Internet gamblers: a latent class analysis of their behaviours and health experiences - PubMed (original) (raw)
Internet gamblers: a latent class analysis of their behaviours and health experiences
Joanne Lloyd et al. J Gambl Stud. 2010 Sep.
Free article
Abstract
In order to learn about the behaviours and health experiences of people who gamble on the Internet, we conducted an international online survey with respondents recruited via gambling and gambling-related websites. The mean (SD) age of the 4,125 respondents completing the survey was 35.5 (11.8) years, with 79.1% being male and 68.8% UK residents. Respondents provided demographic details and completed validated psychometric screening instruments for problem gambling, mood disturbances, as well as alcohol and substance misuse, and history of deliberate self harm. We applied latent class analysis to respondents' patterns of regular online gambling activities, and identified subgroups of individuals who used the Internet to gamble in different ways (L (2) = 44.27, bootstrap P = 0.07). We termed the characteristic profiles as 'non-to-minimal gamblers'; 'sports bettors'; 'casino & sports gamblers'; 'lottery players'; and 'multi-activity gamblers'. Furthermore, these subgroups of respondents differed on other demographic and psychological dimensions, with significant inter-cluster differences in proportion of individuals scoring above threshold for problem gambling, mood disorders and substance misuse, and history of deliberate self harm (all Chi (2)s > 23.4, all P-values <0.001). The 'casino & sports' and 'multi-activity-gamblers' clusters had the highest prevalence of mental disorder. Internet gamblers appear to be heterogeneous but composed of several subgroups, differing markedly on both demographic and clinical characteristics.
Similar articles
- Mental Health and Online, Land-Based and Mixed Gamblers.
Blaszczynski A, Russell A, Gainsbury S, Hing N. Blaszczynski A, et al. J Gambl Stud. 2016 Mar;32(1):261-75. doi: 10.1007/s10899-015-9528-z. J Gambl Stud. 2016. PMID: 25744658 - Typology of online lotteries and scratch games gamblers' behaviours: A multilevel latent class cluster analysis applied to player account-based gambling data.
Perrot B, Hardouin JB, Grall-Bronnec M, Challet-Bouju G. Perrot B, et al. Int J Methods Psychiatr Res. 2018 Dec;27(4):e1746. doi: 10.1002/mpr.1746. Epub 2018 Oct 18. Int J Methods Psychiatr Res. 2018. PMID: 30338605 Free PMC article. Clinical Trial. - Latent Class Analysis of Gambling Activities in a Sample of Young Swiss Men: Association with Gambling Problems, Substance Use Outcomes, Personality Traits and Coping Strategies.
Studer J, Baggio S, Mohler-Kuo M, Simon O, Daeppen JB, Gmel G. Studer J, et al. J Gambl Stud. 2016 Jun;32(2):421-40. doi: 10.1007/s10899-015-9547-9. J Gambl Stud. 2016. PMID: 25929440 - Prevalence of comorbid disorders in problem and pathological gambling: systematic review and meta-analysis of population surveys.
Lorains FK, Cowlishaw S, Thomas SA. Lorains FK, et al. Addiction. 2011 Mar;106(3):490-8. doi: 10.1111/j.1360-0443.2010.03300.x. Addiction. 2011. PMID: 21210880 Review. - [Internet gambling: what are the risks?].
Bonnaire C. Bonnaire C. Encephale. 2012 Feb;38(1):42-9. doi: 10.1016/j.encep.2011.01.014. Epub 2011 Apr 8. Encephale. 2012. PMID: 22381723 Review. French.
Cited by
- Online Gambling: A Systematic Review of Risk and Protective Factors in the Adult Population.
Ghelfi M, Scattola P, Giudici G, Velasco V. Ghelfi M, et al. J Gambl Stud. 2024 Jun;40(2):673-699. doi: 10.1007/s10899-023-10258-3. Epub 2023 Nov 14. J Gambl Stud. 2024. PMID: 37964161 Free PMC article. Review. - Do Online Gambling Products Require Traditional Therapy for Gambling Disorder to Change? Evidence from Focus Group Interviews with Mental Health Professionals Treating Online Gamblers.
Lopez-Gonzalez H, Jimenez-Murcia S, Rius-Buitrago A, Griffiths MD. Lopez-Gonzalez H, et al. J Gambl Stud. 2022 Jun;38(2):681-697. doi: 10.1007/s10899-021-10064-9. Epub 2021 Oct 16. J Gambl Stud. 2022. PMID: 34655397 Free PMC article. - Video Game Streaming in Young People and Teenagers: Uptake, User Groups, Dangers, and Opportunities.
Cabeza-Ramírez LJ, Muñoz-Fernández GA, Santos-Roldán L. Cabeza-Ramírez LJ, et al. Healthcare (Basel). 2021 Feb 10;9(2):192. doi: 10.3390/healthcare9020192. Healthcare (Basel). 2021. PMID: 33578675 Free PMC article. - Impulsivity, Lack of Premeditation, and Debts in Online Gambling Disorder.
López-Torres I, León-Quismondo L, Ibáñez A. López-Torres I, et al. Front Psychiatry. 2021 Jan 20;11:618148. doi: 10.3389/fpsyt.2020.618148. eCollection 2020. Front Psychiatry. 2021. PMID: 33551878 Free PMC article. - Peer Group Identification as Determinant of Youth Behavior and the Role of Perceived Social Support in Problem Gambling.
Savolainen I, Sirola A, Kaakinen M, Oksanen A. Savolainen I, et al. J Gambl Stud. 2019 Mar;35(1):15-30. doi: 10.1007/s10899-018-9813-8. J Gambl Stud. 2019. PMID: 30465150 Free PMC article.
References
- Am J Addict. 2007 Sep-Oct;16(5):325-30 - PubMed
- J Gambl Stud. 2007 Sep;23(3):245-57 - PubMed
- JAMA. 1984 Oct 12;252(14):1905-7 - PubMed
- BMJ. 2004 Nov 6;329(7474):1055-6 - PubMed
- Psychol Addict Behav. 2002 Mar;16(1):76-9 - PubMed
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Medical