Technology addictions and related factors in university students

Aim: In this study, it was aimed to determine the extent of technology dependencies and its relationship with sociodemographic characteristics, opportunities and age of using related technologies in Düzce university students. Materials and Methods: The population of the study consisted of 13925 people studying at the central campus of Duzce University for 4 years. In this cross-sectional study, the sample size was calculated as 1304. Each faculty was accepted as a stratified and stratified sampling method was used. Based on the population / sample ratio, the sample size was calculated as approximately one in 10 people and 1465 students were included in the study. In the data collection, a questionnaire consisting of 67 questions was shown to be valid and reliable and internet, smartphone, social media and digital game scales were used. The relationship between the scores obtained from the scales and the factors such as sociodemographic characteristics, opportunities and age of using related technologies were examined. SPSS package program was used for data analysis, Mann-Whitney U and Kruskal-Wallis tests and Spearman Correlation and Multiple Regression analyzes were performed. P <0.05 was considered significant. Results: Of the 1465 students participating in the research, 56.9% were women and 43.1% were men. In the study, pun means of scales; 28,07 ± 8,46 in internet addiction, 26,59 ± 11 in smartphone addiction, 50,75 ± 14,34 in social media addiction and 13,41 ± 6,87 in digital game addiction. The mean scores on the scales were higher in males in internet and digital game addictions, and females in smartphone and social media addictions. The average smartphone and social media addiction scores were found to be low in the individuals who stated that they regularly do sports, and the average scores were lower in all four addictive types in those who perceived their health status and academic success as good. Internet, smart phone and social media addiction scores averages were higher in those who use the internet for surfing, while the average of smart phone and social media addiction scores were lower in those who use the internet for surfing purposes. Four types of addiction were more common among those who met the internet at an early age, and the average of smartphone addiction iv was higher in those who met mobile phones and smartphones at an early age, and the game addiction points were higher in those who used computers at an early age. There is a strong correlation (0,694; 0,662; 0,730) between internet, smartphone and social media addiction, and a weak correlation between digital game addiction and other addictions (0,359; 0,255; 0,270). Conclusion: The mean score of internet addiction in the university was higher than the literature. Technological dependencies reduce students' academic achievement. The fact that students start using computers and phones and play digital games at an early age increases the risk of addiction. Prevention policies can be developed by conducting studies to determine the prevalence and risk factors of technological dependencies.