{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T06:24:27Z","timestamp":1787293467722,"version":"build-2736575974"},"reference-count":34,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Rapid integration of artificial intelligence (AI) into maternal and child healthcare introduces unique psychological challenges for nursing staff. This study aimed to explore the network structure of AI anxiety among Chinese maternal and child health nurses and examine its associations with willingness to receive AI-related training, thereby generating preliminary implications for organizational support strategies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A multicenter cross-sectional survey was conducted between May and August 2025, enrolling 848 nurses from 46 maternal and child healthcare institutions across 26 Chinese provinces. AI anxiety was assessed using the Artificial Intelligence Anxiety Scale (AIAS), and willingness to receive AI-related training was assessed using a single 10-point item. Network analysis using the Least Absolute Shrinkage and Selection Operator (LASSO) and the Extended Bayesian Information Criterion (EBIC) was performed to estimate statistically central nodes, cross-dimensional bridge connectivity, and node predictability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The highest strength centrality values were observed for a humanoid-AI-fear item and a learning-anxiety item. AI misuse concerns and job replacement fears showed the highest bridge-strength values, indicating relatively strong cross-dimensional connectivity among the anxiety dimensions. Notably, learning-anxiety items showed the strongest positive associations with willingness to receive AI-related training, with edge weights ranging from 0.22 to 0.24. The estimated strength and bridge-strength rankings showed acceptable stability, with correlation-stability coefficients of 0.594 and 0.750, respectively, while node predictability ranged from 69.3 to 92.1%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>AI anxiety among maternal and child health nurses showed a multifaceted network structure in which learning-related stress and fear of anthropomorphic AI were statistically prominent. These data generate preliminary hypotheses about organizational support but do not identify effective intervention targets. Because willingness to receive AI-related training was assessed using a single global item, the study does not identify nurses' multidimensional educational needs, preferred content or delivery modalities, competency priorities, or perceived barriers. Literature-informed options such as phased or simulation-based training should therefore undergo needs assessment and longitudinal or interventional evaluation before implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1889617","type":"journal-article","created":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T05:38:06Z","timestamp":1787290686000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence anxiety and its association with willingness to receive AI-related training among maternal and child health nurses: a multicenter network analysis"],"prefix":"10.3389","volume":"14","author":[{"given":"Cheng","family":"Huang","sequence":"first","affiliation":[{"name":"National Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University","place":["Chengdu, Sichuan, China"]},{"name":"Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education","place":["Chengdu, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qin","family":"Zeng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education","place":["Chengdu, Sichuan, China"]},{"name":"Department of Pediatric Gastroenterology Nursing, West China Second University Hospital, Sichuan University","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Zhu","sequence":"additional","affiliation":[{"name":"National Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University","place":["Chengdu, Sichuan, China"]},{"name":"Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education","place":["Chengdu, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuji","family":"Wang","sequence":"additional","affiliation":[{"name":"National Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University","place":["Chengdu, Sichuan, China"]},{"name":"Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education","place":["Chengdu, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education","place":["Chengdu, Sichuan, China"]},{"name":"Department of Neonatology Nursing, West China Second University Hospital, Sichuan University","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,21]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1001\/jama.2023.25057","article-title":"Three epochs of artificial intelligence in health care","volume":"331","author":"Howell","year":"2024","journal-title":"JAMA."