{"title":"Evaluation of nurses' perspectives on the design and use of assistant nurse robots in obstetrics and neonatal care: a mixed-method study.","authors":"Özen İnam, Samet Okay","doi":"10.1186/s12912-025-03025-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This 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.</p><p><strong>Methods: </strong>The 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.</p><p><strong>Results: </strong>Quantitative 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).</p><p><strong>Conclusions: </strong>The 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.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":48580,"journal":{"name":"BMC Nursing","volume":"24 1","pages":"359"},"PeriodicalIF":3.1000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11963551/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12912-025-03025-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
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Abstract
Background: This 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.
Methods: The 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.
Results: Quantitative 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).
Conclusions: The 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.
期刊介绍：
BMC Nursing is an open access, peer-reviewed journal that considers articles on all aspects of nursing research, training, education and practice.
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