BACKGROUND: Gaming disorder (GD) is a new official diagnosis in the International Classification of Diseases, 11th Revision, and with its recognition, the need to offer treatment for the condition has become apparent. More knowledge is needed about the type of treatment needed for this group of patients.
OBJECTIVE: This study aims to evaluate the effectiveness and acceptability of a novel module-based psychological treatment for GD based on cognitive behavioral therapy and family therapy.
METHODS: This study is a nonrandomized intervention study, with a pretest, posttest, and 3-month follow-up design. It will assess changes in GD symptoms, psychological distress, and gaming time, alongside treatment satisfaction, working alliance, and a qualitative exploration of patients\' and relatives\' experiences of the treatment.
RESULTS: This study started in March 2022 and the recruitment is expected to close in August 2024.
CONCLUSIONS: This study evaluates the effectiveness and acceptability of a psychological treatment for patients with problematic gaming behavior and GD. It is an effectiveness trial and will be conducted in routine care. This study will have high external validity and ensure that the results are relevant for a diverse clinical population with psychiatric comorbidity.
BACKGROUND: ClinicalTrials.gov NCT06018922; https://clinicaltrials.gov/study/NCT06018922.
UNASSIGNED: DERR1-10.2196/56315.

BACKGROUND: Internet gaming disorder (IGD) has become increasingly prevalent worldwide and is recognized as a significant public health concern because of its negative consequences on individuals mental and physical health, social relationships, academic performance and overall well-being. While research on IGD has gained significant momentum in the past decade, the neural substrates underlying this disorder remains unclear. This study aims to investigate resting-state cortical activation in male subjects with IGD using a concurrent functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG) hybrid system.
METHODS: Twenty-two male individuals with IGD (18-23 years old) and twenty-two male healthy, age-matched healthy controls were included in the study. Mean oxygenation of the prefrontal cortex (PFC) and whole head neural activity were measured using fNIRS and EEG respectively, during eyes-open and eyes-closed conditions at the resting state. EEG signals were decomposed into distinct frequency sub-bands with wavelet transform, followed by the analysis of the power spectral density within each band. Mean oxygenation of PFC is measured using a multichannel fNIRS system.
RESULTS: Results revealed that the individuals with IGD had significantly higher beta power in the frontal region compared to the control group. Individuals with IGD showed significantly increased PFC oxygenation compared to healthy controls. Additionally, both frontal beta power and PFC oxygenation were significantly correlated with IGD severity. However, there were no significant correlations observed between oxygenation and beta powers.
CONCLUSIONS: This study is the first to examine resting-state cortical activation using multimodal EEG-fNIRS system in young adults with IGD. Moreover, it provides an important contribution to the understanding of the underlying neural mechanisms of IGD and offer new insights for the diagnosis and intervention of the disorder using multimodal EEG-fNIRS system. Further studies should aim to replicate the findings of this study using a larger and more culturally diverse sample to support the neurophysiological basis of IGD.

Background: Several studies focused on the escalating prevalence of Problematic Use of Internet (PUI) and its consequential impact on mental health globally. This study investigates the relationship between PUI and associated psychological variables across different cultural contexts in Italy, Spain, Ecuador, and Peru. Method: A total of 675 participants, aged 18 to 54 (M = 22.73; SD = 4.05), completed measures assessing Internet addiction, social media addiction, Fear of Missing Out, Internet Gaming Disorder, and Phubbing. Results: Significant cultural variations were found, with Italian participants showing higher levels of Internet addiction but lower levels of social media addiction compared to other countries. Fear of Missing Out was higher in Italy, while the Italian sample exhibited lower Internet Gaming Disorder levels compared to Peru. As regards the communication disturbance caused by Phubbing, the Italian sample demonstrated significantly higher scores than the Peruvian sample. Linear regression analyses revealed distinct predictors for problematic Internet use in each country, emphasizing the importance of considering the cultural context in understanding this phenomenon. Conclusions: These findings contribute valuable insights into the interplay of cultural factors, psychological variables, and problematic Internet use, guiding future research and interventions.

