Ethical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era

Ethical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Ethical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era Heryyanoor, Margono, Setiyo Adi Nugroho, Moses Glorino Rumambo Pandin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8092188/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The integration of artificial intelligence (AI) into healthcare has fundamentally transformed nursing practice. While increasing efficiency and accuracy, these changes also pose ethical challenges and a humanistic crisis. Objective This literature review aims to examine the challenges and opportunities for implementing ethical leadership to maintain humanistic care in the AI era, analyze philosophical reflections on the moral crisis arising from digitalization, and formulate a conceptual framework that responsibly integrates ethics, humanism, and technology. Methods The review was conducted according to PRISMA guidelines, using a literature search across Scopus, PubMed, Web of Science, and EBSCO with relevant keywords. A total of eight articles published between 2020 and 2025 met the inclusion criteria and were analyzed narratively. Results Moral sensitivity, ethical competence, and a favorable ethical climate improve ethical behavior and quality of care. Transformational and humanistic leadership enhance moral reflection and organizational justice, while a hostile ethical climate increases moral distress. The philosophical perspectives of deontology, virtue ethics, and social justice provide a reflective foundation for maintaining moral autonomy in the AI ​​era. Conclusion Ethical leadership bridges technology and humanity, ensuring digital innovation upholds human dignity through moral foundations, reflective leadership, and responsible AI integration. Nursing Ethical Leadership Nursing Ethics Patient-Centered Care Artificial Intelligence Humanism Figures Figure 1 INTRODUCTION The use of artificial intelligence (AI) in healthcare systems has brought about fundamental changes in nursing practice (Rony, Parvin and Ferdousi, 2024 ). AI offers significant opportunities to improve efficiency, clinical accuracy, and data-driven decision-making (Giordano et al., 2021 ; Salam and Abhinesh, 2024 ). However, the benefits of AI also present significant ethical and philosophical challenges in the healthcare sector, including nursing. Therefore, the role of leaders, particularly ethical leadership, is crucial for navigating the rapidly changing technological landscape while maintaining the humanistic values ​​at the core of the nursing profession (Ricci, 2024 ; Sullivan, Hall and Morrison, 2024 ). Key emerging issues and challenges include data privacy and security, accountability for algorithm-based decisions, and the risk of losing the human touch in the nurse-patient relationship (Lameesa et al., 2024 ; Pepito et al., 2025 ). Nursing leaders are now required not only to understand technology but also to maintain moral values, empathy, and human dignity in an increasingly digitalized system (Arcadi, 2025 ). The use of AI in global healthcare is skyrocketing Zuhair et al., ( 2024 ). AI is now applied in nursing documentation, work scheduling, real-time patient monitoring, and even early detection of changes in clinical conditions (Alfuraydi and Al-Moteri, 2025 ; Wei et al., 2025 ). However, this progress has not been matched by the ethical and cognitive readiness of nursing staff. The results of the study Namdar Areshtanab et al., ( 2025 ) in Iran showed that most nurses (41.1%) had low knowledge, (65.8%) had good attitudes, (74.6%) had moderate levels of acceptance, and (55.8%) implemented AI at a high level. This situation reflects a gap between technological innovation and ethical preparedness, thereby increasing the risk of moral disorientation in AI-based decision-making. In this regard, ethical leadership plays a crucial role in fostering transparency in the use of algorithms, ensuring accountability, and maintaining human oversight as the center of control and moral responsibility in AI-based systems (Park et al., 2022 ; Cheong, 2024 ; Hosseini Tabaghdehi and Ayaz, 2025 ). The integration of AI into nursing practice carries profound philosophical implications. The automation of clinical processes and algorithm-based decisions has the potential to shift nurses' space for moral reflection and empathy toward patients. This phenomenon is known as the displacement of moral agency, where humans gradually lose their role as autonomous moral subjects and become merely part of a data-driven system (Lee, 2021 ; Zhang and Wang, 2025 ). Within the context of Heideggerian existentialist philosophy, this phenomenon illustrates a humanistic crisis in which humans risk becoming objects of their own creation (Ugwu and Ozoemena, 2023 ; Zhang, 2025 ). This shift can be interpreted as moving from care ethics, which emphasizes empathy and interpersonal relationships, to technological determinism, in which moral decisions are reduced to the outcomes of algorithmic logic (Villegas-Galaviz and Martin, 2024 ). This condition results in a decline in the meaning of patient-centered care, and human dignity is potentially neglected in professional nursing relationships. Efforts that can be made include developing and implementing ethical leadership in nursing to make it a moral force guiding the integration of AI with human values (Ronquillo et al., 2021 ). Nursing leaders function not only as administrative decision-makers but also as moral agents who ensure that technological innovation does not erode empathy and compassion, the essence of the profession (Arcadi, 2025 ). In this context, virtue ethics is relevant, as it emphasizes the development of moral character traits such as wisdom (phronesis), empathy, and compassion in nursing leadership (Nurmeksela et al, 2020 ). Deontological and consequentialist ethical approaches are also important for assessing nurses' ethical actions, both in terms of moral obligations and the consequences for patients and the organization (Ateeq, 2024 ). The ethical leadership approach in nursing encompasses not only individual moral dimensions but also profound structural and social dimensions. Based on John Rawls's theory of justice, the principle of social justice should be reflected in the equal distribution of responsibilities, welfare, and opportunities for healthcare workers to develop their ethical competencies. Therefore, developing a fair, reflective, and value-oriented work system is a concrete manifestation of social justice in nursing practice (Park et al., 2022 ; Kim, Kim and Oh, 2023 ). Nursing leaders play a central role in fostering a conducive ethical climate by creating space for moral reflection, strengthening nursing staff's psychological well-being, and preventing systemic pressures that can lead to dehumanization in clinical practice. Based on the description, this literature review aims to examine ethical leadership in nursing and patient-centered care by explicitly examining the challenges and opportunities for implementing ethical leadership in maintaining humanistic care in the era of artificial intelligence (AI) and health digitalization, analyzing philosophical reflections on the humanistic crisis that arises due to the shift in values ​​and moral autonomy in modern nursing practice, and formulating a conceptual framework for ethical leadership that can integrate patient-centered care, moral principles, and the responsible application of AI technology. By incorporating the perspectives of ethics, philosophy, and nursing leadership, this review is expected to provide a solid conceptual foundation for the development of nursing practice that is not only adaptive to technological advances but also remains rooted in the values ​​of humanity, justice, and human dignity as the core of health services in the digital era. METHODS Study Design The literature selection stages followed the PRISMA guidelines (Page et al., 2021 ), and the literature search used Scopus, Web of Science (WoS), PubMed, and EBSCO databases, with a time limit of 2020 to 2025. Inclusion and Exclusion Criteria Ethical leadership in nursing should be patient-centered, but technological developments, including AI, in healthcare are creating a humanistic crisis. This systematic review included studies involving nurses, nursing students, or nursing leaders in healthcare settings; studies addressing ethical leadership, moral sensitivity, professional ethics, patient-centered care, or the integration of AI digitalization into nursing practice; studies assessing or discussing the quality of patient care, ethical climate, nursing staff well-being, perceptions of AI, or humanistic values ​​in nursing practice; empirical studies (quantitative, qualitative, or mixed methods); conceptual/philosophical; English-language articles; and a focus on clinical nursing services, nursing education, or nursing management. Exclusion criteria included studies conducted on healthcare professionals other than nurses, studies that did not address ethical or leadership aspects, non-peer-reviewed articles, duplicate articles, articles lacking full text, and articles irrelevant to AI or patient-centered care settings. Searching Strategy Literature search using Scopus, Web of Science, PubMed, and Ebsco databases with a limitation of 2020 to 2025. The keywords used are (Nurses AND "Ethical leadership" AND "Patient-centered care" OR "AI in healthcare"). Figure 1 shows the identification, screening, and inclusion procedures for studies available in Scopus, Web of Science (WoS), PubMed, and EBSCO databases. Three independent researchers conducted the entire process based on the title and abstract, followed by a full-text review. If there was any uncertainty or doubt regarding the selected articles, a fourth researcher was contacted for consultation to resolve the issue. Full-text studies were obtained from electronic databases or the Airlangga University library in Surabaya. Procedure of Data Extraction Three independent researchers conducted data extraction. However, if there were any differences of opinion, a fourth researcher was consulted to provide insight and resolve any issues. All necessary information was obtained from the full text of the studies. RESULT Table 1 shows the results of research articles on Ethical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era. Table 1 Research articles on Ethical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era No Title, Author, Years Method Result 1. Digitization in Everyday Nursing Care: A Vignette Study in German Hospitals (Korte and Bohnet-Joschko, 2022 ) The research was a vignette study that evaluated a fictional situation involving the introduction of digital technology in a hospital. The sample consisted of 299 nurses. Variables included motivation towards technology use, attitudes towards innovation, and perceptions of the benefits and barriers of digital technology in care. The instrument used a Likert-scale questionnaire and open-ended questions. Data analysis used the Friedman test to compare variations in motivation between vignettes and the Wilcoxon test for paired comparisons. Other analyses included regression and correlation to evaluate the relationship between independent variables and motivation for technology use. Respondents indicated greater motivation to use tablets than to use smart glasses as innovative technologies. No significant differences were found between intrinsic and extrinsic motivation. Messages from nurse leaders emphasizing efficiency increased nurses' motivation to use digital technology more than messages focused on patient orientation. In general, nurses' attitudes toward digital technology use are high, and management support and training can strengthen their involvement in adopting new technologies. 