Introduction
Randomised controlled trials (RCTs) provide high-quality evidence to inform practice. However, much routine care is not based on available RCT evidence. Understanding this disconnect may improve trial design, reporting and implementation. Published literature commenting on RCTs may yield relevant insights. This protocol presents a new approach examining how researchers understand, contextualise and use evidence from RCTs, through analysis of letters, editorials and discussion pieces citing individual RCTs. Surgical case studies will illustrate its ability to identify wide-ranging factors influencing application of trials evidence.
Methods and analysisIn-depth study of published literature will explore written responses to RCTs. After purposefully selecting individual RCTs, we will systematically identify all citing articles covered in Web of Science and Scopus. Editorials, discussions and letters will be included. These are considered most likely to provide critiques and opinions about index RCTs. Original articles and reviews will be excluded. Clinical specialty, RCT design, outcomes and bibliographical data will be collected for RCTs and citing articles. Citing articles will be thematically analysed using the constant comparison technique to explore author understanding, contextualisation and relationship to clinical practice for the index trial. Coding will include generic issues relevant to all RCTs, such as sample size or blinding, and features specific to surgery, such as learning curve. Index trial quality will be examined using validated tools. Results will be combined to create a broad overview of the understanding and use of RCT evidence.
Ethics and disseminationThis study involves secondary use of existing articles and does not require ethical approval. Pilot work will establish its feasibility and inform progression to larger scale utilisation across a broad range of RCTs. Findings will be published in a peer-reviewed journal and presented at surgical and methodological conferences. Results will guide future work on trial design to optimise implementation of results.
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