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Introduction
The global growth of gambling
and the increased popularity of the Internet have led to a greater number
of people having the ability and willingness to engage in Internet gambling
(Sinclair, 2000). Although Internet gambling is considered to be at an
early stage, virtually all observers assume the rapid growth of Internet
gambling will continue (National Gambling Impact Study Commission, 1999).
According to some estimates, $2.3 billion (US) a year is being spent on
Internet gaming worldwide, and the market has more than tripled in size
since 1997 (Mitka, 2001). One study, which features details on more than
1,400 gambling sites available worldwide, estimates that the number of
Internet gamblers will grow from approximately 4 million people in 1999
to 15 million by the year 2004 (Sinclair, 2000).
It has been argued that new
technologies are linked to "technological addictions" such as
computer game playing or gambling using video lottery terminals (Griffiths,
1995, 1996, 1999). Because the Internet can be used anonymously and is
open 24 hours a day, concerns have been raised regarding its potential
abuse by underage gamblers, seniors and pathological gamblers (National
Gambling Impact Study Commission, 1999).
In Canada, legalized gambling
experienced a rapid expansion in the 1990s and recent studies show that
the prevalence of gambling and gambling-related problems in the general
adult population is increasing (Jacques, Ladouceur & Ferland, 2000;
Korn, 2000; Shaffer, Hall & Vander Bilt, 1999). Although Internet
gambling represents another emerging public health issue (Korn, 2000;
Mitka, 2001), to date, there is no published research in the professional
literature on prevalence of Internet gambling among adults in Canada.
The purpose of this paper is to provide epidemiological estimates of Internet
gambling among Ontario adults.
Method
Our data are derived from the
2000 cycle of the Centre for Addiction and Mental Health CAMH Monitor
(CM), an annual cross-sectional telephone survey of Ontario adults.
The CM cycle consists of 12 independent monthly surveys with 200
completions expected each month. The 2000 survey used random-digit dialling
(RDD) methods via Computer Assisted Telephone Interviewing (CATI).
The design employed a two-stage
probability selection procedure. Each month a random sample of telephone
numbers was selected with equal probability in the first stage of selection
(i.e. households). Within selected households, one respondent aged 18
or older (who could complete the interview in English or French) was chosen
according to which household member had the most recent birthday. To increase
the precision of estimates from different areas of Ontario, the sample
was equally allocated among six strata by area code. The design resulted
in a total sample of 2,406 respondents, representing an effective response
rate of 61%. To maximize content coverage without increasing the length
of any single interview, two questionnaires were employed in CM 2000:
Panel A, representing interviews conducted from January to June, 2000,
and Panel B, representing interviews conducted from July to December,
2000. The gambling items discussed in this study were asked only of Panel
B respondents (N=1,294). Further details about the CM 2000 are available
(Adlaf, Ialomiteanu & Paglia, 2001).
Prevalence of Internet gambling
refers to betting money on-line to gamble. Respondents were asked how
often, in the past 12 months, they bet money using the Internet? Because
our design employed complex sampling methods, we used Taylor linearization
methods in order to ensure proper variance estimation for weighted complex
sampling (Stata Corporation, 1999). Subgroup analyses were conducted by
gender, age, marital status, region, education and income, using logit
models. The significance of the group effect was determined by adjusted
Wald statistics.
Results
As seen in Figure 1, Internet
gambling was the least commonly reported form of gambling for both men
and women. Overall, 5.3% (4.1% to 6.9%, 95% CI) of Ontario adults interviewed
in 2000 reported having gambled on the Internet during the past 12 months
(see Table 1). Although women were more likely to gamble on-line than
males (6.3% vs. 4.3%), the difference was not statistically significant.
There was a significant univariate effect for age, with people aged 50
to 64 reporting the lowest rates of Internet gambling, and those aged
65 and over reporting the highest rates (1.5% vs. 8.1% respectively),
but after controlling for other demographics this effect did not hold.
click for larger image
Only marital status was significantly
related to Internet gambling. Previously married (widowed, divorced) people
were significantly more likely to report on-line gambling compared to
those who were married (10.9% vs. 4.9%). There were no dominant regional,
educational or income differences.