2. How do ethically competent nurses behave in clinical nursing practice? A qualitative study (Choe, Kwon and Kim, 2022 ) Research: A qualitative study with a phenomenological approach to understand the ethical behavior of nurses in clinical practice. A total of 20 participants were nurses working in various hospital departments in South Korea, with at least several months of experience, and were willing to participate. Sampling used a snowball sampling technique, where initial participants invited their colleagues who met the criteria to join. Research variables were factors and behaviors that indicate nurses' ethical competence in clinical practice, including caring attitudes, professional responsibility, and other ethical behaviors. Data were collected through semi-structured online interviews via a video platform. Questions were directed to discuss experiences, assessments, and observations of ethical behavior in clinical practice. Data analysis used a thematic analysis grounded in a phenomenological approach. The analysis process included repeated reading of transcripts, coding, grouping codes into categories, and developing main themes that represent nurses' ethical behavior. Research shows that nurses' ethical competence is based on their ability to serve patients with sincerity, professionalism, and compassion. Factors supporting ethical behavior include good working conditions, a supportive administrative system, effective communication among nurses, and a wealth of personal experience. Nurses who show sensitivity to patient needs, effective communication, and professional responsibility tend to exhibit high ethical behavior. A supportive work environment and positive experiences contribute to the strengthening of ethical practices in clinical practice. 3. Moral sensitivity and person-centred care among mental health nurses in South Korea: A cross-sectional study (Jang, Kim and Lee, 2022 ) The study used a cross-sectional study of 220 mental health nurses in South Korea. The sample was selected according to criteria set by mental health nurses who had been actively working for at least 6 months and had provided written consent. The study variables were moral sensitivity, person-centered care, general characteristics (age, marital status, education level, work experience, job position), and educational history in bioethics and biomedical ethics. The research instrument was the Korean version of the Moral Sensitivity Questionnaire (MSQ), a 7-point Likert scale comprising 27 items that measure aspects such as patient orientation, professional responsibility, moral conflict, moral meaning, and virtue. The Korean version of the Person-Centered Practice Inventory - Staff (PCPI-S), a 5-point Likert scale, measured the level of patient-centered care practices. Data analysis used Pearson correlation tests to assess relationships among primary variables, t-tests to assess differences based on general characteristics, and analysis of variance to compare differences across general characteristics. Multiple regression analysis was used to identify predictors of patient-centered care practices, testing for multicollinearity and residual independence. Moral sensitivity was the strongest predictor of improved patient-centered care practices. Bioethics education, history, and marital status also significantly influenced these practices. The regression model showed that moral sensitivity accounted for approximately 28% of the variation in patient-centered care practices, highlighting the importance of moral factors in improving care quality. 4. When breaking the rule becomes necessary: The impact of leader– member exchange quality on nurses pro- social rule- breaking (Irshad et al., 2022 ) This quantitative study involved 224 nurses working in a hospital, selected via convenience sampling. The research variables were Leader–Member Exchange (LMX), Organizational Identification, and Pro-social Rule-breaking (PSRB). All variables were measured using a questionnaire using a five-point Likert scale, with validated and reliable instruments. The data were then analyzed using structural equation modeling (SEM) to test direct and mediating relationships among variables. The analysis also included instrument reliability and validity tests, as well as statistical model testing. A positive relationship was found between the quality of leader-member exchange (LMX) relationships and nurses' levels of organizational identification. Nurses with good relationships with their superiors tended to demonstrate high levels of organizational identification. High levels of organizational identification increased nurses' tendency to engage in pro-social rule-breaking, a form of constructive deviance. These findings confirm that positive relationships with superiors and a sense of organizational identification can foster positive pro-social behavior in the nursing context. 5. Attitudes Towards AI in Healthcare Among University of Hail Health Sciences Students: A Qualitative Exploration (Alhur et al., 2025 ) The research is a qualitative case study with a sample of 18 health students, including nursing students. The research variables are students' understanding of AI in the health sector, students' attitudes towards AI integration in clinics, perceived benefits and challenges of AI, ethical considerations related to AI, and educational needs and training on AI. The research instrument is a semi-structured interview guide covering five main areas: understanding AI, attitudes towards AI integration, perceived benefits, concerns and challenges, and educational needs about AI. Data analysis uses a six-stage thematic analysis framework by Braun and Clarke, namely: data familiarization, initial coding, theme search, theme review, theme definition and naming, and reporting results. The analysis approach is combined inductively and deductively: initially through open coding, then highlighted and organized in line with the literature and study objectives. Students generally recognized AI's potential to improve efficiency and accuracy in healthcare and expressed positive attitudes toward its benefits. However, they also expressed concerns about data privacy, over-reliance on algorithms, and their impact on human relationships and ethical issues. Many participants expressed the need to integrate AI training into their curricula to enhance their preparedness and competency in responsibly addressing this technology. 6. Impact of ethical climate, moral distress, and moral sensitivity on turnover intention among haemodialysis nurses: a cross sectional study (Kim, Kim and Oh, 2023 ) This cross-sectional study involved 148 nurses working in hemodialysis wards across 11 public hospitals in South Korea. The sample was drawn using convenience sampling. The research variables were turnover intention, ethical climate (trust in colleagues, managers, patients, physicians, and the hospital environment), moral distress associated with physician practice and aspects of future care, and moral sensitivity. The research instrument was the Korean version of the KTI (Turnover Intention) questionnaire, consisting of four items on a 5-point Likert scale, with a Cronbach's alpha reliability of 0.88. Data analysis included descriptive statistics (mean, standard deviation), t-tests, and ANOVA to examine group differences. Pearson's correlation coefficients were used to assess relationships between variables, and multiple regression with the stepwise method was used to identify factors influencing turnover intention. Research shows that moral distress arising from physician practice and the hospital's ethical climate are significant factors influencing nurses' intention to leave their jobs. A hostile ethical climate and moral distress significantly increase the likelihood that nurses will intend to quit. Conversely, a favorable ethical climate can help reduce turnover intentions. Although moral sensitivity did not significantly influence intention to quit, the study recommends addressing moral distress and improving the workplace ethical climate to reduce hemodialysis nurse turnover. 7. Relationships between nurse managers’ work activities, nurses’ job satisfaction, patient satisfaction, and medication errors at the unit level: a correlational study (Nurmeksela et al, 2020 ) This cross-sectional, correlational study involved nurse managers (n = 29), nursing staff (n = 306), and patients (n = 651) from 28 units across three acute hospitals in Finland, all drawn from convenience samples of staff and patients. The study variables were nurse managers' work activities, nurse job satisfaction, patient satisfaction, and medication errors (data from incident reports over one year). The study instruments used questionnaires: the NMWCQ (measuring nurse managers' work activities), the KUHJSS (measuring nurses' job satisfaction), and the RHCS (measuring patient satisfaction with the care they received). Data on medication error incidents were also collected from official hospital reports. Data Analysis: Spearman's correlation matrix was used to identify relationships between variables. Analysis of covariance (ANCOVA) was used to examine relationships among the NMWCQ, KUHJSS, and RHCS subscales, as well as between categorical variables such as hospital and the number of nurses per nurse manager. The Relationship between Nurse Managers' Work Activities and Nurse Job Satisfaction: Activities such as "Making arrangements" and "Making schedules" were positively associated with nurse job satisfaction. Conversely, activities such as "Attending meetings and providing guidance" showed a negative relationship with nurse motivation and job satisfaction. The Influence of Nurse Managers' Activities on Patient Satisfaction: Overall patient satisfaction was influenced by positive perceptions of nurse managers' leadership. Eight subdimensions of patient satisfaction were significantly related to nurse managers' work activities, nurse satisfaction, and medication error incidence. The Role of Nurse Satisfaction in Patient Satisfaction indicates that nurse satisfaction with nurse managers' leadership was positively correlated with outcome variables, including patient satisfaction and quality of care. The speed and amount of time spent in meetings and consultations. In general, the more time nurse managers spend in meetings and consultations, the more negatively associated it is with nurse motivation and job satisfaction. Strength and Significance of the Relationship: Work-related factors have the most significant influence on job satisfaction, patient satisfaction, and medication error incidence (p < 0.001). This relationship indicates that workload and complexity of managerial activities play a significant role in these outcomes. Statistical analysis results showed positive and negative relationships between managerial activities and outcome variables, indicating that appropriate activity management can improve work outcomes and service quality. Influence of Number of Nurses and Hospital: Organizational factors such as the number of nurses per nurse manager and hospital characteristics influence job satisfaction and medication error incidence. 