Correlation between precontemplation and alpha activity in gambling disorder
Jaewon Lee,1,* Sam-Wook Choi,2,* Kyoung Min Kim,3 Young Sik Lee,4 Jun Won Kim51Department of Psychiatry, Easybrain Center, Seoul, Republic of Korea; 2Department of Psychiatry, True Mind Mental Health Clinic, Seoul, Republic of Korea; 3Department of Psychiatry, Dankook University Hospital, Cheonan, R...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
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Dove Medical Press
2019
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| Acceso en línea: | https://doaj.org/article/8ab0e96cd41c4e9aadf90abbecbe682e |
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| Sumario: | Jaewon Lee,1,* Sam-Wook Choi,2,* Kyoung Min Kim,3 Young Sik Lee,4 Jun Won Kim51Department of Psychiatry, Easybrain Center, Seoul, Republic of Korea; 2Department of Psychiatry, True Mind Mental Health Clinic, Seoul, Republic of Korea; 3Department of Psychiatry, Dankook University Hospital, Cheonan, Republic of Korea; 4Department of Psychiatry, Chung-Ang University, College of Medicine, Seoul, Republic of Korea; 5Department of Psychiatry, Catholic University of Daegu School of Medicine, Daegu, Republic of Korea*These authors contributed equally to this work Purpose: Gambling disorder is a psychiatric condition characterized by persistent and recurrent maladaptive gambling. In the present study, we evaluated the characteristics of resting-state electroencephalogram (EEG) recordings in patients with gambling disorder. In addition, we explored the association between the EEG characteristics of the patients and the stages of change in a transtheoretical model.Methods: All participants were men who visited a gambling disorder clinic in Seoul, Korea. At the assessment, questionnaires, including the Readiness to Change Questionnaire (RCQ), were administered and resting-state EEGs were carried out. Participants were grouped based on Ward’s method for cluster analysis. Independent sample t-tests were used to evaluate group differences. To assess the relationship between the clinical data and the EEG recordings, we used Pearson’s partial correlation analysis.Results: Overall, 63 male participants were enrolled. Cluster analysis of the alpha activity revealed two clusters. No significant differences were observed in the demographic or clinical data between the two groups except for the Beck Depression Inventory (BDI). We found that the precontemplation score of the RCQ was positively correlated with the z-score of the relative alpha power in almost all cortical regions.Conclusion: This study suggests that EEG parameters, particularly alpha activity, could inform us about the subtypes or stages of change in gambling disorder. Alpha power is the predominant EEG rhythm in a relaxed, alert person; thus, alpha power serves as an index of relaxation. We expect that the level of alpha activity could be utilized as an additional parameter to help clinicians assess and treat patients with gambling disorder.Keywords: quantitative electroencephalography, gambling disorder, stages-of-change model, alpha activity |
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