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Interdisciplinarity in Translational Medicine: A Bibliometric Case Study

机译:转化医学的跨学科性:文献计量案例研究

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摘要

Translational research (TR) is the process of bringing innovations from basic science into applied science, usually referring to the practice of medicine. It has been assumed that cross-disciplinary collaboration, or interdisciplinarity research (IDR), is essential to translation. Yet there is a gap in the literature regarding the interaction between interdisciplinarity and translation. If interdisciplinarity is highly correlated with translational research, this relationship would open up the possibility of using bibliometric techniques to help evaluate and target TR research.;This dissertation uses a bibliometric case study approach to explore the progression of three innovations through the published literature, in order to better understand the role of interdisciplinarity in translation and study the application of bibliometric methods to TR. The translational importance of the literature of these cases was determined by qualitative coding in collaboration with a physician consultant, while interdisciplinarity was operationalized by both a variety of bibliometric IDR indicators as well as through qualitative coding.;The results show that there is a weak correlation between interdisciplinary indicators and translational research, with a random forest prediction model able to correctly identify translational records with 69% accuracy using these indicators. The progression of records in the cases did not fit the theoretical linear model of translation, and better supports a balanced circular model. Multidisciplinary research is observed in some cases, but interdisciplinary work is rare. Interdisciplinary research did not appear to be a necessary or sufficient component of translation. The bibliometric diversity indicators of Integration and Diffusion are shown to be useful in identifying this distribution of information in practice. The use of subject categories to study translational research is found to be useful, but several caveats are noted, including the overlap of translational research areas within overly broad subjects.;It is hoped that the results from this study will enable TR policymakers to fund research with more confidence, promote the kinds of cross-disciplinary information flows that are most likely to benefit translation, and better evaluate the performance of such research using appropriate bibliometric methods. Ultimately, this understanding will improve TR and aid in its major goal of improving the health of society.
机译:转化研究(TR)是将创新从基础科学转变为应用科学的过程,通常是指医学实践。已经假定跨学科合作或跨学科研究(IDR)对于翻译至关重要。然而,关于跨学科与翻译之间相互作用的文献尚存在空白。如果跨学科性与翻译研究高度相关,则这种关系将开启使用文献计量技术来帮助评估和研究TR研究的可能性。本论文采用文献计量案例研究的方法,通过已发表的文献探索了三种创新的进展。为了更好地理解跨学科在翻译中的作用,并研究文献计量学方法在翻译中的应用。这些病例文献的翻译重要性是通过与医师顾问合作进行定性编码来确定的,而跨学科性是通过各种文献计量学IDR指标以及通过定性编码来实现的;结果表明存在弱相关性在跨学科指标和翻译研究之间,使用随机森林预测模型能够使用这些指标正确识别翻译记录,准确度达到69%。案例中的记录进度与翻译的理论线性模型不符,可以更好地支持平衡的圆形模型。在某些情况下,可以进行多学科研究,但很少进行跨学科研究。跨学科研究似乎不是翻译的必要或充分组成部分。实践证明,积分和扩散的文献计量学多样性指标可用于识别这种信息分布。发现使用主题类别来研究翻译研究是有用的,但需要注意一些警告,包括翻译研究领域在过于广泛的主题中的重叠。希望这项研究的结果将使TR政策制定者能够资助研究以更大的信心,促进最有可能使翻译受益的跨学科信息流,并使用适当的文献计量方法更好地评估此类研究的绩效。最终,这种理解将改善TR,并有助于其改善社会健康的主要目标。

著录项

  • 作者

    Young, Jonathan.;

  • 作者单位

    University of Hawai'i at Manoa.;

  • 授予单位 University of Hawai'i at Manoa.;
  • 学科 Information science.;Health sciences.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 181 p.
  • 总页数 181
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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