使用实施研究统一框架(CFIR)的快速对比传统定性分析。

Andrea L Nevedal, Caitlin M Reardon, Marilla A Opra Widerquist, George L Jackson, Sarah L Cutrona, Brandolyn S White, Laura J Damschroder
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引用次数: 120

摘要

背景:定性方法,单独或混合方法,在实施科学中是突出的。然而,传统的定性方法是资源密集型的,这导致了快速定性方法的发展。已发表的快速方法通常是归纳性的,依赖于采访的文字记录。我们描述了一种使用使用笔记和录音的实施研究统一框架(CFIR)的演绎快速分析方法。本文比较了我们的快速和传统的演绎cir方法。方法:采用半结构化访谈法对两组退伍军人健康管理局(VHA)卓越传播计划(DoE)进行调查。CFIR指导数据收集和分析。在队列A中,我们使用传统的基于cfr的演绎分析方法(定向内容分析),其中两名分析师使用定性软件独立完成访谈记录的深度手工编码。在队列B中,我们使用了新的基于CFIR的快速演绎分析方法(定向内容分析),其中主要分析师在采访期间写下详细的笔记,并立即通过设施矩阵将笔记“编码”到MS Excel CFIR结构中;然后,一名二级分析师听取录音并编辑矩阵。我们使用电子表格跟踪传统和快速扣除cir方法的时间,并从发票中获取转录成本。我们回顾性地比较了我们的方法的有效性和严谨性。结果:A组和B组在数据收集量方面相似。然而,我们的快速扣除CFIR方法需要409.5个分析师小时,而传统的扣除CFIR方法需要683个小时。快速演绎法减少了7250美元的转录成本。设施级分析阶段提供了最大的节省:传统分析为14小时/设施,而快速分析为3.92小时/设施。两种方法的数据解释所需的小时数相同。结论:我们的快速演绎CFIR方法节省了时间,消除了转录成本,但有效地满足了评估目标并建立了严密性。研究人员在使用我们的方法时应考虑以下几点:(1)团队在CFIR和定性方法方面的专业知识,(2)满足项目目标所需的详细程度,(3)分析数据的模式,以及(4)使用CFIR的优缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR).

Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR).

Background: Qualitative approaches, alone or in mixed methods, are prominent within implementation science. However, traditional qualitative approaches are resource intensive, which has led to the development of rapid qualitative approaches. Published rapid approaches are often inductive in nature and rely on transcripts of interviews. We describe a deductive rapid analysis approach using the Consolidated Framework for Implementation Research (CFIR) that uses notes and audio recordings. This paper compares our rapid versus traditional deductive CFIR approach.

Methods: Semi-structured interviews were conducted for two cohorts of the Veterans Health Administration (VHA) Diffusion of Excellence (DoE). The CFIR guided data collection and analysis. In cohort A, we used our traditional CFIR-based deductive analysis approach (directed content analysis), where two analysts completed independent in-depth manual coding of interview transcripts using qualitative software. In cohort B, we used our new rapid CFIR-based deductive analysis approach (directed content analysis), where the primary analyst wrote detailed notes during interviews and immediately "coded" notes into a MS Excel CFIR construct by facility matrix; a secondary analyst then listened to audio recordings and edited the matrix. We tracked time for our traditional and rapid deductive CFIR approaches using a spreadsheet and captured transcription costs from invoices. We retrospectively compared our approaches in terms of effectiveness and rigor.

Results: Cohorts A and B were similar in terms of the amount of data collected. However, our rapid deductive CFIR approach required 409.5 analyst hours compared to 683 h during the traditional deductive CFIR approach. The rapid deductive approach eliminated $7250 in transcription costs. The facility-level analysis phase provided the greatest savings: 14 h/facility for the traditional analysis versus 3.92 h/facility for the rapid analysis. Data interpretation required the same number of hours for both approaches.

Conclusion: Our rapid deductive CFIR approach was less time intensive and eliminated transcription costs, yet effective in meeting evaluation objectives and establishing rigor. Researchers should consider the following when employing our approach: (1) team expertise in the CFIR and qualitative methods, (2) level of detail needed to meet project aims, (3) mode of data to analyze, and (4) advantages and disadvantages of using the CFIR.

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