Summary

We explored how bias—systematic errors in study design, conduct, or reporting—can distort research findings and why addressing it is essential for producing reliable evidence.

Key topics covered:

• Types of bias: Selection bias, performance bias, attrition bias, detection bias, and reporting bias.

• Difference between bias and imprecision: Bias leads to systematic errors, while imprecision results in random errors. Both can impact the validity of findings.

• Assessing risk of bias: Tools like the Cochrane Risk of Bias Tool help systematically evaluate potential biases across studies.

• Study quality assessment: Creating a risk of bias graph and summary for a systematic review involves assessing the methodological quality of the included studies and presenting the findings in a clear and standardised manner.

Understanding these concepts is crucial for conducting and interpreting systematic reviews. By applying structured assessment tools, researchers can ensure higher transparency, reliability, and accuracy in evidence-based decision-making.