RoBDA - RCT-Bias Assessment Tool

Example

Analyzing allocation sequence generation and concealment mechanisms to ensure they adequately prevent foreknowledge of treatment assignments, thus minimizing selection bias.

Scenario

In a trial comparing two hypertension treatments, RoBDA - RCT would evaluate whether the method of randomizing participants effectively prevents researchers and participants from predicting assignments, ensuring comparability between groups.

Example

Examining how deviations from the protocol impact study outcomes and whether the analysis accounts for these deviations appropriately.

Scenario

In a study on diabetes management, RoBDA - RCT would assess how deviations, such as participants not adhering to the intervention protocol, are accounted for in the study's analysis.

Example

Determining the extent of missing data and its potential impact on the reliability and validity of the trial's results.

Scenario

In an RCT on a new cancer therapy, RoBDA - RCT would investigate how much data is missing, why it's missing, and how this affects the interpretation of the treatment's efficacy.

Example

Evaluating the methods used to measure trial outcomes and the blinding of assessors to minimize detection bias.

Scenario

For a trial assessing the effectiveness of a mental health intervention, RoBDA - RCT would scrutinize the objectivity of outcome measurement methods and whether outcome assessors were blinded to treatment allocation.

Example

Reviewing pre-specified plans for data analysis and whether the reported results selectively emphasize favorable findings.

Scenario

In an RCT on a new diet regimen, RoBDA - RCT would examine if the analysis was pre-planned and whether the selection of reported outcomes could introduce bias.