The Ultimate Guide to Mastering Systematic Literature Reviews: A 10-Step Roadmap
A comprehensive framework for conducting rigorous and transparent research syntheses that deliver impactful insights
Essential SLR Highlights
A systematic literature review requires methodical planning - Following a structured protocol dramatically increases the quality and reproducibility of your research synthesis.
Comprehensive search strategies are the foundation of reliable results - Utilizing multiple databases and documenting your search process is critical for minimizing bias.
Quality assessment of included studies is non-negotiable - The strength of your conclusions depends directly on the rigor of your evaluation of the primary research.
What is a Systematic Literature Review?
A systematic literature review (SLR) is a rigorous, transparent approach to synthesizing research evidence on a specific topic. Unlike traditional narrative reviews, SLRs follow a predefined protocol to minimize bias and ensure comprehensive coverage of existing literature. They are the gold standard for evidence synthesis in many fields, including healthcare, social sciences, and education.
The systematic approach helps researchers collect, evaluate, and synthesize all available evidence relevant to a specific research question. By following a step-by-step process, researchers can produce reliable, reproducible findings that inform practice, policy, and future research directions.
The 10-Step Systematic Literature Review Process
Step 1: Formulate a Clear Research Question
Every effective systematic review begins with a well-defined research question. This question guides the entire review process, from search strategy development to result synthesis. Many researchers use the PICO framework to structure their question:
Population: Who or what is the focus of your research?
Intervention: What intervention or exposure are you examining?
Comparison: What is the alternative to the intervention?
Outcomes: What results are you measuring?
A precise research question narrows your focus and sets clear boundaries for your review. Without this foundation, you risk conducting an unfocused search that yields irrelevant results or misses crucial studies.
Step 2: Develop a Comprehensive Review Protocol
A protocol is essentially a detailed plan that outlines the methods and procedures for your systematic review. Think of it as your research blueprint that documents:
The specific research question
Inclusion and exclusion criteria
Search strategy and information sources
Study selection process
Data extraction methods
Quality assessment approach
Data synthesis plan
Protocol Registration
Registering your protocol on platforms like PROSPERO for health and social care reviews or following Cochrane guidelines for intervention reviews adds transparency and helps prevent duplication. This also demonstrates your commitment to methodological rigor before beginning the review process.
Step 3: Define Inclusion and Exclusion Criteria
Clear eligibility criteria determine which studies will be included in your review. These criteria should be explicit, comprehensive, and directly tied to your research question. Common criteria include:
Study design: Which study types will you include? (e.g., RCTs, cohort studies, case-control studies)
Publication timeframe: What date range will you consider?
Language restrictions: Which languages will you include?
Population characteristics: What specific demographic features are relevant?
Outcome measures: Which specific outcomes must be reported?
Well-defined criteria ensure your review remains focused and manageable while capturing all relevant evidence.
Step 4: Conduct a Comprehensive Literature Search
A thorough literature search is crucial for identifying all relevant studies. This typically involves:
Database Selection
Include multiple databases relevant to your field. Common options include:
PubMed/MEDLINE
Scopus
Web of Science
Embase
CINAHL
PsycINFO
Google Scholar
Search Strategy Development
Create a comprehensive search strategy using:
Keywords and subject headings
Boolean operators (AND, OR, NOT)
Truncation symbols and wildcards
Field-specific search limiters
Additional Sources
Supplement database searches with:
Grey literature (dissertations, conference proceedings)
Reference list checking (snowballing)
Citation tracking
Expert consultations
Document your search process meticulously, including the exact search terms, filters, and date of search for each database. This ensures transparency and reproducibility.
Step 5: Screen Studies for Eligibility
The screening process typically involves two stages:
Initial Screening
Review titles and abstracts to identify potentially relevant studies based on your inclusion criteria. This is often done by at least two independent reviewers to minimize bias.
Full-Text Screening
Obtain and review the full text of potentially relevant studies to make final eligibility decisions. Document reasons for excluding studies at this stage.
Using systematic review software like Covidence, Rayyan, or EPPI-Reviewer can streamline this process and facilitate collaboration among multiple reviewers.
