Artificial intelligence in nursing: a systematic review of attitudes, literacy, readiness, and adoption intentions among nursing students and practicing nurses
Open accessAbstract
Background: Artificial intelligence (AI) could reshape healthcare delivery, but its adoption depends on nurses' attitudes, literacy, readiness, and intentions. Methods: Following PRISMA 2020, we searched six databases from inception to May 2025 and undertook thematic synthesis. A non-systematic horizon scan (June–August 2025) informed interpretation only. Results: Thirty-seven studies met inclusion: 28 analytical cross-sectional surveys, 8 qualitative studies, and 1 quasi-experimental trial. Nursing students generally held moderately positive attitudes towards AI; senior students were more enthusiastic than juniors, and men more than women. Students reported moderate literacy and readiness; prior AI training and stronger computer skills correlated with more favourable attitudes and greater adoption intentions, whereas anxiety dampened readiness. Many students doubted AI's ability to outperform humans in routine tasks and flagged integrity risks, underscoring the need for age-appropriate instruction and safeguards. Practising nurses expressed moderate safety and error concerns but showed greater optimism among younger staff; across studies, nurses consistently argued AI should augment—not replace—human empathy and judgement. Targeted training substantially improved, and largely maintained, AI knowledge; leadership endorsement and phased, user-centred roll-outs strengthened readiness, while outdated infrastructure, resource constraints, ethical/privacy concerns, and fear of deskilling impeded progress. Determinants of attitudes and intentions clustered around perceived usefulness/performance and effort expectancy, self-efficacy, digital literacy, and facilitating conditions. The horizon scan added signals of a preparedness–impact gap among nurse leaders, syllabus/policy language as a faculty readiness multiplier, role-specific adoption gaps (e.g., lower use among head nurses despite positive attitudes), and coexistence of high AI anxiety with positive attitudes in students. Conclusion: Global nursing exhibits guarded optimism grounded in moderate literacy and readiness yet constrained by infrastructural, ethical, and pedagogical barriers. Adoption is driven by perceived usefulness, self-efficacy, and enabling environments, with anxiety and demographics moderating engagement. Priorities include embedding longitudinal AI competencies in curricula, iterative hands-on training, robust governance/ethics, and modernised infrastructure. Evidence dominated by cross-sectional designs and a narrow set of countries should be strengthened through longitudinal and experimental studies that validate psychometrics cross-culturally and link self-reports to objective use and patient-safety outcomes.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
AI adoption is influenced by perceived usefulness, self-efficacy, infrastructure, and leadership support.
“AI adoption is influenced by perceived usefulness, self-efficacy, infrastructure, and leadership support [2,3].”
Nursing learners generally report more favorable responses when AI tools are clearly relevant to clinical practice and introduced with appropriate guidance and support.
“Nursing learners generally report more favorable responses when AI tools are clearly relevant to clinical practice and introduced with appropriate guidance and support [2,10,23].”
Nursing students and practicing nurses often report moderate levels of AI readiness.
“nursing students and practicing nurses often report moderate levels of AI readiness”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035 · see citing works
Rayyan-a web and mobile app for systematic reviews.
Ouzzani, M., Hammady, H., Fedorowicz, Z., & Elmagarmid, A. (2016) · Systematic Reviews · doi:10.1186/s13643-016-0384-4 · Cited by 26,092 · cited 1× · see citing works
“All records were uploaded into Rayyan for de-duplication (27).”
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions
Sterne, J. A., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., Henry, D., Altman, D. G., Ansari, M. T., Boutron, I., et al. (2016) · BMJ · doi:10.1136/bmj.i4919 · Cited by 20,329 · see citing works
Methods for the thematic synthesis of qualitative research in systematic reviews
Thomas, J., & Harden, A. (2008) · BMC Medical Research Methodology · doi:10.1186/1471-2288-8-45 · Cited by 9,312 · see citing works
Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., & Moher, D. (2021) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2021.02.003 · Cited by 3,490 · see citing works
Methley, A. M., Campbell, S., Chew-Graham, C., McNally, R., & Cheraghi-Sohi, S. (2014) · BMC Health Services Research · doi:10.1186/s12913-014-0579-0 · Cited by 2,706 · see citing works
JBI Manual for Evidence Synthesis
(2024) · doi:10.46658/jbimes-24-01 · Cited by 2,483 · see citing works
Lockwood, C., Munn, Z., & Porritt, K. (2015) · International Journal of Evidence-Based Healthcare · doi:10.1097/xeb.0000000000000062 · Cited by 2,456 · see citing works
Qualitative Data Analysis with ATLAS.ti
Friese, S. (2012) · doi:10.4135/9781529799590 · Cited by 1,093 · see citing works
Ethical and regulatory challenges of AI technologies in healthcare: A narrative review
Mennella, C., Maniscalco, U., De Pietro, G., & Esposito, M. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26297 · Cited by 1,083 · see citing works
The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century
Varnosfaderani, S. M., & Forouzanfar, M. (2024) · Bioengineering · doi:10.3390/bioengineering11040337 · Cited by 1,069 · see citing works
Barker, T. H., Habibi, N., Aromataris, E., Stone, J. C., Leonardi-Bee, J., Sears, K., Hasanoff, S., Klugar, M., Tufanaru, C., Moola, S., et al. (2024) · JBI Evidence Synthesis · doi:10.11124/jbies-23-00268 · Cited by 843 · see citing works
Barriers to and facilitators of artificial intelligence adoption in health care: scoping review
Hassan, M., Kushniruk, A., & Borycki, E. (2024) · JMIR Human Factors · doi:10.2196/48633 · Cited by 324 · see citing works
Barker, T. H., Hasanoff, S., Aromataris, E., Stone, J., Leonardi‐Bee, J., Sears, K., Klugar, M., Tufănaru, C., Moola, S., Liu, X., et al. (2025) · JBI Evidence Synthesis · doi:10.11124/jbies-24-00523 · Cited by 300 · see citing works
Faiyazuddin, M., Rahman, S. J. Q., Anand, G., Siddiqui, R. K., Mehta, R., Khatib, M. N., Gaidhane, S., Zahiruddin, Q. S., Hussain, A., & Sah, R. (2025) · Health Science Reports · doi:10.1002/hsr2.70312 · Cited by 299 · see citing works
Kwak, Y., Ahn, J.-W., & Seo, Y. H. (2022) · BMC Nursing · doi:10.1186/s12912-022-01048-0 · Cited by 291 · see citing works
Artificial intelligence for low income countries
Khan, M. S., Umer, H., & Faruqe, F. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03947-w · Cited by 210 · see citing works
Zuhair, V., Babar, A., Ali, R., Oduoye, M. O., Noor, Z., Chris, K., Okon, I. I., & Rehman, L. U. (2024) · Journal of Primary Care & Community Health · doi:10.1177/21501319241245847 · Cited by 197 · see citing works
Labrague, L. J., Aguilar-Rosales, R., Yboa, B. C., Sabio, J. B., & de los Santos, J. A. (2023) · Nurse Education in Practice · doi:10.1016/j.nepr.2023.103815 · Cited by 196 · see citing works
Rony, M. K. K., Kayesh, I., Bala, S. D., Akter, F., & Parvin, M. R. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e25718 · Cited by 190 · see citing works
Abou Hashish, E. A., & Alnajjar, H. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05482-3 · Cited by 185 · see citing works
Systematic reviews of qualitative evidence
Lockwood, C., Porritt, K., Munn, Z., Rittenmeyer, L., Salmond, S., Bjerrum, M., Loveday, H., Carrier, J., & Stannard, D. (2024) · JBI Manual for Evidence Synthesis · doi:10.46658/jbimes-24-02 · Cited by 165 · see citing works
Kwak, Y., Seo, Y. H., & Ahn, J. (2022) · Nurse Education Today · doi:10.1016/j.nedt.2022.105541 · Cited by 162 · see citing works
The Role of AI in Nursing Education and Practice: Umbrella Review
El Arab, R. A., Al Moosa, O. A., Abuadas, F. H., & Somerville, J. (2025) · Journal of Medical Internet Research · doi:10.2196/69881 · Cited by 160 · see citing works
Systematic review of cost effectiveness and budget impact of artificial intelligence in healthcare
El Arab, R. A., & Al Moosa, O. A. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01722-y · Cited by 149 · see citing works
Ramadan, O. M. E., Alruwaili, M. M., Alruwaili, A. N., Elsehrawy, M. G., & Alanazi, S. (2024) · BMC Nursing · doi:10.1186/s12912-024-02571-y · Cited by 139 · see citing works
Cho, K. A., & Seo, Y. H. (2024) · BMC Nursing · doi:10.1186/s12912-024-01887-z · Cited by 137 · see citing works
Artificial intelligence in nursing: an integrative review of clinical and operational impacts
