{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T11:16:50Z","timestamp":1780917410890,"version":"3.54.1"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T00:00:00Z","timestamp":1780876800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T00:00:00Z","timestamp":1780876800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100000272","name":"National Institute for Health and Care Research","doi-asserted-by":"publisher","award":["NIHR303691"],"award-info":[{"award-number":["NIHR303691"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"DOI":"10.1038\/s41746-026-02873-2","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T10:55:16Z","timestamp":1780916116000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Reconciling how clinical reasoning is learned in the age of artificial intelligence"],"prefix":"10.1038","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9300-573X","authenticated-orcid":false,"given":"Ariel Yuhan","family":"Ong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret","family":"Sui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyra L.","family":"Rosen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph C.","family":"Kvedar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,8]]},"reference":[{"key":"2873_CR1","doi-asserted-by":"publisher","first-page":"e2542338","DOI":"10.1001\/jamanetworkopen.2025.42338","volume":"8","author":"R Sivakumar","year":"2025","unstructured":"Sivakumar, R., Lue, B. & Kundu, S. FDA Approval of Artificial Intelligence and Machine Learning Devices in Radiology: A Systematic Review. JAMA Netw. Open 8, e2542338 (2025).","journal-title":"JAMA Netw. Open"},{"key":"2873_CR2","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1093\/jamia\/ocaf065","volume":"32","author":"EG Poon","year":"2025","unstructured":"Poon, E. G., Lemak, C. H., Rojas, J. C., Guptill, J. & Classen, D. Adoption of artificial intelligence in healthcare: survey of health system priorities, successes, and challenges. J. Am. Med Inf. Assoc. 32, 1093\u20131100 (2025).","journal-title":"J. Am. Med Inf. Assoc."},{"key":"2873_CR3","doi-asserted-by":"publisher","unstructured":"Chatterji, A. et al. How People Use ChatGPT. Working Paper at https:\/\/doi.org\/10.3386\/w34255 (2025).","DOI":"10.3386\/w34255"},{"key":"2873_CR4","unstructured":"Appel, R. et al. The Anthropic Economic Index report: Uneven geographic and enterprise AI adoption"},{"key":"2873_CR5","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1038\/s41746-026-02410-1","volume":"9","author":"AY Ong","year":"2026","unstructured":"Ong, A. Y. et al. Flight rules for clinical AI: lessons from aviation for human-AI collaboration in medicine. npj Digit. Med. 9, 201 (2026).","journal-title":"npj Digit. Med."},{"key":"2873_CR6","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1056\/NEJMra2503232","volume":"393","author":"R-EE Abdulnour","year":"2025","unstructured":"Abdulnour, R.-E. E., Gin, B. & Boscardin, C. K. Educational Strategies for Clinical Supervision of Artificial Intelligence Use. N. Engl. J. Med 393, 786\u2013797 (2025).","journal-title":"N. Engl. J. Med"},{"key":"2873_CR7","doi-asserted-by":"publisher","first-page":"1719","DOI":"10.1016\/S0140-6736(25)02075-6","volume":"406","author":"TM Berzin","year":"2025","unstructured":"Berzin, T. M. & Topol, E. J. Preserving clinical skills in the age of AI assistance. Lancet 406, 1719 (2025).","journal-title":"Lancet"},{"key":"2873_CR8","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-026-02521-9","author":"Y Xin","year":"2026","unstructured":"Xin, Y., Yan, D., Shuren, L., Minyang, L. & Liuheng, L. AI literacy mediates AI assisted diagnosis participation and critical thinking among medical students under supervision. npj Digit. Med. https:\/\/doi.org\/10.1038\/s41746-026-02521-9 (2026).","journal-title":"npj Digit. Med."},{"key":"2873_CR9","doi-asserted-by":"publisher","first-page":"1537","DOI":"10.1016\/j.chest.2024.12.013","volume":"167","author":"C Gauld","year":"2025","unstructured":"Gauld, C., Grasman, R. P. P. P. & Bailly, S. Usefulness of Cross-Lagged Panel Models for Clinical Research. CHEST 167, 1537\u20131540 (2025).","journal-title":"CHEST"},{"key":"2873_CR10","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1177\/1094428119847278","volume":"23","author":"MJ Zyphur","year":"2020","unstructured":"Zyphur, M. J. et al. From Data to Causes I: Building A General Cross-Lagged Panel Model (GCLM). Organ. Res. Methods 23, 651\u2013687 (2020).","journal-title":"Organ. Res. Methods"},{"key":"2873_CR11","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-026-02547-z","author":"D Teng","year":"2026","unstructured":"Teng, D. et al. Impact of AI misinformation on diagnostic accuracy and confidence calibration in novice medical students. npj Digit. Med. https:\/\/doi.org\/10.1038\/s41746-026-02547-z (2026).","journal-title":"npj Digit. Med."