Comparison of Social Interactions between Student Athletes and Students Active in Electronic Games
محورهای موضوعی : Sport management
1 - Department of Sports Management, Da.C., Islamic Azad University, Damghan, Iran
کلید واژه: Bojnord, Computer games, Social interaction, Traditional sports,
چکیده مقاله :
The aim of this study was to compare social interactions between student athletes and students active in computer games. This research is applied in terms of purpose and descriptive-comparative in nature, conducted in the field using a questionnaire. The statistical population included all male high school students (second level) in the city of Bojnord. Since the exact size of the population was not known, the sample size was estimated at 210—70 individuals in each group—using G*Power software, and convenience sampling was employed. The tool used for data collection was the standardized Social Interaction Questionnaire by Lee and Robinson (1998). To analyze the statistical data, descriptive statistics and inferential statistics, including the Kolmogorov–Smirnov test, one-sample t-test, ANOVA, and Tukey’s post hoc test, were conducted using SPSS version 26. The results of the one-sample t-test indicated that the social interaction status of adolescents active in traditional sports, electronic sports, and the control group was favorable. Moreover, the results of the ANOVA test showed that there is a significant difference in the variable of social interactions among the three groups: adolescents active in traditional sports, adolescents active in electronic sports, and the control group.
The aim of this study was to compare social interactions between student athletes and students active in computer games. This research is applied in terms of purpose and descriptive-comparative in nature, conducted in the field using a questionnaire. The statistical population included all male high school students (second level) in the city of Bojnord. Since the exact size of the population was not known, the sample size was estimated at 210—70 individuals in each group—using G*Power software, and convenience sampling was employed. The tool used for data collection was the standardized Social Interaction Questionnaire by Lee and Robinson (1998). To analyze the statistical data, descriptive statistics and inferential statistics, including the Kolmogorov–Smirnov test, one-sample t-test, ANOVA, and Tukey’s post hoc test, were conducted using SPSS version 26. The results of the one-sample t-test indicated that the social interaction status of adolescents active in traditional sports, electronic sports, and the control group was favorable. Moreover, the results of the ANOVA test showed that there is a significant difference in the variable of social interactions among the three groups: adolescents active in traditional sports, adolescents active in electronic sports, and the control group.
Jenny SE, Manning RD, Keiper MC, Olrich TW (2017) Virtual (ly) athletes: where eSports fit within the definition of “Sport”. Quest. 69(1), 1-18.
Kari T, Karhulahti VM (2016) Do e-athletes move?: a study on training and physical exercise in elite e-sports. International Journal of Gaming and Computer-Mediated Simulations (IJGCMS). 8(4), 53-66.
Nahavandi Erfan (2021) A Comparative Study of Managerial Problem-Solving Skills in E-Sports Players and Other Athletes. Master’s Thesis, Allameh Tabataba’i University
Pluhar E, McCracken C, Griffith KL, Christino MA, Sugimoto D, Meehan WP (2019) Team sport athletes may be less likely to suffer anxiety or depression than individual sport athletes. Journal of Sports Science & Medicine. 18(3), 490.
Raeisoon M, Mohammadi Y, Bijari B, Mogharrab M (2012) Comparison of mental health in athletic and non-athletic male students in Birjand payam-e-noor University (2010-2011). Modern care, Scientific Quarterly of Birjand Nursing and Midwifery Faculty. 9, 310-316.
Sheehan RB, Herring MP, Campbell MJ (2018) Associations between motivation and mental health in sport: A test of the hierarchical model of intrinsic and extrinsic motivation. Frontiers in Psychology. 9, 707.
Soares AKS, Goedert MCF, Vargas AF (2022) Mental health and social connectedness during the COVID-19 pandemic: An analysis of sports and e-sports players. Frontiers in Psychology. 13, 802653.
Taylor T L (2021) Raising the Stakes: E-sports and the Professionalization of Computer Gaming. MIT Pres.pp. 23-25.
Wu YJ, Chen CW, Wu YJ, Sun R (2021) The relations of social support and social connectedness to well-being during the COVID-19 pandemic: cross-cultural generalizability across 49 countries.
Zwibel H, DiFrancisco-Donoghue J, DeFeo A, Yao S (2019) An osteopathic physician's approach to the Esports athlete. Journal of Osteopathic Medicine. 119(11), 756-762.
