Date of Award
2027
Degree Type
Restricted to Claremont Colleges Dissertation
Program
School of Community and Global Health
Advisor/Supervisor/Committee Chair
Paula Palmer
Dissertation or Thesis Committee Member
Rachaline Napier
Dissertation or Thesis Committee Member
Jay Orr
Terms of Use & License Information
Rights Information
© 2025 Mulfi Alkhinjar
Keywords
Large Language Models, Shinners Artificial Intelligence Perception, Chat Generative Pretrained Transformer, Job requirements, Health professionals
Subject Categories
Public Health
Abstract
Context: Large Language Models (LLMs) such as ChatGPT, Gemini, and DeepSeek are transforming professional work across sectors by enhancing information processing and decision support. In public health, these technologies offer the potential to improve efficiency, analytical capacity, and data-driven decision-making. Yet, their integration raises concerns about workforce preparedness, evolving skill requirements, and ethical oversight. In Saudi Arabia, where Vision 2030 prioritizes digital transformation in healthcare, understanding how public health professionals adapt to these technologies is vital for workforce and policy planning. Methods: This exploratory mixed-methods study examined the professional impact of LLMs and the preparedness of public health professionals for their integration. The validated Shinners Artificial Intelligence Perception (SHAIP) survey—adapted for LLMs and public health—was distributed to employees of the Saudi Public Health Authority, yielding 32 complete responses. Ten semi-structured interviews further explored four constructs: professional impact, preparedness, new essential skills, and obsolete skills. Quantitative data were analyzed descriptively, and qualitative data were coded using thematic analysis. Findings: Survey results indicated that LLMs positively influence efficiency and workflow but revealed gaps in training and ethical guidance. Interview themes reinforced these findings, identifying new essential skills such as prompt engineering, digital literacy, and critical oversight, while traditional tasks like manual data entry and report drafting were viewed as increasingly automated. Conclusions: LLMs are transforming the roles of public health professionals. Successful adoption requires structured training, institutional readiness, and ethical governance. The study offers actionable recommendations to align workforce development and recruitment strategies with Saudi Vision 2030, emphasizing capacity building and responsible AI integration in public health practice.
ISBN
9798273311121
Recommended Citation
Alkhinjar, Mulfi. (2027). How Large Language Models Are Reshaping Skills and Job Requirements for Public Health Professionals in Saudi Arabia. CGU Theses & Dissertations, 1038. https://scholarship.claremont.edu/cgu_etd/1038.
