Best Practices for Systematic Reviews

🛡️ Why Best Practices Matter in Systematic Reviews

A systematic review is only as strong as its transparency and reproducibility. The gold standard in evidence synthesis, systematic reviews inform policy, practice, and future research. To ensure your review stands up to scrutiny, you must document every step, minimize bias, and make your process replicable.

💡 Pro Tip: The more transparent your process, the more valuable your review is to the research community!

📝 Step 1: Write a Clear, Structured Protocol

Every systematic review should begin with a detailed protocol. This document is your blueprint, outlining:

• The research question (using frameworks like PICO or SPIDER)
• Inclusion and exclusion criteria
• Databases and sources to be searched
• Planned methods for screening, data extraction, and analysis

Register your protocol in a public repository (like PROSPERO) to promote transparency and prevent duplication.

🔍 Step 2: Develop and Document Your Search Strategy

A reproducible search strategy is essential. Best practices include:

• Listing all search terms, synonyms, and truncations
• Documenting Boolean operators and field tags
• Recording any changes or adaptations to search strings
• Presenting the final search strategy in a table for easy copy-paste and reproducibility

PubMed: ("systematic review"[Title/Abstract]) AND ("best practice*"[Title/Abstract]) Scopus: TITLE-ABS("systematic review" AND "best practice")

💡Tip: Save your search history and export it for your appendix or supplementary materials.

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👀 Step 3: Rigorous Screening with Multiple Reviewers

Pilot Screening for Consistency

• Involve at least two independent reviewers for all screening stages.
• Conduct a pilot screening: both reviewers screen the same set (e.g., 100 articles) using agreed inclusion/exclusion criteria.
• Compare results to assess agreement. If discrepancies are high, revisit and clarify your criteria.

Inclusion/Exclusion Criteria

• Make criteria as concrete and unambiguous as possible.
• Document all decisions and reasons for exclusion at each stage.

📊 Step 4: Data Extraction – Practice with a Pilot

• Use a standardized data extraction form or spreadsheet.
• Both reviewers should pilot the extraction on a small sample to ensure consistency.
• Clarify what data should be extracted (study characteristics, outcomes, etc.) before full extraction begins.

✍️ Step 5: Manuscript Writing – Structure and Clarity

Introduction

• Build a clear argument, supported by evidence and references.
• End with a precise research question and objectives.

Methods

• Report exactly what was done: search strategy, screening, data extraction, and analysis.
• Include enough detail for full reproducibility.

Results

• Present only the numbers and outcomes (or qualitative findings).
• Use tables and figures for clarity.

Discussion

• Interpret results in context, referencing supporting and contrasting evidence.
• Discuss limitations and suggest future research directions.

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