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Future doctors' silence: An empirical study of declining speaking-up behavior among medical students.

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Title: Future doctors' silence: An empirical study of declining speaking-up behavior among medical students.
Authors: Chen, Hui-Wen1 (AUTHOR), Chen, Yi-Chun2 (AUTHOR), Tsai, Hung-Wei3 (AUTHOR), Kang, Enoch Yi-No4 (AUTHOR), Wu, Jen-Chieh3 (AUTHOR) lendiswu@tmu.edu.tw, Issenberg, S. Barry5 (AUTHOR)
Source: Medical Teacher. Apr2026, Vol. 48 Issue 4, p568-578. 11p.
Subject Terms: *Academic medical centers, *Data analysis, *Health occupations students, *Internship programs, *Experience, *Students, *Longitudinal method, *Communication, *Clinical competence, *Psychology of medical students, *Clinical education, *Student attitudes, *Comparative studies, Prevention of medical errors, Cross-sectional method, Patient safety, Research funding, Sex distribution, Empirical research, Multiple regression analysis, Pilot projects, Age distribution, Descriptive statistics, Multivariate analysis, Catastrophic illness, Patient advocacy, Statistics, Data analysis software
Geographic Terms: Taiwan
Abstract: Introduction: Speaking-up behavior is crucial for preventing patient harm, yet evidence suggests that increased clinical experience does not necessarily promote it. Gender, contextual factors, and prior patient safety training may also influence speaking-up tendencies, but research on their interaction remains limited. To address this gap, this study examines the impact of clinical experience, gender, patient safety training, and scenario severity on speaking-up behavior to inform targeted educational interventions. Methods: This cross-sectional study analyzed 306 medical students from two cohorts (2020 and 2023) at a medical university in Northern Taiwan. A simulation-based assessment session evaluated students' speaking-up behavior in life-threatening and non-life-threatening medical error scenarios. Data on clinical experience, gender, and prior patient safety training were collected. Speaking-up behavior was assessed using the Speaking-Up Behavior Checklist, and binary logistic regression was conducted to examine associations. Results: Increased clinical experience was significantly associated with lower speaking-up behavior (Exp(B) = 0.916, p = 0.005), particularly among male students, while female students' behavior remained unchanged. Additionally, students were less likely to speak up in life-threatening scenarios (Exp(B) = 0.886, p = 0.007), while scenario type had no significant effect on those with less clinical experience. Prior patient safety training was not significantly associated with speaking-up behavior. Discussion: These findings suggest that clinical experience, gender, and scenario influence speaking-up behavior. While clinical skills improve with experience, heightened hierarchical awareness and professional relationships may increase hesitation. This implies the importance of structured policies, targeted training, and cultural transformation to foster a safe environment for speaking up. Future research should also examine psychological and organizational factors to better guide educational and systemic interventions. [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.)
Database: Education Research Complete
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  Data: Introduction: Speaking-up behavior is crucial for preventing patient harm, yet evidence suggests that increased clinical experience does not necessarily promote it. Gender, contextual factors, and prior patient safety training may also influence speaking-up tendencies, but research on their interaction remains limited. To address this gap, this study examines the impact of clinical experience, gender, patient safety training, and scenario severity on speaking-up behavior to inform targeted educational interventions. Methods: This cross-sectional study analyzed 306 medical students from two cohorts (2020 and 2023) at a medical university in Northern Taiwan. A simulation-based assessment session evaluated students' speaking-up behavior in life-threatening and non-life-threatening medical error scenarios. Data on clinical experience, gender, and prior patient safety training were collected. Speaking-up behavior was assessed using the Speaking-Up Behavior Checklist, and binary logistic regression was conducted to examine associations. Results: Increased clinical experience was significantly associated with lower speaking-up behavior (Exp(B) = 0.916, p = 0.005), particularly among male students, while female students' behavior remained unchanged. Additionally, students were less likely to speak up in life-threatening scenarios (Exp(B) = 0.886, p = 0.007), while scenario type had no significant effect on those with less clinical experience. Prior patient safety training was not significantly associated with speaking-up behavior. Discussion: These findings suggest that clinical experience, gender, and scenario influence speaking-up behavior. While clinical skills improve with experience, heightened hierarchical awareness and professional relationships may increase hesitation. This implies the importance of structured policies, targeted training, and cultural transformation to foster a safe environment for speaking up. Future research should also examine psychological and organizational factors to better guide educational and systemic interventions. [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.2025.2570818
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        Text: English
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