[Study of the Background Variables of Depression Among Female University Students: The Role of Online Self-Disclosure and Social Media Addiction].

Abstract

Objectives: Mental health of university students has become a public health priority: approximately one quarter of them reported depression. Besides the classic risk factors, more studies are focusing on the phenomena of the digital world. As women are particularly at risk for depression, in the present study, we analyzed depressive symptoms in college girls exploring the role of online self-disclosure and social media addiction.

Methods: Data were collected using a self-reported online questionnaire shared on social networking sites. The study sample consisted of college girls aged 15-30 years (N=237; M= 23.2; SD=2.8 years). Our questionnaire package included the Beck Depression Inventory, the Revised Self-Disclosure Scale, and the Bergen Social Media Addiction Scale. In addition to descriptive statistics and calculations of correlation coefficients, the analysis focused on multivariate linear regression analysis.

Results: In the multivariate analysis, we found that a specific pattern of online self-disclosure in relation to depressive symptoms emerges: in terms of the content shared about themselves, college girls prone to depression tend to be more likely to disclose less (quantity: ß=-0.12, p< 0.05), but deeper/more intimate (depth: ß=0.22, p<0.001), and also more negative (positivity: ß=-0.34, p<0.001) and less honest (honesty: ß=-0.29, p<0.001) information. Social media addiction remained a significant predictor along with online self-disclosure variables, but its role decreased (ß=0.15, p<0.05).

Conclusions: The dangers of self-disclosure on social media platforms should be highlighted in prevention and treatment, especially because people with mental health problems tend to spend a lot of time online, which in many cases they find safer than face-to-face interactions.