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Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module
BACKGROUND: A major problem arising from searching across bibliographic databases is the retrieval of duplicate citations. Removing such duplicates is an essential task to ensure systematic reviewers do not waste time screening the same citation multiple times. Although reference management software...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4320616/ https://www.ncbi.nlm.nih.gov/pubmed/25588387 http://dx.doi.org/10.1186/2046-4053-4-6 |
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author | Rathbone, John Carter, Matt Hoffmann, Tammy Glasziou, Paul |
author_facet | Rathbone, John Carter, Matt Hoffmann, Tammy Glasziou, Paul |
author_sort | Rathbone, John |
collection | PubMed |
description | BACKGROUND: A major problem arising from searching across bibliographic databases is the retrieval of duplicate citations. Removing such duplicates is an essential task to ensure systematic reviewers do not waste time screening the same citation multiple times. Although reference management software use algorithms to remove duplicate records, this is only partially successful and necessitates removing the remaining duplicates manually. This time-consuming task leads to wasted resources. We sought to evaluate the effectiveness of a newly developed deduplication program against EndNote. METHODS: A literature search of 1,988 citations was manually inspected and duplicate citations identified and coded to create a benchmark dataset. The Systematic Review Assistant-Deduplication Module (SRA-DM) was iteratively developed and tested using the benchmark dataset and compared with EndNote’s default one step auto-deduplication process matching on (‘author’, ‘year’, ‘title’). The accuracy of deduplication was reported by calculating the sensitivity and specificity. Further validation tests, with three additional benchmarked literature searches comprising a total of 4,563 citations were performed to determine the reliability of the SRA-DM algorithm. RESULTS: The sensitivity (84%) and specificity (100%) of the SRA-DM was superior to EndNote (sensitivity 51%, specificity 99.83%). Validation testing on three additional biomedical literature searches demonstrated that SRA-DM consistently achieved higher sensitivity than EndNote (90% vs 63%), (84% vs 73%) and (84% vs 64%). Furthermore, the specificity of SRA-DM was 100%, whereas the specificity of EndNote was imperfect (average 99.75%) with some unique records wrongly assigned as duplicates. Overall, there was a 42.86% increase in the number of duplicates records detected with SRA-DM compared with EndNote auto-deduplication. CONCLUSIONS: The Systematic Review Assistant-Deduplication Module offers users a reliable program to remove duplicate records with greater sensitivity and specificity than EndNote. This application will save researchers and information specialists time and avoid research waste. The deduplication program is freely available online. |
format | Online Article Text |
id | pubmed-4320616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43206162015-02-08 Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module Rathbone, John Carter, Matt Hoffmann, Tammy Glasziou, Paul Syst Rev Research BACKGROUND: A major problem arising from searching across bibliographic databases is the retrieval of duplicate citations. Removing such duplicates is an essential task to ensure systematic reviewers do not waste time screening the same citation multiple times. Although reference management software use algorithms to remove duplicate records, this is only partially successful and necessitates removing the remaining duplicates manually. This time-consuming task leads to wasted resources. We sought to evaluate the effectiveness of a newly developed deduplication program against EndNote. METHODS: A literature search of 1,988 citations was manually inspected and duplicate citations identified and coded to create a benchmark dataset. The Systematic Review Assistant-Deduplication Module (SRA-DM) was iteratively developed and tested using the benchmark dataset and compared with EndNote’s default one step auto-deduplication process matching on (‘author’, ‘year’, ‘title’). The accuracy of deduplication was reported by calculating the sensitivity and specificity. Further validation tests, with three additional benchmarked literature searches comprising a total of 4,563 citations were performed to determine the reliability of the SRA-DM algorithm. RESULTS: The sensitivity (84%) and specificity (100%) of the SRA-DM was superior to EndNote (sensitivity 51%, specificity 99.83%). Validation testing on three additional biomedical literature searches demonstrated that SRA-DM consistently achieved higher sensitivity than EndNote (90% vs 63%), (84% vs 73%) and (84% vs 64%). Furthermore, the specificity of SRA-DM was 100%, whereas the specificity of EndNote was imperfect (average 99.75%) with some unique records wrongly assigned as duplicates. Overall, there was a 42.86% increase in the number of duplicates records detected with SRA-DM compared with EndNote auto-deduplication. CONCLUSIONS: The Systematic Review Assistant-Deduplication Module offers users a reliable program to remove duplicate records with greater sensitivity and specificity than EndNote. This application will save researchers and information specialists time and avoid research waste. The deduplication program is freely available online. BioMed Central 2015-01-14 /pmc/articles/PMC4320616/ /pubmed/25588387 http://dx.doi.org/10.1186/2046-4053-4-6 Text en © Rathbone et al.; licensee BioMed Central. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Rathbone, John Carter, Matt Hoffmann, Tammy Glasziou, Paul Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module |
title | Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module |
title_full | Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module |
title_fullStr | Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module |
title_full_unstemmed | Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module |
title_short | Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module |
title_sort | better duplicate detection for systematic reviewers: evaluation of systematic review assistant-deduplication module |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4320616/ https://www.ncbi.nlm.nih.gov/pubmed/25588387 http://dx.doi.org/10.1186/2046-4053-4-6 |
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