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Tuesday's match between Greece and the Czech Republic has huge implications poland greece betting preview goal both sides poland greece betting preview goal terms of their chances to advance to the knockout stages of the European Championship. Greece was able to come away with a draw in its opening match against Poland in Warsaw, despite playing the majority of the match a man down. Poland greece betting preview goal Polish side looked in control, and it seemed they would start the tournament off with a win, but substitute Dimitris Salpingidis found the back of the net in the 51st minute to tie the game at one. The Czech Republic was taken behind the woodshed by Russia in its first match, falling in embarrassing fashion They'll certainly need a better effort if they want to avoid being all but mathematically eliminated after their first two games. Sokratis Papastathopoulos is suspended for this one after being sent off against Poland on a controversial call, to say the least. Avraam Papadopoulos, another key defensive contributor for the Greeks, is out of the tournament with a knee injury.

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Plus or minus in sports betting If you continue with this browser, you may medlar betting websites unexpected results. This measure was selected for medlar betting websites brevity, strong psychometric properties, and ability to discriminate pathological gambling cases from non-cases in general-purpose health surveys. Updated regularly. Bureau of the Census U. The heavily involved players played frequently, for a long duration, and were recognized by their financial commitment.
What companies will gain with legalized sports betting Inspec Analytics This link opens in a new window. How do gamblers start gambling: identifying behavioural markers for high-risk Internet gambling. Indexing and abstracts for scholarly business journals back to are included. The website indicates that Video Poker and Slots had the lowest returns to the players, overall losses of 6. Unlimited more Addresses from other domains [e. Comments 0.
Medlar betting websites Popular Databases. Medlar betting websites, the correlations based on the total sample suggest that some gamblers might experience personal problems unrelated to the amount of money risked. Toward a paradigm shift in Medlar betting websites gambling research: from opinion and self-report to actual behavior. The results in table 1 were conducted using chi-square goodness of fit tests. As such, results drawn from such studies may produce biased results that are not representative of Internet gamblers. Submit Cancel. This has led to concerns that the easy accessibility of gambling will contribute to and elevate the prevalence of problem gambling.
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Bettinger eric notaire dupuis Perceived disadvantages of Internet gambling medlar betting websites land-based gambling ref. Disordered gambling, type of gambling and gambling involvement in medlar betting websites British Gambling Prevalence Survey Results: The median betting behaviour was to play casino games once every 2 weeks during a period of 9 months. Related articles in PubMed An enhanced psychological mindset intervention to promote adolescent wellbeing within educational settings: A feasibility randomized controlled trial. Sarah E. Comment title.
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MOHEGAN SUN FOXWOODS SPORTS BETTING EXCLUSIVITY

This article reports the results of the first prospective longitudinal study of actual Internet casino gambling behaviour. Methods: Data include 2 years of recorded Internet betting activity by a cohort of gamblers who subscribed to an Internet gambling service during February We examined computer records of each transaction and transformed them into measures of gambling involvement.

The sample included gamblers who played casino games. Results: The median betting behaviour was to play casino games once every 2 weeks during a period of 9 months. Subscribers lost a median of 5. Their median percent of wagers lost, 2. The findings also show the need to consider time spent as a marker of disordered gambling.

These findings provide the evidence to steer public health debates away from speculation and toward the creation of empirically-based strategies to protect the public health. Pathological gambling is a public health problem associated with many physiological, psychological and social repercussions—some of which are shared with other expressions of addiction and some of which are unique to excessive gambling behaviour.

This article provides the first glimpse into the actual gambling behaviour, as opposed to self-reported gambling behaviour, of online casino gamblers. Rates of Internet gambling currently are low compared to other types of gambling. Studies have reported higher prevalence rates of Internet gambling in special populations, suggesting differential popularity and potency of Internet gambling for these groups.

LaBrie et al. This study revealed primarily moderate gambling behaviour at the population level i. However, the research also showed that a small percentage of subscribers i. Similarly, analyses of temporal patterns of sports gambling behaviour showed evidence of rapid population-level adaptation to online gambling. Our previous research 29 provided a unique description of actual Internet sports gambling, and a description of actual Internet poker play is forthcoming.

In comparison, chance governs casino games entirely. As a result, we expect that casino game play will differ in a few important ways from sports gambling and poker play. Structurally, casino play is more rapid; therefore, we expect that volume measures, such as number of bets, will be greater for casino gambling than for sports betting. Our research focusing on the gambling behaviour of people in treatment for gambling-related problems 31—33 suggests that casino games are the game of choice for people seeking treatment.

Despite the absence of epidemiologic evidence other than that presented here, we hypothesize that individuals betting in virtual casinos will exhibit riskier behaviours, such as more excessive loss patterns or time spent gambling, than observed among Internet sports bettors and poker players. However, we expect to find moderate and consistent gambling among the majority of the population with a small minority i.

This article describes the actual Internet casino gambling behaviour of a large cohort of participants during 2 years of a longitudinal study. We established a research cohort and accumulated their subsequent casino gambling transactions at a gambling website. The cumulative information base of these transactions documents each player's gambling behaviour at that site.