UNASSIGNED: Sex-specific differences in internet gaming disorder (IGD) neurophysiology remain underexplored. Here we investigated sex-related variability in regional homogeneity (ReHo) and functional connectivity (FC) in IGD and their correlations with sleep quality.
UNASSIGNED: Resting-state functional magnetic resonance imaging (fMRI) scans were performed on 52 subjects with IGD and 50 healthy controls (HCs). Two-way ANOVA was used to examine sex and diagnosis interactions in ReHo and FC, followed by post-hoc analyses to explore FC biomarkers for different sexes.
UNASSIGNED: In ReHo analysis, the four groups showed significant sex and diagnosis interactions in the right middle frontal gyrus (rMFG). FC analysis with rMFG as the seed region revealed a significant sex and diagnosis interaction effect in FC of the rMFG with the bilateral postcentral gyrus (PoCG). In male IGD group, FC between the rMFG and the bilateral PoCG correlates strongly with daytime dysfunction score and the Pittsburgh sleep quality inventory (PSQI) total score.
UNASSIGNED: These findings emphasize the importance of considering sexual dimorphism in the neurobiology of IGD, which might influence subsequent treatment strategies.

BACKGROUND: Internet gaming disorder (IGD) becomes a growing concern during the digital era, especially with the pandemic\'s social distancing measures. It is essential to comprehend the psychosocial predictors and impacts of IGD.
METHODS: A two-wave annual panel study was conducted in Zigong, China, utilizing regional sampling through school-based surveys involving upper primary school to high school students. Data were collected in October 2020 (T1, N = 94,020) and October 2021 (T2, N = 60,551). Self-report data were collected on demographic information, internet gaming behavior, and other mental health factors. Cross-lagged panel models (CLPM) were employed to estimate the bidirectional relationships between the variables.
RESULTS: At T1, 65,643 (72.6 %) participants identified as gamers; at T2, this number decreased to 42,213 (69.7 %). T1 IGD symptoms demonstrated predictability for all T2 psychological variables. Within the framework of the CLPM examining the interplay between IGD symptoms, anxiety symptoms, and hyperactivity/inattention, we uncovered significant reciprocal cross-lagged effects between these variables over time. The relationship between T1 IGD symptoms and T2 anxiety symptoms had age-specific differences, with 13-15-year-old boys displaying the highest coefficient, which decreased for the 16-18 age group.
CONCLUSIONS: Our study is subject to potential recall bias associated with self-reported retrospective data. Additionally, our analysis assumes temporal ordering between variables, an assumption that may not always hold in complex systems.
CONCLUSIONS: There are reciprocal relationships between IGD symptoms, anxiety symptoms, and hyperactivity/inattention in adolescents, underscoring the imperative need for comprehensive strategies aimed at addressing the impact of IGD on mental health and overall well-being.

