Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…

RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…

Evidence-based medicine (EBM) is helpful for laypersons' decision-making. This study aimed to evaluate the effectiveness of e-learning materials on the essential components of EBM for laypersons. We conducted a web-based, open-label, randomized controlled trial with laypersons in Japan aged [greater than or equal to]20 years who used the internet.…

Many randomized controlled trials have investigated the role of school-based prevention interventions to reduce symptoms of anxiety and depression in young people. Systematic reviews have subsequently demonstrated a small, beneficial effect of these interventions when compared to a combined control group including usual care, no intervention, or…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…