gambling in alberta - Research Services - University of Lethbridge

census. A supplemental Online General Population sample was also collected via email
solicitation to Alberta online panellists 4 who were members of NetPanel. The purpose of
collecting an online sample was to investigate whether prevalence rates obtained with this
method would approximate the rates obtained with telephone surveys and potentially
supplement or replace telephone surveys (in light of their steadily declining response rates).
The size of the online sample was 2,019 in the summer of 2008 and 1,006 in the summer of
2009. The actual surveys themselves as well as comprehensive details about the methodology
used to conduct them are contained in Appendix A.
Changes in population attitudes, behaviour, and problem gambling prevalence rates over time
also provide an indirect way of gauging the impact of the introduction/expansion of the various
forms of gambling. Fortunately there have been several different population surveys of
gambling beginning in 1992 that permit this type of analysis (see Appendix B).
In addition to General Population surveys of adult Albertans, we also conducted ‘Targeted
Population Surveys’ where we examined the changes in attitudes, gambling behaviour, and
problem gambling in the summer of 2008 versus 2009 in 4 geographic areas that did not have
casinos prior to their introduction in late 2007/early 2008 (‘New Casino Areas’): Cold Lake area;
Whitecourt area; Camrose area; Morley area. To control for changes that might have occurred
simply as a function of time, we compared changes in the New Casino Areas to changes
observed in 5 geographic areas with well-established casinos (‘Established Casino Areas’): Fort
McMurray area; Grande Prairie area; Red Deer area; Medicine Hat area; Lethbridge area. (Note
also that these 5 control regions represent ‘rural’ areas, similar to the 4 New Casino areas). The
4 In recent years Survey Research firms have created ‘online panels’ composed of hundreds of thousands of
individuals who have agreed to receive online solicitations to participate in various online surveys in return for
compensation (most often, a collection of ‘points’ that have some cash value) (Göritz, 2007; Göritz et al., 2002).
When an individual joins one of these panels, information is collected concerning his/her demographics.
Subsequently, when a group is needed for a particular survey (e.g., ‘representative sample of Alberta adults’), the
survey is only sent out to this selected subsample. Online panels are now commonly used in market research, but
have rarely been used in academic studies. The advantages of online panel surveys are that a) the validity of
answers to ‘sensitive questions’ (e.g., gambling) tends to be higher in self-administered formats (Tourangeau &
Smith, 1996; van der Heijden et al., 2000); b) everyone has agreed to be and expects to be contacted (unlike
telephone surveys); c) the results can be obtained in a much shorter period of time; and d) they are roughly onethird
the cost of telephone surveys. However, there are several unanswered questions concerning online panels.
One concern is the degree to which panels are representative of the population. One obvious problem is that a
significant nonrandom minority of people still do not use the Internet. The most recent data for Canada shows
that 27% of Canadians 16 and older did not use the Internet in 2007, with nonusers significantly more likely to be
located in rural areas, have lower income, be older, and have less education (Statistics Canada, 2008).
Furthermore, although online panelists are structured to be demographically representative, other differences
likely exist, as only a small minority of people invited to be part of an online panel agree to participate (Sparrow,
2006). Concerns have also been expressed about the data quality when using ‘professional respondents’ who may
do dozens of surveys within the span of a few months (Göritz, 2007; Toepoel, Das & van Soest, 2008). Other
questions concern the optimal way of creating online panels, the effects of different types and magnitudes of
rewards, the appropriate number of contact/request attempts, appropriate deadline for questionnaire completion,
and the effects of nonresponse.
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