Social media's rapidly expanding influence has transformed modern communication paradigms and reshaped user experiences, bringing particular repercussions for psychological well-being. Against this backdrop, the psychological impact of social media usage, especially among female users, is emerging as a significant area of both academic interest and societal concern. Grounded in the Media System Dependency (MSD) theory, this study delved into the complex dynamics of users' dependence on social media. Within this theoretical framework, three primary dependency dimensions—understanding, orientation, and play—were identified. These were further delineated across personal and societal dimensions, yielding six distinct dependency factors: Self-understanding (SeU), Social Understanding (SoU), Action Orientation (AO), Interaction Orientation (IO), Solitary Play (SiP), and Social Play (ScP). The primary aim of this research was to discern the impact of these dependency relations on media-induced anxiety. To achieve this, a meticulously designed cross-sectional study was conducted, surveying 400 female users of Weibo, a leading social media platform. By employing the robust PLS-SEM methodology for data analysis, the study formulated and tested a set of hypotheses. The empirical findings clearly demonstrated that dependency relations significantly influence media anxiety. This research not only enriches the academic discourse on MSD in varied digital contexts but also sheds light on the intricate relationship between media dependency and the mental well-being of female Weibo users.
Ball-Rokeach, S. J. (1985). The origins of individual media-system dependency: A sociological framework. Communication research, 12(4), 485-510.
Ball-Rokeach, S. J., & DeFleur, M. L. (1976). A dependency model of mass-media effects. Communication research, 3(1), 3-21.
Ball-Rokeach, S. J., Power, G. J., Guthrie, K. K., & Waring, H. R. (1990). Value-framing abortion in the United States: An application of media system dependency theory. International Journal of Public Opinion Research, 2(3), 249-273.
Ball-Rokeach, S. J., Rokeach, M., & Grube, J. (1984). The Great American Values Test: Influencing Behavior and Belief through Television. The Free Press, New York.
Bekker, H. L., Legare, F., Stacey, D., O'Connor, A., & Lemyre, L. (2003). Is anxiety a suitable measure of decision aid effectiveness: a systematic review? Patient education and counseling, 50(3), 255-262.
Cheng, Y., Liang, J., & Leung, L. (2015). Social network service use on mobile devices: An examination of gratifications, civic attitudes and civic engagement in China. New Media & Society, 17(7), 1096-1116.
Conway, J. C., & Rubin, A. M. (1991). Psychological predictors of television viewing motivation. Communication research, 18(4), 443-463.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388.
Guo, M. (2021). Influence of Female Media Information on Female Media Use Anxiety: Take a Survey of Weibo Users on Social Media as an Example. ICA 2019: Procedings of the 1st ICA Regional Conference, ICA 2019, October 16-17 2019, Bali, Indonesia,
Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N., Shablack, H., Jonides, J., & Ybarra, O. (2013). Facebook use predicts declines in subjective well-being in young adults. PLoS ONE, 8(8), e69841.
Lin, C. A. (1993). Modeling the gratification?seeking process of television viewing. Human Communication Research, 20(2), 224-244.
Loges, W. E. (1994). Canaries in the coal mine: Perceptions of threat and media system dependency relations. Communication research, 21(1), 5-23.
Lowrey, W. (2004). Media dependency during a large-scale social disruption: The case of September 11. Mass communication & society, 7(3), 339-357.
McCord, B., Rodebaugh, T. L., & Levinson, C. A. (2014). Facebook: Social uses and anxiety. Computers in Human Behavior, 34, 23-27.
Osatuyi, B. (2015). Personality traits and information privacy concern on social media platforms. Journal of Computer Information Systems, 55(4), 11-19.
Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among US young adults. Computers in Human Behavior, 69, 1-9.
Smith, A., & Anderson, M. (2018). Social media use in 2018. Pew research center. https://policycommons.net/artifacts/617452/social-media-use-in-2018/1598263/
Sumter, S. R., Cingel, D. P., & Antonis, D. (2018). “To be able to change, you have to take risks# fitspo”: Exploring correlates of fitspirational social media use among young women. Telematics and Informatics, 35(5), 1166-1175.
Svennevig, M. (2000). Needs, not nerds: researching technological change. International Journal of Advertising, 19(5), 645-663.
Twenge, J. M., & Campbell, W. K. (2018). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 12, 271-283.
