Digital Game Addiction

Harmful use of digital technologies is increasing among different age groups in society, especially children. Therefore, it is important to pay attention to this issue and educate families to empower them to deal with this issue properly. This study was conducted to investigate the effect of family education on digital game addiction. The method of the present study was quasi-experimental with pre-test-post-test design and witness group. The statistical population of this study included male students of the fourth and fifth grades of Farid School in Ramsar city in the academic year of 2019-2020. Those had a cut point above 90 in Videogame Addiction Scale for Children (VASC) were selected and randomly assigned to experimental (n = 20) and witness (n = 20) groups. First, in the pre-test stage, the Videogame Addiction Scale for Children (Yilmatz, Griffiths, & Ken, 2017) was performed on both groups. The experimental group then takes a family education course. At the end of the training period, post-test was performed again in both groups and the data were analyzed using analysis of covariance and SPSS software version 24. The results showed that the mean of digital game addiction and its components in the experimental group decreased significantly compared to the control group (p <0.05). According to the findings, it can be concluded that family education is effective in reducing addiction to digital games. Therefore, designing and implementing training courses for families can be helpful in reducing their children's harmful use of such new electronic technologies.

Aim: The growing prevalence of digital games and their potential impact on mental health highlight the need to identify protective mechanisms against possible negative effects. The present study aimed to investigate the role of parental phubbing and ego-resilience in adolescents’ tendency toward digital game addiction: a neural network approach. Method: This research employed a descriptive-correlational design. The statistical population included all male high school students (second cycle) in public schools of Karaj during the 2024 academic year. A total of 300 students were selected using a cluster random sampling method and completed the Digital Game Addiction Scale by Başol et al. (2018), the Parental Phubbing Scale by Ding et al. (2020), and the Ego-Resilience Scale by Block and Kremen (1996). The collected data were analyzed through an artificial neural network using the multilayer perceptron (MLP) approach in SPSS version 26. Results: The findings indicated that parental phubbing and ego-resilience significantly contributed to predicting digital game addiction among adolescents (p< 0.01). Neural network analysis revealed that parental phubbing positively predicted digital game addiction, whereas ego-resilience negatively predicted it. Parental phubbing emerged as the strongest predictor (100%), while ego-resilience served as a protective factor (57.8%). Moreover, the artificial neural network model accurately captured the trends and variations of digital game addiction based on these variables. Conclusion: The results demonstrated that parental phubbing and ego-resilience are critical factors in explaining adolescents’ digital game addiction. Moreover, the artificial neural network model showed high accuracy in predicting the intensity and course of this addiction.