Where Lies the Harm in Lottery Gambling? A Portrait of Gambling Practices and Associated Problems

Costes, Jean-Michel; Kairouz, Sylvia; Monson, Eva; Eroukmanoff, Vincent

doi:10.1007/s10899-018-9761-3

Cited by 28 publications

(37 citation statements)

References 18 publications

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“…This figure is similar to the global prevalence estimated in an Inserm report in 2008, in the French general population, in which from 1.5% to 3% were deemed to be problem and pathological gamblers 31) . In 2014, Costes measured the prevalence of problem gambling at 2.7% 32) . We used the same tool (CPGI) and the same definitions of problem gambling as Costes.…”

Section: Discussionmentioning

confidence: 99%

Prevalence of problem gambling in an employed population in Brittany, France

Dezutter¹,

Guillou-Landréat

Dewitte

et al. 2020

INDUSTRIAL HEALTH

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Some employees may have recourse to gambling, notably as an adaptive strategy. Although many studies have been performed on specific occupational groups (i.e. gambling industry, transportation or teaching), none have been conducted with workers followed-up by Occupational Health Services (OHS). Our aim was to evaluate the prevalence of problem gambling in an employed population and its links with work. We performed a cross-sectional study between November 2016 and April 2017, in an OHS in France. We evaluated the prevalence of gambling using the Lie or Bet questionnaire and the Canadian Problem Gambling Index. Among the 410 employees included, 138 (33.7%) had gambled in the previous year, 12 (2.9%) considered their gambling experience to be work-related, 13 (3.2%) were identified as problem gamblers. The influence of colleagues and the workplace hierarchy and ease of access to gambling (in tobacco shops, bars…) could be risk factors. Screening for gambling behavior could be offered by occupational health services, using the Lie or Bet, especially for employees exposed to readily available gambling opportunities at their workplace.

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Section: Discussionmentioning

confidence: 99%

Prevalence of problem gambling in an employed population in Brittany, France

Dezutter¹,

Guillou-Landréat

Dewitte

et al. 2020

INDUSTRIAL HEALTH

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“…Large research programs [ 21 - 36 ] have been initiated including research [ 36 ] that focuses on rarely studied online lottery gambling tracking data (lottery draws, daily lotteries, and scratch cards). Indeed, such gambling is traditionally considered the least associated with gambling problems, but is the most prevalent form of gambling, leading to an overall sum of low-level harms that could be as important as the harm associated with more problematic but less prevalent forms of gambling [ 37 ].…”

Section: Introductionmentioning

confidence: 99%

Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis

Challet-Bouju¹,

Hardouin²,

Thiabaud³

et al. 2020

J Med Internet Res

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Background Individuals who gamble online may be at risk of gambling excessively, but internet gambling also provides a unique opportunity to monitor gambling behavior in real environments which may allow intervention for those who encounter difficulties. Objective The objective of this study was to model the early gambling trajectories of individuals who play online lottery. Methods Anonymized gambling‐related records of the initial 6 months of 1152 clients of the French national lottery who created their internet gambling accounts between September 2015 and February 2016 were analyzed using a two-step approach that combined growth mixture modeling and latent class analysis. The analysis was based upon behavior indicators of gambling activity (money wagered and number of gambling days) and indicators of gambling problems (breadth of involvement and chasing). Profiles were described based upon the probabilities of following the trajectories that were identified for the four indicators, and upon several covariates (age, gender, deposits, type of play, net losses, voluntary self-exclusion, and Playscan classification—a responsible gambling tool that provides each player with a risk assessment: green for low risk, orange for medium risk and red for high risk). Net losses, voluntary self-exclusion, and Playscan classification were used as external verification of problem gambling. Results We identified 5 distinct profiles of online lottery gambling. Classes 1 (56.8%), 2 (14.8%) and 3 (13.9%) were characterized by low to medium gambling activity and low values for markers of problem gambling. They displayed low net losses, did not use the voluntary self-exclusion measure, and were classified predominantly with green Playscan tags (range 90%-98%). Class 4 (9.7%) was characterized by medium to high gambling activity, played a higher breadth of game types (range 1-6), and had zero to few chasing episodes. They had high net losses but were classified with green (66%) or orange (25%) Playscan tags and did not use the voluntary self-exclusion measure. Class 5 (4.8%) was characterized by medium to very high gambling activity, played a higher breadth of game types (range 1-17), and had a high number of chasing episodes (range 0-5). They experienced the highest net losses, the highest proportion of orange (32%) and red (39%) tags within the Playscan classification system and represented the only class in which voluntary self-exclusion was present. Conclusions Classes 1, 2, 3 may be considered to represent recreational gambling. Class 4 had higher gambling activity and higher breadth of involvement and may be representative of players at risk for future gambling problems. Class 5 stood out in terms of much higher gambling activity and breadth of involvement, and the presence of chasing behavior. Individuals in classes 4 and 5 may benefit from early preventive measures.