8. The status of ethical behaviour in clinical nursing in three Chinese hospitals: A qualitative interview study (Wang et al., 2022 ) This was a qualitative descriptive study with a sample of 40 participants, comprising 21 head nurses and 19 clinical nurses with diverse backgrounds (department, position, age, gender, years of service) working across three hospitals in Anhui Province, China. The research variables were ethical behavior and non-compliance with ethical standards among nurses, along with their contributing factors, including ethical knowledge, attitudes, work environment, and personal factors. The research instrument was a semi-structured interview guide designed based on the literature and the researcher's experience. It contained questions related to perceptions, experiences, and factors influencing ethical and unethical behavior in clinical practice. Data were analyzed using content analysis. Data were coded and categorized by similar themes, then interpreted to identify key themes regarding ethical behavior and its determinants. Data analysis from in-depth interviews and focus group discussions revealed seven key themes related to nurses' ethical behavior in clinics: lack of awareness of patient privacy protection, violation of patient autonomy, inappropriate communication, failure to protect patients' best interests, lack of moral emotion, lack of psychological attention to specific patients, and factors contributing to unethical behavior, including personal factors of nurses, patient factors, high workload, ethical climate in the workplace, and inadequate regulations and policies. This study indicates that ethical behavior in clinical practice remains suboptimal, and numerous cases of unethical behavior are encountered. The leading causes include lack of awareness, an unconducive work environment, and personal and systemic factors influencing nurses' behavior. DISCUSSION Based on the analysis of selected articles, in the context of healthcare service safety and quality, studies on nurses' ethical behavior and its determinants indicate that many challenges remain in modern clinical practice. Research by Wang et al., ( 2022 ) indicates that low ethical awareness, an unsupportive work environment, and personal and systemic factors often lead to unethical behavior in the nursing workplace. These findings indicate that psychosocial aspects and organizational culture play a crucial role in building a strong ethical culture in the nursing environment. Based on organizational ethics theory and social norms theory, a conducive work environment will increase awareness and commitment to ethical behavior, thereby minimizing unethical behavior. The basic assumption is that external factors (organizational climate) and internal factors (individual moral values) interact to shape nurses' ethical behavior. Therefore, holistic, contextual, and value-oriented interventions are needed to strengthen professional integrity in nursing practice. Qualitative studies conducted by Wang et al., ( 2022 ) and Choe, Kwon and Kim, 2022 ) emphasized the importance of ethical competence and moral sensitivity as key components of patient-centered nursing practice. Moral sensitivity was shown to be a significant predictor of strengthening ethical behavior and improving the quality of patient-centered care. Based on professional ethics theory and moral development theory, increasing moral awareness and developing ethical competence are crucial for strengthening nurses' ability to address workplace moral dilemmas. The implication of these findings is the need for continuous integration of ethics education and moral training into nursing professional development programs. A feasible solution is to implement programs that strengthen moral sensitivity and professional ethics within healthcare institutions' education and training systems, enabling nurses to maintain moral integrity and autonomy in complex clinical situations. Regarding ethical climate and moral distress, Kim, Kim and Oh's, (2023) research shows that a hostile ethical climate and high levels of moral distress significantly influence nurses' intention to leave their jobs. Based on work stress and burnout theories, the mismatch between personal moral values and organizational conditions causes psychological distress, ultimately leading to a decline in the well-being of nursing staff. These findings emphasize the importance of managing an ethical climate and stress management as a primary focus in creating a humanistic and supportive work environment. Policy implications include strengthening ethical culture through ethical leadership training, facilitating psychological support, and establishing a safe ethical reporting system for healthcare workers. A long-term solution is to build an ethical support system and a reflective community in the workplace so that moral distress can be managed constructively and human values ​​remain the foundation of nursing practice. Research by Korte and Bohnet-Joschko, ( 2022 ), Choe, Kwon and Kim, ( 2022 ), Kim, Kim and Oh, ( 2023 ), and Nurmeksela et al, ( 2020 ) shows a strong relationship between job satisfaction, ethical perceptions, and managerial activities with nurses' ethical behavior. Irshad et al., ( 2022 ) added that the dynamics of leadership and communication within the organization strongly influence nurses' ethical behavior and empathy. A positive relationship between the head nurse and staff, accompanied by work activities that prioritize nurse well-being, directly impacts motivation and job satisfaction, ultimately improving service quality and patient safety. Based on transformational leadership theory and learning organization theory, ethical, humanistic leadership can create a positive, collaborative, and productive organizational culture. The underlying assumption is that developing leadership competencies and empathetic communication can enhance the ethical and humanistic dimensions of nursing care. The strategic implication is the need for ethical and humanistic leadership training at all managerial levels, as well as for integrating ethical principles into hospital policies and management systems. Overall, the synthesis of these studies demonstrates that the humanistic and ethical aspects of nursing must be a primary focus as we face the era of artificial intelligence (AI) and digital technology-based healthcare services. This era presents new challenges, including potential dehumanization, reduced empathy, and moral dilemmas in clinical decision-making. The implications of these findings underscore the need for ongoing ethics education, the strengthening of a humanistic organizational culture, and the systematic management of stress and moral distress. A comprehensive solution involves collaboration among nursing managers, educators as emphasized by Alhur et al., ( 2025 ), and healthcare workers to build a fair, reflective, and ethical work system that enables nursing professionals to maintain moral integrity and public trust amid rapid, complex changes in the healthcare system. The Integration of Philosophical Perspectives in the Analysis of Nursing Ethics in this review explains that philosophical approaches, particularly in normative and professional ethics, provide an important reflective framework for understanding and strengthening ethical behavior in nursing practice. Ethical philosophy explains not only what should be done but also why those actions are moral, and how character and virtue shape a nurse's professionalism. From a deontological ethical perspective, nurses have a moral obligation to respect human dignity and uphold patient autonomy. This principle asserts that ethical behavior is not solely measured by its outcomes, but by adherence to universal moral obligations. In contrast, a consequentialist (utilitarian) ethical approach evaluates actions based on their impact on patients' and society's well-being. In the context of AI-based nursing, both approaches are relevant for assessing how well technology-based decisions align with moral principles, patient safety, and human well-being (Wang et al., 2022 ). Virtue ethics emphasizes the importance of developing nurses' moral character, characterized by empathy, honesty, and compassion virtues that align with empirical findings on moral sensitivity and empathy in nursing practice (Nurmeksela et al, 2020 ; Choe, Kwon and Kim, 2022 ; Korte and Bohnet-Joschko, 2022 ; Kim, Kim and Oh, 2023 ). Virtue ethics positions moral values as character qualities that develop through reflective practice, rather than simply adherence to rules. From a social and political philosophy perspective, a just and humane work environment is a manifestation of the principle of social justice, as explained by John Rawls. When nursing staff face moral burdens and systemic pressures, this can be understood as a structural failure to uphold distributive justice and recognize worker dignity. Therefore, efforts to strengthen an ethical culture and reduce moral distress are a form of implementing social justice in the workplace (Nurmeksela et al, 2020 ; Wang et al., 2022 ; Kim, Kim and Oh, 2023 ). Thus, integrating ethical philosophy into nursing practice not only enriches theoretical understanding but also strengthens the moral foundations of professional decision-making, particularly in the digital and advanced technological era. Philosophically grounded ethical reflection is crucial to ensuring that technological advances, including AI, remain aligned with humanitarian values, justice, and moral integrity in healthcare (Choe, Kwon and Kim, 2022 ; Korte and Bohnet-Joschko, 2022 ; Wang et al., 2022 ). Therefore, strengthening moral competence, ethical leadership, and a compassionate organizational culture will make nursing practice more humane, meaningful, and socially just, ensuring the rights and dignity of patients and healthcare workers. CONCLUSION Ethical leadership is key to maintaining humanistic values ​​amidst the development of artificial intelligence (AI) and the digitalization of healthcare services. Various studies confirm that ethical behavior, moral sensitivity, and an organization's ethical climate mutually influence the quality of nursing practice. Leadership grounded in ethical values ​​has been shown to improve professional integrity, job satisfaction, and the quality of patient-centered care. From a philosophical perspective, ethical challenges in the digital age reflect a humanistic crisis where technological advances have the potential to shift moral autonomy and human closeness in nursing practice. Deontological, virtue-ethical, and social-justice approaches provide a reflective framework to ensure that technology is used responsibly and in a manner that upholds human dignity. Conceptually, ideal ethical leadership in the AI era should integrate three main dimensions: a moral foundation and ethical sensitivity; reflective, humanistic leadership practices; and accountable, human-centered technology use. The combination of these three aspects enables the nursing profession to continuously adapt to technological change without losing its human identity, thus ensuring that healthcare remains meaningful and ethical. References Alfuraydi AA, Al-Moteri M (2025) ‘Real-time assessment of triage nurse situational awareness (SA) using the situation awareness global assessment technique (SAGAT)’, PLoS ONE , 20(2 February), pp. 1–15. Available at: https://doi.org/10.1371/journal.pone.0318555 Alhur A, Ali et al (2025) ‘Attitudes Towards AI in Healthcare Among University of Hail Health Sciences Students: A Qualitative Exploration’, Journal of Pioneering Medical Sciences , 14(3), pp. 1–6. Available at: https://doi.org/10.47310/jpms2025140301 Arcadi P (2025) ‘Nursing leadership and artificial intelligence ethics: Safeguarding relationships and values’, Nursing Ethics , p. 09697330251366599. Available at: https://doi.org/10.1177/09697330251366599 Ateeq A (2024) ‘Ethical Paradigms at Work: A Comparative Analysis of Consequentialism, Deontology, and Islamic Perspectives’, Studies in Systems, Decision and Control , 524(May), pp. 