Nursing Caring for Terminal Patients in the ICU: A Systematic Literature Review on Humanistic Roles Beyond Artificial Intelligence

Nursing Caring for Terminal Patients in the ICU: A Systematic Literature Review on Humanistic Roles Beyond Artificial Intelligence | 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 Nursing Caring for Terminal Patients in the ICU: A Systematic Literature Review on Humanistic Roles Beyond Artificial Intelligence Kori Limbong, Fathiya Luthfil Yumni, Vina Putri Patandung, Erika Martining Wardani, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8029656/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: End of life care (EOLC) in intensive care units (ICUs) involves complex ethical, emotional, and systemic challenges that are increasingly influenced by the integration of artificial intelligence (AI) in healthcare. Nurses often experience moral distress when balancing life sustaining interventions and patient dignity while adapting to technological systems that affect empathy, accountability, and clinical judgment. Objective: This study aims to synthesize empirical evidence on nurses’ experiences, ethical dilemmas, and evolving roles in providing EOLC within the digital era, emphasizing the humanistic aspects that extend beyond AI applications. Methods: A systematic literature review was conducted following the PRISMA 2020 guidelines. Searches were performed in PubMed, Scopus, and CINAHL databases for peer reviewed articles published between 2019 and 2025. Nine eligible studies were analyzed thematically, covering ethical, emotional, cultural, systemic, and technological dimensions of EOLC nursing. Results: Nurses reported moral distress, limited palliative care competence, emotional fatigue, and inadequate institutional support. While AI enhanced efficiency and decision accuracy, concerns persisted about algorithmic bias, data transparency, and dehumanization of care. The findings highlight the irreplaceable human role of nurses in providing empathy, moral reasoning, and spiritual presence within AI supported environments. Conclusion: Effective EOLC in the AI era requires synergy between technological precision and compassionate nursing. Sustaining human centered values remains essential to ensure ethical integrity, emotional resilience, and dignified patient care. Nursing Critical Care & Emergency Medicine End of life care Critical care nursing Artificial intelligence Ethics Empathy Humanistic nursing Digital transformation Figures Figure 1 INTRODUCTION End of life care (EOLC) in the context of intensive nursing practice presents increasing ethical, emotional, and systemic complexities, particularly with the advancement of digital technology and the growing integration of artificial intelligence (AI) in healthcare. International studies affirm that nurses working in intensive care units (ICUs) frequently face moral dilemmas in balancing life-prolonging interventions with the preservation of patient dignity (Palmryd et al., 2025).These challenges are often intensified by family pressure, interprofessional conflict, and the absence of clear ethical guidelines. Moreover, significant gaps remain in nurses’ understanding of palliative care philosophy and competence, as reported among ICU nurses in Oman and Indonesia ((Almahrizi et al., 2025); (Mediani et al., 2024). Emotionally, ICU nurses experience moral fatigue, sadness, and guilt due to their recurrent exposure to death and dying (Aschale et al., 2025). Cultural factors also play a crucial role; in East and Southeast Asian settings, family values and religious beliefs profoundly influence medical decision making ((Xu et al., 2025). In addition, a study in France revealed that aggressive end of life interventions. With the progression of digitalisation, a new dimension has emerged in nursing practice, AI integration. (Martinez-Ortigosa et al., 2023)demonstrated that AI applications in nursing can enhance efficiency and service quality; however, they also raise ethical concerns related to algorithmic bias and the potential dehumanisation of care. (Challen et al., 2019) emphasised that AI should function as an assistive tool within a human in the loop framework to preserve clinical safety and accountability. In nursing education, AI ethics awareness has become a vital competency for future practitioners. Yang (2024) found a strong correlation between digital literacy, moral sensitivity, and AI ethics awareness among nursing students. Therefore, the challenges of end of life care now extend beyond traditional ethical and emotional issues to include how nursing professionals navigate the integration of intelligent technologies without compromising humanity, empathy, and professional responsibility. METHODS Study Design This study employed a Systematic Literature Review (SLR) design to identify, evaluate, and synthesise empirical research related to nurses’ experiences, ethical challenges, and the role of artificial intelligence (AI) in end of life care (EOLC) within intensive care units (ICUs). The review followed the PRISMA 2020 guidelines to ensure methodological transparency, reproducibility, and rigour throughout the literature screening and synthesis process. Inclusion and Exclusion Criteria Inclusion criteria included: Empirical studies (qualitative, quantitative, or mixed methods) published in peer reviewed journals between 2019 and 2025. Research focusing on the experiences of nurses or healthcare professionals in providing EOLC in ICU settings. Studies exploring ethical, emotional, competency-related, or technological aspects (including AI integration) within critical care nursing contexts. Full text articles published in English. Exclusion criteria encompassed non empirical works (e.g., editorials or letters), single case reports, and studies unrelated to ICU populations or nursing practice. Search Strategy A comprehensive literature search was conducted across PubMed, Scopus, CINAHL, and Web of Science databases using combinations of the following keywords: “end of life care,” “critical care nurses,” “ethical challenges,” “palliative care,” “artificial intelligence,” “digital ethics,” and “nursing education.” Additional searches of reference lists and grey literature were undertaken to ensure completeness and minimise publication bias. Articles meeting the relevance criteria were downloaded and screened by title, abstract, and full text. Screening and selection were performed independently by two reviewers, with discrepancies resolved through discussion and consensus. Data Extraction Procedure Data were extracted using a structured form that captured the following elements: author(s) and year of publication, country, study design, participants, main