Analysis & synthesisEvidence synthesisPolicy developmentResearch gapsSystematic reviewEBPM

Evidence Gap Map

Evidence Gap Map
Also known as: EGM、Evidence gap mapping、Evidence map

Systematically searches and classifies research to display where evidence exists and is missing within a framework such as interventions and outcomes. Distinguish this from conclusions about effects. [1]

Difficulty
Advanced
Cost
Medium
Duration
Planning example, not a universal standard duration: 2–6 weeks for a small map; 2–6 months for a full version
Content updated: 2026-09-13Source checked: 2026-09-13 (includes AI cross-checking)No documented human reviewIncludes fictional examples

How it works at a glance

An evidence gap map defines scope and categories before searching and organizing which evidence exists in which areas. It helps users locate relevant studies and consider priorities for new research. [1]

An empty cell means eligible studies were not found within the specified search scope, not that an effect is absent. Even evidence-rich areas should not be judged effective without checking study quality and population differences. [1]

  1. Define scope and questions
  2. Design matrix axes
  3. Develop the search strategy
  4. Screen literature
  5. Code quality and characteristics
  6. Interpret gaps and dense areas
Sequence of implementation steps. See “Implementation steps” for details of each stage.

When to use it and when it is unsuitable

When to use it

  • When seeking an overview of existing evidence in a new program or policy area
  • When prioritizing topics for further evaluation or research investment
  • When developing an evidence-building strategy in a grant-making foundation, government or research institution
  • When separating existing knowledge from untested issues before evaluation planning

When it is unsuitable

  • When seeking field information for short-term improvement of a single program
  • When arrangements for searching, screening and assessing literature quality are unavailable

Participants, roles, and deliverables

Participants and roles

Evaluators, literature reviewers, subject specialists and policy staff. Separating search and classification roles improves reliability even for a small map.

Main deliverables

  • Evidence Gap Map
  • Literature register
  • Priorities for further evaluation and research

Implementation steps

  1. Define scope and questions
    Define the field, interventions, outcomes, countries or areas, publication types and period. Excessively broad scope becomes unworkable.
  2. Design matrix axes
    Develop intervention and outcome categories at a level practitioners can use. Avoid excessive overlap.
  3. Develop the search strategy
    Document databases, institutional websites, grey literature, search terms and exclusion criteria. Record search dates for reproducibility.
  4. Screen literature
    Select eligible literature through titles, abstracts and full texts. Improve consistency through review by 2 people or sample checks.
  5. Code quality and characteristics
    Code study design, population, area, outcomes, quality assessment and main conclusions, and place studies in the matrix.
  6. Interpret gaps and dense areas
    Discuss with stakeholders areas without evidence, areas needing review and priorities for additional evaluation.

Strengths and limitations

Strengths

  • Visualizes the distribution of existing evidence.
  • Avoids duplicate evaluation or research investment and directs resources to gaps.
  • Produces findings that are easy to explain to policy-makers and funders.
  • Particularly valuable upstream of learning agendas or evaluation plans.

Limitations

  • Shows whether studies exist, but cannot independently establish effects.
  • Visible gaps depend on search scope and category design.
  • A full version requires literature review and quality assessment expertise.

Common pitfalls

  • Misreading abundant evidence on the map as proof of effectiveness
  • Producing an irreproducible evidence map without documenting the search strategy
  • Using excessively detailed categories that practitioners cannot use

Conditions of use and evidence

  • Distinguish absence of evidence from absence of effects, and show search scope and study content. [1]
Fictional example; not actual results

Locate learning support research in a small matrix

A fictional illustrative example with invented study counts to explain the method, not actual papers.

InterventionStudies of attendanceStudies of sense of security
Transport support20
Individual learning support31

Common errors in judgment

Common mistake

Judging effectiveness by the number of studies

How to revise

Check designs, quality, populations and effect content separately.

ReasonCounts do not include findings' direction or credibility.

Common mistake

Labeling an empty cell “No effect”

How to revise

Label it “No eligible studies found.”

ReasonAn unresearched issue differs from evidence of no effect.

References and checked sections

  1. Strategic evidence creation and use with evidence and gap maps
    Campbell Collaboration · 2018
    Section consulted
    Evidence and gap maps
    How it relates to the text
    Distinguish absence of evidence from absence of effects, and show search scope and study content.
    Source checked: (includes AI cross-checking)

Editorial and checking information

Content updated: Source checked: (includes AI cross-checking)No documented human reviewIncludes fictional examplesEditorial policy and scope of checkingCite this pageReport a correction

How to cite this page

EvalCompass Editorial Team. “Evidence Gap Map”. EvalCompass, updated 2026-09-13. https://evalcompass.jun-nakatani.com/en/methods/evidence-gap-map/
Add the date you accessed the page. Text created by this site is available under CC BY 4.0. Quotations, external materials, and bundled fonts have their own terms of use. When reusing content, credit the source, link to the license, and indicate any changes.

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Change history
  • — Checked sources for definitions and applicability conditions, and added fictional examples, reasons for judgments and examples for every worksheet field. Revised unverified claims about history and adoption. Also reviewed existing procedures and cautions, and adjusted fixed participant counts and thresholds and generalizations about institutions.