@inproceedings{65eb0d8ca60e4ae9ada73a3ffdc445e6,
title = "Opportunities for computer support for systematic reviewing - A gap analysis",
abstract = "Systematic review is a type of literature review designed to synthesize all available evidence on a given question. Systematic reviews require significant time and effort, which has led to the continuing development of computer support. This paper seeks to identify the gaps and opportunities for computer support. By interviewing experienced systematic reviewers from diverse fields, we identify the technical problems and challenges reviewers face in conducting a systematic review and their current uses of computer support. We propose potential research directions for how computer support could help to speed the systematic review process while retaining or improving review quality.",
keywords = "Gap analysis, Interview study, Meta-analysis, Systematic review",
author = "Linh Hoang and Jodi Schneider",
note = "Funding Information: Acknowledgments. We would like to show our gratitude to all of the interview participants for sharing their experiences and also the pearls of wisdom that allowed us to complete this study. We would also like to thank our colleagues Lori Kendall and Peter Darch for discussions about qualitative research methodologies; Susan Lafferty who provided expertise that greatly assisted in the IRB process; and Katrina Felon for comments that greatly improved the manuscript. Research reported in this publication was supported in part by the National Library of Medicine of the National Institutes of Health under grant number R01LM010817, “Text Mining Pipeline to Accelerate Systematic Reviews in Evidence-based Medicine”. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Funding Information: We would like to show our gratitude to all of the interview participants for sharing their experiences and also the pearls of wisdom that allowed us to complete this study. We would also like to thank our colleagues Lori Kendall and Peter Darch for discussions about qualitative research methodologies; Susan Lafferty who provided expertise that greatly assisted in the IRB process; and Katrina Felon for comments that greatly improved the manuscript. Research reported in this publication was supported in part by the National Library of Medicine of the National Institutes of Health under grant number R01LM010817, “Text Mining Pipeline to Accelerate Systematic Reviews in Evidence-based Medicine”. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 13th International Conference on Transforming Digital Worlds, iConference 2018 ; Conference date: 25-03-2018 Through 28-03-2018",
year = "2018",
doi = "10.1007/978-3-319-78105-1_40",
language = "English (US)",
isbn = "9783319781044",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "367--377",
editor = "Gobinda Chowdhury and Julie McLeod and Val Gillet and Peter Willett",
booktitle = "Transforming Digital Worlds - 13th International Conference, iConference 2018, Proceedings",
address = "Germany",
}