Novel Citation-Based Literature Search Method: Application to Meta-analyses

项目摘要/摘要 文献检索效率低下是一个古老的信息学问题。在……方面取得了很大进展 便利文献检索，如试验和观察性研究的登记，提议 针对各个领域的最优搜索策略，以及搜索过滤器的提出，但文献效率不高 搜索结果并没有明显改善。该项目的目标是加强 CoCites方法，是我们最近开发的一种基于引文的科学文献搜索方法。这个 方法的目的是在连续两次搜索中找到与一篇或多篇已知文章相似的文章：1) 通过对同被引文献进行排序，找出与已知文献一起被引用的文献；2) 通过对引文频率进行排序来查找后向和前向引文。频次高于 对选择阈值进行相似性筛选。在两个试点研究中，我们的目标是重现文献 对52篇已发表的Meta分析进行搜索，我们发现每个Meta分析中包含的文章排名靠前 在(共同)被引用频率列表上。CoCites方法比关键字搜索更有效，并且能够 检索纳入Meta分析的研究的80%。拟议的项目旨在完善CoCites 方法，并对其在各个领域的应用进行了研究。与试验研究类似，我们将重现 对已发表的荟萃分析的文献搜索，它允许计算 方法。为了调查与引文实践和研究特点有关的方法，我们将创建一个 数据库，我们在其中记录了250个已发表的Meta分析的特征以及特征 他们所收录的每一项研究。这些引文将从Web of Science下载。我们将编写一份 Microsoft Excel中的宏，用于自动处理下载的文件并生成共引和引文 排名。我们将把这种方法应用于250项荟萃分析中的所有或部分，在这些分析中，我们调查 灵敏度和效率，同时：改变第一次搜索的选择阈值(目标1)；增加第三次搜索 联合引用、直接引用或两者兼而有之(目标2)；以及改变“已知”文章的选择和数量(目标 4)。我们将调查网络的影响和研究特征对敏感度和使用效率的影响 回归分析(目标5)。为了调查Meta分析的结果是否在研究发生变化时发生变化 没有发现，我们重复荟萃分析，排除“遗漏”的研究(目标3)。我们将把该方法应用于 引文实践不同的五个领域的荟萃分析(目标5)。最后，我们将前瞻性地应用 对在疾病中心社区指南进行的五项当时正在进行的系统审查的方法 控制和预防。

PROJECT SUMMARY/ABSTRACT The inefficiency of literature searches is an old informatics problem. There has been much progress in facilitating literature searches, such as the registration of trials and observational studies, the proposal of optimal search strategies for various fields, and the proposal of search filters, but the efficiency of literature searches has not markedly improved. The goal of this project is to strengthen the scientific basis of the CoCites method, a novel citation-based search method for scientific literature that we recently developed. The method aims to find articles that are similar to one or more `known' articles in two consecutive searches: 1) finding articles that are cited together with the known articles by ranking their co-citation frequencies; and 2) finding backward and forward citations by ranking their citation frequencies. Articles with frequencies above the selection thresholds are screened for similarity. In two pilot studies, where we aimed to reproduce the literature searches of 52 published meta-analyses, we showed that articles included in each meta-analysis ranked high on the list of (co-)citation frequencies. The CoCites method was more efficient than keyword searches and able to retrieve 80% of the studies included in the meta-analyses. The proposed project aims to refine the CoCites method and investigates its application in various fields. Similar as in the pilot studies, we will reproduce the literature searches of published meta-analyses, which allows to calculate the sensitivity and efficiency of the method. To investigate the method in relation to citation practices and study characteristics, we will create a database in which we document the characteristics of 250 published meta-analyses as well as characteristics of each of their included studies. The cocitations will be downloaded from Web of Science. We will write a macro in Microsoft Excel to automatically process the downloaded files and produce the co-citation and citation rankings. We will apply the method to all or selections of the 250 meta-analyses, where we investigate the sensitivity and efficiency while: varying the selection threshold of the first search (Aim 1); adding a third search of co-citations, direct citations or both (Aim 2); and varying the selection and number of `known' articles (Aim 4). We will investigate the impact of network and study characteristics on the sensitivity and efficiency using regression analysis (Aim 5). To investigate whether the results of the meta-analyses change when studies are not found, we repeat the meta-analyses excluding the `missed' studies (Aim 3). We will apply the method to meta-analyses in five fields that differ in citation practice (Aim 5). Finally, we will prospectively apply the method to five then-ongoing systematic reviews conducted at the Community Guide of the Centers for Disease Control and Prevention.