Characteristics and quality assessment of online mentoring profile texts in academic medical mentoring

被引:1
作者
Gernert, Jonathan A. [1 ,2 ]
Warm, Maximilian [1 ]
Salvermoser, Lukas [1 ,3 ]
Krueger, Nils [1 ]
Bethe, Stephan [1 ]
Kocheise, Lorenz [1 ]
von Hake, Malte [1 ]
Meyer-Schwickerath, Charlotte [1 ,4 ]
Graupe, Tanja [1 ]
Fischer, Martin R. [1 ]
Dimitriadis, Konstantinos [1 ,5 ,6 ]
机构
[1] LMU Univ Hosp, Inst Med Educ, Pettenkoferstr 8a, D-80336 Munich, Germany
[2] LMU Univ Hosp, Inst Clin Neuroimmunol, Munich, Germany
[3] LMU Univ Hosp, Dept Radiol, Munich, Germany
[4] Univ Cologne, Univ Hosp Cologne, Fac Med, Dept Internal Med 1, Cologne, Germany
[5] LMU Univ Hosp, Dept Neurol, Munich, Germany
[6] LMU Univ Hosp, Inst Stroke & Dementia Res ISD, Munich, Germany
关键词
Medical mentoring; Online matching; Online mentoring profiles; PROGRAMS; FACULTY;
D O I
10.1186/s12909-023-04804-1
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
BackgroundMentoring is important for a successful career in academic medicine. In online matching processes, profile texts are decisive for the mentor-selection. We aimed to qualitatively characterize mentoring-profile-texts, identify differences in form and content and thus elements that promote selection.MethodsIn a mixed method study first, quality of texts in 150 selected mentoring profiles was evaluated (10-point Likert scale; 1 = insufficient to 10 = very good). Second, based on a thematic and content analysis approach of profile texts, categories and subcategories were defined. We compared the presence of the assigned categories between the 25% highest ranked profiles with the 25% lowest ranked ones. Finally, additional predefined categories (hot topics) were labelled on the selected texts and their impact on student evaluation was statistically examined.ResultsStudents rated the quality of texts with a mean of 5.89 +/- 1.45. 5 main thematic categories, 21 categories and a total of 74 subcategories were identified. Ten subcategories were significantly associated with high- and four with low-rated profiles. The presence of three or more hot topics in texts significantly correlated with a positive evaluation.ConclusionThe introduced classification system helps to understand how mentoring profile texts are composed and which aspects are important for choosing a suited mentor.
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页数:8
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