605–611. Available at: https://doi.org/10.1007/978-3-031-54379-1_53 Cheong BC (2024) ‘Transparency and accountability in AI systems: safeguarding wellbeing in the age of algorithmic decision-making’, Frontiers in Human Dynamics , 6. Available at: https://doi.org/10.3389/fhumd.2024.1421273 Choe K, Kwon S, Kim S (2022) ‘How do ethically competent nurses behave in clinical nursing practice? A qualitative study’, Journal of Nursing Management , 30(8), pp. 4461–4471. Available at: https://doi.org/10.1111/jonm.13884 Giordano C et al (2021) ‘Accessing Artificial Intelligence for Clinical Decision-Making’, Frontiers in Digital Health , 3(June), pp. 1–9. Available at: https://doi.org/10.3389/fdgth.2021.645232 Hosseini Tabaghdehi SA, Ayaz Ö (2025) ‘AI ethics in action: a circular model for transparency, accountability and inclusivity’. J Managerial Psychol [Preprint]. Irshad M et al (2022) ‘When breaking the rule becomes necessary: The impact of leader–member exchange quality on nurses pro-social rule-breaking’, Nursing Open , 9(5), pp. 2289–2303. Available at: https://doi.org/10.1002/nop2.979 Jang SJ, Kim EH, Lee H (2022) ‘Moral sensitivity and person-centred care among mental health nurses in South Korea: A cross-sectional study’, Journal of Nursing Management , 30(7), pp. 2227–2235. Available at: https://doi.org/10.1111/jonm.13554 Kim H, Kim H, Oh Y (2023) ‘Impact of ethical climate, moral distress, and moral sensitivity on turnover intention among haemodialysis nurses: a cross-sectional study’, BMC Nursing , 22(1), pp. 1–9. Available at: https://doi.org/10.1186/s12912-023-01212-0 Korte L, Bohnet-Joschko S (2022) ‘Digitization in Everyday Nursing Care: A Vignette Study in German Hospitals’, International Journal of Environmental Research and Public Health , 19(17). Available at: https://doi.org/10.3390/ijerph191710775 Lameesa A et al (2024) ‘Role of metaheuristic algorithms in healthcare: a comprehensive investigation across clinical diagnosis, medical imaging, operations management, and public health’, Journal of Computational Design and Engineering , 11(3), pp. 223–247. Available at: https://doi.org/10.1093/jcde/qwae046 Lee A (2021) ‘Towards Informatic Personhood: understanding contemporary subjects in a data-driven society’, Information Communication and Society , 24(2), pp. 167–182. Available at: https://doi.org/10.1080/1369118X.2019.1637446 Namdar Areshtanab H et al (2025) ‘Nurses perceptions and use of artificial intelligence in healthcare’, Scientific Reports , 15(1), pp. 1–7. Available at: https://doi.org/10.1038/s41598-025-11002-0 Nurmeksela et al (2020) ‘Relationships between nurse managers’ work activities, nurses’ job satisfaction, patient satisfaction, and medication errors at the unit level: a correlational study’, Malaysian Journal of Medical Research , 4(2), pp. 1–13. Available at: https://doi.org/10.31674/mjmr.2020.v04i02.004 Page MJ et al (2021) ‘The PRISMA 2020 statement: An updated guideline for reporting systematic reviews’, Bmj , 372. Available at: https://doi.org/10.1136/bmj.n71 Park M et al (2022) ‘Nursing Students’ Orientation toward Patient-Centered Care: Testing the Effects of Empathy and Psychological Capital Using a Mediation Model’, Journal of Korean Academy of Nursing Administration , 28(4), pp. 361–370. Available at: https://doi.org/10.11111/jkana.2022.28.4.361 Pepito JA et al (2025) ‘Opportunities, Challenges, and Future Directions for the Integration of Automation in Nursing Practice: Discursive Study’, JMIR Nursing , 8. Available at: https://doi.org/10.2196/72674 Ricci E (2024) ‘Transforming leaders to transform hospitals. Cultivating ethical leadership for compassionate healthcare’. Med e Morale, 73(3) Ronquillo CE et al (2021) ‘Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative’, Journal of Advanced Nursing , 77(9), pp. 3707–3717. Available at: https://doi.org/10.1111/jan.14855 Rony MKK, Parvin MR, Ferdousi S (2024) ‘Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future’, Nursing Open , 11(1), pp. 1–9. Available at: https://doi.org/10.1002/nop2.2070 Salam A, Abhinesh N (2024) ‘Revolutionizing dermatology: The role of artificial intelligence in clinical practice’, IP Indian Journal of Clinical and Experimental Dermatology , 10(2), pp. 107–112. Available at: https://doi.org/10.18231/j.ijced.2024.021 Sullivan D, Hall VP, Morrison J (2024) ‘Navigating the future: artificial intelligence’s impact on transformational nurse leadership’, Teaching and Learning in Nursing , 19(3), pp. 298–300. Available at: https://doi.org/ https://doi.org/10.1016/j.teln.2024.04.017 Ugwu AK, Ozoemena LC (2023) A Critique of the Ethical Implications of the Existentialist Philosophy of Martin Heidegger. J Adv Res Social Sci Humanit ISSN 2208:2387 Villegas-Galaviz C, Martin K (2024) ‘Moral distance, AI, and the ethics of care’, AI and Society , 39(4), pp. 1695–1706. Available at: https://doi.org/10.1007/s00146-023-01642-z Wang S et al (2022) ‘The status of ethical behaviour in clinical nursing in three Chinese hospitals: A qualitative interview study’, Journal of Nursing Management , 30(7), pp. 2424–2433. Available at: https://doi.org/10.1111/jonm.13810 Wei Q et al (2025) ‘The integration of AI in nursing: addressing current applications, challenges, and future directions’, Frontiers in Medicine , 12(4). Available at: https://doi.org/10.3389/fmed.2025.1545420 Zhang J (2025) ‘Patočka’s phenomenology of the natural world: from Husserl to Heidegger and beyond’, Studies in East European Thought [Preprint]. Available at: https://doi.org/10.1007/s11212-025-09741-x Zhang X, Wang Q (2025) ‘The moral inversion of administrative AI: A critical interpretation on regime values’. Public Policy Adm, p. 09520767251379689 Zuhair V et al (2024) ‘Exploring the Impact of Artificial Intelligence on Global Health and Enhancing Healthcare in Developing Nations’, Journal of Primary Care and Community Health , 15. Available at: https://doi.org/10.1177/21501319241245847 Additional Declarations The authors declare potential competing interests as follows: We hereby declare that all authors agree that this review article will be published. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":277865,"visible":true,"origin":"","legend":"\u003cp\u003eProcedures for identifying, screening, and including research articles in the Scopus, Web of Science (WoS), PubMed, and EBSCO databases are available.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8092188/v1/17f51a9638769fda68dffbaf.jpg"},{"id":96255346,"identity":"d7d03a6d-8dd9-4315-a014-ef3fed9dea26","added_by":"auto","created_at":"2025-11-19 07:48:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":813802,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8092188/v1/63c6c2df-68a3-41f9-b56d-dcbc961e86be.pdf"}],"financialInterests":"The authors declare potential competing interests as follows: We hereby declare that all authors agree that this review article will be published.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eEthical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe use of artificial intelligence (AI) in healthcare systems has brought about fundamental changes in nursing practice (Rony, Parvin and Ferdousi, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). AI offers significant opportunities to improve efficiency, clinical accuracy, and data-driven decision-making (Giordano et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Salam and Abhinesh, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, the benefits of AI also present significant ethical and philosophical challenges in the healthcare sector, including nursing. Therefore, the role of leaders, particularly ethical leadership, is crucial for navigating the rapidly changing technological landscape while maintaining the humanistic values ​​at the core of the nursing profession (Ricci, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sullivan, Hall and Morrison, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Key emerging issues and challenges include data privacy and security, accountability for algorithm-based decisions, and the risk of losing the human touch in the nurse-patient relationship (Lameesa et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pepito et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Nursing leaders are now required not only to understand technology but also to maintain moral values, empathy, and human dignity in an increasingly digitalized system (Arcadi, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe use of AI in global healthcare is skyrocketing Zuhair et al., (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). AI is now applied in nursing documentation, work scheduling, real-time patient monitoring, and even early detection of changes in clinical conditions (Alfuraydi and Al-Moteri, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Wei et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, this progress has not been matched by the ethical and cognitive readiness of nursing staff. The results of the study Namdar Areshtanab et al., (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) in Iran showed that most nurses (41.1%) had low knowledge, (65.8%) had good attitudes, (74.6%) had moderate levels of acceptance, and (55.8%) implemented AI at a high level. This situation reflects a gap between technological innovation and ethical preparedness, thereby increasing the risk of moral disorientation in AI-based decision-making. In this regard, ethical leadership plays a crucial role in fostering transparency in the use of algorithms, ensuring accountability, and maintaining human oversight as the center of control and moral responsibility in AI-based systems (Park et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Cheong, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hosseini Tabaghdehi and Ayaz, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe integration of AI into nursing practice carries profound philosophical implications. The automation of clinical processes and algorithm-based decisions has the potential to shift nurses' space for moral reflection and empathy toward patients. This phenomenon is known as the displacement of moral agency, where humans gradually lose their role as autonomous moral subjects and become merely part of a data-driven system (Lee, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang and Wang, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Within the context of Heideggerian existentialist philosophy, this phenomenon illustrates a humanistic crisis in which humans risk becoming objects of their own creation (Ugwu and Ozoemena, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhang, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This shift can be interpreted as moving from care ethics, which emphasizes empathy and interpersonal relationships, to technological determinism, in which moral decisions are reduced to the outcomes of algorithmic logic (Villegas-Galaviz and Martin, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This condition results in a decline in the meaning of patient-centered care, and human dignity is potentially neglected in professional nursing relationships.