In a systematic review protocol, which activities are typically predefined before reviewing studies?

In a systematic review protocol, which activities are typically predefined before reviewing studies?

• A. Data extraction collects study details (design, population, outcomes); quality appraisal assesses risk of bias; both are predefined in the protocol.
• B. Data extraction is optional and happens after publication.
• C. Quality appraisal is not necessary for systematic reviews.
• D. Data extraction is done by the funding body.

Answer: (A)

In planning a systematic review, key steps are locked in the protocol before you start examining studies. Data extraction and quality appraisal are two of those steps that are typically predefined. Data extraction means specifying in advance exactly what study details you will pull from each included study—things like design, population, interventions, outcomes, and numeric results. Quality appraisal means deciding ahead of time how you will assess risk of bias and which criteria or tools you will use. Defining these methods upfront helps keep the review consistent across reviewers, reduces the chance of cherry-picking data or changing approaches after seeing the results, and makes the process transparent and reproducible. That’s why this option is the best: both data extraction and quality appraisal are planned in the protocol. The other statements are not aligned with standard practice—data extraction isn’t optional or something done only after publication, quality appraisal is a necessary part of systematic reviews, and data extraction isn’t typically done by the funding body.

In planning a systematic review, key steps are locked in the protocol before you start examining studies. Data extraction and quality appraisal are two of those steps that are typically predefined. Data extraction means specifying in advance exactly what study details you will pull from each included study—things like design, population, interventions, outcomes, and numeric results. Quality appraisal means deciding ahead of time how you will assess risk of bias and which criteria or tools you will use. Defining these methods upfront helps keep the review consistent across reviewers, reduces the chance of cherry-picking data or changing approaches after seeing the results, and makes the process transparent and reproducible.

That’s why this option is the best: both data extraction and quality appraisal are planned in the protocol. The other statements are not aligned with standard practice—data extraction isn’t optional or something done only after publication, quality appraisal is a necessary part of systematic reviews, and data extraction isn’t typically done by the funding body.