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

BACKGROUND: Mentoring 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...

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Detalles Bibliográficos
Autores principales: Gernert, Jonathan A., Warm, Maximilian, Salvermoser, Lukas, Krüger, Nils, Bethe, Stephan, Kocheise, Lorenz, von Hake, Malte, Meyer-Schwickerath, Charlotte, Graupe, Tanja, Fischer, Martin R., Dimitriadis, Konstantinos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636985/
https://www.ncbi.nlm.nih.gov/pubmed/37946146
http://dx.doi.org/10.1186/s12909-023-04804-1
Descripción
Sumario:BACKGROUND: Mentoring 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. METHODS: In 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. RESULTS: Students 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. CONCLUSION: The introduced classification system helps to understand how mentoring profile texts are composed and which aspects are important for choosing a suited mentor. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12909-023-04804-1.