\u003c/p\u003e\u003cp\u003eEfforts that can be made include developing and implementing ethical leadership in nursing to make it a moral force guiding the integration of AI with human values (Ronquillo et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Nursing leaders function not only as administrative decision-makers but also as moral agents who ensure that technological innovation does not erode empathy and compassion, the essence of the profession (Arcadi, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In this context, virtue ethics is relevant, as it emphasizes the development of moral character traits such as wisdom (phronesis), empathy, and compassion in nursing leadership (Nurmeksela et al, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Deontological and consequentialist ethical approaches are also important for assessing nurses' ethical actions, both in terms of moral obligations and the consequences for patients and the organization (Ateeq, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe ethical leadership approach in nursing encompasses not only individual moral dimensions but also profound structural and social dimensions. Based on John Rawls's theory of justice, the principle of social justice should be reflected in the equal distribution of responsibilities, welfare, and opportunities for healthcare workers to develop their ethical competencies. Therefore, developing a fair, reflective, and value-oriented work system is a concrete manifestation of social justice in nursing practice (Park et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kim, Kim and Oh, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nursing leaders play a central role in fostering a conducive ethical climate by creating space for moral reflection, strengthening nursing staff's psychological well-being, and preventing systemic pressures that can lead to dehumanization in clinical practice.\u003c/p\u003e\u003cp\u003eBased on the description, this literature review aims to examine ethical leadership in nursing and patient-centered care by explicitly examining the challenges and opportunities for implementing ethical leadership in maintaining humanistic care in the era of artificial intelligence (AI) and health digitalization, analyzing philosophical reflections on the humanistic crisis that arises due to the shift in values ​​and moral autonomy in modern nursing practice, and formulating a conceptual framework for ethical leadership that can integrate patient-centered care, moral principles, and the responsible application of AI technology. By incorporating the perspectives of ethics, philosophy, and nursing leadership, this review is expected to provide a solid conceptual foundation for the development of nursing practice that is not only adaptive to technological advances but also remains rooted in the values ​​of humanity, justice, and human dignity as the core of health services in the digital era.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThe literature selection stages followed the PRISMA guidelines (Page et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and the literature search used Scopus, Web of Science (WoS), PubMed, and EBSCO databases, with a time limit of 2020 to 2025.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eInclusion and Exclusion Criteria\u003c/h3\u003e\n\u003cp\u003eEthical leadership in nursing should be patient-centered, but technological developments, including AI, in healthcare are creating a humanistic crisis. This systematic review included studies involving nurses, nursing students, or nursing leaders in healthcare settings; studies addressing ethical leadership, moral sensitivity, professional ethics, patient-centered care, or the integration of AI digitalization into nursing practice; studies assessing or discussing the quality of patient care, ethical climate, nursing staff well-being, perceptions of AI, or humanistic values ​​in nursing practice; empirical studies (quantitative, qualitative, or mixed methods); conceptual/philosophical; English-language articles; and a focus on clinical nursing services, nursing education, or nursing management. Exclusion criteria included studies conducted on healthcare professionals other than nurses, studies that did not address ethical or leadership aspects, non-peer-reviewed articles, duplicate articles, articles lacking full text, and articles irrelevant to AI or patient-centered care settings.\u003c/p\u003e\n\u003ch3\u003eSearching Strategy\u003c/h3\u003e\n\u003cp\u003eLiterature search using Scopus, Web of Science, PubMed, and Ebsco databases with a limitation of 2020 to 2025. The keywords used are (Nurses AND \"Ethical leadership\" AND \"Patient-centered care\" OR \"AI in healthcare\").\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the identification, screening, and inclusion procedures for studies available in Scopus, Web of Science (WoS), PubMed, and EBSCO databases. Three independent researchers conducted the entire process based on the title and abstract, followed by a full-text review. If there was any uncertainty or doubt regarding the selected articles, a fourth researcher was contacted for consultation to resolve the issue. Full-text studies were obtained from electronic databases or the Airlangga University library in Surabaya.\u003c/p\u003e\n\u003ch3\u003eProcedure of Data Extraction\u003c/h3\u003e\n\u003cp\u003eThree independent researchers conducted data extraction. However, if there were any differences of opinion, a fourth researcher was consulted to provide insight and resolve any issues. All necessary information was obtained from the full text of the studies.\u003c/p\u003e"},{"header":"RESULT","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the results of research articles on Ethical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResearch articles on Ethical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTitle, Author, Years\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMethod\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResult\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDigitization in Everyday Nursing Care: A Vignette Study in German Hospitals (Korte and Bohnet-Joschko, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe research was a vignette study that evaluated a fictional situation involving the introduction of digital technology in a hospital. The sample consisted of 299 nurses. Variables included motivation towards technology use, attitudes towards innovation, and perceptions of the benefits and barriers of digital technology in care. The instrument used a Likert-scale questionnaire and open-ended questions. Data analysis used the Friedman test to compare variations in motivation between vignettes and the Wilcoxon test for paired comparisons. Other analyses included regression and correlation to evaluate the relationship between independent variables and motivation for technology use.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRespondents indicated greater motivation to use tablets than to use smart glasses as innovative technologies.\u003c/p\u003e\u003cp\u003eNo significant differences were found between intrinsic and extrinsic motivation.\u003c/p\u003e\u003cp\u003eMessages from nurse leaders emphasizing efficiency increased nurses' motivation to use digital technology more than messages focused on patient orientation.\u003c/p\u003e\u003cp\u003eIn general, nurses' attitudes toward digital technology use are high, and management support and training can strengthen their involvement in adopting new technologies.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHow do ethically competent nurses behave in clinical nursing practice? A qualitative study (Choe, Kwon and Kim, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResearch: A qualitative study with a phenomenological approach to understand the ethical behavior of nurses in clinical practice. A total of 20 participants were nurses working in various hospital departments in South Korea, with at least several months of experience, and were willing to participate. Sampling used a snowball sampling technique, where initial participants invited their colleagues who met the criteria to join. Research variables were factors and behaviors that indicate nurses' ethical competence in clinical practice, including caring attitudes, professional responsibility, and other ethical behaviors. Data were collected through semi-structured online interviews via a video platform. Questions were directed to discuss experiences, assessments, and observations of ethical behavior in clinical practice. Data analysis used a thematic analysis grounded in a phenomenological approach. The analysis process included repeated reading of transcripts, coding, grouping codes into categories, and developing main themes that represent nurses' ethical behavior.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResearch shows that nurses' ethical competence is based on their ability to serve patients with sincerity, professionalism, and compassion. Factors supporting ethical behavior include good working conditions, a supportive administrative system, effective communication among nurses, and a wealth of personal experience. Nurses who show sensitivity to patient needs, effective communication, and professional responsibility tend to exhibit high ethical behavior. A supportive work environment and positive experiences contribute to the strengthening of ethical practices in clinical practice.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMoral sensitivity and person-centred care among mental health nurses in South Korea: A cross-sectional study (Jang, Kim and Lee, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe study used a cross-sectional study of 220 mental health nurses in South Korea. The sample was selected according to criteria set by mental health nurses who had been actively working for at least 6 months and had provided written consent.\u003c/p\u003e\u003cp\u003eThe study variables were moral sensitivity, person-centered care, general characteristics (age, marital status, education level, work experience, job position), and educational history in bioethics and biomedical ethics. The research instrument was the Korean version of the Moral Sensitivity Questionnaire (MSQ), a 7-point Likert scale comprising 27 items that measure aspects such as patient orientation, professional responsibility, moral conflict, moral meaning, and virtue. The Korean version of the Person-Centered Practice Inventory - Staff (PCPI-S), a 5-point Likert scale, measured the level of patient-centered care practices.\u003c/p\u003e\u003cp\u003eData analysis used Pearson correlation tests to assess relationships among primary variables, t-tests to assess differences based on general characteristics, and analysis of variance to compare differences across general characteristics. Multiple regression analysis was used to identify predictors of patient-centered care practices, testing for multicollinearity and residual independence.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMoral sensitivity was the strongest predictor of improved patient-centered care practices.\u003c/p\u003e\u003cp\u003eBioethics education, history, and marital status also significantly influenced these practices.\u003c/p\u003e\u003cp\u003eThe regression model showed that moral sensitivity accounted for approximately 28% of the variation in patient-centered care practices, highlighting the importance of moral factors in improving care quality.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhen breaking the rule becomes necessary: The impact of leader\u0026ndash; member exchange quality on nurses pro- social rule- breaking (Irshad et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThis quantitative study involved 224 nurses working in a hospital, selected via convenience sampling. The research variables were Leader\u0026ndash;Member Exchange (LMX), Organizational Identification, and Pro-social Rule-breaking (PSRB). All variables were measured using a questionnaire using a five-point Likert scale, with validated and reliable instruments. The data were then analyzed using structural equation modeling (SEM) to test direct and mediating relationships among variables. The analysis also included instrument reliability and validity tests, as well as statistical model testing.