research focus, key findings, and identified ethical issues. A thematic analysis approach was applied to categorise findings into five overarching themes: Ethical and Professional Challenges, Knowledge and Skill Gaps,Emotional and Cultural Dimensions, and Systemic and Technological Constraints and Human– Artificial Intelligence Synergy in End of Life Nursing Care The synthesis process was conducted narratively by comparing contexts, designs, and outcomes across studies to identify common patterns and unique contributions. This analysis also integrated emerging perspectives on the role of AI and digital ethics in modern nursing practice. RESULT Study Characteristics Table 1. Study Characteristics No Author(s) (Year) Country Design Participants Main Focus 1 (Almahrizi et al., 2025) Oman Quantitative (Cross-sectional) 131 ICU nurses Knowledge and attitudes toward palliative care among critical care nurses 2 (Palmryd et al., 2025) Sweden Qualitative (Interpretive Descriptive) 20 Critical Care Nurses (CCNs) Ethical challenges faced by nurses in end of life care (EOLC) 3 Agius et al. (2025) France Retrospective Observational 270 cancer patients Intensity and economic burden of end of life chemotherapy 4 Aschale et al. (2025) Ethiopia Qualitative (Phenomenological) 12 ICU nurses Emotional experiences and coping strategies in providing EOLC 5 Xu et al. (2025) China Qualitative (Descriptive Phenomenological) 13 ICU nurses Cultural conflict and communication in end of life decision making 6 Mediani et al. (2024) Indonesia Qualitative (Phenomenological) 7 healthcare professionals (nurses and physicians) Experiences in providing palliative care in the ICU context 7 Martínez-Ortigosa et al. (2023) Spain Systematic Review (PRISMA-based) 21 studies, total 10–230,936 participants (mean 14,948) Applications of artificial intelligence in nursing practice (diagnosis, monitoring, education, and workflow efficiency) 8 Challen et al. (2019) United Kingdom, USA Narrative Review Theoretical and clinical AI applications (no specific participants) Analysis of algorithmic bias, safety, and clinical quality in AI based decision making systems Main Findings The synthesis of eight reviewed studies generated five overarching cross cutting themes that characterise the complexities of end of life care (EOLC) in intensive care settings and its intersection with technological advancement: Ethical and Professional Challenges Nurses frequently encounter moral dilemmas when balancing the prolongation of life with the preservation of patient dignity. Ethical tensions often arise from pressure to continue futile treatments, the use of palliative sedation, and conflicts with physicians or family members regarding treatment withdrawal decisions (Palmryd et al., 2025; Xu et al., 2025). These dilemmas underscore the need for institutional ethical support systems and reflective decision-making frameworks in critical care environments. Knowledge and Skill Gaps in Palliative Care A persistent deficit in knowledge concerning the philosophy and holistic principles of palliative care remains evident among critical care nurses. Gaps are particularly notable in addressing psychosocial and spiritual aspects of patient care (Almahrizi et al., 2025). Empirical evidence indicates that formal education and clinical exposure significantly enhance nurses’ competence and confidence in delivering EOLC. Emotional and Cultural Dimensions Emotional distress manifested as sadness, guilt, and burnout was common across all settings (Aschale et al., 2025). In collectivist Eastern contexts such as China and Indonesia, cultural values related to family obligation and religious norms strongly influence end of life decision making (Xu et al., 2025; Mediani et al., 2024). These findings highlight the necessity of culturally responsive and emotionally supportive interventions for ICU nurses. Systemic and Economic Constraints From a systemic perspective, aggressive medical interventions at the terminal stage, such as end of life chemotherapy, were found to elevate healthcare costs while diminishing patients’ quality of life (Agius et al., 2025). Additionally, organisational and policy limitations hinder the timely integration of palliative care practices in ICUs, particularly in low and middle income settings (Mediani et al., 2024). Human Artificial Intelligence Synergy in End of Life Nursing Care The integration of artificial intelligence (AI) into end of life nursing practice highlights the critical need to balance technological analytical capability with human emotional intelligence. While AI improves diagnostic precision and workflow efficiency, nurses remain central in ensuring ethical judgment, empathy, and patient safety (Martínez-Ortigosa et al., 2023; Challen et al., 2019). This synergy reinforces the imperative that technological innovation should augment rather than replace the moral and compassionate dimensions of nursing care. DISCUSSION End of life care (EOLC) in intensive care units (ICUs) represents one of the most complex challenges in modern healthcare, requiring a delicate balance between life sustaining technologies and respect for human dignity. Palmryd et al. (2025) emphasised that ICU nurses often face ethical dilemmas when aggressive treatments continue despite a poor prognosis, creating significant moral distress. This finding aligns with the systematic review by Henrich et al. (2022) in Intensive and Critical Care Nursing, which revealed that ICU nurses frequently experience moral distress when performing interventions perceived as futile or inconsistent with their professional values. Institutional support, such as ethics consultations and team reflections, has been shown to reduce moral conflict and strengthen moral resilience among healthcare professionals. Deficits in palliative care knowledge also emerged as a central issue across studies. Almahrizi et al. (2025) found that most ICU nurses in Oman demonstrated limited knowledge of palliative care principles, particularly regarding spiritual communication and the management of non physical symptoms. Similarly, Ma et al. (2023) in BMC Palliative Care reported that nurses’ competence in EOLC was strongly influenced by clinical experience, formal education, and exposure to terminal cases. A cross national study by Boucher et al. (2022) in palliative medicine confirmed that continuous education and interprofessional simulation training improve both clinical skills and empathy when caring for terminally ill patients. In Indonesia, Mediani et al. (2024) highlighted that the absence of hospital policies and structured training often leads healthcare workers to perceive palliative care merely as end stage management rather than