Department of Pediatric Nursing, Faculty of Health Sciences, Kütahya University of Health Sciences, Kütahya, Turkey.
Department of Pediatric Nursing, Faculty of Health Sciences, Eskisehir Osmangazi University, Eskişehir, Turkey.
J Eval Clin Pract. 2024 Oct;30(7):1319-1326. doi: 10.1111/jep.14062. Epub 2024 Jun 18.
Evaluating future nurses' perspectives on artificial intelligence, determining their missing or incorrect information on the subject and determining their anxiety levels are of great importance in terms of providing science and technology-based health services in the future.
This research was conducted to evaluate the knowledge, attitude and anxiety levels of future nurses about artificial intelligence applications.
The research was a descriptive type, conducted with 552 nursing students. In collecting data, 'Data collection form' and 'Artificial Intelligence Anxiety Scale' (AIAS) were used. Analysis of data was performed with descriptive statistics, Kolmogorov-Smirnov, Shapiro-Wilk, Spearman, Mann-Whitney U and Kruskal-Wallis tests. In the study, p < 0.05 value was considered statistically significant.
It was determined that the students' average AIAS score was 51.68 ± 12.32. It was determined that 95.3% of the students did not receive training on artificial intelligence, and 94.0% did not have artificial intelligence-related subjects in their school courses. It was determined that 79.2% of the students wanted artificial intelligence-related subjects to be included in school courses.
In the study, it was determined that the artificial intelligence anxiety levels of nursing students were high. It has been determined that students with negative feelings about artificial intelligence have higher artificial intelligence anxiety levels. Our suggestion; adding courses or subjects related to artificial intelligence to the university curriculum and starting to include nurses in the working processes during their student years.
评估未来护士对人工智能的看法,确定他们在该主题上缺失或错误的信息,并确定他们的焦虑水平,这对于未来提供基于科学技术的医疗服务非常重要。
本研究旨在评估未来护士对人工智能应用的知识、态度和焦虑水平。
该研究为描述性研究,共纳入 552 名护理专业学生。在数据收集过程中,使用了“数据收集表”和“人工智能焦虑量表”(AIAS)。数据分析采用描述性统计、Kolmogorov-Smirnov、Shapiro-Wilk、Spearman、Mann-Whitney U 和 Kruskal-Wallis 检验。在研究中,p 值<0.05 被认为具有统计学意义。
研究发现,学生的平均 AIAS 得分为 51.68±12.32。95.3%的学生没有接受过人工智能培训,94.0%的学生在学校课程中没有人工智能相关科目。79.2%的学生希望在学校课程中加入人工智能相关科目。
研究表明,护理学生的人工智能焦虑水平较高。对人工智能持负面情绪的学生,其人工智能焦虑水平更高。我们建议将与人工智能相关的课程或科目添加到大学课程中,并在学生时代开始让护士参与工作流程。