Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA.
Health Info Libr J. 2012 Sep;29(3):214-22. doi: 10.1111/j.1471-1842.2012.00992.x. Epub 2012 Jun 19.
Medical literature searches provide critical information for clinicians. However, the best strategy for identifying relevant high-quality literature is unknown.
We compared search results using PubMed and Google Scholar on four clinical questions and analysed these results with respect to article relevance and quality.
Abstracts from the first 20 citations for each search were classified into three relevance categories. We used the weighted kappa statistic to analyse reviewer agreement and nonparametric rank tests to compare the number of citations for each article and the corresponding journals' impact factors.
Reviewers ranked 67.6% of PubMed articles and 80% of Google Scholar articles as at least possibly relevant (P = 0.116) with high agreement (all kappa P-values < 0.01). Google Scholar articles had a higher median number of citations (34 vs. 1.5, P < 0.0001) and came from higher impact factor journals (5.17 vs. 3.55, P = 0.036).
PubMed searches and Google Scholar searches often identify different articles. In this study, Google Scholar articles were more likely to be classified as relevant, had higher numbers of citations and were published in higher impact factor journals. The identification of frequently cited articles using Google Scholar for searches probably has value for initial literature searches.
医学文献检索为临床医生提供了关键信息。然而，确定相关高质量文献的最佳策略尚不清楚。
我们比较了使用 PubMed 和 Google Scholar 对四个临床问题进行搜索的结果，并根据文章的相关性和质量对这些结果进行了分析。
对每个搜索的前 20 条引文的摘要进行了分类，分为三个相关性类别。我们使用加权 kappa 统计来分析评论者的一致性，并使用非参数秩检验来比较每篇文章的引文数量和相应期刊的影响因子。
评论者将 67.6%的 PubMed 文章和 80%的 Google Scholar 文章至少归类为可能相关（P = 0.116），一致性很高（所有 kappa P 值均<0.01）。Google Scholar 文章的引文中位数更高（34 比 1.5，P < 0.0001），且来自更高影响因子的期刊（5.17 比 3.55，P = 0.036）。
PubMed 搜索和 Google Scholar 搜索经常会识别出不同的文章。在这项研究中，Google Scholar 文章更有可能被归类为相关，引用数量更多，且发表在更高影响因子的期刊上。使用 Google Scholar 进行频繁引用文章的识别可能对初始文献搜索有价值。
