The effect of artificial intelligence supported case analysis on nursing students' case management performance and satisfaction: A randomized controlled trial

IF 3.3 3区医学 Q1 NURSING

Nurse Education in Practice Pub Date : 2024-09-12 DOI:10.1016/j.nepr.2024.104142

{"title":"The effect of artificial intelligence supported case analysis on nursing students' case management performance and satisfaction: A randomized controlled trial","authors":"","doi":"10.1016/j.nepr.2024.104142","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Rapid developments in artificial intelligence have begun to necessitate changes and transformations in nursing education.</p></div><div><h3>Objective</h3><p>This study aimed to evaluate the impact of an artificial intelligence-supported case created in the in-class case analysis lecture for nursing students on students' case management performance and satisfaction.</p></div><div><h3>Design</h3><p>This study was a randomized controlled trial.</p></div><div><h3>Method</h3><p>The study involved 188 third-year nursing students randomly assigned to the AI group (n=94) or the control group (n=94). An information form, case evaluation form, knowledge test and Mentimeter application were used to assess the students' case management performance and nursing diagnoses. The level of satisfaction with the case analysis lecture was evaluated using the VAS scale.</p></div><div><h3>Results</h3><p>The case management performance scores of the students in the artificial intelligence group were significantly higher than those of the control group (p<0.05). There was no statistically significant difference in satisfaction levels between the artificial intelligence (AI) group and the control group (p>0.05).</p></div><div><h3>Conclusions</h3><p>The study's results indicated that AI-supported cases improved students' case management performance and were as effective as instructor-led cases regarding satisfaction with the case analysis lecture, focus and interest in the case. The integration of artificial intelligence into traditional nursing education curricula is recommended.</p></div><div><h3>Clinical trials registration number</h3><p><span><span>https://register.clinicaltrials.gov</span><svg><path></path></svg></span>; (NCT06443983).</p></div>","PeriodicalId":48715,"journal":{"name":"Nurse Education in Practice","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nurse Education in Practice","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1471595324002713","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}

引用次数: 0

Abstract

Background

Rapid developments in artificial intelligence have begun to necessitate changes and transformations in nursing education.

Objective

This study aimed to evaluate the impact of an artificial intelligence-supported case created in the in-class case analysis lecture for nursing students on students' case management performance and satisfaction.

Design

This study was a randomized controlled trial.

Method

The study involved 188 third-year nursing students randomly assigned to the AI group (n=94) or the control group (n=94). An information form, case evaluation form, knowledge test and Mentimeter application were used to assess the students' case management performance and nursing diagnoses. The level of satisfaction with the case analysis lecture was evaluated using the VAS scale.

Results

The case management performance scores of the students in the artificial intelligence group were significantly higher than those of the control group (p<0.05). There was no statistically significant difference in satisfaction levels between the artificial intelligence (AI) group and the control group (p>0.05).

Conclusions

The study's results indicated that AI-supported cases improved students' case management performance and were as effective as instructor-led cases regarding satisfaction with the case analysis lecture, focus and interest in the case. The integration of artificial intelligence into traditional nursing education curricula is recommended.

Clinical trials registration number

https://register.clinicaltrials.gov; (NCT06443983).

查看原文本刊更多论文

人工智能支持的病例分析对护理专业学生病例管理绩效和满意度的影响：随机对照试验

背景人工智能的快速发展已开始要求护理教育进行变革和转型。目的本研究旨在评估在护理学生课内病例分析讲座中创建的人工智能辅助病例对学生病例管理表现和满意度的影响。使用信息表、病例评估表、知识测试和 Mentimeter 应用程序来评估学生的病例管理绩效和护理诊断。结果人工智能组学生的病例管理成绩得分明显高于对照组（p<0.05）。结论研究结果表明，人工智能支持的病例提高了学生的病例管理绩效，在对病例分析讲座的满意度、对病例的关注和兴趣方面，人工智能支持的病例与教师指导的病例同样有效。建议将人工智能融入传统护理教育课程。临床试验注册号：https://register.clinicaltrials.gov; (NCT06443983)。

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分钟内获得全文求助全文

来源期刊

Nurse Education in Practice NURSING-

CiteScore

5.40

自引率

9.40%

发文量

180

审稿时长

51 days

期刊介绍： Nurse Education in Practice enables lecturers and practitioners to both share and disseminate evidence that demonstrates the actual practice of education as it is experienced in the realities of their respective work environments. It is supportive of new authors and will be at the forefront in publishing individual and collaborative papers that demonstrate the link between education and practice.

文献相关原料

公司名称	产品信息	采购帮参考价格