Although previous investigations examined the self-reported betting activity of Internet gambling on various types of games, 34 this is the first study to document the actual gambling behaviour of Internet gamblers playing casino-type games of chance. We present three types of results: i an epidemiological description of demographic characteristics of sequentially subscribed Internet casino gamblers; ii an epidemiological description of the casino gambling behaviour of these Internet gamblers and iii an epidemiological description of the Internet casino gambling behaviour of an empirically-determined group of heavily involved bettors.

The full research cohort included 48 people who opened an account with the Internet betting service provider, bwin Interactive Entertainment, AG bwin , in February The majority of subscribers engaged primarily in sports gambling. The large number of bettors excluded for limited involvement is typical of people curious enough to try the product, but not sufficiently interested to continue casino betting.

Finally, we excluded 15 bettors because they had limited exposure to casino play, starting their casino play less than 1 month before the end of the current study period i. The longitudinal cohort eligible for the study consisted of participants. The available demographic characteristics of the research sample included age, gender, country of residence and preferred language.

At enrollment, participants elected to interact with the wagering system in one of 22 languages. The daily aggregations provided summary measures of gambling behaviour. We obtained number of bets and total wagered by summing the daily aggregations. We measured the duration of gambling involvement as the number of days from the first eligible bet to the last i.

We defined the frequency of involvement as the percent of days within duration that included a bet i. We obtained the average bets per day by dividing the total number of bets made by the total number of days on which a bet was placed i. The net result of gambling i.

The dominant outcome is a net loss and, by subtracting total winnings from total wagers, positive values indicate net losses, the cost of gambling. Converting net losses to a percent of total wagers i. We conducted a secondary data analysis of the subscriber database obtained from bwin as described above.

We received approval from our Institutional Review Board to conduct this secondary data analyses. Tests for differences between group means included testing the assumption of equal variances and, if necessary, adjusting for unequal variances. We organized the analyses into three sections: i cohort characteristics; ii cohort gambling behaviour and iii the behaviour of heavily involved bettors. For cohort characteristics, we reported gender and country distributions, as well as gambling behaviour differences by gender.

For cohort gambling behaviour, we reported gambling involvement by time i. For gambling behaviour, we report medians because of the skewed nature of the gambling data. The players represented 46 countries. Consequently, the data did not justify additional gender-specific analyses.

The relationships between the means and the medians, and the size of the standard deviations in relation to the means, indicate that the total distribution is markedly skewed i. We will consider the heavily involved bettors in a later section. The distributions of the measures violate assumptions of bivariate normality required for product-moment correlations.

Consequently, our analysis of the independence among measures used non-parametric rank-order correlation procedures to avoid the undue influence from extreme observations. Table 2 presents the Spearman rank—order correlations between pairs of measures. In large samples, relatively small correlations in this case, as small as 0.

Only one correlation presented in Table 2 , the correlation between duration and bets per day, was not statistically significant. Therefore, it is important to consider the size of these correlations as well as their significance. Duration, interval in days between first and last bet; frequency, percent of days within duration when a bet was placed; net loss, total wagers minus total winnings; Percent lost, net loss divided by total wagered.

In Table 2 , most of the correlations between measures are both significant and large. Participants who wagered larger amounts of money also placed more total bets, more bets per day, wagered more per bet and lost more money overall.

Percent lost was negatively correlated with all other measures of betting involvement, indicating that bettors who bet more and more often lost a lower percent of their total wagers than others. Though duration and frequency were highly negatively correlated, indicating that the longer subscribers remained active on the site the lower the percent of days on which they bet, these two measures did not correlate highly with the other measures of gambling behaviour.

We examined subject centile plots to identify empirically whether subgroups within our sample evidenced discontinuously high involvement with casino wagering. This also was the case for net loss. As shown in Table 2 , total wagered was correlated more highly with betting activity, both total bets and bets per day, and was considered a better measure of gambling involvement.

The temporal measures of duration and frequency were skewed but not markedly discontinuous. The single exception was gender. Although Internet gambling is often the subject of public health debate and concern, there is little empirical evidence available to inform such debate and address that concern. Stakeholders, however, have speculated about Internet gambling and related public policy in both the popular press and public health circles.

Contributing to this growth, this study presents the first ever analysis of real-time betting behaviour of Internet casino gamblers. These findings provide a description of the Internet casino gambling behaviour evidenced by a large cohort of bettors followed prospectively for 2 years. We also identified and reported the characteristics of a distinct group of heavily involved players who comprise five percent of the overall cohort.

This information will allow stakeholders to participate in evidence-based public health debate, rather than rely on conventional wisdom and professional speculation. It is important for public health officials who might be developing Internet gambling-related policy to understand the magnitude of a population's involvement in various types of Internet gambling. We hypothesized that games of chance would not be a popular gambling choice for our longitudinal cohort of sports bettors. This finding suggests that, rather than a general interest in Internet gambling, participants are likely to be selective in the types of games that they choose to play.

