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Background The successful integration of Artificial Intelligence (AI) in healthcare depends heavily on the literacy and attitudes of the frontline nursing workforce. While psychological barriers like “AI fear” are known, the complex interplay between literacy and attitudes across different levels of expertise remains poorly understood from a systemic perspective. Objective This study aimed to utilize psychological network analysis (PNA) to map and compare the AI literacy and attitude cognitive networks of clinical preceptors (experts) and nurse interns (novices) within the maternal and child health (MCH) nursing context. Methods A large-scale, multicenter cross-sectional study was conducted across 32 institutions in 26 provinces in China. A total of 1,031 participants (498 clinical preceptors and 533 nurse interns) completed the AI Literacy Scale and the General Attitudes toward AI Scale. Regularized partial correlation networks were estimated to identify core cognitive nodes. The Network Comparison Test (NCT) was employed to evaluate statistical differences in network topology and global strength between the expert and novice groups. Results “AI Fear” (specifically technological dread and future anxiety) emerged as the most central and influential node, dominating the cognitive networks of both groups. However, the overall network topology differed significantly between the two groups ( p = 0.023). Novices exhibited a “high-density, undifferentiated” structure (Global Strength S = 16.29 vs. 15.58, p = 0.033), where ethical concerns and anxieties were diffusely interconnected. In contrast, experts demonstrated a “low-density, strong-structure” network, characterized by significantly stronger associations along specific “application-ethics” pathways. Conclusion The cognitive architecture of AI perception differs fundamentally by expertise level. For public health systems to effectively implement AI, “one-size-fits-all” training is insufficient. Strategies must shift toward stratified cognitive reshaping: providing structured scaffolding to manage diffuse anxiety in novices, and empowering experts to lead evidence-based evaluation and clinical implementation.
Zeng et al. (Tue,) studied this question.