This seminar focused on how longitudinal data can be used to investigate young people’s social media use.
Dr Amy Orben is College Research Fellow at Emmanuel College and the MRC Cognition and Brain Sciences Unit. Her work using large-scale datasets to investigate social media use and teenage mental health has been published in a range of leading scientific journals. The results have put into question many long-held assumptions about the potential risks and benefits of ’screen time’. Alongside her research, Amy campaigns for the use of improved statistical methodology in the behavioural sciences and the adoption of more transparent and open scientific practices, having co-founded the global ReproducibiliTea initiative. Amy also regularly contributes to both media and policy debate.
Using Longitudinal Data to Disentangle the Association Between Teenage Tech Use and Well-Being
While the concerns about adolescent social media use and its effect on life satisfaction are rising, scientific evidence in the area is still surprisingly sparse: with most studies being cross-sectional and unable to dissociate between-person associations and individual longitudinal relations. While comparisons of different people simultaneously are inherently different from examinations of the same person longitudinally, many previous studies erroneously interpret the former as the latter. Disentangling these estimates, we use Understanding Society panel data to examine the relationships between social media use and life satisfaction. Implementing Specification Curve Analysis and Random Intercept Cross-lagged Panel Models, we show a negative median cross-sectional association between social media use and life satisfaction. The individual longitudinal relationships are also negative, but so small they merit little consideration. It is however in evidence that gender is a substantial and important determinant of the link between social media use and well-being. For adolescent boys there is little evidence for cross-sectional relations, or longitudinal effects. For adolescent girls, however, increases in life satisfaction predicts lower social media use one year later and increases in social media use also predicts lower life satisfaction one year later. We further investigate these sex differences using non-linear modelling approaches on data from the UK Millennium Cohort Study.