Abstract
According to the Uses and Gratifications theory and Transformation Framework, social media users are drawn to different platforms according to platform affordances and motivations for use, with potential implications for wellbeing and functional outcomes. However, most research uses single- or cross-platform data. We tested the hypothesis, therefore, that the use of different social media platforms differentially predicts outcomes. Using undergraduate survey data (n = 3500+) regression analyses explored associations between time spent on eight common platforms and perceived stress and GPA scores. Platforms were also rated on design features using the Transformation Framework in order to identify potential affordance-outcome links. Our hypothesis was supported: platforms showed differential patterns of association (positive and negative) with stress and GPA, with little overlap in patterns of association with the two outcome variables. These findings suggest platforms should not be treated as a homogenous phenomenon, and implicate independent mechanisms underlying social media, wellbeing and attainment links.
Acknowledgements
The authors would like to thank Dr Michael Eisen and Dr James Hanley for comments on the manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
Data not available due to ethical restrictions.
Additional information
Funding
Notes on contributors
Marc S. Tibber
Marc Tibber is a Clinical Psychologist and Lecturer in Clinical Psychology at UCL specialising in young people’s mental health. His recent work has focused on the role of interpersonal/social processes in mental health (including social media communication), and how issues of connection and disconnection affect individuals and communities.
Minglei Wang
Minglei Wang is a doctoral student in journalism and communication at the College of Media and International Culture of Zhejiang University. Her current research interests include social comparison, data quality of ecological momentary assessment, and E-sports.
Chan Zhang
Chan Zhang is an assistant professor at the College of Media and International Culture at Zhejiang University, China. Her expertise is in the measurement errors of online data collection. She received a Ph.D. in Survey Methodology from the University of Michigan.