Evaluating physicians’ serendipitous knowledge discovery in online discovery systems
| Autor: | Mark E. Hopkins, Oksana L. Zavalina |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Serendipity 05 social sciences 050401 social sciences methods Library and Information Sciences Data science Confirmatory factor analysis 0504 sociology Knowledge extraction Information system Survey data collection Systems design Imputation (statistics) 0509 other social sciences 050904 information & library sciences Reliability (statistics) Information Systems |
| Zdroj: | Aslib Journal of Information Management. 71:755-772 |
| ISSN: | 2050-3806 |
| DOI: | 10.1108/ajim-02-2019-0045 |
| Popis: | 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. Research limitations/implications This method allows to improve the reliability in measuring SKD and the generalisability of findings. 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. |
| Databáze: | OpenAIRE |
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