},{"key":"B2","doi-asserted-by":"publisher","first-page":"3027","DOI":"10.1016\/S0140-6736(16)31593-8","article-title":"Global, regional, and national causes of under-5 mortality in 2000-15: an updated systematic analysis with implications for the sustainable development goals","volume":"388","author":"Liu","year":"2016","journal-title":"Lancet."},{"key":"B3","doi-asserted-by":"publisher","first-page":"103472","DOI":"10.1016\/j.ijnurstu.2019.103472","article-title":"Factors associated with compassion satisfaction, burnout, and secondary traumatic stress among Chinese nurses in tertiary hospitals: a cross-sectional study","volume":"102","author":"Wang","year":"2020","journal-title":"Int J Nurs Stud."},{"key":"B4","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1097\/NMC.0000000000000674","article-title":"Secondary traumatic stress among labor and delivery nurses","volume":"46","author":"Nicholls","year":"2021","journal-title":"MCN Am J Matern Child Nurs."},{"key":"B5","doi-asserted-by":"publisher","first-page":"e028789","DOI":"10.1136\/bmjopen-2018-028789","article-title":"Exploratory study on development challenges of maternal and child healthcare institutions in China: a qualitative study combining interviews and focus groups","volume":"9","author":"Tang","year":"2019","journal-title":"BMJ Open."},{"key":"B6","unstructured":"Geneva\n          International Council of Nurses\n          Recover to rebuild: investing in the nursing workforce for health system effectiveness.\n          \n          2023"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1386","DOI":"10.21608\/ejhc.2021.209023","article-title":"Nurses' anxiety level toward partnering with artificial intelligence in providing nursing care: pre & post training session","volume":"12","author":"Othman","year":"2021","journal-title":"Egypt J Health Care."},{"key":"B8","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1080\/10494820.2019.1674887","article-title":"Development and validation of an artificial intelligence anxiety scale: an initial application in predicting motivated learning behavior","volume":"30","author":"Wang","year":"2019","journal-title":"Interact Learn Environ."},{"key":"B9","doi-asserted-by":"publisher","first-page":"2087","DOI":"10.1111\/jan.16435","article-title":"Sentiment of nurses towards artificial intelligence and resistance to change in healthcare organisations: a mixed-method study","volume":"81","author":"Amin","year":"2025","journal-title":"J Adv Nurs."},{"key":"B10","doi-asserted-by":"publisher","first-page":"104153","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","year":"2022","journal-title":"Int J Nurs Stud."},{"key":"B11","doi-asserted-by":"publisher","first-page":"106899","DOI":"10.1016\/j.nedt.2025.106899","article-title":"AI-driven maternal and child healthcare nursing education: network analysis of self-efficacy and usage demands","volume":"156","author":"Zeng","year":"2026","journal-title":"Nurse Educ Today."},{"key":"B12","doi-asserted-by":"publisher","first-page":"1622802","DOI":"10.3389\/fpubh.2025.1622802","article-title":"Mechanisms of nurses' AI use intention formation in Sichuan, Yunnan, and Beijing, China: mediating effects of AI literacy via self-efficacy-to-attitude pathways","volume":"13","author":"Zeng","year":"2025","journal-title":"Front Public Health."},{"key":"B13","doi-asserted-by":"publisher","first-page":"1846","DOI":"10.37989\/gumussagbil.1274522","article-title":"Artificial intelligence anxiety of nurses and related factors","volume":"12","author":"\u00c7obanoglu","year":"2023","journal-title":"G\u00fcm\u00fc\u015fhane Univ J Health Sci."},{"key":"B14","doi-asserted-by":"publisher","first-page":"e16","DOI":"10.1016\/j.pedn.2024.09.012","article-title":"Evaluation of neonatal nurses' anxiety and readiness levels towards the use of artificial intelligence","volume":"79","author":"\u00dcnal","year":"2024","journal-title":"J Pediatr Nurs."},{"key":"B15","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1186\/s12912-025-04142-1","article-title":"Nurses' attitudes toward artificial intelligence: AI literacy as a predictor and the mediating effect of AI anxiety","volume":"24","author":"Liu","year":"2025","journal-title":"BMC Nurs."},{"key":"B16","doi-asserted-by":"publisher","first-page":"617","DOI":"10.1037\/met0000167","article-title":"A tutorial on regularized partial correlation networks","volume":"23","author":"Epskamp","year":"2018","journal-title":"Psychol Methods."},{"key":"B17","doi-asserted-by":"publisher","first-page":"195","DOI":"10.3758\/s13428-017-0862-1","article-title":"Estimating psychological networks and their accuracy: a tutorial paper","volume":"50","author":"Epskamp","year":"2018","journal-title":"Behav Res Methods."