Designing a stepped wedge trial: three main designs, carry-over effects and randomisation approaches.

Andrew J Copas,James R Hargreaves,Gianluca Baio,Calum Davey,James J Lewis,Jennifer A Thompson

doi:10.1186/s13063-015-0842-7

Andrew J Copas, James R Hargreaves + Show 4 more

Open Access

https://doi.org/10.1186/s13063-015-0842-7

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Abstract

BackgroundThere is limited guidance on the design of stepped wedge cluster randomised trials. Current methodological literature focuses mainly on trials with cross-sectional data collection at discrete times, yet many recent stepped wedge trials do not follow this design. In this article, we present a typology to characterise the full range of stepped wedge designs, and offer guidance on several other design aspects.MethodsWe developed a framework to define and report the key characteristics of a stepped wedge trial, including cluster allocation and individual participation. We also considered the relative strengths and weaknesses of trials according to this framework. We classified recently published stepped wedge trials using this framework and identified illustrative case studies. We identified key design choices and developed guidance for each.ResultsWe identified three main stepped wedge designs: those with a closed cohort, an open cohort, and a continuous recruitment short exposure design. In the first two designs, many individuals experience both control and intervention conditions. In the final design, individuals are recruited in continuous time as they become eligible and experience either the control or intervention condition, but not both, and then provide an outcome measurement at follow-up. While most stepped wedge trials use simple randomisation, stratification and restricted randomisation are often feasible and may be useful. Some recent studies collect outcome information from individuals exposed a long time before or after the rollout period, but this contributes little to the primary analysis. Incomplete designs should be considered when the intervention cannot be implemented quickly. Carry-over effects can arise in stepped wedge trials with closed and open cohorts.ConclusionsStepped wedge trial designs should be reported more clearly. Researchers should consider the use of stratified and/or restricted randomisation. Trials should generally not commit resources to collect outcome data from individuals exposed a long time before or after the rollout period. Though substantial carry-over effects are uncommon in stepped wedge trials, researchers should consider their possibility before conducting a trial with closed or open cohorts.

Highlights

There is limited guidance on the design of stepped wedge cluster randomised trials
We developed a typology of individual exposure and measurement, and with that in mind, examined the recently published Stepped wedge cluster randomized controlled trial (SWT) reviewed in this series [1] to identify commonly used designs and illustrative case studies
Defining characteristics of stepped wedge cluster randomised trials, allocation and terminology An SWT is a trial in which clusters receive the intervention at different time points, the order in which they receive it is randomised, and data are collected from clusters over time

Summary

Introduction

There is limited guidance on the design of stepped wedge cluster randomised trials. Current methodological literature focuses mainly on trials with cross-sectional data collection at discrete times, yet many recent stepped wedge trials do not follow this design. SWTs encompass a broad range of designs, and the methodological literature is lagging behind the growth in the conduct of SWTs. Much of the literature to date has focussed on a small range of SWT designs where data are collected from individuals at discrete time points, and individuals contribute one measurement during the study [2,3,4,5]. Much of the literature to date has focussed on a small range of SWT designs where data are collected from individuals at discrete time points, and individuals contribute one measurement during the study [2,3,4,5] This may, for example, arise from cross-sectional sampling from all clusters just before each crossover point (whenever a group of clusters changes from control to intervention condition). There is limited published guidance for planning SWTs, and adapting the published guidance to the broad range of designs in use is not straightforward

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