Discussing Data: A UK-wide public consultation on the use of low fidelity synthetic data for research - Claire Nollett; Fiona Lugg-Widger; Joshua Stock; Lucy Brookes-Howell; Jim Fitzgibbon; Sean Johnson; Kim Munnery; Michael Robling; Farheen Yameen; Rob Trubey (International journal of population data science, 2025)
Introduction Synthetic data is an emerging tool for health and social care researchers which can be used to expedite research processes and enhance the safety of personal data handling. Although data owners across the UK and globally currently make synthetic datasets available, public awareness and perceptions of its use for research remain underexplored. Objectives We aimed to agree a set of recommendations for data owners on producing and releasing synthetic data and communicating with the UK public about this topic. Methods Forty-four public members were invited to four deliberative workshops to co-create a set of recommendations for data owners. Notes and transcripts from workshops 1-3, along with public member survey feedback, were reviewed to identify key topics. Results Thirty-seven individuals contributed. We developed ten recommendations spanning five areas: introducing synthetic data; explaining its purpose; creating datasets; managing access, use, and misuse; and clear communication. These were iteratively refined with public input during the final workshop. Conclusions This study offers a unique insight into public attitudes towards synthetic data use in health and administrative research. The recommendations developed are intended to support UK data owners in releasing synthetic data responsibly, aligning with public expectations and fostering trust in its use as a research innovation tool. Future research should continue to assess evolving public attitudes to both low and high-fidelity data as its use expands.