Hassanein, S., El Arab, R. A., Abdrbo, A., Abu-Mahfouz, M. S., Gaballah, M. K. F., Seweid, M. M., Almari, M., & Alzghoul, H. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1552372 · Cited by 134 · see citing works
Self-citationEl-Sayed, B. K. M., El‐Sayed, A. A. I., Alsenany, S. A., & Asal, M. G. R. (2024) · Nurse Education in Practice · doi:10.1016/j.nepr.2024.104208 · Cited by 131 · see citing works
Lukić, A., Kudelić, N., Antičević, V., Mosler, E. L., Gluncić, V., Hren, D., & Lukić, I. K. (2023) · Nurse Education in Practice · doi:10.1016/j.nepr.2023.103735 · Cited by 129 · see citing works
Ratti, E., Morrison, M. C., & Jakab, I. (2025) · BMC Medical Ethics · doi:10.1186/s12910-025-01198-1 · Cited by 120 · see citing works
Arab, R. A. E., Moosa, O. A. A., Sagbakken, M., Ghannam, A., Abuadas, F. H. A., Somerville, J. G., & Mutair, A. S. A. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1619378 · Cited by 119 · see citing works
Self-citationAlruwaili, M. M., Abuadas, F. H., Alsadi, M., Alruwaili, A. N., Elsayed Ramadan, O. M., Shaban, M., Al Thobaity, A., Alkahtani, S. M., & El Arab, R. A. (2024) · DIGITAL HEALTH · doi:10.1177/20552076241271803 · Cited by 114 · see citing works
El Arab, R. A., Abu-Mahfouz, M. S., Abuadas, F. H., Alzghoul, H., Almari, M., Ghannam, A., & Seweid, M. M. (2025) · Healthcare · doi:10.3390/healthcare13070701 · Cited by 108 · see citing works
Rony, M. K. K., Numan, S. M., Akter, K., Tushar, H., Debnath, M., Johra, F. T., Akter, F., Mondal, S., Das, M., Uddin, M. J., et al. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e36702 · Cited by 93 · see citing works
Omari, O. A., Alshammari, M., Jabri, W. A., Yahyaei, A. A., Aljohani, K. A., Sanad, H. M., Al‐Jubouri, M. B., Bashayreh, I., Fawaz, M. A., ALBashtawy, M., et al. (2024) · BMC Medical Education · doi:10.1186/s12909-024-06452-5 · Cited by 84 · see citing works
Artificial intelligence in vaccine research and development: an umbrella review
Arab, R. A. E., Alkhunaizi, M., Alhashem, Y. N., Khatib, A. A., Bubsheet, M., & Hassanein, S. E. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1567116 · Cited by 81 · see citing works
Self-citationThe Nursing Human Capital Value Model
Yakusheva, O., Lee, K. A., & Weiss, M. (2024) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2024.104890 · Cited by 77 · see citing works
Almagharbeh, W. T., Alfanash, H. A., Alnawafleh, K. A., Alasmari, A. A., Alsaraireh, F. A., Dreidi, M. M., & Nashwan, A. J. (2025) · BMC Nursing · doi:10.1186/s12912-024-02658-6 · Cited by 74 · see citing works
Atalla, A. D. G., El‐Ashry, A. M., & Mohamed, S. M. S. (2024) · BMC Nursing · doi:10.1186/s12912-024-02143-0 · Cited by 72 · see citing works
Nursing students' attitudes and literacy toward artificial intelligence: a cross-sectional study
Sümengen, A. A., Subaşı, D. Ö., & Çakır, G. N. (2024) · Teaching and learning in nursing · doi:10.1016/j.teln.2024.10.022 · Cited by 71 · see citing works
Summers, A., Haddad, M. E., Prichard, R., Clarke, K.-A., Lee, J., & Oprescu, F. (2024) · Nurse Education in Practice · doi:10.1016/j.nepr.2024.104062 · Cited by 67 · see citing works
Artificial intelligence in hospital infection prevention: an integrative review
Arab, R. A. E., Almoosa, Z., Alkhunaizi, M., Abuadas, F. H. A., & Somerville, J. G. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1547450 · Cited by 67 · see citing works
Santamato, V., Tricase, C., Faccilongo, N., Iacoviello, M., & Marengo, A. (2024) · Applied Sciences · doi:10.3390/app142210144 · Cited by 67 · see citing works
Kaymak, Z. D., Turan, Z., Bıdık, N. Ü., & Ünkazan, S. (2024) · Nurse Education in Practice · doi:10.1016/j.nepr.2024.103994 · Cited by 66 · see citing works
Rony, M. K. K., Numan, S. M., Johra, F. T., Akter, K., Akter, F., Debnath, M., Mondal, S., Wahiduzzaman, M., Das, M., Ullah, M., et al. (2024) · Health Science Reports · doi:10.1002/hsr2.70006 · Cited by 64 · see citing works
Atalla, A. D. G., El-Gawad Mousa, M. A., Hashish, E. A. A., Elseesy, N. A. M., Abd El kader Mohamed, A. I., & Sobhi Mohamed, S. M. (2025) · BMC Nursing · doi:10.1186/s12912-025-03306-3 · Cited by 58 · see citing works
Arab, R. A. E., Moosa, O. A. A., & Sagbakken, M. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1617138 · Cited by 58 · see citing works
Self-citationYalcinkaya, T., Ergin, E., & Yucel, S. C. (2024) · Teaching and Learning in Nursing · doi:10.1016/j.teln.2024.07.008 · Cited by 57 · see citing works
Kotp, M. H., Ismail, H. A., Basyouny, H. A. A., Aly, M. A., Hendy, A. S., Nashwan, A. J., Hendy, A., & Elmoaty, A. E. E. A. (2025) · BMC Nursing · doi:10.1186/s12912-024-02653-x · Cited by 56 · see citing works
