一个随机因子实验的数据集,以优化乳腺癌妇女的信息传单
Sophie M C Green1, Samuel G Smith1
1Leeds Institute of Health Sciences, University of Leeds, Leeds, England, LS2 9LU, UK.
NIHR open research
|August 15, 2024
概括
在乳腺癌患者中改善辅助内分泌疗法 (AET) 的坚持是至关重要的. 这项研究优化了信息传单,以增加AET的必要性信念和减少担忧,旨在提高治疗坚持.
科学领域:
- 在瘤学瘤学.
- 行为科学 行为科学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 在乳腺癌患者中,辅助内分泌疗法 (AET) 的坚持是不理想的,增加了复发和死亡风险.
- 对AET的低感知必要性和高度关注是遵守的关键障碍.
- 对于药物信仰的现有干预措施的有效性有限,并没有专门针对这些信仰.
研究的目的:
- 优化信息传单的内容,旨在改善人们对AET的看法.
- 增加对AET的感知必要性,并减少乳腺癌患者对AET的担忧.
- 为未来的研究提供开放式数据集和方法示例,使用多相优化策略 (MOST).
主要方法:
- 一个全功率的在线2^5因数实验被用来优化传单内容.
- 五个候选组件在两个级别 (开启/关闭或增强/基本) 上进行了测试.
- 1604名健康女性被随机分配,看32种传单版本之一,并填写干预前后的问卷.
主要成果:
- 这项研究生成了来自2^5因数实验的数据集,以优化AET信息传单.
- 参与者数据包括药物信仰,对AET的客观和主观知识以及满意度.
- 该数据集适用于对MOST和复杂因数设计感兴趣的研究人员.
结论:
- 该研究成功优化了信息传单,以解决AET遵守的障碍.
- 生成的数据集对于应用MOST.的研究人员来说是一个有价值的资源.
- 这项工作提供了通过因数设计优化卫生干预措施的方法论范例.
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