Limited awareness, social stigma, and access to mental health professionals hinder early detection and intervention of internet gaming disorder (IGD), which has emerged as a significant concern among young individuals. Prevalence estimates vary between 0.7% and 15.6%, and its recognition in the International Classification of Diseases, 11th Revision and Diagnostic and Statistical Manual of Mental Disorders, 5th Edition underscores its impact on academic functioning, social isolation, and mental health challenges.
This study aimed to uncover digital phenotypes for the early detection of IGD among adolescents in learning settings. By leveraging sensor data collected from student tablets, the overarching objective is to incorporate these digital indicators into daily school activities to establish these markers as a mental health screening tool, facilitating the early identification and intervention for IGD cases.
A total of 168 voluntary participants were engaged, consisting of 85 students with IGD and 83 students without IGD. There were 53% (89/168) female and 47% (79/168) male individuals, all within the age range of 13-14 years. The individual students learned their Korean literature and mathematics lessons on their personal tablets, with sensor data being automatically collected. Multiple regression with bootstrapping and multivariate ANOVA were used, prioritizing interpretability over predictability, for cross-validation purposes.
A negative correlation between IGD Scale (IGDS) scores and learning outcomes emerged (r166=-0.15; P=.047), suggesting that higher IGDS scores were associated with lower learning outcomes. Multiple regression identified 5 key indicators linked to IGD, explaining 23% of the IGDS score variance: stroke acceleration (β=.33; P<.001), time interval between keys (β=-0.26; P=.01), word spacing (β=-0.25; P<.001), deletion (β=-0.24; P<.001), and horizontal length of strokes (β=0.21; P=.02). Multivariate ANOVA cross-validated these findings, revealing significant differences in digital phenotypes between potential IGD and non-IGD groups. The average effect size, measured by Cohen d, across the indicators was 0.40, indicating a moderate effect. Notable distinctions included faster stroke acceleration (Cohen d=0.68; P=<.001), reduced word spacing (Cohen d=.57; P=<.001), decreased deletion behavior (Cohen d=0.33; P=.04), and longer horizontal strokes (Cohen d=0.34; P=.03) in students with potential IGD compared to their counterparts without IGD.
The aggregated findings show a negative correlation between IGD and learning performance, highlighting the effectiveness of digital markers in detecting IGD. This underscores the importance of digital phenotyping in advancing mental health care within educational settings. As schools adopt a 1-device-per-student framework, digital phenotyping emerges as a promising early detection method for IGD. This shift could transform clinical approaches from reactive to proactive measures.

BACKGROUND: Metacognitions about online gaming have been shown to be correlated with Internet Gaming Disorder (IGD). Knowledge of metacognitions about online gaming can help to understand IGD. The Metacognitions about Online Gaming Scale (MOGS) is a reliable and valid tool to measure specific metacognitions about online gaming in both adults and adolescents, which is lacking in China.
OBJECTIVE: This study was conducted to assess the psychometric properties of the Chinese version of the MOGS (C-MOGS) and its relationship with IGD in the Chinese population.
METHODS: A total of 772 Chinese individuals (age: mean 21.70, SD 8.81 years; age range: 13-57 years; 458/772, 59.3% male) completed a web-based questionnaire survey, including the C-MOGS and a battery of validated scales measuring IGD, gaming motives, depression, and anxiety.
RESULTS: Through exploratory and confirmatory factor analyses, the 3-factor structure was confirmed to have adequate model fit and internal consistency reliability (Cronbach α≥.799, Guttman split-half coefficients≥0.754). Concurrent validity of the C-MOGS was supported by its correlations with IGD (P<.001), gaming motives (P<.001), depression (P<.001), and anxiety (P<.001). Furthermore, the incremental validity analysis showed that the C-MOGS predicted 13% of the variance in IGD while controlling for gender, age, weekly gaming hours, gaming motives, depression, and anxiety.
CONCLUSIONS: This study provides evidence that the psychometric properties of the C-MOGS are appropriate and emphasizes its positive association with IGD. The C-MOGS is a reliable and valid instrument for mental health workers to assess metacognitions about online gaming in the Chinese population.

