Zhou Shan
Florida Research and Innovation Center, Cleveland Clinic, Port St. Lucie, FL 34987, United States.
World J Clin Oncol. 2025 Jul 24;16(7):106687. doi: 10.5306/wjco.v16.i7.106687.
This editorial comment on the article by Agidew in the recent issue of the . Breast cancer remains a growing challenge in Ethiopia, where high mortality results from low awareness, delayed diagnosis, and restricted healthcare access. Agidew report that women with a family history of breast disease exhibit significantly higher levels of knowledge (83.9% 10.5%), more positive attitudes (49% 32.1%), and greater engagement in preventive practices (74.1% 16.7%). However, with 69%-79% of women living below the poverty line, socioeconomic barriers severely limit preventive actions. Education, income, and community health insurance emerge as key predictors of health behaviors. We propose integrated interventions including deploying community-based approaches, culturally tailored education, and artificial intelligence-powered education tools, to bridge knowledge gaps and transform awareness into action. This multifaceted strategy offers a scalable model for resource-limited settings globally, addressing both individual awareness and structural barriers to improve breast cancer outcomes.
这篇社论评论了阿吉德乌(Agidew)在最近一期《》上发表的文章。在埃塞俄比亚,乳腺癌仍然是一个日益严峻的挑战,当地乳腺癌死亡率高是由于意识淡薄、诊断延误和医疗服务获取受限。阿吉德乌报告称,有乳腺疾病家族史的女性表现出显著更高的知识水平(83.9%±10.5%)、更积极的态度(49%±32.1%)以及更高的预防措施参与度(74.1%±16.7%)。然而,由于69% - 79%的女性生活在贫困线以下,社会经济障碍严重限制了预防行动。教育、收入和社区医疗保险成为健康行为的关键预测因素。我们建议采取综合干预措施,包括采用基于社区的方法、文化适应性教育以及人工智能驱动的教育工具,以弥合知识差距并将意识转化为行动。这种多方面的策略为全球资源有限的环境提供了一个可扩展的模式,解决个体意识和结构性障碍,以改善乳腺癌治疗结果。