Youssef Allami1,2, David C Hodgins3, Matthew Young4,5, Natacha Brunelle6, Shawn Currie3, Magali Dufour7, Marie-Claire Flores-Pajot4, Louise Nadeau8. 1. ALLY Addiction Consulting, Montréal, QC, Canada. 2. Centre de Réadaptation en Dépendance de Montréal, Institut Universitaire, CIUSSS du Centre-Sud-de-l'Ile-de-Montréal, Montréal, QC, Canada. 3. Department of Psychology, University of Calgary, Calgary, AB, Canada. 4. Canadian Centre on Substance Use and Addiction, Ottawa, ON, Canada. 5. Department of Psychology, Carleton University, Ottawa, ON, Canada. 6. Département de psychoéducation, Université du Québec à Trois-Rivières, Trois-Rivières, QC. 7. Département de psychologie, Université du Québec à Montréal, Montréal, QC, Canada. 8. Département de psychologie, Université de Montréal, Montréal, QC, Canada.
Abstract
BACKGROUND AND AIMS: Few meta-analyses have been conducted to pool the most constant risk factors for problem gambling. The present meta-analysis summarizes effect sizes of the most frequently assessed problem gambling risk factors, ranks them according to effect size strength and identifies any differences in effects across genders. METHOD: A random-effects meta-analysis was conducted on jurisdiction-wide gambling prevalence surveys on the general adult population published until March 2019. One hundred and four studies were eligible for meta-analysis. The number of participants varied depending on the risk factor analyzed, and ranged from 5327 to 273 946 (52% female). Weighted mean odds ratios were calculated for 57 risk factors (socio-demographic, psychosocial, gambling activity and substance use correlates), allowing them to be ranked from largest to smallest with regard to their association with problem gambling. RESULTS: The highest odds ratio (OR) was for internet gambling [OR = 7.59, 95% confidence interval (CI) = 5.24, 10.99, P < 0.000] and the lowest was for employment status (OR = 1.03, 95% CI = 0.87, 1.22, P = 0.718). The largest effect sizes were generally in the gambling activity category and the smallest were in the socio-demographic category. No differences were found across genders for age-associated risk. CONCLUSIONS: A meta-analysis of 104 studies of gambling prevalence indicated that the most frequently assessed problem gambling risk factors with the highest effect sizes are associated with continuous-play format gambling products.
BACKGROUND AND AIMS: Few meta-analyses have been conducted to pool the most constant risk factors for problem gambling. The present meta-analysis summarizes effect sizes of the most frequently assessed problem gambling risk factors, ranks them according to effect size strength and identifies any differences in effects across genders. METHOD: A random-effects meta-analysis was conducted on jurisdiction-wide gambling prevalence surveys on the general adult population published until March 2019. One hundred and four studies were eligible for meta-analysis. The number of participants varied depending on the risk factor analyzed, and ranged from 5327 to 273 946 (52% female). Weighted mean odds ratios were calculated for 57 risk factors (socio-demographic, psychosocial, gambling activity and substance use correlates), allowing them to be ranked from largest to smallest with regard to their association with problem gambling. RESULTS: The highest odds ratio (OR) was for internet gambling [OR = 7.59, 95% confidence interval (CI) = 5.24, 10.99, P < 0.000] and the lowest was for employment status (OR = 1.03, 95% CI = 0.87, 1.22, P = 0.718). The largest effect sizes were generally in the gambling activity category and the smallest were in the socio-demographic category. No differences were found across genders for age-associated risk. CONCLUSIONS: A meta-analysis of 104 studies of gambling prevalence indicated that the most frequently assessed problem gambling risk factors with the highest effect sizes are associated with continuous-play format gambling products.
Authors: Carrie A Shaw; David C Hodgins; Robert J Williams; Yale D Belanger; Darren R Christensen; Nady El-Guebaly; Daniel S McGrath; Fiona Nicoll; Garry J Smith; Rhys M G Stevens Journal: J Gambl Stud Date: 2021-09-20
Authors: David Forsström; Alexander Rozental; Anders Kottorp; Philip Lindner; Markus Jansson-Fröjmark; Hugo Hesser Journal: Int J Environ Res Public Health Date: 2021-04-30 Impact factor: 3.390
Authors: Isabel Baenas; Mikel Etxandi; Ester Codina; Roser Granero; Fernando Fernández-Aranda; Mónica Gómez-Peña; Laura Moragas; Sandra Rivas; Marc N Potenza; Anders Håkansson; Amparo Del Pino-Gutiérrez; Bernat Mora-Maltas; Eduardo Valenciano-Mendoza; José M Menchón; Susana Jiménez-Murcia Journal: Front Psychol Date: 2021-12-14