Step 6: Assess the Quality of Included Studies
Evaluating the methodological quality of included studies is essential for determining the reliability of their findings. Various tools are available for quality assessment, including:
Cochrane Risk of Bias Tool: For randomized controlled trials
ROBINS-I: For non-randomized intervention studies
CASP Checklists: For various study designs
JBI Critical Appraisal Tools: For different study types
Newcastle-Ottawa Scale: For cohort and case-control studies
Quality assessment should be performed by multiple reviewers independently, with disagreements resolved through discussion or by a third reviewer.
Step 7: Extract Data from Included Studies
Data extraction involves systematically collecting relevant information from each included study using a standardized form. Common data elements include:
Study characteristics (authors, year, country, design)
Participant details (sample size, demographics)
Intervention/exposure characteristics
Comparison details
Outcome measures and results
Funding sources and conflicts of interest
Using a pilot-tested data extraction form ensures consistency across studies and reviewers. Like screening and quality assessment, data extraction should ideally be performed by multiple reviewers.
Step 8: Analyze and Synthesize Data
Data synthesis can be qualitative, quantitative, or mixed, depending on the nature of your research question and the included studies.
Qualitative Synthesis
When studies are too heterogeneous for statistical combination, a narrative synthesis can summarize findings, identify patterns, and explore relationships among studies.
Quantitative Synthesis (Meta-Analysis)
When appropriate, meta-analysis can statistically combine results from multiple studies to produce a weighted average effect size with increased precision and power.
Consider factors such as statistical heterogeneity, publication bias, and the quality of included studies when interpreting synthesized results.
Step 9: Interpret Results and Draw Conclusions
Interpreting the findings involves considering:
The strength and consistency of evidence
The quality of included studies
The applicability of findings to different contexts or populations
Potential biases in the review process
Agreements and disagreements with other reviews
Your conclusions should directly address your research question and reflect the strength of the available evidence, acknowledging any limitations or uncertainties.
Step 10: Report the Review
The final step is to document your systematic review following established reporting guidelines, such as:
PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
MOOSE: Meta-analysis Of Observational Studies in Epidemiology
ENTREQ: Enhancing Transparency in Reporting the Synthesis of Qualitative Research
A well-structured report typically includes:
A clear title indicating it's a systematic review
An abstract summarizing key information
A detailed introduction establishing context
A comprehensive methods section
Well-presented results, including a PRISMA flow diagram
A thoughtful discussion of findings and implications
A conclusion summarizing key points
Consider updating your review periodically as new evidence emerges to maintain its relevance and value.
Comparing the Complexity of SLR Phases
The radar chart below illustrates the relative complexity, time requirement, and importance of each phase in the systematic review process. Understanding these dimensions can help researchers allocate resources effectively and identify stages that may require additional attention or support.
Systematic Review Process Flow
The mindmap below illustrates the interconnected nature of the systematic review process, showing how each step relates to others and the decision points that guide the journey from research question to final report. Understanding these relationships helps maintain coherence throughout the review process.
Planning your systematic review timeline is essential for successful completion. The table below provides a typical timeframe for each step and indicates the level of workload and number of team members typically required. This can help you plan resources efficiently and set realistic expectations.
Step
Typical Duration
Workload Intensity
Recommended Team Size
Key Challenges
1. Formulate Research Question
1-2 weeks
Moderate
2-3 members
Balancing specificity with feasibility
2. Develop Protocol
2-4 weeks
Moderate
2-3 members
Anticipating methodological issues
3. Define Inclusion/Exclusion Criteria
1-2 weeks
Moderate
2-3 members
Creating criteria that are neither too broad nor too narrow
4. Conduct Literature Search
2-4 weeks
High
1-2 members + librarian
Balancing sensitivity and specificity
5. Screen Studies
4-8 weeks
Very High
2-4 members
Managing large numbers of citations
6. Assess Study Quality
2-4 weeks
High
2-3 members
Resolving assessment disagreements
7. Extract Data
3-6 weeks
Very High
2-3 members
Handling inconsistently reported data
8. Synthesize Data
3-6 weeks
High
1-3 members + statistician
Addressing heterogeneity across studies
9. Interpret Results
2-3 weeks
Moderate-High
All team members
Contextualizing findings appropriately
10. Report Findings
4-8 weeks
High
1-2 primary writers + team review
Meeting reporting guidelines comprehensively
Note: Timeframes can vary significantly based on the scope of the review, team expertise, available resources, and complexity of the topic. Novice teams should allow for additional time, especially in the early phases of the process.