The service provider that generated the sample of gamblers for the current investigation is most well known for its sports betting services; consequently, it is not entirely clear whether our findings suggest population-level game preferences or indicate a level of specificity only observed among Internet sport gamblers. We noted that females are underrepresented in the longitudinal cohort and this might be the result of gender differences in game preferences.

However, gender does not appear to influence actual betting behaviour; neither this study of casino gambling nor the sports gambling study 29 observed behavioural differences sufficient to discriminate between genders. Although casino gamblers comprise a small portion of the longitudinal sample, both the full subscriber sample and the subsample of casino gamblers are large i. As we hypothesized, the typical daily cost of casino gambling is modest, but considerably larger than the sports betting costs of this cohort.

The correlation analyses provide important insights about general patterns of Internet gambling behaviour. The high correlations exhibit the consistency of casino betting patterns among these bettors. In our cohort, we also observed a general tendency for rational decision making.

The total amount of money wagered correlated negatively with the percent that was lost; wagering decreased as losses increased. Similarly, measures of betting activity and amount per bet also correlated negatively with percent lost. These findings suggest that for this cohort, bad luck was a disincentive for gambling, though more research focused on the temporal nature of these patterns is necessary to confirm this suspicion.

Although many gambling outcomes were uniform i. More specifically, the time involvement measures, duration and frequency, were negatively correlated. This suggests two styles of casino play in our sample: playing on more days during a shorter total play period, and playing less frequently but for a longer period of time. Both play styles had similar outcomes as measured by monies lost.

Although future research is necessary to clarify this issue, our findings suggest that winning reinforces playing on adjacent days more than it reinforces playing over a longer period of time. Similar to our earlier analysis of Internet sports gamblers, 29 the pattern of gambling involvement in this cohort of casino gamblers was discontinuous. If such groups of heavily involved players indicate noteworthy rates of disorder, behavioural algorithms comprised of temporal, intensity and financial gambling measures might be useful indices for developing website warning systems.

However, an equally important consequence of pathological gambling might be how gamblers redistribute their time e. The heavily involved players played frequently, for a long duration, and were recognized by their financial commitment. However, the correlations based on the total sample suggest that some gamblers might experience personal problems unrelated to the amount of money risked. The negative correlation could signal the presence of gamblers who played intensely but for only a few days: an episodic loss of control that could be problematic, but associated with only limited financial losses.

The relatively small correlations of duration and frequency with monies wagered could signal the presence of gamblers who spent a long time playing casino games, but did not or could not bet more than very small sums. In this case, the time engaged in casino betting, rather than the amount lost, could be the negative outcome of disordered gambling.

The time-related findings confirm the suggestion that interventions need to target a range of behaviours and that identification of disordered gambling behaviour needs to move beyond financially related consequences. Despite the strength of this sample and the research focus on actual gambling behaviour, this study is not without limitations.

The observed Internet betting behaviour might not represent a participant's total online gambling behaviour. In addition to playing other types of games on bwin e. It also is possible that multiple individuals bet using the same account. The service provider, bwin , is best known as a sports gaming service. It is possible that many gamblers whose primary interest is casino games would select sites that emphasize casino games. The casino players in this sample also bet on sports and might represent bettors with more varied gambling interests than players at sites that emphasize casino games.

Although epidemiological information from this and other studies derived from our longitudinal cohort 29 advance our understanding of Internet gambling, additional research is necessary to determine how well these findings generalize to other types of Internet gambling. Research has indicated that game preferences at casinos and other land-based gambling venues e. Table 1 illustrates the proportions of SAHs and MAHs who reported having gambled online at least once over the last 12 months, for each gambling form.

When asked about their Internet gambling behaviour, MAHs were significantly more likely to do most or all of their gambling online MAHs were significantly more likely to rate the following as disadvantages of Internet gambling compared with SAHs: unreliable technology or Internet access, difficulty verifying fairness of games, Internet gambling is more addictive, and that it is easier to spend money table 2.

Table 2 Perceived advantages and disadvantages of Internet gambling over land-based gambling by number of Internet gambling accounts. Perceived advantages and disadvantages of Internet gambling over land-based gambling by number of Internet gambling accounts. Table 3 Number and percentage of respondents who stated that each reason influenced their decision to choose one operator over another by number of Internet gambling accounts. Number and percentage of respondents who stated that each reason influenced their decision to choose one operator over another by number of Internet gambling accounts.

SAHs were significantly more likely than MAHs to say that promotions have no impact on how much they gamble online MAHs were significantly more likely to say that the use of credit cards or electronic funds transfer had increased the amount that they gamble MAHs were significantly more likely to be classified as moderate risk The dependent variable was single vs.

MAH status coded as 0 and 1, respectively. Positive coefficients indicate higher scores are related to MAHs. Predictors included in the model were: gender, level of education, age, proportion of gambling done via the Internet and in land-based gambling venues, participation in each gambling form last 12 months , professional gambling status, Kessler 6 scale score, PGSI group, perceived advantages of Internet gambling, perceived disadvantages of Internet gambling and reasons for choosing one online operator.