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“…instant‐win, fixed‐prize and progressive‐prize lottery). Current literature suggests that participation in traditional lottery gambling—fixed‐payout and progressive‐prize payouts—is a relatively harmless form of gambling, but instant‐win ticket gambling is related to problem gambling [7,9]. Our finding that instant‐win, progressive‐prize and fixed‐prize lottery participation rates are differentially predicted by SES implies that these categories of lottery gambling might be best studied separately.…”

Section: Discussionmentioning

confidence: 83%

“…Lottery gambling has enjoyed world‐wide appeal, owing to the low cost of participation and compelling prize sizes [1]—for example, in Canada, lottery gambling is the most popular form of legal gambling [2–4]. Despite that fact that it is known that increased gambling participation is associated with an increased risk of gambling‐related problems [5], the existing gambling literature suggests that lottery is not a high‐risk activity for problem gambling [6–8]. However, studies rarely differentiate between lottery subtypes (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Costes et al . [7] found that grouping exclusive lottery gamblers and non‐exclusive lottery gamblers may bias data and dilute the gambling associated problems measured by surveys. When considering specific forms of lottery gambling, recent survey‐based research has found that the frequency of instant‐win gambling predicted problem gambling severity and number of gambling activities, whereas lottery (i.e.…”

Section: Introductionmentioning

confidence: 99%

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Relationships between socio‐economic status and lottery gambling across lottery types: neighborhood‐level evidence from a large city

Monson

Otto

2020

Addiction

Self Cite

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Background and aims Lottery gambling participation tends to be higher among lower socio‐economic status (SES) individuals, but it is unclear how this relationship differs as a function of lottery type. We estimated how the relationship between SES and lottery gambling rates varies across different types of lottery gambling: fixed‐prize, progressive‐prize (jackpot) and instant‐win (scratch card) lottery tickets in a large Canadian city. Design Neighborhood‐level lottery purchase data obtained from the Ontario Lottery and Gaming Commission were analysed in conjunction with demographic data. Mixed‐effects regression was used to assess simultaneously how neighborhood‐level SES predicts per‐person lottery gambling rates across fixed‐prize, progressive‐prize lottery and instant‐win lotteries. Setting and participants Neighborhoods in Toronto, Ontario, Canada in the years 2012–15. Measurements Per‐capita sales in dollars (CAD) of fixed‐prize lottery, progressive‐prize lottery and instant‐win tickets in Toronto postal codes. SES was estimated as a composite of income, years of education and white‐collar employment. Findings Lower‐SES neighborhoods engaged in higher rates of lottery gambling overall [β = −0.084, standard error (SE) = 0.24, P = 0.0007]. The predictive effect of SES varied significantly by lottery type (fixed‐prize: β = −0.105, SE = 0.004, P < 0.0001, instant‐win: β = −0.054, SE = 0.004, P < 0.0001; relative to progressive‐prize). The predictive effect of SES was strongest for fixed‐prize lotteries and weakest for progressive‐prize lotteries, such that we did not observe a significant predictive effect of SES for progressive‐prize lotteries (β = −0.031, SE = 0.024, P = 0.198). Conclusions People in lower socio‐economic status neighborhoods in Toronto, Canada appear to engage in more lottery gambling than those in higher socio‐economic status neighborhoods, with the difference being largest for fixed prize lotteries followed by instant win lotteries, and no clear difference for progressive prize lotteries.

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Where Lies the Harm in Lottery Gambling? A Portrait of Gambling Practices and Associated Problems

Cited by 28 publications

References 18 publications

Prevalence of problem gambling in an employed population in Brittany, France

Prevalence of problem gambling in an employed population in Brittany, France

Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis

Relationships between socio‐economic status and lottery gambling across lottery types: neighborhood‐level evidence from a large city

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