How to Use Litmaps for Systematic Review Research

To answer how to use Litmaps for a systematic review: start with a focused review question, add several eligible seed papers, use Litmaps to trace backward citations and forward citations, screen every discovered record against predefined criteria, and document the whole process outside the map.

Litmaps is useful for finding papers your database search may miss. It is not a substitute for a systematic review protocol, database searching, deduplication, eligibility screening, quality appraisal, or a defensible audit trail.

Treat the map as a discovery layer. Your reference manager, screening tool, extraction sheet, and methods log remain the authoritative record.

How to use Litmaps for a systematic review

A safe Litmaps workflow has six parts:

1. Define the review question and eligibility criteria before opening Litmaps.

2. Choose seed papers from documented sources, not from intuition alone.

3. Build a map using multiple seed papers.

4. Trace both backward citations and forward citations.

5. Screen every candidate paper outside the visualization.

6. Report the citation-chasing step transparently in your methods.

The key distinction is this: Litmaps helps you discover and follow citation relationships; it does not decide what belongs in the review.

That matters because citation networks can feel more objective than they are. A paper near the center of a map may be influential, but it may still be outside your population, time period, geography, intervention, outcome, language criteria, or study design.

Before depending on a specific Litmaps button, export option, or plan feature, check the current Litmaps documentation. Tool interfaces change faster than systematic review methods do. The method below is deliberately framed around the workflow, not fragile interface details.

Prepare your review question and seed papers before opening Litmaps

Litmaps works best when the seed papers are already relevant. If the starting set is weak, the map will expand the wrong neighborhood.

Start by translating the review question into explicit concepts. For health and social science reviews, that often means something like population, setting, intervention or exposure, comparator, outcome, and study design. For other fields, use the equivalent structure: phenomenon, domain, method, material, context, and evidence type.

For example:

Review question: What is the effect of remote blood pressure monitoring on medication adherence among adults with hypertension in primary care?

Break it into searchable concepts:

This concept work should happen before the map because it sets the inclusion and exclusion criteria. A citation network can show proximity. It cannot tell whether “remote monitoring” in a heart failure population fits a hypertension review.

Next, choose seed papers through a documented search. Use relevant databases and source-discovery sites for the field, such as PubMed, Scopus, Web of Science, IEEE Xplore, ERIC, PsycINFO, ACM Digital Library, Google Scholar, or discipline-specific indexes. For a broader source-discovery workflow, see Otio’s guide to good websites for research.

Do not pick seed papers only because they look large or central in a visualization. Highly cited papers are often useful, but they can also reflect older terminology, dominant labs, English-language bias, or a review article that does not match your eligibility criteria.

Create a seed-paper log before mapping. A simple spreadsheet is enough.

Include:

• Full citation

• DOI or stable identifier

• Database or source where you found it

• Search string or search route used

• Reason it qualifies as a seed

• Publication type

• Inclusion status at the time of selection

• Notes on duplicates, preprints, corrections, or retractions

• Any relevance concerns

A strong seed set usually includes more than one citation pathway. Avoid building the map from a single famous article if the topic spans several disciplines, methods, populations, or regional literatures.

For the larger review-writing process around question framing, synthesis, and structure, use Otio’s guide on how to write a literature review. Litmaps is one part of that process, not the whole review.

Build a Litmaps map from backward and forward citations

Litmaps is most useful when used for citation chasing. There are two directions:

Backward citation chasing means reviewing the papers cited by your seed paper. This helps find older studies, theoretical foundations, original instruments, prior trials, methods papers, and earlier evidence that shaped the seed.

Forward citation chasing means reviewing later papers that cite your seed paper. This helps find newer studies, replications, critiques, systematic reviews, extensions, and applications in adjacent fields.

A systematic review usually needs both. Backward chasing can recover foundational work; forward chasing can recover recent studies that use newer terminology or cite an important predecessor without matching your exact database query.

Add several independent seed papers to the map. In practical terms, aim for seed papers from different authors, journals, years, and methods where the topic warrants it. If every seed comes from the same lab or citation circle, the resulting network may simply amplify that circle.

Once the map is built, use the visualization to generate leads:

• Papers connected to multiple seeds may be worth screening early.

