Contamination in trials: is cluster randomisation the answer?

Most randomised trials allocate individual participants to different treatments. However, cluster randomised trials in which groups of subjects are allocated to different treatments are becoming increasingly popular.1 Cluster randomisation is often advocated to minimise treatment “contamination” between intervention and control participants. For example, in a trial of dietary change, people in the control group might learn about the experimental diet and adopt it themselves.

Contamination of control participants has two related effects. It reduces the point estimate of an intervention's effectiveness and this apparent reduction may lead to a type II error—that is, rejection of an effective intervention as ineffective because the observed effect size was neither statistically nor clinically significant.

Although the threat of contamination is an issue in some controlled trials, it may be not be of much practical importance in many. Trialists should use individual randomisation if possible because of the drawbacks of cluster allocation. Cluster trials are associated with problems of recruitment bias and the need for larger samples than would be required in similar, individually randomised trials. In recruitment bias, different sorts of participants are selected into the various arms of the trial, thereby defeating the objective of randomisation, while a larger sample size may increase the cost of a trial, its length, or its complexity. This paper describes the difficulties of cluster trials and argues that the problem of contamination can often be dealt with by individual randomisation.