ONLINE PROBLEM GAMBLING AMONG YOUNG ADULTS IN GREECE
Author(s)
Foteini Tsotra, MSc, MPH, Alkinoos Emmanouil-Kalos, MSc, Konstantina Briola, MSc, Symeon Sidiropoulos, PhD, Athanassios Vozikis, PhD.
Laboratory of Health Economics & Management (LabHEM), University of Piraeus, Economics Dept., Piraeus, Greece.
Laboratory of Health Economics & Management (LabHEM), University of Piraeus, Economics Dept., Piraeus, Greece.
OBJECTIVES: Problem gambling is increasingly recognized as a public health concern among young adults. This study examined the prevalence of online gambling-related problems and identified demographic, behavioral, and mental health factors associated with gambling severity among young individuals.
METHODS: A cross-sectional survey of young adults (with focus on university students) in Greece, was implemented. Online gambling severity was assessed using the Problem Gambling Severity Index (PGSI) and categorized as no problems (0), low risk (1-2), moderate risk (3-7), and problem gambling (8-27). Associations between categorical variables and PGSI categories were assessed using Pearson's chi-square tests, while Spearman's rank correlation coefficients were used to examine associations between PGSI scores and online gambling-related behaviors. A generalized linear model (GLM) with binomial distribution and logit link function was used to identify factors associated with moderate/problem gambling (PGSI ≥3), adjusting for age, sex, smoking status, alcohol consumption, mental health, internet use, gambling time, and gambling expenditure. The model showed good discrimination (AUC=0.84) and low multicollinearity (VIF<1.5).
RESULTS: PGSI score was strongly correlated with online gambling time (ρ=0.61, p<0.001) and online gambling expenditure (ρ=0.60, p<0.001), whereas internet use showed only a weak correlation (ρ=0.09, p<0.001). In the GLM, younger age (OR=0.95, 95% CI: 0.93-0.98), male sex (OR=2.52, 95% CI: 2.04-3.13), smoking (OR=1.12, 95% CI: 1.02-1.24), alcohol consumption (OR=1.12, 95% CI: 1.03-1.21), poorer mental health (OR=1.38, 95% CI: 1.19-1.61), gambling time (OR=1.46, 95% CI: 1.38-1.55), and gambling expenditure (OR=1.02, 95% CI: 1.01-1.02) were independently associated with moderate/problem gambling (PGSI ≥3). Internet use was not independently associated with online gambling severity.
CONCLUSIONS: Prevention and harm-reduction strategies should focus on identifying young adults exhibiting intensive online gambling behaviors. Targeted screening and early intervention programs may help reduce the burden of online gambling-related harms among young adults.
METHODS: A cross-sectional survey of young adults (with focus on university students) in Greece, was implemented. Online gambling severity was assessed using the Problem Gambling Severity Index (PGSI) and categorized as no problems (0), low risk (1-2), moderate risk (3-7), and problem gambling (8-27). Associations between categorical variables and PGSI categories were assessed using Pearson's chi-square tests, while Spearman's rank correlation coefficients were used to examine associations between PGSI scores and online gambling-related behaviors. A generalized linear model (GLM) with binomial distribution and logit link function was used to identify factors associated with moderate/problem gambling (PGSI ≥3), adjusting for age, sex, smoking status, alcohol consumption, mental health, internet use, gambling time, and gambling expenditure. The model showed good discrimination (AUC=0.84) and low multicollinearity (VIF<1.5).
RESULTS: PGSI score was strongly correlated with online gambling time (ρ=0.61, p<0.001) and online gambling expenditure (ρ=0.60, p<0.001), whereas internet use showed only a weak correlation (ρ=0.09, p<0.001). In the GLM, younger age (OR=0.95, 95% CI: 0.93-0.98), male sex (OR=2.52, 95% CI: 2.04-3.13), smoking (OR=1.12, 95% CI: 1.02-1.24), alcohol consumption (OR=1.12, 95% CI: 1.03-1.21), poorer mental health (OR=1.38, 95% CI: 1.19-1.61), gambling time (OR=1.46, 95% CI: 1.38-1.55), and gambling expenditure (OR=1.02, 95% CI: 1.01-1.02) were independently associated with moderate/problem gambling (PGSI ≥3). Internet use was not independently associated with online gambling severity.
CONCLUSIONS: Prevention and harm-reduction strategies should focus on identifying young adults exhibiting intensive online gambling behaviors. Targeted screening and early intervention programs may help reduce the burden of online gambling-related harms among young adults.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EPH106
Topic
Epidemiology & Public Health, Health Policy & Regulatory, Real World Data & Information Systems
Topic Subcategory
Public Health
Disease
No Additional Disease & Conditions/Specialized Treatment Areas