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Title
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A qualitative textual analysis of feedback comments in ePortfolios : quality and alignment with the CanMEDS roles
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Author
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Abstract
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| Introduction: Competency-based education requires high-quality feedback to guide students' acquisition of competencies. Sound assessment and feedback systems, such as ePortfolios, are needed to facilitate seeking and giving feedback during clinical placements. However, it is unclear whether the written feedback comments in ePortfolios are of high quality and aligned with the current competency focus. Therefore, this study investigates the quality of written feedback comments in ePortfolios of healthcare students, as well as how these feedback comments align with the CanMEDS roles. Methods: A qualitative textual analysis was conducted. 2,349 written feedback comments retrieved from the ePortfolios of 149 healthcare students (specialist medicine, general practice, occupational therapy, speech therapy and midwifery) were analysed retrospectively using deductive content analysis. Two structured categorisation matrices, one based on four literature-derived feedback quality criteria (performance, judgment, elaboration and improvement) and another one on the seven CanMEDS roles (Medical Expert, Communicator, Collaborator, Leader, Health Advocate, Scholar and Professional), guided the analysis. Results: The minority of the feedback comments (n = 352; 14.9%) could be considered of high quality because they met all four quality criteria. Most feedback comments were of moderate quality and met only two to three quality criteria. Regarding the CanMEDS roles, the Medical Expert role was most frequently represented in the feedback comments, as opposed to the roles Leader and Health Advocate. Discussion: The results highlighted that providing high-quality feedback is challenging. To respond to these challenges, it is recommended to set up individual and continuous feedback training. |
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Language
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English
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Source (journal)
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Perspectives on medical education. - Houten, 2012, currens
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Publication
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Houten
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2023
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ISSN
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2212-2761
[print]
2212-277X
[online]
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DOI
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10.5334/PME.1050
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Volume/pages
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12
:1
(2023)
, p. 584-593
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ISI
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001173324400022
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Pubmed ID
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38144672
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Full text (Publisher's DOI)
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Full text (open access)
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