Increasing retention in a large-scale decentralised clinical trial: learnings from the COVID-RED trial
Increasing retention in a large-scale decentralised clinical trial: learnings from the COVID-RED trial
Objective: to present retention strategies implemented in the coronavirus disease 2019 (COVID-19) rapid early detection trial, a decentralized trial investigating the use of a wearable device for severe acute respiratory syndrome coronavirus 2 detection, and to provide insights into study retention and investigate determinants of discontinuation.
Patients and methods: the COVID-2019 rapid early detection trial collected data from 17,825 participants from February 22, 2021 to November 18, 2021. Participants wore a wearable device overnight and synchronized it with a mobile application on waking. Retention strategies included common and personalized activities. Multivariable logistic regression was used to identify participants at high risk of discontinuation after 6 months in the trial. Results were combined with insights from behavioral theory to target participants with additional telephone calls.
Results: total of 14,326 (80.4%) participants remained in the trial after 6 months and 12,208 (68.5%) until the end of the trial. Multivariable logistic regression identified age, employment situation, living situation, and COVID-19 vaccination status as predictors of discontinuation. Subgroups at high risk of discontinuation were identified, and behavioral assessments indicated that the subgroup of vaccinated pensioners would receive additional telephone calls. Their dropout rate was 11.4% after telephone calls.
Conclusion: this study describes how innovative and targeted data-driven retention strategies can be applied in a large decentralized clinical trial and presents the implemented retention strategies and discontinuation rates. Results can serve as a starting point for designing retention strategies in future decentralized trials.
Zwiers, Laura C.
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Veen, Duco
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Mitratza, Marianna
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Brakenhoff, Timo B.
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Goodale, Brianna M.
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Klaver, Paul
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Hage, Kay Y.
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van Willigen, Marcel
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Downward, George S.
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Lugtig, Peter
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van Maanen, Leendert
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Van der Stigchel, Stefan
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van der Heijden, Peter
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Cronin, Maureen
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Grobbee, Diederick E.
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30 September 2025
Zwiers, Laura C.
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Veen, Duco
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Mitratza, Marianna
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Brakenhoff, Timo B.
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Goodale, Brianna M.
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Klaver, Paul
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Hage, Kay Y.
048f645e-deb2-4c43-aed2-3f5405882248
van Willigen, Marcel
ec2b39a1-7458-4aff-b7f3-4acd390fa530
Downward, George S.
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Lugtig, Peter
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van Maanen, Leendert
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Van der Stigchel, Stefan
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van der Heijden, Peter
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Cronin, Maureen
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Grobbee, Diederick E.
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Zwiers, Laura C., Veen, Duco, Mitratza, Marianna, Brakenhoff, Timo B., Goodale, Brianna M., Klaver, Paul, Hage, Kay Y., van Willigen, Marcel, Downward, George S., Lugtig, Peter, van Maanen, Leendert, Van der Stigchel, Stefan, van der Heijden, Peter, Cronin, Maureen and Grobbee, Diederick E.
(2025)
Increasing retention in a large-scale decentralised clinical trial: learnings from the COVID-RED trial.
Mayo Clinic Proceedings: Digital Health, 3 (4), [100264].
(doi:10.1016/j.mcpdig.2025.100264).
Abstract
Objective: to present retention strategies implemented in the coronavirus disease 2019 (COVID-19) rapid early detection trial, a decentralized trial investigating the use of a wearable device for severe acute respiratory syndrome coronavirus 2 detection, and to provide insights into study retention and investigate determinants of discontinuation.
Patients and methods: the COVID-2019 rapid early detection trial collected data from 17,825 participants from February 22, 2021 to November 18, 2021. Participants wore a wearable device overnight and synchronized it with a mobile application on waking. Retention strategies included common and personalized activities. Multivariable logistic regression was used to identify participants at high risk of discontinuation after 6 months in the trial. Results were combined with insights from behavioral theory to target participants with additional telephone calls.
Results: total of 14,326 (80.4%) participants remained in the trial after 6 months and 12,208 (68.5%) until the end of the trial. Multivariable logistic regression identified age, employment situation, living situation, and COVID-19 vaccination status as predictors of discontinuation. Subgroups at high risk of discontinuation were identified, and behavioral assessments indicated that the subgroup of vaccinated pensioners would receive additional telephone calls. Their dropout rate was 11.4% after telephone calls.
Conclusion: this study describes how innovative and targeted data-driven retention strategies can be applied in a large decentralized clinical trial and presents the implemented retention strategies and discontinuation rates. Results can serve as a starting point for designing retention strategies in future decentralized trials.
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Accepted/In Press date: 2 September 2025
e-pub ahead of print date: 9 September 2025
Published date: 30 September 2025
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Local EPrints ID: 506019
URI: http://eprints.soton.ac.uk/id/eprint/506019
ISSN: 2949-7612
PURE UUID: 15a1de5f-1f22-4b66-a90b-9ac32c328a04
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Date deposited: 27 Oct 2025 17:57
Last modified: 01 Nov 2025 02:44
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Contributors
Author:
Laura C. Zwiers
Author:
Duco Veen
Author:
Marianna Mitratza
Author:
Timo B. Brakenhoff
Author:
Brianna M. Goodale
Author:
Paul Klaver
Author:
Kay Y. Hage
Author:
Marcel van Willigen
Author:
George S. Downward
Author:
Peter Lugtig
Author:
Leendert van Maanen
Author:
Stefan Van der Stigchel
Author:
Maureen Cronin
Author:
Diederick E. Grobbee
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