Artificial Intelligence and AI-Adjacent Digital Technologies in Nursing Practice Within Gastroenterology: A Scoping Review of Current Applications, Challenges, and Future Directions.
4 affiliations
- 1Department of Gastroenterology, São João Hospital, 4200-319 Porto, Portugal.
- 2Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, 4099-002 Porto, Portugal.
- 3Faculty of Logistics, Molde University College, NO-6410 Molde, Norway.
- 4Center for Research of Technologies and Architecture, Information Sciences, Technologies and Architecture Research Centre (ISTAR), Instituto Universitario de Lisboa ISCTE-IUL, 1649-026 Lisbon, Portugal.
Abstract
Background/Objectives: Artificial intelligence (AI) is increasingly integrated into clinical gastroenterology, with emerging applications in nursing contexts. However, the extent and nature of these applications in gastroenterology nursing remain under-explored. This scoping review aimed to map the current landscape of AI and closely related AI-adjacent digital technologies in gastroenterology nursing. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline, PubMed, Medline, Web of Science, and Scopus were searched for peer-reviewed, English-language studies published since 2000, and the findings were synthesized narratively. Results: Of 184 records identified, 11 studies were included, highlighting the potential of these technologies in clinical decision support, workflow optimization, patient education, and endoscopy assistance. Reported benefits include gains in workflow efficiency, technical accuracy, and reduced administrative workload; direct evidence of improved nursing-led patient outcomes was reported in only a minority of studies. Challenges encompass limited nurse-led research, insufficient external validation, implementation gaps, and ethical concerns. Conclusions: Greater nurse involvement in AI development is essential to drive paradigm shifts in clinical practice. This review synthesizes evidence to inform future applications, research, and policy in AI-enhanced gastroenterology nursing.
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BibTeX
@article{barros2026artificial,
title = {{Artificial Intelligence and AI-Adjacent Digital Technologies in Nursing Practice Within Gastroenterology: A Scoping Review of Current Applications, Challenges, and Future Directions.}},
author = {Sonia Barros and Ana Carvalho and Guilherme Macedo and Joao C Ferreira and Miguel Mascarenhas},
journal = {Nursing reports (Pavia, Italy)},
year = {2026},
month = oct,
doi = {10.3390/nursrep16100357},
url = {https://europepmc.org/article/MED/42931330},
note = {CC BY},
}
RIS
TY - JOUR
TI - Artificial Intelligence and AI-Adjacent Digital Technologies in Nursing Practice Within Gastroenterology: A Scoping Review of Current Applications, Challenges, and Future Directions.
AU - Sonia Barros
AU - Ana Carvalho
AU - Guilherme Macedo
AU - Joao C Ferreira
AU - Miguel Mascarenhas
PY - 2026
DA - 2026/10/10
JO - Nursing reports (Pavia, Italy)
DO - 10.3390/nursrep16100357
UR - https://europepmc.org/article/MED/42931330
AB - Background/Objectives: Artificial intelligence (AI) is increasingly integrated into clinical gastroenterology, with emerging applications in nursing contexts. However, the extent and nature of these applications in gastroenterology nursing remain under-explored. This scoping review aimed to map the current landscape of AI and closely related AI-adjacent digital technologies in gastroenterology nursing. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline, PubMed, Medline, Web of Science, and Scopus were searched for peer-reviewed, English-language studies published since 2000, and the findings were synthesized narratively. Results: Of 184 records identified, 11 studies were included, highlighting the potential of these technologies in clinical decision support, workflow optimization, patient education, and endoscopy assistance. Reported benefits include gains in workflow efficiency, technical accuracy, and reduced administrative workload; direct evidence of improved nursing-led patient outcomes was reported in only a minority of studies. Challenges encompass limited nurse-led research, insufficient external validation, implementation gaps, and ethical concerns. Conclusions: Greater nurse involvement in AI development is essential to drive paradigm shifts in clinical practice. This review synthesizes evidence to inform future applications, research, and policy in AI-enhanced gastroenterology nursing.
SN - 2039-439X
SN - 2039-4403
ER -