Internet gambling: A school-based survey among Macau students

2010 ◽  
Vol 38 (3) ◽  
pp. 365-371 ◽  
Author(s):  
Irene Lai Kuen Wong
Keyword(s):  
Problem Gambling ◽  
Internet Gambling ◽  
The Internet ◽  
Gambling Problems ◽  
Pathological Gamblers ◽  
The Past ◽  
School Grades ◽  
School Based ◽  
Survey Results ◽  
Shed Light

Internet gambling was examined among 422 Macau students (240 male; 182 female) aged 12-22, who were recruited from 6 schools. Results indicated that 6.6% of the participants had gambled online in the past year, wagering on soccer matches (50%), mahjong (35.7%), and casino games (14.3%). They were attracted by the operators' acceptance of low wagers (39.3%), anonymity assurance (28.6%), and convenience and accessibility (25%). Using the Massachusetts Gambling Screen (MAGS; Shaffer, LaBrie, Scanlan, & Cummings, 1994), 10.7% and 25% of the Internet gamblers could be classified as problem and pathological gamblers, respectively. Males were twice as likely as females to gamble online and have gambling problems. Rates of participation and problem gambling increased with school grades. Survey results shed light on prevention.

scholarly journals Searching for a Mate

2012 ◽  
Vol 77 (4) ◽  
pp. 523-547 ◽  
Author(s):  
Michael J. Rosenfeld ◽  
Reuben J. Thomas
Keyword(s):  
Internet Access ◽  
Romantic Partners ◽  
The Internet ◽  
Grade School ◽  
Same Sex ◽  
Same Sex Couples ◽  
The Past ◽  
Thin Market ◽  
Survey Results ◽  
Data Source

This article explores how the efficiency of Internet search is changing the way Americans find romantic partners. We use a new data source, the How Couples Meet and Stay Together survey. Results show that for 60 years, family and grade school have been steadily declining in their influence over the dating market. In the past 15 years, the rise of the Internet has partly displaced not only family and school, but also neighborhood, friends, and the workplace as venues for meeting partners. The Internet increasingly allows Americans to meet and form relationships with perfect strangers, that is, people with whom they had no previous social tie. Individuals who face a thin market for potential partners, such as gays, lesbians, and middle-aged heterosexuals, are especially likely to meet partners online. One result of the increasing importance of the Internet in meeting partners is that adults with Internet access at home are substantially more likely to have partners, even after controlling for other factors. Partnership rate has increased during the Internet era (consistent with Internet efficiency of search) for same-sex couples, but the heterosexual partnership rate has been flat.

scholarly journals Gambling Behaviours and Problem Gambling Among Older Adults Who Patronize Ontario Casinos or Racinos

2018 ◽  
Author(s):  
Nigel E Turner ◽  
Mark Van der Maas ◽  
John McCready ◽  
Hayley A Hamilton ◽  
Tracy Schrans ◽  
...  
Keyword(s):  
Older Adults ◽  
Problem Gambling ◽  
Severity Index ◽  
Slot Machines ◽  
Gambling Problems ◽  
Severe Problem ◽  
The Past ◽  
Gambling Severity ◽  
Quota Sampling ◽  
Gaming Machines

This study examined the rate of gambling problems among Ontario older adults at gambling venues. Herein we describe an intercept survey that took place at casinos and horse racing tracks with slot machines or other forms of casino games (racinos) in southwestern Ontario, Canada. This method provided a significant opportunity to obtain a large sample of older adult casino gamblers in order to understand the gambling habits and gambling problems of this population. We used an intercept recruitment method to obtain a sample of 2,103 older adults (aged 55 and older) who were gambling at each of the seven gaming venues, as well as a systematic quota sampling method for age category (e.g., 55–64, 65–74, and 75 and above) and sex. On average, the participants engaged in 3.6 forms of gambling in the past year, and 78.6% reported playing slot machines or other forms of electronic gaming machines monthly or more often. They reported spending an average of 3.29 hr gambling at casinos or racinos per visit and 134.9 hr at casinos or racinos per year. Just over one-fifth of the sample reported spending more than $6,000 in casinos or racinos in the past year. Based on the Problem Gambling Severity Index (PGSI), the proportion of the sample experiencing severe problem gambling (PGSI = 8+) was 6.9%, and an additional 20.3% reported moderate gambling problems (PGSI = 3 to 7).RésuméCette étude a examiné le taux de problèmes de jeu de personnes âgées de l’Ontario sur les sites de jeu. On y décrit un sondage par interception qui a eu lieu dans des casinos et des pistes de course de chevaux où se trouvent des machines à sous ou d’autres formes de jeux de casino (racinos) dans le sud-ouest de l’Ontario, au Canada. Cette méthode a fourni une occasion importante d’obtenir un vaste échantillon de joueurs de casino adultes plus âgés afin de comprendre les habitudes de jeu et les problèmes de jeu de cette population. Nous avons utilisé une méthode de recrutement par interception pour obtenir un échantillon de 2 103 aînés (âgés de 55 ans et plus) qui jouaient à chacun des sept sites de jeu, ainsi qu’une méthode d’échantillonnage systématique par quotas pour les catégories d’âge (p. ex. 55–64, 65–74 et 75 ans et plus) et le sexe. En moyenne, les participants ont joué à 3,6 formes de jeu au cours de la dernière année, et 78,6 % ont déclaré jouer aux machines à sous ou à d’autres formes de machines de jeux électroniques tous les mois ou plus souvent. Ils ont déclaré avoir consacré en moyenne 3,29 heures à jouer dans les casinos ou les racinos par visite et 134,9 heures dans les casinos ou les racinos par année. Un peu plus d’un cinquième de l’échantillon a déclaré avoir dépensé plus de 6 000 $ dans des casinos ou des racinos au cours de la dernière année. Selon l’Indice de gravité du jeu problématique (IGJP), la proportion de joueurs de l’échantillon ayant eu des problèmes de jeu excessifs (IGJP = 8+) était de 6,9 %, et une autre partie de 20,3 % des joueurs a signalé avoir des problèmes de jeu modérés (IGJP = 3 à 7).

