Ma Guozhen, Miao Chuyuan, Jiang Pengjun, He Guiqing, Li Huiping, Huang Yanhui, Yu Huiwen, Chen Tianwen
Day Surgery Centre, Shenzhen Nanshan People's Hospital, Shenzhen, Guangdong, China.
Department of Anorectal Surgery, Shenzhen Nanshan People's Hospital, Shenzhen, Guangdong, China.
Breast. 2025 Apr 24;82:104481. doi: 10.1016/j.breast.2025.104481.
To explore the effect of AI-based pre-hospital health education via QR code on preoperative anxiety and information needs in patients with breast nodules and provide a decision-making reference for ongoing optimizing clinical workflows.
This retrospective study analyzed the clinical data of 718 breast nodule patients from January to December 2024. Patients were sequentially divided into a non-viewed group (receiving routine health education) and a viewed group (receiving AI-based pre-hospital health education) to compare Amsterdam Preoperative Anxiety and Information Scale (APAIS) scores between the two groups. Univariate analysis and multivariate regression were used to examine factors influencing preoperative anxiety and information needs in patients with breast nodules.
718 patients were included, with 367 in the non-viewed group and 351 in the viewed group. Patients in the viewed group reported higher satisfaction scores and had shorter hospital stay compared to those in the non-viewed group. The multiple linear regression analysis revealed a significant negative correlation between the viewed group and preoperative anxiety (β = -5.31, 95 % CI: -6.03, -4.59; P = 0.001) and information needs (β = -1.40, 95 % CI: -1.63, -1.18; P = 0.001). Additionally, patient satisfaction also influences their preoperative anxiety and information needs (P < 0.001).
AI-based pre-hospital health education can help reduce patients with breast nodules' preoperative anxiety and information needs, as well as increase their satisfaction and shorten hospital stay. AI-based pre-hospital health education via QR code can be applied in clinical practice.
探讨基于人工智能的二维码院前健康教育对乳腺结节患者术前焦虑及信息需求的影响，为持续优化临床工作流程提供决策参考。
本回顾性研究分析了2024年1月至12月718例乳腺结节患者的临床资料。将患者依次分为未观看组（接受常规健康教育）和观看组（接受基于人工智能的院前健康教育），比较两组的阿姆斯特丹术前焦虑和信息量表（APAIS）得分。采用单因素分析和多因素回归分析影响乳腺结节患者术前焦虑和信息需求的因素。
纳入718例患者，未观看组367例，观看组351例。观看组患者的满意度得分更高，住院时间比未观看组短。多元线性回归分析显示，观看组与术前焦虑（β = -5.31，95%CI：-6.03，-4.59；P = 0.001）和信息需求（β = -1.40，95%CI：-1.63，-1.18；P = 0.001）之间存在显著负相关。此外，患者满意度也会影响其术前焦虑和信息需求（P < 0.001）。
基于人工智能的院前健康教育有助于降低乳腺结节患者的术前焦虑和信息需求，提高其满意度并缩短住院时间。基于人工智能的二维码院前健康教育可应用于临床实践。