This model was initially run through a linear regression procedure to check for tolerance between predictors. The lowest recorded tolerance was 0. Overall prediction success was MAHs were significantly more likely to have an undergraduate level of education compared with those with less than 12 years of education , to engage in sports betting, horse or dog race betting or poker, to classify themselves as semi-professional or professional gamblers compared with amateur gamblers , to be moderate risk or problem gamblers compared with non-problem gamblers , to perceive the price and lower secondary costs as advantages of Internet gambling over land-based gambling, to report the difficult of verifying the fairness of Internet gambling games as a disadvantage of Internet gambling and to choose operators based on price, greater selection of games, better game experience and the software used.

Contrary to the results above, when controlling for all other variables, MAHs were significantly more likely to be older than SAHs. The results suggest that the majority of Australian Internet gamblers use multiple Internet accounts. MAHs were more involved gamblers with respect to gambling frequency and engagement with multiple activities. In particular, betting on sports and races and playing poker were predictive of being a MAH.

This may indicate that some gambling activities are more likely to be used by those who switch operators, or alternatively that online poker players may also wager and require additional accounts. The results are consistent with the findings that MAHs were more involved in both online and offline gambling than SAHs.

Almost two-thirds of MAHs were influenced by price and gambling promotions in selecting a gambling operator and were more likely to be influenced by the greater selection of games and overall game experience. The emphasis of MAHs on price, costs and experience is consistent with the greater proportion of this group stating that their gambling represented a main form of income.

Professional gamblers are known to make more informed decisions and to treat gambling as work, 27 , 28 making them more likely to search for the best offers requiring multiple accounts. Over one-fifth of SAHs chose a gambling site based on its legality and consumer protection provided, demonstrating that this cohort is seeking a legitimate gambling experience and may prefer the stability of gambling with a single provider rather than switching accounts to optimise price.

Although advertising was influential for a proportion of SAHs and differentiated this cohort from MAH, they were less likely to respond to promotions, suggesting that advertising may be influential in their initial decision to choose an operator, which they then remain with. This result aligns with previous findings that gambling advertising has a greater impact on more involved gamblers. However, SAH were also likely to do most of their gambling offline, reducing the need for multiple accounts.

MAHs were almost twice as likely as SAHs to be classified as problem gamblers and were more likely to experience psychological distress. The tendency for MAHs to experience a greater level of gambling problems is likely to be related to their greater gambling involvement, consistent with existing research.

Gambling through multiple accounts makes it difficult for individuals to track their expenditure, which may result in more money spent than intended and subsequent problems. This study included a large sample of Internet gamblers and included a range of relevant variables enabling it to be the first study known to the authors to specifically compare SAHs and MAHs.

Participants self-selected into the study meaning the results are not representative of all Internet gamblers. The extent to which gamblers actively used their various Internet gambling accounts was not measured and this is only one variable to indicate gambling involvement. Other variables may moderate the relationship between use of multiple sites and gambling problems. For example, the use of multiple sites may be an indicator of novelty seeking, which is associated with impulse control problems.

This would fit with the theory that arousal dysfunction requires increased stimulation such that if this is not fulfilled by one website, they may seek others. The current study does not allow inferences about the causal nature of relationships between variables.

Further research is needed to explore how Internet gamblers use multiple sites and their motivations for doing so. The differences between gamblers with a single as compared with multiple online gambling accounts have important implications for the field.

Behavioural tracking data are increasingly being used to understand how consumers use Internet gambling sites and identify potentially problematic play. As such, results drawn from such studies may produce biased results that are not representative of Internet gamblers. Similarly, gambling operators who use behavioural tracking to identify potentially risky play are unable to evaluate gambling that occurs outside their own site.

The current results demonstrate that use of multiple websites for online gambling may also be an important behavioural marker of gambling-related problems. Internet gamblers may benefit from public awareness campaigns of the risks of gambling with multiple operators, including unregulated operators. The European Commission has recommended that Internet gambling operators take greater steps to identify risky gamblers and implement resources to facilitate responsible gambling, such as setting time and monetary limits.

Therefore, tools that allow gamblers to track their gambling across multiple sites may be useful in enhancing the ability to track expenditure and reduce excessive gambling. The authors would like to thank Prof. Daniel Lubman and Dr. Robert Wood who assisted with the research on which this manuscript is based.

GRA had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication. Key points. This is the first study to examine the difference between Internet gamblers who hold multiple as compared with a single online gambling account. The study revealed that MAHs are more highly involved in gambling, more influenced by price and betting options and have a greater risk of experiencing gambling harms.

Single Internet gambling account holders are a more stable but steady group of gamblers who are more concerned with legality and consumer protection. The results presented here question previous findings based on analysis of player behaviour from a single gambling operator and suggest that these may underestimate actual gambling behaviour. The results suggest that harm minimization strategies should be implemented that are effective across multiple operators, rather than restricted to use of a single gambling site.