• Clusters may reveal subtopics, methods, populations, or schools of thought.

• Publication dates can show whether the literature has shifted over time.

• Isolated papers may indicate a separate terminology stream.

• Dense links may point to review articles, canonical studies, or shared methods.

None of these signals equal eligibility. They are triage cues.

Here is a worked example using the hypertension question above.

Hypothetical Litmaps pass

Seed papers

• Seed A: Randomized trial of home blood pressure telemonitoring in adults with hypertension.

• Seed B: Cohort study of remote monitoring and adherence in primary care.

• Seed C: Qualitative study on patient experience with blood pressure self-monitoring.

• Seed D: Review article on digital adherence interventions for chronic disease.

After adding these seeds, Litmaps surfaces candidate records through backward and forward citations.

You might label records like this in your screening log:

The map helps you see connections. The screening log explains the review decisions.

That separation is the difference between a useful citation-chasing step and an undocumented browsing session.

Screen Litmaps results without turning citation prominence into relevance

The most common mistake is treating map position as evidence. It is not.

A central paper may be a methods paper, a background theory article, a broad review, or a landmark study in a different population. A peripheral paper may be a recent eligible study with few citations because it is new, regional, non-English, or published outside the dominant database ecosystem.

Apply the same inclusion and exclusion criteria to every Litmaps candidate that you apply to database-search records.

At minimum, screen in stages:

1. Title and abstract screening

2. Duplicate and version checks

3. Full-text retrieval

4. Full-text eligibility assessment

5. Quality appraisal or risk-of-bias assessment

6. Data extraction

Record exclusion reasons in a structured way. “Not relevant” is usually too vague for a systematic review. Better reasons include:

• Wrong population

• Wrong intervention or exposure

• Wrong comparator

• Wrong outcome

• Wrong study design

• Outside date range

• Not original empirical research

• Not available in required language

• Full text unavailable

• Duplicate record

• Protocol, abstract, commentary, or editorial only

Also check versions. A map may surface a preprint, conference abstract, dissertation, working paper, corrected article, or duplicate publication. Decide in advance how the review will treat each version.

Citation-checking tools can help here, but they do not replace reading. For example, Scite can help examine how later papers cite a study, and Otio has a separate guide on using Scite for citation checking and literature reviews. Citation context can flag support, contrast, or mention patterns, but eligibility and evidence quality still require the original paper.

A useful Litmaps screening log should include:

• Candidate citation

• DOI or stable URL if available

• Litmaps map or project name

• Discovery route: backward, forward, or both

• Seed paper that led to discovery

• Date discovered

• Date screened

• Reviewer decision

• Exclusion reason, if excluded

• Full-text status

• Conflict resolution, if more than one reviewer screened

• Final status: included, excluded, awaiting full text, duplicate, or unresolved

If a review team has two screeners, Litmaps itself should not become the place where final screening happens unless the team has a reliable way to preserve decisions and reviewer independence. A dedicated screening tool is better for blinded title-and-abstract screening.

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Combine Litmaps with database searching and review-management tools

Litmaps should sit beside structured database searching, not replace it.

Database searches are better for reproducible retrieval across controlled vocabulary, fields, filters, and indexed metadata. Citation maps are better for following relationships between papers once some relevant literature is known.

Use both because they fail in different ways.

After a database search and a Litmaps pass, compare the results.

Ask four questions:

1. Which Litmaps records were already found by the database search?

2. Which Litmaps records are unique?

3. Do the unique records use different terminology?

4. Do they suggest a missing database, subject heading, author cluster, or date range?

That comparison can improve the main search strategy. For example, if Litmaps keeps surfacing eligible papers that use “self-measured blood pressure” while the original search used only “home blood pressure monitoring,” revise the database search before final reporting.

Use a reference manager or screening system as the source of truth. Zotero, Mendeley, EndNote, Covidence, Rayyan, EPPI-Reviewer, DistillerSR, and spreadsheets can all play a role depending on the review’s scale and budget. If the immediate task is systematic review screening, see Otio’s guide to using Rayyan for systematic review screening.

If the team uses Otio, use it as a research workspace after discovery: store PDFs, web links, notes, project materials, and source summaries in one library. Otio’s AI PDF reader can help inspect and query full-text papers while keeping the original document visible.