scholarly journals Subtyping Gambling Acitivities: Case of Korca City, Albania

2016 ◽  
Vol 1 (3) ◽  
pp. 73
Author(s):  
Besa Shahini ◽  
Emil Frasheri
Keyword(s):  
Problem Gambling ◽  
Self Report ◽  
Gambling Problems ◽  
Factor Solution ◽  
Cross Sectional ◽  
The Past ◽  
Scratch Cards ◽  
Cross Sectional Design ◽  
Gambling Activities ◽  
Gambling Subtypes

Gambling research has grown dramatically over the past 2-3 decades, however a lack of consensus regarding the risk factors and gambling etiology related to youth problem gambling still remain. So a better understanding of the nature of youth problem gambling could help us to clarify the etiology of gambling problems. Understanding gambling subtypes is necessary to improve our understanding of the etiology of problem gambling. The prediction of problem gambling is related with the participation in gambling activities. It is necessary to obtain a structure of gambling activities, in order to better understand gambling related problems and to treat problems in a more specified manner. The aim of the study was to determine the appropriate structure of gambling activities using factor analysis in a confirmatory framework. Students are a particularly interesting population in which to study gambling. The research utilized a cross-sectional design and self-report questionnaires. The study concludes that the two-factor solution better represents the chance-and skill-based gambling activities. The first factor is most strongly associated with chance-based activities (lottery, bingo, scratch cards). The second factor is most strongly associated with activities that require some degree of skill (poker, roulette, sport bet, racing, etc. ).

scholarly journals Trust in Internet gambling and its association with problem gambling in university students

2013 ◽  
pp. 1
Author(s):  
Nicholas M. Harris ◽  
Dwight Mazmanian ◽  
John Jamieson
Keyword(s):  
Problem Gambling ◽  
University Student ◽  
Internet Gambling ◽  
The Internet ◽  
South Oaks Gambling Screen ◽  
Negative Effects ◽  
Student Sample ◽  
Dsm Iv ◽  
Problematic Gambling ◽  
Gambling Activities

The Internet has become a major means of accessing a variety of gambling activities. As a result, there is concern that the Internet may provide more opportunities for consumers to engage in problematic gambling behaviours. The current study examined factors related to Internet gambling and problem gambling in a university student sample (N = 325). Measures included the South Oaks Gambling Screen, the DSM-IV-TR-Based Questionnaire, the Canadian Problem Gambling Index, and a questionnaire examining Internet gambling behaviours and trust. Internet gamblers (n = 53) reported significantly higher levels of trust in Internet gambling sites than non-Internet gamblers (n = 182) and non-gamblers (n = 90). Among Internet gamblers, significant predictors of problem gambling included level of trust in Internet gambling sites, negative effects of this activity on academic achievement and class attendance, and alcohol consumption while gambling on the Internet. Implications of these findings are discussed.

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

10.2196/17675 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e17675
Author(s):  
Gaëlle Challet-Bouju ◽  
Jean-Benoit Hardouin ◽  
Elsa Thiabaud ◽  
Anaïs Saillard ◽  
Yann Donnio ◽  
...  
Keyword(s):  
At Risk ◽  
Problem Gambling ◽  
Latent Class ◽  
Growth Mixture Modeling ◽  
Responsible Gambling ◽  
Gambling Behavior ◽  
Internet Gambling ◽  
Gambling Problems ◽  
Gambling Activity ◽  
Lottery Gambling

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.

