{"title":"A comparison of preprint search aggregators: comprehensive identification of preprints in the information retrieval stage of evidence syntheses.","authors":"Zahra Premji, Sarah McGill, Amy Riegelman","doi":"10.1017/rsm.2026.10101","DOIUrl":null,"url":null,"abstract":"<p><p>This study investigated information retrieval of preprint records in the context of evidence synthesis work and compared 12 sources used to discover preprints. Identification of grey literature is often required or recommended in evidence synthesis guidance, and preprints are categorized as grey literature. The purpose of this work is to inform how and where to search for preprints to maximize coverage (through exploration of preprint server across aggregators and databases) while balancing search efficiency. Authors selected aggregators and databases hosting two or more preprint servers and then tested search functionality and extracted characteristics and features. Authors analyzed and compared the selected sources, tabulated the number of essential features, and created comparison tables reflecting database and aggregator features. The study protocol was registered in Open Science Framework registries. Preprint aggregators and databases differ in their content coverage, and their ability to design a comprehensive and reproducible search strategy. Limitations such as character or word limits for queries, limited advanced search operators, and missing export functionality affect the usability of aggregators for evidence synthesis searches. Ongoing updates to search interfaces and functionality and differing approaches to versioning make it challenging to study discovery of preprints across sources. The recommendations and scenarios in this article will assist searchers engaged in evidence synthesis to make informed decisions about where to search for preprints.</p>","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":" ","pages":"1-26"},"PeriodicalIF":8.0000,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research Synthesis Methods","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1017/rsm.2026.10101","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigated information retrieval of preprint records in the context of evidence synthesis work and compared 12 sources used to discover preprints. Identification of grey literature is often required or recommended in evidence synthesis guidance, and preprints are categorized as grey literature. The purpose of this work is to inform how and where to search for preprints to maximize coverage (through exploration of preprint server across aggregators and databases) while balancing search efficiency. Authors selected aggregators and databases hosting two or more preprint servers and then tested search functionality and extracted characteristics and features. Authors analyzed and compared the selected sources, tabulated the number of essential features, and created comparison tables reflecting database and aggregator features. The study protocol was registered in Open Science Framework registries. Preprint aggregators and databases differ in their content coverage, and their ability to design a comprehensive and reproducible search strategy. Limitations such as character or word limits for queries, limited advanced search operators, and missing export functionality affect the usability of aggregators for evidence synthesis searches. Ongoing updates to search interfaces and functionality and differing approaches to versioning make it challenging to study discovery of preprints across sources. The recommendations and scenarios in this article will assist searchers engaged in evidence synthesis to make informed decisions about where to search for preprints.
期刊介绍:
Research Synthesis Methods is a reputable, peer-reviewed journal that focuses on the development and dissemination of methods for conducting systematic research synthesis. Our aim is to advance the knowledge and application of research synthesis methods across various disciplines.
Our journal provides a platform for the exchange of ideas and knowledge related to designing, conducting, analyzing, interpreting, reporting, and applying research synthesis. While research synthesis is commonly practiced in the health and social sciences, our journal also welcomes contributions from other fields to enrich the methodologies employed in research synthesis across scientific disciplines.
By bridging different disciplines, we aim to foster collaboration and cross-fertilization of ideas, ultimately enhancing the quality and effectiveness of research synthesis methods. Whether you are a researcher, practitioner, or stakeholder involved in research synthesis, our journal strives to offer valuable insights and practical guidance for your work.