{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T08:25:36Z","timestamp":1791275136168,"version":"4.1.0"},"reference-count":51,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Nursing"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Integrating artificial intelligence (AI) systems into nursing care often encounters obstacles stemming from unmet requirements and insufficient engagement with well-documented sociotechnical pitfalls. Readiness models offer a systematic way to evaluate project preparedness and to build the capabilities needed for successful artificial intelligence in nursing care (AINC) research, development, and implementation. As of yet, an evidence-based AI readiness assessment prioritizing AINC projects and accounting for their diversity in care settings is missing.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to develop a comprehensive artificial intelligence nursing care readiness assessment (AINCRA) to support planning, execution, and evaluation of AINC projects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In a sequential exploratory multimethods bottom-up approach to maturity model development, key AI readiness dimensions and attributes were identified to develop a pilot readiness assessment. The pilot version was grounded on insights from an expert workshop (n=21) and expert interviews (n=14), an online survey (n=53), a rapid review (n=292), and a nominal group consensus process. A systematic literature review (n=7) further triangulated AI readiness attributes. Finally, a think-aloud interview study and focus group discussions involving experts (n=18) from nursing practice, nursing science, and AI research and development who had conducted AINC projects prior to data collection validated the attributes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The resulting AINCRA encompasses 5 core dimensions: regulatory, processual, technical, social, ethical, and community building requirements and aspects. Including 69 attributes and capabilities of AI nursing care readiness, the core dimensions reflect key areas of action where AINC project stakeholders can influence project outcomes. Clinical partners can assess their organization\u2019s maturity level in relation to the implementation of AI. An assessment of each dimension and its attributes across 5 maturity levels allows reflecting on and proactively shaping individual project approaches. Overall, experts regarded AINCRA as a useful instrument for the development, management, and evaluation of AINC projects while emphasizing that established principles of good practice in project and data management should not be neglected when using AINCRA as a project management tool.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AINCRA enables practitioners from AI research and development, clinical partners, and nursing and health scientists to plan, evaluate, and enhance AI projects across their lifecycle, thereby supporting effective AI integration in nursing care. While AINCRA was developed within the European and German legal framework for AI in health care settings, respective attributes can be adapted to international requirements.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/84148","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T17:50:05Z","timestamp":1776793805000},"page":"e84148-e84148","source":"Crossref","is-referenced-by-count":1,"title":["Readiness Assessment for AI in Nursing Care Projects: Multimethods Study"],"prefix":"10.2196","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0422-3637","authenticated-orcid":false,"given":"Kathrin","family":"Seibert","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5876-0334","authenticated-orcid":false,"given":"Dominik","family":"Domhoff","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9357-3504","authenticated-orcid":false,"given":"Janissa","family":"Altona","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9420-8571","authenticated-orcid":false,"given":"Sebastian","family":"J\u00e4ger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3422-1026","authenticated-orcid":false,"given":"Felix","family":"Bie\u00dfmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5194-5585","authenticated-orcid":false,"given":"Alessia","family":"Nowak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1231-1987","authenticated-orcid":false,"given":"Rahel","family":"Gubser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6096-0906","authenticated-orcid":false,"given":"Matthias","family":"Schulte-Althoff","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8490-7707","authenticated-orcid":false,"given":"Daniel","family":"F\u00fcrstenau","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8040-7007","authenticated-orcid":false,"given":"J\u00f6rg","family":"Pohle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4651-0745","authenticated-orcid":false,"given":"Lea","family":"Bergmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2882-2930","authenticated-orcid":false,"given":"David","family":"Walter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1833-452X","authenticated-orcid":false,"given":"Kathi","family":"Beier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0558-7486","authenticated-orcid":false,"given":"Dagmar","family":"Borchers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8513-3125","authenticated-orcid":false,"given":"Karin","family":"Wolf-Ostermann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,6,2]]},"reference":[{"key":"R1","doi-asserted-by":"publisher","DOI":"10.3389\/fdgth.2025.1552372","article-title":"Artificial