The PRISMA 2020 statement requires systematic review authors to provide a complete account of all information sources searched, including grey literature. Transparent reporting of your grey literature search strategy is not optional; it is a requirement for publication in most journals. For a complete walkthrough of PRISMA reporting requirements, see our PRISMA 2020 guidelines explained.
In the Methods section of your manuscript, you should report the following for each grey literature source:
- Name of the source (e.g., ClinicalTrials.gov, ProQuest Dissertations and Theses Global, WHO ICTRP)
- Date the search was conducted (specific to each source, as you may search different sources on different days)
- Search terms and strategy used (exact keywords, filters, and any limitations applied)
- Number of records retrieved from each source
- Any contact with study authors or experts and the outcomes of those contacts
In the PRISMA flow diagram, grey literature records should be reported separately from database records. PRISMA 2020 introduced a revised flow diagram with a dedicated box for "Records identified from other sources," which includes grey literature databases, trial registries, citation searching, and expert contacts. This separation allows readers to see how much of your evidence base came from non-traditional sources.
In the search strategy appendix, include the complete search strings for each grey literature source, just as you would for PubMed or Embase. Even if the search was a simple keyword search, documenting it verbatim enables other researchers to reproduce your work.
Common documentation mistakes to avoid:
- Listing "grey literature was searched" without specifying which sources were searched
- Failing to record the date of each search
- Not distinguishing grey literature results from database results in the flow diagram
- Omitting grey literature sources from the search strategy appendix
- Searching Google Scholar without documenting the number of results screened and the screening method (since Google Scholar can return tens of thousands of results, you must specify how many were screened, typically the first 200 to 300 results sorted by relevance)
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Grey literature has not undergone traditional peer review, which raises legitimate questions about its quality and reliability. However, excluding grey literature entirely introduces a different type of bias: the systematic omission of evidence that may be methodologically sound but simply unpublished. The solution is to include grey literature while applying appropriate quality assessment.
Apply the same risk of bias tools you use for published studies. If you are using the Cochrane Risk of Bias tool (RoB 2) for randomized trials or ROBINS-I for non-randomized studies, apply these tools to grey literature studies just as you would to published ones. A conference abstract reporting a well-conducted randomized trial should be assessed on the same criteria as a journal article reporting the same trial design.
Use AACODS for non-research grey literature. The AACODS checklist (Tyndall, 2010) was developed specifically for appraising grey literature. It evaluates six dimensions: Authority (who produced the document and what are their credentials), Accuracy (is the information supported by evidence), Coverage (are limitations stated), Objectivity (is there potential bias), Date (is the information current), and Significance (is the source relevant to your review question). AACODS is particularly useful for government reports, organizational publications, and technical documents that do not fit the mold of traditional clinical research.
Conduct sensitivity analyses. After including grey literature in your synthesis, run a sensitivity analysis that compares results with and without grey literature studies. If the pooled effect changes substantially when grey literature is excluded, this finding is itself informative: it suggests that published studies alone may overestimate or underestimate the true effect. Report these sensitivity analyses transparently.
Acknowledge limitations explicitly. In the Discussion section of your manuscript, address the quality of included grey literature. Note which studies were conference abstracts (and therefore provide limited methodological detail), which were theses (and therefore underwent committee review but not journal peer review), and which were regulatory documents (and therefore contained data reviewed by regulatory scientists). This nuanced discussion demonstrates methodological awareness without dismissing grey literature entirely.
Handle incomplete data proactively. Grey literature sources, particularly conference abstracts, often report limited data (e.g., effect sizes without confidence intervals, or sample sizes without detailed outcome data). Contact the study authors to request complete data. Document these attempts and their outcomes. If data remain incomplete, consider including the study in a narrative synthesis while excluding it from quantitative meta-analysis, and explain this decision in your manuscript.
Peer reviewers frequently raise questions about grey literature inclusion. Anticipating these questions and addressing them in your manuscript strengthens your submission and reduces the likelihood of revision requests.
"Why did you include unpublished studies?" The answer is methodological: excluding unpublished studies introduces publication bias, which the Cochrane Handbook and PRISMA 2020 both recognize as a threat to review validity. Cite the empirical evidence showing that meta-analyses excluding grey literature overestimate effects.
"How did you assess the quality of grey literature?" Describe the specific tools you used (RoB 2, ROBINS-I, AACODS, or others appropriate to your review). Explain that grey literature studies were assessed using the same criteria as published studies, or describe the alternative appraisal framework used for non-research documents.
"Conference abstracts provide insufficient methodological detail. How can you assess risk of bias?" Acknowledge this limitation honestly. State that you contacted authors for additional information and report the response rate. Note that conference abstracts were included to reduce publication bias and that sensitivity analyses explored their impact on the pooled results.
"Did the inclusion of grey literature change your results?" Report your sensitivity analysis. If results were robust to the exclusion of grey literature, this strengthens confidence in your findings. If results changed, this demonstrates that publication bias was present and that grey literature inclusion provided a more accurate estimate.
"How did you search Google Scholar systematically?" Explain your protocol: the exact search terms used, the number of results screened (commonly the first 200 to 300 results sorted by relevance), and the screening criteria applied. Reviewers want to see that your Google Scholar search was reproducible and bounded, not an unstructured browse.
"Is grey literature of lower quality than published literature?" Not necessarily. Some grey literature, such as FDA medical reviews and Cochrane protocol data, undergoes rigorous scrutiny by regulatory scientists or methodologists. Theses and dissertations are reviewed by academic committees. The distinction between "published" and "grey" reflects distribution channels, not inherent quality differences.
For a comprehensive understanding of how to construct your overall search approach, including database selection, search term development, and grey literature integration, see our complete search strategy guide.
