Identifting the cell phone addiction levels among Ankara Yildirim Beyazit University Medical school students

Introduction and Aim: Smart phone usage is growing fast in parallel to the technological developments, newly developed applications are penetrating all aspects of daily life and are making users addicted. Work is in progress to define the diagnosis of the addiction and its remedy. Current scales can only determine the level of addiction, however diagnosis cannot be made. Purpose of this study was to identify the relationship between the cell phone addiction levels and sociodemographic variables, usage of Internet and social media sites, and other addictive materials among Ankara Yildirim Beyazit University Medical School students. Material and Methods: The 366 study participants were chosen from students enrolled in Medical School of Ankara Yildirim Beyazit University during the academic year of 2015-2016. An information questionnaire accessing the sociodemographic characteristics and a survey containing a smart phone addictiveness scale developed by Kwon, M., and colleagues and further qualified and quality accessed in Turkish by Demirci, K., and his colleagues in 2014 were applied. Data were collected and analyzed using the SPSS for Windows, version 20.0. Differences among groups using qualitative data were investigated using Chi-Square, Student's t, One-Way ANOVA, Mann Withney-U, Spearman correlation analysis, Pearson correlation analysis, Kruskal – Wallis tests. A statistical significance level of p<0,05 was assumed when analyzing the results. Results: 366 student smart phone users articipated in our study. The sampling group included 207 female (% 56,6), and 159 male (%43,4) students. Smart phone addiction levels were 80,96; 81,55 and 80,18, repectively, for the whole group, only female and only male students, respectively. Level seems to be high for females but proves to be statistically insignificant (p=0,.57). A negative correlation existed between addiction score and age but again proved to be statistically insignificant (Pearson correlation, p=0,529 r= -0,03). In terms of usage purpose, the addiction levels of those preferring internet surfing (p<0,01), social media participation (p=0,01), and camera usage (p=0,03) were above the average in a statistically significant manner. Among the social media sites, the addiction levels of those using Twitter were higher than the other two well-known sites (statistical significance level of p =0,01). No statistical correlation was found between smart phone addiction and using cigarettes or alcohol with corresponding p=0,407 and p=0,559, respectively. Addiction level was 64.19 for Windows smart phone users which statistically lower than the average (p=0,003). There is a small degree of negative correlation between the age of owning a first cell phone and smart phone addiction level but with an insignificant statistical correlation (r=-0,001, p=0,98). Conclusion: Addiction levels determined by the existing smart phone addiction scales demonstrate discrepancies based on the usage levels of different countries. This study revealed levels of smart phone addiction for our sample set, however, to make a diagnostic, a threshold value needs to be defined. These scales need to be developed further by participation from users. The statistically significant correlation between internet surfing and social media interactions suggestsevaluation of these two addictions as a single entity in future. Based on these results, battle against addiction should target the severance of ties with virtual media and establishment of new in-person relationships by direct assistance and collaboration of family medicine practitioners, other healthcare workers, social media and internet organizations, GSM (Global System for Mobile) companies, civil society organizations, and volunteers. Keywords: Smart phone, Addiction, Mobile phones, Family Medicine