Abstract

This thesis explores the intricate relationship between gaming behaviors and their impact on anxiety levels and life satisfaction among gamers. Utilizing a dataset from Kaggle comprising 13,465 participants and 55 variables, the study employs both logistic and probabilistic regression analyses to examine how various demographic, behavioral, and sociocultural factors influence mental health outcomes in gamers. The regression models identify significant predictors for different anxiety and satisfaction with life classes, highlighting the roles of factors like gender, employment status, reason for playing, and gaming hours.

The findings underscore the pervasive nature of anxiety and its negative impact on life satisfaction. High levels of anxiety often overshadow positive experiences, leading to diminished well-being. The study also highlights the importance of focusing on interventions based on which factors have the most significant effect on these mental health concerns under study, suggesting that strategies to reduce anxiety and enhance life satisfaction should consider demographic differences and specific gaming behaviors. Despite the reliance on self-reported data and potential sample biases, the research provides valuable insights for developing targeted mental health interventions for the gaming community.