Published on in Vol 11 (2025)

This is a member publication of JISC

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60022, first published .
Strategies to Increase Response Rate and Reduce Nonresponse Bias in Population Health Research: Analysis of a Series of Randomized Controlled Experiments during a Large COVID-19 Study

Strategies to Increase Response Rate and Reduce Nonresponse Bias in Population Health Research: Analysis of a Series of Randomized Controlled Experiments during a Large COVID-19 Study

Strategies to Increase Response Rate and Reduce Nonresponse Bias in Population Health Research: Analysis of a Series of Randomized Controlled Experiments during a Large COVID-19 Study

Christina J Atchison   1 , PhD ;   Nicholas Gilby   2 , BA ;   Galini Pantelidou   2 , MSc ;   Sam Clemens   2 , BA ;   Kevin Pickering   2 , MSc ;   Marc Chadeau-Hyam   1 , PhD ;   Deborah Ashby   1 , PhD ;   Wendy S Barclay   3 , PhD ;   Graham S Cooke   3 , PhD ;   Ara Darzi   4 , MD ;   Steven Riley   1 , PhD ;   Christl A Donnelly   1, 5 , ScD ;   Helen Ward   1 , PhD ;   Paul Elliott   1 , PhD

1 School of Public Health, Imperial College London, London, United Kingdom

2 Ipsos, London, United Kingdom

3 Department of Infectious Disease, Imperial College London, Norfolk Place, London, United Kingdom

4 Institute of Global Health Innovation, Imperial College London, South Kensington Campus, London, United Kingdom

5 Department of Statistics, University of Oxford, Oxford, United Kingdom

Corresponding Author:

  • Paul Elliott, PhD
  • School of Public Health
  • Imperial College London
  • White City Campus, 90 Wood Lane
  • London, W12 0BZ
  • United Kingdom
  • Email: p.elliott@imperial.ac.uk