Literature DB >> 26827154

Gambling transitions among adult gamblers: A multi-state model using a Markovian approach applied to the JEU cohort.

Mélanie Bruneau1, Marie Grall-Bronnec1, Jean-Luc Vénisse1, Lucia Romo2, Marc Valleur3, David Magalon4, Mélina Fatséas5, Isabelle Chéreau-Boudet6, Amandine Luquiens7, Gaëlle Challet-Bouju1, Jean-Benoit Hardouin8.   

Abstract

INTRODUCTION: The aim of this paper is to study transitions between two states of gambling in adulthood (problem gambling and non-problem gambling) and to identify factors that might influence these transitions.
METHODS: Data for this 2-year long longitudinal study were collected in a French Outpatient Addiction Treatment Center, in gambling establishments and through the press. Both problem gamblers and non-problem gamblers were evaluated using a structured interview and self-report questionnaires. The statistical analysis was carried out using a Markovian approach.
RESULTS: The analyzed cohort consisted of 304 gamblers with 519 observed transitions. Participants with no past-year gambling problems (based on the DSM-IV) had a probability of about 90% of also having no past-year gambling problems at the following assessment, whereas the observed percentage of problem gamblers transitioning to non-problem gambling was of 48%. We reported (i) vulnerability factors of transitioning to problem gambling (such as an anxiety disorder or an Attention Deficit Hyperactivity Disorder (ADHD) during the childhood), (ii) protective factors for non-problem gamblers, (iii) recovery factors (such as ongoing treatment and younger age) and (iv) persistence factors of a gambling problem (such as a persistent ADHD).
CONCLUSIONS: The status of problem gambler is unstable over time, whereas we found stability among non-problem gamblers. Our findings suggest the existence of vulnerability and protective factors in gambling. These results lead to think about preventive actions and adaptive care, such as cognitive-behavioral therapy or researching gambling problems in people with an anxiety disorder or ADHD.
Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Gambling; Longitudinal study; Markov process; Prevalence; Risk factors; Transitions

Mesh:

Year:  2016        PMID: 26827154     DOI: 10.1016/j.addbeh.2016.01.010

Source DB:  PubMed          Journal:  Addict Behav        ISSN: 0306-4603            Impact factor:   3.913


  12 in total

1.  Self-efficacy and Physical Activity in Overweight and Obese Adults Participating in a Worksite Weight Loss Intervention: Multistate Modeling of Wearable Device Data.

Authors:  Michael C Robertson; Charles E Green; Yue Liao; Casey P Durand; Karen M Basen-Engquist
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-12-23       Impact factor: 4.254

2.  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

3.  Effectiveness of At-Risk Gamblers' Temporary Self-Exclusion from Internet Gambling Sites.

Authors:  J Caillon; M Grall-Bronnec; B Perrot; J Leboucher; Y Donnio; L Romo; G Challet-Bouju
Journal:  J Gambl Stud       Date:  2019-06

4.  Cognitive distortions and ADHD in pathological gambling: A national longitudinal case-control cohort study.

Authors:  Lucia Romo; Cindy Legauffre; Alice Guilleux; Marc Valleur; David Magalon; Mélina Fatséas; Isabelle Chéreau-Boudet; Amandine Luquiens; Jean-Luc Vénisse; Marie Grall-Bronnec; Gaëlle Challet-Bouju
Journal:  J Behav Addict       Date:  2016-10-24       Impact factor: 6.756

5.  Measuring Gambling Reinforcers, Over Consumption and Fallacies: The Psychometric Properties and Predictive Validity of the Jonsson-Abbott Scale.

Authors:  Jakob Jonsson; Max W Abbott; Anders Sjöberg; Per Carlbring
Journal:  Front Psychol       Date:  2017-10-16

6.  Typology of patients with behavioral addictions or eating disorders during a one-year period of care: Exploring similarities of trajectory using growth mixture modeling coupled with latent class analysis.

Authors:  Marion Montourcy; Jean-Benoit Hardouin; Julie Caillon; Juliette Leboucher; Morgane Rousselet; Marie Grall-Bronnec; Gaëlle Challet-Bouju
Journal:  PLoS One       Date:  2018-11-14       Impact factor: 3.240

7.  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

8.  Gambling Marketing Strategies and the Internet: What Do We Know? A Systematic Review.

Authors:  Morgane Guillou-Landreat; Karine Gallopel-Morvan; Delphine Lever; Delphine Le Goff; Jean-Yves Le Reste
Journal:  Front Psychiatry       Date:  2021-02-26       Impact factor: 4.157

9.  Spiritual experiences are related to engagement of a ventral frontotemporal functional brain network: Implications for prevention and treatment of behavioral and substance addictions.

Authors:  Clayton H McClintock; Patrick D Worhunsky; Jiansong Xu; Iris M Balodis; Rajita Sinha; Lisa Miller; Marc N Potenza
Journal:  J Behav Addict       Date:  2019-12-01       Impact factor: 6.756

10.  Five-year follow-up on a sample of gamblers: predictive factors of relapse.

Authors:  Marie Grall-Bronnec; Morgane Guillou-Landreat; Julie Caillon; Caroline Dubertret; Lucia Romo; Irène Codina; Isabelle Chereau-Boudet; Christophe Lancon; Marc Auriacombe; Jean-Benoit Hardouin; Gaëlle Challet-Bouju
Journal:  J Behav Addict       Date:  2021-04-01       Impact factor: 6.756

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.