Types and sources of bias

Bias is a critical factor that affects the validity and reliability of research findings.

Unlike random errors, which occur unpredictably, bias systematically skews results, leading to potentially misleading conclusions.

Why does bias matter?

Bias can distort study outcomes, making research appear more reliable than it actually is. In systematic reviews, addressing bias is essential to ensure that findings reflect the true effects of an intervention or exposure.

Common types of bias in research

1. Selection bias

• Occurs when there are systematic differences in baseline characteristics between comparison groups.

Example: If one group is healthier than another at the start of a study, results may not accurately reflect the intervention’s impact.

• Prevention: Randomisation and proper allocation concealment.

2. Performance bias

• Arises when one group receives different care or attention aside from the studied intervention.

Example: If researchers or healthcare providers treat one group more favourably, outcomes may be influenced.

• Prevention: Blinding participants and researchers to treatment allocation.

3. Attrition bias

• Occurs when there are systematic differences in participant dropout rates between groups.

Example: If more participants withdraw from one group due to adverse effects, results may not be representative of the original study population.

• Prevention: Careful follow-up and intention-to-treat analysis.

4. Detection bias

• Happens when outcome assessment differs systematically between groups.

Example: A researcher knowing which participants received the intervention may subconsciously assess them more favourably.

• Prevention: Blinding outcome assessors.

5. Reporting bias

• Arises when certain study findings are selectively reported while others are omitted.

Example: Studies publishing only significant results while ignoring negative or non-significant findings.

• Prevention: Pre-registering study protocols and using comprehensive reporting guidelines.

Addressing bias in systematic reviews

To improve the credibility of research findings, systematic reviews should:

• Use risk of bias assessments to evaluate the quality of included studies.

• Ensure rigorous study designs that minimize systematic errors.

• Promote transparent reporting of all findings, whether significant or not.

Bias can significantly affect the trustworthiness of research. By recognising its types and sources, researchers can take proactive steps to minimise bias, ensuring that their work contributes to high-quality and reliable evidence.