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

Establishing and proving methodological rigor has long been a challenge for qualitative researchers where quantitative methods prevail, but much published literature on qualitative analysis assumes a relatively small number of researchers working in relative proximity. This is particularly true for research conducted with a grounded theory approach. Different versions of grounded theory are commonly used, but this methodology was originally developed for a single researcher collecting and analyzing data in isolation. Although grounded theory has evolved since its development, little has been done to reconcile this approach with the changing nature and composition of international research teams. Advances in technology and an increased emphasis on transnational collaboration have facilitated a shift wherein qualitative datasets have been getting larger and the teams collecting and analyzing them more diverse and diffuse. New processes and systems are therefore required to respond to these conditions. Data for this article are drawn from the experiences of the Innovations for Choice and Autonomy (ICAN) Research Consortium. ICAN aims to understand how self-injectable contraceptives can be implemented in ways that best meet women's needs in Kenya, Uganda, Malawi, and Nigeria. We found that taking a structured approach to analysis was important for maintaining consistency and making the process more manageable across countries. However, it was equally important to allow for flexibility within this structured approach so that teams could adapt more easily to local conditions, making data collection and accompanying analysis more feasible. Meaningfully including all interested researchers in the analysis process and providing support for learning also increased rigor. However, competing priorities in a complex study made it difficult to adhere to planned timelines. We conclude with recommendations for both funders and study teams to design and conduct global health studies that ensure more equitable contributions to analysis while remaining logistically feasible and methodologically sound.

Remote Interviewer Training for COVID-19 Data Collection: Challenges and Lessons Learned From 3 Countries in Sub-Saharan Africa.

There is an urgent need for data to inform coronavirus disease (COVID-19) pandemic response efforts. At the same time, the pandemic has created challenges for data collection, one of which is interviewer training in the context of social distancing. In sub-Saharan Africa, in-person interviewer training and face-to-face data collection remain the norm, requiring researchers to think creatively about transitioning to remote settings to allow for safer data collection that respects government guidelines. Performance Monitoring for Action (PMA, formerly PMA2020) has collected both cross-sectional and longitudinal data on key reproductive health measures in Africa and Asia since 2013. Relying on partnerships with in-country research institutes and cadres of female interviewers recruited from sampled communities, the project was well-positioned to transition to collecting data on COVID-19 from the onset of the pandemic. This article presents PMA's development of a remote training system for COVID-19 surveys in the Democratic Republic of the Congo, Kenya, and Nigeria, including challenges faced and lessons learned. We demonstrate that remote interviewer training can be a viable approach when data are critically needed and in-person learning is not possible. We also argue against systematic replacement of in-person trainings with remote learning, instead recommending consideration of local context and a project's individual circumstances when contemplating a transition to remote interviewer training.