Simulation modeling to assist with childhood obesity control: perceptions of Baltimore City policymakers

J Public Health Policy. 2018 May;39(2):173-188. doi: 10.1057/s41271-018-0125-0.

Abstract

Computational simulation models have potential to inform childhood obesity prevention efforts. To guide their future use in obesity prevention policies and programs, we assessed Baltimore City policymakers' perceptions of computational simulation models. Our research team conducted 15 in-depth interviews with stakeholders (policymakers in government and non-profit sectors), then transcribed and coded them for analysis. We learned that informants had limited understanding of computational simulation modeling. Although they did not understand how the model was developed, they perceived the tool to be useful when applying for grants, adding to the evidence base for decision-making, piloting programs and policies, and visualizing data. Their concerns included quality and relevance of data used to support the model. Key recommendations for model design included a visual display with explanations to facilitate understanding and a formal method for gathering feedback during model development.

Keywords: Agent based model; Childhood obesity; Policymakers; Qualitative research.

MeSH terms

  • Administrative Personnel / psychology*
  • Administrative Personnel / statistics & numerical data
  • Baltimore
  • Child
  • Computer Simulation*
  • Humans
  • Pediatric Obesity / prevention & control*
  • Qualitative Research