In recent years, there has been a notable increase in the popularity of multiplayer online gaming (MOG), attracting significant attention for its potential impact on individuals and communities. While much research has focused on various aspects of MOG, there are gaps in understanding the comprehensive array of both positive and negative consequences associated with it. This research contributes significantly by employing a multi-method approach across three distinct phases. Initially, exploratory factor analysis (EFA) and principal component analysis (PCA) were used to identify four positive and three negative components of multiplayer online gaming effects. In the subsequent phase, diverse regression modeling techniques in machine learning were applied to these components. Notably, both XGBoost and LightGBM algorithms demonstrated the highest accuracy, achieving 75.6% and 77.5% respectively for positive and negative components, surpassing other algorithms used. Finally, an Android-based application was employed for experimental validation, specifically targeting cognitive functions such as reaction time and multitasking. "Results indicated that multiplayer online gamers exhibited quicker visual reflexes (0.393 s) compared to non-gamers (0.525 s) and slightly better multitasking ability (6.033 s vs. 7.067 s). These findings suggest that multiplayer online gaming can positively impact cognitive skills, yet excessive engagement may lead to detrimental effects such as a decline in academic performance. This research aims to analyze the cognitive impacts of multiplayer online gaming by identifying its positive and negative effects, providing valuable insights for future researchers, parents, and gamers to promote informed decision-making and well-being.