Google Scholar. Inside the virtual casino: a prospective longitudinal study of actual Internet casino gambling Eur J Public Health 18 — 6. Gambling Commission Gambling participation: activities and mode of access Google Preview. How the Internet is changing gambling: findings from an Australian prevalence survey J Gambl Stud doi: Gainsbury S Wood R Internet gambling policy in critical comparative perspective: the effectiveness of existing regulatory frameworks Int Gambl Stud 11 — Gainsbury S Parke J Suhonen N Attitudes towards Internet gambling: perceptions of responsible gambling, consumer protection, and regulation of gambling sites Comput Hum Behav 29 — Defining the online gambler and patterns of behaviour integration: evidence from the British Gambling Prevalence Survey Int Gambl Stud 11 — Woolley R Mapping Internet gambling: emerging modes of online participation in wagering and sports betting Int Gambl Stud 3 3 — 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 12 — The prevalence and determinants of problem gambling in Australia: assessing the impact of interactive gambling and new technologies Psychol Addict Behav 28 — Int Gambl Stud 14 — How risky is Internet gambling?

A comparison of subgroups of Internet gamblers based on problem gambling status New Media Soc doi A digital revolution: Comparison of demographic profiles, attitudes and gambling behaviour of Internet and non-Internet gamblers Computers in Human Behavior 28 — Interactive Gambling. Report commissioned by Gambling Research Australia Short screening scales to monitor population prevalence and trends in non-specific psychological distress Psychol Med 32 — Radburn B Horsley R Gamblers, grinders, and mavericks: the use of membership categorisation to manage identity by professional poker players J Gambl Issues 26 30 — Dragicevic S Tsogas G Kudic A Analysis of casino online gambling data in relation to behavioural risk markers for high-risk gambling and player protection Int Gambl Stud 11 — Toward a paradigm shift in Internet gambling research: from opinion and self-report to actual behavior Addict Res Theory 18 — Gainsbury S Player account-based gambling: potentials for behaviour-based research methodologies Int Gambl Stud 11 — European Commission Commission recommendation on principles for the protection of consumers and players of online gambling services and for the prevention of minors from gambling online Brussels European Commission.

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Volume Article Contents Introduction. Article Navigation. Greater involvement and diversity of Internet gambling as a risk factor for problem gambling Sally M. Gainsbury , Sally M. Oxford Academic. Alex Russell. Alex Blaszczynski. Nerilee Hing.

Cite Cite Sally M. Select Format Select format. Permissions Icon Permissions. Form of gambling. Single account. Multiple accounts. Open in new tab. Gender ref. Note: Bold text indicates significant predictors within the model. Associations between national gambling policies and disordered gambling prevalence rates within Europe. Google Scholar Crossref.

QPR V WOLVES BETTING TRENDS

Where the dependent variable was continuous, assumptions for parametric analyses were checked and independent samples t -tests were used. For nominal dependent variables, chi-square tests of independence were employed with post hoc pairwise comparisons Z -tests used for all dependent variables with more than two response options. The results in table 1 were conducted using chi-square goodness of fit tests.

Categorical Principal Component Analysis was conducted on the 17 reasons that may have influenced the decision to choose one operator over another and no clear dimensions emerged. Instead, a Bonferroni correction was applied to correct for the multiple comparisons, with critical alpha for these analyses set at 0. A multivariate binary logistic regression was run in order to determine whether the significant results from the univariate analyses were relatively independent,.

A total of respondents Respondents mostly lived in a major metropolitan city The most commonly reported marital statuses were married Most worked full- MAHs were significantly more likely to be male Significant differences were also observed in terms of education, with MAHs significantly more likely to have a university or college degree No differences were observed between the groups in terms of postgraduate qualifications or other levels of education.

Table 1 illustrates the proportions of SAHs and MAHs who reported having gambled online at least once over the last 12 months, for each gambling form. When asked about their Internet gambling behaviour, MAHs were significantly more likely to do most or all of their gambling online MAHs were significantly more likely to rate the following as disadvantages of Internet gambling compared with SAHs: unreliable technology or Internet access, difficulty verifying fairness of games, Internet gambling is more addictive, and that it is easier to spend money table 2.

Table 2 Perceived advantages and disadvantages of Internet gambling over land-based gambling by number of Internet gambling accounts. Perceived advantages and disadvantages of Internet gambling over land-based gambling by number of Internet gambling accounts. Table 3 Number and percentage of respondents who stated that each reason influenced their decision to choose one operator over another by number of Internet gambling accounts.

Number and percentage of respondents who stated that each reason influenced their decision to choose one operator over another by number of Internet gambling accounts. SAHs were significantly more likely than MAHs to say that promotions have no impact on how much they gamble online MAHs were significantly more likely to say that the use of credit cards or electronic funds transfer had increased the amount that they gamble MAHs were significantly more likely to be classified as moderate risk The dependent variable was single vs.

