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      The Use of Social Media for Health Research Purposes: Scoping Review

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          Abstract

          Background

          As social media are increasingly used worldwide, more and more scientists are relying on them for their health-related projects. However, social media features, methodologies, and ethical issues are unclear so far because, to our knowledge, there has been no overview of this relatively young field of research.

          Objective

          This scoping review aimed to provide an evidence map of the different uses of social media for health research purposes, their fields of application, and their analysis methods.

          Methods

          We followed the scoping review methodologies developed by Arksey and O’Malley and the Joanna Briggs Institute. After developing search strategies based on keywords (eg, social media, health research), comprehensive searches were conducted in the PubMed/MEDLINE and Web of Science databases. We limited the search strategies to documents written in English and published between January 1, 2005, and April 9, 2020. After removing duplicates, articles were screened at the title and abstract level and at the full text level by two independent reviewers. One reviewer extracted data, which were descriptively analyzed to map the available evidence.

          Results

          After screening 1237 titles and abstracts and 407 full texts, 268 unique papers were included, dating from 2009 to 2020 with an average annual growth rate of 32.71% for the 2009-2019 period. Studies mainly came from the Americas (173/268, 64.6%, including 151 from the United States). Articles used machine learning or data mining techniques (60/268) to analyze the data, discussed opportunities and limitations of the use of social media for research (59/268), assessed the feasibility of recruitment strategies (45/268), or discussed ethical issues (16/268). Communicable (eg, influenza, 40/268) and then chronic (eg, cancer, 24/268) diseases were the two main areas of interest.

          Conclusions

          Since their early days, social media have been recognized as resources with high potential for health research purposes, yet the field is still suffering from strong heterogeneity in the methodologies used, which prevents the research from being compared and generalized. For the field to be fully recognized as a valid, complementary approach to more traditional health research study designs, there is now a need for more guidance by types of applications of social media for health research, both from a methodological and an ethical perspective.

          International Registered Report Identifier (IRRID)

          RR2-10.1136/bmjopen-2020-040671

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          Most cited references91

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          PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation

          Scoping reviews, a type of knowledge synthesis, follow a systematic approach to map evidence on a topic and identify main concepts, theories, sources, and knowledge gaps. Although more scoping reviews are being done, their methodological and reporting quality need improvement. This document presents the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) checklist and explanation. The checklist was developed by a 24-member expert panel and 2 research leads following published guidance from the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network. The final checklist contains 20 essential reporting items and 2 optional items. The authors provide a rationale and an example of good reporting for each item. The intent of the PRISMA-ScR is to help readers (including researchers, publishers, commissioners, policymakers, health care providers, guideline developers, and patients or consumers) develop a greater understanding of relevant terminology, core concepts, and key items to report for scoping reviews.
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            Scoping studies: towards a methodological framework

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              The COVID-19 social media infodemic

              We address the diffusion of information about the COVID-19 with a massive data analysis on Twitter, Instagram, YouTube, Reddit and Gab. We analyze engagement and interest in the COVID-19 topic and provide a differential assessment on the evolution of the discourse on a global scale for each platform and their users. We fit information spreading with epidemic models characterizing the basic reproduction number \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_0$$\end{document} R 0 for each social media platform. Moreover, we identify information spreading from questionable sources, finding different volumes of misinformation in each platform. However, information from both reliable and questionable sources do not present different spreading patterns. Finally, we provide platform-dependent numerical estimates of rumors’ amplification.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                May 2021
                27 May 2021
                : 23
                : 5
                : e25736
                Affiliations
                [1 ] Department of Population Health Luxembourg Institute of Health Strassen Luxembourg
                [2 ] Inserm U1018 Center for Research in Epidemiology and Population Health (CESP) Paris Saclay University Villejuif France
                [3 ] Epiconcept Paris France
                [4 ] Competence Centre for Methodology and Statistics Luxembourg Institute of Health Strassen Luxembourg
                [5 ] Luxembourg Institute of Socio-Economic Research Esch/Alzette Luxembourg
                Author notes
                Corresponding Author: Guy Fagherazzi guy.fagherazzi@ 123456lih.lu
                Author information
                https://orcid.org/0000-0001-8537-2097
                https://orcid.org/0000-0001-9463-9064
                https://orcid.org/0000-0003-4753-1709
                https://orcid.org/0000-0003-0654-3746
                https://orcid.org/0000-0001-7723-0304
                https://orcid.org/0000-0001-5033-5966
                Article
                v23i5e25736
                10.2196/25736
                8193478
                34042593
                c7d90208-e3a2-4cfd-99ea-7c9c7bd4fa98
                ©Charline Bour, Adrian Ahne, Susanne Schmitz, Camille Perchoux, Coralie Dessenne, Guy Fagherazzi. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.05.2021.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 16 November 2020
                : 30 November 2020
                : 15 January 2021
                : 18 March 2021
                Categories
                Review
                Review

                Medicine
                social media,public health,epidemiology,research,health,medical,social networking,infodemiology,ehealth,text mining

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