Neonatal Intensive Care Nurses’ Perceptions of Artificial Intelligence Integration in Neonatal Skin Assessment: A Qualitative Phenomenological Study

Abstract

OBJECTIVE: This study explores neonatal intensive care unit (NICU) nurses' perceptions of artificial intelligence (AI)-assisted neonatal skin assessment, focusing on its benefits, challenges, and ethical implications. Optimizing AI integration requires understanding nurses' attitudes. METHODS: A qualitative phenomenological approach was employed. Semi-structured interviews were conducted with 23 NICU nurses from a public hospital in Gaziantep, Turkey, between January and March 2025. Data were analyzed using inductive content analysis to identify emerging themes related to AI's impact on clinical decision-making, workflow efficiency, and professional autonomy. RESULTS: Findings revealed that nurses acknowledged AI's potential to enhance diagnostic accuracy, standardize assessments, and reduce interobserver variability. However, concerns were raised regarding algorithm reliability, professional autonomy, and ethical considerations. Nurses recognized AI's potential but stressed the need for transparency, training, and safeguards against over-reliance. Participants emphasized human oversight to ensure patient-centered care. CONCLUSIONS: Artificial intelligence may improve neonatal skin assessment, but integration must balance technology and ethics. Engaging NICU nurses in AI system development and implementation is essential to fostering trust and ensuring alignment with clinical needs. Future research should assess AI's long-term impact and support interdisciplinary tool development that complements nursing expertise.

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