Ayed, A., Ejheisheh, M. A., Al-Amer, R. M., Aqtam, I. F., Ali, A. M., Othman, E. H., Farajallah, M., Qaddumi, J. A. S., & Batran, A. (2025) · BMC Nursing · doi:10.1186/s12912-025-03490-2 · Cited by 54 · see citing works
Alruwaili, A. N., Alshammari, A. M., Alhaiti, A., Elsharkawy, N. B., Ali, S. I., & Ramadan, O. M. E. (2025) · BMC Nursing · doi:10.1186/s12912-025-03044-6 · Cited by 54 · see citing works
Tuncer, G. Z., & Tuncer, M. (2024) · Digital Health · doi:10.1177/20552076241277025 · Cited by 51 · see citing works
O’Hara, S., Ackerman, M., Raderstorf, T., Kilbridge, J. F., & Melnyk, B. M. (2022) · Journal of Professional Nursing · doi:10.1016/j.profnurs.2022.08.001 · Cited by 50 · see citing works
Artificial Intelligence Literacy Levels of Perioperative Nurses: The Case of Türkiye
Kahraman, H., Akutay, S., Kaçmaz, H. Y., & Taşçı, S. (2025) · Nursing and Health Sciences · doi:10.1111/nhs.70059 · Cited by 46 · see citing works
Salama, N., Bsharat, R., Alwawi, A., & Khlaif, Z. N. (2025) · BMC Nursing · doi:10.1186/s12912-025-02913-4 · Cited by 42 · see citing works
Nurses perceptions and use of artificial intelligence in healthcare
Areshtanab, H. N., Rahmani, F., Vahidi, M., Saadati, S. Z., & Pourmahmood, A. (2025) · Scientific Reports · doi:10.1038/s41598-025-11002-0 · Cited by 37 · see citing works
Attitudes and anxiety levels of nursing students toward artificial intelligence
Sarman, A., & Tuncay, S. (2024) · Teaching and learning in nursing · doi:10.1016/j.teln.2024.12.006 · Cited by 36 · see citing works
Arab, R. A. E., Moosa, O. A. A., Albahrani, Z., Alkhalil, I., Somerville, J. G., & Abuadas, F. H. A. (2025) · Nursing Reports · doi:10.3390/nursrep15080281 · Cited by 34 · see citing works
Ünal, A. S., & Avcı, A. (2024) · Journal of Pediatric Nursing · doi:10.1016/j.pedn.2024.09.012 · Cited by 33 · see citing works
Utilization of Artificial Intelligence in Health Care: Nursesꞌ Perspectives and Attitudes
Sabra, H. E., Abd-Elaal, H., Sobhy, K., & Bakr, M. M. (2023) · Menoufia Nursing Journal · doi:10.21608/menj.2023.297411 · Cited by 33 · see citing works
(2025) · doi:10.1177/23779608251342931 · Cited by 32 · see citing works
Exploring the ethical dimensions of AI integration in nursing practice: A systematic review
Alnawafleh, K. A., Almagharbeh, W. T., Alfanash, H. A., Alasmari, A. A., Alharbi, A. A., Alamrani, M. H., Alkubati, S. A., Altayar, M. A., & Rezq, K. A. (2025) · Journal of Nursing Regulation · doi:10.1016/j.jnr.2025.08.001 · Cited by 31 · see citing works
Göktepe, N., & Sarıköse, S. (2025) · International Nursing Review · doi:10.1111/inr.70043 · Cited by 30 · see citing works
Systematic Review of Qualitative Evidence
Salmond, S. W., & Bennett, M. J. (2021) · Springer Publishing Company eBooks · doi:10.1891/9780826152268.0012 · Cited by 26 · see citing works
Nurses’ perceptions of artificial intelligence (AI) integration into practice: An integrative review
Lora, L., & Foran, P. (2024) · Journal of Perioperative Nursing · doi:10.26550/2209-1092.1366 · Cited by 23 · see citing works
Oweidat, I. A., Alkhatib, M., ALBashtawy, M., Omar, S. A., Al-Rjoub, S. F., Alsaqer, K., Al‐Mugheed, K., & Abdelaliem, S. M. F. (2025) · Digital Health · doi:10.1177/20552076251336106 · Cited by 22 · see citing works
Hamad, N. I., El‐Ashry, A. M., Ibrahim, I. M., & Hassan, E. A. (2024) · Teaching and learning in nursing · doi:10.1016/j.teln.2024.12.017 · Cited by 22 · see citing works
Mohamed, S. H., El‐Rahman, M. A., Mahmoud, S. F., & Heggy, E. H. Y. (2023) · Egyptian Journal of Health Care · doi:10.21608/ejhc.2023.312617 · Cited by 21 · see citing works
Chen, Y., Wu, F., Zhang, W., Xing, W., Zhu, Z., Huang, Q., & Yuan, C. (2025) · Nursing Reports · doi:10.3390/nursrep15060218 · Cited by 20 · see citing works
Alqaraleh, M., Almagharbeh, W. T., & Ahmad, M. W. (2025) · Nurse Education in Practice · doi:10.1016/j.nepr.2025.104438 · Cited by 18 · see citing works
Alenazi, L., & Alhalal, E. (2025) · Nurse Education Today · doi:10.1016/j.nedt.2025.106780 · Cited by 17 · see citing works
Mariano, M. E. M., Shahin, M. A. H., Ancheta, S. J., Vijayan, M., Dossary, N. M. A., Ojaimi, S. F. A., Qudah, S. A. A., & Harbi, H. F. A. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.101384 · Cited by 17 · see citing works
Ehmke, S., Bridges, J., & Patel, S. E. (2025) · Teaching and learning in nursing · doi:10.1016/j.teln.2025.01.029 · Cited by 16 · see citing works
