International medical students‘ improvement in communication skills in psychosomatic care: a natural language processing based analysis [data]
In this study, we evaluated international medical students' communication skills in the context of psychosomatic medicine, after attending a three-day training seminar. Using a pre-post-assessment-design, we assessed the development in communication skills using Natural Language Processing (NLP...
Gespeichert in:
| Hauptverfasser: | , , , , , , |
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| Dokumenttyp: | Datenbank Forschungsdaten |
| Sprache: | Englisch |
| Veröffentlicht: |
Heidelberg
Universität
2025-11-06
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| DOI: | 10.11588/DATA/2ETDYP |
| Schlagworte: | |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.11588/DATA/2ETDYP Verlag, kostenfrei, Volltext: https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/DATA/2ETDYP 
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| Verfasserangaben: | Julia Sgrott, Christoph Nikendei, Ede Nagy, Aleksei Smirnov, Josefina Arias Alvarado, Hans-Christoph Friederich, Ivo Dönnhoff |
MARC
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| 245 | 1 | 0 | |a International medical students‘ improvement in communication skills in psychosomatic care |b a natural language processing based analysis [data] |c Julia Sgrott, Christoph Nikendei, Ede Nagy, Aleksei Smirnov, Josefina Arias Alvarado, Hans-Christoph Friederich, Ivo Dönnhoff |
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| 520 | |a In this study, we evaluated international medical students' communication skills in the context of psychosomatic medicine, after attending a three-day training seminar. Using a pre-post-assessment-design, we assessed the development in communication skills using Natural Language Processing (NLP) as well as traditional rating scales. International students significantly improved their communication style towards a more patient-centered approach. This dataverse contains the following data: all the materials used in the training seminar; the binary and global rating instruments used in the ratings; the rating results; international students' demographic data; the transcription rules in German and English, which were followed in the video transcription process; R-Markdowns with the R code used in statistical analysis of NLP parameters and rating data as well as our results. All participants were anonymized. | ||
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