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Background/Aims: The standard approach to designing stepped wedge trials that recruit participants in a continuous stream is to divide time into periods of equal length. But the choice of design in such cases is infinitely more flexible: each cluster could cross from the control to the intervention at any point on the continuous time-scale. We consider the case of a stepped wedge design with clusters randomised to just three sequences (designs with small numbers of sequences may be preferred for their simplicity and practicality) and investigate the choice of design that minimises the variance of the treatment effect estimator under different assumptions about the intra-cluster correlation. Methods: We make some simplifying assumptions in order to calculate the variance: in particular that we recruit the same number of participants, m , from each cluster over the course of the trial, and that participants present at regularly spaced intervals. We consider an intra-cluster correlation that decays exponentially with separation in time between the presentation of two individuals from the same cluster, from a value of ρ for two individuals who present at the same time, to a value of ρ τ for individuals presenting at the start and end of the trial recruitment interval. We restrict attention to three-sequence designs with centrosymmetry – the property that if we reverse time and swap the intervention and control conditions then the design looks the same. We obtain an expression for the variance of the treatment effect estimator adjusted for effects of time, using methods for generalised least squares estimation, and we evaluate this expression numerically for different designs, and for different parameter values. Results: There is a two-dimensional space of possible three-sequence, centrosymmetric stepped wedge designs with continuous recruitment. The variance of the treatment effect estimator for given ρ and τ can be plotted as a contour map over this space. The shape of this variance surface depends on τ and on the parameter m ρ / (1 − ρ) , but typically indicates a broad, flat region of close-to-optimal designs. The 'standard' design with equally spaced periods and 1:1:1 allocation rarely performs well, however. Conclusions: In many different settings, a relatively simple design can be found (e.g. one based on simple fractions) that offers close-to-optimal efficiency in that setting. There may also be designs that are robustly efficient over a wide range of settings. Contour maps of the kind we illustrate can help guide this choice. If efficiency is offered as one of the justifications for using a stepped wedge design, then it is worth designing with optimal efficiency in mind. [ABSTRACT FROM AUTHOR]

Many clinical trials involve partially clustered data, where some observations belong to a cluster and others can be considered independent. For example, neonatal trials may include infants from single or multiple births. Sample size and analysis methods for these trials have received limited attention. A simulation study was conducted to (1) assess whether existing power formulas based on generalized estimating equations (GEEs) provide an adequate approximation to the power achieved by mixed effects models, and (2) compare the performance of mixed models vs GEEs in estimating the effect of treatment on a continuous outcome. We considered clusters that exist prior to randomization with a maximum cluster size of 2, three methods of randomizing the clustered observations, and simulated datasets with uninformative cluster size and the sample size required to achieve 80% power according to GEE‐based formulas with an independence or exchangeable working correlation structure. The empirical power of the mixed model approach was close to the nominal level when sample size was calculated using the exchangeable GEE formula, but was often too high when the sample size was based on the independence GEE formula. The independence GEE always converged and performed well in all scenarios. Performance of the exchangeable GEE and mixed model was also acceptable under cluster randomization, though under‐coverage and inflated type I error rates could occur with other methods of randomization. Analysis of partially clustered trials using GEEs with an independence working correlation structure may be preferred to avoid the limitations of mixed models and exchangeable GEEs. [ABSTRACT FROM AUTHOR]

Unravelling the impact of the sex of the anaesthesia provider on the outcomes of patients requires careful statistical analysis and the validity of many assumptions. A recent study in the British Journal of Anaesthesia investigates the effect of anaesthesia provider sex on patient outcomes, using data from two academic healthcare networks in the USA. The authors show that female provider sex was associated with a lower risk of intraoperative complications. They also show that there was no meaningful difference between male and female providers with respect to postoperative outcomes. There have been several recent studies considering the effect of healthcare provider sex on outcomes. We will discuss the interpretation of these results and the validity of the underlying assumptions. [ABSTRACT FROM AUTHOR]

This article introduces the 'staircase' design, derived from the zigzag pattern of steps along the diagonal of a stepped wedge design schematic where clusters switch from control to intervention conditions. Unlike a complete stepped wedge design where all participating clusters must collect and provide data for the entire trial duration, clusters in a staircase design are only required to be involved and collect data for a limited number of pre- and post-switch periods. This could alleviate some of the burden on participating clusters, encouraging involvement in the trial and reducing the likelihood of attrition. Staircase designs are already being implemented, although in the absence of a dedicated methodology, approaches to sample size and power calculations have been inconsistent. We provide expressions for the variance of the treatment effect estimator when a linear mixed model for an outcome is assumed for the analysis of staircase designs in order to enable appropriate sample size and power calculations. These include explicit variance expressions for basic staircase designs with one pre- and one post-switch measurement period. We show how the variance of the treatment effect estimator is related to key design parameters and demonstrate power calculations for examples based on a real trial. [ABSTRACT FROM AUTHOR]

Stepped wedge trials are increasingly adopted because practical constraints necessitate staggered roll‐out. While a complete design requires clusters to collect data in all periods, resource and patient‐centered considerations may call for an incomplete stepped wedge design to minimize data collection burden. To study incomplete designs, we expand the metric of information content to discrete outcomes. We operate under a marginal model with general link and variance functions, and derive information content expressions when data elements (cells, sequences, periods) are omitted. We show that the centrosymmetric patterns of information content can hold for discrete outcomes with the variance‐stabilizing link function. We perform numerical studies under the canonical link function, and find that while the patterns of information content for cells are approximately centrosymmetric for all examined underlying secular trends, the patterns of information content for sequences or periods are more sensitive to the secular trend, and may be far from centrosymmetric. [ABSTRACT FROM AUTHOR]

*OBJECTIVE: To determine whether the effect of hip exercise on patellofemoral pain is mediated through changes in hip muscle strength or psychological factors. *DESIGN: Secondary mediation analysis of a randomized clinical trial, in which 218 participants with patellofemoral pain were randomly assigned to receive foot orthoses or hip exercises. *METHODS: Pain (Knee injury and Osteoarthritis Outcome Score pain subscale) and number of pain-free squats at 12 weeks were the outcomes for this mediation analysis, as they are pathognomonic of patellofemoral pain. Hip strength dynamometry (abduction, adduction, and external rotation) and psychological characteristics (pain catastrophizing, kinesiophobia, and anxiety) measured at 6 weeks were considered as potential mediators. We used mediation analysis to decompose the total effect of treatment on the outcome into (1) the "indirect effect" (ie, the portion acting through the mediator) and (2) the "direct effect." *RESULTS: The effect of hip exercise on pain and squats was not mediated by any of the strength or psychological mediators analyzed. All indirect effects were small and showed wide 95% confidence intervals (CIs) that contained zero (eg, for pain-free squats: abduction strength, -0.13; 95% CI: -0.49, 0.23; Tampa Scale of Kinesiophobia, -0.17; 95% CI: -0.64, 0.30). *CONCLUSION: Hip strength improved after hip exercise, yet strength did not mediate improvements in pain and pain-free squats, and alternative psychological mediators were not implicated. [ABSTRACT FROM AUTHOR]