ANADOLU PSIKIYATRI DERGISI-ANATOLIAN JOURNAL OF PSYCHIATRY, cilt.19, ss.383-389, 2018 (SCI İndekslerine Giren Dergi)
Objective: The aim of this study is determine to university students' Internet addiction, Internet use behavior and change during university life. Methods: The study was conducted on students who were studying at Erciyes University between the years 2013 and 2016. A medical (pharmacy), a social (theology) and a science (computer engineering) programs has been chosen to represent the university student profile. The Internet Dependency Scale (SCL) was used to determine internet addiction. Normal distribution fitness of the data was tested by the Shapiro-Wilk test. The Mann-Whitney U test, unpaired t test, and Pearson chi-square test was used. Results: The number of students who think that they are addicted to internet has increased about two fold during university life. Despite the fact that no student is in the dependent category according to the IA score, the number of students with limited symptoms decreased about three fold over the years. Time spent in the face of the TV decreased for the years, 1.27 +/- 1.32, 0.85 +/- 1.20 hours between 2013 and 2016, respectively. However, the use of the daily internet has increased over time, 2.27 +/- 1.75 and 2.94 +/- 1.84 hours for the years 2013 and 2016, respectively. The first three lines of internet using purpose are social media, watching video and surfing on internet. Over the years, social media, which remark most attention to the changes in students' internet use, has increased from 39.3% to 61.6%. Conclusion: Despite the increase in students' access, internet and internet use time their university life, their rate of addiction was decreased. This study suggests that students use internet more intensively with their level of education increases but use more consciously. None of student was internet addiction, this may be due to fact that using this scale is inadequate to determine internet addiction. The use of more comprehensive methods to identify addicted individuals, particularly those with limited symptoms with clinical observation can guide treatment planning with clearer outcomes.