Background: Current assessment tools focus on the methods that are commonly used in trials to reduce bias. However, these methods minimize but do not guarantee lack of bias. It is important that sources of bias are assessed too. Moreover, many reviewers do not have in-depth knowledge of trial methods.
Objectives: The aim of our paper is to show how reviewers can use their content knowledge to identify bias in trials.
Methods: We introduce causal diagrams (DAGs) to illustrate how structural bias occurs as result of baseline differences, incorrect outcome measurement, and attrition. Selective reporting is, by exclusion, the fourth source of bias.
Results: According to source of bias, we illustrate with examples how content knowledge allows the identification of (potential) bias, even if important trial methods such as randomization have been applied correctly. We also show how causal diagrams can help to understand the goals and proper use of trials methods.
Conclusions: Reviewers can use their medical or other content knowledge to assess sources of bias in trials. Causal diagrams complement the definitions for correct application of trial methods in current assessment tools.