Authors:Hyeonseok Jeong, Jin Kyoung Oh, Eun Kyoung Choi, Jooyeon Jamie Im, Sujung Yoon, Helena Knotkova, Marom Bikson, In-Uk Song, Sang Hoon Lee, and Yong-An Chung
Background and aims
Some online gamers may encounter difficulties in controlling their gaming behavior. Previous studies have demonstrated beneficial effects of transcranial direct current stimulation (tDCS) on various kinds of addiction. This study investigated the effects of tDCS on addictive behavior and regional cerebral metabolic rate of glucose (rCMRglu) in problematic online gamers.
Problematic online gamers were randomized and received 12 sessions of either active (n = 13) or sham tDCS (n = 13) to the dorsolateral prefrontal cortex over 4 weeks (anode F3/cathode F4, 2 mA for 30 min, 3 sessions per week). Participants underwent brain 18F-fluoro-2-deoxyglucose positron emission tomography scans and completed questionnaires including the Internet Addiction Test (IAT), Brief Self-Control Scale (BSCS), and Behavioral Inhibition System/Behavioral Activation System scales (BIS/BAS) at the baseline and 4-week follow-up.
Significant decreases in time spent on gaming (P = 0.005), BIS (P = 0.03), BAS-fun seeking (P = 0.04), and BAS-reward responsiveness (P = 0.01), and increases in BSCS (P = 0.03) were found in the active tDCS group, while decreases in IAT were shown in both groups (P < 0.001). Group-by-time interaction effects were not significant for these measures. Increases in BSCS scores were correlated with decreases in IAT scores in the active group (β = −0.85, P < 0.001). rCMRglu in the left putamen, pallidum, and insula was increased in the active group compared to the sham group (P for interaction < 0.001).
Discussion and conclusions
tDCS may be beneficial for problematic online gaming potentially through changes in self-control, motivation, and striatal/insular metabolism. Further larger studies with longer follow-up period are warranted to confirm our findings.
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Authors:Tania Moretta, Shubao Chen, and Marc N. Potenza
and diagnosing IUDs. A key feature of IUDs and new technologies-related addictivebehaviors, which is often not shared with any other addictivebehaviors, is the number of available visual (e.g., colored graphical app interfaces; advertisements
Authors:Magdalen G. Schluter, David C. Hodgins, Barna Konkolÿ Thege, and T. Cameron Wild
: Further validation of a tool for simultaneous assessment of multiple addictivebehaviours . AddictiveBehaviors , 28 ( 2 ), 225 – 248 . https://doi.org/10.1016/s0306-4603(01)00231-3 . 10.1016/S0306-4603(01)00231-3 Davison , C. , Smith , G. D
Authors:Oren Lior, Reizer Abira, and Weinstein Aviv
In their critical review, Griffiths et al. (2018) discussed 10 myths in the study of work addiction, and addressed the need to conceptualize and investigate this area of research more carefully. In this commentary, we expand their arguments, suggesting that indeed some of the popular myths have solid evidence-based results in the organizational literature. Yet, some of the arguments are only indirectly related to previous organizational findings. Therefore, we emphasize the need to resolve the ambiguities of work addiction, as well as to develop a comprehensive and interdisciplinary understanding of the well-known phenomenon of addictive work behavior.
Authors:Deborah Louise Sinclair, Wouter Vanderplasschen, Shazly Savahl, Maria Florence, David Best, and Steve Sussman
original addiction and substitution. Using an illustrative case from South Africa, we discuss COVID-19-related pornography use through the lens of relapse and substitute addictions. Substitute addictions represent the replacement of one addictivebehavior
Authors:Ana Estévez, Paula Jáuregui, Inmaculada Sánchez-Marcos, Hibai López-González, and Mark D. Griffiths
this to screen for the existence of addictivebehaviors (substance and non-substance behaviors) and associated problems. The target population is women and men aged between 14 and 90 years. The scale comprises 32 dichotomous items (“yes” or “no” answers
Authors:Vladan Starcevic, Daniel L. King, Paul H. Delfabbro, Adriano Schimmenti, Jesús Castro-Calvo, Alessandro Giardina, and Joël Billieux
Montag, Wegmann, Sariyska, Demetrovics, and Brand (2020) propose a new classification scheme for Internet use disorders (IUD), conceptualised as “predominantly online addictivebehaviors” (p. 3). Their model suggests two “forms” of IUD
to include both diagnostic and hazardous designations as currently being proposed for ICD-11 and is analogous to designations for other addictivebehaviors (e.g., alcohol-use disorders and hazardous alcohol use as currently exist in the ICD-10). I