Background: Increasing adolescent engagement in video game use and its associations with public health outcomes has been a controversial topic over the last several decades, with studies conducted in the United States only managing to produce contradictory results. This dissertation explores the statistical associations between video game use in adolescents and various physical, mental and social health outcomes as they develop into adulthood in the United States.
Methodology: Secondary data analysis was conducted, guided by Life Course Theory, utilizing publicly available data from the National Longitudinal Study of Adolescent to Adult Health.
Results: Video game use during adolescence was significantly associated with the risk for development of metabolic syndrome in adulthood (p =.034). No significant association was found between video game use at any time point and increased measures of violence and aggression. A significant association was found between weekly hours of video game use and sleep problems (p = .002), depression (p = .006), anxiety / panic attacks (p = .021), and marijuana use (p = .001). No significant association was found between video game use and ADHD/ADD and drug use excluding marijuana.
Conclusion: This dissertation highlights several risks and benefits associated with engaging in video game use. These findings help to inform future public health practice and research. In moderation video game use was shown to have prosocial and positive effects on youth development as they grow into adulthood. However, when video game use exceeded 30 hours or more per week, detrimental effects began to emerge, including an increased risk for the development of metabolic syndrome, sleep problems, depression, anxiety, and marijuana use. Demographic variables such as gender and race / ethnicity and Life Course Theory variables of education and marital status were shown to have greater associations across all health outcomes than video game use at any time point. Recommendations for future research on the topic are discussed, including further investigation of the more significant findings and replication of the statistical analyses using Add Health wave V data once available
