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Factors Affecting Nursing Students' Perception of Workplace Bullying.

Jeong-Sil ChoiKa Young Kim
Published in: Healthcare (Basel, Switzerland) (2024)
Workplace bullying is a critical and prevalent issue that causes serious problems in healthcare settings. However, there is little research on the factors affecting nursing students' perception of workplace bullying despite their forthcoming transition into the nursing profession. Therefore, this study aimed to identify the factors related to nursing students' perception of workplace bullying in Korea. A cross-sectional study was conducted among 242 nursing students who had experienced clinical practice. The survey questionnaire included general characteristics, perceived susceptibility and severity of bullying, and perception of workplace bullying. Data were analyzed using multiple regression analysis. In this study, the significant factors affecting nursing students' perception of workplace bullying included bullying experience in clinical practice and the perceived severity of bullying. Therefore, it is crucial for nursing managers and instructors to have a clear understanding of the bullying situations experienced by nursing students during clinical practice. We should promote the perception of workplace bullying through indirect experiences such as systematic education about workplace bullying for nursing students, which may prevent workplace bullying in clinical practice and work environments. Furthermore, a comprehensive and multifaceted approach is necessary to effectively prevent workplace bullying in clinical practice and work environments. This study reveals that systemic and persistent education and intervention to bullying may improve nursing students' perception of workplace bullying and prevent workplace bullying in clinical practice and work environments. Furthermore, this study provides basic data on the prevention and management of bullying in nursing students' clinical practice.
Keyphrases
  • nursing students
  • clinical practice
  • healthcare
  • high school
  • mental health
  • health promotion
  • randomized controlled trial
  • depressive symptoms
  • machine learning
  • social media
  • big data
  • health insurance