开发一种定性数据集成方法,以在研究联盟中推进实施科学
Lisa DiMartino1,2, Allison J Carroll3, Jennifer L Ridgeway4
1Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA. lisa.dimartino@utsouthwestern.edu.
Implementation science communications
|February 26, 2025
概括
在多个研究站点整合定性数据是具有挑战性的. 本研究概述了一种系统的,以框架为指导的方法,以改善研究联盟中的定性数据整合和共享.
科学领域:
- 实施科学 实施科学
- 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:
- 定性数据整合方法不如定量方法发达,阻碍了跨研究调查和数据共享.
- 国家癌症研究所在癌症治疗期间和之后改善症状管理 (IMPACT) 联盟在定性数据整合方面面临挑战.
- 强调开放科学和数据共享,需要强有力的方法来进行定性数据整合.
研究的目的:
- 描述一个系统的方法,在多个地点的研究联盟内整合定性数据.
- 为应对跨不同环境和研究整合定性数据的挑战.
- 为跨站点的定性调查和数据共享提供可复制的方法.
主要方法:
- 影响联盟利用实施研究综合框架 (CFIR) 来指导数据收集和分析.
- 开发了一个半结构面试指南,并根据特定的医疗保健环境和干预措施量身定制.
- 试点测试涉及交换和分析跨研究中心的定性成绩单.
主要成果:
- 整合多样化的环境中的定性数据是资源密集和复杂的.
- 建议包括使用一个共同的框架,分层编码 (域然后构建) 和集中流程.
- 基于CFIR 2.0的代精细代码书被开发为指导程序员.
结论:
- 对于在多项研究中进行定性数据整合,交换和共享,存在有限的指导.
- 一种系统的,以框架为导向的方法可以促进研究联盟中的定性数据集成.
- 该方法支持跨站点的定性调查,并增强对基于证据的干预实施的理解.
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