MAH status coded as 0 and 1, respectively. Positive coefficients indicate higher scores are related to MAHs. Predictors included in the model were: gender, level of education, age, proportion of gambling done via the Internet and in land-based gambling venues, participation in each gambling form last 12 months , professional gambling status, Kessler 6 scale score, PGSI group, perceived advantages of Internet gambling, perceived disadvantages of Internet gambling and reasons for choosing one online operator.

This model was initially run through a linear regression procedure to check for tolerance between predictors. The lowest recorded tolerance was 0. Overall prediction success was MAHs were significantly more likely to have an undergraduate level of education compared with those with less than 12 years of education , to engage in sports betting, horse or dog race betting or poker, to classify themselves as semi-professional or professional gamblers compared with amateur gamblers , to be moderate risk or problem gamblers compared with non-problem gamblers , to perceive the price and lower secondary costs as advantages of Internet gambling over land-based gambling, to report the difficult of verifying the fairness of Internet gambling games as a disadvantage of Internet gambling and to choose operators based on price, greater selection of games, better game experience and the software used.

Contrary to the results above, when controlling for all other variables, MAHs were significantly more likely to be older than SAHs. The results suggest that the majority of Australian Internet gamblers use multiple Internet accounts. MAHs were more involved gamblers with respect to gambling frequency and engagement with multiple activities. In particular, betting on sports and races and playing poker were predictive of being a MAH. This may indicate that some gambling activities are more likely to be used by those who switch operators, or alternatively that online poker players may also wager and require additional accounts.

The results are consistent with the findings that MAHs were more involved in both online and offline gambling than SAHs. Almost two-thirds of MAHs were influenced by price and gambling promotions in selecting a gambling operator and were more likely to be influenced by the greater selection of games and overall game experience. The emphasis of MAHs on price, costs and experience is consistent with the greater proportion of this group stating that their gambling represented a main form of income.

Professional gamblers are known to make more informed decisions and to treat gambling as work, 27 , 28 making them more likely to search for the best offers requiring multiple accounts. Over one-fifth of SAHs chose a gambling site based on its legality and consumer protection provided, demonstrating that this cohort is seeking a legitimate gambling experience and may prefer the stability of gambling with a single provider rather than switching accounts to optimise price.

Although advertising was influential for a proportion of SAHs and differentiated this cohort from MAH, they were less likely to respond to promotions, suggesting that advertising may be influential in their initial decision to choose an operator, which they then remain with. This result aligns with previous findings that gambling advertising has a greater impact on more involved gamblers. However, SAH were also likely to do most of their gambling offline, reducing the need for multiple accounts.

MAHs were almost twice as likely as SAHs to be classified as problem gamblers and were more likely to experience psychological distress. The tendency for MAHs to experience a greater level of gambling problems is likely to be related to their greater gambling involvement, consistent with existing research. Gambling through multiple accounts makes it difficult for individuals to track their expenditure, which may result in more money spent than intended and subsequent problems.

This study included a large sample of Internet gamblers and included a range of relevant variables enabling it to be the first study known to the authors to specifically compare SAHs and MAHs. Participants self-selected into the study meaning the results are not representative of all Internet gamblers. The extent to which gamblers actively used their various Internet gambling accounts was not measured and this is only one variable to indicate gambling involvement.

Other variables may moderate the relationship between use of multiple sites and gambling problems. For example, the use of multiple sites may be an indicator of novelty seeking, which is associated with impulse control problems. This would fit with the theory that arousal dysfunction requires increased stimulation such that if this is not fulfilled by one website, they may seek others.

The current study does not allow inferences about the causal nature of relationships between variables. Further research is needed to explore how Internet gamblers use multiple sites and their motivations for doing so. The differences between gamblers with a single as compared with multiple online gambling accounts have important implications for the field.

Behavioural tracking data are increasingly being used to understand how consumers use Internet gambling sites and identify potentially problematic play. As such, results drawn from such studies may produce biased results that are not representative of Internet gamblers.

Similarly, gambling operators who use behavioural tracking to identify potentially risky play are unable to evaluate gambling that occurs outside their own site. The current results demonstrate that use of multiple websites for online gambling may also be an important behavioural marker of gambling-related problems.

Internet gamblers may benefit from public awareness campaigns of the risks of gambling with multiple operators, including unregulated operators. The European Commission has recommended that Internet gambling operators take greater steps to identify risky gamblers and implement resources to facilitate responsible gambling, such as setting time and monetary limits.

Therefore, tools that allow gamblers to track their gambling across multiple sites may be useful in enhancing the ability to track expenditure and reduce excessive gambling. The authors would like to thank Prof. Daniel Lubman and Dr. Robert Wood who assisted with the research on which this manuscript is based. GRA had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Key points. This is the first study to examine the difference between Internet gamblers who hold multiple as compared with a single online gambling account. The study revealed that MAHs are more highly involved in gambling, more influenced by price and betting options and have a greater risk of experiencing gambling harms. Single Internet gambling account holders are a more stable but steady group of gamblers who are more concerned with legality and consumer protection.

