Analysis on the status and influencing factors of evidence-based nursing competence among clinical nurses in tertiary grade A hospitals of Anhui province nurses based on random forest model
10.3760/cma.j.cn211501-20231203-01189
- VernacularTitle:基于随机森林模型的安徽省三级甲等医院临床护士循证护理能力现状及影响因素分析
- Author:
Dong XU
1
;
Xi WANG
;
Guixia XU
;
Long ZHAO
;
Manyu ZHANG
;
Yixin WANG
Author Information
1. 蚌埠医科大学护理学院，蚌埠 233030
- Keywords:
Clinical nurses;
Evidence-based nursing competence;
Random forest model;
Influencing factors
- From:
Chinese Journal of Practical Nursing
2024;40(18):1395-1402
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the status of evidence-based nursing competence among clinical nurses in tertiary grade A hospitals of Anhui province, and analyze the influencing factors based on random forest model, so as to provide reference for improving the evidence-based nursing ability of clinical nurses and formulating intervention strategies.Methods:The convenience sampling method was used to select 543 clinical nurses from 4 tertiary grade A hospitals in Anhui Province from October to December 2022. The general data questionnaire, Evidence-based Nursing Competence Scale, Information Literacy Scale, and Nurse Innovation Ability Scale were used to investigate. The random forest model was used to evaluate the importance of the influencing factors. The Lasso regression analysis was used to complete the screening of the influencing factors. The influencing factors of the evidence-based nursing competence among clinical nurses were explored by multiple linear regression analysis.Results:A total of 543 valid questionnaires were retrieved. Among 543 clinical nurses, 55 males and 388 females, aged (32.34 ± 6.93) years old. Evidence-based nursing competence scored (45.49 ± 21.18) points, information literacy scored (73.50 ± 10.47) points, innovation ability scored (126.78 ± 21.99) points. The random forest model and Lasso regression analysis showed that the model achieved the best fit with 8 variables. In order of importance, the top 8 variables were information literacy (25.78%), innovation ability (22.37%), night shift per month (9.91%), educational background (9.19%), English proficiency (8.44%), professional title (6.71%), scientific research and innovation experience (5.17%), and professional attitude (4.50%). Multiple linear regression analysis showed that information literacy, innovation ability, and English proficiency were the influencing factors of evidence-based nursing competence among clinical nurses ( t=9.17, 7.31, 2.52, all P<0.05). Conclusions:The level of evidence-based nursing ability among clinical nurses in tertiary grade A hospitals of Anhui province needs to be improved. From the perspective of improving the information literacy among clinical nurses, nursing managers can increase the training of information retrieval ability and English ability, enhance their English literature reading skills, pay attention to the cultivation of nurses' innovation ability, stimulate the innovative consciousness and thinking among clinical nurses, formulate and implement targeted interventions, so as to gradually improve the level of evidence-based nursing ability among clinical nurses.
