WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/6

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Department: search.filters.department.Fenerbahçe UniversitySubject: search.filters.subject.Attitude

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  • Article
    The Relationship Between Nurses Anxiety and Attitudes Towards Artificial Intelligence and Examination of Influencing Factors
    (BMC, 2026) Nirgiz, Cansu; Sari, Merve Kiymac; Cayli, Nazan
    Aim to explore the relationships between nurses'anxiety and attitudes toward artificial intelligence (AI) and the factors associated with them. Background Although AI technologies are increasingly integrated into healthcare, research exploring nurses ' psychological readiness and emotional responses to AI remains limited. Existing studies have primarily focused on nursing students or general healthcare professionals, leaving a gap in understanding how practicing nurses perceive and emotionally adapt to AI within real clinical environments-particularly in T & uuml;rkiye, where digital transformation in healthcare is accelerating. Addressing this gap is essential, as nurses play a pivotal role in ensuring the safe and ethical implementation of AI-driven tools in patient care. Methods This descriptive and correlational study included 562 nurses from 14 branches of a private hospital chain across seven Turkish cities between November 2024 and January 2025.This sample was selected because it represents nurses actively engaged in clinical decision-making within healthcare systems that are rapidly adopting AI technologies. According to a power analysis performed in G*Power (rho = 0.25, alpha = 0.05, power = 0.95), the required sample size was 202 participants. Data were collected through an online questionnaire comprising a Descriptive Information Form, the AI Anxiety Scale, and the General Attitudes toward AI Scale. Descriptive statistics, independent samples t-tests, ANOVA (F), Tukey post hoc test, Pearson correlation, and multiple regression analyses were conducted. Ethical approval was obtained from the Fenerbah & ccedil;e University Ethics Committee, and informed consent was obtained digitally. Results Nurses reported moderate anxiety levels and generally positive attitudes toward AI. Male nurses showed an association with lower anxiety levels and higher positive attitude scores than female nurses. Single individuals and those with higher levels of education showed higher positive attitudes toward AI. Those with 0-3 years of experience in the profession were associated with lower anxiety and higher positive attitude scores. Nurses who used AI in practice, were knowledgeable about its use, or perceived it as reliable showed a relationship with lower anxiety and more positive attitudes. Regression analysis showed that each one-unit increase in the learning and AI configuration subscales of the AI Anxiety Scale was associated with a 0.740-and 0.716-point lower score in the total attitude score, respectively. Conclusion The findings suggest that lower levels of anxiety related to learning and AI configuration are associated with more positive attitudes toward AI. Addressing these specific anxiety domains may be related to the successful integration of AI technologies into clinical practice and could be linked to the digital transformation in healthcare.
  • Article
    Investigating the Personal and Professional Variables That Predict Discrimination Attitudes Among Nurses and Physicians
    (Wiley, 2025) Tekin, Suat; Seren, Arzu Kader Harmanci; Harmanci Seren, Arzu Kader
    Introduction: Healthcare professionals are expected to provide holistic care to their patients without discrimination based on factors such as religion, language, age, gender, and race. Design: It is a cross-sectional descriptive study. Aim: The study aimed to examine the discriminatory attitudes of nurses and physicians working in hospitals in Sanliurfa and to define whether the personal and professional variables predict discriminatory attitudes among them. Methods: The STROBE reporting method, which is one of the EQUATOR guidelines, was followed. Data were collected from a total of 376 physicians and nurses through online platforms between March and June 2020 via the information form and the Discrimination Attitude Scale. Results: The discriminatory attitudes of the nurses and physicians participating in the study were above average. The total discriminatory attitudes scores of the participants varied according to sex, income levels, profession, hospital experience, and unit (p < 0.05). In addition, sex, profession and unit variables predicted the total discriminatory attitudes of nurses and physicians (p < 0.05). Conclusion: Although nurses' and physicians' discriminatory attitudes scores were generally higher, the highest mean score was in the subscale "discrimination against other nationalities." Sex, profession, and unit variables predicted the total discriminatory attitudes of nurses and physicians. Further quantitative and qualitative research is needed to understand the reasons for the highest discriminatory attitudes towards other nationalities among healthcare professionals, to overcome this issue. Clinical Relevance: Nursing or healthcare managers, as well as policymakers, may consider the predictive variables when staffing and training nurses and physicians working in similar regions and conditions.