intelligence in nursing: an integrative review of clinical and operational impacts","volume":"7","author":"Hassanein","journal-title":"Front Digit Health"},{"issue":"13-14","key":"R2","doi-asserted-by":"publisher","first-page":"2951","DOI":"10.1111\/jocn.16478","article-title":"Artificial intelligence in nursing and midwifery: a systematic review","volume":"32","author":"O\u2019Connor","journal-title":"J Clin Nurs"},{"issue":"11","key":"R3","doi-asserted-by":"publisher","DOI":"10.2196\/26522","article-title":"Application scenarios for artificial intelligence in nursing care: rapid review","volume":"23","author":"Seibert","journal-title":"J Med Internet Res"},{"key":"R4","unstructured":"Approval of the content of the draft communication from the commission - commission guidelines on the definition of an artificial intelligence system established by regulation (EU) 2024\/1689 (AI act). European Commission; 2025. URL: https:\/\/ec.europa.eu\/newsroom\/dae\/redirection\/document\/118559 [Accessed 08-05-2026]"},{"issue":"1","key":"R5","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-023-00988-4","article-title":"Generative AI and large language models in health care: pathways to implementation","volume":"7","author":"Raza","journal-title":"NPJ Digit Med"},{"issue":"1","key":"R6","doi-asserted-by":"publisher","DOI":"10.1186\/s12912-025-03448-4","article-title":"Nursing-centered development of an AI-based decision support system in pressure ulcer and incontinence-associated dermatitis management - a mixed methods study","volume":"24","author":"Majjouti","journal-title":"BMC Nurs"},{"key":"R7","doi-asserted-by":"publisher","DOI":"10.3389\/fcdhc.2022.986672","article-title":"Digital algorithm-guided insulin therapy in home healthcare for elderly persons with type 2 diabetes: a proof-of-concept study","volume":"3","author":"Kopanz","journal-title":"Front Clin Diabetes Healthc"},{"key":"R8","unstructured":"Majjouti K Tapp-Herrenbrueck M Pinnekamp H et al. KIADEKU: identification of wound types with AI. In: Yurish SY , editor. Presented at: Proceedings of the 1st International Conference on AI in Medicine and Healthcare (AiMH\u2019 2025); Apr 8-10, 2025; Innsbruck, Austria. URL: https:\/\/sensorsportal.com\/AIMH_2025\/AIMH_2025_Proceedings.pdf [Accessed 08-05-2026]"},{"issue":"4","key":"R9","doi-asserted-by":"publisher","DOI":"10.3390\/nursrep15040126","article-title":"Pressure injury prediction in intensive care units using artificial intelligence: a scoping review","volume":"15","author":"Alves","journal-title":"Nurs Rep"},{"issue":"5","key":"R10","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1001\/jamainternmed.2024.0084","article-title":"Effectiveness of an artificial intelligence-enabled intervention for detecting clinical deterioration","volume":"184","author":"Gallo","journal-title":"JAMA Intern Med"},{"key":"R11","unstructured":"Schwabe K Ferizaj D Neumann S . Reducing nurses\u2019 workload with an AI speech assistant for documentation. In: Yurish SY , editor. Presented at: First International Conference on AI in Medicine and Healthcare (AiMH\u2019 2025); Apr 8-10, 2025; Innsbruck, Austria. 2025.[doi: 10.13140\/RG.2.2.20387.77606]"},{"key":"R12","doi-asserted-by":"crossref","unstructured":"Ferizaj D Neumann S . Assessing perceptions and experiences of an AI-driven speech assistant for nursing documentation: a qualitative study in german nursing homes. Presented at: Human-Computer Interaction: Thematic Area, HCI 2024, Held as Part of the 26th HCI International Conference; Jun 29 to Jul 4, 2024:17-34; Washington, DC, USA. 2024.[doi: 10.1007\/978-3-031-60449-2_2]","DOI":"10.1007\/978-3-031-60449-2_2"},{"issue":"1","key":"R13","doi-asserted-by":"publisher","DOI":"10.1186\/s44247-023-00015-2","article-title":"Exploring needs and challenges for AI in nursing care \u2013 results of an explorative sequential mixed methods study","volume":"1","author":"Seibert","journal-title":"BMC Digit Health"},{"key":"R14","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijnurstu.2021.104153","article-title":"Artificial Intelligence -based technologies in nursing: a scoping literature review of the evidence","volume":"127","author":"von Gerich","journal-title":"Int J Nurs Stud"},{"issue":"4","key":"R15","doi-asserted-by":"publisher","first-page":"958","DOI":"10.1038\/s41591-024-02902-1","article-title":"Causal machine learning for predicting treatment outcomes","volume":"30","author":"Feuerriegel","journal-title":"Nat Med"},{"key":"R16","unstructured":"State of the world\u2019s nursing 2025. World Health Organization; 2025. URL: https:\/\/www.who.int\/publications\/i\/item\/9789240110236 [Accessed 08-05-2026]"},{"key":"R17","unstructured":"EFN policy statement on improving frontline nurses\u2019 time for direct patient care with digitalisation and responsible AI. European Federation of Nurses Association; 2024. URL: https:\/\/efn.eu\/wp-content\/uploads\/2024\/10\/EFN-PS-improving-frontline-nurses-time-for-direct-patient-care-with-digitalisation-responsible-AI-Oct.