Background: Nicotine dependence and internet addiction are two important problems among university student.
Aims: We aimed to determine the prevalence of ND and IA among the university students, and to investigate the parameters that affect these clinical problems.
Study design: This study is designed as a descriptive, cross-sectional, epidemiological study.
Methods: The academicians of Department of Family Medicine formed a questionnaire (9 questions). Turkish versions of Young’s Internet Addiction Test (YIAT) and Fagerstrom Test for Nicotine Dependence (FTND) were used as data collection tools. Sample volume was calculated as 1632 students, and a total of 1816 students were randomly selected. In classes, cafes and social fields we spoke to the students and informed them about the study. Voluntaries were requested to answer the questions in the questionnaire and fill the scales.
Results: Mean age of the participants was 21.45±2.58 years (range 18-35 years), and 908 (50%) were male. The mean FTND score was 1.18±2.27 (range 0-10). Of the participants, 24.2% were moderate, high or very high nicotine dependent. Binary logistic regression analysis showed that the gender (p=0.000), place of residence (p=0.000), monthly intake (p=0.023) and presence of symptoms of IA (p=0.000) were independent risk factors for smoking. The mean YIAT score was 40.30±14.95 (range 20-100). Of the participants 76% were users without symptom, 19.6% were users with limited symptoms and 4.4% were pathologic internet users. Binary logistic regression analysis showed that gender (0.004), smoking (p=0.001) and the device used for internet connection (p=0.008) are independent risk factors for presence of symptoms of IA. The FTND score was significantly correlated with the YIAT score (Pearson correlation coefficient=0.164, p=0.000).
Conclusion: Our results indicate that the prevalence of ND and IA are high among the university students. Also, there is a significant relation between ND and IA. Male gender, living in home alone and a higher monthly income are significant risk factors. The educational and preventive activities should take these risk factors into account.