gambling behaviour may be
integrated more broadly with offline gambling [48, 65].
Gainsbury Online Gambling Addiction 7
Risk factors for Internet gambling problems
Personal variables
Socio-demographic variables
Analysis of demographic variables suggests that Internet problem gamblers overall do not
represent a distinctly different cohort than gamblers who experience problems related to land-
based gambling. Risk factors for Internet problem gambling identified include being male,
younger adults, and being from a culturally diverse background [13, 20, 41, 66, 67]. The
consistent relationship found between problematic Internet gambling and younger age
suggests that this population is particularly vulnerable to harms related to this form and use of
Internet gambling amongst young males is an area that warrants further attention in terms of
research as well as harm minimisation.
Risk factors identified do not appear to be universal, for example, Gainsbury, Russell, Wood,
Hing, and Blaszczynski [13] found problem Internet gamblers more likely to be young, less
educated and have greater debts than non-problem Internet gamblers. A subsequent study
found only age differed between Internet and non-Internet problem gamblers when
controlling for Internet gambling participation and there were no significant differences based
on education or income [20]. In contrast, Jiménez-Murcia and colleagues [68] found that
online problem gamblers had higher educational levels, higher socio-economic status than
non-Internet problem gamblers, however, both groups showed similar psychopathological
profiles or personality characteristics. Other studies have also found that Internet gamblers
are more likely to have higher educational levels and socio-economic profiles [e.g., 43, 48,
65], as well as higher levels of problem gambling than non-Internet gamblers. However these
are associations that do not control for the interaction between variables so it is difficult to
draw firm conclusions about problem as compared to non-problem Internet gamblers. It is
likely that the profile of those at-risk for developing Internet gambling problems will change
as this mode of gambling becomes more accepted and widely used and further research is
conducted.
Physical and mental health comorbidities
Studies have also found higher rates of health and mental health comorbidities, including
smoking and alcohol consumption, as well as substance abuse or dependence, and mood
disorders among Internet as compared to non-Internet gamblers [13, 15, 30, 31, 43, 44, 47,
49, 57, 67, 69, 70]. (One study found that Internet gambling frequency was significantly
associated with poor physical and mental health, after controlling for demographics and
pathological gambling, but overall gambling frequency was not [71]. A study examining
irrational and erroneous thinking found that greater levels of erroneous cognitions
significantly predicted problem gambling severity when controlling for other variables among
Internet gamblers [46]. As psychological comorbidities and irrational thinking are related to
Gainsbury Online Gambling Addiction 8
problems amongst land-based gamblers these results suggest that the clinical characteristics
of Internet problem gamblers are similar to offline gamblers.
There is also evidence that Internet problem gamblers have higher rates of drug and alcohol
use than non-problem gamblers. Analysis of 1,119 surveys completed by online gamblers
indicated that compared to non-problem gamblers, problem gamblers were more likely to
smoke cigarettes, have a disability, and drink alcohol while gambling online [67]. This is
consistent with higher rates of mood and substance use disorders and self-harm among highly
involved Internet gamblers [70]. An Australian telephone survey found that illicit drug use
was a significant predictor of having greater levels of gambling problems [13]. These results
may indicate that Internet who are at risk for gambling problems may engage in a range of
risk-taking behaviours, for example due to high levels of impulsivity [72].
Nonetheless, the relationships between Internet gambling, gambling problems and other
mental health issues are still unclear [73]. For example, multiple studies in Sweden did not
support the assumption that Internet gambling would attract people with low social support,
psychological problems, physical problems or health problems such as risky alcohol
consumption [41]. Similarly, offline gamblers were more likely to report health and
psychological impacts of problem gambling than Internet gamblers in an Australian study
comparing at-risk and problem gamblers [20]. Furthermore, in a nationally representative
Australian telephone survey, Internet gamblers were less likely to drink alcohol and smoke
when they were gambling online than when gambling in land-based venues, indicating they
were unlikely to be using Internet modes to avoid restrictions on smoking or alcohol [13].
Overall, existing studies fail to define specific personal or behavioural risk factors to
differentiate between Internet and non-Internet problem gamblers. There is some evidence
that these do represent at least partially different cohorts, however, the heterogeneity in each
group makes identification of specific risk factors difficult to identify. No studies have
established the causation between associations found and the direction of any link between
problem online gambling. The individual factors related to Internet gambling problems are
under-researched and would benefit from longitudinal studies to clarify the mechanism of
action of any relationships between variables.
Gambling behaviours
Intense gambling involvement has been verified as a predictor of gambling problems for
online and offline gamblers. Other gambling-related behaviours have also been identified as
being potential markers of risky Internet gambling. Gambling online on unregulated sites [41,
74] and using multiple different accounts [75] and different online activities [20, 48, 57] have
been found to be predictive of higher levels of gambling problems. It is possible that
unregulated sites attract individuals who are at greater risk for experiencing problems and use
Gainsbury Online Gambling Addiction 9
of multiple online accounts and multiple activities are proxy indicators of gambling
involvement, a known predictor of harm.
Analyses of player accounts, including players who exhibit what appears to be risky
behaviour, as well as those who have closed accounts due to stated gambling problems, have
enabled markers of problem gambling, including early predictors, to be identified. Potential
predictors of risky Internet gambling or the emergence of problems include: engaging in
multiple online gambling activities, high variability in betting, multiple bets per day, many
active betting days per month, many bets per betting day, high overall stakes and net loss,
increasing bet size and losses, chasing losses, and intervals of increasing wagering size,
followed by rapid drops [58, 59, 76-80]. One notable finding from studies of the bwin.party
dataset (which include most of the behavioural analyses that have been conducted) is the
consistent finding that participation in Live Action sports betting (also known as in-play) is
an independent predictor of problem gambling severity, when controlling for gambling
involvement [58, 59, 79]. This type of betting allows frequent and repeated bets to be placed
during a single sporting event, with rapidly determined outcomes, which may be particularly
attractive to people who are highly impulsive and at greater risk for disordered gambling
[81]. However, this relationship has not been investigated in independent samples.
