Artificial Intelligence Applications in Pediatric Nursing: A Scoping Review with Mental Health and Physical Perspectives

Abstract

Background: Artificial intelligence is increasingly being integrated into healthcare to support clinical decision making, patient monitoring, individualized care, education, and healthcare delivery. Pediatric nursing represents an important context for artificial intelligence implementation because children have distinctive developmental, physiological, psychological, and communication needs, while their care frequently involves active family participation. In addition to physical illness, children may experience anxiety, fear, emotional distress, developmental challenges, and psychosocial difficulties related to illness, hospitalization, and treatment. Although research on artificial intelligence in pediatric healthcare is expanding, the evidence remains distributed across diverse clinical, educational, technological, and psychosocial applications. A comprehensive mapping of this evidence is therefore needed to clarify the current role of artificial intelligence in pediatric nursing and its potential contribution to holistic physical and mental health care.

Objective: This scoping review aimed to map the existing literature on applications of artificial intelligence in pediatric nursing, identify the major areas of implementation, summarize reported benefits and challenges, and examine the potential contribution of artificial intelligence to holistic physical and mental health care for children and their families.

Methods: This scoping review was informed by the Joanna Briggs Institute (JBI) methodology for scoping reviews and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses Extension for Scoping Reviews (PRISMA ScR). Evidence from published studies was synthesized using narrative thematic analysis. The extracted information included publication characteristics, study design, artificial intelligence application, healthcare setting, reported outcomes, and key findings.

Results: Studies published between 2022 and 2026 were included. Nine major areas of artificial intelligence application were identified: clinical decision support; pediatric patient monitoring; pediatric oncology nursing; nursing education; digital psychosocial interventions; generative artificial intelligence; nursing informatics and healthcare transformation; ethical and legal considerations; and pediatric nurses' perceptions and readiness for artificial intelligence implementation. Overall, the literature suggests that artificial intelligence may support clinical decision making, patient safety, individualized care, education, communication, psychosocial support, and healthcare efficiency. However, important challenges remain, including data privacy, algorithmic bias, transparency, accountability, workforce preparedness, digital competency, infrastructure limitations, and the need for rigorous evaluation across diverse pediatric populations.

Conclusion: Artificial intelligence has the potential to support pediatric nursing by strengthening clinical decision making, monitoring, education, individualized care, and selected psychosocial interventions. Its contribution should be considered within a holistic framework that recognizes the interrelationship between children's physical and mental health. Artificial intelligence should complement, rather than replace, pediatric nurses' professional judgment, therapeutic communication, and child and family centered care. Further research is needed to establish clinical effectiveness, safety, ethical governance, and the long-term impact of artificial intelligence on holistic pediatric health outcomes.