A scoping review of the problems and solutions associated with contamination in trials of complex interventions in mental health

Nicholas Magill,Ruth Knight,Paul Mccrone,Khalida Ismail,Sabine Landau

doi:10.1186/s12874-018-0646-z

Abstract

BackgroundIn a randomised controlled trial, contamination is defined as the receipt of active intervention amongst participants in the control arm. This review assessed the processes leading to contamination, its typical quantity, methods used to mitigate it, and impact of use of cluster randomisation to prevent it on study findings in trials of complex interventions in mental health.MethodsThis is a scoping review of trial design approaches and methods of study conduct to address contamination. Studies included were randomised controlled trials of complex interventions in mental health that described the process leading to, amount of, or solution used to counter contamination. The Medline, Embase, and PsycInfo databases were searched for trials published between 2000 and 2015. Risk of bias was assessed using the Jadad score and domains recommended by Cochrane plus some relevant to cluster randomised trials.ResultsTwo hundred and thirty-four articles were included in the review. The main processes that led to contamination were health professionals delivering both active and comparator treatments and communication among clinicians and participants from the different trial arms. Twenty-three trials (10%) measured binary treatment receipt in the control arm with median 13% of participants found to be contaminated (IQR 5–33%). The most common design approach for dealing with contamination was the use of cluster randomisation (n = 93). In addition, many researchers used simple trial conduct methods to minimise contamination due to suspected contamination processes, such as organising for each clinician to provide only one treatment and separating trial arms spatially or temporally. There was little evidence for a relationship between cluster randomisation to avoid contamination and size of treatment effect estimate.ConclusionThere was some evidence of modest levels of treatment contamination with a large range, although a minority of studies reported the amount of contamination. A limitation was that many trials described the problem in little detail. Overall there is a need for greater measurement and reporting of treatment receipt in the control arm of trials. Researchers should be aware of trial conduct methods that can be used to minimise contamination without resorting to cluster randomisation.

Highlights

In a randomised controlled trial, contamination is defined as the receipt of active intervention amongst participants in the control arm
Treatment contamination is defined as the receipt of active intervention amongst participants in the control arm of a randomised controlled trial (RCT) [1]
The aims of this article were fourfold: to identify the processes that are considered to lead to contamination in trials of complex interventions in mental health, to quantify typical levels of contamination, to summarise what researchers do in order to prevent or mitigate it, and to compare treatment effect estimates within trials of complex interventions that used both cluster- and individual-level treatment allocation to quantify the contamination bias

Summary

Introduction

In a randomised controlled trial, contamination is defined as the receipt of active intervention amongst participants in the control arm. Treatment contamination is defined as the receipt of active intervention amongst participants in the control arm of a randomised controlled trial (RCT) [1]. Psychological therapies are complex interventions that comprise several interacting constituent parts [2]. Such intervention components are often transportable and difficult to confine, meaning that their receipt by participants within the control arm is possible. The effect of contamination is to make the control arm more similar to the active intervention arm, i.e. to dilute the treatment contrast. This is a concern to researchers because the contrast between the randomised groups (intention-to-treat estimator) will be biased for the effect of treatment receipt (efficacy)

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