a comprehensive approach that enhances quality of life throughout the disease trajectory. Beyond knowledge gaps, effective communication between healthcare providers and patients’ families emerged as a key determinant of dignified EOLC. Aschale et al. (2025) and Xu et al. (2025) found that open and empathetic communication not only facilitates family understanding but also reduces decisional conflict. Evidence from a randomised controlled trial by Curtis et al. (2016) in the American Journal of Respiratory and Critical Care Medicine demonstrated that structured communication interventions in ICUs significantly improved family satisfaction by 27% and alleviated post loss anxiety. Similarly, Anderson et al. (2019) in Palliative Medicine confirmed that value based communication training centred on empathy and shared decision making is an effective strategy to improve the quality of EOLC. Cultural context also plays a critical role in shaping end of life decisions. Xu et al. (2025) noted that in Chinese culture, the value of filial piety often compels families to continue all forms of medical treatment, even when the prognosis is poor. In contrast, Mediani et al. (2024) found that spiritual and religious beliefs strongly influence EOL decisions in Indonesia, highlighting the need for high levels of cultural and spiritual sensitivity among healthcare providers. Chan et al. (2021) in the Journal of Advanced Nursing further demonstrated that cultural competence significantly enhances patient and family satisfaction in multicultural ICU settings. A cultural humility approach defined as reflective awareness of patients’ beliefs and values proved to be more effective than rigid adherence to universal communication protocols. Psychologically, repeated exposure to death and dying places ICU nurses at high risk of chronic stress, emotional exhaustion, and burnout. Aschale et al. (2025) and Palmryd et al. (2025) underscored the importance of internal support mechanisms such as debriefing sessions, ethical reflection, and peer support to help nurses manage grief, guilt, and emotional fatigue. Brooks et al. (2017) in Australian Critical Care showed that post death reflective sessions reduce burnout and improve psychological resilience among ICU nurses. Organisationally, Schwarzkopf et al. (2024) in Healthcare emphasised the necessity for hospital policies that provide structured emotional and psychosocial support as part of quality and patient safety strategies. Roles Beyond Artificial Intelligence in EOLC Nursing The emergence of artificial intelligence (AI) in healthcare has begun to transform clinical practice in ICUs, particularly in mortality prediction, early detection of organ failure, and clinical decision support systems. However, amid these technological advancements, fundamental questions arise concerning the nurse’s role “beyond AI.” Recent literature highlights that the unique strength of nurses lies in their capacity to integrate empathy, ethical reasoning, and contextual judgment dimensions that cannot be replicated by algorithmic systems. Topol (2019) in Nature Medicine asserted that although AI can automate diagnostic and predictive functions, decisions involving meaning, values, and human suffering remain inherently within the ethical and emotional domain of human caregivers. In the ICU context, roles beyond AI encompass emotional presence, therapeutic communication with families, and moral advocacy in end of life decision making. Luo et al. (2024) in BMJ Health & Care Informatics reported that AI systems can assist in predicting terminal phases, yet without human interpretation, such recommendations risk dehumanised decision making. Here, the nurse’s role as a bridge between data and meaning becomes indispensable. Kim et al. (2023) in Nursing Philosophy further argued that AI integration in nursing practice must be guided by philosophical and ethical reflection to prevent the erosion of care’s humanistic dimension. Thus, roles beyond AI do not reject technological advancement; instead, they affirm the principle that AI should serve as an assistive rather than a substitutive tool supporting nurses’ moral, communicative, and spiritual competencies. Consequently, nursing education and institutional policy must prepare nurses to become empathetic data interpreters professionals capable of using AI generated insights ethically while upholding patient values, spirituality, and humane interaction. This aligns with the WHO Human Centred Digital Health Framework (2023), which emphasises placing humans at the core of health innovation. Therefore, EOLC in the digital era should not focus on AI replacing human roles but rather on how technology can extend nurses’ reflective, ethical, and compassionate capacities. These roles empathy, moral advocacy, and spiritual presence will remain the enduring essence of critical care nursing in the modern ICU. CONCLUSION This systematic review demonstrates that end of life care (EOLC) in intensive care units (ICUs) represents a multidimensional challenge encompassing ethical, emotional, educational, systemic, and technological factors. Nurses frequently experience moral distress when balancing life sustaining interventions with the preservation of patient dignity, often in contexts lacking institutional guidance and ethical clarity. Deficiencies in palliative and spiritual care competence further constrain the delivery of holistic and compassionate services. Emotional exhaustion and cultural influences continue to shape decision making in critical care, underscoring the need for human centred and context sensitive approaches. The integration of artificial intelligence (AI) introduces both opportunities and ethical complexities: although AI enhances efficiency and clinical precision, it raises concerns regarding bias, accountability, and the erosion of empathy. Hence, nurses’ roles must transcend technical adaptation to reaffirm their humanistic capacities ethical reflection, emotional presence, and moral advocacy. Future nursing education and policy should strengthen digital literacy, ethical sensitivity, and interprofessional collaboration to ensure that AI remains an assistive, rather than substitutive, tool. Ultimately, sustaining a synergy between technological innovation and human compassion is essential to uphold the ethical integrity and dignity of end of life nursing care. References Almahrizi, H. A., Alaloul, F., Al Mamari, O. K., Rani, E. K., Al Mahrizi, Z. A., Al Harthy, S. A., & Al-Naamani, Z. (2025). Empowering critical care nurses: Bridging knowledge gaps in palliative care. BMC Nursing, 24(1127). https://doi.org/10.1186/s12912-025-03699-1 Altaker, K. W., Howie-Esquivel, J., & Cataldo, J. K. (2018). Relationships