↓ Skip to main content

Five questions to consider before conducting a stepped wedge trial

Overview of attention for article published in Trials, August 2015
Altmetric Badge

Mentioned by

policy
1 policy source
twitter
108 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
57 Dimensions

Readers on

mendeley
176 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Five questions to consider before conducting a stepped wedge trial
Published in
Trials, August 2015
DOI 10.1186/s13063-015-0841-8
Pubmed ID
Authors

James R Hargreaves, Andrew J Copas, Emma Beard, David Osrin, James J Lewis, Calum Davey, Jennifer A Thompson, Gianluca Baio, Katherine L Fielding, Audrey Prost

Abstract

Researchers should consider five questions before starting a stepped wedge trial. Why are you planning one? Researchers sometimes think that stepped wedge trials are useful when there is little doubt about the benefit of the intervention being tested. However, if the primary reason for an intervention is to measure its effect, without equipoise there is no ethical justification for delaying implementation in some clusters. By contrast, if you are undertaking pragmatic research, where the primary reason for rolling out the intervention is for it to exert its benefits, and if phased implementation is inevitable, a stepped wedge trial is a valid option and provides better evidence than most non-randomized evaluations. What design will you use? Two common stepped wedge designs are based on the recruitment of a closed or open cohort. In both, individuals may experience both control and intervention conditions and you should be concerned about carry-over effects. In a third, continuous-recruitment, short-exposure design, individuals are recruited as they become eligible and experience either control or intervention condition, but not both. How will you conduct the primary analysis? In stepped wedge trials, control of confounding factors through secular variation is essential. 'Vertical' approaches preserve randomization and compare outcomes between randomized groups within periods. 'Horizontal' approaches compare outcomes before and after crossover to the intervention condition. Most analysis models used in practice combine both types of comparison. The appropriate analytic strategy should be considered on a case-by-case basis. How large will your trial be? Standard sample size calculations for cluster randomized trials do not accommodate the specific features of stepped wedge trials. Methods exist for many stepped wedge designs, but simulation-based calculations provide the greatest flexibility. In some scenarios, such as when the intracluster correlation coefficient is moderate or high, or the cluster size is large, a stepped wedge trial may require fewer clusters than a parallel cluster trial. How will you report your trial? Stepped wedge trials are currently challenging to report using CONSORT principles. Researchers should consider how to demonstrate balance achieved by randomization and how to describe trends for outcomes in both intervention and control clusters.

X Demographics

X Demographics

The data shown below were collected from the profiles of 108 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 2%
Netherlands 1 <1%
Sweden 1 <1%
Unknown 171 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 20%
Student > Ph. D. Student 31 18%
Student > Master 26 15%
Student > Doctoral Student 11 6%
Other 11 6%
Other 30 17%
Unknown 31 18%
Readers by discipline Count As %
Medicine and Dentistry 64 36%
Social Sciences 17 10%
Nursing and Health Professions 11 6%
Mathematics 10 6%
Psychology 8 5%
Other 25 14%
Unknown 41 23%