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

Author

Listed:
  • 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
    This research was conducted when Dr. Parimbelli was a postdoctoral fellow at the Telfer School of Management, University of Ottawa, Ottawa, ON K1N 6N5, Canada.)

  • 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)

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.

Suggested Citation

  • Martin Michalowski & Szymon Wilk & Wojtek Michalowski & Dympna O’Sullivan & Silvia Bonaccio & Enea Parimbelli & Marc Carrier & Grégoire Le Gal & Stephen Kingwell & Mor Peleg, 2021. "A Health eLearning Ontology and Procedural Reasoning Approach for Developing Personalized Courses to Teach Patients about Their Medical Condition and Treatment," IJERPH, MDPI, vol. 18(14), pages 1-28, July.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7355-:d:591437
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    References listed on IDEAS

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    1. Christopher R. Wolfe & Valerie F. Reyna & Colin L. Widmer & Elizabeth M. Cedillos & Christopher R. Fisher & Priscila G. Brust-Renck & Audrey M. Weil, 2015. "Efficacy of a Web-Based Intelligent Tutoring System for Communicating Genetic Risk of Breast Cancer," Medical Decision Making, , vol. 35(1), pages 46-59, January.
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    Cited by:

    1. Yao Cai & Fei Yu & Manish Kumar & Roderick Gladney & Javed Mostafa, 2022. "Health Recommender Systems Development, Usage, and Evaluation from 2010 to 2022: A Scoping Review," IJERPH, MDPI, vol. 19(22), pages 1-15, November.
    2. Akeem Pedro & Anh-Tuan Pham-Hang & Phong Thanh Nguyen & Hai Chien Pham, 2022. "Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies," IJERPH, MDPI, vol. 19(2), pages 1-18, January.

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