Healthcare providers' perceptions of artificial intelligence in diabetes care: A cross-sectional study in China

Diabetes remains a major global health challenge in China. Artificial intelligence (AI) has demonstrated considerable potential in improving diabetes management. This study aimed to assess healthcare providers' perceptions regarding AI in diabetes care across China.

A cross-sectional survey was conducted using snowball sampling from November 12 to November 24, 2024. We selected 514 physicians and nurses by a snowball sampling method from healthcare providers across 30 cities or provinces in China. The self-developed questionnaire comprised five sections with 19 questions assessing medical workers' demographic characteristics, AI-related experience and interest, awareness, attitudes, and concerns regarding AI in diabetes care. Statistical analysis was performed using t-test, analysis of variance (ANOVA), and linear regression.

Among them, 20.0 % and 48.1 % of respondents had participated in AI-related research and training, while 85.4 % expressed moderate to high interest in AI training for diabetes care. Most respondents reported partial awareness of AI in diabetes care, and only 12.6 % exhibited a comprehensive or substantial understanding. Attitudes toward AI in diabetes care were generally positive, with a mean score of 24.50 ± 3.38. Nurses demonstrated significantly higher scores than physicians (P < 0.05). Greater awareness, prior AI training experience, and higher interest in AI training in diabetes care were strongly associated with more positive attitudes (P < 0.05). Key concerns regarding AI included trust issues from AI-clinician inconsistencies (77.2 %), increased workload and clinical workflow disruptions (63.4 %), and incomplete legal and regulatory frameworks (60.3 %). Only 34.2 % of respondents expressed concerns about job displacement, indicating general confidence in their professional roles.

While Chinese healthcare providers show moderate awareness of AI in diabetes care, their attitudes are generally positive, and they are considerably interested in future training. Tailored, role-specific AI training is essential for equitable and effective integration into clinical practice. Additionally, transparent, reliable, ethical AI models must be prioritized to alleviate practitioners' concerns.