Maraş Gülseren, Albayrak Günday Eda, Sürme Yeliz
Erciyes University, Faculty of Health Sciences, Surgical Nursing, Kayseri, Türkiye.
Erciyes University, Faculty of Health Sciences, Mental Health and Disease Nursing, Kayseri, Türkiye.
J Clin Nurs. 2024 Nov 18. doi: 10.1111/jocn.17562.
This study examined the anxiety levels of nurses and nurse candidates regarding humanoid nurse robots and artificial intelligence health technologies in perioperative patient care.
Descriptive and cross-sectional study.
The research was conducted with 158 intern students and 167 surgical nurses. Socio-demographic characteristics form, Questions Form Regarding Humanoid Nurse Robots and Artificial Intelligence Health Technologies, Artificial Intelligence Anxiety Scale and The Medical Artificial Intelligence Preparedness Scale were used. The independent t-test and one-way analysis of variance (ANOVA) were used. This study complied with Appendix S1.
The total scores on the Artificial Intelligence Anxiety Scale for nurses and nursing students are 73.089 ± 31.667 and 73.624 ± 28.029, respectively. The total scores on the Artificial Intelligence Readiness Scale for nurses and nursing students are 71.736 ± 15.064 and 72.183 ± 13.714, respectively. When comparing the sociodemographic characteristics and scale scores of nurses, a statistically significant difference was found between age and the Artificial Intelligence Anxiety Scale scores (p < 0.05). There was also a statistically significant difference between age, gender and work duration and the Artificial Intelligence Readiness Scale scores for nurses (p < 0.05).
Both groups exhibited moderate levels of anxiety and readiness regarding artificial intelligence. Comprehensive research is needed to elucidate the impact of artificial intelligence technologies on nursing professionals.
The proper use of Artificial Intelligence technologies can enhance the quality of patient care, alleviate the workload, increase patient and staff satisfaction and foster new perspectives on acceptance. With their integration into clinics, a patient-centred care environment will emerge, improving patient safety, outcomes and overall well-being. Thus, the anxieties of nurses and students towards artificial intelligence technologies will decrease, and their readiness will increase.
No Patient or Public Contribution.
本研究调查了护士及护士候选人在围手术期患者护理中对人形护士机器人和人工智能健康技术的焦虑水平。
描述性横断面研究。
对158名实习学生和167名外科护士进行了研究。使用了社会人口学特征表、关于人形护士机器人和人工智能健康技术的问题表、人工智能焦虑量表和医学人工智能准备量表。采用独立t检验和单因素方差分析（ANOVA）。本研究符合附录S1。
护士和护生在人工智能焦虑量表上的总分分别为73.089±31.667和73.624±28.029。护士和护生在人工智能准备量表上的总分分别为71.736±15.064和72.183±13.714。比较护士的社会人口学特征和量表得分时，年龄与人工智能焦虑量表得分之间存在统计学显著差异（p<0.05）。护士的年龄、性别和工作时长与人工智能准备量表得分之间也存在统计学显著差异（p<0.05）。
两组在人工智能方面均表现出中等程度的焦虑和准备水平。需要进行全面研究以阐明人工智能技术对护理专业人员的影响。
正确使用人工智能技术可以提高患者护理质量、减轻工作量、提高患者和员工满意度，并培养新的接受观念。随着它们融入临床，将出现以患者为中心的护理环境，提高患者安全性、改善治疗效果并增进整体健康。因此，护士和学生对人工智能技术的焦虑将会减少，他们的准备程度将会提高。
无患者或公众贡献。