Alnomasy, N., Pangket, P. P., Alreshidi, B. G., Alrashedi, H., Shinners, L., Alsaqri, S., & Mostoles, R. (2025) · Digital Health · doi:10.1177/20552076251356362 · Cited by 14 · see citing works
Şimşek, E., Kudubeş, A. A., & Semerci, R. (2025) · Teaching and learning in nursing · doi:10.1016/j.teln.2025.02.036 · Cited by 10 · see citing works
Ahmed, E. A. A., Sayed, Y. M., & Mohamed, A. F. A. (2024) · Egyptian Journal of Health Care · doi:10.21608/ejhc.2024.363907 · Cited by 9 · see citing works
Revolutionizing healthcare with an in-depth analysis of AI's transformative impact in India
Gnana Sanga Mithra, S., & Srinivasan, B. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.101467 · Cited by 8 · see citing works
The Role of Personality Traits in Nursing Students’ Attitudes Toward Artificial Intelligence
Tsiara, A., Bakalis, V. I., Toska, A. G., Zyga, S., Stathoulis, J. D., Albani, E. N., Saridi, M. I., Togas, C., Agraniotis, M., & Fradelos, Ε. C. (2025) · Cureus · doi:10.7759/cureus.78847 · Cited by 6 · see citing works
Jalal, S. M., Jalal, S. H., Alasmakh, K. E., Alnasser, Z., Alhamdan, W. Y., & Alabdullatif, A. A. (2025) · Cureus · doi:10.7759/cureus.82943 · Cited by 4 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Lan, X., Li, M., Wang, Y., Chen, M., Jiang, H., Lu, S., & Zhou, Y. (2026) · International Journal of Nursing Studies Advances · doi:10.1016/j.ijnsa.2026.100482 · Cited by 17 · see citing works
Artificial intelligence in mental health care: a scoping review of reviews
Abu‐Mahfouz, M. S., AlFehaid, S., Burqan, H. M., & Arab, R. A. E. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2026.1688043 · Cited by 17 · see citing works
Research on artificial intelligence literacy among nursing professionals: a scoping review
Wang, Q., Lu, N., Yu, C., Qi, J., Zhang, H., & Shi, H. (2026) · BMC Nursing · doi:10.1186/s12912-026-04448-8 · Cited by 16 · see citing works
Nirgiz, C., Sarı, M. K., & Çaylı, N. (2026) · BMC Nursing · doi:10.1186/s12912-026-04293-9 · Cited by 15 · see citing works
Tusyanah, T., Samsudin, N. B., Ismiyati, I., Chayati, N., Pramusinto, H., & Suryanto, E. (2026) · Journal of Pedagogical Sociology and Psychology · doi:10.33902/jpsp.202642865 · Cited by 7 · see citing works
Artificial Intelligence: Readiness, Attitudes, and AI-Related Anxiety Among Oncology Nurses
Dönmez, E., Temiz, G., Mete, B., Marangoz, E., & Ortabağ, T. (2026) · Healthcare · doi:10.3390/healthcare14070848 · Cited by 6 · see citing works
Chen, X., Ding, W., Wang, X., Wang, Y., Ma, S., & Tao, M. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1885808 · Cited by 5 · see citing works
Alrasheeday, A., Alhawsawi, A. A., Alshammari, B., Alkubati, S. A., Aouicha, W., Tlili, M. A., Alharbi, A., Siam, B. G. A. E., Mahmoud, S. K. M., Elamin, B. A., et al. (2026) · Nursing Reports · doi:10.3390/nursrep16050154 · Cited by 4 · see citing works
Liu, Y., 赵秀芳, & Zeng, Q. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1812848 · Cited by 4 · see citing works
Ma, X., & Wang, H. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1903509 · Cited by 4 · see citing works
Sayed, Z. A., Alnjadat, R. M., Khwaldeh, A., & Alqudah, L. M. M. (2026) · Nursing in Critical Care · doi:10.1111/nicc.70477 · Cited by 3 · see citing works
Nurses’ experiences regarding role boundaries in collaborative AI-Assisted nursing: A meta-synthesis
Zhang, Z., Hou, J., Xu, C., Li, H., & Wan, H. (2026) · Social Science & Medicine · doi:10.1016/j.socscimed.2026.119385 · Cited by 3 · see citing works
Yaşar, O. M., Mancı, E., Yakut, H., Bahçecioğlu, H., & Yürekli, G. (2025) · Herkes için Spor ve Rekreasyon Dergisi · doi:10.56639/jsar.1805307 · Cited by 2 · see citing works
Mapping factors associated with nurses’ attitudes toward artificial intelligence: a scoping review
Jin, S., Feng, C., Xin, Y., Zhang, M., & Jin, Y. (2026) · BMC Nursing · doi:10.1186/s12912-026-04459-5 · Cited by 2 · see citing works
El‐Ashry, A. M., AlOtaibi, N. G., AlSaleh, N. S., Karim, N. A. H. A., Amin, S. M., Mohamed, H. A. A., Tawfik, A. F., Ali, A. S., Ibrahim, M. N., Ghoneam, M. A., et al. (2026) · Archives of Psychiatric Nursing · doi:10.1016/j.apnu.2026.152091 · Cited by 2 · see citing works
Bilkay, H. İ., Şirin, B., & Gürhan, N. (2026) · Journal of research in nursing · doi:10.1177/17449871261427667 · Cited by 2 · see citing works
Clej, E. E., Mavrea, A., Fizedean, C. M., Tănase, A. D., Ilie, A. C., & Tischer, A. A. (2026) · Healthcare · doi:10.3390/healthcare14080996 · Cited by 2 · see citing works
