Online from: 1949
Subject Area: Library and Information Studies
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|Title:||How do health care professionals select medical images they need?|
|Author(s):||Shahram Sedghi, (Department of Librarianship and Medical Information Sciences, Tehran University of Medical Sciences, Tehran, Iran), Mark Sanderson, (School of Computer Science and Information Technology, RMIT University, Melbourne, Australia), Paul Clough, (Information School, University of Sheffield, Sheffield, UK)|
|Citation:||Shahram Sedghi, Mark Sanderson, Paul Clough, (2012) "How do health care professionals select medical images they need?", Aslib Proceedings, Vol. 64 Iss: 4, pp.437 - 456|
|Keywords:||Digital images, Health care, Image retrieval, Image seeking behaviour, Information retrieval, Medical imaging, Medical personnel, Relevance criteria, Relevance judgement, Visual databases|
|Article type:||Research paper|
|DOI:||10.1108/00012531211244815 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – This paper aims to report the results of a study investigating the relevance criteria used by health care professionals when seeking medical images.
Design/methodology/approach – Data were collected from 29 participants using a think-aloud protocol and face-to-face interviews and analysed using the Straussian version of grounded theory (GT).
Findings – The results show that participants made use of 15 relevance criteria, although they agreed on topicality being the most important. The findings suggest that users apply different criteria in different situations when evaluating the relevancy of medical images.
Originality/value – To the best of the authors' knowledge, there have been few studies that investigate relevance judgments for visually orientated documents. Thus, this study helps to contribute to the understanding of medical image resources and the information needs of health care professionals. A clear understanding of the medical image information needs of health care professionals is also vital to the design process and development of medical image retrieval systems.
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