Table Of Content
- Three main stepped wedge cluster randomised trial designs: individual exposure and measurement
- Case Study House 20… b
- OPPORTUNITIES FOR CONSIDERING STEPPED WEDGE DESIGNS IN FUTURE NEUROSURGERY TRIALS
- TRESemmé TRES Two Extra Firm Control Gel
- Authors’ original submitted files for images
- Epidemiology and study details
- Associated Data

For example, cross-sectional measurement to assess change within a closed cohort (T1/D1/M3) is less sensitive than measuring the same individuals. Researchers planning SWTs must consider a range of design issues, starting with how individuals from within clusters will participate. The design literature makes little distinction between SWTs where individuals are exposed to one condition only, or to both control and intervention conditions. The literature has also not clearly addressed the role of data collected before and/or after the rollout period in the study. The limited range of designs considered has also hampered the growth of terminology to describe the conduct of SWTs, and allow them to be reported in a transparent and consistent way, though others have begun this process [6].
Three main stepped wedge cluster randomised trial designs: individual exposure and measurement
This feature tends to enhance the precision of the study compared with a simple parallel study if substantial cluster effects are present (that is, if the intra-cluster correlation is large). 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. The 12 studies included in this review describe evaluations of a wide range of interventions, across different diseases in different settings. However the stepped wedge design appears to have found a niche for evaluating interventions in developing countries, specifically those concerned with HIV. There were few consistent motivations for employing a stepped wedge design or methods of data analysis across studies.
Case Study House 20… b
Special methods are needed for analysis and sample size estimation for these studies, as detailed below and in the SWGRT sample size calculator. Aldo’s 5-inch wedges look dangerously steep but are designed with the brand’s Pillow Walk foam padded insoles, along with memory foam to simultaneously absorb impact while comfortably molding to your foot and providing key support in places like your heel and the ball of your foot. The delicate, adjustable ankle strap helps hold your foot in place, so you can actually walk in this pair, too. In SW-CRTs, all sites are introduced to the intervention before their intervention starts, in some cases more than a year in advance. This might lead to the Hawthorne effect, which is when study subjects modify their behavior when made aware that they are being observed. The North Carolina cooperative might have experienced the effect more acutely than others, owing to its institutional policies, which required contracts be signed up front specifying the outcome measures of interest.

OPPORTUNITIES FOR CONSIDERING STEPPED WEDGE DESIGNS IN FUTURE NEUROSURGERY TRIALS
However, interviewees recommended carefully weighing the advantages and challenges of SW-CRT design (Table 2) before selecting this design, given its numerous challenges, because deviations from the study design might introduce bias into the analyses. We believe that a well-conducted SWT, in which participants experience only one condition and analysis appropriately takes account of period effects, provides strong evidence concerning the effectiveness of an intervention, and that this evidence will be far stronger than that from a non-randomised rollout. In our view, such a carefully designed and analysed SWT can in principle be as rigorous as a standard CRT, and deserves to be viewed as an experimental design rather than quasi-experimental.
There was also the risk that facilitators working across multiple sequences were delivering the intervention to sites that were in the control period. For example, in New York City facilitators continued to visit sites in the control period to deliver other programs that the network leadership was implementing. The Oklahoma cooperative attempted to decrease cross-contamination by strengthening training and quality control. Specifically the attendance of pupils in a term when the intervention is introduced (school breakfasts) is unlikely to be affected by whether a school had exposed pupils to the control condition (no breakfast) for one or two more terms more than in other schools. In case study three, carry-over effects are again unlikely as the control condition is a standard approach that staff will have experienced for a while before the trial, and the outcome is likely to remain stable.
TRESemmé TRES Two Extra Firm Control Gel
A stepped wedge design also allows investigators to examine the way in which the impact of the intervention develops (over time) once it is introduced into a cluster. This might be important where an intervention needs an initial period of adjustment before becoming fully embedded in the setting. In such cases the length of the period (up to the current observation) during which the cluster has been exposed to the intervention can be included in the model as an effect modifier. Adjusting for the systematically different observation periods and for clustering in the data is accomplished by fitting an appropriate generalised linear mixed model or using generalised estimating equations. Interviewees reported that many sites had difficulty contributing data for every time block of the implementation timeline on the specified cardiovascular disease outcome measures. In comparison, a parallel CRT does not require measurements across multiple time blocks and has a shorter time frame.
Overview of Statistical Models for the Design and Analysis of Stepped Wedge Cluster Randomized Trials - NIH Office of Disease Prevention
Overview of Statistical Models for the Design and Analysis of Stepped Wedge Cluster Randomized Trials.
Posted: Tue, 14 Jul 2020 07:00:00 GMT [source]
The ICC measures the similarity among values on the outcome variable for different members of the same group or cluster within a given time period. It is often described as the average correlation among members within the same group or cluster and within the same time period or as the proportion of variance due to group or cluster membership. The CAC is the correlation between the population means from the same group or cluster at two different time periods; it is sometimes called over-time correlation at the group level. The IAC is the correlation on the outcome variable for the same individual at two different time periods; it is sometimes called over-time correlation at the member level. Four groups of units initiated the intervention at four separate points in time between April 2009 and March 2011.
