Improving the academic resilience of hospital nursing interns through a hybrid multi-criteria decision analysis model

Author:

Ye Mao1,Xu Weifang2,Feng Lili3,Liu Siqi1,Yang Jianhong2,Chuang Yen-Ching456ORCID,Tang Fuqin3

Affiliation:

1. Department of Intensive Care Unit, Taizhou Central Hospital, Taizhou University, Taizhou, Zhejiang, China

2. Department of Orthopedics, Taizhou Central Hospital, Taizhou University, Taizhou, Zhejiang, China

3. Nursing Department, Taizhou Central Hospital, Taizhou University, Taizhou, Zhejiang, China

4. Institute of Public Health and Emergency Management, Taizhou University, Taizhou, China

5. Business College, Taizhou University, Taizhou, China

6. Key Laboratory of Evidence-based Radiology of Taizhou, Linhai, Zhejiang, China

Abstract

Purpose: To identify the main variables affecting the academic adaptability of hospital nursing interns and key areas for improvement in preparing for future unpredictable epidemics. Methods: The importance of academic resilience-related variables for all nursing interns was analyzed using the random forest method, and key variables were further identified. An importance-performance analysis was used to identify the key improvement gaps regarding the academic resilience of nursing interns in the case hospital. Results: The random forest showed that five items related to cooperation, motivation, confidence, communication, and difficulty with coping were the main variables impacting the academic resilience of nursing interns. Moreover, the importance-performance analysis revealed that three items regarding options examination, communication, and confidence were the key improvement areas for participating nursing interns in the case hospital. Conclusions: For the prevention and control of future unpredictable pandemics, hospital nursing departments can strengthen the link between interns, nurses, and physicians and promote their cooperation and communication during clinical practice. At the same time, an application can be created considering the results of this study and combined with machine learning methods for more in-depth research. These will improve the academic resilience of nursing interns during the routine management of pandemics within hospitals.

Funder

the Education Planning Project of Taizhou City, Zhejiang Province

Nursing Discipline Development Special Fund Project of Taizhou University, Zhejiang Province

The Zhejiang Medical and Health Science and Technology Program

Publisher

SAGE Publications

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