The results presented here question previous findings based on analysis of player behaviour from a single gambling operator and suggest that these may underestimate actual gambling behaviour. The results suggest that harm minimization strategies should be implemented that are effective across multiple operators, rather than restricted to use of a single gambling site.

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Volume Article Contents Introduction. Article Navigation. Greater involvement and diversity of Internet gambling as a risk factor for problem gambling Sally M. Gainsbury , Sally M. Oxford Academic. Alex Russell.

The longitudinal cohort eligible for the study consisted of participants. The available demographic characteristics of the research sample included age, gender, country of residence and preferred language. At enrollment, participants elected to interact with the wagering system in one of 22 languages. The daily aggregations provided summary measures of gambling behaviour. We obtained number of bets and total wagered by summing the daily aggregations. We measured the duration of gambling involvement as the number of days from the first eligible bet to the last i.

We defined the frequency of involvement as the percent of days within duration that included a bet i. We obtained the average bets per day by dividing the total number of bets made by the total number of days on which a bet was placed i. The net result of gambling i. The dominant outcome is a net loss and, by subtracting total winnings from total wagers, positive values indicate net losses, the cost of gambling.

Converting net losses to a percent of total wagers i. We conducted a secondary data analysis of the subscriber database obtained from bwin as described above. We received approval from our Institutional Review Board to conduct this secondary data analyses. Tests for differences between group means included testing the assumption of equal variances and, if necessary, adjusting for unequal variances.

We organized the analyses into three sections: i cohort characteristics; ii cohort gambling behaviour and iii the behaviour of heavily involved bettors. For cohort characteristics, we reported gender and country distributions, as well as gambling behaviour differences by gender. For cohort gambling behaviour, we reported gambling involvement by time i. For gambling behaviour, we report medians because of the skewed nature of the gambling data. The players represented 46 countries.

Consequently, the data did not justify additional gender-specific analyses. The relationships between the means and the medians, and the size of the standard deviations in relation to the means, indicate that the total distribution is markedly skewed i. We will consider the heavily involved bettors in a later section.

The distributions of the measures violate assumptions of bivariate normality required for product-moment correlations. Consequently, our analysis of the independence among measures used non-parametric rank-order correlation procedures to avoid the undue influence from extreme observations. Table 2 presents the Spearman rank—order correlations between pairs of measures.

In large samples, relatively small correlations in this case, as small as 0. Only one correlation presented in Table 2 , the correlation between duration and bets per day, was not statistically significant. Therefore, it is important to consider the size of these correlations as well as their significance.

Duration, interval in days between first and last bet; frequency, percent of days within duration when a bet was placed; net loss, total wagers minus total winnings; Percent lost, net loss divided by total wagered.

In Table 2 , most of the correlations between measures are both significant and large. Participants who wagered larger amounts of money also placed more total bets, more bets per day, wagered more per bet and lost more money overall. Percent lost was negatively correlated with all other measures of betting involvement, indicating that bettors who bet more and more often lost a lower percent of their total wagers than others. Though duration and frequency were highly negatively correlated, indicating that the longer subscribers remained active on the site the lower the percent of days on which they bet, these two measures did not correlate highly with the other measures of gambling behaviour.

We examined subject centile plots to identify empirically whether subgroups within our sample evidenced discontinuously high involvement with casino wagering. This also was the case for net loss. As shown in Table 2 , total wagered was correlated more highly with betting activity, both total bets and bets per day, and was considered a better measure of gambling involvement.

The temporal measures of duration and frequency were skewed but not markedly discontinuous. The single exception was gender. Although Internet gambling is often the subject of public health debate and concern, there is little empirical evidence available to inform such debate and address that concern. Stakeholders, however, have speculated about Internet gambling and related public policy in both the popular press and public health circles.

Contributing to this growth, this study presents the first ever analysis of real-time betting behaviour of Internet casino gamblers. These findings provide a description of the Internet casino gambling behaviour evidenced by a large cohort of bettors followed prospectively for 2 years. We also identified and reported the characteristics of a distinct group of heavily involved players who comprise five percent of the overall cohort. This information will allow stakeholders to participate in evidence-based public health debate, rather than rely on conventional wisdom and professional speculation.

It is important for public health officials who might be developing Internet gambling-related policy to understand the magnitude of a population's involvement in various types of Internet gambling. We hypothesized that games of chance would not be a popular gambling choice for our longitudinal cohort of sports bettors.

This finding suggests that, rather than a general interest in Internet gambling, participants are likely to be selective in the types of games that they choose to play. The service provider that generated the sample of gamblers for the current investigation is most well known for its sports betting services; consequently, it is not entirely clear whether our findings suggest population-level game preferences or indicate a level of specificity only observed among Internet sport gamblers.

We noted that females are underrepresented in the longitudinal cohort and this might be the result of gender differences in game preferences. However, gender does not appear to influence actual betting behaviour; neither this study of casino gambling nor the sports gambling study 29 observed behavioural differences sufficient to discriminate between genders.

