Peers can have a large impact on health behaviour during adolescence. Social network interventions in schools, which involve using influential, or well-connected, students to help change behaviour, are increasingly common and show great potential. However, we still don’t know the best method for choosing ‘peer leaders’ in these social network interventions, especially across different types of behaviour, social structure, and contexts.
This PhD will employ methods from social network analysis and agent-based modelling to compare the effectiveness of a range of strategies for selecting peer leaders in network-based interventions. The project will use data from two large social network interventions with young people aged 13-16 who participated in the A Stop Smoking in Schools Trial (ASSIST) and the Sexually Transmitted Infections and Sexual Health trial (STASH). Advanced computational models, such as stochastic actor-oriented models, will use the empirical data to simulate a wide range of intervention scenarios (e.g., differences in peer leader selection, school size, network structure), assessing how the effectiveness of each strategy differs according to context.
The project findings will help design new social network interventions to improve health and well-being in schools, including addressing issues related to smoking, alcohol use, sexual health, and mental health. The student will receive training in social network analysis methods and agent-based modelling, and will work with the Relationships and Health team in the Social and Public Health Sciences Unit (SPHSU).
First Supervisor: Dr. Emily Long, University of Glasgow