DOI: 10.1155/jonm/6814652 ISSN: 0966-0429

Latent Profiles of Attitudes Toward Artificial Intelligence Applications Among Traditional Chinese Medicine Nurses and Associated Factors: A Multicenter Cross‐Sectional Study

Shuang Lu, Xian Liu, Longxian Liu, Xinrong Tan, Guo Yu, Wenxia Hu, Meigui Peng, Ziyi Yuan, Shaoyang Cui, Meng Wu, Zining Guo

Background

Artificial intelligence (AI) technologies are increasingly being integrated into clinical nursing practice. However, nurses with different professional backgrounds may differ in their attitudes toward AI applications. Traditional Chinese medicine (TCM) nurses, whose practice integrates traditional Chinese nursing techniques, may have distinct perceptions and levels of acceptance of AI compared with general clinical nurses.

Methods

A multicenter cross‐sectional survey was conducted from 10 January to 7 April 2026 in three hospitals and 30 community health service centers in South China. A total of 590 TCM nurses were included. Data were collected using a self‐designed general information questionnaire and standardized scales. Latent profile analysis was performed using the 15‐item scores of the Attitude Scale Toward the Use of Artificial Intelligence Technologies in Nursing as observed indicators. Associations with profile membership were examined using R3STEP to account for classification uncertainty, with simultaneous adjustment for 13 covariates.

Results

The mean total score for attitudes toward AI applications among TCM nurses was 48.13 ± 13.49. Three latent profiles were identified: the low AI acceptance profile (25.14%), the moderate AI acceptance profile (39.68%), and the high AI acceptance profile (35.18%). R3STEP analyses identified profile‐specific associations of TCM specialist nursing experience, education, professional title, TCM nursing professional level, intelligent‐device use, self‐rated familiarity with AI, AI‐related training, and technology anxiety with profile membership.

Conclusions

TCM nurses demonstrated three latent profiles of attitudes toward AI applications: low, moderate, and high AI acceptance. Profile membership was associated with several occupational and technology‐related characteristics, with patterns varying across profile comparisons. These findings may inform AI training and implementation that take differences in nurses’ acceptance into account.

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