Institute for Research in Operative Medicine (IFOM), Faculty of Health, School of Medicine, Witten/Herdecke University, Cologne, Germany.
Department of Health Care Management, Technische Universität Berlin, Berlin, Germany.
J Clin Epidemiol. 2023 Jul;159:214-224. doi: 10.1016/j.jclinepi.2023.05.027. Epub 2023 Jun 5.
Data extraction is a prerequisite for analyzing, summarizing, and interpreting evidence in systematic reviews. Yet guidance is limited, and little is known about current approaches. We surveyed systematic reviewers on their current approaches to data extraction, opinions on methods, and research needs.
We developed a 29-question online survey and distributed it through relevant organizations, social media, and personal networks in 2022. Closed questions were evaluated using descriptive statistics, and open questions were analyzed using content analysis.
162 reviewers participated. Use of adapted (65%) or newly developed extraction forms (62%) was common. Generic forms were rarely used (14%). Spreadsheet software was the most popular extraction tool (83%). Piloting was reported by 74% of respondents and included a variety of approaches. Independent and duplicate extraction was considered the most appropriate approach to data collection (64%). About half of respondents agreed that blank forms and/or raw data should be published. Suggested research gaps were the effects of different methods on error rates (60%) and the use of data extraction support tools (46%).
Systematic reviewers used varying approaches to pilot data extraction. Methods to reduce errors and use of support tools such as (semi-)automation tools are top research gaps.
数据提取是系统评价中分析、总结和解释证据的前提。然而，相关指导有限，目前的方法也知之甚少。我们调查了系统评价者在数据提取方面的当前方法、对方法的看法以及研究需求。
我们开发了一个 29 个问题的在线调查，并于 2022 年通过相关组织、社交媒体和个人网络进行了分发。使用描述性统计对封闭问题进行评估，对开放问题进行内容分析。
共有 162 名评论者参与。使用改编（65%）或新开发的提取表格（62%）很常见。很少使用通用表格（14%）。电子表格软件是最受欢迎的数据提取工具（83%）。74%的受访者报告了预试验，且采用了各种方法。独立和重复提取被认为是最适合数据收集的方法（64%）。约一半的受访者同意应公布空白表格和/或原始数据。建议的研究空白包括不同方法对错误率的影响（60%）以及数据提取支持工具的使用（46%）。
系统评价者使用了不同的方法来预试验数据提取。减少错误的方法和使用数据提取支持工具（如半自动工具）是研究的最大空白。
