ArticleBMC nursing2025
Evaluation of nurses' perspectives on the design and use of assistant nurse robots in obstetrics and neonatal care: a mixed-method study.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reimagining nursing practice in the era of AI: a qualitative systematic review and meta-synthesis of nurses' lived experiences.Journal of health, population, and nutrition · 2026Pooled it
- A concept analysis of artificial intelligence anxiety among nurses based on Walker and Avant's method.BMC nursing · 2026Article
- Robotic surgical nurses' perceptions of artificial intelligence: a qualitative study.Journal of robotic surgery · 2025Article
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aims to evaluate nurses' perspectives on the design of nurse assistant robots that can be utilized in obstetrics and neonatal units. The research examines the potential of these robots in enhancing the quality of patient care, reducing workload, and standardizing care processes from the nurses' perspective.
methodsThe study was conducted with 52 nurses working in obstetrics and neonatal units of hospitals. Conjoint analysis was used to evaluate preferences for the features of nurse assistant robots while qualitative data were obtained through semi-structured questions. The Artificial Intelligence Anxiety Scale was used to measure nurses' concerns.
resultsQuantitative analysis results indicate that nurses prioritize features such as sterilization, data transfer, alarm systems, precision, and autonomous navigation in nurse assistant robots. Qualitative analysis findings reveal positive perceptions regarding the robots' potential to reduce error rates, enhance patient safety, and alleviate workload. However, concerns about technological dependency, sterilization issues, and potential job displacement were also expressed. Furthermore, technological/systematic issues and lack of communication/empathy were identified as disadvantages of nurse assistant robots. Considering the sensitive nature of obstetrics and neonatal units, it was suggested that these robots should primarily focus on vital sign monitoring and material preparation tasks. The findings from the Artificial Intelligence Anxiety Scale indicate that participants exhibit moderate-to-high levels of general anxiety (87.6). Specifically, the Socio-Technical Blindness and Job Transition subscales scored higher compared to other dimensions (r = -0.35, p < 0.01).
conclusionsThe findings emphasize that features such as sterilization, data transfer, safety sensors, and user-friendly guidance systems should be prioritized in the design of nurse assistant robots. Moreover, experience and training were found to positively influence technological adaptation. The results provide valuable insights into the design and integration of nurse assistant robots into healthcare services. This study offers both theoretical and practical guidance for the development of nurse assistant robots. CLINICAL TRIAL NUMBER: Not applicable.
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