A Health eLearning Ontology and Procedural Reasoning Approach for Developing Personalized Courses to Teach Patients about Their Medical Condition and Treatment

Martin Michalowski, Szymon Wilk, Wojtek Michalowski, Dympna O’Sullivan, Silvia Bonaccio, Enea Parimbelli, Marc Carrier, Grégoire Le Gal, Stephen Kingwell and Mor Peleg
Additional contact information
Martin Michalowski: Nursing Informatics, School of Nursing, University of Minnesota, Minneapolis, MN 55455, USA
Szymon Wilk: Institute of Computing Science, Poznan University of Technology, 60-965 Poznań, Poland
Wojtek Michalowski: Telfer School of Management, University of Ottawa, Ottawa, ON K1N 6N5, Canada
Dympna O’Sullivan: School of Computer Science, Technological University Dublin, D02 HW71 Dublin, Ireland
Silvia Bonaccio: Telfer School of Management, University of Ottawa, Ottawa, ON K1N 6N5, Canada
Enea Parimbelli: Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
Marc Carrier: Division of Hematology, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada
Grégoire Le Gal: Department of Medicine, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada
Stephen Kingwell: Department of Orthopaedic Surgery, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada
Mor Peleg: Department of Information Systems, University of Haifa, Haifa 3498838, Israel

IJERPH, 2021, vol. 18, issue 14, 1-28

Abstract: We propose a methodological framework to support the development of personalized courses that improve patients’ understanding of their condition and prescribed treatment. Inspired by Intelligent Tutoring Systems (ITSs), the framework uses an eLearning ontology to express domain and learner models and to create a course. We combine the ontology with a procedural reasoning approach and precompiled plans to operationalize a design across disease conditions. The resulting courses generated by the framework are personalized across four patient axes—condition and treatment, comprehension level, learning style based on the VARK (Visual, Aural, Read/write, Kinesthetic) presentation model, and the level of understanding of specific course content according to Bloom’s taxonomy. Customizing educational materials along these learning axes stimulates and sustains patients’ attention when learning about their conditions or treatment options. Our proposed framework creates a personalized course that prepares patients for their meetings with specialists and educates them about their prescribed treatment. We posit that the improvement in patients’ understanding of prescribed care will result in better outcomes and we validate that the constructs of our framework are appropriate for representing content and deriving personalized courses for two use cases: anticoagulation treatment of an atrial fibrillation patient and lower back pain management to treat a lumbar degenerative disc condition. We conduct a mostly qualitative study supported by a quantitative questionnaire to investigate the acceptability of the framework among the target patient population and medical practitioners.

Keywords: patient education; educational learning; VARK; Bloom’s taxonomy; personalization; ontology; procedural reasoning system; precompiled planning (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1660-4601/18/14/7355/pdf (application/pdf)
https://www.mdpi.com/1660-4601/18/14/7355/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:18:y:2021:i:14:p:7355-:d:591437

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().