Toward an AI-integrated nursing curriculum: A Kano model analysis of generative AI competency needs
Xia, Y., Liu, J., Wang, K., Chen, T., Gong, X., Wu, L., & Zhuang, Y. (2026) · Nurse Education Today · doi:10.1016/j.nedt.2026.107133 · Cited by 2 · see citing works
El‐Sayed, A. A. I., Alsenany, S. A., Younes, B. M., Hawash, M. A. H., & Asal, M. G. R. (2026) · Journal of Emergency Nursing · doi:10.1016/j.jen.2026.04.008 · Cited by 2 · see citing works
Alhumaidi, B. N., & Alharbi, T. A. F. (2026) · Healthcare · doi:10.3390/healthcare14101407 · Cited by 2 · see citing works
Liu, D., Li, W., Lu, G., Ma, Z., Jing, J., Qiu, H., Li, K., Xu, X., & Chen, C. (2026) · Nurse Education Today · doi:10.1016/j.nedt.2026.107237 · Cited by 2 · see citing works
Zhu, H., Xie, Z., Wang, Q., Wang, J., Zhang, H., Xiao, J., Huang, C., Ding, J., & Xiao, L. (2026) · Nurse Education Today · doi:10.1016/j.nedt.2026.107250 · Cited by 2 · see citing works
Clej, E. E., Fizedean, C. M., Mavrea, A., Ilie, A. C., Bratu, M. L., & Marc, F. (2026) · Healthcare · doi:10.3390/healthcare14142063 · Cited by 2 · see citing works
Ravi, R. K., Kaur, D., Kavumpurath, J., Jacob, J., Sharma, S., Baby, P., & Ahmed, S. K. (2026) · Nursing Forum · doi:10.1155/nuf/5278157 · Cited by 1 · see citing works
Бабенко, О. (2026) · International Medical Education · doi:10.3390/ime5020038 · Cited by 1 · see citing works
Shen, M., Xue, S., Liu, F., & Lang, J. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2026.1776845 · Cited by 1 · see citing works
Hamadeh, S., Abdelkader, A., Winchester, T., Cowan, A., Olasoji, M., & Joseph, B. (2026) · Nurse Educator · doi:10.1097/nne.0000000000002181 · Cited by 1 · see citing works
Karaçay, P., Yaşar, Ö., Göktaş, P., & Küçükkaya, A. (2026) · BMC Nursing · doi:10.1186/s12912-026-04832-4 · Cited by 1 · see citing works
AI Utilization and Clinical Judgment: Predictors of Caring Behavior Among Nursing Students
Kulintang, M. B. M., & Ngo, A. L. (2026) · Journal of Nursing Education · doi:10.3928/01484834-20260522-03 · Cited by 1 · see citing works
Ariga, R. A., Imelda, F., Herriyance, H., Edianto, E., Ariga, F. A., Ariga, S., Astuti, S. B., Ariga, H. P. S., Pasaribu, G. M. B., Pasaribu, T. A., et al. (2026) · Journal of Patient Experience · doi:10.1177/23743735261461920 · Cited by 1 · see citing works
Guo, L., Ding, Q., Tang, M., Wei, S., Chen, L., Cao, X., Zhang, X., & Zheng, Z. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1864635 · Cited by 1 · see citing works
Madar, I. H., Kurkute, S. S., & R, L. S. (2026) · Journal of Clinical Nursing · doi:10.1111/jocn.70184 · Cited by 1 · see citing works
Readiness for AI-Enabled Healthcare Systems: Insights from Healthcare Professionals
Afzal, M. T., Afzal, M. A., & Zaib, S. (2026) · Indus journal of bioscience research. · doi:10.70749/ijbr.v4i1.2827 · Cited by 1 · see citing works
Aanazy, W., & Almutairi, N. (2026) · Journal of Pioneering Medical Science · doi:10.47310/jpms202515s0110 · Cited by 1 · see citing works
Mutabazi, P., & Sangwa, S. (2026) · Open Journal of Transformative Education & Lifelong Learning · doi:10.65655/openchristianpress.2026.117 · Cited by 1 · see citing works
Cura, Ş. Ü., Atay, S., Çi̇men, M., & Işık, E. (2026) · BMC Nursing · doi:10.1186/s12912-026-04763-0 · Cited by 1 · see citing works
Sherayne Harrigan, B. (2026) · Clinical Medicine And Health Research Journal · doi:10.18535/cmhrj.v6i03.602 · Cited by 1 · see citing works
Artificial intelligence literacy of nursing students: A cross-sectional study
Dong, X. (2026) · Nurse Education Today · doi:10.1016/j.nedt.2026.107272 · Cited by 1 · see citing works
AI Use, Perceptions, and Perceived Impact Among Nursing Students: Cross-Sectional Study
Taka, I., Hasalla, E., Sula, A., Bahiti, B., Oboni, R. H., & Bani, B. (2026) · JMIR Nursing · doi:10.2196/97832 · Cited by 1 · see citing works
Tang, Z., Song, S., Chen, X., Qin, J., Li, Y., Yu, J., Chen, Y., Liu, H., & 陶香香 (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1963947 · Cited by 1 · see citing works
Feng, L., Zhao, Y., Zhai, J., Nie, X., Huang, Q., & Jing, J. (2026) · Research Square · doi:10.21203/rs.3.rs-10670363/v1 · Cited by 1 · see citing works
Almalki, M. (2026) · Cureus · doi:10.7759/cureus.117315
“However, nursing students and practicing nurses often report moderate levels of AI readiness, and AI adoption is influenced by perceived usefulness, self-efficacy, infrastructure, and leadership support [2,3].”
