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

IF 2.2 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Health Informatics Journal Pub Date : 2024-07-01 DOI:10.1177/14604582241272771
Mao Ye, Weifang Xu, Lili Feng, Siqi Liu, Jianhong Yang, Yen-Ching Chuang, Fuqin Tang
{"title":"Improving the academic resilience of hospital nursing interns through a hybrid multi-criteria decision analysis model.","authors":"Mao Ye, Weifang Xu, Lili Feng, Siqi Liu, Jianhong Yang, Yen-Ching Chuang, Fuqin Tang","doi":"10.1177/14604582241272771","DOIUrl":null,"url":null,"abstract":"<p><p><b>Purpose:</b> To identify the main variables affecting the academic adaptability of hospital nursing interns and key areas for improvement in preparing for future unpredictable epidemics. <b>Methods:</b> 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. <b>Results:</b> 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. <b>Conclusions:</b> 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.</p>","PeriodicalId":55069,"journal":{"name":"Health Informatics Journal","volume":"30 3","pages":"14604582241272771"},"PeriodicalIF":2.2000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Informatics Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/14604582241272771","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过混合多标准决策分析模型提高医院护理实习生的学习适应能力。
目的:确定影响医院护理实习生学术适应能力的主要变量,以及在为未来不可预测的流行病做准备时需要改进的关键领域。方法使用随机森林法分析所有护理实习生学习适应性相关变量的重要性,并进一步确定关键变量。通过重要性-绩效分析,找出病例医院护理实习生学术适应能力的主要改进差距。结果显示随机森林显示,与合作、动机、自信、沟通和应对困难相关的五个项目是影响护理实习生学业适应能力的主要变量。此外,重要性-绩效分析显示,有关选项检查、沟通和信心的三个项目是案例医院参与实习的护理实习生的关键改进领域。结论为了预防和控制未来不可预测的流行病,医院护理部可以加强实习生、护士和医生之间的联系,促进他们在临床实践中的合作与交流。同时,可根据本研究的结果创建应用程序,并结合机器学习方法进行更深入的研究。这些都将提高护理实习生在医院日常管理流行病时的学术应变能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Health Informatics Journal
Health Informatics Journal HEALTH CARE SCIENCES & SERVICES-MEDICAL INFORMATICS
CiteScore
7.80
自引率
6.70%
发文量
80
审稿时长
6 months
期刊介绍: Health Informatics Journal is an international peer-reviewed journal. All papers submitted to Health Informatics Journal are subject to peer review by members of a carefully appointed editorial board. The journal operates a conventional single-blind reviewing policy in which the reviewer’s name is always concealed from the submitting author.
期刊最新文献
Empowering healthcare education: A multilingual ontology for medical informatics and digital health (MIMO) integrated to artificial intelligence powered training in smart hospitals. Analysis of health recommendations using longitudinal quality of life data: QoL@TbA - A transformer-based approach. Analysis of total RNA as a potential biomarker of developmental neurotoxicity in silico. Characterizing pituitary adenomas in clinical notes: Corpus construction and its application in LLMs. HealthCheck: A method for evaluating persuasive mobile health applications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1