Do not treat any AI workspace as proof of systematic-review compliance. The compliance comes from the protocol, search log, screening records, reproducible decisions, and transparent reporting.

Document and report the Litmaps step in the systematic review

If a paper was discovered through Litmaps, the review methods should say so.

Document the step while doing it, not after the manuscript is drafted. Retrospective reconstruction is where errors creep in: forgotten seed papers, changed filters, missing candidate counts, and unclear exclusion reasons.

Record:

• Litmaps project or map identifier, if available

• Date the map was searched or updated

• Seed-paper selection method

• Full seed-paper list

• Whether backward citations, forward citations, or both were searched

• Filters used, if any

• Number of candidate records retrieved

• How records were exported, saved, or copied into the review library

• Number of duplicates removed

• Number screened

• Number excluded at title/abstract stage

• Number assessed at full text

• Number included

• Exclusion reasons

• Reviewer names or initials, if part of the review process

In the methods section, describe Litmaps as citation chasing or citation-network-assisted discovery. Avoid language that implies the map validated completeness. It did not.

A plain methods sentence might look like this:

Example methods wording: “We conducted supplementary backward and forward citation chasing in Litmaps using eligible seed studies identified from the database search. Candidate records were imported into the review library, deduplicated, and screened against the same eligibility criteria as database records. Search dates, seed records, screening decisions, and exclusion reasons were recorded in the review log.”

For a flow diagram, keep the Litmaps records distinct enough that readers can see what came from database searching versus citation chasing. Then merge them before deduplication or screening, depending on how the team actually processed the records.

The main limitation should be stated clearly: citation-based discovery reflects the structure of existing citations. It can reproduce disciplinary bias, language bias, publisher bias, geography bias, senior-author bias, and citation-age bias. It may miss relevant studies that are poorly indexed, newly published, uncited, published in local journals, or disconnected from the seed set.

When Litmaps is useful—and when another method is better

Litmaps is most useful when a review already has a reliable starting set and needs to expand around it.

Use Litmaps when you need to:

• Find newer papers that cite eligible studies

• Identify older papers that shaped a study’s methods or theory

• Follow research lineages across time

• Spot clusters of related work

• Check whether database searches are missing a terminology stream

• Test whether the review is approaching conceptual saturation

• Find adjacent literature for scoping work before a final systematic search

Prefer structured database searching when you need:

• Reproducible keyword coverage

• Controlled vocabulary searching

• Field-specific search logic

• Protocol-driven reporting

• Comprehensive retrieval across indexed records

• Transparent search strings for peer review

Use Scite or another citation-context tool when the question is not “what else is connected?” but “how has this paper been cited?” Use Rayyan or another screening tool when the main job is blinded, collaborative title-and-abstract screening. Use Zotero, Mendeley, EndNote, or another reference manager when the main job is citation control and deduplication.

The practical next action is simple: run one documented Litmaps citation-chaining pass from several eligible seed papers, then compare the unique Litmaps records with the records from the primary database search. If Litmaps finds eligible studies the database search missed, update the search strategy before calling the review complete.

FAQ

Q: Can Litmaps replace database searching in a systematic review?
A: No. Litmaps can supplement database searches through backward and forward citation chasing, but it should not replace protocol-driven searches needed for reproducible coverage.

Q: Is every paper found through Litmaps suitable for inclusion?
A: No. Each record still needs duplicate checks, eligibility screening, full-text assessment, and quality or risk-of-bias review according to the review protocol.

Q: How many seed papers should I use in Litmaps?
A: Use multiple relevant seed papers selected through a documented search rather than relying on one highly cited article. The right number depends on the scope and maturity of the topic, so record how the seed set was chosen.

Q: What should I record when using Litmaps for a systematic review?
A: Record the seed-paper selection method, search date, citation directions, filters, candidate count, screening decisions, exclusions, and final included records. Preserve the project or map information when possible so the process can be audited.

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Related reading

• How to Write a Literature Review

• Rayyan: How to Use It for Systematic Review Screening

• Scite AI: How to Use Scite for Citation Checking and Literature Reviews

• 22 Good Websites for Research Papers and Academic Articles