Social Statistics Seminar - 3 May 2022
|Starts:||16:00 3 May 2022|
|Ends:||17:00 3 May 2022|
|What is it:||Seminar|
|Organiser:||School of Social Sciences|
|Who is it for:||University staff, External researchers, Adults, Alumni, Current University students|
Social Statistics Seminars 2021/22 – May Session
Integrating and evaluating social network and systems approaches in health interventions
Kayla de la Haye (University of Southern California)
Join us at 4pm (BST) on 3 May 2022!
Registration link: http://bit.ly/socialstats0522
Please register using your full name and your email address.
- Eating and physical activity habits are a major cause of non-communicable diseases and are strongly influenced by social networks and social-ecological contexts; factors that are insufficiently addressed in many interventions.
- Multi-level interventions can integrate components that effectively leverage or alter social networks of family, friends, peers, and community stakeholders to change eating and activity habits and improve health outcomes.
- Innovations in network and data science methods, big data, and transdisciplinary team science is important to advancing and evaluating this work.
About the speaker
Dr. de la Haye works to promote health and prevent disease by applying social network analysis and systems science to key public health issues. Her research focuses on family and community social networks to promote healthy eating, nutrition security, and prevent non-communicable diseases like obesity. She also explores the role of social networks in how families, teams, and coalitions solve complex problems. She serves on the Board of Directors of the International Network of Social Network Analysis (INSNA), and in 2018, she received the INSNA Freeman Award for significant contributions to the study of social structure. She holds a PhD in psychology from the University of Adelaide, Australia.
For regular updates on our events, sign up to our seminar mailing list on JiscMail: bit.ly/socialstatslist
Travel and Contact Information