In addition to behavioural variables, other information about gamblers’ risk levels can be
observed by online operators. Analysis of customer communication with online operators
identified risk markers that predicted customers closing their accounts due to stated gambling
problems. These included expressed doubts about results of games, requests for account
reopening, queries about financial transactions and account administration, the frequency of
contacts per month (urgency), and use of a threatening tonality [82]. These results were based
on a relatively small sample with a limited control group. A subsequent study found that
automated text analyses of email correspondence aided by human assessment could identify
anger (abusive tonality) as well as urgency (time-related words) and a lower use of
justification for demands and/or actions, which were found to predict self-exclusion [83].
Single, unmistakable indicators for problems are uncommon, and therefore detection of risk
indicators usually relies on algorithms to detect interaction between these. Further research is
still required to untangle whether game-specific characteristics play a causal role in the
emergence of gambling problems. Research is also needed on a variety of different player
accounts, as the vast majority of research has been done with a single dataset from one
European gambling site, which may not be generalizable to other online gamblers.
Identifying, detecting, and acting on early risk indicators may reduce gambling-related harms
sustained by Internet gamblers. However, few online operators have shared their data to be
used for research purposes or implemented policies and strategies to detect potentially risky
players and implement appropriate resources. Such preventative action is generally not
Gainsbury Online Gambling Addiction 10
required by Internet gambling regulators, meaning that further action is reliant on operator
initiated action.
Conclusions
Taken together, the evidence reviewed here suggests that Internet gambling does not cause
gambling problems in, and of, itself. However, use of Internet gambling is more common
among highly involved gamblers and for some Internet gamblers, this medium appears to
significantly contribute to gambling problems. Internet gamblers are a heterogeneous group
and the impact of this mode of access on gambling problems is moderated by a range of
individual, social, and environmental variables. As Internet gambling continues to evolve and
participation increases, particularly among young people who are highly familiar with
Internet technology and online commerce, it is likely that related problems will emerge.
Research and regulation will have to evolve to further the understanding of the impact of this
mode of access on the experience and incidence of gambling disorders.
There appear to be some unique differences between Internet and land-based gamblers who
experience problems [20]. Theoretical models for gambling and problem gambling have been
developed based on land-based gambling, largely not considering the recent emergence of
Internet modes. It is important to revisit these conceptual models to verify if they account for
pathological gambling among Internet gamblers, and whether any new variables or
interactions should be included to explain the emergence of gambling problems. Research
will likely continue to distinguish the characteristics (mediators and moderator) that may be
used to identify online gamblers who are at-risk for gambling-related problems. This is
necessary to develop a more comprehensive understanding of how people develop gambling
problems.
Research is needed to understand how to reduce the likelihood of people transitioning to
disordered gambling. The Internet offers a potentially strong environment for the provision of
responsible gambling, including player-focused tools and resources for moderating play such
as expenditure tracking, self-set spend limits, time-outs, and information[19, 84].
Furthermore, operators can enact strategies to assist customers including targeted
notifications (e.g., pop-up messages) based on patterns of play, and other tailored contacts
derived from analysis of player accounts to identify risky behaviour [2, 85]. Enhancing the
provision of a responsible gambling environment will require cooperation between
independent researchers to design, evaluate, and verify strategies, operators to enable access
to appropriate data and implement procedures, and regulators to require the use of effective
responsible gambling policies. Treatment and prevention strategies must be revisited to
ensure that these are relevant and effective for Internet gamblers. Brief online interventions as
well as in-depth online treatment programs may be relevant for Internet gamblers [86].
Online self-exclusion programs should be developed that would allow individuals to exclude
themselves from multiple gambling sites simultaneously.
Gainsbury Online Gambling Addiction 11
The findings presented here are important for policy makers due to evidence that Internet
gambling in itself is not harmful. The research is also relevant for clinicians, as it suggests
that in addition to some gambling forms being more likely to lead to problems, how
individuals access these also has an impact on subsequent harms. This highlights the
importance of considering the broad spectrum of gambling behaviour and how different
patterns of gambling may be associated with the experience of gambling-related harm.
Further research is required to identify the protective factors of online gambling
environments that may reduce levels of harms among Internet gamblers. These may include
the capacity for lower bet sizes than in land-based venues (due to lower costs for operators),
the ability to track wins, losses, and deposits using an online account, gambling only for short
sessions due to other activities concurrently occurring in the home, or outside of a gambling
venue, presence of others when gambling, and access to responsible gambling tools and
resources [51].
Compliance with Ethics Guidelines
Conflict of Interest
Dr. Gainsbury has received grants from Gambling Research Australia, NSW Office of Liquor, Gaming
and Racing, Echo Entertainment, Aristocrat Leisure Industries, Manitoba Gambling Research
Program, and Sportsbet pertaining to research to understand and enhance the responsible provision
of Internet gambling; research to understand optimal treatment approaches for gambling; research
to enhance responsible gambling strategies; and assessment of problem gambling among casino
employees. Dr. Gainsbury has received honoraria from the Department of Broadband
Communication and the Digital Economy, Department of Social Services, Gaming Technologies
Association, British Columbia Lottery Corporation; and Nova Scotia Provincial Lotteries and Casino
Corporation for research and expertise to inform responsible gambling messages and responsible
gambling strategies for Internet gambling. Dr. Gainsbury has received travel accommodations or
expense reimbursement from the British Columbia Lottery Corporation, Clubs ACT, Leagues Clubs
Australia, National RSL Clubs, Nova Scotia Gaming Corporation, and Casinos Austria to attend and
present at conferences on topic of responsible gambling. Dr. Gainsbury was a board member on
Techlink Entertainment’s Responsible Gambling Advisor Board from January 2012 through May
2013.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the
authors.
