Both. literature reviews can be qualitative, quantitative, or mixed; the method matches your research question and the evidence you need.
What A Literature Review Actually Does
A literature review gathers prior studies, judges their quality, and weaves their findings into a clear picture. It can scan a narrow niche or map a wide area. Some reviews crunch numbers. Others distill themes and lived experiences. Many combine both. The shape of the output depends on the kind of data inside the studies you include and the way you combine that data. are literature reviews qualitative or quantitative? That question guides your method choice.
Are Literature Reviews Qualitative Or Quantitative? Use Cases And Limits
Ask two questions. First, what kind of evidence do the studies report. Second, what type of answer do you need. If most papers report numbers such as test scores, risk ratios, or rates, a numeric synthesis fits. If studies report words from interviews, field notes, or policy texts, a thematic synthesis fits. Many topics mix both forms of evidence, so a hybrid design also makes sense. The goal is a fit between question, studies, and synthesis method.
Broad Review Types At A Glance
The table below shows common review types, the kind of data they tend to include, and the output that readers can expect.
| Review Type | Typical Data | Common Output |
|---|---|---|
| Narrative Review | Mixed studies | Expert synthesis and interpretation |
| Scoping Review | Mixed studies | Map of topics, gaps, and study designs |
| Systematic Review | Primarily numeric outcomes | Structured synthesis; may include meta-analysis |
| Qualitative Evidence Synthesis | Interviews, focus groups, texts | Themes, concepts, and experiences |
| Mixed-Methods Review | Both numeric and textual | Integrated narrative with quantitative and qualitative strands |
| Rapid Review | Mixed studies | Time-bounded evidence summary |
| Umbrella Review | Existing reviews | Overview across multiple review findings |
| Integrative Review | Mixed primary research | Conceptual model or synthesized perspective |
Qualitative Reviews: When Words Carry The Signal
Choose a qualitative route when your studies aim to capture meaning, experience, or context. Think interviews with patients about barriers to care, teacher reflections on a curriculum, or policy documents that steer practice. A common approach is a qualitative evidence synthesis, which collects rigorously appraised qualitative studies and produces themes or synthesized statements that speak to context, mechanisms, and lived experience. In health and social care, this style often pairs with an intervention review to connect effect sizes with real-world nuance.
How Qualitative Synthesis Works In Practice
Reviewers frame a focused question, set inclusion rules, and search across databases. They screen studies, appraise quality, extract findings, and code those findings to build themes. One widely used method is meta-aggregation from the JBI program. It groups comparable findings, then builds clear synthesized statements that policy makers and practitioners can act on.
Quantitative Reviews: When Numbers Lead The Answer
Choose a quantitative route when studies report measurable outcomes. Think test scores, survival rates, or adoption counts. Reviewers set strict criteria, extract effect sizes or summary measures, and judge bias. If studies are similar enough, they may run a meta-analysis to estimate a pooled effect. If studies vary a lot, they may provide a structured narrative of numeric findings without pooling. Either way, the output is numeric first, with plain language to help readers use the numbers.
Core Steps You’ll See In Numeric Reviews
Typical steps include protocol registration, a comprehensive search, dual screening, risk-of-bias assessment, and transparent synthesis. Many fields follow the Cochrane Handbook. That guide spells out ways to handle heterogeneity, missing data, and small-study effects. It also outlines how to judge certainty in the body of evidence.
Teams often grade certainty across domains such as risk of bias, inconsistency, indirectness, imprecision, and publication bias. That grading sets the strength of your takeaways and flags where fresh studies would shift the picture.
Why So Many Review Labels Exist
Scholars have named many review types over the years, from narrative and integrative to umbrella and scoping. The labels help set reader expectations clearly. A classic typology maps these labels across aims and methods, which is handy when you’re picking the design that suits your own project.
Mixed Approaches: When The Topic Needs Both
Some questions call for both strands. You might pool outcomes to answer “what works” and then synthesize interviews to show “how and for whom.” Reviewers can run two linked reviews and integrate the findings, or they can plan a mixed-methods synthesis from the start. The integrated product is stronger because it reports size and context together.
Literature Reviews: Qualitative Or Quantitative In Research?
