Analyzing fast and slow: Combining traditional and rapid qualitative analysis to meet multiple objectives of a complex transnational study

Abstract

Much of the methodological literature on rapid qualitative analysis describes processes used by a relatively small number of researchers focusing on one study site and using rapid analysis to replace a traditional analytical approach. In this paper, we describe the experiences of a transnational research consortium integrating both rapid and traditional qualitative analysis approaches to develop social theory while also informing program design. Research was conducted by the Innovations for Choice and Autonomy (ICAN) consortium, which seeks to understand how self-injection of the contraceptive subcutaneous depot medroxyprogesterone acetate (DMPA-SC) can be implemented in a way that best meets women's needs, as defined by women themselves. Consortium members are based in Kenya, Uganda, Malawi, Nigeria, and the United States. Data for the ICAN study was collected in all four countries in sub-Saharan Africa. In order to both illuminate social phenomena across study sites and inform the program design component of the study, researchers developed tools meant to gather both in-depth information about women's contraceptive decision-making and data targeted specifically to program design during the formative qualitative phase of the study. Using these two bodies of data, researchers then simultaneously conducted both a traditional qualitative and rapid analysis to meet multiple study objectives. To complete the traditional analysis, researchers coded interview transcripts and kept analytical memos, while also drawing on data collected by tools developed for the rapid analysis. Rapid analysis consisted of simultaneously collecting data and reviewing notes developed specifically for this analysis. We conclude that integrating traditional and rapid qualitative analysis enabled us to meet the needs of a complex transnational study with the added benefit of grounding our program design work in more robust primary data than normally is available for studies using a human-centered design approach to intervention development. However, the realities of conducting a multi-faceted study across multiple countries and contexts made truly “rapid” analysis challenging.

Implementing a Hospital Call Center Service for Mental Health in Uganda: User-Centered Design Approach

“…Data analysis A directed (deductive) content analysis approach 35 was used. We began with a rapid qualitative analysis [36][37][38] of the FGDs in order to quickly identify the requirements and other insights needed to inform initial iterations of system development (see Step 2 below). Rapid qualitative analysis is aimed at getting actionable and targeted insights in a timely manner and is suitable for studies such as this one, where there is a need to refine and adapt an intervention or program, as opposed to developing new theories.…”

“…Later, a traditional qualitative analysis was done [36][37][38] . The first and second authors (JKK and RN) independently read one of the seven transcripts and extracted meaningful units or statements, and coded them into themes related to the research objectives and the CFIR as described above.…”

Many Cooks in the Kitchen: Iterating a Qualitative Analysis Process Across Multiple Countries, Sites, and Teams

“…We chose this approach over other methods commonly used to develop social theory, such as ethnography 14 or case studies, 15 because it best fit the needs of the ICAN study overall. As we have described in detail elsewhere, 16 the ICAN study has both theoretical and applied goals. Other methods would not have fit within the study timeline while also generating adequate evidence for the study's applied research goals.…”

“…Notes from the analysis meetings and the post-interview report forms were also used in adjacent ICAN study activities, which are detailed elsewhere. 16 …”

“…Notes from the analysis meetings and the post-interview report forms were also used in adjacent ICAN study activities, which are detailed elsewhere. 16 Data collection and analysis were slightly staggered across countries due to logistical issues and to enable the U.S. ICAN researchers, as facilitators of the cross-country analysis, to participate in each country's preliminary analysis. This staggering also allowed country teams to learn from one another and was particularly beneficial for teams rolling out data collection later to refine field procedures and tools based on prior learnings.…”