Evidence map›Paper›PMID 39791251›Full record

Trial reportJMIR public health and surveillance2025

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, Nicholas Gilby, Galini Pantelidou, Sam Clemens, Kevin Pickering, Marc Chadeau-Hyam, Deborah Ashby, Wendy S Barclay, Graham S Cooke, Ara Darzi and 4 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in JMIR public health and surveillance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
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  3. With qualitative research, the risks of data sharing can outweigh the rewards.Proceedings of the National Academy of Sciences of the United States of America · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Christina J AtchisonSchool of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0001-8304-7389
Nicholas GilbyIpsos, London, United Kingdom.ORCID 0009-0005-0915-8124
Galini PantelidouIpsos, London, United Kingdom.ORCID 0009-0007-3105-5740
Sam ClemensIpsos, London, United Kingdom.ORCID 0000-0001-8204-9083
Kevin PickeringIpsos, London, United Kingdom.ORCID 0000-0002-0509-0039
Marc Chadeau-HyamSchool of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0001-8341-5436
Deborah AshbySchool of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0003-3146-7466
Wendy S BarclayDepartment of Infectious Disease, Imperial College London, Norfolk Place, London, United Kingdom.ORCID 0000-0002-3948-0895
Graham S CookeDepartment of Infectious Disease, Imperial College London, Norfolk Place, London, United Kingdom.ORCID 0000-0001-6475-5056
Ara DarziInstitute of Global Health Innovation, Imperial College London, South Kensington Campus, London, United Kingdom.ORCID 0000-0001-7815-7989
Steven RileySchool of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0001-7904-4804
Christl A DonnellySchool of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-0195-2463
Helen WardSchool of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0001-8238-5036
Paul ElliottSchool of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-7511-5684

Funding

Medical Research Council MR/X020258/1Wellcome Trust
6 · The paper itself

Abstract

Background: High response rates are needed in population-based studies, as nonresponse reduces effective sample size and bias affects accuracy and decreases the generalizability of the study findings. Objective: We tested different strategies to improve response rate and reduce nonresponse bias in a national population-based COVID-19 surveillance program in England, United Kingdom. Methods: Over 19 rounds, a random sample of individuals aged 5 years and older from the general population in England were invited by mail to complete a web-based questionnaire and return a swab for SARS-CoV-2 testing. We carried out several nested randomized controlled experiments to measure the impact on response rates of different interventions, including (1) variations in invitation and reminder letters and SMS text messages and (2) the offer of a conditional monetary incentive to return a swab, reporting absolute changes in response and relative response rate (95% CIs). Results: Monetary incentives increased the response rate (completed swabs returned as a proportion of the number of individuals invited) across all age groups, sex at birth, and area deprivation with the biggest increase among the lowest responders, namely teenagers and young adults and those living in more deprived areas. With no monetary incentive, the response rate was 3.4% in participants aged 18-22 years, increasing to 8.1% with a £10 (US $12.5) incentive, 11.9% with £20 (US $25.0), and 18.2% with £30 (US $37.5) (relative response rate 2.4 [95% CI 2.0-2.9], 3.5 [95% CI 3.0-4.2], and 5.4 [95% CI 4.4-6.7], respectively). Nonmonetary strategies had a modest, if any, impact on response rate. The largest effect was observed for sending an additional swab reminder (SMS text message or email). For example, those receiving an additional SMS text message were more likely to return a completed swab compared to those receiving the standard email-SMS approach, 73.3% versus 70.2%: percentage difference 3.1% (95% CI 2.2%-4.0%). Conclusions: Conditional monetary incentives improved response rates to a web-based survey, which required the return of a swab test, particularly for younger age groups. Used in a selective way, incentives may be an effective strategy for improving sample response and representativeness in population-based studies.

Indexed as

COVID-19AdolescentAdultAgedBiasChildChild, PreschoolEnglandFemaleHumansMaleMiddle AgedMotivationPopulation HealthRandomized Controlled Trials as TopicSurveys and QuestionnairesCOVID-19population-based researchresponse rateSARS-CoV-2study recruitmentweb-based questionnaires

Identifiers

PMID39791251
PMCPMC11737284

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.