Jane Candlish
Statistical design and analysis in trials of proportionate interventions: a systematic review
Candlish, Jane; Teare, M. Dawn; Cohen, Judith; Bywater, Tracey
Authors
M. Dawn Teare
Professor Judith Cohen J.Cohen@hull.ac.uk
Director, Hull Health Trials Unit
Tracey Bywater
Abstract
Background: In proportionate or adaptive interventions, the dose or intensity can be adjusted based on individual need at predefined decision stages during the delivery of the intervention. The development of such interventions may require an evaluation of the effectiveness of the individual stages in addition to the whole intervention. However, evaluating individual stages of an intervention has various challenges, particularly the statistical design and analysis. This review aimed to identify the use of trials of proportionate interventions and how they are being designed and analysed in current practice. Methods: We searched MEDLINE, Web of Science and PsycINFO for articles published between 2010 and 2015 inclusive. We considered trials of proportionate interventions in all fields of research. For each trial, its aims, design and analysis were extracted. The data synthesis was conducted using summary statistics and a narrative format. Results: Our review identified 44 proportionate intervention trials, comprising 28 trial results, 13 protocols and three secondary analyses. These were mostly described as stepped care (n=37) and mainly focussed on mental health research (n=30). The other studies were aimed at finding an optimal adaptive treatment strategy (n=7) in a variety of therapeutic areas. Further terminology used included adaptive intervention, staged intervention, sequentially multiple assignment trial or a two-phase design. The median number of decision stages in the interventions was two and only one study explicitly evaluated the effect of the individual stages. Conclusions: Trials of proportionate staged interventions are being used predominantly within the mental health field. However, few studies consider the different stages of the interventions, either at the design or the analysis phase, and how they may interact with one another. There is a need for further guidance on the design, analyses and reporting across trials of proportionate interventions. Trial registration: Prospero, CRD42016033781. Registered on 2 February 2016.
Citation
Candlish, J., Teare, M. D., Cohen, J., & Bywater, T. (2019). Statistical design and analysis in trials of proportionate interventions: a systematic review. Trials, 20(1), Article 151. https://doi.org/10.1186/s13063-019-3206-x
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 17, 2019 |
Online Publication Date | Feb 28, 2019 |
Publication Date | Feb 28, 2019 |
Deposit Date | Apr 12, 2019 |
Publicly Available Date | Apr 22, 2021 |
Journal | Trials |
Print ISSN | 1745-6215 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 20 |
Issue | 1 |
Article Number | 151 |
DOI | https://doi.org/10.1186/s13063-019-3206-x |
Keywords | Systematic review; Complex intervention; Trial; Proportionate intervention; Stepped care; Adaptive treatment strategy; Adaptive intervention; Sequential multiple assignment randomised trial; Proportionate universalism |
Public URL | https://hull-repository.worktribe.com/output/1592865 |
Publisher URL | https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-019-3206-x |
Additional Information | Received: 14 June 2017; Accepted: 17 January 2019; First Online: 28 February 2019; : Not applicable.; : Not applicable.; : The authors declare that they have no competing interests.; : Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
Contract Date | Apr 12, 2019 |
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© The Author(s) 2019. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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