References
Papers of particular interest, published recently, have been highlighted as:
* Of importance
Gainsbury Online Gambling Addiction 12
** Of major importance
1. Gainsbury S, Wood R. Internet gambling policy in critical comparative perspective:
The effectiveness of existing regulatory frameworks. Int Gambl Stud. 2011;11:309-
323.
2. Monaghan S. Responsible gambling strategies for Internet gambling: The theoretical
and empirical base of using pop-up messages to encourage self-awareness. Comput
Hum Behav. 2009;25(1):202-207.
3. American Psychiatric Association. DSM 5. American Psychiatric Association; 2013.
4. Dowling NA. Issues raised by the DSM5 internet gaming disorder classification and
proposed diagnostic criteria. Addiction. 2014;109(9):1408-9.
5. H2 Gambling Capital. The online gambling market. Reported by Bwin.party digitial
entertainment; 2014. Available from:
https://www.bwinparty.com/AboutUs/OurMarkets/The%20online%20gaming%20mar
ket.aspx
6. Global Betting and Gaming Consultants. Global Gaming Report (6th ed.). Castletown,
Isle of Man, British Isles: Author; 2011.
7. H2 Gambling Capital. There’s nothing virtual about the opportunity in real-money
gambling. Odobo: Gibraltar; 2013.
8. PricewaterhouseCoopers. Global gaming outlook. Dec 2011. Available from
http://www.pwc.com/en_GX/gx/entertainment-media/publications/global-gaming-
outlook.jhtml
9. Lycka M. Online gambling: towards a transnational regulation. Gaming Law Review
and Economics. 2011;15(4);179-195.
10. Gambling Commission (2014, Apr). Gambling participation: Activities and mode of
access. Gambling Commission. 2014 Apr. Available from:
http://www.gamblingcommission.gov.uk/pdf/Survey%20data%20on%20gambling%2
0participation%20year%20to%20March%202014.pdf
11. Productivity Commission. Gambling. Productivity Commission, Government of
Australia; 2010.
12. **Gainsbury S, Russell A, Hing N, Wood R, Lubman D, Blaszczynski A. The
prevalence and determinants of problem gambling in Australia: Assessing the impact
of interactive gambling and new technologies. Psychol Addict Behav.
2014;28(3):769-779.
Using a nationally representative telephone survey, this paper compared problem
gambling among Internet and non-Internet gamblers to reveal variables related to
each. The findings demonstrate that Internet problem gamblers experience harms also
related to land-based gambling and that gambling problems are related to overall
involvement and intensity rather than the mode of access used.
Gainsbury Online Gambling Addiction 13
13. Wardle H, Sproston K, Orford J, Erens B, Griffiths M, Constantine R, Pigott S.
British gambling prevalence survey 2007. NatCen; 2007 Available from:
http://www.gamblingcommission.gov.uk/pdf/britsh%20gambling%20prevalence%20s
urvey%202007%20-%20sept%202007.pdf
14. Gainsbury S, Wood R, Russell A, Hing N, Blaszczynski A. A digital revolution:
Comparison of demographic profiles, attitudes and gambling behavior of Internet and
non-Internet gamblers. Comput Hum Behav. 2012;28(4):1388-1398.
15. McCormack A, Griffiths MD. Motivating and inhibiting factors in online gambling
behaviour: A grounded theory study. Int J Ment Health Addict. 2012;10(1):39-53.
16. Wood RT, Williams RJ, Lawton PK. Why do Internet gamblers prefer online versus
land-based venues? Some preliminary findings and implications. J Gambl Issues.
2007;20:235-252.
17. Cotte J, Latour KA. Blackjack in the kitchen: Understanding online versus casino
gambling. J Consum Res. 2009;35(5):742-758.
18. Gainsbury S, Parke J, Suhonen N. Attitudes towards Internet gambling: Perceptions of
responsible gambling, consumer protection, and regulation of gambling sites. Comput
Hum Behav. 2013;29:235-245.
19. *Gainsbury SM, Russell A, Hing N, Wood R, Blaszczynski A. The impact of Internet
gambling on gambling problems: A comparison of moderate-risk and problem
Internet and non-Internet gamblers. Psychol Addict Behav. 2013;27:10921101.
Based on a large online survey, moderate-risk and problem gamblers were compared
based on their use of Internet gambling. The results demonstrate that Internet
gamblers who experience gambling-related harms appear to represent a somewhat
different group from non-Internet problem and moderate-risk gamblers - Internet
gamblers were younger, engaged in a greater number of gambling activities, and
were more likely to bet on sports.
20. Griffiths MD, Parke J. The social impact of internet gambling. Soc Sci Comput
Rev. 2002;20(3):312-320.
21. National Gambling Impact Study Commission. National Gambling Impact Study
Commission-Final Report; 1999. Available from
http://www.ncfpc.org/specialngisc.html.
22. Watson S, Liddell Jr P, Moore RS, Eshee Jr WD. The legalization of Internet
gambling: a consumer protection perspective. J Public Policy Mark. 2004;23(2):209-
213.
23. *Wood RT, Williams RJ. Problem gambling on the Internet: Implications for Internet
gambling policy in North America. New Media Soc. 2007;9(3):520-542.
