Factors associated with patient privacy concerns in AI-based health monitoring devices among nursing students: a cross-sectional study - Yang Yang; Hui Wang; Kunshuo Du; Xue Wang; Jiukai Zhao; Dong Han; Yu Yang; Shuang Zang (BMC Nursing)
Abstract Background The rapid integration of artificial intelligence (AI) into healthcare has raised important patient privacy concerns, particularly regarding AI-based health monitoring devices. As future healthcare professionals, nursing students will play a critical role in adopting and implementing AI-based health monitoring devices. Objective This study aims to evaluate the level of patient privacy concerns in AI-based health monitoring devices among nursing students and analyze the associated factors. Methods A group of 967 nursing students was extracted from the 2023 Chinese Population Psychology and Behavior Survey (PBICR). The multivariate generalized linear model analysis was used to evaluate the associated factors of the level of patient privacy concerns in AI-based health monitoring devices among nursing students. Result The mean score of nursing students’ level of patient privacy concerns in AI-based health monitoring devices was 69.00 (50.00,88.00) (range 0-100). Family health [Tertile 2: 35 ~ 39 (β = 0.03), Tertile 3: 40 ~ 50 (β = 0.03)], anxiety symptoms [Tertile 2: 2 ~ 7 (β = 0.07), Tertile 3: 8 ~ 21 (β = 0.10)], resilience [Tertile 2: 4 ~ 6 (β = 0.02), Tertile 3: 7 ~ 8 (β = 0.10)], and with no sibling (β=-0.02) were associated with patient privacy concerns in AI-based health monitoring devices among nursing students. Conclusion The results of the study indicate that nursing students have certain concerns about AI-based health monitoring devices. The study emphasizes the need for targeted educational programs to mitigate patient privacy concerns and enhance the acceptance of AI-based health monitoring devices in nursing education based on their associated factors. Clinical trial number Not applicable.