Abstract

Rigorous evidence identification is essential for systematic reviews and meta‐analyses (evidence syntheses) because the sample selection of relevant studies determines a review's outcome, validity, and explanatory power. Yet, the search systems allowing access to this evidence provide varying levels of precision, recall, and reproducibility and also demand different levels of effort. To date, it remains unclear which search systems are most appropriate for evidence synthesis and why. Advice on which search engines and bibliographic databases to choose for systematic searches is limited and lacking systematic, empirical performance assessments. This study investigates and compares the systematic search qualities of 28 widely used academic search systems, including Google Scholar, PubMed, and Web of Science. A novel, query‐based method tests how well users are able to interact and retrieve records with each system. The study is the first to show the extent to which search systems can effectively and efficiently perform (Boolean) searches with regards to precision, recall, and reproducibility. We found substantial differences in the performance of search systems, meaning that their usability in systematic searches varies. Indeed, only half of the search systems analyzed and only a few Open Access databases can be recommended for evidence syntheses without adding substantial caveats. Particularly, our findings demonstrate why Google Scholar is inappropriate as principal search system. We call for database owners to recognize the requirements of evidence synthesis and for academic journals to reassess quality requirements for systematic reviews. Our findings aim to support researchers in conducting better searches for better evidence synthesis.

Keywords

Computer scienceSystematic reviewInformation retrievalUsabilityMetasearch engineRecallData scienceOnline searchMEDLINESearch engineWeb search queryPsychology

MeSH Terms

AlgorithmsBiomedical ResearchDatabasesBibliographicDatabasesFactualInformation Storage and RetrievalInternetMeta-Analysis as TopicPeriodicals as TopicPubMedReproducibility of ResultsResearch DesignSearch EngineSoftwareSystematic Reviews as Topic

Affiliated Institutions

Related Publications

Publication Info

Year
2019
Type
article
Volume
11
Issue
2
Pages
181-217
Citations
1754
Access
Closed

Citation Metrics

1754
OpenAlex
56
Influential

Cite This

Michael Gusenbauer, Neal Haddaway (2019). Which academic search systems are suitable for systematic reviews or meta‐analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources. Research Synthesis Methods , 11 (2) , 181-217. https://doi.org/10.1002/jrsm.1378

Identifiers

DOI
10.1002/jrsm.1378
PMID
31614060
PMCID
PMC7079055

Data Quality

Data completeness: 86%