This paper was based on one of the first comprehensive studies of Internet gambling
in a Canadian and international sample. The article provided substantial new insight
into how Internet and land-based gamblers differ.
Gainsbury Online Gambling Addiction 14
24. Adams GR, Sullivan AM, Horton KD, Menna R, Guilmette AM. A study of
differences in Canadian university students' gambling and proximity to a casino. J
Gambling Issues. 2007;19:9-18.
25. LaPlante, DA, Shaffer HJ. Understanding the influence of gambling opportunities:
Expanding exposure models to include adaptation. Am J Orthopsychiat.
2007;77(4):616-623.
26. Reith G. Beyond addiction or compulsion: the continuing role of environment in the
case of pathological gambling. Addiction. 2012;107:1736-1737.
27. Sévigny S, Ladouceur R, Jacques C, Cantinotti M. Links between casino proximity
and gambling participation, expenditure, and pathology. Psychol Addict Behav.
2008;22(2):295-301.
28. Storer J, Abbott M, Stubbs J. Access or adaptation? A meta-analysis of surveys of
problem gambling prevalence in Australia and New Zealand with respect of
concentration of electronic gaming machines. Int Gambl Stud, 2009;9:225244.
29. Welte JW, Wieczorek WF, Barnes GM, Tidwell MC, Hoffman JH. The relationship
of ecological and geographic factors to gambling behavior and pathology. J Gambl
Stud. 2004;20(4):405-423.
30. Griffiths MD, Wardle H, Orford J, Sproston K, Erens B. Sociodemographic correlates
of internet gambling: Findings from the 2007 British gambling prevalence survey.
Cyberpsychol Behav. 2009;12:199202.
31. Hing N, Cherney L, Gainsbury S, Lubman D, Wood R, Blaszczynski A. Maintaining
and losing control during Internet gambling: A qualitative study of gamblers’
experiences. New Med Soc. 2014. Online first 27-01-14 DOI:
10.1177/1461444814521140
32. McCormack A, Griffiths MD. A scoping study of the structural and situational
characteristics of internet gambling. Int J Cyber Behav Psychol Learn. 2013;3(1):29-
49.
33. Valentine G, Hughes K. Shared space, distant lives? Understanding family and
intimacy at home through the lens of internet gambling. T I Brit
Geogr. 2012;37(2):242-255.
34. Wood RT, Williams RJ, Parke J. The relationship between Internet gambling and
problem gambling. In R. J. Williams, R.T. Wood., & J. Parke (Eds.) Routledge
Handbook on Internet Gambling, Oxon, UK; 2012:200-212.
35. *Gainsbury S, Russell A, Wood R, Hing N, Blaszczynski A. How risky is Internet
gambling? A comparison of subgroups of Internet gamblers based on problem
gambling status. New Media Soc. Published OnlineFirst Jan 15, 2014.
doi:10.1177/1461444813518185
Based on an online survey, problem and non-problem Internet gamblers were
compared. Problem gamblers were shown to represent a distinct cohort of gamblers,
demonstrating the heterogeneity of Internet gamblers. Problem gambling respondents
Gainsbury Online Gambling Addiction 15
were younger, less educated, had higher household debt, lost more money and
gambled on a greater number of activities, and were more likely to use drugs while
gambling as compared to non-problem and at-risk gamblers. For problem gamblers,
Internet gambling poses unique problems related to electronic payment and constant
availability leading to disrupted sleeping and eating patterns.
36. Hing N, Gainsbury S, Blaszczynski A, Wood R, Lubman D, Russell A. Interactive
Gambling. Report commissioned by Gambling Research Australia. Centre for
Gambling Education & Research, Southern Cross University; 2014. Available from:
http://www.gamblingresearch.org.au/home/interactive+gambling+pdf
37. Siemens JC, Kopp SW. The influence of online gambling environments on self-
control. Journal Public Policy Mark. 2011;30:279293.
38. Wood R, Williams R. Internet Gambling: Prevalence, Patterns, Problems, and Policy
Options. Guelph, Ontario: Ontario Problem Gambling Research Centre; 2010.
39. GamCare (2014). Briefing paper: GamCare annual statistics 2013/14. Available from:
http://www.gamcare.org.uk/news-and-media/publications/annual-reviews-and-
statistics#.VL7vDUeUfwg
40. Svensson J, Romild U. Incidence of Internet gambling in Sweden: results from the
Swedish longitudinal gambling study. Int Gambl Stud. 2011;11(3):357-375.
41. Hing N, Russell AMT, Gainsbury SM, Blaszczynski A. Characteristics and help-
seeking behaviors of Internet gamblers based on most problematic mode of
gambling. J Med Internet Res. 2015;17(1): E13. DOI:10.2196/jmir.3781
42. Wood R, Williams R. A comparative profile of the Internet gambler: Demographic
characteristics, game play patterns, and problem gambling status. New Media Soc.
2011;13:11231141.
43. Griffiths M, Wardle H, Orford J, Sproston K, Erens B. Internet gambling, health,
smoking and alcohol use: Findings from the 2007 British Gambling Prevalence
Survey. Int J Ment Health Addict. 2011;9:111.
44. Kairouz S, Paradis C, Nadeau L. Are online gamblers more at risk than offline
gamblers? Cyberpsychol Behav Soc Netw. 2012;15:175180.
45. MacKay TL, Hodgins DC. Cognitive distortions as a problem gambling risk factor in
Internet gambling. Int Gambl Stud. 2012;12(2):163-175.
46. Petry NM. Internet gambling: an emerging concern in family practice medicine? Fam
Pract. 2006;23:421-426.