UNASSIGNED: Internet Gaming Disorder (IGD), recognized as a mental disorder in both the Diagnostic and Statistical Manual (DSM-5) and International Classification of Diseases (ICD-11), poses significant threats to physical, social, and mental well-being. This study aims to delve into the experiences of individuals grappling with IGD.
UNASSIGNED: The study employed an interpretive phenomenology, conducting interviews with 10 graduate students at Makerere University. Participants were purposefully sampled until data saturation was achieved during interviews, which took place between May and July 2023. An interview guide facilitated data collection (Supplementary File 1), and thematic analysis was manually applied for data interpretation, utilizing intuition and imaginative approaches.
UNASSIGNED: The findings revealed that the majority of participants started gaming during childhood, starting with offline games. Exposure to gadgets and games, idle time, and stress emerged as key triggers for IGD. Participants reported experiencing sleep deficits, deteriorating interpersonal relationships, declining job performance, unhealthy eating habits, academic challenges, and wastage of money and time. The study also identified strategies employed by participants to mitigate their gaming behaviors, such as refraining from purchasing data, seeking support from friends, and uninstalling the game app, although relapses were common.
UNASSIGNED: The study highlights a global pattern of early initiation into gaming, emphasizing the need for early intervention and preventive measures. Factors such as easy accessibility and affordability of gaming platforms, idleness, and stress play significant roles in motivating internet gaming, contributing to a higher prevalence among the studied population. The research underscores the adverse effects of IGD on students, affecting academic performance, interpersonal relationships, and job performance. Notably, participants demonstrate agency in addressing IGD through practical coping strategies, including controlling data access, seeking social support, and uninstalling games. These coping mechanisms provide valuable insights into the complex nature of addressing IGD and form a basis for developing targeted interventions and support systems within the higher education setting in Uganda.

UNASSIGNED: Impaired inhibitory control accompanied by enhanced craving is hallmark of addiction. This study investigated the effects of transcranial direct current stimulation (tDCS) on response inhibition and craving in Internet gaming disorder (IGD). We examined the brain changes after tDCS and their correlation with clinical variables.
UNASSIGNED: Twenty-four males with IGD were allocated randomly to an active or sham tDCS group, and data from 22 participants were included for analysis. Participants self-administered bilateral tDCS over the dorsolateral prefrontal cortex (DLPFC) for 10 sessions. Stop-signal tasks were conducted to measure response inhibition and participants were asked about their cravings for Internet gaming at baseline and post-tDCS. Functional magnetic resonance imaging data were collected at pre- and post-tDCS, and group differences in resting-state functional connectivity (rsFC) changes from the bilateral DLPFC and nucleus accumbens were examined. We explored the relationship between changes in the rsFC and behavioral variables in the active tDCS group.
UNASSIGNED: A significant group-by-time interaction was observed in response inhibition. After tDCS, only the active group showed a decrease in the stop-signal reaction time (SSRT). Although craving decreased, there were no significant group-by-time interactions or group main effects. The anterior cingulate cortex (ACC) showed group differences in post- versus pre-tDCS rsFC from the right DLPFC. The rsFC between the ACC and left middle frontal gyrus was negatively correlated with the SSRT.
UNASSIGNED: Our study provides preliminary evidence that bilateral tDCS over the DLPFC improves inhibitory control and could serve as a therapeutic approach for IGD.

Addictions have recently been classified as substance use disorder (SUD) and behavioral addiction (BA), but the concept of BA is still debatable. Therefore, it is necessary to conduct further neuroscientific research to understand the mechanisms of BA to the same extent as SUD. The present study used machine learning (ML) algorithms to investigate the neuropsychological and neurophysiological aspects of addictions in individuals with internet gaming disorder (IGD) and alcohol use disorder (AUD).
We developed three models for distinguishing individuals with IGD from those with AUD, individuals with IGD from healthy controls (HCs), and individuals with AUD from HCs using ML algorithms, including L1-norm support vector machine, random forest, and L1-norm logistic regression (LR). Three distinct feature sets were used for model training: a unimodal-electroencephalography (EEG) feature set combined with sensor- and source-level feature; a unimodal-neuropsychological feature (NF) set included sex, age, depression, anxiety, impulsivity, and general cognitive function, and a multimodal (EEG + NF) feature set.
The LR model with the multimodal feature set used for the classification of IGD and AUD outperformed the other models (accuracy: 0.712). The important features selected by the model highlighted that the IGD group had differential delta and beta source connectivity between right intrahemispheric regions and distinct sensor-level EEG activities. Among the NFs, sex and age were the important features for good model performance.
Using ML techniques, we demonstrated the neurophysiological and neuropsychological similarities and differences between IGD (a BA) and AUD (a SUD).