Ta'an Wafa'a, Damrah Sadeq, Al-Hammouri Mohammed M, Williams Brett
Community and Mental Health Nursing Department, Faculty of Nursing, Jordan University of Science and Technology, Irbid, Jordan.
Department of Mathematics and Physics, College of Engineering, Australian University, Safat, Kuwait.
PLoS One. 2025 May 16;20(5):e0322794. doi: 10.1371/journal.pone.0322794. eCollection 2025.
In contemporary healthcare practices, the convergence of Artificial Intelligence (AI) and interprofessional collaboration represents a transformative era marked by unprecedented opportunities and challenges. The introduction of AI technologies is assumed to lead to changes in the nature of interprofessional collaboration that require revisiting the already established professional identity; however, research is lacking in the area.
To examine professional identity and its relationships with AI readiness domains and interprofessional collaboration components.
A multisite cross-sectional research design was used to recruit 512 participants from different healthcare professions in Jordan between November 14th, 2023, and February 13th, 2024. The Medical Artificial Intelligence Readiness Scale and the Readiness for Interprofessional Learning Scale were used in data collection. Data analysis included descriptive, correlation, and comparative analyses.
Professional identity significantly and positively correlated with artificial intelligence readiness total and subscale scores with ρ ranging from 0.37 to 0.47 (p < .01). In addition, professional identity significantly correlated with interprofessional teamwork and collaboration (ρ=0.79, p < .01) and the roles and responsibilities components of interprofessional collaboration (ρ=0.37, p < .01). Professional identity was significantly higher among male participants and participants with experience of five years or higher.
The study sets the grounding roles to develop the healthcare workforce's professional identity within the dynamic healthcare environment in the age of artificial intelligence and interprofessional collaboration. The study highlights areas of development for healthcare managers and practitioners, such as AI interprofessional collaboration-based training, targeting both artificial intelligence domains and interprofessional collaboration components while preserving a positive professional identity.
在当代医疗实践中，人工智能（AI）与跨专业协作的融合代表了一个变革的时代，具有前所未有的机遇和挑战。人们认为，人工智能技术的引入会导致跨专业协作性质的变化，这需要重新审视已确立的专业身份；然而，该领域缺乏相关研究。
研究专业身份及其与人工智能准备领域和跨专业协作组成部分之间的关系。
采用多地点横断面研究设计，于2023年11月14日至2024年2月13日期间，从约旦不同医疗专业招募512名参与者。数据收集使用了《医学人工智能准备量表》和《跨专业学习准备量表》。数据分析包括描述性分析、相关性分析和比较性分析。
专业身份与人工智能准备总分及各分量表得分显著正相关，相关系数ρ范围为0.37至0.47（p <.01）。此外，专业身份与跨专业团队合作与协作（ρ = 0.79，p <.01）以及跨专业协作的角色与责任组成部分（ρ = 0.37，p <.01）显著相关。男性参与者以及有五年或以上工作经验的参与者的专业身份显著更高。
该研究为在人工智能和跨专业协作时代的动态医疗环境中发展医疗劳动力的专业身份奠定了基础作用。该研究突出了医疗管理者和从业者的发展领域，例如基于人工智能跨专业协作的培训，在保持积极专业身份的同时，针对人工智能领域和跨专业协作组成部分。