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA positive relationship was found between the quality of leader-member exchange (LMX) relationships and nurses' levels of organizational identification.\u003c/p\u003e\u003cp\u003eNurses with good relationships with their superiors tended to demonstrate high levels of organizational identification.\u003c/p\u003e\u003cp\u003eHigh levels of organizational identification increased nurses' tendency to engage in pro-social rule-breaking, a form of constructive deviance.\u003c/p\u003e\u003cp\u003eThese findings confirm that positive relationships with superiors and a sense of organizational identification can foster positive pro-social behavior in the nursing context.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttitudes Towards AI in Healthcare Among University of Hail Health Sciences Students: A Qualitative Exploration (Alhur et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe research is a qualitative case study with a sample of 18 health students, including nursing students. The research variables are students' understanding of AI in the health sector, students' attitudes towards AI integration in clinics, perceived benefits and challenges of AI, ethical considerations related to AI, and educational needs and training on AI. The research instrument is a semi-structured interview guide covering five main areas: understanding AI, attitudes towards AI integration, perceived benefits, concerns and challenges, and educational needs about AI. Data analysis uses a six-stage thematic analysis framework by Braun and Clarke, namely: data familiarization, initial coding, theme search, theme review, theme definition and naming, and reporting results. The analysis approach is combined inductively and deductively: initially through open coding, then highlighted and organized in line with the literature and study objectives.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStudents generally recognized AI's potential to improve efficiency and accuracy in healthcare and expressed positive attitudes toward its benefits. However, they also expressed concerns about data privacy, over-reliance on algorithms, and their impact on human relationships and ethical issues. Many participants expressed the need to integrate AI training into their curricula to enhance their preparedness and competency in responsibly addressing this technology.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImpact of ethical climate, moral distress, and moral sensitivity on turnover intention among haemodialysis nurses: a cross sectional study (Kim, Kim and Oh, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThis cross-sectional study involved 148 nurses working in hemodialysis wards across 11 public hospitals in South Korea. The sample was drawn using convenience sampling. The research variables were turnover intention, ethical climate (trust in colleagues, managers, patients, physicians, and the hospital environment), moral distress associated with physician practice and aspects of future care, and moral sensitivity.\u003c/p\u003e\u003cp\u003eThe research instrument was the Korean version of the KTI (Turnover Intention) questionnaire, consisting of four items on a 5-point Likert scale, with a Cronbach's alpha reliability of 0.88. Data analysis included descriptive statistics (mean, standard deviation), t-tests, and ANOVA to examine group differences. Pearson's correlation coefficients were used to assess relationships between variables, and multiple regression with the stepwise method was used to identify factors influencing turnover intention.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResearch shows that moral distress arising from physician practice and the hospital's ethical climate are significant factors influencing nurses' intention to leave their jobs. A hostile ethical climate and moral distress significantly increase the likelihood that nurses will intend to quit. Conversely, a favorable ethical climate can help reduce turnover intentions. Although moral sensitivity did not significantly influence intention to quit, the study recommends addressing moral distress and improving the workplace ethical climate to reduce hemodialysis nurse turnover.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRelationships between nurse managers\u0026rsquo; work activities, nurses\u0026rsquo; job satisfaction, patient satisfaction, and medication errors at the unit level: a correlational study (Nurmeksela et al, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThis cross-sectional, correlational study involved nurse managers (n\u0026thinsp;=\u0026thinsp;29), nursing staff (n\u0026thinsp;=\u0026thinsp;306), and patients (n\u0026thinsp;=\u0026thinsp;651) from 28 units across three acute hospitals in Finland, all drawn from convenience samples of staff and patients. The study variables were nurse managers' work activities, nurse job satisfaction, patient satisfaction, and medication errors (data from incident reports over one year).\u003c/p\u003e\u003cp\u003eThe study instruments used questionnaires: the NMWCQ (measuring nurse managers' work activities), the KUHJSS (measuring nurses' job satisfaction), and the RHCS (measuring patient satisfaction with the care they received). Data on medication error incidents were also collected from official hospital reports.\u003c/p\u003e\u003cp\u003eData Analysis: Spearman's correlation matrix was used to identify relationships between variables. Analysis of covariance (ANCOVA) was used to examine relationships among the NMWCQ, KUHJSS, and RHCS subscales, as well as between categorical variables such as hospital and the number of nurses per nurse manager.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThe Relationship between Nurse Managers' Work Activities and Nurse Job Satisfaction: Activities such as \"Making arrangements\" and \"Making schedules\" were positively associated with nurse job satisfaction. Conversely, activities such as \"Attending meetings and providing guidance\" showed a negative relationship with nurse motivation and job satisfaction.\u003c/p\u003e\u003cp\u003eThe Influence of Nurse Managers' Activities on Patient Satisfaction: Overall patient satisfaction was influenced by positive perceptions of nurse managers' leadership. Eight subdimensions of patient satisfaction were significantly related to nurse managers' work activities, nurse satisfaction, and medication error incidence.\u003c/p\u003e\u003cp\u003eThe Role of Nurse Satisfaction in Patient Satisfaction indicates that nurse satisfaction with nurse managers' leadership was positively correlated with outcome variables, including patient satisfaction and quality of care.\u003c/p\u003e\u003cp\u003eThe speed and amount of time spent in meetings and consultations. In general, the more time nurse managers spend in meetings and consultations, the more negatively associated it is with nurse motivation and job satisfaction.\u003c/p\u003e\u003cp\u003eStrength and Significance of the Relationship: Work-related factors have the most significant influence on job satisfaction, patient satisfaction, and medication error incidence (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This relationship indicates that workload and complexity of managerial activities play a significant role in these outcomes.\u003c/p\u003e\u003cp\u003eStatistical analysis results showed positive and negative relationships between managerial activities and outcome variables, indicating that appropriate activity management can improve work outcomes and service quality.\u003c/p\u003e\u003cp\u003eInfluence of Number of Nurses and Hospital: Organizational factors such as the number of nurses per nurse manager and hospital characteristics influence job satisfaction and medication error incidence.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe status of ethical behaviour in clinical nursing in three Chinese hospitals: A qualitative interview study (Wang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThis was a qualitative descriptive study with a sample of 40 participants, comprising 21 head nurses and 19 clinical nurses with diverse backgrounds (department, position, age, gender, years of service) working across three hospitals in Anhui Province, China.\u003c/p\u003e\u003cp\u003eThe research variables were ethical behavior and non-compliance with ethical standards among nurses, along with their contributing factors, including ethical knowledge, attitudes, work environment, and personal factors. The research instrument was a semi-structured interview guide designed based on the literature and the researcher's experience. It contained questions related to perceptions, experiences, and factors influencing ethical and unethical behavior in clinical practice. Data were analyzed using content analysis. Data were coded and categorized by similar themes, then interpreted to identify key themes regarding ethical behavior and its determinants.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eData analysis from in-depth interviews and focus group discussions revealed seven key themes related to nurses' ethical behavior in clinics: lack of awareness of patient privacy protection, violation of patient autonomy, inappropriate communication, failure to protect patients' best interests, lack of moral emotion, lack of psychological attention to specific patients, and factors contributing to unethical behavior, including personal factors of nurses, patient factors, high workload, ethical climate in the workplace, and inadequate regulations and policies.\u003c/p\u003e\u003cp\u003eThis study indicates that ethical behavior in clinical practice remains suboptimal, and numerous cases of unethical behavior are encountered. The leading causes include lack of awareness, an unconducive work environment, and personal and systemic factors influencing nurses' behavior.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eBased on the analysis of selected articles, in the context of healthcare service safety and quality, studies on nurses' ethical behavior and its determinants indicate that many challenges remain in modern clinical practice. Research by Wang et al., (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) indicates that low ethical awareness, an unsupportive work environment, and personal and systemic factors often lead to unethical behavior in the nursing workplace. These findings indicate that psychosocial aspects and organizational culture play a crucial role in building a strong ethical culture in the nursing environment. Based on organizational ethics theory and social norms theory, a conducive work environment will increase awareness and commitment to ethical behavior, thereby minimizing unethical behavior. The basic assumption is that external factors (organizational climate) and internal factors (individual moral values) interact to shape nurses' ethical behavior. Therefore, holistic, contextual, and value-oriented interventions are needed to strengthen professional integrity in nursing practice.\u003c/p\u003e\u003cp\u003eQualitative studies conducted by Wang et al., (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Choe, Kwon and Kim, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) emphasized the importance of ethical competence and moral sensitivity as key components of patient-centered nursing practice. Moral sensitivity was shown to be a significant predictor of strengthening ethical behavior and improving the quality of patient-centered care. Based on professional ethics theory and moral development theory, increasing moral awareness and developing ethical competence are crucial for strengthening nurses' ability to address workplace moral dilemmas. The implication of these findings is the need for continuous integration of ethics education and moral training into nursing professional development programs. A feasible solution is to implement programs that strengthen moral sensitivity and professional ethics within healthcare institutions' education and training systems, enabling nurses to maintain moral integrity and autonomy in complex clinical situations.