47. *Wardle H, Moody A, Griffiths M, Orford J, Volberg R. Defining the online gambler
and patterns of behaviour integration: Evidence from the British Gambling Prevalence
Survey 2010. Int Gamb Stud. 2011;11(3):339-356.
This paper presented analyses based on the 2010 British Gambling Prevalence
Survey examining the integration of online and offline gambling, including gamblers
that use both modes. This was one of the first papers to highlight that there are very
Gainsbury Online Gambling Addiction 16
few pure Internet-only gamblers and gambling problems appeared to be highest
among those who were more involved in a variety of forms.
48. McBride J, Derevensky J. Internet gambling behavior in a sample of online
gamblers. Int J Ment Health Addict. 2009;7(1):149-167.
49. LaPlante, DA, Nelson SE, LaBrie RA, Shaffer HJ. Disordered gambling, type of
gambling and gambling involvement in the British gambling prevalence survey 2007.
Eur J Public Health. 2011;21:5327.
50. **Philander KS, MacKay TL. Online gambling participation and problem gambling
severity: is there a causal relationship?. International Gambling Studies, 2014;14:214-
227.
This paper presents the results of a sophisticated analysis of several gambling
prevalence surveys. Controlling for involvement, the analyses demonstrate that
Internet gambling is not related to gambling problems and public health concerns
based on simplistic analyses may be overstated.
51. Welte JW, Barnes GM, Tidwell MO, Hoffman JH. The association of form of
gambling with problem gambling among American youth. Psychol Addict Behav.
2009;23:105112.
52. Abbott M, Bellringer M, Garrett N, Mundy-McPherson S. New Zealand 2012
National Gambling Study: Gambling harm and problem gambling: Report number 2.
Gambling & Addictions Research Centre. AUT University: Auckland, New Zealand;
2014.
53. Welte JW, Barnes GM, Tidwell MCO, Hoffman JH, Wieczorek WF. Gambling and
Problem Gambling in the United States: Changes Between 1999 and 2013. J Gambl
Stud. 2014. DOI: 10.1007/s10899-014-9471-4.
54. Planzer S, Gray HM, Shaffer HJ. Associations between national gambling policies
and disordered gambling prevalence rates within Europe. Int J Law
Psychiat. 2014;37(2):217-229.
55. **Gainsbury S. Russell A, Blaszczynski A, Hing N. The interaction between
gambling activities and modes of access: A comparison of Internet-only, land-based
only, and mixed-mode gamblers. Addict Behav. 2015; 41:34-40.
Based on a large online survey, participants were compared based on their use of
Internet, as well as land-based gambling. Results demonstrate that gamblers using
both Internet and land-based modes had the greatest overall involvement in gambling
and greatest level of gambling problems. This study confirms the importance of
considering gambling involvement across subgroups of Internet or land-based gamblers.
56. *Lloyd J, Doll H, Hawton K, Dutton WH, Geddes JR, Goodwin GM, Rogers RD.
Internet gamblers: A latent class analysis of their behaviours and health experiences. J
Gambl Stud. 2010a;26(3);387-399.
This paper reports the results of a large online survey in the UK using latent class
analyses to identify subgroups of gamblers based on their use of the Internet to
Gainsbury Online Gambling Addiction 17
gamble. This was one of the first papers to move away from the dichotomy of Internet
vs. non-Internet gamblers and made a significant contribution by showing that more
involved gamblers had highest clusters of gambling problems and that Internet
gamblers are a heterogeneous group.
57. **LaPlante DA, Nelson SE, Gray HM. Breadth and depth involvement:
Understanding Internet gambling involvement and its relationship to gambling
problems. Psychol Addict Behav 2014;28:396-403.
This is one of a series of papers based on an online database of actual gamblers from
a European operator. This paper includes the innovative methodology of a self-report
screen with behavioural data. Analysing gambling across different types of activities,
this paper demonstrates that the extent of overall involvement (types of games and
days played) is related to gambling problems.
58. Brosowski T, Meyer G, Hayer T. Analyses of multiple types of online gambling
within one provider: An extended evaluation framework of actual online gambling
behaviour. Int Gambl Stud. 2012;12(3): 405-419.
59. Currie SR, Hodgins DC, Wang J, el-Guebaly N, Wynne H, Chen S. Risk of harm
from gambling in the general population as a function of level of participation in
gambling activities. Addiction. 2006;101:570580.
60. Holtgraves T. Evaluating the problem gambling severity index. J Gambl Stud.
2009;25(1):105-120.
61. LaPlante DA, Afifi TO, Shaffer H J. Games and gambling involvement among casino
patrons. J Gambl Stud. 2013;29:191203.
62. McCormack A, Shorter GW, Griffiths MD. An examination of participation in online
gambling activities and the relationship with problem gambling. J Behav Addict.
2013a;2(1):31-41.
63. Tom MA, LaPlante DA, Shaffer HJ. Does Pareto Rule Internet Gambling? Problems
Among The “Vital Few” & “Trivial Many”. J Gambl Bus Econ. 2014;8(1):73-100.
64. Dowling NA, Lorains FK, Jackson AC. Are the profiles of past-year internet gamblers
generalizable to regular internet gamblers? Comput Hum Behav. 2015;43:118-128.
65. Hayer T, Meyer G. Internet self-exclusion: Characteristics of self-excluded gamblers
and preliminary evidence for its effectiveness. Int J Ment Health
Addict. 2011;9(3):296-307.
66. McCormack A, Shorter GW, Griffiths MD. Characteristics and predictors of problem
gambling on the Internet. Int J Ment Health Addict. 2013b;11(6):634-657.
