THE INVESTIGATION OF THE RELATIONSHIP BETWEEN MENTAL HEALTH INDICATORS, PROBLEMATIC USAGE OF SOCIAL NETWORKING, AND GENDER IN A SAMPLE OF TRANSYLVANIAN HUNGARIAN STUDENTS
THE INVESTIGATION OF THE RELATIONSHIP BETWEEN MENTAL HEALTH INDICATORS, PROBLEMATIC USAGE OF SOCIAL NETWORKING, AND GENDER IN A SAMPLE OF TRANSYLVANIAN HUNGARIAN STUDENTS

Summary/Abstract: Recent research has documented an increase in loneliness and mental health problems, which are considered to be significant risk factors of mental health malfunctioning. The advent of internet and the vertiginous development of technology have provided a vast palette of opportunities for individuals to virtually reduce social isolation, thus trying to ameliorate feelings of loneliness. However, some persons are driven to use the SNSs (Social Networking Sites) in maladaptive ways, research indicating that the problematic and excessive usage of SNS may have a profound negative effect on the individual’s mental health. The major objectives of our study are: 1) to investigate the possible gender differences in mental health indicators and the proclivity to dysfunctional use the social networks and the internet, and 2) to investigate the relationship between dysfunctional social networking usage and loneliness, depressive symptoms and subjective well-being in a sample of Transylvanian Hungarian students. Our study included 305 Transylvanian Hungarian first and second year students, from Babes-Bolyai University in Cluj-Napoca, Sapientia, Targu-Mures, Romania, assessed on: depression symptoms, loneliness, subjective well-being, and dysfunctional use of social media. Our results indicate that female students have significantly lower levels of subjective well-being than male students and are significantly more drawn to dysfunctional use of social networking for informational purposes. Those students who have moderate/severe levels of depressive symptoms experience significantly higher levels of loneliness, and significantly lower levels of subjective well-being, In the same time, they also engage significantly more in dysfunctional social networking. Finally, the regression analyses indicated that loneliness is the best predictor of both depression and subjective well-being, while dysfunctional use of social networks explaining only a small amount of the variance for both depression and subjective well-being. Our results may be useful in the development of appropriate prevention and intervention programs targeting the optimization of levels of loneliness, thus enhancing the indicators of mental functioning.

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