The evidence synthesis and meta-analysis in R conference (ESMARConf): levelling the playing field of conference accessibility and equitability

Author:

Haddaway Neal R.ORCID,Bannach-Brown Alexandra,Grainger Matthew J.,Hamilton W. Kyle,Hennessy Emily A.,Keenan Ciara,Pritchard Chris C.,Stojanova Jana

Abstract

AbstractRigorous evidence is vital in all disciplines to ensure efficient, appropriate, and fit-for-purpose decision-making with minimised risk of unintended harm. To date, however, disciplines have been slow to share evidence synthesis frameworks, best practices, and tools amongst one another. Recent progress in collaborative digital and programmatic frameworks, such as the free and Open Source software R, have significantly expanded the opportunities for development of free-to-use, incrementally improvable, community driven tools to support evidence synthesis (e.g. EviAtlas, robvis, PRISMA2020 flow diagrams and metadat). Despite this, evidence synthesis (and meta-analysis) practitioners and methodologists who make use of R remain relatively disconnected from one another. Here, we report on a new virtual conference for evidence synthesis and meta-analysis in the R programming environment (ESMARConf) that aims to connect these communities. By designing an entirely free and online conference from scratch, we have been able to focus efforts on maximising accessibility and equity—making these core missions for our new community of practice. As a community of practice, ESMARConf builds on the success and groundwork of the broader R community and systematic review coordinating bodies (e.g. Cochrane), but fills an important niche. ESMARConf aims to maximise accessibility and equity of participants across regions, contexts, and social backgrounds, forging a level playing field in a digital, connected, and online future of evidence synthesis. We believe that everyone should have the same access to participation and involvement, and we believe ESMARConf provides a vital opportunity to push for equitability across disciplines, regions, and personal situations.

Publisher

Springer Science and Business Media LLC

Subject

Medicine (miscellaneous)

Reference16 articles.

1. Donnelly CA, Boyd I, Campbell P, Craig C, Vallance P, Walport M, et al. Four principles for synthesizing evidence; 2018.

2. The Campbell Collaboration. Campbell systematic reviews: policies and guidelines; 2020.

3. Collaboration for Environmental Evidence. Guidelines and standards for evidence synthesis in environmental management. Version 5.0; 2018. Available from: https://environmentalevidence.org/information-for-authors/

4. Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane handbook for systematic reviews of interventions: Wiley; 2019.

5. Cartabellotta A, Tilson JK. The ecosystem of evidence cannot thrive without efficiency of knowledge generation, synthesis, and translation. J Clin Epidemiol. 2019;110:90–5.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3