67. Jiménez-Murcia S, Stinchfield R, Fernández-Aranda F, Santamaría JJ, Penelo E,
Granero R, ... Menchón JM. Are online pathological gamblers different from non-
online pathological gamblers on demographics, gambling problem severity,
psychopathology and personality characteristics?. Int Gambl Stud. 2011;11(3):325-
337.
Gainsbury Online Gambling Addiction 18
68. Hopley AA, Nicki RM. Predictive factors of excessive online poker
playing. Cyberpsychol Behav Soc Netw. 2010;13(4):379-385.
69. Lloyd J, Doll H, Hawton K, Dutton WH, Geddes JR, Goodwin GM, Rogers RD. How
psychological symptoms relate to different motivations for gambling: An online study
of internet gamblers. Biol Psychiat. 2010b;68(8):733-740.
70. Petry NM, Weinstock J. Internet gambling is common in college students and
associated with poor mental health. Am J Addiction. 2007;16:325330.
71. Leeman RF, Potenza MN. Similarities and differences between pathological gambling
and substance use disorders: a focus on impulsivity and
compulsivity. Psychopharmacology. 2012;219(2):469-490.
72. Scholes-Balog KE, Hemphill SA. Relationships between online gambling, mental
health, and substance use: a review. Cyberpsych Behav Soc Netw. 2012;15(12):688-
692.
73. Tryggvesson K. Internet poker in Sweden: The extent, development and structure in
2006, English summary of Nätpokerspelandet i Sverige: Omfattning, utveckling och
karaktär 2006 Soradrapport 43 Stockholm: Stockholm University; 2007.
74. Gainsbury S, Russell A, Blaszczynski A, Hing N. Greater involvement and diversity
of internet gambling as a risk factor for problem gambling. Eur J Pub Health (in
press).
75. Adami N, Benini S, Boschetti A, Canini L, Maione F, Temporin M. Markers of
unsustainable gambling for early detection of at-risk online gamblers. Int Gambl Stud.
2013;188-204.
76. Braverman J, LaPlante DA, Nelson SE, Shaffer HJ. Using cross-game behavioral
markers for early identification of high-risk internet gamblers. Psychol Addict Behav.
2013;27(3):868-877.
77. Braverman J, Shaffer HJ. How do gamblers start gambling: Identifying behavioural
markers for high-risk internet gambling. Eur J Public Health. 2012;22(2), 273-8.
78. Gray HM, LaPlante DA, Shaffer H J. Behavioral characteristics of Internet gamblers
who trigger corporate responsible gambling interventions. Psychol Addict Behav.
2012;26(3):527.
79. Xuan Z, Shaffer H. How do gamblers end gambling: Longitudinal analysis of
Internet gambling behaviors prior to account closure due to gambling related
problems. J Gambl Stud. 2009;25(2):239-252.
80. Blaszczynski A, Nower L. A pathways model of problem and pathological
gambling. Addiction. 2002;97(5):487-499.
81. Haefeli J, Lischer S, Schwarz J. Early detection items and responsible gambling
features for online gambling. Int Gambl Stud. 2011;11: 273288.
82. Haefeli J, Lischer S, Haeusler J. Communications-based early detection of gambling-
related problems in online gambling. Int Gambl Stud. 2015. Advanced online
publication DOI: 10.1080/14459795.2014.980297
Gainsbury Online Gambling Addiction 19
83. Griffiths MD, Wood RTA, Parke J. Social responsibility tools in online gambling: A
survey of attitudes and behaviour among Internet gamblers. Cyberpsychol Behav.
2009;12:413-421.
84. Gainsbury S. Player account-based gambling: Potentials for behaviour-based research
methodologies. Int Gambl Stud. 2011;11(2):153-171.
85. Gainsbury S, Blaszczynski A. Online self-guided interventions for the treatment of
problem gambling. Int Gambl Stud. 2011;11:289-308.
... Individuals can gamble in offline brickand-mortar establishments such as casinos, gambling halls, amusement arcades and betting shops or they can gamble online. Online gambling products are usually similar to landbased products and the only difference is the mode of access (Gainsbury, 2015). A number of previous studies have underlined the elevated risk of online gambling (e.g., Griffiths et al. 2006;Hubert & Griffiths 2018;McBride & Derevensky, 2009;McCormack et al., 2014). ...
... Moreover, online gamblers are usually able to select from a greater variety of games and play multiple games in parallel on the internet which has shown to be a risk factor for problematic gambling (Braverman et al., 2013;McCormack et al., 2014). In a review of the available literature Gainsbury (2015) concluded that online gambling did not cause gambling problems in, and of, itself. However, the review showed that online gambling was more common among highly involved gamblers, and for some online gamblers, this medium appeared to significantly contribute to gambling problems. ...
... Researchers have also found that adolescents are vulnerable to developing online gambling problems (e.g., Gainsbury 2015;Hubert & Griffiths, 2018). Part of the explanation involves the developmental characteristics of adolescence, which is a period of particular vulnerability to engage in multiple forms of risky behavior (Jessor, 1991) and develop addiction problems due to immature self-regulation capacity, impulsivity, external locus of control, and susceptibility to contextual factors (Hollén et al., 2020). ...
