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

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          Abstract

          Background and Aims

          Few studies have been conducted on the long-term evolution of gambling disorder (GD). The aim of this study was to identify factors that could predict GD relapse.

          Methods

          Data were part of a dataset from a large 5-year cohort of gamblers who were assessed at inclusion and each year thereafter. Participants were recruited from an outpatient addiction treatment center, from various gambling places and through the press. For this specific study, inclusion criteria included (i) transitioning from GD to recovery at a follow-up time and (ii) undergoing at least one follow-up visit afterwards. Participants were evaluated using a structured clinical interview and self-report questionnaires assessing sociodemographic, gambling and clinical characteristics. “Relapse” was defined as the presence of GD (according to the DSM-5) at the N+1 th visit following the absence of GD at the N th visit. A Markov model-based approach was employed to examine predictive factors associated with relapse at a subsequent follow-up visit.

          Results

          The sample consisted of 87 participants, aged 47.6 years (sd = 12.6), who were predominantly male (65%). Among the participants, 49 remained in recovery, whereas 38 relapsed. Participants who reported not having experienced at least one month of abstinence and those with a low level of self-directedness at the previous follow-up visit were more likely to relapse.

          Conclusions

          Our findings suggest the existence of factors that are predictive of relapse in individuals with GD who had previously achieved recovery. These results can inspire the development of measures to promote long-term recovery.

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          Most cited references72

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          Applied Logistic Regression

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            The Mini International Neuropsychiatric Interview (MINI). A short diagnostic structured interview: reliability and validity according to the CIDI

            The Mini International Neuropsychiatric Interview (MINI) is a short diagnostic structured interview (DSI) developed in France and the United States to explore 17 disorders according to Diagnostic and Statistical Manual (DSM)-III-R diagnostic criteria. It is fully structured to allow administration by non-specialized interviewers. In order to keep it short it focuses on the existence of current disorders. For each disorder, one or two screening questions rule out the diagnosis when answered negatively. Probes for severity, disability or medically explained symptoms are not explored symptom-by-symptom. Two joint papers present the inter-rater and test-retest reliability of the MINI the validity versus the Composite International Diagnostic Interview (CIDI) (this paper) and the Structured Clinical Interview for DSM-III-R patients (SCID) (joint paper). Three-hundred and forty-six patients (296 psychiatric and 50 non-psychiatric) were administered the MINI and the CIDI ‘gold standard’. Forty two were interviewed by two investigators and 42 interviewed subsequently within two days. Interviewers were trained to use both instruments. The mean duration of the interview was 21 min with the MINI and 92 for corresponding sections of the CIDI. Kappa coefficient, sensitivity and specificity were good or very good for all diagnoses with the exception of generalized anxiety disorder (GAD) (kappa = 0.36), agoraphobia (sensitivity = 0.59) and bulimia (kappa = 0.53). Interrater and test-retest reliability were good. The main reasons for discrepancies were identified. The MINI provided reliable DSM-III-R diagnoses within a short time frame, The study permitted improvements in the formulations for GAD and agoraphobia in the current DSM-IV version of the MINI.
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              A psychobiological model of temperament and character.

              In this study, we describe a psychobiological model of the structure and development of personality that accounts for dimensions of both temperament and character. Previous research has confirmed four dimensions of temperament: novelty seeking, harm avoidance, reward dependence, and persistence, which are independently heritable, manifest early in life, and involve preconceptual biases in perceptual memory and habit formation. For the first time, we describe three dimensions of character that mature in adulthood and influence personal and social effectiveness by insight learning about self-concepts. Self-concepts vary according to the extent to which a person identifies the self as (1) an autonomous individual, (2) an integral part of humanity, and (3) an integral part of the universe as a whole. Each aspect of self-concept corresponds to one of three character dimensions called self-directedness, cooperativeness, and self-transcendence, respectively. We also describe the conceptual background and development of a self-report measure of these dimensions, the Temperament and Character Inventory. Data on 300 individuals from the general population support the reliability and structure of these seven personality dimensions. We discuss the implications for studies of information processing, inheritance, development, diagnosis, and treatment.
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                Author and article information

                Contributors
                Journal
                J Behav Addict
                J Behav Addict
                JBA
                Journal of Behavioral Addictions
                Akadémiai Kiadó (Budapest )
                2062-5871
                2063-5303
                01 April 2021
                April 2021
                April 2021
                : 10
                : 1
                : 42-54
                Affiliations
                [1 ]Department of Addictology and Psychiatry, CHU Nantes , Nantes, France
                [2 ]Université de Nantes, Université de Tours, Inserm U1246 , Nantes, France
                [3 ]Department of Addictology, CHU Brest , Brest, France
                [4 ]Université de Bretagne Occidentale, ERCR SPURBO , Brest, France
                [5 ]Institute of Psychiatry and Neurosciences, INSERM UMR1266, Université de Paris , Team 1, Paris, France
                [6 ]Department of Psychiatry, AP-HP, Louis Mourier Hospital , Colombes, France
                [7 ]Department of Psychology, Université Paris Nanterre , EA 4430 CLIPSYD, Nanterre, France
                [8 ]CMME, GHU Paris Psychiatrie et Neurosciences, INSERM U1266 , Paris, France
                [9 ]Marmottan Medical Center, GPS Perray-Vaucluse , Paris, France
                [10 ]Psychiatry Department, CHU Clermont-Ferrand , Clermont-Ferrand, France
                [11 ]Centre d'études et de recherches sur les services de santé et la qualité de vie, Université de la Méditerranée , Marseille, France
                [12 ]University of Bordeaux , Bordeaux, France
                [13 ]Addiction Team, Sleep Addiction and Neuropsychiatry Laboratory (SANPSY) , CNRS USR 3413, Bordeaux, France
                [14 ]Pôle Addictologie, CH Charles Perrens and CHU de Bordeaux , Bordeaux, France
                [15 ]Methodology and Biostatistic Department, CHU Nantes , Nantes, France
                Author notes
                [* ]Corresponding author. E-mail: marie.bronnec@ 123456chu-nantes.fr
                [†]

                Members of the JEU-Group: Marie Grall-Bronnec, Gaëlle Challet-Bouju, Jean-Luc Vénisse, Lucia Romo, Cindy Legauffre, Caroline Dubertret, Jean Adès, Irène Codina, Marc Valleur, Marc Auriacombe, Mélina Fatséas, Jean-Marc Alexandre, Pierre-Michel Llorca, Isabelle Chéreau-Boudet, Christophe Lançon, David Magalon, Amandine Luquiens, Michel Reynaud.

                Article
                10.1556/2006.2021.00009
                8969856
                33793415
                cab182f1-2184-46f1-af12-74dbf226b891
                © 2021 The Author(s)

                Open Access. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated.

                Page count
                Figures: 2, Tables: 4, Equations: 0, References: 63, Pages: 13
                Product
                Funding
                Funded by: French Inter-departmental Mission
                Funded by: French National Institute of Health and Medical Research (INSERM)
                Funded by: French Ministry of Health
                Award ID: PHRC 2009 – RCB 2008-A01188-47
                Categories
                Article

                gambling disorder,recovery,relapse,predictive model,markov,self-directedness

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