among palliative care, ethical climate, empowerment, and moral distress in intensive care unit nurses. American Journal of Critical Care, 27 (4), 295–302. https://doi.org/10.4037/ajcc2018252 Aschale, A., Gishu, T., Mengist, S., & Tsehay, M. (2025). Experiences of intensive care unit nurses in providing end-of-life care in public hospitals: A phenomenological study. BMC Nursing, 24(1185). https://doi.org/10.1186/s12912-025-03849-5 Brooks, L. A., Manias, E., & Nicholson, P. (2017). Barriers, enablers, and challenges to implementing end-of-life care in critical care settings. Australian Critical Care, 30 (3), 161–165. https://doi.org/10.1016/j.aucc.2016.10.003 Chan, E. A., Wong, F., Cheung, K., & Lam, W. (2021). Cultural competence in end-of-life nursing care: A systematic review. Journal of Advanced Nursing, 77 (4), 1873–1885. https://doi.org/10.1111/jan.14748 Henrich, N. J., et al. (2022). Moral distress and ethical climate in critical care nursing: A systematic review. Intensive and Critical Care Nursing, 68 , 103136. https://doi.org/10.1016/j.iccn.2022.103136 Li, M., et al. (2023). Knowledge, attitudes, and practices of end-of-life care among ICU nurses: A cross-sectional survey. BMJ Supportive & Palliative Care, 13 (2), 230–238. https://doi.org/10.1136/bmjspcare-2021-003012 Mediani, H. S., Sada, F. R., Nuraeni, A., & Subu, M. A. (2024). Healthcare professionals’ experiences in providing palliative care in an intensive care unit in Indonesia: A phenomenological study. Journal of Multidisciplinary Healthcare, 17, 4427–4439. https://doi.org/10.2147/JMDH.S486021 Palmryd, L., Rejnö, Å., Alvariza, A., & Godskesen, T. (2025). Critical care nurses’ experiences of ethical challenges in end-of-life care. Nursing Ethics, 32(2), 424–436. https://doi.org/10.1177/09697330241252975 Xu, D.-D., Li, J., Ding, X.-B., Ma, J., Hou, R.-T., Chen, N.-N., Cheng, X.-L., & Hu, F. (2025). Experiences of providing end-of-life care in adult intensive care units: A qualitative study. BMC Nursing, 24(768). https://doi.org/10.1186/s12912-025-03340-1 Topol, E. J. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine , 25(1), 44-56. https://doi.org/10.1038/s41591-018-0300-7 Challen, R., Denny, J., Pitt, M., Gompels, L., Edwards, T., & Tsaneva-Atanasova, K. (2019). Artificial intelligence, bias and clinical safety. BMJ Quality & Safety , 28(3), 231-237. https://doi.org/10.1136/bmjqs-2018-008370 Martinez-Ortigosa, A. (2023). Applications of artificial intelligence in nursing care: A review. [Journal] , (note: full journal details to confirm) https://doi.org/10.1155/2023/3219127 Yang, Y. (2024). Influences of digital literacy and moral sensitivity on artificial intelligence ethics awareness among nursing students. Healthcare , 12(21), 2172. https://doi.org/10.3390/healthcare12212172 Additional Declarations The authors declare no competing interests. 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10:07:33","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":53387,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8029656/v1/1d32c02d4dd9c21434237244.html"},{"id":95190023,"identity":"cd867d80-4123-447a-82ff-0664bf5e5ecc","added_by":"auto","created_at":"2025-11-05 10:07:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36041,"visible":true,"origin":"","legend":"\u003cp\u003eThe identification, screening, and inclusion procedures of the studies were available in Scopus, Web of Science, PubMed, and CINAHL databases.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8029656/v1/030ffbdd990ccb7b152cc966.png"},{"id":95230580,"identity":"4119926d-b5b0-4dae-ad09-c621dcdba97f","added_by":"auto","created_at":"2025-11-05 16:38:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":646511,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8029656/v1/788961cf-b10c-4df1-b4d0-26bfde2f425e.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eNursing Caring for Terminal Patients in the ICU: A Systematic Literature Review on Humanistic Roles Beyond Artificial Intelligence\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eEnd of life care (EOLC) in the context of intensive nursing practice presents increasing ethical, emotional, and systemic complexities, particularly with the advancement of digital technology and the growing integration of artificial intelligence (AI) in healthcare. International studies affirm that nurses working in intensive care units (ICUs) frequently face moral dilemmas in balancing life-prolonging interventions with the preservation of patient dignity (Palmryd et al., 2025).These challenges are often intensified by family pressure, interprofessional conflict, and the absence of clear ethical guidelines. Moreover, significant gaps remain in nurses\u0026rsquo; understanding of palliative care philosophy and competence, as reported among ICU nurses in Oman and Indonesia ((Almahrizi et al., 2025); (Mediani et al., 2024).\u003c/p\u003e\u003cp\u003eEmotionally, ICU nurses experience moral fatigue, sadness, and guilt due to their recurrent exposure to death and dying (Aschale et al., 2025). Cultural factors also play a crucial role; in East and Southeast Asian settings, family values and religious beliefs profoundly influence medical decision making ((Xu et al., 2025). In addition, a study in France revealed that aggressive end of life interventions.\u003c/p\u003e\u003cp\u003eWith the progression of digitalisation, a new dimension has emerged in nursing practice, AI integration. (Martinez-Ortigosa et al., 2023)demonstrated that AI applications in nursing can enhance efficiency and service quality; however, they also raise ethical concerns related to algorithmic bias and the potential dehumanisation of care. (Challen et al., 2019) emphasised that AI should function as an \u003cem\u003eassistive tool\u003c/em\u003e within a human in the loop framework to preserve clinical safety and accountability. In nursing education, AI ethics awareness has become a vital competency for future practitioners. Yang (2024) found a strong correlation between digital literacy, moral sensitivity, and AI ethics awareness among nursing students.\u003c/p\u003e\u003cp\u003eTherefore, the challenges of end of life care now extend beyond traditional ethical and emotional issues to include how nursing professionals navigate the integration of intelligent technologies without compromising humanity, empathy, and professional responsibility.\u003c/p\u003e"},{"header":"METHODS","content":"\u003ch2\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study employed a \u003cstrong\u003eSystematic Literature Review (SLR)\u003c/strong\u003e design to identify, evaluate, and synthesise empirical research related to nurses’ experiences, ethical challenges, and the role of artificial intelligence (AI) in end of life care (EOLC) within intensive care units (ICUs). The review followed the \u003cstrong\u003ePRISMA 2020\u003c/strong\u003e guidelines to ensure methodological transparency, reproducibility, and rigour throughout the literature screening and synthesis process.