Problem and non-problem gamblers: a cross-sectional clustering study by gambling characteristics

Morgane Guillou Landreat, Isabelle Chereau Boudet, Bastien Perrot, Lucia Romo, Irene Codina, David Magalon, Melina Fatseas, Amandine Luquiens, Georges Brousse, Gaëlle Challet-Bouju, Marie Grall-Bronnec, JEU-Group, Marie Grall-Bronnec, Gaëlle Challet-Bouju, Jean-Luc Vénisse, Lucia Romo, Cindy Legauffre, Caroline Dubertret, Irène Codina, Marc Valleur, Marc Auriacombe, Mélina Fatséas, Jean-Marc Alexandre, Pierre-Michel Llorca, Isabelle Chéreau-Boudet, Christophe Lançon, David Magalon, Michel Reynaud, Amandine Luquiens, Morgane Guillou Landreat, Isabelle Chereau Boudet, Bastien Perrot, Lucia Romo, Irene Codina, David Magalon, Melina Fatseas, Amandine Luquiens, Georges Brousse, Gaëlle Challet-Bouju, Marie Grall-Bronnec, JEU-Group, Marie Grall-Bronnec, Gaëlle Challet-Bouju, Jean-Luc Vénisse, Lucia Romo, Cindy Legauffre, Caroline Dubertret, Irène Codina, Marc Valleur, Marc Auriacombe, Mélina Fatséas, Jean-Marc Alexandre, Pierre-Michel Llorca, Isabelle Chéreau-Boudet, Christophe Lançon, David Magalon, Michel Reynaud, Amandine Luquiens

Abstract

Objectives: Gambling characteristics are factors that could influence problem gambling development. The aim of this study was to identify a typology of gamblers to frame risky behaviour based on gambling characteristics (age of initiation/of problem gambling, type of gambling: pure chance/chance with pseudoskills/chance with elements of skill, gambling online/offline, amount wagered monthly) and to investigate clinical factors associated with these different profiles in a large representative sample of gamblers.

Design and setting: The study is a cross-sectional analysis to the baseline data of the french JEU cohort study (study protocol : Challet-Bouju et al, 2014). Recruitment (April 2009 to September 2011) involved clinicians and researchers from seven institutions that offer care for or conduct research on problem gamblers (PG). Participants were recruited in gambling places, and in care centres. Only participants who reported gambling in the previous year between 18 and 65 years old were included.Participants gave their written informed consent, it was approved by the French Research Ethics Committee.

Participants: The participants were 628 gamblers : 256 non-problem gamblers (NPG), 169 problem gamblers without treatment (PGWT) and 203 problem gamblers seeking treatment (PGST).

Results: Six clustering models were tested, the one with three clusters displayed a lower classification error rate (7.92%) and was better suited to clinical interpretation : 'Early Onset and Short Course' (47.5%), 'Early Onset and Long Course' (35%) and 'Late Onset and Short Course' (17.5%). Gambling characteristics differed significantly between the three clusters.

Conclusions: We defined clusters through the analysis of gambling variables, easy to identify, by psychiatrists or by physicians in primary care. Simple screening concerning these gambling characteristics could be constructed to prevent and to help PG identification. It is important to consider gambling characteristics : policy measures targeting gambling characteristics may reduce the risk of PG or minimise harm from gambling.

Trial registration number: NCT01207674 (ClinicalTrials.gov); Results.

Keywords: addiction; addictive behaviors; gamblers; gambling disorder; long term course.

Conflict of interest statement

Competing interests: MGB and GCB declare that the University Hospital of Nantes has received funding from the gambling industry (FDJ and PMU) in the form of a sponsorship that supports the gambling section of the BALANCED Unit (Reference Centre for Excessive Gambling). Scientific independence towards gambling industry operators is warranted. There were no constraints on publishing. LR declares that the University of Paris Ouest Nanterre La Défense has received funding directly from gambling industry (FDJ and PMU) as part of other research contracts – this funding has never had any influence on the present work.

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Clustering: three clusters and significant variables and covariables. AUD, alcohol use disorder; NPG, non-problem gamblers; PG, problem gamblers; PGST, problem gamblers seeking treatment; SUD, substance use disorder.

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