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    Exploring Nursing Students' Attitudes and Readiness for Artificial fi cial Intelligence: A Cross-Sectional Study
    (Elsevier Science Inc, 2024) Yalcinkaya, Turgay; Ergin, Eda; Yucel, Sebnem Cinar
    Background: Understanding nursing students' attitudes towards and readiness for artificial intelligence (AI) is crucial for the effective integration of AI into nursing education and practice. AI has the potential to enhance clinical decision-making and personalize patient care. Aim: This study aimed to determine nursing students' attitudes towards and readiness for AI. Methods: This was a cross-sectional descriptive study conducted at a nursing faculty in the west of Turkey and included 291 nursing students. Data were collected using the Individual Information Form, the General Attitudes towards Artificial Intelligence Scale (GAAIS), and the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS). Results: The mean scores for Positive GAAIS, Negative GAAIS, and MAIRS-MS were 3.86 +/- 0.62, 3.23 +/- 0.82, and 76.93 +/- 13.63, respectively. Fourth-year students scored significantly higher on the MAIRS-MS compared to second-year students (F = 3.750, p = 0.011). A positive correlation was found between MAIRS-MS and GAAIS scores (r = 0.330, p < 0.01). Conclusions: The findings are anticipated to guide nursing faculties and academicians in incorporating AI into the curriculum. (c) 2024 Organization for Associate Degree Nursing. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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    Nurses' knowledge of, attitudes towards and awareness of the metaverse, and their future time perspectives: a cross-sectional study
    (BMC, 2024) Ergin, Eda; Yalcinkaya, Turgay; Yucel, Sebnem Cinar
    Background The metaverse is a new and developing technology used in the field of healthcare. The perception of future explains time as a psychological phenomenon rather than a physical one. This study aimed to determine nurses' thoughts of the metaverse and their perceptions of future.Methods The study in which the cross-sectional descriptive design was used was conducted with nurses working in a hospital in Trkiye from September 2022 to December 2022. Face-to-face interviews were conducted with 374 nurses who were chosen using the convenience sampling method. Personal Identification Form, Metaverse Scale (MS) and Future Time Perspective Scale (FTPS) were used to collect data. The Statistical Package for Social Sciences (SPSS) for Windows 25.0 program was used to analyse the data.Results The findings revealed that 81.6% of the nurses believed that they could provide patient education using the metaverse in the future, whereas 46% believed that they could do virtual nursing. The mean scores obtained from the FTPS and MS by the nurses were 3.45 (SD = 0.37) and 3.74 (SD = 0.56), respectively. There was a weak positive relationship between perception of future, and knowledge of, attitudes towards and awareness of the metaverse (r = 0.157, p = 0.002), and a weak, positive relationship between internet use duration and MS (r = 0.169, p = 0.001).Conclusions This study underscores the potential of the metaverse in nursing, revealing that nurses are optimistic about its application in patient education and virtual care. We recommend the development of specialized training programs to equip nurses with the necessary skills and knowledge to effectively utilize the metaverse in healthcare settings.