比较一个概念框架和因素分析,以实现调查项目减少,预测药物不持续性
Chidimma F Umeaghadi1, Jeff G Taylor1, Shenzhen Yao2
1College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Patient preference and adherence
|March 5, 2026
概括
使用概念领域或因子分析 (FA) 减少调查项目,产生了类似的坚持预测模型性能. 概念方法为研究和实践提供了更相关的结构.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 心理测量 心理测量 心理测量
- 生物统计学 生物统计学
背景情况:
- 坚持调查通常是漫长的,促使项目减少到概念领域.
- 项目减少可以通过概念框架或统计方法,如因子分析 (FA) 引导.
- 不同的域创建方法对坚持预测模型的影响以前不清楚.
研究的目的:
- 为了比较概念与因子分析 (FA) 引导的域缩减对坚持预测模型性能的影响.
- 评估域结构是否影响下游模型效用.
主要方法:
- 开发了两个逻辑回归模型,使用相同的调查数据来预测非持久性.
- 调查项目被缩小为三个领域,使用概念 (世卫组织框架) 或因子分析 (FA) 方法.
- 模型的预测性能使用c-statistics进行了评估.
主要成果:
- 概念方法和FA方法都从51个调查项目中确定了三个领域.
- 根据FA指导的域包括跨越概念界限的项目,与世卫组织基于框架的域不同.
- 两种模型都显示了可比的预测性能:c-统计值为0.84 (概念) 和0.82 (FA),没有显著差异 (p=0.060).
结论:
- 在概念和FA引导的域缩小之间没有观察到预测性能的权衡.
- 概念方法提供了更相关和以实践为导向的数据结构.
- 域创建方法影响数据组织,但不一定在这种情况下预测准确性.
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