Department of Software and Information Systems, The University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.
Department of Family Medicine and Center for Quantitative Medicine, The University of Connecticut Health Center, Farmington, CT, 06030, USA.
BMC Med Inform Decis Mak. 2017 Jul 5;17(Suppl 2):74. doi: 10.1186/s12911-017-0463-z.
To deliver evidence-based medicine, clinicians often reference resources that are useful to their respective medical practices. Owing to their busy schedules, however, clinicians typically find it challenging to locate these relevant resources out of the rapidly growing number of journals and articles currently being published. The literature-recommender system may provide a possible solution to this issue if the individual needs of clinicians can be identified and applied.
We thus collected from the CiteULike website a sample of 96 clinicians and 6,221 scientific articles that they read. We examined the journal distributions, publication types, reading times, and geographic locations. We then compared the distributions of MeSH terms associated with these articles with those of randomly sampled MEDLINE articles using two-sample Z-test and multiple comparison correction, in order to identify the important topics relevant to clinicians.
We determined that the sampled clinicians followed the latest literature in a timely manner and read papers that are considered landmarks in medical research history. They preferred to read scientific discoveries from human experiments instead of molecular-, cellular- or animal-model-based experiments. Furthermore, the country of publication may impact reading preferences, particularly for clinicians from Egypt, India, Norway, Senegal, and South Africa.
These findings provide useful guidance for developing personalized literature-recommender systems for clinicians.
为了提供循证医学，临床医生经常参考对其各自医疗实践有用的资源。然而，由于日程繁忙，临床医生通常发现很难在当前大量出版的期刊和文章中找到这些相关资源。如果能够识别和应用临床医生的个体需求，文献推荐系统可能是解决这一问题的一种方法。
我们从 CiteULike 网站收集了 96 名临床医生和他们阅读的 6221 篇科学文章的样本。我们检查了期刊分布、出版类型、阅读时间和地理位置。然后，我们使用两样本 Z 检验和多重比较校正，比较了与这些文章相关的 MeSH 术语分布与随机抽样的 MEDLINE 文章的分布，以确定与临床医生相关的重要主题。
我们确定，抽样临床医生及时跟踪最新文献，并阅读被认为是医学研究史上里程碑的论文。他们更喜欢阅读来自人体实验的科学发现，而不是基于分子、细胞或动物模型的实验。此外，出版国家可能会影响阅读偏好，特别是对于来自埃及、印度、挪威、塞内加尔和南非的临床医生。
这些发现为为临床医生开发个性化文献推荐系统提供了有用的指导。
