Which bias is most effectively reduced by using blinded assessors and objective endpoints?

• A. Selection bias
• B. Information bias
• C. Observer bias
• D. Attrition bias

Answer: (C)

The key idea here is that blinding who evaluates outcomes prevents their expectations from shaping how results are recorded. When assessors don’t know who received the treatment, they’re less likely to let guesses or hopes influence their judgments, especially for outcomes that require some subjective interpretation. Pairing that with objective endpoints—measurements that are automated or clearly defined—reduces any remaining room for personal interpretation. This combination directly targets bias arising from the observer’s knowledge, known as observer bias.

Selection bias happens before data collection, tied to how participants are chosen or assigned, so blinding assessors doesn’t address that. Information bias is a broader category of errors in data collection, though blinding helps; observer bias is the specific form most directly mitigated by blinded assessment. Attrition bias comes from differential loss to follow-up, which blinding doesn’t specifically fix.