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Player protection has become an important area for the gambling industry over the past decade. A number of gambling regulators now require gambling operators to interact with customers if they suspect they are gambling in a problematic way. The present study provided insight on the impact of personalized feedback interventions (PFIs) on subsequent gambling behavior among a Dutch sample of real-world gamblers. Nederlandse Loterij (the national Dutch Lottery operator) provided access to a secondary dataset comprising tracking data from online casino and sports betting gamblers (N = 2,576) who were contacted either by e-mail or telephone between November 2021 and March 2022 if they showed signs of problematic gambling as identified using behavioral tracking software. Compared to matched controls (n = 369,961 gamblers), Dutch gamblers who received a PFI (via e-mail [n = 1876] or a telephone call [n = 700]) from the gambling operator had a significant reduction in amount of money deposited, amount of money wagered, number of monetary deposits, and time spent gambling in the 30 days after being contacted. Gambling frequency as measured by the number of gambling days did not change significantly after a PFI. Telephone calls did not lead to a significant larger reduction with respect to the aforementioned behavioral metrics. High-intensity players reduced their gambling behavior as frequently as low-intensity players, which means that the intervention’s success was independent of gambling intensity. The impact on subsequent gambling was the same across age groups and gender. The results of the present study are of use to many different stakeholder groups including researchers in the gambling studies field and the gambling industry as well as regulators and policymakers who can recommend or enforce that gambling operators utilize responsible gambling tools such as using PFIs to those who may be displaying problematic gambling behaviors as a way of minimizing harm and protecting gamblers.
... The present study is the second phase of the EDEIN project (Etude de Dépistage des comportements Excessifs de jeu sur Internet; Screening for Excessive Gambling Behaviours on the Internet) (Gainsbury, 2015). Here, we developed and validated a prediction model for online gambling problems based on players' account data, and addressed the aforementioned limitations (i.e. using a clinical definition of problematic gambling, considering the full range of authorized online gambling activity, and using appropriate statistical methods). ...
... The chasing behavior is indeed considered as a very relevant indicator for identifying gamblers at risk of gambling problems, especially based on behavioral data (Braverman et al., 2014;Costes et al., 2015;Gerstein et al., 1999;Griffiths, 2003;Haefeli, Lischer, & Schwarz, 2011). Because the chasing behavior is not observable directly from the gambling tracking data, we had to approximate it with two proxies as was done by Perrot et al. (Gainsbury, 2015). The first was based on the observation of recurrent deposits of money within a short period of time. ...
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Background and aims: Gambling disorder is characterized by problematic gambling behavior that causes significant problems and distress. This study aimed to develop and validate a predictive model for screening online problem gamblers based on players' account data. Methods: Two random samples of French online gamblers in skill-based (poker, horse race betting and sports betting, n = 8,172) and pure chance games (scratch games and lotteries, n = 5,404) answered an online survey and gambling tracking data were retrospectively collected for the participants. The survey included age and gender, gambling habits, and the Problem Gambling Severity Index (PGSI). We used machine learning algorithms to predict the PGSI categories with gambling tracking data. We internally validated the prediction models in a leave-out sample. Results: When predicting gambling problems binary based on each PGSI threshold (1 for low-risk gambling, 5 for moderate-risk gambling and 8 for problem gambling), the predictive performances were good for the model for skill-based games (AUROCs from 0.72 to 0.82), but moderate for the model for pure chance games (AUROCs from 0.63 to 0.76, with wide confidence intervals) due to the lower frequency of problem gambling in this sample. When predicting the four PGSI categories altogether, performances were good for identifying extreme categories (non-problem and problem gamblers) but poorer for intermediate categories (low-risk and moderate-risk gamblers), whatever the type of game. Conclusions: We developed an algorithm for screening online problem gamblers, excluding online casino gamblers, that could enable the setting of prevention measures for the most vulnerable gamblers.
... Some research suggests features specific to online gambling, such as constant availability, ease of access, electronic payments, and anonymity contribute to a greater potential for harm [29]. One 2015 review paper did not find an association between online gambling and PG, however, the study found that while online gambling participation rates increased in several jurisdictions, limited evidence showed an increase in PG prevalence rates [30]. In addition, factors relating to the unique characteristics and behaviors of online gamblers may also play a role in risk of harm. ...
... McGee (2020) also explored the impacts of advertising and betting-related promotions, such as free-bet inducements, on younger populations (which the authors defined as ages [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] and suggested such promotions were encouraging risky gambling behaviors [64]. Meanwhile, Newall et al., (2019) posit that in-play betting is growing as a result of betting advertising and they identify in-play promotions as playing a significant role in PG behaviors, as previously outlined in Key Area I [65]. ...
... It is currently defined as persistent and recurrent engagement in gambling behavior that leads to clinically significant impairment or distress (24). Recent studies have shown that video game microtransactions are associated with a greater risk of problem gambling (25)(26)(27)(28)(29)(30). Systematic reviews, meta-analyses, and cross-sectional studies have reported a significant relationship between problem gambling and video game microtransaction, mainly through loot box (31-37) but rarely with gacha. ...
... Furthermore, male gamers were found, by and large, to spend more on loot box as compared to female gamers (15,25,32,37,41,(45)(46)(47). Gamers with habits of online gambling and other gambling activities also had a higher risk of problem gambling (28,48). ...
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Objective The objective of this study is to explore the association of problem gambling with demographics, psychological distress, and gaming behavior in young adult gacha gamers in Hong Kong. Materials and methods Cross-sectional data was collected in the first and fifth waves of COVID-19 pandemic in Hong Kong online. Participants who aged 18–25 years and had been playing gacha games over the past 12 months were recruited. Stepwise multiple regression was used to explore the association among risk of problem gambling, gaming behavior, participation in gaming activities and psychological distress. A two-sided p-value <0.05 was considered as statistical significance. Results Three hundred and thirty-seven completed questionnaires were received with no missing data. 34.7% ( n = 117) of the participants had non/low-risk of problem gambling. About 40% ( n = 136) of them had moderate-risk and the remaining 25% ( n = 84) were at high risk of problem gambling. A higher proportion of female participants (78.6%) were found in high-risk group as compared to 39.7% and 55.6% only in the non/low-risk and moderate-risk groups, respectively. The regression model ( R ² = 0.513, F = 71.895, p < 0.001) showed that 51.3% of the variance of the total problem gambling score could be explained by stress, anxiety, monthly expenses on gacha purchases, number of motives for gacha purchase and number of gambling activities engaged. Conclusion The present study provides empirical evidence to support the association between problem gambling and microtransaction especially for gacha which is the most popular type of video game microtransaction in Asia. The established regression model suggests that gacha gamers with higher risk of problem gambling tend to have greater stress, higher anxiety level, spend more on gacha purchase, have more motives for gacha purchases and engage in more gambling activities. In contrast to the extant literature, higher proportion of female participants in high-risk group indicates that female gacha gamers are also at very high risk of becoming problem gamblers.
