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Doctoral Education in Nursing in Ibero‐America: An Analysis of Its Evolution and Perspectives for the Future

ABSTRACT

Aim

To provide an overview of doctoral programs in nursing offered in Ibero-American countries to inform regional collaboration and academic development.

Design

This study was a descriptive, document analysis.

Methods

A systematic mapping was conducted using data obtained from official university and program websites, national postgraduate databases, and academic documents. The variables analysed included country, institution, year of implementation, number of faculty and students, course duration, delivery modality, costs, scholarship availability, internationalisation activities, and research lines.

Results

A total of 94 active nursing doctoral programs were identified. Brazil emerged as the pioneer, launching the first doctoral program in 1982, and remains the regional leader, accounting for 43 programs. Most programs are offered by public institutions (76.6%), delivered primarily in face-to-face format (64.1%), and emphasise research (90.4%). There has been a consistent upward trend in the establishment of programs since 2000, with notable expansion between 2011 and 2025. Despite this progress, regional disparities persist, along with a lack of data standardisation and a limited presence of professional doctorates. While 69.1% of programs reported international activities, few offer joint or dual degrees. The most common thematic axis, “Health Care and Nursing,” proved to be broad and non-specific.

Conclusion

The study reveals the expanding landscape of nursing doctoral education in Ibero-America, while also exposing persistent challenges regarding access, curricular clarity and regional articulation.

Implications for the Profession and/or Patient Care

Doctoral programs are essential for developing research capacity, academic leadership and evidence-based care. Strengthening these programs could enhance nursing responses to local health needs and promote scientific progress in care delivery.

Impact

This study provides the first comprehensive mapping of nursing doctoral programs in Ibero-America, highlighting regional disparities and areas for academic collaboration, with potential impact on policy-making, curriculum development, and the strengthening of research capacity in nursing education.

Reporting Method

STROBE (Strengthening the Reporting of Observational Studies in Epidemiology).

Patient or Public Involvement

No patient or public contribution.

The Effect of Artificial Intelligence in Promoting Positive Nursing Practice Environments: Mixed Methods Systematic Review

ABSTRACT

Aim

To synthesise the available evidence on the effect of artificial intelligence in promoting positive nursing practice environments, exploring outcomes for professionals, clients, and institutions.

Background

Artificial intelligence has undergone significant advancements and shows great potential to transform nursing practice. However, this technological evolution is not without challenges, which must be identified and addressed.

Methods

A systematic mixed-methods review following the PRISMA 2020 guidelines and the methodology proposed by JBI. The search strategy was conducted in PubMed, CINAHL, Scopus, and Web of Science, including grey literature. Quantitative, qualitative, and mixed-methods studies were included, and the selection process involved screening by two independent reviewers, who assessed all studies, their methodological quality and extracted their data.

Results

From the conducted search, 11 studies were included, addressing how artificial intelligence has transformed nursing practice by optimising decision-making, task execution, and patient safety. Artificial intelligence, through predictive models and assistants such as ChatGPT, can enhance nursing management. However, challenges such as privacy concerns, resistance to change, and the need for professional training must be addressed to maximise its effectiveness.

Conclusion

Artificial intelligence has the potential to positively transform the nursing practice environment, optimising decision-making, enhancing patient safety, and improving operational efficiency, with clear benefits for professionals, patients, and healthcare institutions.

Relevance to Clinical Practice

This study analysed the impact of artificial intelligence on nursing, highlighting improvements in clinical decision-making, patient safety, and institutional efficiency. Despite the identified benefits, the implementation of artificial intelligence in nursing is not without challenges and risks, which must be identified and addressed to ensure safe and effective adoption.

Reporting Method

The review followed the PRISMA 2020 checklist.

Patient or Public Contribution

No.

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