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eInclusion and Exclusion Criteria\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria\u003c/strong\u003e included:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eEmpirical studies (qualitative, quantitative, or mixed methods) published in peer reviewed journals between 2019 and 2025.\u003c/li\u003e\n \u003cli\u003eResearch focusing on the experiences of nurses or healthcare professionals in providing EOLC in ICU settings.\u003c/li\u003e\n \u003cli\u003eStudies exploring ethical, emotional, competency-related, or technological aspects (including AI integration) within critical care nursing contexts.\u003c/li\u003e\n \u003cli\u003eFull text articles published in English.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria\u003c/strong\u003e encompassed non empirical works (e.g., editorials or letters), single case reports, and studies unrelated to ICU populations or nursing practice.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSearch Strategy\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA comprehensive literature search was conducted across \u003cstrong\u003ePubMed, Scopus, CINAHL, and Web of Science\u003c/strong\u003e databases using combinations of the following keywords:\u0026nbsp;\u003cem\u003e“end of life care,” “critical care nurses,” “ethical challenges,” “palliative care,” “artificial intelligence,” “digital ethics,”\u003c/em\u003e and\u0026nbsp;\u003cem\u003e“nursing education.”\u003c/em\u003e\u003cbr\u003e\u0026nbsp;Additional searches of reference lists and\u0026nbsp;\u003cem\u003egrey literature\u003c/em\u003e were undertaken to ensure completeness and minimise publication bias. Articles meeting the relevance criteria were downloaded and screened by title, abstract, and full text. Screening and selection were performed independently by two reviewers, with discrepancies resolved through discussion and consensus.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData Extraction Procedure\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eData were extracted using a structured form that captured the following elements: author(s) and year of publication, country, study design, participants, main research focus, key findings, and identified ethical issues.\u003cbr\u003eA\u0026nbsp;\u003cstrong\u003ethematic analysis\u003c/strong\u003e approach was applied to categorise findings into five overarching themes:\u003cbr\u003e\u0026nbsp;Ethical and Professional Challenges, Knowledge and Skill Gaps,Emotional and Cultural Dimensions, and\u003cbr\u003eSystemic and Technological Constraints and \u003cstrong\u003eHuman–\u003c/strong\u003eArtificial\u003cstrong\u003e\u0026nbsp;Intelligence Synergy in End of Life Nursing Care\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe synthesis process was conducted narratively by comparing contexts, designs, and outcomes across studies to identify common patterns and unique contributions. This analysis also integrated emerging perspectives on the role of AI and digital ethics in modern nursing practice.\u003c/p\u003e"},{"header":"RESULT","content":"\u003cp\u003eStudy Characteristics\u003c/p\u003e\n\u003cp\u003eTable 1. Study Characteristics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor(s) (Year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMain Focus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Almahrizi et al., 2025)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQuantitative (Cross-sectional)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e131 ICU nurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKnowledge and attitudes toward palliative care among critical care nurses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Palmryd et al., 2025)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQualitative (Interpretive Descriptive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20 Critical Care Nurses (CCNs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEthical challenges faced by nurses in end of life care (EOLC)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAgius et al. (2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFrance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRetrospective Observational\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e270 cancer patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntensity and economic burden of end of life chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAschale et al. (2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEthiopia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQualitative (Phenomenological)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12 ICU nurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEmotional experiences and coping strategies in providing EOLC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eXu et al. (2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQualitative (Descriptive Phenomenological)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13 ICU nurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCultural conflict and communication in end of life decision making\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMediani et al. (2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndonesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQualitative (Phenomenological)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 healthcare professionals (nurses and physicians)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eExperiences in providing palliative care in the ICU context\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMart\u0026iacute;nez-Ortigosa et al. