동서간호학연구지 (Journal of East-West Nursing Research)

  • 제29권1호
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  • Pages.68-77
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  • 2023
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  • 1226-4938(pISSN)
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  • 2671-8448(eISSN)
경희대학교 동서간호학연구소 (East-west Nursing Research Institute, Kyung Hee University)
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의사결정나무 분석기법을 이용한 상급종합병원 간호사의 이직 예측모형 구축

A Predictive Model of Turnover among Nurses in a Tertiary Hospital: Decision Tree Analysis

  • Kang, Kyung Ok (Department of Nursing, Jeonbuk National University Hospital) ;
  • Han, Nara (Department of Nursing, Jeonbuk National University Hospital) ;
  • Jeong, Jeong A (Department of Nursing, Jeonbuk National University Hospital) ;
  • Choi, Young Eun (Department of Nursing, Jeonbuk National University Hospital) ;
  • Park Jin Kyung (Department of Nursing, Jeonbuk National University Hospital) ;
  • Jeong, Seok Hee (College of Nursing.Research Institute of Nursing Science, Jeonbuk National University)
  • 투고 : 2023.03.10
  • 심사 : 2023.05.07
  • 발행 : 2023.05.31
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초록

Purpose: The purposes of this study were to develop a predictive model and evaluate this model of turnover in hospital nurses. Methods: Participants were 1,565 nurses from a tertiary hospital in South Korea. Descriptive statistics and a decision-tree analysis were performed using the SPSS WIN 23.0 program. Results: The turnover groups were presented in eleven different pathways by decision tree analysis. There were three high-risk groups with a higher turnover rate than the average, and eight low-risk groups with a lower turnover rate. Among them, two low-risk groups had a 0% turnover rate. The groups were classified according to general characteristics such as position, period of temporary position, clinical career at last working unit, total clinical career, and period of leave of absence. The accuracy of the model was 83.2%, sensitivity 63.7%, and specificity 98.1%. Conclusion: This predictive model of turnover may be used to screen the turnover risk groups and contribute for decreasing the turnover of hospital nurses in South Korea.

키워드

과제정보

본 연구는 2022년 전북대학교병원 간호부의 지원을 받아 수행됨.

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