This project develops a web application to generate sample characteristics tables, enhancing generalizability in metaresearch.
Publications reporting research conducted on human participants, such as clinical trials,commonly include a table summarising the relevant characteristics of the study participants.These tables are crucial to compare studies, assess generalisabillity and identify understudiedpopulations. In metaresearch and evidence syntheses, where the sample is instead comprisedof research papers, tables describing features such as the proportion of open access papers,publication language, or authors’ gender are uncommon. Collating these additionalcharacteristics manually would require substantial time and resources. Without thisinformation, however, our understanding of the generalisability of study findings is limited.Furthermore, researchers cannot compare sample characteristics across studies or assess theimpact of different sampling methods. This project aims to: 1) propose a standard samplecharacteristics table structure for studies performed on research papers, 2) determine which ofthese characteristics can be assessed by automated tools, and 3) create a web application thatallows researchers to quickly generate a sample characteristics table using existing automatedtools. We will share progress by updating this preprint as we complete these goals, allowingothers to provide feedback and contribute. We hope that this project will mainstream samplecharacteristics reporting for studies on research papers, stimulate automated tool developmentto fill gaps, and facilitate studies on sample characteristics and generalisability in metaresearch.
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Zellers et al. (2025) studied this question.
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