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首页> 外文期刊>Aslib journal of information management: New information perspectives >Evaluating physicians' serendipitous knowledge discovery in online discovery systems: A new approach
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Evaluating physicians' serendipitous knowledge discovery in online discovery systems: A new approach

机译:评估医生偶然发现的知识发现在网上发现系统:一个新的方法

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Purpose A new approach to investigate serendipitous knowledge discovery (SKD) of health information is developed and tested to evaluate the information flow-serendipitous knowledge discovery (IF-SKD) model. The purpose of this paper is to determine the degree to which IF-SKD reflects physicians' information behaviour in a clinical setting and explore how the information system, Spark, designed to support physicians' SKD, meets its goals. Design/methodology/approach The proposed pre-experimental study design employs an adapted version of the McCay-Peet's (2013) and McCay-Peet et al.'s (2015) serendipitous digital environment (SDE) questionnaire research tool to address the complexity associated with defining the way in which SKD is understood and applied in system design. To test the IF-SKD model, the new data analysis approach combining confirmatory factor analysis, data imputation and Monte Carlo simulations was developed. Findings The piloting of the proposed novel analysis approach demonstrated that small sample information behaviour survey data can be meaningfully examined using a confirmatory factor analysis technique. Originality/value This paper makes an original contribution to developing and refining methods and tools of research into information-system-supported serendipitous discovery of information by health providers.
机译:目的研究的新方法偶然发现(通用)的健康知识信息开发和测试评估flow-serendipitous知识的信息发现(IF-SKD)模型。纸是确定IF-SKD的程度行为反映了医生的信息临床和探索信息的方式系统,火花,旨在支持医生的实现,满足其目标。拟议中的pre-experimental研究设计雇佣McCay-Peet改编版的(2013)和McCay-Peet et al。(2015)偶然的数字环境(SDE)问卷调查研究工具来解决复杂性与定义的方式有关通用是理解和应用系统设计。结合验证性因素分析方法分析、数据归责和蒙特卡洛模拟了。提出了新颖的分析方法证明了小样本信息行为调查数据可以有意义检查使用验证性因素分析技术。原始的贡献发展和精炼研究的方法和工具information-system-supported偶然发现健康信息的提供者。

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