We followed the same process to assess meaning saturation (described below) that we used in our previous study on saturation with in-depth interview data (Hennink et al 2016 (link)), with the addition of two components to reflect the use of focus group data in this study.
To assess meaning saturation, we selected 19 codes that were central to the aims of the original study on diet, exercise and diabetes and included different types of codes. These codes comprised a mix of concrete (13 codes) and conceptual codes (6 codes) and high prevalence (10 codes) and low prevalence (9 codes) codes (as defined above). This selection reflected the nature of codes developed in this study, whereby there were more concrete than conceptual codes. To assess meaning saturation, we traced these 19 codes to identify what we learned about the code in each successive focus group discussion. This involved using the coded data to search for the code in the first focus group discussion and noting what we learned about this issue from this focus group, then searching for the code in the next focus group and noting any new aspects or nuances of the code from that group, and continuing until all 10 focus groups had been reviewed. This process was repeated for all 19 codes that were traced. For each code, we noted at which focus group there were no new aspects of a code raised and no further understanding of the code, only the repetition of earlier aspects. We deemed this as the point of meaning saturation for that code. We then compared the number of focus group discussions needed to reach meaning saturation with the number needed to reach code saturation determined in our earlier analyses.
To assess whether meaning saturation is influenced by the type of code, we compared the timing of saturation for concrete and conceptual codes. Concrete codes included: ‘family time’, ‘homeopathy’, ‘exercise instructor’, ‘exercise measures’, ‘exercise gender’, ‘exercise venues’, ‘physical appearance’, ‘ingredient cost’, ‘food taste’, ‘diabetes cause’, ‘US-Indian food’, ‘exercise barriers’, and ‘exercise perception’. Conceptual codes included: ‘denial’, ‘exercise pleasure’, ‘work success’, ‘women’s responsibility’, ‘mood’, and ‘cultural expectations’. To assess whether meaning saturation is influenced by the prevalence of a code, we compared saturation by high and low prevalence codes.
To assess whether meaning saturation is influenced by the number of participants who discussed a code, we noted the number of participants contributing to the discussion of each code across all focus groups. If 4 people had discussed a code in the first focus group, 2 in the second, and 6 in the third, we determined that a total of 12 participants had discussed this code across the data. We then identified whether there was any pattern in saturation by the number of participants discussing a code. Finally, to assess how saturation is influenced by the demographic stratification of the focus groups (described earlier), we noted the age and sex composition of each group on the trajectories and identified any patterns in saturation by these strata.
To assess meaning saturation, we selected 19 codes that were central to the aims of the original study on diet, exercise and diabetes and included different types of codes. These codes comprised a mix of concrete (13 codes) and conceptual codes (6 codes) and high prevalence (10 codes) and low prevalence (9 codes) codes (as defined above). This selection reflected the nature of codes developed in this study, whereby there were more concrete than conceptual codes. To assess meaning saturation, we traced these 19 codes to identify what we learned about the code in each successive focus group discussion. This involved using the coded data to search for the code in the first focus group discussion and noting what we learned about this issue from this focus group, then searching for the code in the next focus group and noting any new aspects or nuances of the code from that group, and continuing until all 10 focus groups had been reviewed. This process was repeated for all 19 codes that were traced. For each code, we noted at which focus group there were no new aspects of a code raised and no further understanding of the code, only the repetition of earlier aspects. We deemed this as the point of meaning saturation for that code. We then compared the number of focus group discussions needed to reach meaning saturation with the number needed to reach code saturation determined in our earlier analyses.
To assess whether meaning saturation is influenced by the type of code, we compared the timing of saturation for concrete and conceptual codes. Concrete codes included: ‘family time’, ‘homeopathy’, ‘exercise instructor’, ‘exercise measures’, ‘exercise gender’, ‘exercise venues’, ‘physical appearance’, ‘ingredient cost’, ‘food taste’, ‘diabetes cause’, ‘US-Indian food’, ‘exercise barriers’, and ‘exercise perception’. Conceptual codes included: ‘denial’, ‘exercise pleasure’, ‘work success’, ‘women’s responsibility’, ‘mood’, and ‘cultural expectations’. To assess whether meaning saturation is influenced by the prevalence of a code, we compared saturation by high and low prevalence codes.
To assess whether meaning saturation is influenced by the number of participants who discussed a code, we noted the number of participants contributing to the discussion of each code across all focus groups. If 4 people had discussed a code in the first focus group, 2 in the second, and 6 in the third, we determined that a total of 12 participants had discussed this code across the data. We then identified whether there was any pattern in saturation by the number of participants discussing a code. Finally, to assess how saturation is influenced by the demographic stratification of the focus groups (described earlier), we noted the age and sex composition of each group on the trajectories and identified any patterns in saturation by these strata.