Most of us sharing our analysis approaches in the qualitative analysis workshop are working in some kind of team: even the PhD students talked about involving their supervisors or colleagues in the analytical process. There can be headaches and challenges in working as part of a team, but it can be enjoyable, and enrich our learning and the rigor of our analysis. Here, we draw on our experiences of analyzing our recently collected data to describe how teamwork has contributed to the process of analysis for our qualitative research.


Our 5-year project aims to understand and build everyday resilience across health systems. We have research teams based in three sites (one in Kenya and two in South Africa) working collaboratively through all stages of the study: from conception and design, through development of data collection tools, data collection and data analysis. Our data includes a set of formal interviews, informal discussions and observations primarily with health system managers, collected over a relatively long period of time. Even here in Kenya, research team members come from a range of backgrounds and are based both in the capital city and an 8-hour drive away on the coast. To make sure we are as productive as possible, we have to ensure that we are working from the same page. Here are some of the deliberate efforts that we used to ensure ownership and contribution from everybody in the analytical process.

Working together to develop the study conceptual framework: Our work, or at least part of it, involves deliberately testing an initial conceptual framework from a previous body of work that we conducted in the same sites. The initial conceptual framework was developed together as a team in a face-to-face planning meeting held in South Africa. Developing the framework itself was strengthened by lots of different people contributing their ideas and asking questions. Discussions about this conceptual framework over time - in face-to-face meetings and through regular skypes - have served as a focal point in designing our tools and thinking about our analytical process and goals.


Debrief sessions as the first step in analysis: We recognize that data analysis in qualitative research is iterative, beginning during the data collection process and continuing throughout the study. So, after each interview, we had interview debrief sessions between those present at the interview (usually an interviewer, note-taker and occasionally another observer too, where it was comfortable for the interviewee) about what we had asked, heard and learned. These were really useful in understanding how different people might interpret what they had heard; adding context to the data and identifying new questions, or tweaking them. So, these sessions helped us in continually refining our data collection tools to enhance our learning.

Developing interview summaries: Following the debrief sessions we developed interview summaries guided by the interview questions and our field notes as soon as we could. Discussing and constructing these summaries amongst ourselves allowed us to familiarize ourselves further with the data we had collected, organize our learning, begin to compare information by interviewees, and assist further in identifying gaps that we could follow up in the subsequent interviews. The interview summaries included information on key observations as discussed in the debrief sessions to ensure we captured the context of the data.


Reflective meetings and Reflexivity: In addition to regular team meetings, we organized longer reflective practice meetings where we would deliberately try to bring together what we were learning and how we were learning it. We organized these meetings within Kenya (sometimes with our colleagues who are health managers and sometimes without them), and with our South African colleagues (via skype). These meetings allowed those with different experiences, training and ‘insider’/’outsider’ status to share their ideas. They helped us to understand how we all bring our own influences into the analysis process and – when our discussions included managers – offered the opportunity to draw on managers’ tacit knowledge and check resonance of our findings with their experiences. Among the factors that invigorated the team in reflecting on the study findings were the intermediate goals and products that the team had to be developed during the project implementation process, including student’s thesis projects and presentations of preliminary findings to colleagues. Such goals and products have supported us in developing charts based on our theoretical framework from the interview summaries, to support preliminary testing of the framework.

 

All in all, our team approach to analysis has been much more helpful than headache! In an upcoming cross site one week meeting we will continue with the team reflection and planning process, including discussing whether to code all/part of our data in Nvivo, and the coding framework to use.

 

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