Professional identity and its relationships with AI readiness and interprofessional collaboration

W Wafa’a Ta’an S Sadeq Damrah M Mohammed M. Al-Hammouri B Brett Williams

Abstract

Background 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. Objective To examine professional identity and its relationships with AI readiness domains and interprofessional collaboration components. Methods 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. Results 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. Conclusion 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.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 5
Published May 16, 2025
Pages e0322794
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (4)

W

Wafa’a Ta’an

S

Sadeq Damrah

M

Mohammed M. Al-Hammouri

B

Brett Williams