Exploring the application of generative artificial intelligence in nursing: a cross-sectional study

Area of Science:

• Nursing Informatics
• Artificial Intelligence in Healthcare
• Digital Health

Background:

• Generative Artificial Intelligence (GAI) presents novel opportunities for healthcare innovation.
• Understanding the adoption and impact of GAI in clinical practice is crucial for its effective implementation.
• Nursing, as a cornerstone of patient care, stands to benefit significantly from AI-driven advancements.

Purpose of the Study:

• To systematically investigate Generative Artificial Intelligence (GAI) application in Chinese nursing practice.
• To map current usage patterns, identify benefits, challenges, and functional needs of nursing staff regarding GAI.
• To assess the real-world performance and adoption of emerging local GAI platforms in China.

Main Methods:

• A convenience sampling method was employed, surveying 181 nurse interns, staff nurses, and managers across 20 provinces.
• A questionnaire was developed through literature review and evidence extraction, with content validity assessed by experts.
• Data were collected between April and June 2025.

Main Results:

• GAI adoption rate among nurses reached 92.81%, with no significant association with demographic factors.
• Seniority was a significant predictor of GAI usage frequency (p=0.001).
• Local platforms (DeepSeek, Doubao) dominated usage (>60%), with health education material generation being the most prevalent application (61.30%). GAI reduced administrative workload for managers, enhanced efficiency for clinical nurses, and fostered innovation among interns.
• Primary challenges included concerns about content accuracy (40.96%) and impact on clinical autonomy.

Conclusions:

• GAI adoption in Chinese nursing is widespread and influenced by a preference for local platforms and role-specific benefits.
• Concerns regarding content accuracy and clinical autonomy are primary barriers to GAI integration.
• Clinically validated, trustworthy GAI systems, coupled with targeted training and ethical design, are essential for realizing GAI's potential as a collaborative nursing tool.