Use the table below as a quick decision aid. Match your purpose to a review type and a preferred synthesis method. Pick the row that mirrors your own aim and the kind of studies you’re seeing. Use plain rules to choose well.
| Your Goal | Best-Fit Review | Synthesis Technique |
|---|---|---|
| Measure effect size | Systematic review | Meta-analysis or structured numeric synthesis |
| Explain experiences | Qualitative evidence synthesis | Meta-aggregation or thematic synthesis |
| Combine numbers and themes | Mixed-methods review | Parallel or sequential integration |
| Map what exists | Scoping review | Descriptive mapping of topics and methods |
| Summarize fast | Rapid review | Streamlined search and appraisal |
| Summarize reviews | Umbrella review | Comparison across multiple reviews |
| Build a concept model | Integrative review | Cross-method synthesis of concepts |
Picking Methods Step By Step
1. Start With A Clear Question
State the problem and who it affects. Define the setting and outcomes. If you aim to test an intervention, you’ll tend toward numeric synthesis. If you aim to understand lived experience or implementation, you’ll tend toward qualitative synthesis. Many projects track both outcomes and experience, which points to a mixed approach.
2. Scan The Evidence You’ve Found
Open ten sample papers from your search. Do they report effect sizes and confidence intervals. Or are they interview studies with rich quotes and thematic findings. Your pool points to the method. Fit the review to the dominant data type, then plan how you’ll handle the minority strand.
3. Choose A Synthesis Path That Matches
For numeric pooling, decide on fixed or random effects, set rules for heterogeneity, and plan subgroup or sensitivity checks only where they make sense. For qualitative synthesis, pick an approach such as meta-aggregation that builds credible, actionable statements from study findings while preserving the original meaning.
4. Write A Protocol And Stick To It
Register your plan, list inclusion criteria, and write out your search strategy, screening steps, and data extraction forms. Keep records of decisions. The protocol protects against drift and makes your process transparent to readers and peer reviewers.
5. Appraise Study Quality
Numeric reviews often use risk-of-bias tools targeted to study design. Qualitative reviews often use critical appraisal checklists that assess congruity between the research question, methods, data collection, and interpretation. Record judgments and use them in your synthesis and confidence statements.
Method Notes Tied To Authoritative Guides
For numeric reviews of interventions, many teams lean on the Cochrane Handbook for standards on data handling and synthesis. For qualitative evidence, the JBI meta-aggregation guidance sets out a clear, transparent path from coded findings to synthesized statements that decision makers can use in policy and practice.
Quality Signals Readers Trust
Regardless of method, readers look for transparent steps. That means a clear search, duplicate screening, accessible reasons for exclusion, and a visible link between included studies and the claims you make. Show study tables, provide a PRISMA flow diagram if you ran a systematic search, and explain how quality judgments fed into your synthesis. Clarity builds trust.
Common Pitfalls And How To Avoid Them
Mixing Apples And Oranges
Don’t pool studies with incompatible designs or outcomes. If settings or measures differ wildly, stick with structured narrative for numbers and keep themes crisp for qualitative strands.
Skipping Appraisal
Every included study needs a quality check. Low-quality input leads to shaky conclusions. Use tools suited to the design and report the results plainly.
Letting The Method Drive The Question
Pick the method after you’ve scanned the evidence and refined the question, not before. The best reviews are shaped by the problem and the data, not by habit.
Practical Example Scenarios
Policy Adoption Outcomes
If studies report uptake rates across regions, a numeric synthesis fits. You’d extract comparable measures and, where suitable, pool them with a meta-analysis to estimate an average effect and range.
Barriers To Program Use
If studies consist of interviews with participants and staff, a qualitative evidence synthesis fits. You’d code findings, build categories, and synthesize them into clear, user-facing statements that explain barriers and enablers.
End-To-End Program View
Some projects need both. You might ask whether a program works on average and also why adoption varies across sites. A mixed-methods review lets you knit numeric and thematic strands into a single, more useful answer.
What To Report So Your Review Is Useful
Give readers your search strings, databases, date ranges, inclusion decisions, and quality judgments. Provide a table of study characteristics. State your synthesis method and show how it connects to your findings. Keep claims tight and matched to the strength of the evidence.
Bottom Line: Pick The Method That Serves The Question
The phrase are literature reviews qualitative or quantitative appears across guides because both routes are valid. Use the one that matches your question and the data you can gather. Many topics gain from mixing the two. Clear reporting, fair appraisal, and a transparent link between studies and claims matter more than the label. Keep methods aligned to aims precisely. When readers ask are literature reviews qualitative or quantitative, your answer gains power when it shows the match between question, sources, and synthesis.