\u003c/p\u003e\u003cp\u003eRegarding ethical climate and moral distress, Kim, Kim and Oh's, (2023) research shows that a hostile ethical climate and high levels of moral distress significantly influence nurses' intention to leave their jobs. Based on work stress and burnout theories, the mismatch between personal moral values and organizational conditions causes psychological distress, ultimately leading to a decline in the well-being of nursing staff. These findings emphasize the importance of managing an ethical climate and stress management as a primary focus in creating a humanistic and supportive work environment. Policy implications include strengthening ethical culture through ethical leadership training, facilitating psychological support, and establishing a safe ethical reporting system for healthcare workers. A long-term solution is to build an ethical support system and a reflective community in the workplace so that moral distress can be managed constructively and human values ​​remain the foundation of nursing practice.\u003c/p\u003e\u003cp\u003eResearch by Korte and Bohnet-Joschko, (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Choe, Kwon and Kim, (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Kim, Kim and Oh, (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and Nurmeksela et al, (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) shows a strong relationship between job satisfaction, ethical perceptions, and managerial activities with nurses' ethical behavior. Irshad et al., (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) added that the dynamics of leadership and communication within the organization strongly influence nurses' ethical behavior and empathy. A positive relationship between the head nurse and staff, accompanied by work activities that prioritize nurse well-being, directly impacts motivation and job satisfaction, ultimately improving service quality and patient safety. Based on transformational leadership theory and learning organization theory, ethical, humanistic leadership can create a positive, collaborative, and productive organizational culture. The underlying assumption is that developing leadership competencies and empathetic communication can enhance the ethical and humanistic dimensions of nursing care. The strategic implication is the need for ethical and humanistic leadership training at all managerial levels, as well as for integrating ethical principles into hospital policies and management systems.\u003c/p\u003e\u003cp\u003eOverall, the synthesis of these studies demonstrates that the humanistic and ethical aspects of nursing must be a primary focus as we face the era of artificial intelligence (AI) and digital technology-based healthcare services. This era presents new challenges, including potential dehumanization, reduced empathy, and moral dilemmas in clinical decision-making. The implications of these findings underscore the need for ongoing ethics education, the strengthening of a humanistic organizational culture, and the systematic management of stress and moral distress. A comprehensive solution involves collaboration among nursing managers, educators as emphasized by Alhur et al., (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and healthcare workers to build a fair, reflective, and ethical work system that enables nursing professionals to maintain moral integrity and public trust amid rapid, complex changes in the healthcare system.\u003c/p\u003e\u003cp\u003eThe Integration of Philosophical Perspectives in the Analysis of Nursing Ethics in this review explains that philosophical approaches, particularly in normative and professional ethics, provide an important reflective framework for understanding and strengthening ethical behavior in nursing practice. Ethical philosophy explains not only what should be done but also why those actions are moral, and how character and virtue shape a nurse's professionalism.\u003c/p\u003e\u003cp\u003eFrom a deontological ethical perspective, nurses have a moral obligation to respect human dignity and uphold patient autonomy. This principle asserts that ethical behavior is not solely measured by its outcomes, but by adherence to universal moral obligations. In contrast, a consequentialist (utilitarian) ethical approach evaluates actions based on their impact on patients' and society's well-being. In the context of AI-based nursing, both approaches are relevant for assessing how well technology-based decisions align with moral principles, patient safety, and human well-being (Wang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVirtue ethics emphasizes the importance of developing nurses' moral character, characterized by empathy, honesty, and compassion virtues that align with empirical findings on moral sensitivity and empathy in nursing practice (Nurmeksela et al, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Choe, Kwon and Kim, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Korte and Bohnet-Joschko, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kim, Kim and Oh, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Virtue ethics positions moral values as character qualities that develop through reflective practice, rather than simply adherence to rules.\u003c/p\u003e\u003cp\u003eFrom a social and political philosophy perspective, a just and humane work environment is a manifestation of the principle of social justice, as explained by John Rawls. When nursing staff face moral burdens and systemic pressures, this can be understood as a structural failure to uphold distributive justice and recognize worker dignity. Therefore, efforts to strengthen an ethical culture and reduce moral distress are a form of implementing social justice in the workplace (Nurmeksela et al, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kim, Kim and Oh, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThus, integrating ethical philosophy into nursing practice not only enriches theoretical understanding but also strengthens the moral foundations of professional decision-making, particularly in the digital and advanced technological era. Philosophically grounded ethical reflection is crucial to ensuring that technological advances, including AI, remain aligned with humanitarian values, justice, and moral integrity in healthcare (Choe, Kwon and Kim, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Korte and Bohnet-Joschko, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, strengthening moral competence, ethical leadership, and a compassionate organizational culture will make nursing practice more humane, meaningful, and socially just, ensuring the rights and dignity of patients and healthcare workers.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eEthical leadership is key to maintaining humanistic values ​​amidst the development of artificial intelligence (AI) and the digitalization of healthcare services. Various studies confirm that ethical behavior, moral sensitivity, and an organization's ethical climate mutually influence the quality of nursing practice. Leadership grounded in ethical values ​​has been shown to improve professional integrity, job satisfaction, and the quality of patient-centered care.\u003c/p\u003e\u003cp\u003eFrom a philosophical perspective, ethical challenges in the digital age reflect a humanistic crisis where technological advances have the potential to shift moral autonomy and human closeness in nursing practice. Deontological, virtue-ethical, and social-justice approaches provide a reflective framework to ensure that technology is used responsibly and in a manner that upholds human dignity.\u003c/p\u003e\u003cp\u003eConceptually, ideal ethical leadership in the AI era should integrate three main dimensions: a moral foundation and ethical sensitivity; reflective, humanistic leadership practices; and accountable, human-centered technology use. The combination of these three aspects enables the nursing profession to continuously adapt to technological change without losing its human identity, thus ensuring that healthcare remains meaningful and ethical.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlfuraydi AA, Al-Moteri M (2025) \u0026lsquo;Real-time assessment of triage nurse situational awareness (SA) using the situation awareness global assessment technique (SAGAT)\u0026rsquo;, \u003cem\u003ePLoS ONE\u003c/em\u003e, 20(2 February), pp. 1\u0026ndash;15. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0318555\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0318555\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlhur A, Ali et al (2025) \u0026lsquo;Attitudes Towards AI in Healthcare Among University of Hail Health Sciences Students: A Qualitative Exploration\u0026rsquo;, \u003cem\u003eJournal of Pioneering Medical Sciences\u003c/em\u003e, 14(3), pp. 1\u0026ndash;6. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.47310/jpms2025140301\u003c/span\u003e\u003cspan address=\"10.47310/jpms2025140301\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArcadi P (2025) \u0026lsquo;Nursing leadership and artificial intelligence ethics: Safeguarding relationships and values\u0026rsquo;, \u003cem\u003eNursing Ethics\u003c/em\u003e, p. 09697330251366599. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/09697330251366599\u003c/span\u003e\u003cspan address=\"10.1177/09697330251366599\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAteeq A (2024) \u0026lsquo;Ethical Paradigms at Work: A Comparative Analysis of Consequentialism, Deontology, and Islamic Perspectives\u0026rsquo;, \u003cem\u003eStudies in Systems, Decision and Control\u003c/em\u003e, 524(May), pp. 605\u0026ndash;611. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-3-031-54379-1_53\u003c/span\u003e\u003cspan address=\"10.1007/978-3-031-54379-1_53\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheong BC (2024) \u0026lsquo;Transparency and accountability in AI systems: safeguarding wellbeing in the age of algorithmic decision-making\u0026rsquo;, \u003cem\u003eFrontiers in Human Dynamics\u003c/em\u003e, 6. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fhumd.2024.1421273\u003c/span\u003e\u003cspan address=\"10.3389/fhumd.2024.1421273\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoe K, Kwon S, Kim S (2022) \u0026lsquo;How do ethically competent nurses behave in clinical nursing practice? A qualitative study\u0026rsquo;, \u003cem\u003eJournal of Nursing Management\u003c/em\u003e, 30(8), pp. 4461\u0026ndash;4471. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jonm.13884\u003c/span\u003e\u003cspan address=\"10.1111/jonm.13884\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiordano C et al (2021) \u0026lsquo;Accessing Artificial Intelligence for Clinical Decision-Making\u0026rsquo;, \u003cem\u003eFrontiers in Digital Health\u003c/em\u003e, 3(June), pp. 1\u0026ndash;9. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fdgth.2021.645232\u003c/span\u003e\u003cspan address=\"10.3389/fdgth.2021.645232\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHosseini Tabaghdehi SA, Ayaz \u0026Ouml; (2025) \u0026lsquo;AI ethics in action: a circular model for transparency, accountability and inclusivity\u0026rsquo;. J Managerial Psychol [Preprint].