Risk of Bias in Cluster Randomised Controlled Trials of Individual-Level Interventions: Protocol for a Semi-Structured Interview Study

Abstract

Background Many cluster randomised trials of individual-level interventions are at risk of bias, mostly due to identification and recruitment biases, which would not feature under individual randomisation. This bias arises when participants are recruited into the trial with knowledge of the treatment arm they’ve been allocated to. These trials are also at risk of other biases including lack of clear documentation of primary outcome and apparent unconcealed randomisation. Many of these other risks are easily surmountable, and might reflect poor reporting rather than poor practice, or signal lack of knowledge. Objectives To determine whether investigators are aware of the common sources of risks of bias in cluster trials, and methods to mitigate these risks. We will explore why these biases occur in light of what is known about preventing them and what enables these risks to be mitigated. We will also explore the reasons for adopting cluster randomisation. Setting Principal investigators, statisticians and trialists with experience in conducting cluster randomised trials identified via an existing sampling frame of 104 contemporary cluster trials of individual-level interventions. Methods A realist approach will be used to underpin this study. We will conduct semi-structured interviews over Zoom to identify the rationale behind using a cluster trial when the intervention is at the level of the individual, and knowledge of the importance of blinding for those identifying and recruiting participants. Data collected from the interviews will be analysed using thematic analysis. Themes within the data will be mainly captured with the research question in mind but will remain flexible. Anticipated results We aim to understand the reasons why cluster trials are being conducted when they are at risk of bias. It is hoped that understanding these reasons will provide useful information so future cluster trialists are aware of these risks, and provided with practical solutions.