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

Abstract

Background: In 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.

Methods: This 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.

Results: Two 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.

Conclusion: There 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.

Keywords: Complex interventions; Mental health; Randomised controlled trials; Treatment contamination.

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The authors declare that they have no competing interests.

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Figures

Fig. 1

Flow diagram for searching for relevant articles (articles could be excluded for more than one reason)

Fig. 2

Forest plots for four trials that used both individual- and cluster-level randomisation; (P) = primary outcome. a) Clarkson et al. (2009) [36]. Choice of primary outcomes is based on sample size calculation; estimates are adjusted for baseline measures. Larger (more positive) treatment effects indicate benefit. b) Lee & Gay (2011) [37]. Estimates were standardised and calculated from summaries of means and SDs (mothers’ scores only). Larger (more positive) treatment effects indicate benefit. c) Marshall et al. (2004) [38]. Estimates used same adjustments as in the trial publication. Larger (more positive) treatment effects indicate benefit. d) Richards et al. (2008) [39]. Estimates were standardised and calculated from summaries of means and SDs. Larger (more positive) treatment effects indicate benefit