• health services research
• evidence-based practice
• publishing

Bias is generally defined as a systematic error or deviation from the truth in research results, which leads to underestimating or overestimating the true intervention effect or the true effect of any given exposure factor in a specific outcome.1 There are many sources of bias arising from the different stages in research, like the planning and design of a study, the data collection process, statistical analysis, interpretation of results and the publication of the final report.2 A complete catalogue of biases that may affect research, initially developed by David Sackett and regularly refined by the Catalogue of Bias Collaboration can be found at https://catalogofbias.org. In randomised controlled trials, for example, bias has been classified into five general categories: selection, performance, detection, attrition and selective reporting.3 4 As bias can occur both intentionally and unintentionally, there is always some degree of bias in studies, and readers should understand it not as something present or missing in any particular study but as a continuum variable that can be more or less predominant.5 It is usually not possible to know to what extent biases have affected the results of a study and because the results of a study may be unbiased despite methodological flaws, it is more appropriate to consider that a study is at risk of bias (RoB) rather than claiming with certainty that it is biased.1

Assessing RoB targets the question of the extent to which the results of any study should be believed.1 There are several tools for RoB assessment, depending on the design of the studies being considered.6–8 All tools have a similar structure, assessing RoB within specified domains, with signalling questions whose answers flag the potential for bias and requesting the documentation …