Felix Naughton
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Articles (29)
Year:
2025
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2025
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2025
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2025
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2025
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2025
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2025
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2025
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2025
Introduction Poor retention in clinical trials can impact on statistical power, reliability, validity, and generalizability of findings and is a particular challenge in smoking cessation studies. In online trials with automated follow-up mechanisms, poor response also increases the resource need for manual follow-up. This study compared two financial incentives on response rates at 6 months follow up, in an online, automated smoking cessation feasibility trial of a cessation smartphone app (Quit Sense). Aims and Methods A study within a trial (SWAT), embedded within a host randomized controlled trial. Host trial participants were randomized 1:1 to receive either a £10 or £20 voucher incentive, for completing the 6-month questionnaire. Stratification for randomization to the SWAT was by minimization to ensure an even split of host trial arm participants and by 6-week response rate. Outcome measures were: Questionnaire completion rate, time to completion, number of completers requiring manual follow-up, and completeness of responses. Results Two hundred and four participants were randomized to the SWAT. The £20 and £10 incentives did not differ in completion rate at 6 months (79% vs. 74%; p = .362) but did reduce the proportion of participants requiring manual follow-up (46% vs. 62%; p = .018) and the median completion time (7 days vs. 15 days; p = .008). Measure response completeness rates were higher among £20 incentive participants, though differences were small for the host trial’s primary smoking outcome. Conclusions Benefits to using relatively modest increases in incentive for online smoking cessation trials include more rapid completion of follow-up questionnaires and reduced manual follow-up. Implications A modest increase in incentive (from £10 to £20) to promote the completion of follow-up questionnaires in online smoking cessation trials may not increase overall response rates but could lead to more rapid data collection, a reduced need for manual follow-up and reduced missing data among those who initiate completing a questionnaire. Such an improvement may help to reduce bias, increase validity and generalizability, and improve statistical power in smoking cessation trials. Trial Registration Host trial ISRCTN12326962, SWAT repository store ID 164.
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2024
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2024
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2024
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2024
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2024
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2024
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2024
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2024
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2024
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2024
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
Collaborators (28)
Tim Coleman
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Rory Cameron
Lecturer in Health Economics
University of East Anglia Norwich Medical School
Martin Hagger
Distinguished Professor
University of California Merced
Dorothy Szinay
University College London
Meghan Moran
Associate Professor
Johns Hopkins University Bloomberg School of Public Health
Peter Verboon
Open Universiteit
Lisa McDaid
University of East Anglia
Eleni Vangeli
Senior Lecturer
London South Bank University
Catherine Kimber
Lecturer in Psychology
London South Bank University
Andy Jones
University of East Anglia
Caitlin Notley
University of East Anglia
Thomas Pollak
King’s College London
Suzanne Robinson
-
Joanne Louise Emery
University of East Anglia
Daniel Frings
London South Bank University
Nikolas Pontikos
Principal Research Fellow (Associate Professor)
UCL Institute of Ophthalmology, University College London
Daniel Powell
Lecturer
University of Aberdeen
Paul Aveyard
University of Oxford
Jamie Brown
University College London
Alicja Baska
reasearch and teaching assistant
Centrum Medyczne Ksztalcenia Podyplomowego
David Simons
University College London
Sharon Cox
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Kerry Chamberlain
Adjunct Professor / Senior Research Fellow
Victoria University of Wellington
Dennis Petrie
Professor
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Claire Garnett
University College London
Nicola Lindson
-
Juliet High
University of East Anglia
Lynne Dawkins
-
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