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Operating room nurses, who have an important place in the professional healthcare team, should be able to use technology effectively and adapt to innovations. This study is expected to shed light on how effective the development of robotic technologies and artificial intelligence and their integration into operating room nursing will be in fulfilling the requirements of contemporary nursing philosophy. This study was designed as a single group pre- and post-test quasi-experimental study. The quasi-experimental (pretest-posttest) research design was utilized to conduct the study in a Training and Research Hospital in Western Turkey. The nurses (n = 35) working in the operating room of the aforementioned hospital were included in the study. In this study, we aimed to determine whether operating room nurses experienced anxiety due to the use of artificial intelligence and robotic nurses, and the effectiveness of the training given to them in order to raise their awareness. The following three tools were used for data collection: The Nurses' Descriptive Characteristics Form, Artificial Intelligence Knowledge Questionnaire, and Artificial Intelligence Anxiety Scale. Data extraction and analysis were performed in a narrative and tabular way. According to this study, the training given to the operating room nurses significantly increased their knowledge levels about artificial intelligence and robotic nurses, and increased their artificial intelligence- and robotic nurse-related anxiety significantly (p < 0.05). The participating operating room nurses experienced limitations regarding current information, training programs and learning opportunities on robotic surgery. We recommend that the operating room nurses should be provided with trainings on artificial intelligence technologies and robotic nurses, and that they should be enabled to use these information technologies regarding future technologies actively.
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http://dx.doi.org/10.1007/s11701-023-01592-0 | DOI Listing |
JMIR Hum Factors
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York City, NY, United States.
Background: As information and communication technologies and artificial intelligence (AI) become deeply integrated into daily life, the focus on users' digital well-being has grown across academic and industrial fields. However, fragmented perspectives and approaches to digital well-being in AI-powered systems hinder a holistic understanding, leaving researchers and practitioners struggling to design truly human-centered AI systems.
Objective: This paper aims to address the fragmentation by synthesizing diverse perspectives and approaches to digital well-being through a systematic literature review.
J Med Microbiol
September 2025
Alberta Precision Laboratories Public Health Lab, Edmonton, Alberta, Canada.
For thousands of years, parasitic infections have represented a constant challenge to human health. Despite constant progress in science and medicine, the challenge has remained mostly unchanged over the years, partly due to the vast complexity of the host-parasite-environment relationships. Over the last century, our approaches to these challenges have evolved through considerable advances in science and technology, offering new and better solutions.
View Article and Find Full Text PDFInt J Surg
September 2025
Department of Oral and Maxillofacial Surgery, The Affiliated Tai'an City Central Hospital of Qingdao University, Taian, China.
J Robot Surg
September 2025
Department of CSE, United Institute of Technology, Coimbatore, India.
Diabetologia
September 2025
Department of Diabetology and Internal Medicine, Medical University of Warsaw, Warsaw, Poland.
This review article, developed by the EASD Global Council, addresses the growing global challenges in diabetes research and care, highlighting the rising prevalence of diabetes, the increasing complexity of its management and the need for a coordinated international response. With regard to research, disparities in funding and infrastructure between high-income countries and low- and middle-income countries (LMICs) are discussed. The under-representation of LMIC populations in clinical trials, challenges in conducting large-scale research projects, and the ethical and legal complexities of artificial intelligence integration are also considered as specific issues.
View Article and Find Full Text PDF