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Defining healthstyles to plan behavior change interventions in representative samples of children and adults.

Béla BirkásGergely TóthEszter BalkuErzsébet NáraiJózsef Vitrai
Published in: Psychology, health & medicine (2020)
Based on Michie's COM-B model, we developed a survey methodology and segmentation procedure to identify groups of Hungarian school children and adults with distinctive characteristics, named healthstyles. We aimed to find interventions fitting to each healthstyle to generate behavioural change. For the segmentation of data, the latent class analysis method was applied. The analysis resulted in 8 healthstyles for the school children and 13 for the adults. Each healthstyle possess distinctive 'traits' and, therefore, special behavioural change methods and prevention strategies can be fitted for them. For demonstrating the advantages of using healthstyles, we discuss possible approaches for selecting behavioural change interventions, one for school children and one for adults.
Keyphrases
  • physical activity
  • deep learning
  • convolutional neural network
  • electronic health record
  • minimally invasive
  • dna methylation
  • cross sectional
  • genome wide
  • artificial intelligence
  • data analysis