Suzanne F Jackson1. 1. University of Toronto, Center for Health Promotion, Department of Public Health Sciences.
Abstract
BACKGROUND: When conducting community-based participatory research (CBPR), community researchers are often consulted during the analysis step, but rarely participate in the entire process. OBJECTIVES: This paper describes a participatory qualitative data analysis process that was used in three projects with marginalized women in Ontario, Canada. In each project, marginalized women were trained as Inclusion Researchers (IRs) and participated in all stages of the research process. Given the emphasis of the projects on inclusion, it was important that a data analysis process be developed that was group oriented, engaging, understandable, and inclusive of the community researchers. METHODS: A five-part analysis process is described including preparation of the data, grouping and coding, consolidation, making sense of the data, and producing a report. This group analysis process took place over 2 full days with facilitation by an academic researcher, Details about the techniques used for each step are described. CONCLUSIONS: The strengths of this participatory qualitative data analysis process were that it enabled participation of people with a mixture of levels of education and familiarity with analysis; it enabled community member control of the interpretation; and it could handle large volumes of data quickly. The main limitation was that additional time and procedures would be necessary for a deeper analysis or for groups of over 25 participants. The factors that contributed to the success of this participatory analysis process included accessible and clear procedures, use of visual grouping techniques, and a positive and supportive atmosphere for participation.
BACKGROUND: When conducting community-based participatory research (CBPR), community researchers are often consulted during the analysis step, but rarely participate in the entire process. OBJECTIVES: This paper describes a participatory qualitative data analysis process that was used in three projects with marginalized women in Ontario, Canada. In each project, marginalized women were trained as Inclusion Researchers (IRs) and participated in all stages of the research process. Given the emphasis of the projects on inclusion, it was important that a data analysis process be developed that was group oriented, engaging, understandable, and inclusive of the community researchers. METHODS: A five-part analysis process is described including preparation of the data, grouping and coding, consolidation, making sense of the data, and producing a report. This group analysis process took place over 2 full days with facilitation by an academic researcher, Details about the techniques used for each step are described. CONCLUSIONS: The strengths of this participatory qualitative data analysis process were that it enabled participation of people with a mixture of levels of education and familiarity with analysis; it enabled community member control of the interpretation; and it could handle large volumes of data quickly. The main limitation was that additional time and procedures would be necessary for a deeper analysis or for groups of over 25 participants. The factors that contributed to the success of this participatory analysis process included accessible and clear procedures, use of visual grouping techniques, and a positive and supportive atmosphere for participation.
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