Additional analyses revealed
that 6.7 % (5.1% to 8.7%, 95% CI) of past year gamblers (N= 1,042) reported
past year Internet gambling. Moreover, findings evident among the total
sample also held for those who gamble among the respective demographic
groups: women, people over 64, and previously married people reported
the highest rates of Internet gambling. But only marital status was a
significant predictor of gambling on-line after controlling for other
variables (data not shown).
(click
figure for larger image)
Discussion
Although the data provide some
unique and timely information regarding Internet gambling in Ontario,
they are not without limitations. Indeed, we must recognize that the estimates
of Internet gambling are potentially affected both by errors in reporting
Internet gambling and errors due to missing respondents. It is likely
that both types of error would understate the Internet gambling estimates.
Also, no information was gathered regarding the prevalence and frequency
of Internet use among Ontario adults.
Several implications and observations
may be drawn from the findings. First, many traditional demographic factors,
such as sex, age, region and socioeconomic factors, are not particularly
forceful factors in Internet gambling. This form of gambling is robust
and appears to span all configurations of individual social and economic
status. Second, although rates of Internet gambling are not excessive,
given the simultaneous expansion and diffusion of both Internet access
and gambling, continued surveillance is important. Third, given the absence
of a significant association between Internet gambling and low income,
some may speculate the existence of a potential regressive influence of
Internet gambling (Korn, 2000). In this context, investigations must assess
the association between Internet gambling and disposable income, which
was not examined in this study.
Some of the findings provide
a conduit for future investigation. First, we need to assess what may
be generalized and what are potential factors related to the elevated
rate of Internet gambling among previously married respondents. Although
this group also reported elevated rates of alcohol problems and psychological
distress (Adlaf & Ialomiteanu, 2001), additional analyses indicated
that such factors did not nullify the significant association between
marital status and Internet gambling. Another finding worthy of attention
is the elevated rate of Internet gambling among people aged 65 years and
older. Although the association between age and Internet gambling was
not significant, this finding still merits attention in future research.
References
- Adlaf, E.M. & Ialomiteanu,
A. (2001).
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A. & Paglia, A. (2001).
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Anca_Ialomiteanu @camh.net
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- Stata Corporation. (1999).
- Stata
Statistical Software: Release 6.0. College Station, TX: Stata Corporation
This article was peer-reviewed.
Submitted: July 11, 2001
Accepted: September 26, 2001
For correspondence:
Anca Ialomiteanu, MA
Research Analyst
Centre for Addiction and Mental Health
33 Russell Street, Toronto, Ontario, Canada M5S 2S1
Phone: (416) 535-8501 Ext. 6997
Fax: (416) 595-6899
E-mail: Anca_ Ialomiteanu
@camh.net
Anca Ialomiteanu, MA,
is a research analyst in the Social, Prevention and Health Policy Research
Department, Centre for Addiction and Mental Health, Toronto, Ontario.
She has a Master of Arts in Information Studies from the University
of Bucharest, Romania and has substantial experience in population survey
research and analysis, including gambling surveys. She has been involved
in the design and analysis of all cycles of the CAMH Monitor and the
1995 and 1997 Ontario Adult Gambling Surveys. She is a co-author of
the 1996 Ontario Gambling Report and has three peer-reviewed publications
and two conference presentations in the area of adult gambling and adolescent
gambling.
Edward Adlaf, PhD,
is a research scientist and head of the Population and Life Course Studies
Unit in the Social, Prevention and Health Policy Research Department
at the Centre for Addiction and Mental Health. He is currently the Director
of the Ontario Student Drug Use Survey, the longest monitoring study
of drug use among adolescents in Canada, and the CAMH Monitor, an annual
monitoring survey of Ontario adults. Dr. Adlaf holds an appointment
in the Department of Public Health Sciences, Faculty of Medicine, University
of Toronto, where he teaches survey methods.
Other research articles in
this issue
The
Effect of Skilled Gamblers on the Success of Less Skilled Gamblers
Internet
Gambling: Preliminary Results of the First U.K. Prevalence Study
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