... wagering an average of $200 million a day, while the industry generates $2.2 billion in gross revenue annually (Habib, 2005). Along with the growth of the gambling industry and the corresponding increase in approval and convenience, there has also been a rise in the prevalence of pathological and problem gambling, with the rate of disordered gambling among the youths have risen significantly (Gainsbury, 2015). For most individuals, gambling provides a harmless and entertaining diversion from everyday life (Seay & Kraut, 2007). ...
... Studies have shown that college and university students have the highest rates of gambling and problem gambling (Conrad, 2014;Kam et al., 2017;Petry & Gonzalez-Ibanez, 2013;Williams et al., 2006). However, ongoing academic discourse appears to be limited to university students' reasons for gambling, perception and attitudes towards gambling and its implications on their lives on campus especially in developing countries like Ghana (Glozah et al., 2021;Zheng & Peng, 2013;Wu & Chen, 2015;Macau and Singapore, Lungu, 2020;Kim et al., 2017;Seifried et al., 2009;Gainsbury, 2015). It also appears that there is limited literature on students' reasons, perceptions, and attitudes towards gambling and its implications on their lives on campus, especially at the university level in developing countries like Ghana. ...
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Despite the fact that online gambling is increasing among students in low- and middle-income countries, studies on the reasons and attitudes of university students toward gambling and its associated social, economic, and academic implications on their lives have not been adequately explored in the Ghanaian setting. This study employed an exploratory research design to investigate the reasons and attitudes of students toward online gambling and how online gambling has affected their social, economic, and academic lives on campus. An interview guide was used in soliciting data from fifteen participants. The thematic analytical framework was used to analyze the data. The analysis of the empirical data revealed that the ease of making quick money, the anonymous nature of online gambling and a source of entertainment were the main reasons why participants engaged in online gambling. Again, concerning participants’ attitudes towards gambling, most of them were frequent gamblers and gambled four to seven times a week while a few were occasional gamblers who gambled one to three times a month. The study also found that participants who gambled online ended up becoming depressed, had difficulties with sleeping, and barely concentrated in class because of their addictive attitudes towards online gambling. The study further revealed that the academic lives of participants were negatively affected as a result of excessive gambling. The study recommends that the university management should introduce university gambling policies and programmes to regulate gambling among university students and its associated socio-economic and academic implications.
... Adults are expected to self-regulate and when problems with a behavior arise, it could be deemed as personal failure or a lack of will. Adults are then exposed to risks to income loss and relationships [71][72][73][74]. Furthermore, in studies that identified prevention strategies, adult gamers were able to provide valuable insights on prevention [59,60]. ...
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There has been increasing interest in problem Internet use in the past five years, particularly in the areas of video gaming and screen use. Social cognitive approaches to prevention are more common than those that target multiple stakeholder groups and take into consideration the geopolitical-cultural aspect of the problem behavior. Additionally, there is a lack of randomized controlled trials and empirical research on this topic. Younger populations are typically studied with a focus on school-based interventions. Tailored programs that require active engagement should be developed and assessed for long-term efficacy with cost-efficiency in mind. Holistic programs that create change in a culture or society without restricting individual choices may also be beneficial in preventing problem Internet use. Addresses
... The latter limits were higher, and, for some harm indicators, more strongly predictive. They concluded that online gambling might require different limits than land-based gambling because of its higher risk profile (Brosowski, Olason, Turowski, & Hayer, 2021;Gainsbury, 2015). ...
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Background and aims Lower-risk recommendations for avoiding gambling harm have been developed as a primary prevention measure, using self-reported prevalence survey data. The aim of this study was to conduct similar analyses using gambling company player data. Methods The sample ( N = 35,753) were Norsk Tipping website customers. Gambling indicators were frequency, expenditure, duration, number of gambling formats and wager. Harm indicators (financial. social, emotional, harms in two or more areas) were derived from the GamTest self-assessment instrument. Receiver operating characteristics (ROC) curves were performed separately for each of the five gambling indicators for each of the four harm indicators. Results ROC areas under the curve were between 0.55 and 0.68. Suggested monthly lower-risk limits were less than 8.7 days, expenditure less than 54 €, duration less than 72–83 min, number of gambling formats less than 3 and wager less than 118–140€. Most risk curves showed a rather stable harm level up to a certain point, from which the increase in harm was fairly linear. Discussion The suggested lower-risk limits in the present study are higher than limits based on prevalence studies. There was a significant number of gamblers (5–10%) experiencing harm at gambling levels well below the suggested cut-offs and the risk increase at certain consumption levels. Conclusions Risk of harm occurs at all levels of gambling involvement within the specific gambling commercial environment assessed in an increasingly available gambling market where most people gamble in multiple commercial environments, minimizing harm is important for all customers.
... Internet gambling has been becoming increasingly common perhaps in part given its availability and accessibility. 127 Despite increased research of online gambling, most studies rely on self-reports and use convenience or self-selected samples. ...
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