Gaining Insight into Determinants of Physical Activity using Bayesian Network Learning

Abstract

Bayesian network modelling is applied to health psychology data in order to obtain more insight into the determinants of physical activity. This preliminary study discusses some challenges to apply gen-eral machine learning methods to this application domain, and Bayesian networks in particular. We investigate several suitable methods for deal-ing with missing data, and determine which method obtains good results in terms of fitting the data. Furthermore, we present the learnt Bayesian network model for this e-health intervention case study, and conclusions are drawn about determinants of physical activity behaviour change and how the intervention affects physical activity behaviour and its determi-nants. We also evaluate the contributions of Bayesian network analysis compared to traditional statistical analyses in this field. Finally, possible extensions on the performed analyses are proposed