Epidemiology and study details
The Better Health Outcomes through Mentoring and Assessment (BHOMA) study is an SWT of a health systems strengthening intervention in Zambia, conducted in 42 clusters divided into three districts. There were seven clusters in district A, 14 clusters in district B, and 21 clusters in district C, so at each crossover point one cluster from district A, two from district B, and three from district C crossed over from the control to intervention [18]. As there were six clusters in each group, the stratification of the randomisation of clusters to groups assured balance of districts across the order of rollout.
The impact of iterative removal of low-information cluster-period cells from a stepped wedge design - BMC Medical ... - BMC Medical Research Methodology
The impact of iterative removal of low-information cluster-period cells from a stepped wedge design - BMC Medical ....
Posted: Thu, 06 Jul 2023 07:00:00 GMT [source]
SWT designs where individuals experience both conditions may be a good choice, given constraints and the research question. In our opinion however, researchers should consider the possibility of carry-over effects and other bias a priori, and report these considerations when publishing the results of the trial. There is a wide range of stepped wedge trial designs, and key aspects such as the exposure of individuals and their measurement should be reported more clearly.
While the small sample makes generalisations difficult, the stepped wedge design appears to be primarily used in evaluating interventions in developing countries, with HIV the most common disease addressed (Table 1). Table 2 identifies that a number of different interventions were being evaluated, with vaccination, screening and education plans emerging as the most common interventions. Such interventions are likely to have an existing evidence base, adding to intuitive beliefs that the intervention is likely to do more good than harm. It is also possible that the use of the stepped wedge design is increasing, with 9 (75%) of the studies published since 2002. Dr. Xin Zhou is an Assistant Professor in the Department of Biostatistics at Yale School of Public Health.
The aim of the review is to determine the extent to which the stepped wedge design has been employed empirically and, for the available studies, to examine the background epidemiology, why researchers decided on a stepped wedge design and methods of data analysis. However we would be interested to hear about any further examples that our search may have missed. The stepped wedge cluster randomised trial, while pragmatic, also requires cooperation and commitment from the clusters. Clusters will have to be ready to cross to the intervention as and when the randomisation order dictates. Most stepped wedge trials to date have given ample notice of the crossover date to clusters. However, this does not rule out the possibility that some clusters will not be able to initiate the intervention as and when the randomisation schedule dictates.
In SWD trials, all individuals or clusters are observed first for a certain period of time under control conditions and then under intervention conditions until the end of the trial. The number of consecutive points in time at which the outcome variable is observed is identical for all clusters, except for cases with missing values. Individuals may either be treated only once (cross-sectional SWD) or switch from control treatment to the intervention during the trial (open- versus closed-cohort SWD). In practice, however, SWD trials are usually conducted as an alternative to cluster-randomized trials. RESULTS All interviewees reported that SW-CRT can be an effective study design for large-scale intervention implementations. Advantages included (1) incentivized recruitment, (2) staggered resource allocation, and (3) statistical power.
AC led the writing of the text, except the text on randomisation methods which was led by JL. GB and all other authors discussed the content of the paper in meetings, contributed to the text, and suggested edits to earlier drafts. The necessary statistical tools for the planning and evaluation of SWD trials now stand at our disposal. Such trials nevertheless are subject to major risks, as valid results can be obtained only if the far-reaching assumptions of the model are, in fact, justified. The number of individuals is based on recruitment to the trial, rather than completed follow-up numbers.
The stepped wedge design is increasingly popular in a wide variety of settings, including public health intervention evaluations and clinical and health service research. Previous studies presenting power calculation methods for stepped wedge designs have focused on continuous outcomes and relied on normal approximations for binary outcomes. Dr. Xin Zhou introduces two new methods, using maximum likelihood and generalized estimating equations, to improve the power calculation for binary outcomes. Dr. Zhou has also developed user-friendly software, including a SAS macro, an R package, and a Shiny app, for power calculations in stepped wedge designs. In this presentation, uses the R package to show how to use the software for power calculations in stepped wedge designs. This presentation explains the unique characteristics of the stepped wedge cluster randomized design and its implications for sample size calculation and analysis, and discusses its strengths and weaknesses compared to traditional designs.
In the course of that project, a large-scale vaccination program was implemented in Gambia, for which 17 teams were formed. The aim was to have vaccinated all children against hepatitis B viruses (HBVs) after approximately 4 years. The main reason given for proceeding in this way was logistics, including vaccine availability. Indirect evidence that vaccination effectively reduced HBV infection had already been confirmed before in a number of studies in high-risk groups. According to the authors of the trial, it would be valuable to obtain direct evidence that vaccination reduced the incidence of liver tumors. With respect to this trial, there was also debate as to whether a 4-year traditional parallel-group trial should be conducted instead of the SWD.
In a closed cohort trial, in particular, this may also imply a high measurement burden on individual participants, and there may be little marginal gain in information from excessively increasing the number of measurements per individual. A schematic of stepped wedge design for the Early Recognition and Response to Increases in Surgical Site Infection (Early 2RIS) Trial. There are 12 randomization sequences (defined by the first time period during which each group of clusters crossover to intervention). In the Early 2RIS trial, the baseline period is one year, and each subsequent period is 3 months.