使用人工智能设计和开发在线教育模块,以提高高风险人群中肺癌查的普及率
Fang Lei1, Hua Zhao2, Feifei Huang3
1School of Nursing, University of Minnesota, 308 Harvard St SE, Minneapolis, MN 55455, USA.
Cancers
|February 27, 2026
概括
人工智能创建了在线教育模块,以提高肺癌查知识和信念. 这些模块显示出高的有效性和可用性,导致高风险人群查参与度增加.
科学领域:
- 数字健康教育 数字健康教育
- 医疗保健中的人工智能
- 公共卫生干预 公共卫生干预
背景情况:
- 尽管有低剂量计算机断层扫描 (LDCT) 的证据,但肺癌查参与率仍然很低.
- 教育干预对于解决影响查采用知识,态度和信仰差距至关重要.
- 高风险人群需要有针对性的策略来改善对肺癌查指南的遵守.
研究的目的:
- 系统地设计和开发人工智能生成的在线教育模块,用于肺癌查.
- 提高高风险人群对肺癌查的知识,态度和信仰.
- 评估人工智能开发的教育工具的内容有效性,可用性和有效性.
主要方法:
- 使用人工智能开发五个交互式在线模块,以健康信念模型和数字健康原则为指导.
- 由专家小组进行内容验证 (CVI = 0.96) 和高风险个体的可用性测试 (SUS平均得分 = 88/100).
- 进行了定性采访和试点测试,以完善模块设计和内容.
主要成果:
- 所有模块都取得了优异的内容有效性 (I-CVI范围=0.90-1.00) 和高可用性等级.
- 参与者在知识方面显著改善 (p < 0.001),减少了耻辱感 (p < 0.001) 和增强了健康信仰 (p < 0.001).
- 三个月的随访显示,59.1%的参与者获得了LDCT查.
结论:
- 由人工智能驱动的在线模块是改善肺癌查知识和态度的有效和可用的工具.
- 这些教育干预措施有望增加高风险人群的查参与率.
- 开发的模块为未来的大规模干预研究提供了可行的方法,以促进肺癌查.
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