Network Interventions on Physical Activity in an Afterschool Program: An Agent-Based Social Network Study
Authored by Jun Zhang, David A Shoham, Eric Tesdahl, Sabina B Gesell
Date Published: 2015
DOI: 10.2105/ajph.2014.302277
Sponsors:
United States National Institutes of Health (NIH)
Platforms:
NetLogo
Model Documentation:
Other Narrative
Model Code URLs:
http://www.sciencedirect.com.ezproxy1.lib.asu.edu/science/MiamiMultiMediaURL/1-s2.0-S0277953614003438/1-s2.0-S0277953614003438-mmc1.docx/271821/html/S0277953614003438/a7252302de2eb636f1a1340eeff3c052/mmc1.docx
Abstract
Objectives. We studied simulated interventions that leveraged social
networks to increase physical activity in children.
Methods. We studied a real-world social network of 81 children (average
age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs.
The sample was ethnically diverse, and 44\% were overweight or obese. We
used social network analysis and agent-based modeling simulations to
test whether implementing a network intervention would increase
children's physical activity. We tested 3 intervention strategies.
Results. The intervention that targeted opinion leaders was effective in
increasing the average level of physical activity across the entire
network. However, the intervention that targeted the most sedentary
children was the best at increasing their physical activity levels.
Conclusions. Which network intervention to implement depends on whether
the goal is to shift the entire distribution of physical activity or to
influence those most adversely affected by low physical activity.
Agent-based modeling could be an important complement to traditional
project planning tools, analogous to sample size and power analyses, to
help researchers design more effective interventions for increasing
children's physical activity.
Tags
behavior
Obesity
Overweight
calibration
Validation
Children
Simulation-models
Useful antiobesity strategy
Youth
Accelerometer