Design
This descriptive-analytical and cross-sectional study was conducted between June and August 2018.
Sample and sampling method
The research population consisted of all students who were studying at KUMS in the second semester of 2017–2018 academic years. The criteria for entering the study included; studying at the second semester of 2017–2018 academic year, studying at the second semester or above, willing to participation in the study, and completing the questionnaires fully. Stratified random sampling was performed. To calculate the sample size, the result of Masterz’s study (2015) was used [41], according to which, addiction to Facebook, Twitter and YouTube social networks was 14.2, 33.3, and 47.2, respectively. If we assume that, the prevalence of social networking addiction is about 33.3%, then the sample size will be 340 individuals considering 10% drop out of the samples. Thus, in the present study, in order to increase the stability and accuracy of the results, 360 participants using random sampling method were entered into the study.
Instruments
The study tools included a personal information form and the Bergen Social Media Addiction Scale (BSMAS). The information form had 5 questions about gender, age, educational level, school of study, and Grade Point Average (GPA). BSMAS was designed by Andreassen et al. (2012) at the University of Bergen [42]. The reliability coefficient of this questionnaire has been confirmed by the Cronbach’s Alpha method (alpha = 0.8), [42] and its internal consistency has been calculated to be 0.88 [43]. The psychometric properties of the Persian version of the BSMAS using confirmatory factor analysis and Rasch models on 2676 students by quota sampling, have been reviewed and approved in Iran by reporting the indexes such as X2 = 86.52 (P < 0.001), CFI = 0.993, Average variance extracted = 0.51, and composite reliability = 0.86 [44]. In the present study, the reliability coefficient of the questionnaire for internal consistency was 0.88 using Cronbach’s Alpha method.
BSMAS consists of 18 questions and 6 items, in a way that, each item has 3 questions. The items include; salience [1,2,3], tolerance [4,5,6], mood modification [7,8,9], withdrawal [10,11,12], relapse [13,14,15] and conflict [16,17,18]. Salience refers to our thinking and behavior in using social networks. It means that, the addictive use of social networks is manifested in the form of individual’s dependency on social networks. Tolerance (craving) represents a gradual increase in the use of social networks to gain pleasure. Mood modification represents modifying and improving behavior or mood. In other words, this component suggests that some users use social networks to get rid of unpleasant feelings. Withdrawal is an unpleasant feeling that a person experiences when disconnected from social networks or discovers he or she is forbidden to use social network. Relapse is a failed attempt of a person to control his/her social networking usage. Conflict represents issues that cause tensions in relationships with others, workplace, education, etc. [42, 43].
The questions in this scale are in 5-point Likert scale, including very rarely [1], rarely [2], sometimes [3], often [4] and very often [5], which are scored from 1 to 5, respectively. The minimum score in the Social Networking Scale is 18 and the maximum score in 90. In our study, the average response time to the questionnaire was about 20 min. The questionnaires were distributed in faculties at the end of the classes. The sampling lasted for one month.
In this study, the samples were categorized in one of the following categories according to the score they obtained from the questionnaire: Normal use of social networks (0–19), mild social networking addiction [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35, 43, 45,46,47], moderate social networking addiction (40–69) and severe social networking addiction (70–90), [48]. GPA was used to assess the academic performance of students.
Data collection
At first, the study permission was obtained from the KUMS’s Research Deputy. Then, the researcher attended the Department of Education at the faculties of KUMS, including the faculties of Medicine, Para medicine, Dentistry, Pharmacy, Nursing and Midwifery and Health, and received a list of students from each faculty. The list was numbered and then, based on random number table method, samples were selected. The researcher referred to the students based on their classroom schedule and, if they were interested in participating in the study, invited them to enter the study. If any student did not want to participate in the study, he/she was replaced by the next or pervious person in the list. The objectives of the study were explained to all samples and then the questionnaires were given to them to be complete. The questionnaires were collected after the completion.
Data analysis
Data were analyzed by 18th version of the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL, USA) and two levels of descriptive and inferential statistics. The data normality was first evaluated using Kolmogorov-Smirnov test, which indicated an abnormal distribution of variables of social networking addiction and GPA. Spearman’s correlation coefficient was used to examine the correlation between the social networking and GPA. To compare the social networking addiction scores in terms of nominal qualitative variables (such as sex), the Mann-Whitney U test was used, and in terms of ordinal qualitative variables (such as education level and school) and quantitative variables (such as age and group), Kruskal-Wallis H test was used. p-value of less than 0.05 was considered as significant level.
Ethical consideration
The University’s Ethics Committee approved the study with the code: IR.KUMS.REC.1397.077. The goals of study were explained to the samples and written informed consent was obtained from all of them. Concerning the confidentiality of personal information and responses, reassurance was given to the participants.
Findings
Of the 360 students participating in the study, 199 students (55.3%) were female and the rest were male. The mean age of the participants was 25.48 ± 3.39 years and they were mainly at the age range of between 21 and 30 years old. Also, 46.7% of the students (n=168) were undergraduate and most of them were studying at the faculty of dentistry (n=101, 28.1%), (Table 1).
The mean social networking addiction was 50.83 ± 13.00 out of 90, which was at moderate level. Most of the students had moderate addiction (254 students and 70.6%), (Table 2). The addiction to social networking in the male students was significantly higher than female students (p ≤ 0.01), (with the mean and standard deviation of 52.65 ± 11.50 and 49.35 ± 13.96, respectively). In term of age, the highest and lowest levels of social networking addiction were related to age groups of less than 20 years old and 31 to 40 years old (with the mean of 53.78 ± 14.95 and 50.57 ± 11.45, respectively), which showed no statistically significant difference. Undergraduate and PhD students had the highest and lowest level of addiction, respectively, and did not have statistically significant difference (with the mean and standard deviation of 52.8 ± 12.70 and 48.03 ± 13.95, respectively). In terms of school, the highest and lowest levels of addiction were related to the students of Para medicine and nursing and midwifery schools, respectively (with a mean and standard deviation of 53.49 ± 12.53 and 48.08 ± 13.67, respectively), and this difference was not statistically significant. (Table 1). There was a negative and significant correlation between social networking addiction and academic performance (p ≤ 0.01, r = − 0.210) of the students. Also, there was a negative and significant correlation between all the subscales of social networking addiction and GPA (Table 3).