In medicine, a stepped-wedge trial (or SWT) is a type of randomised controlled trial (RCT).
An RCT is a scientific experiment that is designed to reduce bias when testing a new medical treatment, a social intervention, or another testable hypothesis.
In a traditional RCT, the researcher randomly divides the experiment participants into two groups at the same time: In a SWT, a logistic constraint typically prevents the simultaneous treatment of some participants, and instead, all or most participants receive the treatment in waves or "steps".
For instance, a researcher wants to measure whether teaching college students how to make several meals increased their propensity to cook at home instead of eating out.
The term "stepped wedge" was coined by The Gambia Hepatitis Intervention Study due to the stepped-wedge shape that is apparent from a schematic illustration of the design.
[1][2] The crossover is in one direction, typically from control to intervention, with the intervention not removed once implemented.
The stepped-wedge design can be used for individually randomized trials,[3][4] i.e., trials where each individual is treated sequentially, but is more commonly used as a cluster randomized trial (CRT).
[5] The stepped-wedge design involves the collection of observations during a baseline period in which no clusters are exposed to the intervention.
Following this, at regular intervals, or steps, a cluster (or group of clusters) is randomized to receive the intervention[5][6] and all participants are once again measured.
[7] This process continues until all clusters have received the intervention.
Finally, one more measurement is made after all clusters have received the intervention.
[8] Hargreaves and colleagues offer a series of five questions that researchers should answer to decide whether SWT is indeed the optimal design, and how to proceed in every step of the study.
[9] Specifically, researchers should be able to identify: While there are several other potential methods for modeling outcomes in an SWT,[14] the work of Hussey and Hughes[7] "first described methods to determine statistical power available when using a stepped wedge design.
, preferably equally spaced in actual time, some number of clusters are treated.
has been treated at time
, measure the outcome to be studied
Note that the notation allows for clustering by including
where: This model can be viewed as a Hierarchical linear model where at the lowest level
{\displaystyle y_{ict}\sim N(\mu _{ct},\sigma ^{2})}
The design effect (estimate of unit variance) of a stepped wedge design is given by the formula:[11]
{\displaystyle DE_{SW}={\dfrac {1+\rho (ktn+bn-1)}{1+\rho \left({\frac {1}{2}}ktn+bn-1\right)}}*{\dfrac {3(1-\rho )}{2t\left(k-{\frac {1}{k}}\right)}}}
where: To calculate the sample size it is needed to apply the simple formula:[11]
where: Note that increasing either k, t, or b will result to decreasing the required sample size for an SWT.
Further, the required cluster c size is given by:[11]
To calculate how many clusters cs need to switch from the control to the treatment condition, the following formula is available:[11]
If c and cs are not integers, they need to be rounded to the next larger integer and distributed as evenly as possible among k. Stepped wedge design features many comparative advantages to traditional RCTs (Randomized controlled trials).
SWT may suffer from certain drawbacks.
The number of studies using the design have been on the increase.
In 2015, a thematic series was published in the journal Trials.
[19] In 2016, the first international conference dedicated to the topic was held at the University of York.