Konstantinos I. Bougioukas, Theodoros Diakonidis, Anna C. Mavromanoli, Anna-Bettina Haidich
{"title":"ccaR:在概述中评估系统综述中主要研究重叠部分的一揽子方案","authors":"Konstantinos I. Bougioukas, Theodoros Diakonidis, Anna C. Mavromanoli, Anna-Bettina Haidich","doi":"10.1002/jrsm.1610","DOIUrl":null,"url":null,"abstract":"<p>An overview of reviews aims to collect, assess, and synthesize evidence from multiple systematic reviews (SRs) on a specific topic using rigorous and reproducible methods. An important methodological challenge in conducting an overview of reviews is the management of overlapping data due to the inclusion of the same primary studies in SRs. We present a free, open-source R package called ccaR (https://github.com/thdiakon/ccaR) that provides easy-to-use functions for assessing the degree of overlap of primary studies in an overview of reviews with the use of the corrected cover area (CCA) index. A worked example with and without consideration of chronological structural missingness is outlined, illustrating the steps involved in, calculating the CCA index and creating a publication-ready heatmap. We expect ccaR to be useful for overview authors, methodologists, and reviewers who are familiar with the basics of R and contribute to the discussion on different methodological approaches for implementing the CCA index. Future research and applications could further investigate the functionality or potential limitations of our package and other potential uses.</p>","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":"14 3","pages":"443-454"},"PeriodicalIF":5.0000,"publicationDate":"2022-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"ccaR: A package for assessing primary study overlap across systematic reviews in overviews\",\"authors\":\"Konstantinos I. Bougioukas, Theodoros Diakonidis, Anna C. Mavromanoli, Anna-Bettina Haidich\",\"doi\":\"10.1002/jrsm.1610\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>An overview of reviews aims to collect, assess, and synthesize evidence from multiple systematic reviews (SRs) on a specific topic using rigorous and reproducible methods. An important methodological challenge in conducting an overview of reviews is the management of overlapping data due to the inclusion of the same primary studies in SRs. We present a free, open-source R package called ccaR (https://github.com/thdiakon/ccaR) that provides easy-to-use functions for assessing the degree of overlap of primary studies in an overview of reviews with the use of the corrected cover area (CCA) index. A worked example with and without consideration of chronological structural missingness is outlined, illustrating the steps involved in, calculating the CCA index and creating a publication-ready heatmap. We expect ccaR to be useful for overview authors, methodologists, and reviewers who are familiar with the basics of R and contribute to the discussion on different methodological approaches for implementing the CCA index. Future research and applications could further investigate the functionality or potential limitations of our package and other potential uses.</p>\",\"PeriodicalId\":226,\"journal\":{\"name\":\"Research Synthesis Methods\",\"volume\":\"14 3\",\"pages\":\"443-454\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2022-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Research Synthesis Methods\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jrsm.1610\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research Synthesis Methods","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jrsm.1610","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}
ccaR: A package for assessing primary study overlap across systematic reviews in overviews
An overview of reviews aims to collect, assess, and synthesize evidence from multiple systematic reviews (SRs) on a specific topic using rigorous and reproducible methods. An important methodological challenge in conducting an overview of reviews is the management of overlapping data due to the inclusion of the same primary studies in SRs. We present a free, open-source R package called ccaR (https://github.com/thdiakon/ccaR) that provides easy-to-use functions for assessing the degree of overlap of primary studies in an overview of reviews with the use of the corrected cover area (CCA) index. A worked example with and without consideration of chronological structural missingness is outlined, illustrating the steps involved in, calculating the CCA index and creating a publication-ready heatmap. We expect ccaR to be useful for overview authors, methodologists, and reviewers who are familiar with the basics of R and contribute to the discussion on different methodological approaches for implementing the CCA index. Future research and applications could further investigate the functionality or potential limitations of our package and other potential uses.
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.