Visual Guide to Systematic Review Process
The following image illustrates the systematic review process flow, highlighting the relationship between different steps and the iterative nature of the review:
Video Tutorial: Conducting a Systematic Review
This comprehensive tutorial by Dr. Amina Yonis walks through the complete process of conducting a systematic literature review, from formulating your research question to writing up the final report. It offers practical guidance on implementing the PRISMA framework and utilizing the PICO model to structure your approach.
Frequently Asked Questions
How long does a typical systematic literature review take to complete?
A comprehensive systematic literature review typically takes 6-12 months to complete from start to finish. The timeline depends on several factors including the scope and complexity of the research question, the volume of literature to be reviewed, the number of team members involved, and their level of experience with systematic review methods. Projects with larger teams and dedicated resources may be completed more quickly, while those conducted by individuals or small teams with other responsibilities may take longer. The screening and data extraction phases usually require the most time, especially for reviews with hundreds or thousands of potentially relevant studies.
What is the difference between a systematic review and a meta-analysis?
A systematic review is a comprehensive, structured approach to identifying, evaluating, and synthesizing all available research on a specific question using explicit, reproducible methods. A meta-analysis is a statistical technique that quantitatively combines the results of similar studies to provide a more precise estimate of the effect of an intervention or exposure. While a systematic review can be conducted without a meta-analysis (using narrative synthesis instead), a meta-analysis is always preceded by a systematic review to identify and select the studies for statistical combination. Not all systematic reviews include meta-analyses, as they may not be appropriate if the included studies are too heterogeneous in terms of populations, interventions, outcomes, or methodologies.
How many team members are needed for a systematic review?
While a systematic review can technically be conducted by a single researcher, best practice suggests involving a team of at least 2-3 members to enhance rigor and reduce bias. Having multiple reviewers is particularly important during the study selection, quality assessment, and data extraction phases, where independent assessments followed by consensus discussions can significantly improve reliability. Larger reviews often benefit from larger teams of 4-6 members with diverse expertise. It's also valuable to include or consult with specific experts such as: a librarian or information specialist for search strategy development, a statistician for meta-analysis, and subject matter experts to provide context and interpret findings appropriately.
What software tools are recommended for managing systematic reviews?
Several specialized tools can streamline the systematic review process:
Covidence: A web-based platform that supports screening, full-text review, risk of bias assessment, and data extraction
Rayyan: A free web application for screening and selection of studies
EPPI-Reviewer: Comprehensive software supporting all stages of the review process
RevMan: Cochrane's Review Manager software, particularly useful for meta-analysis
JBI SUMARI: Software supporting reviews following Joanna Briggs Institute methodology
EndNote, Zotero, or Mendeley: Reference management software helpful for organizing citations
Microsoft Excel or Google Sheets: Useful for data extraction and management
Stata, R, or Comprehensive Meta-Analysis: Software for conducting meta-analyses
The choice of software depends on budget, team preferences, and specific review requirements. Many institutions provide access to subscription-based tools, while others may rely on free or open-source alternatives.
How do I handle disagreements between reviewers during screening or data extraction?
Disagreements between reviewers are common and should be anticipated in your protocol. Best practices for handling disagreements include:
Discussion and consensus: The primary approach is for the disagreeing reviewers to discuss their rationales and reach consensus. This discussion often reveals misunderstandings or oversight.
Third reviewer arbitration: If consensus cannot be reached, a third reviewer (often a senior team member or subject expert) can review the case and make a final decision.
Clear decision rules: Establishing explicit decision rules in advance can help minimize ambiguity.
Pilot testing: Conducting pilot screening or extraction with a small sample of studies allows the team to identify and resolve potential sources of disagreement before the full process.
Documentation: Regardless of how disagreements are resolved, it's important to document the process and decisions made for transparency.
Some review teams also adopt an inclusive approach during screening, where studies with disagreements are included for full-text review to ensure potentially relevant research isn't missed prematurely.