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Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation

BACKGROUND: Systematic reviews are vital to the pursuit of evidence-based medicine within healthcare. Screening titles and abstracts (T&Ab) for inclusion in a systematic review is an intensive, and often collaborative, step. The use of appropriate tools is therefore important. In this study, we...

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Autores principales: Harrison, Hannah, Griffin, Simon J., Kuhn, Isla, Usher-Smith, Juliet A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6958795/
https://www.ncbi.nlm.nih.gov/pubmed/31931747
http://dx.doi.org/10.1186/s12874-020-0897-3
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author Harrison, Hannah
Griffin, Simon J.
Kuhn, Isla
Usher-Smith, Juliet A.
author_facet Harrison, Hannah
Griffin, Simon J.
Kuhn, Isla
Usher-Smith, Juliet A.
author_sort Harrison, Hannah
collection PubMed
description BACKGROUND: Systematic reviews are vital to the pursuit of evidence-based medicine within healthcare. Screening titles and abstracts (T&Ab) for inclusion in a systematic review is an intensive, and often collaborative, step. The use of appropriate tools is therefore important. In this study, we identified and evaluated the usability of software tools that support T&Ab screening for systematic reviews within healthcare research. METHODS: We identified software tools using three search methods: a web-based search; a search of the online “systematic review toolbox”; and screening of references in existing literature. We included tools that were accessible and available for testing at the time of the study (December 2018), do not require specific computing infrastructure and provide basic screening functionality for systematic reviews. Key properties of each software tool were identified using a feature analysis adapted for this purpose. This analysis included a weighting developed by a group of medical researchers, therefore prioritising the most relevant features. The highest scoring tools from the feature analysis were then included in a user survey, in which we further investigated the suitability of the tools for supporting T&Ab screening amongst systematic reviewers working in medical research. RESULTS: Fifteen tools met our inclusion criteria. They vary significantly in relation to cost, scope and intended user community. Six of the identified tools (Abstrackr, Colandr, Covidence, DRAGON, EPPI-Reviewer and Rayyan) scored higher than 75% in the feature analysis and were included in the user survey. Of these, Covidence and Rayyan were the most popular with the survey respondents. Their usability scored highly across a range of metrics, with all surveyed researchers (n = 6) stating that they would be likely (or very likely) to use these tools in the future. CONCLUSIONS: Based on this study, we would recommend Covidence and Rayyan to systematic reviewers looking for suitable and easy to use tools to support T&Ab screening within healthcare research. These two tools consistently demonstrated good alignment with user requirements. We acknowledge, however, the role of some of the other tools we considered in providing more specialist features that may be of great importance to many researchers.
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spelling pubmed-69587952020-01-17 Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation Harrison, Hannah Griffin, Simon J. Kuhn, Isla Usher-Smith, Juliet A. BMC Med Res Methodol Research Article BACKGROUND: Systematic reviews are vital to the pursuit of evidence-based medicine within healthcare. Screening titles and abstracts (T&Ab) for inclusion in a systematic review is an intensive, and often collaborative, step. The use of appropriate tools is therefore important. In this study, we identified and evaluated the usability of software tools that support T&Ab screening for systematic reviews within healthcare research. METHODS: We identified software tools using three search methods: a web-based search; a search of the online “systematic review toolbox”; and screening of references in existing literature. We included tools that were accessible and available for testing at the time of the study (December 2018), do not require specific computing infrastructure and provide basic screening functionality for systematic reviews. Key properties of each software tool were identified using a feature analysis adapted for this purpose. This analysis included a weighting developed by a group of medical researchers, therefore prioritising the most relevant features. The highest scoring tools from the feature analysis were then included in a user survey, in which we further investigated the suitability of the tools for supporting T&Ab screening amongst systematic reviewers working in medical research. RESULTS: Fifteen tools met our inclusion criteria. They vary significantly in relation to cost, scope and intended user community. Six of the identified tools (Abstrackr, Colandr, Covidence, DRAGON, EPPI-Reviewer and Rayyan) scored higher than 75% in the feature analysis and were included in the user survey. Of these, Covidence and Rayyan were the most popular with the survey respondents. Their usability scored highly across a range of metrics, with all surveyed researchers (n = 6) stating that they would be likely (or very likely) to use these tools in the future. CONCLUSIONS: Based on this study, we would recommend Covidence and Rayyan to systematic reviewers looking for suitable and easy to use tools to support T&Ab screening within healthcare research. These two tools consistently demonstrated good alignment with user requirements. We acknowledge, however, the role of some of the other tools we considered in providing more specialist features that may be of great importance to many researchers. BioMed Central 2020-01-13 /pmc/articles/PMC6958795/ /pubmed/31931747 http://dx.doi.org/10.1186/s12874-020-0897-3 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Harrison, Hannah
Griffin, Simon J.
Kuhn, Isla
Usher-Smith, Juliet A.
Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation
title Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation
title_full Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation
title_fullStr Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation
title_full_unstemmed Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation
title_short Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation
title_sort software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6958795/
https://www.ncbi.nlm.nih.gov/pubmed/31931747
http://dx.doi.org/10.1186/s12874-020-0897-3
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