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSystematic Review (PRISMA-based)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21 studies, total 10\u0026ndash;230,936 participants (mean 14,948)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eApplications of artificial intelligence in nursing practice (diagnosis, monitoring, education, and workflow efficiency)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChallen et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnited Kingdom, USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNarrative Review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTheoretical and clinical AI applications (no specific participants)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAnalysis of algorithmic bias, safety, and clinical quality in AI based decision making systems\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eMain Findings\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe synthesis of eight reviewed studies generated five overarching cross cutting themes that characterise the complexities of\u0026nbsp;end of life care (EOLC) in intensive care settings and its intersection with technological advancement:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eEthical and Professional Challenges\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eNurses frequently encounter moral dilemmas when balancing the prolongation of life with the preservation of patient dignity. Ethical tensions often arise from pressure to continue futile treatments, the use of palliative sedation, and conflicts with physicians or family members regarding treatment withdrawal decisions (Palmryd et al., 2025; Xu et al., 2025). These dilemmas underscore the need for institutional ethical support systems and reflective decision-making frameworks in critical care environments.\u003c/p\u003e\n\u003col start=\"2\"\u003e\n \u003cli\u003e\u003cstrong\u003eKnowledge and Skill Gaps in Palliative Care\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eA persistent deficit in knowledge concerning the philosophy and holistic principles of palliative care remains evident among critical care nurses. Gaps are particularly notable in addressing psychosocial and spiritual aspects of patient care (Almahrizi et al., 2025). Empirical evidence indicates that formal education and clinical exposure significantly enhance nurses\u0026rsquo; competence and confidence in delivering EOLC.\u003c/p\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003e\u003cstrong\u003eEmotional and Cultural Dimensions\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eEmotional distress manifested as sadness, guilt, and burnout was common across all settings (Aschale et al., 2025). In collectivist Eastern contexts such as China and Indonesia, cultural values related to family obligation and religious norms strongly influence\u0026nbsp;end of life decision making (Xu et al., 2025; Mediani et al., 2024). These findings highlight the necessity of culturally responsive and emotionally supportive interventions for ICU nurses.\u003c/p\u003e\n\u003col start=\"4\"\u003e\n \u003cli\u003e\u003cstrong\u003eSystemic and Economic Constraints\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFrom a systemic perspective, aggressive medical interventions at the terminal stage, such as\u0026nbsp;end of life chemotherapy, were found to elevate healthcare costs while diminishing patients\u0026rsquo; quality of life (Agius et al., 2025). Additionally, organisational and policy limitations hinder the timely integration of palliative care practices in ICUs, particularly in low and middle income settings (Mediani et al., 2024).\u003c/p\u003e\n\u003col start=\"5\"\u003e\n \u003cli\u003e\u003cstrong\u003eHuman Artificial Intelligence Synergy in End of Life Nursing Care\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe integration of artificial intelligence (AI) into end of life nursing practice highlights the critical need to balance technological analytical capability with human emotional intelligence. While AI improves diagnostic precision and workflow efficiency, nurses remain central in ensuring ethical judgment, empathy, and patient safety (Mart\u0026iacute;nez-Ortigosa et al., 2023; Challen et al., 2019). This synergy reinforces the imperative that technological innovation should augment rather than replace the moral and compassionate dimensions of nursing care.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eEnd of life care (EOLC) in intensive care units (ICUs) represents one of the most complex challenges in modern healthcare, requiring a delicate balance between life sustaining technologies and respect for human dignity. Palmryd et al. (2025) emphasised that ICU nurses often face ethical dilemmas when aggressive treatments continue despite a poor prognosis, creating significant moral distress. This finding aligns with the systematic review by Henrich et al. (2022) in Intensive and Critical Care Nursing, which revealed that ICU nurses frequently experience moral distress when performing interventions perceived as futile or inconsistent with their professional values. Institutional support, such as ethics consultations and team reflections, has been shown to reduce moral conflict and strengthen moral resilience among healthcare professionals.\u003c/p\u003e\u003cp\u003eDeficits in palliative care knowledge also emerged as a central issue across studies. Almahrizi et al. (2025) found that most ICU nurses in Oman demonstrated limited knowledge of palliative care principles, particularly regarding spiritual communication and the management of non physical symptoms. Similarly, Ma et al. (2023) in \u003cem\u003eBMC Palliative Care\u003c/em\u003e reported that nurses\u0026rsquo; competence in EOLC was strongly influenced by clinical experience, formal education, and exposure to terminal cases. A cross national study by Boucher et al. (2022) in palliative medicine confirmed that continuous education and interprofessional simulation training improve both clinical skills and empathy when caring for terminally ill patients. In Indonesia, Mediani et al. (2024) highlighted that the absence of hospital policies and structured training often leads healthcare workers to perceive palliative care merely as end stage management rather than a comprehensive approach that enhances quality of life throughout the disease trajectory.\u003c/p\u003e\u003cp\u003eBeyond knowledge gaps, effective communication between healthcare providers and patients\u0026rsquo; families emerged as a key determinant of dignified EOLC. Aschale et al. (2025) and Xu et al. (2025) found that open and empathetic communication not only facilitates family understanding but also reduces decisional conflict. Evidence from a randomised controlled trial by Curtis et al. (2016) in the American Journal of Respiratory and Critical Care Medicine demonstrated that structured communication interventions in ICUs significantly improved family satisfaction by 27% and alleviated post loss anxiety. Similarly, Anderson et al. (2019) in \u003cem\u003ePalliative Medicine\u003c/em\u003e confirmed that value based communication training centred on empathy and shared decision making is an effective strategy to improve the quality of EOLC.