How to Write a Systematic Review Protocol for Research Studies
How to Write a Systematic Review Protocol for Research Studies
Introduction
A systematic review protocol is the blueprint for your research. It lays out exactly how you will search, select, analyze, and report evidence, ensuring the review is transparent, reproducible, and free from avoidable bias.
Before starting the actual review, developing a detailed protocol is considered best practice — and in many cases, it’s a requirement for publication in reputable journals or registration in platforms like PROSPERO or Cochrane.
In this guide, we’ll break down how to write a systematic review protocol step-by-step, with tips for healthcare, social sciences, and other fields.
Why a Systematic Review Protocol Is Essential
A protocol ensures:
-
Clarity – Everyone on the research team understands the scope and methods.
-
Consistency – Prevents mid-project changes that could introduce bias.
-
Transparency – Allows peer reviewers and stakeholders to evaluate the process.
-
Reproducibility – Others can replicate the study using your documented methods.
Example:
Without a protocol, one reviewer might change inclusion criteria halfway through, unintentionally altering the review’s conclusions.
Step-by-Step Guide to Writing a Systematic Review Protocol
1. Title and Registration
-
Create a clear, specific title that reflects your research question.
-
Register your protocol with PROSPERO, Open Science Framework (OSF), or relevant registries.
2. Background and Rationale
-
Explain why the review is needed.
-
Summarize existing evidence and identify the gap your review will fill.
Tip: A brief narrative review can be included here to set the context.
3. Research Objectives and Question
-
Use PICO (Population, Intervention, Comparison, Outcome) for quantitative studies.
-
Example: “In older adults (Population), does resistance training (Intervention) compared to balance exercises (Comparison) reduce falls (Outcome)?”
4. Eligibility Criteria
-
Inclusion Criteria: Define study designs, populations, interventions, outcomes, and publication dates to be included.
-
Exclusion Criteria: State what will be excluded and why.
5. Search Strategy
-
List all databases (e.g., PubMed, Cochrane Library, Embase, Scopus).
-
Include keywords, Boolean operators, and controlled vocabulary (e.g., MeSH terms).
-
State if grey literature sources will be searched.
6. Study Selection Process
-
Describe how titles, abstracts, and full texts will be screened.
-
Mention the use of two independent reviewers and conflict resolution methods.
7. Data Extraction
-
Define the data fields to be collected (e.g., study design, sample size, outcomes, follow-up periods).
-
Provide a sample data extraction form in the appendix if possible.
8. Quality Assessment
-
Identify the tool(s) you will use:
-
Cochrane Risk of Bias Tool for RCTs.
-
Newcastle-Ottawa Scale for observational studies.
-
QUADAS-2 for diagnostic accuracy studies.
-
9. Data Synthesis Plan
-
Narrative Synthesis: Explain how qualitative findings will be summarized.
-
Meta-Analysis: Specify statistical models, effect size measures, and heterogeneity tests.
10. Ethics and Dissemination
-
Mention ethical considerations (even if the review uses published data).
-
Describe where you plan to publish — journals, conferences, or online repositories.
Best Practices for Writing a Strong Protocol
-
Be as detailed as possible — vague protocols risk inconsistent execution.
-
Collaborate with subject matter experts and information specialists.
-
Follow guidelines like PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols).
-
Seek peer feedback before starting the review.
Common Mistakes to Avoid
-
Not registering the protocol publicly.
-
Leaving inclusion/exclusion criteria too broad.
-
Forgetting to include grey literature searches.
-
Omitting a plan for handling disagreements between reviewers.
Conclusion
A systematic review protocol is the foundation of a high-quality, credible review. By clearly defining your objectives, methods, and analysis plan before starting, you protect your research from bias and ensure it can withstand peer scrutiny.
In evidence-based practice, transparency isn’t optional — it’s the key to producing findings that others can trust and build upon.