},{"key":"B18","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1509\/jmkr.44.2.175","article-title":"The predictive validity of multiple-item versus single-item measures of the same constructs","volume":"44","author":"Bergkvist","year":"2007","journal-title":"J Mark Res."},{"key":"B19","doi-asserted-by":"publisher","first-page":"1662","DOI":"10.1177\/10731911221113563","article-title":"Examining the concurrent and predictive validity of single items in ecological momentary assessments","volume":"30","author":"Song","year":"2023","journal-title":"Assessment."},{"key":"B20","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1186\/s43058-020-00050-4","article-title":"Predicting implementation: comparing validated measures of intention and assessing the role of motivation when designing behavioral interventions","volume":"1","author":"Fishman","year":"2020","journal-title":"Implement Sci Commun."},{"key":"B21","author":"Cochran","year":"1977","journal-title":"Sampling Techniques"},{"key":"B22","author":"Daniel","year":"2013","journal-title":"Biostatistics: a Foundation for Analysis in the Health Sciences"},{"key":"B23","author":"DeVellis","year":"2016","journal-title":"Scale Development: Theory and Applications"},{"key":"B24","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1111\/cgf.13610","article-title":"The state of the art in multilayer network visualization","volume":"38","year":"2019","journal-title":"Comput Graph Forum."},{"key":"B25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v093.i08","article-title":"mgm: estimating time-varying mixed graphical models in high-dimensional data","volume":"93","author":"Haslbeck","year":"2020","journal-title":"J Stat Softw."},{"key":"B26","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1080\/00273171.2019.1614898","article-title":"Bridge centrality: a network approach to understanding comorbidity","volume":"56","author":"Jones","year":"2021","journal-title":"Multiv Behavi Res."},{"key":"B27","doi-asserted-by":"publisher","first-page":"853","DOI":"10.3758\/s13428-017-0910-x","article-title":"How well do network models predict observations? On the importance of predictability in network models","volume":"50","author":"Haslbeck","year":"2018","journal-title":"Behav Res Methods."},{"key":"B28","doi-asserted-by":"publisher","first-page":"999","DOI":"10.1177\/1745691617705892","article-title":"Moving forward: challenges and directions for psychopathological network theory and methodology","volume":"12","author":"Fried","year":"2017","journal-title":"Perspect Psychol Sci."},{"key":"B29","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1080\/17538157.2021.1883027","article-title":"Users' ambivalent sense of security with humanoid robots in healthcare","volume":"46","author":"Nyholm","year":"2021","journal-title":"Inform Health Soc Care."},{"key":"B30","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1186\/s12912-024-01887-z","article-title":"Dual mediating effects of anxiety to use and acceptance attitude of artificial intelligence technology on the relationship between nursing students' perception of and intention to use them: a descriptive study","volume":"23","author":"Cho","year":"2024","journal-title":"BMC Nurs."},{"key":"B31","doi-asserted-by":"publisher","first-page":"e23933","DOI":"10.2196\/23933","article-title":"Predicted influences of artificial intelligence on nursing education: scoping review","volume":"4","author":"Buchanan","year":"2021","journal-title":"JMIR Nurs."},{"key":"B32","doi-asserted-by":"publisher","first-page":"e14658","DOI":"10.2196\/14658","article-title":"A virtual counseling application using artificial intelligence for communication skills training in nursing education: development study","volume":"21","author":"Shorey","year":"2019","journal-title":"J Med Internet Res."},{"key":"B33","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'Connor","year":"2023","journal-title":"J Clin Nurs."},{"key":"B34","doi-asserted-by":"publisher","first-page":"100072","DOI":"10.1016\/j.glmedi.2024.100072","article-title":"Artificial intelligence in nursing: current trends, possibilities and pitfalls","volume":"3","author":"Ahmed","year":"2024","journal-title":"J Med Surg Public Health."}],"container-title":["Frontiers in Public Health"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2026.1889617\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T05:38:07Z","timestamp":1787290687000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2026.1889617\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,21]]},"references-count":34,"alternative-id":["10.3389\/fpubh.2026.1889617"],"URL":"https:\/\/doi.org\/10.3389\/fpubh.2026.1889617","relation":{},"ISSN":["2296-2565"],"issn-type":[{"value":"2296-2565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,21]]},"article-number":"1889617"}}