Literature DB >> 25192752

A Gamblers Clustering Based on Their Favorite Gambling Activity.

Gaëlle Challet-Bouju1,2, Jean-Benoit Hardouin3,4, Noëlle Renard5,3, Cindy Legauffre6,7, Marc Valleur8, David Magalon9, Mélina Fatséas10, Isabelle Chéreau-Boudet11, Mohamed-Ali Gorsane12,13, Jean-Luc Vénisse5,3, Marie Grall-Bronnec5,3.   

Abstract

The objective of this study was to identify profiles of gamblers to explain the choice of preferred gambling activity among both problem and non-problem gamblers. 628 non-problem and problem gamblers were assessed with a structured interview including "healthy" (sociodemographic characteristics, gambling habits and personality profile assessed with the Temperament and Character Inventory-125) and "pathological" [diagnosis of pathological gambling, gambling-related cognitions (GRCs) and psychiatric comorbidity] variables. We performed a two-step cluster analysis based solely on "healthy" variables to identify gamblers' profiles which typically reflect the choice of preferred gambling activity. The obtained classes were then described using both "healthy" and "pathological" variables, by comparing each class to the rest of the sample. Clusters were generated. Class 1 (Electronic Gaming Machines gamblers) showed high cooperativeness, a lower level of GRC about strategy and more depressive disorders. Class 2 (games with deferred results gamblers) were high novelty seekers and showed a higher level of GRC about strategy and more addictive disorders. Class 3 (roulette gamblers) were more often high rollers and showed a higher level of GRC about strategy and more manic or hypomanic episodes and more obsessive-compulsive disorders. Class 4 (instant lottery gamblers) showed a lower tendency to suicide attempts. Class 5 (scratch cards gamblers) were high harm avoiders and showed a lower overall level of GRC and more panic attacks and eating disorders. The preference for one particular gambling activity may concern different profiles of gamblers. This study highlights the importance of considering the pair gambler-game rather than one or the other separately, and may provide support for future research on gambling and preventive actions directed toward a particular game.

Entities:  

Keywords:  Clustering; Continuous gambling; Distorted cognitions; Gambling; Gambling habits; Personality

Mesh:

Year:  2015        PMID: 25192752     DOI: 10.1007/s10899-014-9496-8

Source DB:  PubMed          Journal:  J Gambl Stud        ISSN: 1050-5350


  29 in total

1.  Clinical gender differences among adult pathological gamblers seeking treatment.

Authors:  Enrique Echeburúa; Itxaso González-Ortega; Paz de Corral; Rocío Polo-López
Journal:  J Gambl Stud       Date:  2011-06

Review 2.  Pathological gambling. A comprehensive review.

Authors:  Namrata Raylu; Tian P S Oei
Journal:  Clin Psychol Rev       Date:  2002-09

3.  Gambling participation and problems among employees at a university health center.

Authors:  Nancy M Petry; Sarita Mallya
Journal:  J Gambl Stud       Date:  2004

4.  Neurocognitive dysfunction in strategic and non-strategic gamblers.

Authors:  Jon E Grant; Brian L Odlaug; Samuel R Chamberlain; Liana R N Schreiber
Journal:  Prog Neuropsychopharmacol Biol Psychiatry       Date:  2012-05-18       Impact factor: 5.067

5.  Irrational thinking among slot machine players.

Authors:  M B Walker
Journal:  J Gambl Stud       Date:  1992-09

6.  Gambling involvement and increased risk of gambling problems.

Authors:  James G Phillips; Rowan Ogeil; Yang-Wai Chow; Alex Blaszczynski
Journal:  J Gambl Stud       Date:  2013-12

7.  Gender differences in pathological gamblers seeking medication treatment.

Authors:  Jon E Grant; Suck Won Kim
Journal:  Compr Psychiatry       Date:  2002 Jan-Feb       Impact factor: 3.735

8.  [Socio-demographic and clinical assessment, and trajectory of a sample of French pathological gamblers].

Authors:  M Grall-Bronnec; G Bouju; M Landréat-Guillou; J-L Vénisse
Journal:  Encephale       Date:  2010-04-03       Impact factor: 1.291

9.  Personality correlates of pathological gambling derived from Big Three and Big Five personality models.

Authors:  Joshua D Miller; James Mackillop; Erica E Fortune; Jessica Maples; Charles E Lance; W Keith Campbell; Adam S Goodie
Journal:  Psychiatry Res       Date:  2012-10-15       Impact factor: 3.222

10.  Rapid onset of pathological gambling in machine gamblers.

Authors:  Robert B Breen; Mark Zimmerman
Journal:  J Gambl Stud       Date:  2002
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  9 in total

1.  Typology of online lotteries and scratch games gamblers' behaviours: A multilevel latent class cluster analysis applied to player account-based gambling data.

Authors:  Bastien Perrot; Jean-Benoit Hardouin; Marie Grall-Bronnec; Gaëlle Challet-Bouju
Journal:  Int J Methods Psychiatr Res       Date:  2018-10-18       Impact factor: 4.035

2.  Are Treatment Outcomes Determined by Type of Gambling? A UK Study.

Authors:  Silvia Ronzitti; Emiliano Soldini; Neil Smith; Andrew Bayston; Massimo Clerici; Henrietta Bowden-Jones
Journal:  J Gambl Stud       Date:  2018-09

3.  Segmenting Chinese Gamblers Based on Gambling Forms: A Latent Class Analysis.

Authors:  Sunny Zhenzhen Nong; Lawrence Hoc Nang Fong; Davis Ka Chio Fong; Desmond Lam
Journal:  J Gambl Stud       Date:  2020-03

4.  Dopamine and Gambling Disorder: Prospects for Personalized Treatment.

Authors:  Andrew Kayser
Journal:  Curr Addict Rep       Date:  2019-03-07

5.  Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis.

Authors:  Gaëlle Challet-Bouju; Jean-Benoit Hardouin; Elsa Thiabaud; Anaïs Saillard; Yann Donnio; Marie Grall-Bronnec; Bastien Perrot
Journal:  J Med Internet Res       Date:  2020-08-12       Impact factor: 5.428

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

Authors:  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
Journal:  BMJ Open       Date:  2020-02-18       Impact factor: 2.692

7.  Types of gambling and levels of harm: A UK study to assess severity of presentation in a treatment-seeking population.

Authors:  Silvia Ronzitti; Emiliano Soldini; Vittorio Lutri; Neil Smith; Massimo Clerici; Henrietta Bowden-Jones
Journal:  J Behav Addict       Date:  2016-09-28       Impact factor: 6.756

8.  The Gambling Consumption Mediation Model (GCMM): A Multiple Mediation Approach to Estimate the Association of Particular Game Types with Problem Gambling.

Authors:  Tim Brosowski; Daniel Thor Olason; Tobias Turowski; Tobias Hayer
Journal:  J Gambl Stud       Date:  2021-03

9.  Inhibitory control in poker: Do experienced non-pathological poker gamblers exhibit better performance than healthy controls on motor, verbal and emotional expression inhibition?

Authors:  G Challet-Bouju; E Hurel; E Thiabaud; J Leboucher; M Leroy; A L Quibel; M Grall-Bronnec
Journal:  J Behav Addict       Date:  2020-06-05       Impact factor: 6.756

  9 in total

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