\u003c/p\u003e\u003cp\u003eCultural context also plays a critical role in shaping end of life decisions. Xu et al. (2025) noted that in Chinese culture, the value of \u003cem\u003efilial piety\u003c/em\u003e often compels families to continue all forms of medical treatment, even when the prognosis is poor. In contrast, Mediani et al. (2024) found that spiritual and religious beliefs strongly influence EOL decisions in Indonesia, highlighting the need for high levels of cultural and spiritual sensitivity among healthcare providers. Chan et al. (2021) in the \u003cem\u003eJournal of Advanced Nursing\u003c/em\u003e further demonstrated that cultural competence significantly enhances patient and family satisfaction in multicultural ICU settings. A \u003cem\u003ecultural humility\u003c/em\u003e approach defined as reflective awareness of patients\u0026rsquo; beliefs and values proved to be more effective than rigid adherence to universal communication protocols.\u003c/p\u003e\u003cp\u003ePsychologically, repeated exposure to death and dying places ICU nurses at high risk of chronic stress, emotional exhaustion, and burnout. Aschale et al. (2025) and Palmryd et al. (2025) underscored the importance of internal support mechanisms such as debriefing sessions, ethical reflection, and peer support to help nurses manage grief, guilt, and emotional fatigue. Brooks et al. (2017) in \u003cem\u003eAustralian Critical Care\u003c/em\u003e showed that post death reflective sessions reduce burnout and improve psychological resilience among ICU nurses. Organisationally, Schwarzkopf et al. (2024) in \u003cem\u003eHealthcare\u003c/em\u003e emphasised the necessity for hospital policies that provide structured emotional and psychosocial support as part of quality and patient safety strategies.\u003c/p\u003e\u003cp\u003eRoles Beyond Artificial Intelligence in EOLC Nursing\u003c/p\u003e\u003cp\u003eThe emergence of artificial intelligence (AI) in healthcare has begun to transform clinical practice in ICUs, particularly in mortality prediction, early detection of organ failure, and clinical decision support systems. However, amid these technological advancements, fundamental questions arise concerning the nurse\u0026rsquo;s role \u0026ldquo;beyond AI.\u0026rdquo; Recent literature highlights that the unique strength of nurses lies in their capacity to integrate empathy, ethical reasoning, and contextual judgment dimensions that cannot be replicated by algorithmic systems. Topol (2019) in \u003cem\u003eNature Medicine\u003c/em\u003e asserted that although AI can automate diagnostic and predictive functions, decisions involving meaning, values, and human suffering remain inherently within the ethical and emotional domain of human caregivers. In the ICU context, roles beyond AI encompass emotional presence, therapeutic communication with families, and moral advocacy in end of life decision making.\u003c/p\u003e\u003cp\u003eLuo et al. (2024) in \u003cem\u003eBMJ Health \u0026amp; Care Informatics\u003c/em\u003e reported that AI systems can assist in predicting terminal phases, yet without human interpretation, such recommendations risk dehumanised decision making. Here, the nurse\u0026rsquo;s role as a bridge between data and meaning becomes indispensable. Kim et al. (2023) in \u003cem\u003eNursing Philosophy\u003c/em\u003e further argued that AI integration in nursing practice must be guided by philosophical and ethical reflection to prevent the erosion of care\u0026rsquo;s humanistic dimension. Thus, roles beyond AI do not reject technological advancement; instead, they affirm the principle that AI should serve as an \u003cem\u003eassistive\u003c/em\u003e rather than a \u003cem\u003esubstitutive\u003c/em\u003e tool supporting nurses\u0026rsquo; moral, communicative, and spiritual competencies.\u003c/p\u003e\u003cp\u003eConsequently, nursing education and institutional policy must prepare nurses to become \u003cem\u003eempathetic data interpreters\u003c/em\u003e professionals capable of using AI generated insights ethically while upholding patient values, spirituality, and humane interaction. This aligns with the WHO Human Centred Digital Health Framework (2023), which emphasises placing humans at the core of health innovation. Therefore, EOLC in the digital era should not focus on AI replacing human roles but rather on how technology can extend nurses\u0026rsquo; reflective, ethical, and compassionate capacities. These roles empathy, moral advocacy, and spiritual presence will remain the enduring essence of critical care nursing in the modern ICU.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis systematic review demonstrates that end of life care (EOLC) in intensive care units (ICUs) represents a multidimensional challenge encompassing ethical, emotional, educational, systemic, and technological factors. Nurses frequently experience moral distress when balancing life sustaining interventions with the preservation of patient dignity, often in contexts lacking institutional guidance and ethical clarity. Deficiencies in palliative and spiritual care competence further constrain the delivery of holistic and compassionate services. Emotional exhaustion and cultural influences continue to shape decision making in critical care, underscoring the need for human centred and context sensitive approaches. The integration of artificial intelligence (AI) introduces both opportunities and ethical complexities: although AI enhances efficiency and clinical precision, it raises concerns regarding bias, accountability, and the erosion of empathy. Hence, nurses’ roles must transcend technical adaptation to reaffirm their humanistic capacities ethical reflection, emotional presence, and moral advocacy. Future nursing education and policy should strengthen digital literacy, ethical sensitivity, and interprofessional collaboration to ensure that AI remains an assistive, rather than substitutive, tool. Ultimately, sustaining a synergy between technological innovation and human compassion is essential to uphold the ethical integrity and dignity of end of life nursing care.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlmahrizi, H. A., Alaloul, F., Al Mamari, O. K., Rani, E. K., Al Mahrizi, Z. A., Al Harthy, S. A., \u0026amp; Al-Naamani, Z. (2025). \u003cem\u003eEmpowering critical care nurses: Bridging knowledge gaps in palliative care.\u003c/em\u003e BMC Nursing, 24(1127). https://doi.org/10.1186/s12912-025-03699-1\u003c/li\u003e\n\u003cli\u003eAltaker, K. W., Howie-Esquivel, J., \u0026amp; Cataldo, J. K. (2018). Relationships among palliative care, ethical climate, empowerment, and moral distress in intensive care unit nurses. \u003cem\u003eAmerican Journal of Critical Care, 27\u003c/em\u003e(4), 295\u0026ndash;302. https://doi.org/10.4037/ajcc2018252\u003c/li\u003e\n\u003cli\u003eAschale, A., Gishu, T., Mengist, S., \u0026amp; Tsehay, M. (2025). \u003cem\u003eExperiences of intensive care unit nurses in providing end-of-life care in public hospitals: A phenomenological study.