The Prediction Dependency on Virtual Social Networks Based on Alexithymia, Attachment Styles, Well-Being Psychological and Loneliness

Introduction: Virtual social networks like others type of addiction can be affected by psychological, developmental, and emotional problems. So, the aim of this research is to The purpose of this study was to investigate prediction dependency on virtual social networks based on alexithymia, attachment styles, well-being psychological and loneliness. The research design was a two-group diagnostic function.  Methods: The statistical population consisted of all all the female students’ high school (125110 students) in Tehran city in the year academic 2018-2019 constituted the research population. We obtained data from 100 normal students and 100 students’ dependency on virtual social networks completed addiction to social networks questionnaire of mobile scale, Toronto alexithymia scale, adult attachment scale, psychological well-being scale, and loneliness scale were used for data collection in this study. The obtained data were analyzed by the discriminant analysis method by SPSS-24.  Results: The results of the analysis showed that alexithymia, attachment styles, well-being psychological and loneliness can help to prediction dependency on virtual social networks and function discriminant analysis assigned 77/5 percent of the normal female students and students with dependency on virtual social networks.  Conclusions: Based on the results of the present study, the predictive variable is an important step in identifying the factors that are effective in dependency on virtual social networks. Therefore, the results study can be useful for the design and development of dependency on virtual social network prevention programs.