{"title":"Tracing data for systematic reviews and meta-analyses in the advanced age of digital and social media","authors":"Nishadi Gamage, P. Ranasinghe, R. Jayawardena","doi":"10.1177/26320843231162587","DOIUrl":null,"url":null,"abstract":"Background When conducting reviews, obtaining unreported information by contacting corresponding authors via traditional methods of correspondence, such as email/postage has become increasingly challenging. Objective/s The current study aimed to identify the different non-traditional sources and approaches to obtain unreported data from respective authors of primary studies eligible for systematic reviews and meta-analyses. Methods Unreported data were obtained initially through traditional methods (email/telephone, searching forward citations of the articles, review of other publications of the same research team and perusal of authors’ institutional profiles). The second stage included communication through digital/social media, which comprised Facebook, ResearchGate, WhatsApp, Viber, LinkedIn, and the online Global Health Data Exchange (GHDx). Results During data extraction, 41 individual data items were missing/unreported, and we were able to identify 36 (87.8%) during data tracing, using both traditional (n = 10, 27.8%) and digital and social media-based (n = 26, 72.2%) methods. These 26 data items were identified through the following methods, (a) Facebook (n = 6), (b) ResearchGate (n = 3), (c) WhatsApp (n = 3), (d) Viber (n = 1), (e) LinkedIn (n = 1) and GHDx database (n = 12). Conclusion Digital/social media platforms were found to be more successful to obtain unreported data. We believe that a combination of both methods is likely to yield the best results in tracing missing data for systematic reviews. Journals should consider including social media links and non-institutional research profiles in addition to traditional methods for correspondence.","PeriodicalId":74683,"journal":{"name":"Research methods in medicine & health sciences","volume":"4 1","pages":"136 - 139"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research methods in medicine & health sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/26320843231162587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background When conducting reviews, obtaining unreported information by contacting corresponding authors via traditional methods of correspondence, such as email/postage has become increasingly challenging. Objective/s The current study aimed to identify the different non-traditional sources and approaches to obtain unreported data from respective authors of primary studies eligible for systematic reviews and meta-analyses. Methods Unreported data were obtained initially through traditional methods (email/telephone, searching forward citations of the articles, review of other publications of the same research team and perusal of authors’ institutional profiles). The second stage included communication through digital/social media, which comprised Facebook, ResearchGate, WhatsApp, Viber, LinkedIn, and the online Global Health Data Exchange (GHDx). Results During data extraction, 41 individual data items were missing/unreported, and we were able to identify 36 (87.8%) during data tracing, using both traditional (n = 10, 27.8%) and digital and social media-based (n = 26, 72.2%) methods. These 26 data items were identified through the following methods, (a) Facebook (n = 6), (b) ResearchGate (n = 3), (c) WhatsApp (n = 3), (d) Viber (n = 1), (e) LinkedIn (n = 1) and GHDx database (n = 12). Conclusion Digital/social media platforms were found to be more successful to obtain unreported data. We believe that a combination of both methods is likely to yield the best results in tracing missing data for systematic reviews. Journals should consider including social media links and non-institutional research profiles in addition to traditional methods for correspondence.