Department of Intensive Care Unit, Taizhou Central Hospital, Taizhou University, Taizhou, Zhejiang, China.
Department of Orthopedics, Taizhou Central Hospital, Taizhou University, Taizhou, Zhejiang, China.
Health Informatics J. 2024 Jul-Sep;30(3):14604582241272771. doi: 10.1177/14604582241272771.
To identify the main variables affecting the academic adaptability of hospital nursing interns and key areas for improvement in preparing for future unpredictable epidemics. 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. 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. 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.
为了确定影响医院护理实习生学术适应性的主要变量以及为未来不可预测的流行病做准备的关键改进领域。采用随机森林方法分析了与学术适应能力相关的重要变量，并进一步确定了关键变量。采用重要性-绩效分析，确定了案例医院护理实习生学术适应能力的关键改进差距。随机森林显示，与合作、动机、信心、沟通和应对困难相关的五个项目是影响护理实习生学术适应能力的主要变量。此外，重要性-绩效分析显示，关于选择考试、沟通和信心的三个项目是案例医院参与护理实习生的关键改进领域。 为了预防和控制未来不可预测的大流行，医院护理部门可以加强实习生、护士和医生之间的联系，并在临床实践中促进他们的合作和沟通。同时，可以根据本研究的结果创建一个应用程序，并结合机器学习方法进行更深入的研究。这些将在医院大流行的常规管理中提高护理实习生的学术适应能力。
