乳腺癌资源的可读性分析共享在X-对患者教育的影响和AI的潜力
Melanie J Wang1, Aref Rastegar1, Theodore A Kung2
1Department of Surgery, Section of Plastic Surgery, University of Michigan, Ann Arbor, MI, USA.
Breast cancer research and treatment
|August 6, 2025
概括
在X (以前的Twitter) 上的乳腺癌信息往往缺乏可读性. 人工智能 (AI) 在简化复杂的医疗内容以提高公众理解方面表现有前途.
科学领域:
- 卫生沟通健康沟通
- 医疗信息学 医疗信息学
- 公共卫生 公共卫生
背景情况:
- 乳腺癌对全球健康构成重大挑战.
- 有效沟通乳腺癌信息对于公共卫生意识和患者教育至关重要.
研究的目的:
- 在乳腺癌宣传月期间在X分享的乳腺癌文章的可读性评估.
- 探索人工智能 (AI) 在提高本内容可读性方面的潜力.
主要方法:
- 通过使用九个可读性测试,对X的377篇乳腺癌文章进行了分析.
- 分类共享实体 (学术医疗中心,医疗保健提供者,政府机构,科学期刊等).
- 试点研究表明AI有能力提高文章可读性.
主要成果:
- 来自政府机构和科学期刊的文章表现出更高的可读性等级,表明更低的可访问性.
- 患者教育文章的平均可读性等级水平最低,但仍然需要改进.
- 人工智能显著降低了样本文章的平均可读性等级水平,从12.58降至6.56 (p < 0.001).
结论:
- 在社交媒体上的乳腺癌信息的推和实际可读性水平之间存在着显著的差距.
- 需要在所有分享乳腺癌内容的来源中改进和标准化可读性.
- 人工智能为开发更容易获得的乳腺癌患者资源提供了一个可行的工具.
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