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Clinical supervision in medical education: A citation analysis.

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Title: Clinical supervision in medical education: A citation analysis.
Authors: Baker, M. J.1,2 matthew.baker1@usuhs.edu, Maggio, L. A.1, Dorris, C. S.3, Uijtdehaage, S.1, Soh, M.1
Source: Medical Teacher. Apr2024, Vol. 46 Issue 4, p505-511. 7p.
Subject Terms: *Medical education, *Bibliographic databases, *Citation analysis, Supervision of employees, Clinical supervision, Translational research
Abstract: Medical education relies on clinical supervision for critical functions, including trainee assessment and ensuring patient safety. Yet, there is substantial variance in supervision, which has led to calls for a shared definition of the concept and guidelines to inform practice. AMEE Guide No. 27 provided these desired elements and is highly cited, suggesting that translation and utilization of the Guide's knowledge is suboptimal. This study investigates utilization by systematically characterizing citations to the Guide and by describing translation of its recommendations in relation to supervision. Citations were identified using Web of Science, Scopus, and Google Scholar. The authors coded all citations and conducted a subanalysis of studies specific to supervision. 583 studies were identified; 268 met inclusion criteria for general analysis of which 167 studies were further analyzed. Most studies reiterated the Guide's characterization of effective supervision, but few demonstrate how these recommendations inform innovations in supervisory practice. Translation of the Guide's recommendations regarding clinical supervision appears limited. Future research should consider the extent of knowledge translation occurring in clinical supervision literature as well as AMEE Guides. Increased attention to knowledge translation in medical education may benefit the distribution of similar knowledge products. [ABSTRACT FROM AUTHOR]
Copyright of Medical Teacher is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Medical education relies on clinical supervision for critical functions, including trainee assessment and ensuring patient safety. Yet, there is substantial variance in supervision, which has led to calls for a shared definition of the concept and guidelines to inform practice. AMEE Guide No. 27 provided these desired elements and is highly cited, suggesting that translation and utilization of the Guide's knowledge is suboptimal. This study investigates utilization by systematically characterizing citations to the Guide and by describing translation of its recommendations in relation to supervision. Citations were identified using Web of Science, Scopus, and Google Scholar. The authors coded all citations and conducted a subanalysis of studies specific to supervision. 583 studies were identified; 268 met inclusion criteria for general analysis of which 167 studies were further analyzed. Most studies reiterated the Guide's characterization of effective supervision, but few demonstrate how these recommendations inform innovations in supervisory practice. Translation of the Guide's recommendations regarding clinical supervision appears limited. Future research should consider the extent of knowledge translation occurring in clinical supervision literature as well as AMEE Guides. Increased attention to knowledge translation in medical education may benefit the distribution of similar knowledge products. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Medical Teacher is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/0142159X.2023.2257375
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              Text: Apr2024
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