Ramadan Osama Mohamed Elsayed, Alruwaili Majed Mowanes, Alruwaili Abeer Nuwayfi, Elsehrawy Mohamed Gamal, Alanazi Sulaiman
College of Nursing, Department of Maternity and Pediatric Health Nursing, Jouf University, Sakaka, 72388, Saudi Arabia.
College of Nursing, Nursing Administration and Education Department, Jouf University, Sakaka, 72388, Saudi Arabia.
BMC Nurs. 2024 Dec 18;23(1):891. doi: 10.1186/s12912-024-02571-y.
Integrating Artificial Intelligence (AI) in nursing practice is revolutionising healthcare by enhancing clinical decision-making and patient care. However, the adoption of AI by registered nurses, especially in varied healthcare settings such as Saudi Arabia, remains underexplored. Understanding the facilitators and barriers from the perspective of frontline nurses is crucial for successful AI implementation.
This study aimed to explore registered nurses' perspectives on the facilitators and barriers to AI adoption in nursing practice in Saudi Arabia and to propose an extended Technology Acceptance Model for AI in Nursing (TAM-AIN).
A qualitative study utilising focus group discussions was conducted with 48 registered nurses from four major healthcare facilities in Al-Kharj, Saudi Arabia. Thematic analysis, guided by the Technology Acceptance Model framework, was employed to analyse the data.
Key facilitators of AI adoption included perceived benefits to patient care (85%), strong organisational support (70%), and comprehensive training programs (75%). Primary barriers involved technical challenges (60%), ethical concerns regarding patient privacy (55%), and fears of job displacement (45%). These findings led to the development of TAM-AIN, an extended model that incorporates additional constructs such as ethical alignment, organisational readiness, and perceived threats to professional autonomy.
AI adoption in nursing practice requires a holistic approach that addresses technical, educational, ethical, and organisational challenges. The proposed TAM-AIN offers a comprehensive framework for optimising AI integration into nursing practice, emphasising the importance of nurse-centred implementation strategies. This model provides healthcare institutions and policymakers with a robust tool to facilitate successful AI adoption and enhance patient outcomes.
将人工智能(AI)融入护理实践正在通过加强临床决策和患者护理来彻底改变医疗保健行业。然而,注册护士对AI的采用情况,尤其是在沙特阿拉伯等不同的医疗环境中,仍未得到充分探索。从一线护士的角度了解促进因素和障碍对于AI的成功实施至关重要。
本研究旨在探讨沙特阿拉伯注册护士对护理实践中采用AI的促进因素和障碍的看法,并提出一个扩展的护理领域人工智能技术接受模型(TAM-AIN)。
对来自沙特阿拉伯哈吉尔四个主要医疗机构的48名注册护士进行了焦点小组讨论的定性研究。在技术接受模型框架的指导下,采用主题分析法对数据进行分析。
采用AI的关键促进因素包括对患者护理的感知益处(85%)、强大的组织支持(70%)和全面的培训计划(75%)。主要障碍包括技术挑战(60%)、对患者隐私的伦理担忧(55%)以及对工作岗位被取代的恐惧(45%)。这些发现促成了TAM-AIN的发展,这是一个扩展模型,纳入了诸如伦理一致性、组织准备情况和对职业自主权的感知威胁等额外的构念。
护理实践中采用AI需要一种全面的方法来应对技术、教育、伦理和组织方面的挑战。所提出的TAM-AIN为优化AI融入护理实践提供了一个全面的框架,强调了以护士为中心的实施策略的重要性。该模型为医疗机构和政策制定者提供了一个强大的工具,以促进AI的成功采用并改善患者结局。