In participatory research, we try to get away from the idea of researchers doing research on people, and move to a model where they are conducting research with people.

 

The movement comes partly from feminist critiques of epistemology, attacking the pervasive notion that knowledge can only be created by experienced academics, The traditional way of doing research generally disempowers people, as the researchers get to decide what questions to ask, how to interpret and present them, and even what topics are worthy of study in the first place. In participatory research the people who are the focus of the research are seen as the experts, rather than the researchers. At face value, this seems to make sense. After all, who knows more about life on a council estate: someone who has lived there for 20 years, or a middle-class outside researcher?

 

In participatory research, the people who are the subject of the study are often encouraged to be a much greater part of the process, active participants rather than aliens observed from afar. They know they are taking part in the research process, and the research is designed to give them input into what the study should be focusing on. The project can also use research methods that allow people to have more power over what they share, for example by taking photos of their environment, having open group discussions in the community, or using diaries and narratives in lieu of short questionnaires. Groups focused on developing and championing this work include the Participatory Geographies working group of the RGS/IBG, and the Institute of Development Studies at the University of Sussex.

 

This approach is becoming increasingly accepted in mainstream academia, and many funding bodies, including the NIHR, now require all proposals for research projects to have had patient or 'lay-person' involvement in the planning process, to ensure the design of the project is asking the right questions in an appropriate way. Most government funded projects will also stipulate that a summary of findings should be written in a non-technical, freely available format so that everyone involved and affected by the research can access it.

 

Engaging with analysis

Sounds great, right? In a transparent way, non-academics are now involved in everything: choosing which studies are the most important, deciding the focus, choosing the methods and collecting and contributing to the data.

 

But then what? There seems to be a step missing there, what about the analysis?

 

It could be argued that this is the most critical part of the whole process, where researchers summarise, piece together and extrapolate answers from the large mass of data that was collectively gathered. But far too often, this process is a 'black-box' conducted by the researchers themselves, with little if any input from the research participants. It can be a mystery to outsiders, how did researchers come to the particular findings and conclusions from all the different issues that the research revealed? What was discarded? Why was the data interpreted in this way?

 

This process is usually glossed over even in journal articles and final reports, and explaining the process to participants is difficult. Often this is a technical limitation: if you are conducting a muli-factor longitudinal study, the calculation of the statistical analysis is usually beyond all but the most mathematically minded academics, let alone the average Jo.

 

Yet this is also a problem in qualitative research, where participatory methods are often used. Between grounded theory, framework analysis and emergent coding, the approach is complicated and contested even within academia. Furthermore, qualitative analysis is a very lengthy process, with researchers reading and re-reading hundreds or thousands of pages of text: a prospect unappealing to often unpaid research participants.

 

Finally, the existing technical solutions don't seem to help. Software like Nvivo, often used for this type of analysis, is daunting for many researchers without training, and encouraging people from outside the field to try and use it, with all the training and licensing implications of this, makes for an effective brick wall. There are ways to make analysis engaging for everyone, but many research projects don't attempt participation at the analysis stage.

 

Intuitive software to the rescue?

By making qualitative analysis visual and engaging, Quirkos hopes to make participatory analysis a bit more feasible. Users don't require lengthy training, and everyone can have a go. They can make their own topics, analyse their own transcripts (or other people's), and individuals in a large community group can go away and do as little or as much as they like, and the results can be combined, with the team knowing who did what (if desired).

 

It can also become a dynamic group exercise, where with a tablet, large touch surface or projector, everyone can be 'hands on' at once. Rather than doing analysis on flip-charts that someone has to take away and process after the event, the real coding and analysis is done live, on the fly. Everyone can see how the analysis is building, and how the findings are emerging as the bubbles grow. Finally, when it comes to share the findings, rather than long spreadsheets of results, you get a picture – the bubbles tell the story and the issues.

 

Quirkos offers a way to practically and affordably facilitate proper end-to-end participatory research, and finally close the loop to make participation part of every stage in the research process.

 

 

Tags : participatoryparticipationanalysismethodsresearch