Internet, smartphone addiction and associatedfactors in adolescents

Objective: In the study, it was aimed to determine the frequency of internet and smartphone addiction and to determine the factors associated with addiction among adolescents studying in 9-10-11th grade adolescents in Şehzadeler District of Manisa Province. Materials and Methods: The cross-sectional study was conducted among 9th, 10th and 11th grade students of a central district in Manisa between 21.02.2023 and 14.03.2023. 700 students, including 227 9th grade, 215 10th grade and 258 11th grade students, participated in the research. The dependent variables of the study are internet addiction and smartphone addiction. Internet Addiction Test (IAT) was used to evaluate internet addiction, those with a score of ≥50 were defined as an internet addict, and those with a score of ≤49 were defined as the average user. Smartphone Addiction Scale-Short Version (SAS-SV) was used for smartphone addiction, and those with a score of ≥29.5 were considered to have "smartphone addiction". The independent variables are; sociodemographic and lifestyle characteristics of adolescents; smartphone usage features; internet usage characteristics, U.C.L.A Loneliness Scale-Short Form, Social Anxiety Scale for Adolescents (SAS-A), The Center for Epidemiological Studies Depression Scale for Children. The data were analyzed using the SPSS 23.0 statistical program. Descriptive statistics were evaluated by number, percentage, mean ± sd, median (min-max). Student t test was used for univariate continuous data and Chi-Square test was used for categorical data. Logistic regression analysis was used in multivariate analysis. The critical type 1 error value was accepted as <0.05. Results: The mean age of 700 adolescents participating in the study was 15.9 ± 0.9 years. The mean age of starting to use the Internet and smartphone is 10.5 ± 2.8 and 12.1 ± 2.2, respectively. 22.7% of the research group (20.4% risky users, 2.3% addicted) are internet addicts. Smartphone addiction is present in 51.2% of the participants who have a smartphone. The average daily screen time is 4.3 ± 2.9 hours. According to the latest model of logistic regression; The risk of internet addiction increases 3.2 times (95%CI 1.4-7.4) in adolescents studying in private school, 2.5 times (95%CI 1.02-6.5) those who evaluate their health as very bad / bad, 1.6 times (95%CI 1.06-2.5) those who sleep after 00:00, 2.1 times (95%CI 1.3-3.4) those who don't do leisure time activities, 2.0 times (95%CI 1.08-3.8) those who talk to their friends in virtual environment, 1.9 times (95%CI 1.2-3.0) those who do not receive training on the correct use of smartphones or the internet and 3.9 times (95%CI 2.4-6.2) adolescents who are phone addicted. Each one-unit increase in the Social Anxiety Scale for Adolescents total score also increases the risk of internet addiction 1.02 (95%CI 1.005-1.03) times. According to the latest logistic regression model on smartphone addiction; adolescents with internet addiction were found to be addicted to smartphones 4.0 (95%CI 2.5-6.4) times more than those who were not. Each unit increase in The Center for Epidemiological Studies Depression Scale for Children total score increases the risk of smartphone addiction 1.03 (95%CI 1.01-1.04) times. Conclusion: In our study, it was determined that almost one out of every four adolescents is an internet addict, and one out of every two adolescents is a smartphone addict. Situations that increase the risk of smartphone addiction are internet addiction and depression. Situations that increase the risk of internet addiction are smartphone addiction, studying in private school, poor perceived health levels, sleeping after 00.00 at night, not doing leisure time activities, meeting with friends more in virtual environment, high social anxiety, lack of training in the correct use of the smartphone/ internet. The two addictions accompany each other and increase each other's risks. On the other hand, one of the most risky situations is studying in a private school; private schools should be given priority in the measures to be taken. Measures should be taken to increase sleep hygiene, such as ensuring that adolescents do not use smartphones before sleeping, and student clubs and branches, etc., should be made more active in order to enable them to acquire hobbies in real life. In addition, studies should be carried out with the contribution of guidance and classroom teachers in order to cope with the anxiety and depression of adolescents. Finally, giving seminars at schools about the correct use of technology can contribute to the struggle.