ArticleFrontiers in medicine2026
Latent profiles of innovative behavior among hemodialysis nurses and their association with artificial intelligence literacy: a cross-sectional study.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The growing hemodialysis patient population has substantially increased nurses' workload in this specialty. While innovative behaviors are known to enhance both hospital operational efficiency and nursing competencies, research focusing on hemodialysis nurses' innovation remains limited. Notably, no studies have yet examined the potential relationship between this workforce's innovative behaviors and their artificial intelligence (AI) literacy. Objective: This study aimed to identify latent profiles of innovative behavior among hemodialysis nurses, examine their associations with sociodemographic factors and artificial intelligence literacy, and explore predictors of profile membership. Methods: A cross-sectional survey was conducted among 493 hemodialysis nurses in Sichuan Province, China. LPA was used to determine the potential categories of innovative behavior of hemodialysis nurses, and Pearson correlation was used to analyze the relationship between innovative behavior and AI literacy. Binary Logistic regression was used to analyze the influencing factors of different categories of innovative behaviors. Results: The latent profile analysis of innovative behaviors of hemodialysis nurses revealed that the second potential model was the best model (AIC = 10902.747, BIC = 11032.963, entropy = 0.940). The two potential categories were as follows: "high innovative behavior-transcendence" (56%) and "low innovative behavior-conservative" (44%). Correlation analysis showed that there was a positive correlation between innovative behavior and AI literacy of hemodialysis nurses ( Discussion: The identification of two distinct innovative behavior profiles reveals substantial heterogeneity among hemodialysis nurses. The significant positive correlation between AI literacy and innovative behavior highlights the potential of AI competency development as a novel pathway to stimulate nursing innovation. Moreover, educational background and job position as key influencing factors imply that systematic continuing education and expanded leadership roles may effectively elevate innovation, especially for nurses in the "low innovative behavior-conservative" group. These findings provide actionable guidance for nursing managers to incorporate AI literacy training into professional development programs and to design targeted support strategies aimed at cultivating a more proactive, innovative nursing workforce.
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