Title: How Much is Too Much? Leveraging Existing and Emerging Large-Scale Social Data to Build Robust Evidence-Based Policy for Children in the Digital Age
Funder: Economic and Social Research Council

Abstract: There is a wide gap between what is scientifically known about the effects of digital technologies on children and young people, and the policies being proposed to address their perceived risks. This programme will capitalise on ESRC data resources to build a more nuanced and transparent empirical understanding of the impacts of digital technologies (including social media, video games, and smartphones) on young people, in line with three objectives: Objective 1. Identify Risk and Resilience Factors: We will investigate the child-, family-, and community-level risk and resilience factors predisposing adolescents to experiencing negative effects on their psychological well-being as a result of technology engagement. Objective 2. Examine Directionality of Effects: We will model the extent to which the links between digital technology engagement and psychological well-being are reciprocal, cumulative, and mediated by the risk and resilience factors identified. Objective 3. Highlight Interventions to Stakeholders: We will propose and evaluate the potential causal pathways linking risk factors, digital technology and psychological well-being, in order to better inform future health and policy interventions aimed at promoting child and adolescent well-being. To address these goals, we will work to fundamentally improve how ESRC data resources are used by combining innovative and replicable research methods with cutting-edge data analytic approaches. We will: (1) Systematically review ESRC data resources and build on our existing contacts with the teams running these studies to identify novel kinds of behavioural trace, geographic, and economic data; (2) Apply machine learning, longitudinal methods, and causal inference techniques to identify risk and resilience factors that influence technology engagement effects; and (3) Broadly disseminate our findings to policy, charity, and industry stakeholders. We will make full use of key ESRC data resources on the UK Data Service, including Understanding Society, the Millennium Cohort Study, and the second Longitudinal Study of Young People in England. These feature converging and largely harmonised measures of digital technology engagement and well-being. We will integrate these data (combined with other public / controlled data) into our hypothesis generation and testing process, creating reproducible and extensible R markdown workflows to merge the datasets into a single, powerful and open resource of high-quality data on technology engagement. We will then apply this workflow to probe the data using innovative statistical approaches including Specification Curve Analysis (SCA), Random-Intercepts Cross Panel Modelling (RI-CPM), and penalised regression techniques. This will enable us to determine the effects of digital technologies on young people, highlighting plausible directions, risk factors, data patterns, and effect sizes from the bottom up. Instead of a single analysis, we will map out and simultaneously evaluate the tens of thousands of decisions a data analyst could make when approaching the question of technology effects. The resulting scientific evidence should provide an important and unique resource for those interested in digital technology effects, identifying possible directional relationships, and which adolescents might be most affected. We will disseminate our findings to our established network of national and international stakeholders, setting new rigorous standards for policy-ready, evidence-based decision making in the digital space. Our workflows will be openly accessible, allowing others to extend our work. We will thereby empower the academic, policy, charity, and industrial sectors to make the most of the ESRC's data resources, and set a strong foundation for future work concerning the rapidly developing technologies (including augmented reality and AI) which are increasingly integral to childhood today.

Lay abstract: The amount of time British children and adolescents spend on digital technologies has more than doubled in the past decade, and debates about the possible impact of excessive screen use are prominent in the scientific and policy arenas, as well as in the public press. The UK House of Commons, DCMS, and Science and Technology Select Committees, the Royal Society for Paediatrics and Child Health, and the UK's Chief Medical Officer have recently investigated whether the Internet, smartphones, digital games, and social media influence the health of children and young people. These initiatives, however, have all acknowledged the lack of scientific knowledge in this area-which stymies the efforts of UK policy makers to craft effective advice, regulations, and interventions. This project aims-for the first time-to use existing ESRC datasets to generate the science required to ground policy in this area. We aim to provide policy-makers, parents, teachers, and GPs with the evidence required to understand the role digital technologies play in the lives of British children, and to highlight potential risk and resilience factors that could be the focus of future interventions. We will use ESRC data assets, advanced statistical approaches, and robust open science methodologies to answer three pressing research questions: 1. What risk and resilience factors predispose adolescents to experiencing an effect of digital technology use on their psychological well-being? 2. What are the directional links between digital technology use and psychological well-being, and do the risk factors identified play a mediating role in this? 3. What are the causal pathways linking risk factors, digital technology use and psychological well-being that can inform future intervention? Answers to these questions are currently elusive, due to the poor data quality and methodological shortcomings that restrain research on technology effects. We will leverage our extensive experience working with large-scale social datasets to examine the general effects of digital technologies and more technology-specific effects (e.g. social media and gaming). We will use machine learning, network modelling, and advanced longitudinal approaches to pinpoint potential risk and resilience factors (e.g. social support, economic deprivation) that alter children's reactions to digital technologies, and which could help guide future technology policy. This will create different profiles of children that we can use to investigate the uses and effects of digital technologies over the longer-term-determining which possible technology effects (e.g. social isolation) are currently unevidenced and over-hyped, and which (e.g. poor sleep) deserve a closer look. We will thoroughly document our methodology and publish each detailed analysis behind our findings. This transparency is almost entirely missing from the current scientific and policy debate. Making our code freely available will enable other research teams in academia, the charity sector and government to build directly on our work, facilitating a new kind of incremental knowledge transfer which has hitherto been missing, and providing a template for empowering all sectors, including charities, to make more regular use of ESRC data. Crucially, this work will inform how our team continues to advise draft guidance under development at the UK Ministry of Health, ongoing deliberations at the UK Council of Internet Safety, UNICEF, OECD, social enterprises like the ParentZone, and children's charities including Barnardo's-with whom we already have a strong relationship. Our work will also provide a lens to understand the effects of novel technologies such as VR and AI, which will soon be measured by ESRC data. While VR and AI are still under the radar of most academic and policy debate, they will increasingly enter the discourse in coming years.

Research activity codes: 1.2 PSYCHOLOGICAL AND SOCIOECONOMIC PROCESSES;2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS
Health categories: MENTAL HEALTH