-2024.pdf [Accessed 08-05-2026]"},{"key":"R18","doi-asserted-by":"publisher","DOI":"10.2196\/62678","article-title":"Advancing AI data ethics in nursing: future directions for nursing practice, research, and education","volume":"7","author":"Ball Dunlap","journal-title":"JMIR Nurs"},{"issue":"1","key":"R19","doi-asserted-by":"publisher","DOI":"10.2196\/23939","article-title":"Predicted influences of artificial intelligence on the domains of nursing: scoping review","volume":"3","author":"Buchanan","journal-title":"JMIR Nurs"},{"issue":"2","key":"R20","doi-asserted-by":"publisher","first-page":"100193","DOI":"10.1016\/j.jjimei.2023.100193","article-title":"A sociotechnical perspective for responsible AI maturity models: findings from a mixed-method literature review","volume":"3","author":"Akbarighatar","journal-title":"Int J Inf Managment Data Insights"},{"issue":"1","key":"R21","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/s12599-020-00676-7","article-title":"Ready or not, AI comes\u2014 an interview study of organizational AI readiness factors","volume":"63","author":"J\u00f6hnk","journal-title":"Bus Inf Syst Eng"},{"key":"R22","author":"Fountaine","journal-title":"Harv Bus Rev"},{"issue":"3","key":"R23","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1007\/s12599-009-0044-5","article-title":"Developing maturity models for IT management","volume":"1","author":"Becker","journal-title":"Bus Inf Syst Eng"},{"key":"R24","unstructured":"Lasrado LA Vatrapu R Andersen KN . Maturity models development in IS research: a literature review. Presented at: System design for, with and by users; Aug 9-12, 2015; Oulu, Finland. 2015.URL: https:\/\/aisel.aisnet.org\/iris2015\/6\/ [Accessed 08-05-2026]"},{"issue":"10","key":"R25","doi-asserted-by":"publisher","DOI":"10.2196\/29301","article-title":"Adoption of machine learning systems for medical diagnostics in clinics: qualitative interview study","volume":"23","author":"Pumplun","journal-title":"J Med Internet Res"},{"key":"R26","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.n71","article-title":"The PRISMA 2020 statement: an updated guideline for reporting systematic reviews","volume":"372","author":"Page","journal-title":"BMJ"},{"issue":"6","key":"R27","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1093\/intqhc\/mzm042","article-title":"Consolidated Criteria for Reporting Qualitative Research (COREQ): a 32-item checklist for interviews and focus groups","volume":"19","author":"Tong","journal-title":"Int J Qual Health Care"},{"issue":"2","key":"R28","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1258\/jhsrp.2007.007074","article-title":"The quality of mixed methods studies in health services research","volume":"13","author":"O\u2019Cathain","journal-title":"J Health Serv Res Policy"},{"key":"R29","unstructured":"Seibert K Domhoff D Altona J et al. ProKIP: rationale and development of the AI-nursing-care-readiness-assessment (AINCRA). In: Yurish SY , editor. Presented at: In First International Conference on AI in Medicine and Healthcare (AiMH\u2019 2025); Apr 8-10, 2025:8-10; Innsbruck, Austria. 2025.URL: https:\/\/sensorsportal.com\/AIMH_2025\/AIMH_2025_Proceedings.pdf [Accessed 08-05-2026]"},{"key":"R30","doi-asserted-by":"crossref","unstructured":"Chang A . Implementation of artificial intelligence in medicine, in intelligence-based medicine artificial. In: Artificial Intelligence and Human Cognition in Clinical Medicine and Healthcare. Academic Press; 2020:397-412. [doi: 10.1016\/B978-0-12-823337-5.00009-3]","DOI":"10.1016\/B978-0-12-823337-5.00009-3"},{"issue":"1","key":"R31","first-page":"58","volume":"112","author":"Boren","journal-title":"Mo Med"},{"issue":"1","key":"R32","doi-asserted-by":"publisher","DOI":"10.1186\/s13643-016-0384-4","article-title":"Rayyan-a web and mobile app for systematic reviews","volume":"5","author":"Ouzzani","journal-title":"Syst Rev"},{"issue":"5","key":"R33","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1007\/s10488-013-0528-y","article-title":"Purposeful sampling for qualitative data collection and analysis in mixed method implementation research","volume":"42","author":"Palinkas","journal-title":"Adm Policy Ment Health"},{"key":"R34","unstructured":"Willis GB . Analysis of the Cognitive Interview in Questionnaire Design. Oxford University Press; 2015. ISBN: 978-0190262853"},{"issue":"5","key":"R35","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1007\/s12599-023-00813-y","article-title":"A maturity model for assessing the digitalization of public health agencies","volume":"65","author":"Doctor","journal-title":"Bus Inf Syst Eng"},{"issue":"1","key":"R36","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1111\/j.1365-2648.2007.04569.x","article-title":"The qualitative content analysis process","volume":"62","author":"Elo","journal-title":"J Adv Nurs"},{"key":"R37","unstructured":"AI nursing care readiness assessment (AINCRA): a tool for structured reflection and preparation of AI projects in nursing care. ProKIP. 