Internet Gambling Among Ontario Adults

2001 ◽  
Author(s):  
Anca Ialomiteanu ◽  
Edward M. Adlaf
Keyword(s):  
General Population ◽  
Marital Status ◽  
Telephone Survey ◽  
Internet Gambling ◽  
The Internet ◽  
Income Differences ◽  
The Past ◽  
On Line ◽  
The Difference

The increased popularity of the Internet among the general population is of particular relevance to the area of Internet gambling. This paper describes the prevalence of Internet gambling among Ontario adults. Data are based on a random telephone survey of 1,294 Ontario adults. Overall, 5.3% of the Ontario adults interviewed in 2000 reported having gambled on the Internet during the past 12 months. Although women were more likely to gamble on-line than males (6.3% vs. 4.3%), the difference was not statistically significant. Only marital status was significantly related to Internet gambling. Those previously married (divorced, widowed) were significantly more likely to report on-line gambling compared to those who were married (10.9% vs. 4.9%). There were no dominant age, regional, educational or income differences.

scholarly journals The Gambling Factors Related with the Level of Adolescent Problem Gambler

2019 ◽  
Vol 16 (12) ◽  
pp. 2110 ◽  
Author(s):  
Kyonghwa Kang ◽  
Jong Sun Ok ◽  
Hyeongsu Kim ◽  
Kun-Sei Lee
Keyword(s):  
Problem Gambling ◽  
Gambling Behavior ◽  
Adolescent Gambling ◽  
Gambling Problem ◽  
Problem Gambler ◽  
Gambling Problems ◽  
Male Adolescents ◽  
Korean Adolescents ◽  
The Past ◽  
Adolescent Problem Gambling

The purpose of this study was to investigate the gambling factors related with the gambling problem level of adolescents to provide basic information for the prevention of adolescent gambling problems. The data was drawn from the 2015 Survey on Youth Gambling Problems of the Korea Center on Gambling Problems for Korean students in grades 7–11 (ages 13–17 years) and included 14,011 study subjects (average age 14.9 years, 52.5% male). The lifetime gambling behavior experience was 42.1%, and 24.2% had a gambling behavior experience within the past three months. The past three-month prevalence of problem gambling was 1.1%. The gambling factors related with the level of adolescent problem gambling include the presence of nearby gambling facilities, having personal relationships with people that gamble, a higher number of experienced gambling behaviors, male adolescents, and a greater amount of time spent gambling. To the best of our knowledge, this study is the first report to identify gambling factors related with the level of adolescent problem gambling in Korean adolescents using national data. These findings suggest that gambling prevention efforts must consider not only access to individual adolescents as early intervention, but also environmental strategies such as accessibility regulations and alternative activities.

scholarly journals Machine learning-based analysis of adolescent gambling factors

2020 ◽  
Vol 9 (3) ◽  
pp. 734-743
Author(s):  
Wonju Seo ◽  
Namho Kim ◽  
Sang-Kyu Lee ◽  
Sung-Min Park
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Problem Gambling ◽  
Online Gambling ◽  
Easy Access ◽  
Support Vector ◽  
Gambling Problems ◽  
Learning Models ◽  
The Past ◽  
Machine Learning Models

AbstractBackground and aimsProblem gambling among adolescents has recently attracted attention because of easy access to gambling in online environments and its serious effects on adolescent lives. We proposed a machine learning-based analysis method for predicting the degree of problem gambling.MethodsOf the 17,520 respondents in the 2018 National Survey on Youth Gambling Problems dataset (collected by the Korea Center on Gambling Problems), 5,045 students who had gambled in the past 3 months were included in this study. The Gambling Problem Severity Scale was used to provide the binary label information. After the random forest-based feature selection method, we trained four models: random forest (RF), support vector machine (SVM), extra trees (ETs), and ridge regression.ResultsThe online gambling behavior in the past 3 months, experience of winning money or goods, and gambling of personal relationship were three factors exhibiting the high feature importance. All four models demonstrated an area under the curve (AUC) of >0.7; ET showed the highest AUC (0.755), RF demonstrated the highest accuracy (71.8%), and SVM showed the highest F1 score (0.507) on a testing set.DiscussionThe results indicate that machine learning models can convey meaningful information to support predictions regarding the degree of problem gambling.ConclusionMachine learning models trained using important features showed moderate accuracy in a large-scale Korean adolescent dataset. These findings suggest that the method will help screen adolescents at risk of problem gambling. We believe that expandable machine learning-based approaches will become more powerful as more datasets are collected.

scholarly journals Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis (Preprint)

2020 ◽  
Author(s):  
Gaëlle Challet-Bouju ◽  
Jean-Benoit Hardouin ◽  
Elsa Thiabaud ◽  
Anaïs Saillard ◽  
Yann Donnio ◽  
...  
Keyword(s):  
At Risk ◽  
Problem Gambling ◽  
Latent Class ◽  
Growth Mixture Modeling ◽  
Responsible Gambling ◽  
Gambling Behavior ◽  
Internet Gambling ◽  
Gambling Problems ◽  
Gambling Activity ◽  
Lottery Gambling

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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