Although casino gamblers comprise a small portion of the longitudinal sample, both the full subscriber sample and the subsample of casino gamblers are large i. As we hypothesized, the typical daily cost of casino gambling is modest, but considerably larger than the sports betting costs of this cohort. The correlation analyses provide important insights about general patterns of Internet gambling behaviour. The high correlations exhibit the consistency of casino betting patterns among these bettors.

In our cohort, we also observed a general tendency for rational decision making. The total amount of money wagered correlated negatively with the percent that was lost; wagering decreased as losses increased. Similarly, measures of betting activity and amount per bet also correlated negatively with percent lost. These findings suggest that for this cohort, bad luck was a disincentive for gambling, though more research focused on the temporal nature of these patterns is necessary to confirm this suspicion.

Although many gambling outcomes were uniform i. More specifically, the time involvement measures, duration and frequency, were negatively correlated. This suggests two styles of casino play in our sample: playing on more days during a shorter total play period, and playing less frequently but for a longer period of time. Both play styles had similar outcomes as measured by monies lost.

Although future research is necessary to clarify this issue, our findings suggest that winning reinforces playing on adjacent days more than it reinforces playing over a longer period of time. Similar to our earlier analysis of Internet sports gamblers, 29 the pattern of gambling involvement in this cohort of casino gamblers was discontinuous. If such groups of heavily involved players indicate noteworthy rates of disorder, behavioural algorithms comprised of temporal, intensity and financial gambling measures might be useful indices for developing website warning systems.

However, an equally important consequence of pathological gambling might be how gamblers redistribute their time e. The heavily involved players played frequently, for a long duration, and were recognized by their financial commitment. However, the correlations based on the total sample suggest that some gamblers might experience personal problems unrelated to the amount of money risked. The negative correlation could signal the presence of gamblers who played intensely but for only a few days: an episodic loss of control that could be problematic, but associated with only limited financial losses.

The relatively small correlations of duration and frequency with monies wagered could signal the presence of gamblers who spent a long time playing casino games, but did not or could not bet more than very small sums. In this case, the time engaged in casino betting, rather than the amount lost, could be the negative outcome of disordered gambling.

The time-related findings confirm the suggestion that interventions need to target a range of behaviours and that identification of disordered gambling behaviour needs to move beyond financially related consequences. Despite the strength of this sample and the research focus on actual gambling behaviour, this study is not without limitations. The observed Internet betting behaviour might not represent a participant's total online gambling behaviour.

In addition to playing other types of games on bwin e. It also is possible that multiple individuals bet using the same account. The service provider, bwin , is best known as a sports gaming service. It is possible that many gamblers whose primary interest is casino games would select sites that emphasize casino games. The casino players in this sample also bet on sports and might represent bettors with more varied gambling interests than players at sites that emphasize casino games.

Although epidemiological information from this and other studies derived from our longitudinal cohort 29 advance our understanding of Internet gambling, additional research is necessary to determine how well these findings generalize to other types of Internet gambling.

Research has indicated that game preferences at casinos and other land-based gambling venues e. Our data did not provide information about the specific casino games that individuals in our sample played. However, published reports of provider odds might shed light on this issue. The outcomes of casino games are governed by chance with the odds set by the provider. The website indicates that Video Poker and Slots had the lowest returns to the players, overall losses of 6. Casino table games were most favourable with a loss rate of 2.

This is an important direction for future research and eventually could suggest directions for targeted public health interventions based on gaming preferences. The purpose of our research collaboration with bwin is to provide an empirical foundation to guide the development and implementation of strategies that will protect the public health.

The rapid expansion of Internet access and services outpaces the acquisition of empirical evidence necessary to develop effective regulations and policies to assure public safety and health. However, an advantage of Internet capabilities is the ability to collect the actual behaviour of a large research sample over a long period of time.

This allows research to avoid the nuances of self-report and the prohibitive logistical constraints of repeatedly surveying large samples. This study is a necessary step toward informing the wide range of gambling stakeholders about the behavioural epidemiology of Internet gambling on casino-type games. Research must next begin to identify the population segments at greater or lesser risk for developing Internet gambling-related addiction problems.

The determinants for increasing or decreasing the likelihood of developing Internet gambling problems can then serve as a guide for the development of prevention and treatment programs. The authors extend special thanks to Christine Thurmond and Ziming Xuan for their support and work on this project.

Dr LaBrie had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Key points. This is the first study to provide evidence about the actual gambling behaviour of a large cohort of Internet gamblers who played casino games during a 2-year period.

A small percentage of the cohort i. Two patterns of Internet casino play emerged among the cohort: playing on more days during a shorter total play period, and playing less frequently but for a longer period of time. Little evidence suggested a difference in outcomes across these distinct play styles.

Internet casino gamblers incurred greater daily losses and played less frequently about twice a month than Internet sports gamblers about 7 times per month. Google Scholar. Google Preview. Oxford University Press is a department of the University of Oxford.

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Close mobile search navigation Article Navigation. Volume Article Contents Abstract.