Elizabeth Coleman
Pre-notification and personalisation of text-messages to retain participants in a smoking cessation pregnancy RCT: an embedded randomised factorial trial
Coleman, Elizabeth; Whitemore, Rachel; Clark, Laura; Daykin, Karen; Clark, Miranda
Authors
Rachel Whitemore
Laura Clark
Karen Daykin
Mrs MIRANDA CLARK Miranda.Clark@nottingham.ac.uk
SENIOR TRIAL MANAGER
Abstract
Background: Low response rates in randomised controlled trials can compromise the reliability of the results, so ways to boost retention are often implemented. Although there is evidence to suggest that sending a text message to participants increases retention, there is little evidence around the timing or personalisation of these messages.
Methods: A two-by-two factorial SWAT (study within a trial) was embedded within the MiQuit-3 trial, looking at smoking cessation within pregnant smokers. Participants who reached their 36-week gestational follow-up were randomised to receive a personalised or non-personalised text message, either one week or one day prior to the telephone follow-up. Primary outcomes were completion rate of questionnaire via telephone. Secondary outcomes included: completion rate via any method, time to completion, and number of reminders required.
Results: In total 194 participants were randomised into the SWAT; 50 to personalised early text, 47 to personalised late text, 50 to non-personalised early text, and 47 to non-personalised late text. There was no evidence that timing of the text message (early: one week before; or late: one day before) had an effect on any of the outcomes. There was evidence that a personalised text would result in fewer completions via telephone compared with a non-personalised text (adjusted OR 0.44, 95% CI 0.22–0.87, p=0.02). However, there was no evidence to show that personalisation or not was better for any of the secondary outcomes.
Conclusion: Timing of the text message does not appear to influence the retention of participants. Personalisation of a text message may be detrimental to retention; however, more SWATs should be undertaken in this field.
Citation
Coleman, E., Whitemore, R., Clark, L., Daykin, K., & Clark, M. (2021). Pre-notification and personalisation of text-messages to retain participants in a smoking cessation pregnancy RCT: an embedded randomised factorial trial. F1000Research, 10, Article 637. https://doi.org/10.12688/f1000research.51964.1
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 26, 2021 |
Online Publication Date | Jul 22, 2021 |
Publication Date | Jul 22, 2021 |
Deposit Date | Aug 17, 2021 |
Publicly Available Date | Aug 17, 2021 |
Journal | F1000Research |
Electronic ISSN | 2046-1402 |
Publisher | F1000Research |
Peer Reviewed | Peer Reviewed |
Volume | 10 |
Article Number | 637 |
DOI | https://doi.org/10.12688/f1000research.51964.1 |
Keywords | Randomised Controlled Trial, Embedded Trial, SWAT, Retention, text, notification, personalisation, SMS |
Public URL | https://nottingham-repository.worktribe.com/output/5817615 |
Publisher URL | https://f1000research.com/articles/10-637/v1 |
Additional Information | Referee status: Awaiting Peer Review; Grant Information: The MiQuit-3 project was co-funded by the National Institute for Health Research (NIHR) under the Programme Grants for Applied Research programme (RP-PG-0109-10020) and Cancer Research UK (CRUK) (C11232/A23434). The factorial SWAT was funded by the PROMETHEUS MRC programme grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.; Copyright: This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Files
Coleman F1000 Research 2021
(783 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search