Rayyan-a web and mobile app for systematic reviews.
Rayyan-a web and mobile app for systematic reviews.
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DOI：
10.1186/s13643-016-0384-4
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发表时间：
2016-12-05
影响因子：
3.7
通讯作者：
Elmagarmid A
中科院分区：
文献类型：
--
作者：
Ouzzani M;Hammady H;Fedorowicz Z;Elmagarmid A
在系统评价中，多项随机对照试验（RCT）的综合可以总结个体结局的影响，并提供有关干预措施有效性的数值答案。搜索过滤是耗时的，并且没有一种方法能够满足速度和准确性的主要要求。系统性综述的自动化是为了加快政策和临床决策当前最佳证据的可用性。我们开发了Rayyan（http：rayyan.qcri.org），这是一款免费的网络和移动的应用程序，有助于使用半自动化流程加快摘要和标题的初步筛选，同时融合了高水平的可用性。在beta测试阶段，我们使用了两篇已发表的科克伦综述，其中纳入的研究是手动选择的。他们的搜索，1030条记录和273条记录，被上传到Rayyan。Rayyan的不同功能使用这两个评论进行了测试。我们还对Rayyan的用户进行了调查，并通过内置功能收集反馈。Rayyan的试点测试侧重于可用性、相对于手动方法的准确性以及预测功能的附加值。“taster”评审（273条记录）允许快速概述Rayyan的可用性早期评论。第二次审查（1030条记录）需要多次迭代以识别先前确定的11项试验。基于“预测模型”的“建议”和“提示”，随着测试的进展超过五项研究而出现。推出后的用户体验和开发人员的自反响应使实时修改和改进成为可能。调查受访者表示，与其他工具相比，使用Rayyan平均节省40%的时间，34%的受访者表示节省了50%以上的时间。此外，大约75%的受访者提到，筛查和标签研究以及合作进行审查是Rayyan的两个最重要的特点。截至2016年11月，Rayyan的用户超过2000人，来自60多个国家，进行了数百次评论，引用次数超过160万次。来自用户的反馈，主要是通过应用程序网站和最近的一项调查获得的，突出了探索搜索的容易性，节省的时间，以及分享和比较包含-排除决策的简单性。在用户反馈中确定和报告的应用程序的最强功能是它能够帮助筛选和协作以及为用户节省时间。Rayyan在使用中反应灵敏且直观，具有减轻审阅者负担的巨大潜力。
Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.