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

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Generative Artificial Intelligence (GAI) is widely adopted by Chinese nurses, with a preference for local platforms. Key challenges include ensuring content accuracy and maintaining clinical autonomy for effective GAI integration in nursing.

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cross-sectional surveycurrent state of applicationgenerative artificial intelligencenursing fieldnursing staff

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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.