Knowledge, attitudes, and practices toward artificial intelligence in medicine among Chinese physicians: A cross-sectional study from January to March 2024 with analysis of influencing factors

BACKGROUND: As artificial intelligence (AI) transforms medicine, understanding physicians' knowledge, attitudes, and practices (KAP) toward AI is crucial. However, large-scale nationwide studies among Chinese physicians are lacking. This study investigates KAP toward AI among Chinese physicians and analyzes its influencing factors. METHODS: A nationwide cross-sectional online survey was conducted from January 15 to March 14, 2024. Multistage sampling was used to recruit practicing physicians across China. A validated, self-administered questionnaire was used to assess demographic characteristics and KAP. The statistical analyses included descriptive statistics, non-parametric tests, multivariate logistic regression, and Spearman correlation. RESULTS: This study included 1,137 participants, with 346 (30.4%) demonstrating good AI knowledge. While 1,034 (90.9%) held positive attitudes toward AI, only 51.2% agreed that medical AI is safe. The rate of clinical AI implementation remained low, with only 328 physicians (28.8%) reporting good AI practices. While "AI in medicine" is the broad field of study, Chinese physicians strongly prefer the term "AI-assisted medicine" (75.1%) to describe AI's functional role, emphasizing its assistive nature. Multivariate analysis identified male gender (OR 1.85; 95% CI 1.42-2.41) and age 50-59 years (OR 2.20; 95% CI 1.31-3.71) as independent predictors of good AI knowledge. Chief physicians showed more positive attitudes than residents (OR 2.06; 95% CI 1.15-3.69). Factors significantly associated with good AI practices included male gender (OR 1.35; 95% CI 1.02-1.80), doctoral degree (OR 2.50; 95% CI 1.71-3.67), and specialization in obstetrics/gynecology (OR 4.95; 95% CI 1.80-13.60), internal medicine (OR 3.94; 95% CI 1.51-10.26), or surgery (OR 4.62; 95% CI 1.77-12.04), compared to pediatrics. Significant positive correlations were found between knowledge and attitude (r = 0.172), knowledge and practice (r = 0.441), and attitude and practice (r = 0.242) (all P < 0.001). CONCLUSIONS: This study found that among Chinese physicians, senior physicians (aged 50-59 years) demonstrated higher AI knowledge than younger colleagues. Additionally, AI adoption rates varied significantly by specialty, with pediatrics showing lower adoption compared to surgery, internal medicine, and obstetrics/gynecology. These findings support targeted strategies, including specialized education for younger and female physicians and the prioritization of AI tool development for underserved specialties such as pediatrics, to foster responsible AI integration into Chinese clinical practice.

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Publication Details

Journal
International Journal of Medical Informatics
Published
2026-05-11
DOI
https://doi.org/10.1016/j.ijmedinf.2026.106476
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Knowledge, attitudes, and practices toward artificial intelligence in medicine among Chinese physicians: A cross-sectional study from January to March 2024 with analysis of influencing factors

Shuming Han, Bei Wang, Zhiqiang Chen, Jun Shu et al.
International Journal of Medical Informatics
Artificial Intelligence in Healthcare and Education
article

Knowledge, attitudes, and practices toward artificial intelligence in medicine among Chinese physicians: A cross-sectional study from January to March 2024 with analysis of influencing factors

Shuming Han, Bei Wang, Zhiqiang Chen, Jun Shu, Haoran Zhang, Lei Qi, Yan Wu, Guangxin Wang, Erlian Sun, Dawei Wang
article en

Abstract

BACKGROUND: As artificial intelligence (AI) transforms medicine, understanding physicians' knowledge, attitudes, and practices (KAP) toward AI is crucial. However, large-scale nationwide studies among Chinese physicians are lacking. This study investigates KAP toward AI among Chinese physicians and analyzes its influencing factors. METHODS: A nationwide cross-sectional online survey was conducted from January 15 to March 14, 2024. Multistage sampling was used to recruit practicing physicians across China. A validated, self-administered questionnaire was used to assess demographic characteristics and KAP. The statistical analyses included descriptive statistics, non-parametric tests, multivariate logistic regression, and Spearman correlation. RESULTS: This study included 1,137 participants, with 346 (30.4%) demonstrating good AI knowledge. While 1,034 (90.9%) held positive attitudes toward AI, only 51.2% agreed that medical AI is safe. The rate of clinical AI implementation remained low, with only 328 physicians (28.8%) reporting good AI practices. While "AI in medicine" is the broad field of study, Chinese physicians strongly prefer the term "AI-assisted medicine" (75.1%) to describe AI's functional role, emphasizing its assistive nature. Multivariate analysis identified male gender (OR 1.85; 95% CI 1.42-2.41) and age 50-59 years (OR 2.20; 95% CI 1.31-3.71) as independent predictors of good AI knowledge. Chief physicians showed more positive attitudes than residents (OR 2.06; 95% CI 1.15-3.69). Factors significantly associated with good AI practices included male gender (OR 1.35; 95% CI 1.02-1.80), doctoral degree (OR 2.50; 95% CI 1.71-3.67), and specialization in obstetrics/gynecology (OR 4.95; 95% CI 1.80-13.60), internal medicine (OR 3.94; 95% CI 1.51-10.26), or surgery (OR 4.62; 95% CI 1.77-12.04), compared to pediatrics. Significant positive correlations were found between knowledge and attitude (r = 0.172), knowledge and practice (r = 0.441), and attitude and practice (r = 0.242) (all P < 0.001). CONCLUSIONS: This study found that among Chinese physicians, senior physicians (aged 50-59 years) demonstrated higher AI knowledge than younger colleagues. Additionally, AI adoption rates varied significantly by specialty, with pediatrics showing lower adoption compared to surgery, internal medicine, and obstetrics/gynecology. These findings support targeted strategies, including specialized education for younger and female physicians and the prioritization of AI tool development for underserved specialties such as pediatrics, to foster responsible AI integration into Chinese clinical practice.

International Journal of Medical InformaticsVol. 216
Weifang Medical University (CN), Jinan Central Hospital (CN), Shandong Provincial Hospital (CN), Shandong Provincial QianFoShan Hospital (CN), Shandong First Medical University (CN), Southern Medical University (CN)
Shandong First Medical University
Quality Education
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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