Chaux, A. (2025) · Revista de Medicina Familiar y Comunidad · doi:10.66476/mf.v2n2.6275
Evolving Role of Emergency Nurses in AI-Supported Care: Experience from the Royal Medical Services
Qawaqzeh, D. T. A. (2026) · The Scientific Journal of Oxford College for International Education · doi:10.65709/0010012
Hairul, Jais, S., Supriadi, & Haryanto (2026) · Riwayat Educational Journal of History and Humanities · doi:10.24815/riwayat.v9i1.132
Hairul, Jais, S., Supriadi, & Haryanto (2026) · Jurnal Ragam Pengabdian · doi:10.62710/9n34f758
(刘灿), C. L., Tian, C., 王向荣, & Wang, F. (2026) · Nurse Education in Practice · doi:10.1016/j.nepr.2026.104860
Wang, X., Li, L., Cai, X., Luo, W., Shen, M., Zuo, Y., Zhang, J., Bai, Z., Yao, Y., Zhang, M., et al. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1779200
Ali, Z., Saeed, H., Bahar, T., Ali, M., Tareen, S. K., Bahar, M., Ali, H., Khan, S. A., Singh, A. K., Gillani, A. S., et al. (2026) · Health Science Reports · doi:10.1002/hsr2.72576
Chen, Y., Wu, S., Zhang, M., Ren, Q., Su, Y., & Li, Z. (2026) · Nurse Education in Practice · doi:10.1016/j.nepr.2026.104885
Çakici, H. B., & Dolu, İ. (2026) · AJIT-e Academic Journal of Information Technology · doi:10.5824/ajite.2026.02.003.x
Risling, T., Newton, L. J., Lam, V., Parry, M., & Downes, E. (2026) · doi:10.2196/preprints.103518
Improving AI literacy reduces anxiety and enhances nurses’ acceptance of AI
Nashwan, A. J. (2026) · Evidence-Based Nursing · doi:10.1136/ebnurs-2026-104563
Alanezi, F. Z., Alenazi, L., Alkathiri, A. M., & Innab, A. (2026) · BMC Medical Education · doi:10.1186/s12909-026-09721-7
Acceptance of AI Tools for Clinical Case Writing in Nursing Education: A TAM3-Based Analysis
Manalese, R. P., Alimurong, R. T., Mallari, C. S., Luciano, R. M., David, R. L., & Miranda, J. P. P. (2026) · International Conference on Information and Education Technology (ICIET) · doi:10.1109/iciet69664.2026.11561690
Surveying Artificial Intelligence (AI) Attitudes, Use, and Competencies Among Nursing Faculty
Turchioe, M. R., Moore, S., Shamnath, A., Hickey, M., & Ferrara, S. A. (2026) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000001586
Bridging the Digital Health Divide: Are Bangladesh’s Frontline Health Workers Ready for AI?
Remal, D. R. A., Chowdhury, S., Islam, A., Zaber, M. I., & Amin, M. A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30044-7_15
Artificial intelligence literacy in nursing: a concept analysis
Li, X., Hu, X., Xu, H., Ju, H., & Yu, P. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1874659
The SPArKED Instrument: Gathering Validity Evidence for Measuring Digital-Age Lifelong Learning
Бабенко, О., Morilova, P., & Daniels, L. M. (2026) · International Medical Education · doi:10.3390/ime5030058
Trustworthy AI and Nursing Education
Küçük, E. E., & Küçük, D. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-2811-7.ch006
Sarika, A., & Rathore, P. (2026) · International Journal of Advance Research in Medical Surgical Nursing · doi:10.33545/surgicalnursing.2026.v8.i6a.347
Mathew, R. (2026) · International Journal of Science and Research (IJSR) · doi:10.21275/sr26707145459
Ethics Used and Acceptance of AI-Based Technology in Nursing Practice
Calagno, H. C., & Ala, M. B. D. (2026) · PAIN JOINTS SPINE · doi:10.1922/pjs.16.6s.2026.1002
Gani, R. R., & Kadhim, J. J. (2026) · Adolescencia e Saude · doi:10.67440/ahj.v21i1s.809
Kewalramani, D., Adeyemi, O. J., Shah, S., Benton, J., Nieman, D. R., Bongu, A., Patel, N. M., Pradhan, A., Sclafani, L., Barone, J. A., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-9955555/v1
Torreno, F., & FLORES, F. (2026) · Research Square · doi:10.21203/rs.3.rs-10357554/v1
Ghazali, M. N. A., & Riaz, M. A. (2026) · BMJ Open · doi:10.1136/bmjopen-2026-121820
Karimtabar, H., Alee, M., & Oghli, S. H. (2026) · BMC Nursing · doi:10.1186/s12912-026-05053-5
Abousoliman, A. D., Atta, M. H. R., & Hamed, H. M. (2026) · International Journal of Africa Nursing Sciences · doi:10.1016/j.ijans.2026.101147
Ganguly, S., Das, S., Siva, N., & Reddy, N. V. (2026) · Scientific Reports · doi:10.1038/s41598-026-63456-5
Profesional de Enfermería como Arquitecto de la Salud Digital
de Bardales, V. V., & de Gómez, J. E. A. A. (2026) · doi:10.48209/978-65-5417-761-0
Berdida, D. J. E., Alhudaib, N. A. A., Grande, R. A. N., Alsharafi, S. A., Agunod, C. D., Santos, A. M., Alanazi, H. H., Al‐Moteri, M., Alqarawi, N., & Alasqah, I. (2026) · Journal of Nursing Management · doi:10.1155/jonm/5338801
Zhang, M., Wei, Y., Feng, F., Tian, H., Yang, Y., Yan, L., Cai, Y., Wang, D., Zhu, C., & Yu, C. (2026) · BMC Nursing · doi:10.1186/s12912-026-05036-6
Gu, J., He, L., Ling, G., Zhan, Z., Liu, H., & Huang, J. (2026) · BMC Nursing · doi:10.1186/s12912-026-05128-3
