Stakeholder experiences of using online spatial data visualisation tools for local public health decision support: A qualitative study

Roxanne Armstrong-Moore*, Martin White, Thomas Burgoine

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The distribution of food outlets within towns and cities and the provision of active travel infrastructure have been associated with health behaviours that can contribute to obesity risk. Decision-makers describe a lack of local data and research evidence as a barrier to policy adoption to improve the public's health. Online spatial data visualisation tools created by researchers can help to bridge this gap. We explored stakeholder experiences of using such tools for decision-support, with a focus on facilitators and barriers to use. We conducted 16 qualitative interviews with Public Health, Planning and Transport Planning professionals, who had used two recently-developed tools. Participants described the importance of tools being open access; their use in “story-telling”, particularly to non-experts; and more broadly their use even when imperfect. They expressed that ‘robustness’ of underpinning data was important, however this was not easily defined. Participants employed personal heuristics, principally based on endorsement and developer credibility, to determine suitability for use. We present key learning points for future developers to maximise engagement and impact.

Original languageEnglish
Article number102648
JournalHealth and Place
Publication statusPublished - Sep 2021
Externally publishedYes

Bibliographical note

Funding Information:
RAM and TB were funded by the National Institute for Health Research ( NIHR ) School for Public Health Research ( SPHR ) (grant number: PD-SPH-2015). TB and MW were funded by the Centre for Diet and Activity Research ( CEDAR ), a UKCRC Public Health Research Centre of Excellence. Funding from the British Heart Foundation , Cancer Research UK , Economic and Social Research Council , Medical Research Council , the National Institute for Health Research , and the Wellcome Trust , under the auspices of the UK Clinical Research Collaboration , is gratefully acknowledged (grant number: MR/K023187/1 ). This work was also supported by the Medical Research Council (grant number: MC_UU_00006/7 ). We acknowledge assistance from the MRC Epidemiology Unit Data Management team. We are grateful to Rachel Aldred and James Woodcock for contributing their specialist knowledge of PCT.

Publisher Copyright:
© 2021


  • Acceptability
  • Decision-support
  • Health behaviours
  • Online spatial data visualisation tools
  • Qualitative methods


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