{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T15:50:11Z","timestamp":1789487411679,"version":"build-2803163510"},"reference-count":37,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T00:00:00Z","timestamp":1772755200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T00:00:00Z","timestamp":1772755200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Advanced Nursing"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To examine determinants of nurses' adoption of generative artificial intelligence outputs in clinical practice using a technology acceptance model and an integrated structural equation modelling framework.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Cross\u2010sectional online survey.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Registered nurses in mainland China completed an anonymous questionnaire assessing perceived performance benefits, perceived ease of use, perceived information quality, perceived source credibility, social influence, facilitating conditions, adoption intention and adoption behaviour. Structural equation modelling was used to evaluate the measurement model and estimate a primary mediation model in which perceived performance benefits and perceived ease of use predicted adoption intention, and adoption intention predicted adoption behaviour. An integrated model added information quality, source credibility, social influence and facilitating conditions as additional determinants. Sensitivity analyses were conducted using an ordinal estimator to assess robustness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The analytic sample comprised 330 nurses. In the primary model, higher perceived performance benefits and greater perceived ease of use were associated with stronger adoption intention, and stronger adoption intention was associated with higher self\u2010reported adoption behaviour. The integrated model showed that perceived information quality contributed to adoption intention beyond core expectancy beliefs, while perceived source credibility showed a small direct association with adoption behaviour. Social influence demonstrated a modest association with adoption intention, whereas facilitating conditions showed weaker associations after accounting for other determinants. Model conclusions were consistent across estimation approaches.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Nurses' adoption of generative artificial intelligence outputs is shaped by perceived performance benefits, ease of use and perceived information quality, with adoption intention functioning as the proximal determinant of self\u2010reported use. Implementation strategies should focus on demonstrable workflow gains, reducing interaction burden and strengthening governance and verification to support safe adoption.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jan.70566","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T17:33:39Z","timestamp":1772991219000},"page":"9250-9262","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Effects of Performance and Effort Expectancy on\n                    <scp>AI<\/scp>\n                    \u2010Generated Information Adoption Among Chinese Nursing Professionals: Survey\u2010Based\n                    <scp>SEM<\/scp>\n                    Analysis"],"prefix":"10.1111","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-6766-8175","authenticated-orcid":false,"given":"Linping","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Palliative Medicine West China Fourth Hospital, Sichuan University  Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Huang","sequence":"additional","affiliation":[{"name":"Otolaryngology Department West China Hospital, Sichuan University  Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Osteoporosis\/Non\u2010Communicable Diseases Research Center, West China\u2010PUMC C.C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital Sichuan University  Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianjun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Gynecology and Obstetrics West China Second University Hospital, Sichuan University, Chengdu, China\/Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education  Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meifang","family":"Xu","sequence":"additional","affiliation":[{"name":"General Office Shulan Health Group  Hangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1397-013X","authenticated-orcid":false,"given":"Yan","family":"Zuo","sequence":"additional","affiliation":[{"name":"Department of Gynecology and Obstetrics Nursing West China Second University Hospital, Sichuan University, Chengdu, China\/West China School of Nursing, Sichuan University, Chengdu, China\/Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education  Chengdu 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