A novel multi-measure approach to study medical students' communication performance and predictors of their communication quality - a cross-sectional study

  • Background: Successful doctor-patient communication is a critical component of effective medical treatment and therefore plays a crucial role already in medical training. The aim of this cross-sectional study was to employ a multi-measure approach assessing different perspectives and variables to investigate how medical students' communication performance differs across medical training (1st vs. 5th or 7th semester). Methods: 43 medical students (1st semester: N = 23; 5th or 7th semester: N = 20) engaged in a simulated doctor-patient consultation with a standardized patient (SP) while being videorecorded. Medical students' communication quality was assessed by a communication expert and by the SP (both being blinded regarding the semester of the medical student) using standardized questionnaires (Berliner Global Rating Scale, Medical Interview Satisfaction Scale). Following our multi-measure approach, we also assessed several non-verbal parameters and variables (back-channeling,Background: Successful doctor-patient communication is a critical component of effective medical treatment and therefore plays a crucial role already in medical training. The aim of this cross-sectional study was to employ a multi-measure approach assessing different perspectives and variables to investigate how medical students' communication performance differs across medical training (1st vs. 5th or 7th semester). Methods: 43 medical students (1st semester: N = 23; 5th or 7th semester: N = 20) engaged in a simulated doctor-patient consultation with a standardized patient (SP) while being videorecorded. Medical students' communication quality was assessed by a communication expert and by the SP (both being blinded regarding the semester of the medical student) using standardized questionnaires (Berliner Global Rating Scale, Medical Interview Satisfaction Scale). Following our multi-measure approach, we also assessed several non-verbal parameters and variables (back-channeling, turn-taking, verbal dominance, automatic analysis of emotional facial expressions, skin conductance level). Results: Analysis of non-verbal measures demonstrates that advanced students used more back-channeling, displayed more facial expressions of happiness and showed elevated skin conductance levels compared to 1st semester students. These non-verbal parameters could significantly predict the expert's communication quality assessment, explaining 31% of the variance in communication quality. As expected, the expert and SP rated the communication quality of 5th /7th semester students as significantly better compared to 1st semester students. Conclusions: We found that non-verbal parameters significantly differed between students of early vs. later stages of their medical training and were predictive of communication quality. Especially, sympathetic responsiveness - likely indicating the level of involvement - correlated with expert evaluations. These findings suggest that effective communication becomes evident across different channels and that sincere engagement into a conversation might be a requisite for successful doctor-patient communication.show moreshow less

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Metadaten
Author:Giulia ZerbiniORCiDGND, Pia Schneider, Miriam ReichertsORCiD, Nina Roob, Kathrin Jung-Can, Miriam KunzGND, Philipp ReichertsGND
URN:urn:nbn:de:bvb:384-opus4-1219622
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/121962
ISSN:1472-6920OPAC
Parent Title (English):BMC Medical Education
Publisher:Springer Science and Business Media LLC
Type:Article
Language:English
Year of first Publication:2025
Publishing Institution:Universität Augsburg
Release Date:2025/05/15
Volume:25
Issue:1
First Page:685
DOI:https://doi.org/10.1186/s12909-025-07018-9
Institutes:Medizinische Fakultät
Medizinische Fakultät / Lehrstuhl für Medical Education Sciences
Medizinische Fakultät / Lehrstuhl für Medizinische Psychologie und Soziologie
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)