\u003c/em\u003e BMC Nursing, 24(1185). https://doi.org/10.1186/s12912-025-03849-5\u003c/li\u003e\n\u003cli\u003eBrooks, L. A., Manias, E., \u0026amp; Nicholson, P. (2017). Barriers, enablers, and challenges to implementing end-of-life care in critical care settings. \u003cem\u003eAustralian Critical Care, 30\u003c/em\u003e(3), 161\u0026ndash;165. https://doi.org/10.1016/j.aucc.2016.10.003\u003c/li\u003e\n\u003cli\u003eChan, E. A., Wong, F., Cheung, K., \u0026amp; Lam, W. (2021). Cultural competence in end-of-life nursing care: A systematic review. \u003cem\u003eJournal of Advanced Nursing, 77\u003c/em\u003e(4), 1873\u0026ndash;1885. https://doi.org/10.1111/jan.14748\u003c/li\u003e\n\u003cli\u003eHenrich, N. J., et al. (2022). Moral distress and ethical climate in critical care nursing: A systematic review. \u003cem\u003eIntensive and Critical Care Nursing, 68\u003c/em\u003e, 103136. https://doi.org/10.1016/j.iccn.2022.103136\u003c/li\u003e\n\u003cli\u003eLi, M., et al. (2023). Knowledge, attitudes, and practices of end-of-life care among ICU nurses: A cross-sectional survey. \u003cem\u003eBMJ Supportive \u0026amp; Palliative Care, 13\u003c/em\u003e(2), 230\u0026ndash;238. https://doi.org/10.1136/bmjspcare-2021-003012\u003c/li\u003e\n\u003cli\u003eMediani, H. S., Sada, F. R., Nuraeni, A., \u0026amp; Subu, M. A. (2024). \u003cem\u003eHealthcare professionals\u0026rsquo; experiences in providing palliative care in an intensive care unit in Indonesia: A phenomenological study.\u003c/em\u003e Journal of Multidisciplinary Healthcare, 17, 4427\u0026ndash;4439. https://doi.org/10.2147/JMDH.S486021\u003c/li\u003e\n\u003cli\u003ePalmryd, L., Rejn\u0026ouml;, \u0026Aring;., Alvariza, A., \u0026amp; Godskesen, T. (2025). \u003cem\u003eCritical care nurses\u0026rsquo; experiences of ethical challenges in end-of-life care.\u003c/em\u003e Nursing Ethics, 32(2), 424\u0026ndash;436. https://doi.org/10.1177/09697330241252975\u003c/li\u003e\n\u003cli\u003eXu, D.-D., Li, J., Ding, X.-B., Ma, J., Hou, R.-T., Chen, N.-N., Cheng, X.-L., \u0026amp; Hu, F. (2025). \u003cem\u003eExperiences of providing end-of-life care in adult intensive care units: A qualitative study.\u003c/em\u003e BMC Nursing, 24(768). https://doi.org/10.1186/s12912-025-03340-1\u003c/li\u003e\n\u003cli\u003eTopol, E. J. (2019). \u003cem\u003eHigh-performance medicine: The convergence of human and artificial intelligence.\u003c/em\u003e \u003cstrong\u003eNature Medicine\u003c/strong\u003e, 25(1), 44-56. https://doi.org/10.1038/s41591-018-0300-7\u003c/li\u003e\n\u003cli\u003eChallen, R., Denny, J., Pitt, M., Gompels, L., Edwards, T., \u0026amp; Tsaneva-Atanasova, K. (2019). \u003cem\u003eArtificial intelligence, bias and clinical safety.\u003c/em\u003e \u003cstrong\u003eBMJ Quality \u0026amp; Safety\u003c/strong\u003e, 28(3), 231-237. https://doi.org/10.1136/bmjqs-2018-008370\u003c/li\u003e\n\u003cli\u003eMartinez-Ortigosa, A. (2023). \u003cem\u003eApplications of artificial intelligence in nursing care: A review.\u003c/em\u003e \u003cstrong\u003e[Journal]\u003c/strong\u003e, \u003cem\u003e(note: full journal details to confirm)\u003c/em\u003e https://doi.org/10.1155/2023/3219127\u003c/li\u003e\n\u003cli\u003eYang, Y. (2024). \u003cem\u003eInfluences of digital literacy and moral sensitivity on artificial intelligence ethics awareness among nursing students.\u003c/em\u003e \u003cstrong\u003eHealthcare\u003c/strong\u003e\u003cstrong\u003e,\u003c/strong\u003e 12(21), 2172. https://doi.org/10.3390/healthcare12212172\u003c/li\u003e\n\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":"End of life care, Critical care nursing, Artificial intelligence, Ethics, Empathy, Humanistic nursing, Digital transformation","lastPublishedDoi":"10.21203/rs.3.rs-8029656/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8029656/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEnd of life care (EOLC) in intensive care units (ICUs) involves complex ethical, emotional, and systemic challenges that are increasingly influenced by the integration of artificial intelligence (AI) in healthcare. Nurses often experience moral distress when balancing life sustaining interventions and patient dignity while adapting to technological systems that affect empathy, accountability, and clinical judgment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eObjective:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study aims to synthesize empirical evidence on nurses\u0026rsquo; experiences, ethical dilemmas, and evolving roles in providing EOLC within the digital era, emphasizing the humanistic aspects that extend beyond AI applications.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA systematic literature review was conducted following the PRISMA 2020 guidelines. Searches were performed in PubMed, Scopus, and CINAHL databases for peer reviewed articles published between 2019 and 2025. Nine eligible studies were analyzed thematically, covering ethical, emotional, cultural, systemic, and technological dimensions of EOLC nursing.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNurses reported moral distress, limited palliative care competence, emotional fatigue, and inadequate institutional support. While AI enhanced efficiency and decision accuracy, concerns persisted about algorithmic bias, data transparency, and dehumanization of care. The findings highlight the irreplaceable human role of nurses in providing empathy, moral reasoning, and spiritual presence within AI supported environments.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEffective EOLC in the AI era requires synergy between technological precision and compassionate nursing. Sustaining human centered values remains essential to ensure ethical integrity, emotional resilience, and dignified patient care.\u003c/p\u003e","manuscriptTitle":"Nursing Caring for Terminal Patients in the ICU: A Systematic Literature Review on Humanistic Roles Beyond Artificial Intelligence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-05 10:07:28","doi":"10.21203/rs.3.rs-8029656/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":"e7df87f0-a3d4-4107-9245-f9794be0b716","owner":[],"postedDate":"November 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57421971,"name":"Nursing"},{"id":57421972,"name":"Critical Care \u0026 Emergency Medicine"}],"tags":[],"updatedAt":"2025-11-05T10:07:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-05 10:07:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8029656","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8029656","identity":"rs-8029656","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}