Generative artificial intelligence in nursing care research: Applications across the research process

Generative artificial intelligence has undergone rapid development in recent years, and its integration into health research is transforming the ways in which scientific studies are designed, conducted, and disseminated. Within the context of nursing research, these technologies offer new opportunities to support and enhance research activity. However, their use also raises important challenges related to the reliability of generated information, the presence of bias, transparency in processes, and adherence to the ethical and regulatory principles governing nursing research. Accordingly, the objectives of this article are to analyse the role of generative artificial intelligence as an enabling tool in nursing research, to describe its main applications and limitations across the different phases of the research process, and to present the regulatory framework, editorial policies, and ethical implications associated with its responsible use. Furthermore, a ten-point plan is proposed for its responsible and effective integration into research in care. To this end, recent evidence and examples of use in care research were integrated, with a focus on applicability to research practice. It is concluded that generative artificial intelligence may represent a valuable resource for nursing research when used in a critical and context-aware manner, as a support to research reasoning rather than a substitute for professional judgement. Its integration requires human oversight, systematic verification of generated outputs, and alignment with current ethical, regulatory, and editorial frameworks to preserve scientific quality, transparency, and the integrity of the research process in nursing.