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.
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.
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.
This method allows to improve the reliability in measuring SKD and the generalisability of findings.
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.
