The focus group qualitative data analysis is similar to the other types of qualitative data analysis discussed in our best practices for interviewing section. The qualitative data from your focus group will be the text of the transcript or audio/video recording, as well as any other materials you might have collected using a creative technique (like pictures or a collage). Your main goal in focus group data analysis remains the same as any research – you are trying to figure out what is going on, trying to get some answers to your research questions. In focus group data analysis, this usually means looking for major themes that emerge from your analysis.
The first thing you need to do is organize your data. Qualitative data can be very messy. Do you have transcripts of your interviews? Audio or video recordings? Your own notes? All of the above? Get these all in order in a way that makes sense for you. There is no one way to go about doing this.
The next thing you have to do is go through these interview data sources – by reading, listening or watching – and use codes as a way to identify major themes. Codes are ways to identify ideas, topics, themes, concepts, words, terms or phrases that appear frequently or seem to be important in your interviews. You might start your analysis with some codes already in mind – this deductive coding will be based on your experience or previous research and theory development others. Or, you may develop these codes as you go through your data, through a process called inductive coding. What separates the focus group data analysis from other types of qualitative data analysis is that you are looking to compare themes both within and between the groups that you conducted.
Get Participatory! Focus group analysis is often done best when done by multiple people in a collaborative process. It can be a great way to get folks involved who are the types of people that you are interested in learning more about in the course of your research.
Let's move back to our example from the Metamorphosis Project. If you remember, we were interested in what people saw as major problems in their community. As we read through the transcripts, we noticed that participants across the different groups often mentioned the word “respect”. They talked about the need for neighbors to respect each other, and about the ways in which they felt disrespected by criminals, by police, and by a lack of quality goods and services in their community. So each time we saw a reference to issues of respect, we jotted down a “respect” code name. After reading through all of the transcripts, we then collected all of the quotes that touched on respect and read through them separately. From there, we could compare and contrast – did participants in the African American groups talk about respect in a different way than participants in the Latino groups, or was there a great deal of similarity? Were different types of respect discussed in each of the individual groups? After additional analysis, were able to draw some conclusions about the role of respect within the community.
As you look through your own qualitative data, you should come up with a number of these types of codes, giving a codename to each different topic you come across. Look for similarities and differences within and across the different groups. As you go through your data more than once, you will then see that some codes are similar and might be able to be combined. After going through your data several times (the number is up to you, but three or four times is a good minimum amount), you should be able to come up with a few major themes related to your research questions. Think hard about these major themes, what they mean for your research question and for your work. Write up your thoughts and include some representative quotes from your interviews that help explain how you came up with your themes.
Recently, several computer software programs have been developed that help people code their qualitative data. They usually cost money and can be a bit difficult to get the hang of, but many researchers find that they can be very helpful when dealing with lots of qualitative data that has been transcribed. We won't go through how to use them here, but a few of the most popular are: AtlasTI, Nudist and Ethnograph.