Participatory Data Analysis Workshops

Challenge

As the Community Food Access research project aimed to be as inclusive and participatory as possible, we felt it was important to include participants in all phases of the research. Furthermore, we were excited at the idea of infusing our analysis with the lived experiences of our participants. Our participants were the real experts in the reality of food insecurity, because they lived it. So they could bring that expertise to bear in the analysis. The challenge facing us however, was how to do it. How could we include participants in a meaningful way in the data analysis process?

Data analysis is a step in most research projects where participants and users are rarely engaged. Data analysis is fairly technical and typically requires significant training to do correctly. This is especially true of quantitative analyses. However, we identified an opportunity around engaging participants in qualitative analysis as the core principles are fairly intuitive.

Approach

In reviewing the literature around participatory data analysis, we found a few examples of researchers who previously used participatory data analysis with qualitative data. They reported positive outcomes and highlighted the fact that participants were readily able to engage and contribute meaningful insights through the process. We looked to these prior studies for inspiration in designing our workshop, especially work reported by Suzanne Jackson.

Our approach focused on breaking up the qualitative data we collected, which was in the form of transcribed semi-structured interviews from the MEI study, into small fragments of no more than a few statements that all related to a singular topic. We cut these fragments into small strips of paper and then randomly selected a subset of them for the activity.
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During the workshop, participants worked together to identify fragments that related to a similar topic. They grouped these fragments together and then worked to come up with a label for that group of topics. In essence, they were doing inductive qualitative analysis to identify salient themes in the data. A more detailed description of the workshops and the full protocol can be found here.

Outcome

In total, we hosted two sets of workshops – one in English and one in Spanish. Across the two workshops we had 15 individuals (9 in English and 6 in Spanish) who self-identified as having experienced food insecurity participate. Participants were extremely engaged with the process and had overwhelmingly positive feedback about their experience. As we had hoped, participants found the process understandable and they were successful in identifying emergent themes from the data. Here are some pictures of the analyses:

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The results from the English analysis workshop. On the left is an image capturing a number of the merged themes between different groups. On the right is an image with the themes identified by a single group, before merging with the rest of the groups.
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The results of the Spanish analysis workshops after the subgroups merged their overlapping and related themes together.

We collected the groupings and themes generated by participants during the workshops. During the English workshop, participants identified 21 different consolidated themes or groupings of themes. In the Spanish workshop, participants identified 14 different consolidated themes.

Here is a sampling of the key themes that participants identified during the workshop:

  • Comparison shopping
  • Phones as tools for food access
  • Desperation
  • Overcoming feelings of guilt (guilt trip)
  • The socialization and community-oriented aspects of poverty
  • Non-profit and government program red tape prevents food access
  • Long wait times and waiting
  • Nutritional bang for the buck
  • Transportation issues
    • Car repairs
    • Lack of fuel
  • People want ideas for how to prepare food
    • Need recipes for unfamiliar foods