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Determinants of physical activity behaviour change in (online) interventions, and gender-specific differences: a Bayesian network model.

Simone Catharina Maria Wilhelmina TummersArjen HommersomLilian LechnerRoger BemelmansCatherine Adriana Wilhelmina Bolman
Published in: The international journal of behavioral nutrition and physical activity (2022)
While previous research provided limited insight into how interventions influence PA through relevant determinants, the Bayesian network analyses show the relevance of determinants mentioned by the theoretical framework. The model clarifies the role that different determinants play, especially in interaction with each other. The Bayesian network provides new knowledge about the complex working mechanism of interventions to change PA by giving an insightful overview of influencing paths. Furthermore, by presenting subpopulation-specific networks, the difference between the influence structure of males and females is illustrated. These new insights can be used to improve interventions in order to enhance their effects. To accomplish this, we have developed a new methodology based on a Bayesian network analysis which may be applicable in various other studies.
Keyphrases
  • physical activity
  • network analysis
  • healthcare
  • body mass index
  • mental health
  • health information