2026. URL: https:\/\/aincra.prokip.care\/en [Accessed 04-08-2026]"},{"issue":"1","key":"R38","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.acra.2020.09.014","article-title":"Assessment of the willingness of radiologists and radiographers to accept the integration of artificial intelligence into radiology practice","volume":"29","author":"Abuzaid","journal-title":"Acad Radiol"},{"key":"R39","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2021.07.009","article-title":"Artificial intelligence and the medical physics profession - a Swedish perspective","volume":"88","author":"Andersson","journal-title":"Phys Med"},{"issue":"6","key":"R40","doi-asserted-by":"publisher","DOI":"10.2196\/34678","article-title":"Perspective of information technology decision makers on factors influencing adoption and implementation of artificial intelligence technologies in 40 German hospitals: descriptive analysis","volume":"10","author":"Weinert","journal-title":"JMIR Med Inform"},{"issue":"ahead-of-print","key":"R41","doi-asserted-by":"publisher","DOI":"10.1108\/JHOM-03-2020-0074","article-title":"Organizational readiness for artificial intelligence in health care: insights for decision-making and practice","volume":"ahead-of-print","author":"Alami","journal-title":"J Health Organ Manag"},{"issue":"4 Suppl 2","key":"R42","doi-asserted-by":"publisher","first-page":"S8","DOI":"10.1016\/j.jmir.2019.09.010","article-title":"Developing an artificial intelligence-enabled health care practice: rewiring health care professions for better care","volume":"50","author":"Wiljer","journal-title":"J Med Imaging Radiat Sci"},{"key":"R43","doi-asserted-by":"publisher","DOI":"10.1258\/135763303322596183","article-title":"Organizational readiness for telemedicine: implications for success and failure","volume":"9 Suppl 2","author":"Jennett","journal-title":"J Telemed Telecare"},{"key":"R44","unstructured":"Pumplun L Tauchert C Heidt M . A new organizational chassis for artificial intelligence - exploring organizational readiness factors. Presented at: 27th European conference on insformation systems (ECIS); Stockholm & Uppsala, Sweden. 2019.URL: https:\/\/aisel.aisnet.org\/ecis2019_rp\/106\/ [Accessed 08-05-2026]"},{"key":"R45","unstructured":"Someren MW Barnard YF Sandberg JAC . The Think Aloud Method A Practical Guide to Modelling Cognitive Processes. Academic Press; 1994. ISBN: \u200e978-0127142708"},{"issue":"2","key":"R46","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/j.cptl.2020.09.005","article-title":"Using cognitive interviews and think-aloud protocols to understand thought processes","volume":"13","author":"Wolcott","journal-title":"Curr Pharm Teach Learn"},{"key":"R47","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2015.02.006","article-title":"The value of retrospective and concurrent think aloud in formative usability testing of a physician data query tool","volume":"55","author":"Peute","journal-title":"J Biomed Inform"},{"issue":"4","key":"R48","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1002\/smr.560","article-title":"A review of methods for evaluation of maturity models for process improvement","volume":"24","author":"Helgesson","journal-title":"J Software Evolu Process"},{"key":"R49","unstructured":"Wolf-Ostermann K F\u00fcrstenau D Theune S et al. Concept for embedding AI systems in nursing care: exploratory project on AI in nursing care (sokip). University of Bremen; URL: https:\/\/media.suub.uni-bremen.de\/entities\/publication\/7f4e91a6-6598-4b1c-bec7-fcbf513dd8eb [Accessed 08-05-2026]"},{"issue":"1","key":"R50","doi-asserted-by":"publisher","DOI":"10.1186\/s12961-018-0322-0","article-title":"Collaborative and partnership research for improvement of health and social services: researcher\u2019s experiences from 20 projects","volume":"16","author":"Nystr\u00f6m","journal-title":"Health Res Policy Syst"},{"key":"R51","doi-asserted-by":"publisher","DOI":"10.3233\/SHTI190123","article-title":"The NASSS framework - a synthesis of multiple theories of technology implementation","volume":"263","author":"Greenhalgh","journal-title":"Stud Health Technol Inform"}],"container-title":["JMIR Nursing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/nursing.jmir.org\/2026\/1\/e84148","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T22:26:04Z","timestamp":1785536764000},"score":1,"resource":{"primary":{"URL":"https:\/\/nursing.jmir.org\/2026\/1\/e84148"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,2]]},"references-count":51,"URL":"https:\/\/doi.org\/10.2196\/84148","relation":{},"ISSN":["2562-7600"],"issn-type":[{"value":"2562-7600","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,2]]},"article-number":"v9i13-14e84148"}}