A mapping exercise using automated techniques to develop a search strategy to identify systematic review tools

IF 5 2区生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Research Synthesis Methods Pub Date : 2023-09-05 DOI:10.1002/jrsm.1665

Anthea Sutton, Hannah O'Keefe, Eugenie Evelynne Johnson, Christopher Marshall

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引用次数: 1

Abstract

The Systematic Review Toolbox aims provide a web-based catalogue of tools that support various tasks within the systematic review and wider evidence synthesis process. Identifying publications surrounding specific systematic review tools is currently challenging, leading to a high screening burden for few eligible records. We aimed to develop a search strategy that could be regularly and automatically run to identify eligible records for the SR Toolbox, thus reducing time on task and burden for those involved. We undertook a mapping exercise to identify the PubMed IDs of papers indexed within the SR Toolbox. We then used the Yale MeSH Analyser and Visualisation of Similarities (VOS) Viewer text-mining software to identify the most commonly used MeSH terms and text words within the eligible records. These MeSH terms and text words were combined using Boolean Operators into a search strategy for Ovid MEDLINE. Prior to the mapping exercise and search strategy development, 81 software tools and 55 ‘Other’ tools were included within the SR Toolbox. Since implementation of the search strategy, 146 tools have been added. There has been an increase in tools added to the toolbox since the search was developed and its corresponding auto-alert in MEDLINE was originally set up. Developing a search strategy based on a mapping exercise is an effective way of identifying new tools to support the systematic review process. Further research could be conducted to help prioritise records for screening to reduce reviewer burden further and to adapt the strategy for disciplines beyond healthcare.

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使用自动化技术开发搜索策略以识别系统审查工具的映射练习。

系统审查工具箱旨在提供一个基于网络的工具目录，支持系统审查和更广泛的证据综合过程中的各种任务。目前，识别围绕特定系统审查工具的出版物具有挑战性，导致少数符合条件的记录的筛选负担很高。我们旨在开发一种搜索策略，该策略可以定期自动运行，以确定SR工具箱的合格记录，从而减少相关人员的任务时间和负担。我们进行了一项绘图工作，以确定SR工具箱中索引的论文的PubMed ID。然后，我们使用Yale MeSH Analyser和相似性可视化（VOS）Viewer文本挖掘软件来识别合格记录中最常用的MeSH术语和文本单词。使用布尔运算符将这些MeSH术语和文本单词组合到Ovid MEDLINE的搜索策略中。在地图绘制和搜索策略开发之前，SR工具箱中包括81个软件工具和55个“其他”工具。自实施搜索策略以来，已添加了146个工具。自从开发搜索并最初在MEDLINE中设置相应的自动警报以来，添加到工具箱中的工具有所增加。在绘制地图的基础上制定搜索策略是确定新工具以支持系统审查过程的有效方法。可以进行进一步的研究，以帮助优先选择筛查记录，进一步减轻审查人员的负担，并将该策略适用于医疗保健以外的学科。

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来源期刊

Research Synthesis Methods MATHEMATICAL & COMPUTATIONAL BIOLOGYMULTID-MULTIDISCIPLINARY SCIENCES

CiteScore

16.90

自引率

3.10%

发文量

期刊介绍： Research Synthesis Methods is a reputable, peer-reviewed journal that focuses on the development and dissemination of methods for conducting systematic research synthesis. Our aim is to advance the knowledge and application of research synthesis methods across various disciplines. Our journal provides a platform for the exchange of ideas and knowledge related to designing, conducting, analyzing, interpreting, reporting, and applying research synthesis. While research synthesis is commonly practiced in the health and social sciences, our journal also welcomes contributions from other fields to enrich the methodologies employed in research synthesis across scientific disciplines. By bridging different disciplines, we aim to foster collaboration and cross-fertilization of ideas, ultimately enhancing the quality and effectiveness of research synthesis methods. Whether you are a researcher, practitioner, or stakeholder involved in research synthesis, our journal strives to offer valuable insights and practical guidance for your work.