Şahin, R. S., Kudubeş, A. A., Özbay, S. Ç., & Sarıkahya, S. D. (2026) · Nurse Education Today · doi:10.1016/j.nedt.2026.107313
Balachandran, S., Muliira, J. K., Lazarus, E. R., Bulushi, S. A. J. A., Mamari, R. A., Bakri, A. N. A., & Alawi, S. A. (2026) · Sci · doi:10.3390/sci8080194
Nigrelli, D., Monaco, M. L., Figura, M., Peghetti, A., Iacorossi, L., Latina, R., & Anastasi, G. (2026) · Advancements in health research. · doi:10.4081/ahr.2026.136
Advancing nurse-led governance of artificial intelligence in healthcare
Abuhammad, S. (2026) · Journal of research in nursing · doi:10.1177/17449871261465136
Factors Influencing Attitude Toward Artificial Intelligence Among Nursing Students
Kim, H. (2026) · Journal of Digital Contents Society · doi:10.9728/dcs.2026.27.7.2011
Xie, Z., Han, J., Kuang, D., Hu, J., Liao, C., & Wang, R. (2026) · BMC Nursing · doi:10.1186/s12912-026-05215-5
David-Olawade, A. C., Osonuga, A. A., & Olawade, D. B. (2026) · Applied Nursing Research · doi:10.1016/j.apnr.2026.152135
Yapay zekâ çağında diyetisyen adayı olmak: tutumlar, endişeler ve eğitim ihtiyaçları
Baykan, H. K. (2026) · Mersin üniversitesi sağlık bilimleri dergisi/Mersin üniversitesi sağlık bilimleri dergisi · doi:10.26559/mersinsbd.1836080
Alnomasy, N., Banappagoudar, S. B., Alrashedi, H., Alsayed, S., Alsayed, R., & Hashish, E. A. A. (2026) · Digital Health · doi:10.1177/20552076261479419
Travelbee and relational AI: A triadic model for nursing
Neves, H. L., Sousa, J. P., Seguro, J. M., Bernardes, R. A., Caldeira, S., Shapira, R., Oliveira, I., Coelho, A., & Parola, V. S. D. O. (2026) · Nursing Outlook · doi:10.1016/j.outlook.2026.102878
Han, S., Kang, H. S., Gimber, P., & Lim, S. (2026) · Nursing Reports · doi:10.3390/nursrep16080292
Avoiding the “Desert of the Real”: Preserving Evidence‐Based Nursing in the Age of AI
Azama, K. A., & Nishikawa, J. (2026) · Journal of Advanced Nursing · doi:10.1111/jan.70732
Li, X., Hu, X., Xu, H., Guo, J., Ju, H., & Yu, P. (2026) · Journal of Nursing Management · doi:10.1155/jonm/7972792
Kundi, G. M., Torres, T. M., & Pasha, S. A. (2026) · Open Access Public Health and Health Administration Review · doi:10.59644/oaphhar.5(1).299
Alrazeeni, D. M., Alharrasi, M., Rony, M. K. K., Biswas, R. K., Saima, S. M., Akhter, M. A., Aktery, A., & Khatun, M. T. (2026) · SAGE Open Nursing · doi:10.1177/23779608261485044
Artificial Intelligence Responsiveness in Nursing
Al‐Hamad, A., Yasin, Y. M., & Yasin, L. (2026) · Advances in Nursing Science · doi:10.1097/ans.0000000000000695
Kayaoğlu, S. Ç., ERASLAN, Ş. S., & Tufan, S. (2026) · Nursing Open · doi:10.1002/nop2.70776
Syed, M. A., Alnuaimi, A. S., Kaissi, D. B. E., & Syed, M. A. (2026) · PLoS ONE · doi:10.1371/journal.pone.0345347
babaei, P., & Azami, H. (2026) · Intelligent Hospital · doi:10.1016/j.inhs.2026.100117
Hassan, J., Al-Kharusi, H., Al-Farsi, H., Al-Kharusi, R., Al-Tamtami, Z., Al-Tubi, I., Al-Ruqieshi, A., Al-Balushi, S., & Azri, Z. A. (2026) · Nursing Forum · doi:10.1155/nuf/4700220
Regis, L. T. C., & de Santana, E. R. (2026) · Research Society and Development · doi:10.33448/rsd-v15i9.51723
News-Driven Production Networks and Aggregate Output DynamicsPreprint
Dong, M. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7493705
Artificial Intelligence and the Future of Preventive Care in Nursing and Midwifery
Aghahosseini, S. S. (2026) · Preventive Care In Nursing and Midwifery Journal · doi:10.66224/pcnm.16.2.1
El‐Ashry, A. M., Alanazi, E. F. A., Khedr, M. A., Othman, A. A., Baaqil, S. M., Alwadei, N. H., Rajhi, F. A., Alsharari, A. S., Alanazi, H. F. A., Almutairi, W. A., et al. (2026) · Healthcare · doi:10.3390/healthcare14183065
Wang, C., Yang, L., Cai, X., Wu, Y., Lin, Y., huang, F., & Geng, C. (2026) · doi:10.2196/preprints.112293
- Authors
- El Arab, R. A., Alshakihs, A. H., Alabdulwahab, S. H., Almubarak, Y. S., Alkhalifah, S. S., Abdrbo, A., Hassanein, S., & Sagbakken, M.
- Affiliations
- OsloMet – Oslo Metropolitan University (NO)
- Corresponding author
- Sagbakken, Mette
- Venue
- Frontiers in Digital Health
- Publisher
- Frontiers Media SA
- Published
- 2025-09-25
- Volume
- 7
- Pages
- 1666005-1666005
- ISSN
- 2673-253X (ISSN-L)
- PMC
- PMC12507812
- OpenAlex
- W4414520430
- Cited by
- 113
- References
- 77
- Citations by year
- 2026: 112 · 2025: 1
- FWCI
- 6.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Digital Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- artificial intelligence in nursing, nursing students, attitudes toward AI, AI literacy, technology readiness, adoption intention, AI anxiety, AI training, perceived usefulness, self-efficacy, digital literacy, AI ethics and privacy, AI governance, nursing curriculum, AI adoption barriers, human-AI coexistence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
