Taubman Health Sciences Library, University of Michigan, Ann Arbor, Michigan.
PCOM Library, Philadelphia College of Osteopathic Medicine-Georgia Campus, Suwanee, Georgia.
Res Synth Methods. 2018 Dec;9(4):540-550. doi: 10.1002/jrsm.1318. Epub 2018 Sep 21.
When the Medical Library Association identified questions critical for the future of the profession, it assigned groups to use systematic reviews to find the answers to these questions. Group 6, whose question was on emerging technologies, recognized early on that the systematic review process would not work well for this question, which looks forward to predict future trends, whereas the systematic review process looks back in time. We searched for new methodologies that were more appropriate to our question, developing a process that combined systematic review, text mining, and visualization techniques. We then discovered tech mining, which is very similar to the process we had created. In this paper, we describe our research design and compare tech mining and systematic review methodologies. There are similarities and differences in each process: Both use a defined research question, deliberate database selection, careful and iterative search strategy development, broad data collection, and thoughtful data analysis. However, the focus of the research differs significantly, with systematic reviews looking to the past and tech mining mainly to the future. Our comparison demonstrates that each process can be enhanced from a purposeful consideration of the procedures of the other. Tech mining would benefit from the inclusion of a librarian on their research team and a greater attention to standards and collaboration in the research project. Systematic reviews would gain from the use of tech mining tools to enrich their data analysis and corporate management communication techniques to promote the adoption of their findings.
当医学图书馆协会确定了对该专业未来至关重要的问题时，它分配了几个小组使用系统评价来寻找这些问题的答案。第六组的问题是关于新兴技术的，他们很早就意识到，系统评价过程并不适用于这个前瞻性地预测未来趋势的问题，而系统评价过程是回顾过去的。我们寻找了更适合我们问题的新方法，开发了一种将系统评价、文本挖掘和可视化技术相结合的方法。然后我们发现了技术挖掘，它与我们创建的过程非常相似。在本文中，我们描述了我们的研究设计，并比较了技术挖掘和系统评价方法。每个过程都有相似之处和不同之处：都使用明确的研究问题、深思熟虑的数据库选择、仔细和迭代的搜索策略制定、广泛的数据收集和深思熟虑的数据分析。然而，研究的重点有很大的不同，系统评价着眼于过去，而技术挖掘主要着眼于未来。我们的比较表明，每个过程都可以通过有目的地考虑另一个过程的程序来得到增强。技术挖掘将受益于在其研究团队中加入一名图书馆员，并更加关注研究项目的标准和协作。系统评价将从使用技术挖掘工具丰富其数据分析以及采用企业管理沟通技术来促进其研究结果的采用中获益。