\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIrshad M et al (2022) \u0026lsquo;When breaking the rule becomes necessary: The impact of leader\u0026ndash;member exchange quality on nurses pro-social rule-breaking\u0026rsquo;, \u003cem\u003eNursing Open\u003c/em\u003e, 9(5), pp. 2289\u0026ndash;2303. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/nop2.979\u003c/span\u003e\u003cspan address=\"10.1002/nop2.979\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJang SJ, Kim EH, Lee H (2022) \u0026lsquo;Moral sensitivity and person-centred care among mental health nurses in South Korea: A cross-sectional study\u0026rsquo;, \u003cem\u003eJournal of Nursing Management\u003c/em\u003e, 30(7), pp. 2227\u0026ndash;2235. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jonm.13554\u003c/span\u003e\u003cspan address=\"10.1111/jonm.13554\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim H, Kim H, Oh Y (2023) \u0026lsquo;Impact of ethical climate, moral distress, and moral sensitivity on turnover intention among haemodialysis nurses: a cross-sectional study\u0026rsquo;, \u003cem\u003eBMC Nursing\u003c/em\u003e, 22(1), pp. 1\u0026ndash;9. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12912-023-01212-0\u003c/span\u003e\u003cspan address=\"10.1186/s12912-023-01212-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKorte L, Bohnet-Joschko S (2022) \u0026lsquo;Digitization in Everyday Nursing Care: A Vignette Study in German Hospitals\u0026rsquo;, \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e, 19(17). Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph191710775\u003c/span\u003e\u003cspan address=\"10.3390/ijerph191710775\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLameesa A et al (2024) \u0026lsquo;Role of metaheuristic algorithms in healthcare: a comprehensive investigation across clinical diagnosis, medical imaging, operations management, and public health\u0026rsquo;, \u003cem\u003eJournal of Computational Design and Engineering\u003c/em\u003e, 11(3), pp. 223\u0026ndash;247. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jcde/qwae046\u003c/span\u003e\u003cspan address=\"10.1093/jcde/qwae046\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee A (2021) \u0026lsquo;Towards Informatic Personhood: understanding contemporary subjects in a data-driven society\u0026rsquo;, \u003cem\u003eInformation Communication and Society\u003c/em\u003e, 24(2), pp. 167\u0026ndash;182. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/1369118X.2019.1637446\u003c/span\u003e\u003cspan address=\"10.1080/1369118X.2019.1637446\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNamdar Areshtanab H et al (2025) \u0026lsquo;Nurses perceptions and use of artificial intelligence in healthcare\u0026rsquo;, \u003cem\u003eScientific Reports\u003c/em\u003e, 15(1), pp. 1\u0026ndash;7. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-025-11002-0\u003c/span\u003e\u003cspan address=\"10.1038/s41598-025-11002-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNurmeksela et al (2020) \u0026lsquo;Relationships between nurse managers\u0026rsquo; work activities, nurses\u0026rsquo; job satisfaction, patient satisfaction, and medication errors at the unit level: a correlational study\u0026rsquo;, \u003cem\u003eMalaysian Journal of Medical Research\u003c/em\u003e, 4(2), pp. 1\u0026ndash;13. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.31674/mjmr.2020.v04i02.004\u003c/span\u003e\u003cspan address=\"10.31674/mjmr.2020.v04i02.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePage MJ et al (2021) \u0026lsquo;The PRISMA 2020 statement: An updated guideline for reporting systematic reviews\u0026rsquo;, \u003cem\u003eBmj\u003c/em\u003e, 372. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmj.n71\u003c/span\u003e\u003cspan address=\"10.1136/bmj.n71\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark M et al (2022) \u0026lsquo;Nursing Students\u0026rsquo; Orientation toward Patient-Centered Care: Testing the Effects of Empathy and Psychological Capital Using a Mediation Model\u0026rsquo;, \u003cem\u003eJournal of Korean Academy of Nursing Administration\u003c/em\u003e, 28(4), pp. 361\u0026ndash;370. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.11111/jkana.2022.28.4.361\u003c/span\u003e\u003cspan address=\"10.11111/jkana.2022.28.4.361\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePepito JA et al (2025) \u0026lsquo;Opportunities, Challenges, and Future Directions for the Integration of Automation in Nursing Practice: Discursive Study\u0026rsquo;, \u003cem\u003eJMIR Nursing\u003c/em\u003e, 8. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2196/72674\u003c/span\u003e\u003cspan address=\"10.2196/72674\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRicci E (2024) \u0026lsquo;Transforming leaders to transform hospitals. Cultivating ethical leadership for compassionate healthcare\u0026rsquo;. Med e Morale, 73(3)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRonquillo CE et al (2021) \u0026lsquo;Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative\u0026rsquo;, \u003cem\u003eJournal of Advanced Nursing\u003c/em\u003e, 77(9), pp. 3707\u0026ndash;3717. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jan.14855\u003c/span\u003e\u003cspan address=\"10.1111/jan.14855\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRony MKK, Parvin MR, Ferdousi S (2024) \u0026lsquo;Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future\u0026rsquo;, \u003cem\u003eNursing Open\u003c/em\u003e, 11(1), pp. 1\u0026ndash;9. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/nop2.2070\u003c/span\u003e\u003cspan address=\"10.1002/nop2.2070\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalam A, Abhinesh N (2024) \u0026lsquo;Revolutionizing dermatology: The role of artificial intelligence in clinical practice\u0026rsquo;, \u003cem\u003eIP Indian Journal of Clinical and Experimental Dermatology\u003c/em\u003e, 10(2), pp. 107\u0026ndash;112. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.18231/j.ijced.2024.021\u003c/span\u003e\u003cspan address=\"10.18231/j.ijced.2024.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSullivan D, Hall VP, Morrison J (2024) \u0026lsquo;Navigating the future: artificial intelligence\u0026rsquo;s impact on transformational nurse leadership\u0026rsquo;, \u003cem\u003eTeaching and Learning in Nursing\u003c/em\u003e, 19(3), pp. 298\u0026ndash;300. Available at: https://doi.org/\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.teln.2024.04.017\u003c/span\u003e\u003cspan address=\"10.1016/j.teln.2024.04.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUgwu AK, Ozoemena LC (2023) A Critique of the Ethical Implications of the Existentialist Philosophy of Martin Heidegger. J Adv Res Social Sci Humanit ISSN 2208:2387\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVillegas-Galaviz C, Martin K (2024) \u0026lsquo;Moral distance, AI, and the ethics of care\u0026rsquo;, \u003cem\u003eAI and Society\u003c/em\u003e, 39(4), pp. 1695\u0026ndash;1706. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00146-023-01642-z\u003c/span\u003e\u003cspan address=\"10.1007/s00146-023-01642-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang S et al (2022) \u0026lsquo;The status of ethical behaviour in clinical nursing in three Chinese hospitals: A qualitative interview study\u0026rsquo;, \u003cem\u003eJournal of Nursing Management\u003c/em\u003e, 30(7), pp. 2424\u0026ndash;2433. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jonm.13810\u003c/span\u003e\u003cspan address=\"10.1111/jonm.13810\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWei Q et al (2025) \u0026lsquo;The integration of AI in nursing: addressing current applications, challenges, and future directions\u0026rsquo;, \u003cem\u003eFrontiers in Medicine\u003c/em\u003e, 12(4). Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fmed.2025.1545420\u003c/span\u003e\u003cspan address=\"10.3389/fmed.2025.1545420\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang J (2025) \u0026lsquo;Patočka\u0026rsquo;s phenomenology of the natural world: from Husserl to Heidegger and beyond\u0026rsquo;, \u003cem\u003eStudies in East European Thought\u003c/em\u003e [Preprint]. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11212-025-09741-x\u003c/span\u003e\u003cspan address=\"10.1007/s11212-025-09741-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang X, Wang Q (2025) \u0026lsquo;The moral inversion of administrative AI: A critical interpretation on regime values\u0026rsquo;. Public Policy Adm, p. 09520767251379689\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZuhair V et al (2024) \u0026lsquo;Exploring the Impact of Artificial Intelligence on Global Health and Enhancing Healthcare in Developing Nations\u0026rsquo;, \u003cem\u003eJournal of Primary Care and Community Health\u003c/em\u003e, 15. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/21501319241245847\u003c/span\u003e\u003cspan address=\"10.1177/21501319241245847\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ethical Leadership, Nursing Ethics, Patient-Centered Care, Artificial Intelligence, Humanism","lastPublishedDoi":"10.21203/rs.3.rs-8092188/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8092188/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe integration of artificial intelligence (AI) into healthcare has fundamentally transformed nursing practice. While increasing efficiency and accuracy, these changes also pose ethical challenges and a humanistic crisis.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis literature review aims to examine the challenges and opportunities for implementing ethical leadership to maintain humanistic care in the AI era, analyze philosophical reflections on the moral crisis arising from digitalization, and formulate a conceptual framework that responsibly integrates ethics, humanism, and technology.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThe review was conducted according to PRISMA guidelines, using a literature search across Scopus, PubMed, Web of Science, and EBSCO with relevant keywords. A total of eight articles published between 2020 and 2025 met the inclusion criteria and were analyzed narratively.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMoral sensitivity, ethical competence, and a favorable ethical climate improve ethical behavior and quality of care. Transformational and humanistic leadership enhance moral reflection and organizational justice, while a hostile ethical climate increases moral distress. The philosophical perspectives of deontology, virtue ethics, and social justice provide a reflective foundation for maintaining moral autonomy in the AI ​​era.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eEthical leadership bridges technology and humanity, ensuring digital innovation upholds human dignity through moral foundations, reflective leadership, and responsible AI integration.\u003c/p\u003e","manuscriptTitle":"Ethical Leadership in Nursing and Patient-Centered Care: A Philosophical Reflection on the Humanistic Crisis in an AI-Driven Healthcare Era","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 16:10:12","doi":"10.21203/rs.3.rs-8092188/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f484ee3c-91e9-4ab4-b3e0-96dd04c65caa","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57842497,"name":"Nursing"}],"tags":[],"updatedAt":"2025-11-14T16:10:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 16:10:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8092188","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8092188","identity":"rs-8092188","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}