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      Reconsidering the roots, structure, and implications of gambling motives: An integrative approach

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          Abstract

          Rationale and method

          Accurately identifying motives to gamble is crucial in the functional analysis of gambling behavior. In this study, a data-driven approach was followed to clarify the factor structure underlying a pool of motives for gambling, selected from the Gambling Motives Questionnaire–Financial (GMQ-F), and the Reasons for Gambling Questionnaire (RGQ), in a sample of regular problem and non-problem gamblers. Additionally, the role of gambling motives in the relationship between root behavioral activation/inhibition systems (BIS/BAS) and gambling severity, frequency, and preferences was explored using structural equation modelling (SEM).

          Results and conclusions

          The present study identified Social, Financial, and Fun/thrill-related gambling motives factors, but also a fourth factor in which some positive and negative reinforcement-based motives were grouped into a single and broader Affect regulation factor. This Affect regulation factor shared variance both with BIS and BAS-related measures, and was the only direct predictor of disordered gambling symptoms. The Fun/thrill factor was directly related to frequency of participation in high-arousal, skill-based games, and all factors were related to participation in lower-arousal, chance games (with Social motives negatively predicting both participation in the latter and total severity). In the SEM model, measures of BIS/BAS sensitivity were connected to gambling behavior only through gambling motives. Based on measures of items’ specificity, a shortened Spanish scale (the brief Gambling Motives Inventory, bGMI) is proposed to assess gambling motives in accordance with the observed 4-factor structure.

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          Most cited references70

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          Dealing with feeling: a meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation.

          The present meta-analysis investigated the effectiveness of strategies derived from the process model of emotion regulation in modifying emotional outcomes as indexed by experiential, behavioral, and physiological measures. A systematic search of the literature identified 306 experimental comparisons of different emotion regulation (ER) strategies. ER instructions were coded according to a new taxonomy, and meta-analysis was used to evaluate the effectiveness of each strategy across studies. The findings revealed differences in effectiveness between ER processes: Attentional deployment had no effect on emotional outcomes (d(+) = 0.00), response modulation had a small effect (d(+) = 0.16), and cognitive change had a small-to-medium effect (d(+) = 0.36). There were also important within-process differences. We identified 7 types of attentional deployment, 4 types of cognitive change, and 4 types of response modulation, and these distinctions had a substantial influence on effectiveness. Whereas distraction was an effective way to regulate emotions (d(+) = 0.27), concentration was not (d(+) = -0.26). Similarly, suppressing the expression of emotion proved effective (d(+) = 0.32), but suppressing the experience of emotion or suppressing thoughts of the emotion-eliciting event did not (d(+) = -0.04 and -0.12, respectively). Finally, reappraising the emotional response proved less effective (d(+) = 0.23) than reappraising the emotional stimulus (d(+) = 0.36) or using perspective taking (d(+) = 0.45). The review also identified several moderators of strategy effectiveness including factors related to the (a) to-be-regulated emotion, (b) frequency of use and intended purpose of the ER strategy, (c) study design, and (d) study characteristics.
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            Emotion-based dispositions to rash action: positive and negative urgency.

            Under heightened emotional states, individuals are more inclined to engage in ill-considered or rash actions than at other times. The authors present evidence for the existence of 2 related traits called positive and negative urgency. The traits refer to individual differences in the disposition to engage in rash action when experiencing extreme positive and negative affect, respectively. The authors provide evidence that these traits are distinct from other dispositions toward rash action and that they play distinct roles in predicting problem levels of involvement in behaviors such as alcohol consumption, binge eating, drug use, and risky sexual behavior. The authors identify facilitative conditions for the emergence of the urgency traits from neuroscience. Certain gene polymorphisms are associated with low levels of serotonin and high levels of dopamine; that pattern of neurotransmitter activity in a brain system linking the orbitofrontal cortex and the amygdala appears to facilitate the development of positive and negative urgency. The authors discuss the implications of this theory.
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              MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus

              MplusAutomation is a package for R that facilitates complex latent variable analyses in Mplus involving comparisons among many models and parameters. More specifically, MplusAutomation provides tools to accomplish three objectives: to create and manage Mplus syntax for groups of related models; to automate the estimation of many models; and to extract, aggregate, and compare fit statistics, parameter estimates, and ancillary model outputs. We provide an introduction to the package using applied examples including a large-scale simulation study. By reducing the effort required for large-scale studies, a broad goal of MplusAutomation is to support methodological developments in structural equation modeling using Mplus .
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                22 February 2019
                2019
                : 14
                : 2
                : e0212695
                Affiliations
                [1 ] Departamento de Psicología y Sociología, Universidad de Zaragoza, Teruel, Spain
                [2 ] Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain
                [3 ] Addictive and Compulsive Behaviours Lab, Institute for Health and Behaviour, University of Luxembourg, Esch-sur-Alzette, Luxembourg
                [4 ] Centre for Excessive Gambling, Lausanne University Hospital, Lausanne, Switzerland
                [5 ] Laboratory for Experimental Psychopathology (LEP), Psychological Sciences Research Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
                [6 ] Service Universitaire d'Addictologie de Lyon (SUAL), CH Le Vinatier, Bron, France
                [7 ] Scientific Research and Publication Cell (CRPS), Le Beau Vallon, Namur, Belgium
                Ariel University, ISRAEL
                Author notes

                Competing Interests: The authors have declared that no competing interests exist. Although José C. Perales is an academic editor for PLOS ONE, this does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0002-9521-6642
                http://orcid.org/0000-0001-5163-8811
                Article
                PONE-D-18-29972
                10.1371/journal.pone.0212695
                6386301
                30794642
                4e109ec3-18f7-4535-b2c3-6e71442ff88d
                © 2019 Barrada et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 16 October 2018
                : 7 February 2019
                Page count
                Figures: 1, Tables: 3, Pages: 22
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100010198, Ministerio de Economía, Industria y Competitividad, Gobierno de España;
                Award ID: PSI2017-85488-P
                This work is supported by a grant from the Spanish Government (Ministerio de Economía y Competitividad, Secretaría de Estado de Investigación, Desarrollo e Innovación; Convocatoria 2017 de Proyectos I+D de Excelencia, Spain; co-funded by the Fondo Europeo de Desarrollo Regional, FEDER, European Union), with reference number PSI2017-85488-P. The funding agency is public and played no role in planning or executing this work, nor interfered with the collection and interpretation of data.
                Categories
                Research Article
                Biology and Life Sciences
                Psychology
                Behavior
                Recreation
                Gambling
                Social Sciences
                Psychology
                Behavior
                Recreation
                Gambling
                Biology and Life Sciences
                Psychology
                Addiction
                Gambling Addiction
                Social Sciences
                Psychology
                Addiction
                Gambling Addiction
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Gambling Addiction
                Research and Analysis Methods
                Microscopy
                Electron Microscopy
                Scanning Electron Microscopy
                Biology and Life Sciences
                Psychology
                Behavior
                Social Sciences
                Psychology
                Behavior
                Social Sciences
                Economics
                Finance
                Biology and Life Sciences
                Psychology
                Behavior
                Recreation
                Games
                Social Sciences
                Psychology
                Behavior
                Recreation
                Games
                Research and Analysis Methods
                Research Design
                Survey Research
                Questionnaires
                Biology and Life Sciences
                Psychology
                Emotions
                Social Sciences
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                The open database and code files for these analyses are available at the Open Science Framework repository ( https://osf.io/drfpu/).

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