},{"key":"2873_CR12","doi-asserted-by":"publisher","first-page":"6","DOI":"10.12688\/mep.21479.1","volume":"16","author":"S Heslin","year":"2026","unstructured":"Heslin, S. Developing Critical Judgment of Artificial Intelligence in Medical Education: Applied Insights. MedEdPublish 16, 6 (2026).","journal-title":"MedEdPublish"},{"key":"2873_CR13","doi-asserted-by":"publisher","first-page":"pgaf316","DOI":"10.1093\/pnasnexus\/pgaf316","volume":"4","author":"S Melumad","year":"2025","unstructured":"Melumad, S. & Yun, J. H. Experimental evidence of the effects of large language models versus web search on depth of learning. PNAS Nexus 4, pgaf316 (2025).","journal-title":"PNAS Nexus"},{"key":"2873_CR14","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.6097646","author":"SD Shaw","year":"2026","unstructured":"Shaw, S. D. & Nave, G. Think.\u2014Fast, Slow., Artif.: How AI is. Reshaping Hum. Reasoning Rise Cogn. Surrender https:\/\/doi.org\/10.2139\/ssrn.6097646 (2026).","journal-title":"Think.\u2014Fast, Slow., Artif.: How AI is. Reshaping Hum. Reasoning Rise Cogn. Surrender"},{"key":"2873_CR15","doi-asserted-by":"publisher","first-page":"3225","DOI":"10.1080\/10494820.2025.2514372","volume":"33","author":"TKF Chiu","year":"2025","unstructured":"Chiu, T. K. F. AI literacy and competency: definitions, frameworks, development and future research directions. Interact. Learn. Environ. 33, 3225\u20133229 (2025).","journal-title":"Interact. Learn. Environ."},{"key":"2873_CR16","first-page":"359","volume":"20","author":"HJ Walberg","year":"1983","unstructured":"Walberg, H. J. & Tsai, S.-L. \u2018Matthew\u2019 Effects in Education. Am. Educ. Res. J. 20, 359\u2013373 (1983).","journal-title":"Am. Educ. Res. J."},{"key":"2873_CR17","first-page":"100225","volume":"6","author":"N Knoth","year":"2024","unstructured":"Knoth, N., Tolzin, A., Janson, A. & Leimeister, J. M. AI literacy and its implications for prompt engineering strategies. Computers Educ.: Artif. Intell. 6, 100225 (2024).","journal-title":"Computers Educ.: Artif. Intell."},{"key":"2873_CR18","doi-asserted-by":"publisher","DOI":"10.2196\/81652","volume":"13","author":"X Shi","year":"2026","unstructured":"Shi, X., Jiang, Z., Xiong, L., Siu, K.-C. & Chen, Z. Utilization of AI Among Medical Students and Development of AI Education Platforms in Medical Institutions: Cross-Sectional Study. JMIR Hum. Factors 13, e81652 (2026).","journal-title":"JMIR Hum. Factors"},{"key":"2873_CR19","doi-asserted-by":"publisher","DOI":"10.1186\/s12909-025-06704-y","volume":"25","author":"A Sami","year":"2025","unstructured":"Sami, A. et al. Medical students\u2019 attitudes toward AI in education: perception, effectiveness, and its credibility. BMC Med Educ. 25, 82 (2025).","journal-title":"BMC Med Educ."},{"key":"2873_CR20","doi-asserted-by":"publisher","first-page":"238212052412646","DOI":"10.1177\/23821205241264695","volume":"11","author":"JS Zhang","year":"2024","unstructured":"Zhang, J. S., Yoon, C., Williams, D. K. A. & Pinkas, A. Exploring the Usage of ChatGPT Among Medical Students in the United States. J. Med Educ. Curric. Dev. 11, 23821205241264695 (2024).","journal-title":"J. Med Educ. Curric. Dev."},{"key":"2873_CR21","doi-asserted-by":"publisher","first-page":"319","DOI":"10.2307\/249008","volume":"13","author":"FD Davis","year":"1989","unstructured":"Davis, F. D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Q. 13, 319\u2013340 (1989).","journal-title":"MIS Q."}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02873-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02873-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02873-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T10:55:21Z","timestamp":1780916121000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02873-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,8]]},"references-count":21,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["2873"],"URL":"https:\/\/doi.org\/10.1038\/s41746-026-02873-2","relation":{},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,8]]},"assertion":[{"value":"19 April 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"J.C.K. is the editor-in-chief of\n                      npj Digital Medicine\n                      and had no role in the peer review or decision to publish this manuscript. The remaining authors do not have any conflicts of interest to declare.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"435"}}