Fisabio and the UJI propose ten guidelines for integrating generative artificial intelligence into nursing research

Researchers from the Fisabio Foundation and Universitat Jaume I have published a study in the journal Enfermería Clínica outlining ten guidelines for the responsible integration of generative artificial intelligence (GenAI) into nursing research. The study examines how GenAI can support various research stages, including literature reviews and data analysis, while highlighting the necessity of human oversight to prevent errors. This framework is vital for the AI sector as it provides a structured approach to maintaining scientific integrity and ethical standards within specialized healthcare research.

The research was developed by members of the Nursing Research Group at Universitat Jaume I and the eNURSYS group at Fisabio within the NURSIA Joint Research Unit, focusing on technology-applied care and information systems. Authors including M.J. Valero-Chillerón and V.M. González-Chordá report that while GenAI offers significant opportunities to improve research efficiency, it also introduces "hallucinations"—the production of non-existent references or inaccurate interpretations. Consequently, the study mandates that all AI-generated information must be verified before being incorporated into scientific work to ensure the reliability of the research process.

A significant portion of the study addresses the unique challenges AI poses to nursing, a field that relies heavily on qualitative methodologies and contextualized patient experiences. The researchers warn that AI models may oversimplify complex therapeutic relationships or overlook social determinants of health by prioritizing mainstream biomedical data and English-language literature. This bias risks marginalizing perspectives specific to the nursing discipline or diverse cultural contexts, making it essential for researchers to subject AI outputs to rigorous critical analysis rather than accepting them automatically.

The proposed ten guidelines serve as a practical framework for researchers, emphasizing that AI should only be used when it provides added value to human work and that its use must be transparently documented. The recommendations also stress the importance of avoiding the introduction of sensitive data and adhering to international regulations, including the new European Artificial Intelligence Act. By focusing on the ability of researchers to use these technologies without compromising methodological rigor, the study aims to guide the AI sector toward more ethical and accountable integration in the health sciences.