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Updated: Jun 21, 2025

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确定定性访谈的适当样本大小,以实现真实和近代码和:数据的二次分析
Claudia M Squire1, Kristen C Giombi1, Douglas J Rupert1
1RTI International, Research Triangle Park, NC, United States.
Journal of medical Internet research
|July 9, 2024
概括
在基于网络的采访中,接近和可能是足够的,这可能会减少所需的采访数量. 使用结构化指南和演编码的研究更快地达到和,这表明在此之后的回报率下降.
科学领域:
- 定性研究方法 定性研究方法
- 医疗保健服务研究 医疗服务研究
背景情况:
- 深度采访对于定性数据收集至关重要,为人们的感知和行为提供了丰富的见解.
- 在定性研究中,确定和的最佳样本大小仍然是一个挑战.
- 基于网络的数据收集的兴起需要在这种情况下评估和发现.
研究的目的:
- 确定实现真正或接近代码和所需的基于Web的采访次数.
- 为了比较基于网络的采访中的和点与现有关于个人数据收集的文献.
主要方法:
- 基于网络采访的5项食品和药物管理局资助的研究数据的分析.
- 提取和检查代码和采访特定数据以确定和点.
- 评估影响和度的因素,包括面试指南结构和编码方法.
主要成果:
- 在计划面试 (30-67名参与者) 中,真实和率在91%至100%之间.
- 接近和的程度早些时候达到,在计划面试的33%到60%之间 (15-23名参与者).
- 使用演编码和结构化面试指南的研究更快地达到和.
结论:
- 接近和可能是一个充足的终点,表明额外采访的回报正在减少.
- 面试指南结构,编码方法和人口特征影响了和所需的面试数量.
- 这些发现有助于理解基于网络的定性研究中的和,基于实体数据收集研究.
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