NVivo Focus Group Workflow: Clean, Code, Theme Fast (Full Transcript)

[00:00:00] Speaker 1: Hello everyone. I am going to show you how to analyze your focus group data using in vivo. As you can see here, I have uploaded transcripts from group one and group two focus group. And then when you go to cases, I have created a case for each of the participants, right? And I will give you a little bit of more information about the participants, right? So you can see that I've created containers for each of the participants. And then as you can see, when I go to case classification and double click on speaker, I have demographic information here, right? I was able to bring their demographic here. I was able to create cases for each case for each participant. And then when you go to codes, I was able to code the data, identify information that are significant, developing codes and themes to help me to address my research questions. So this is what I'm going to show you. There are about seven steps that you have to follow. And the first step is data cleaning, right? You have to clean your data. So what I'm going to do is I'm going to show you the data that I have. And then I'm going to go ahead to show you how to use in vivo to analyze your focus group data. So let me start with what the data is all about. So as you can see here, this one is about responsible innovation. So taking into consideration stakeholders' needs as you try to come up with new innovation or new technology. Participants were asked about their perceptions and views about responsible innovation, how they conceptualize responsible innovation. And I have my three research questions here. There are 10 participants, and then this is the demographic information. Five participants were in group one and another five were in group two. So this information about the study. So let me show you this transcript for you to see how it looks like. I have two transcripts and you can see here that this transcript is like basically giving you background information and also a little bit of description about who the participants are. So you can see here that I have five participants and then a brief description about their positions, what they do. And then this is a transcript of the conversation the researcher had with participants. As you can see, I have cleaned the data. So as you can see here, I've removed any identifiable information and then put participants' positions and their IDs. So I gave them P1, P2, P3. You can see P3 here, P1 here, P4 here. So you see how it has been arranged nicely. If you want in vivo to determine who said what, this is how you have to arrange it, right? So you provide information about participant name or you provide participant ID or participant information and then column and also what they said, right? Sometimes it's difficult to know who said what. In this case, then you don't have to worry about arranging in this way, right? But if you know who said what and then it's important for you to do it this way, especially when you code the data, if you want to know who is the quotation from or who made that statement, then it's very important to provide who said it. But as I said, sometimes it's difficult to determine what participants said. In this case, we just have to ignore this kind of arrangement. But based on best practice, this one is a perfect arrangement before you upload all the information into in vivo. So this is my first transcript and I'm going to show you the second transcript. So the second one, the similar format. I have all the information about what participants said and then, yes, it looks like this one is ready for us to upload. Whenever you want to upload, you have to close it first, right? Make sure you save and close it before you upload. So I'm closing them and then I go ahead to do the upload, right? But before you also do the upload, you have to create a project. So let's open in vivo. So I'm using in vivo 15, windows version. So I click on the vivo 15 icon and it takes a few seconds to open. When it's open, you go to new project and you can just say focus group project and then you click on browse to determine where you want to save it. I just want to save this one on my desktop and then you can give a description if you want. It's not required. If you want, you can do that. You can also check keep a log user actions. So this one will document any action that you take when you are analyzing your data. So I don't think this one important. You can check and see what you're going to get, but I'm not going to check this one. I go to next. I choose yes here to indicate that I want the system to automatically save any action I take within the project and then I go to create project. So this is what you're going to see. You click on skip talk and then the first action that you have to take is to import your transcript. How do you do that? You go to import files. As you can see here, I have the two transcripts. So I select both and open it and then I click on import. So you can see here that I've uploaded the two transcripts. One transcript for group one and also one transcript for group two. Right. So what will be the next step? The next step is to create a case for each of the participants. We want to create a case for each of the participants or speaker. Right. And the reason being that I want to bring demographic information. Before you bring demographic information, you have to create cases for each of the participants. If your transcript doesn't have who said what there, then there's no need for you to create a case. You can create a case for each of the files, group one and group two, but normally it's useful if you have participant information. If you have who said what so that you can create case for each of the participants. So how are you going to do that? What you're going to do is that you can select both. So I've selected both transcripts and I go to home and I click on auto code and then you see here this speaker name. Right. So what you are telling the system is that try to call the data based on a speaker name. The reason why we are doing that is the system is going to extract each of the speakers and what they said. Right. So that you can, you'll be able to create case for each of the participants or the system will automatically create case for each of them. So I go to Nest and then it's asking you who are the speakers. What you have to do is to open the transcript and then, you know, copy the names here and use it to search for the speakers. So that's what I'm going to do. You can, so let me, so AI Tech Innovator, let me copy that and put it here and then the system has found it. So when it's found, it just, it will check here that it's found it. Then we're going, I'm also going to look for the second participant from the document. So it's like bringing all the participants here. If their names are in the transcript. Right. Or if they are, the label that you have for them are the transcript. So that's what I'm doing now. The fourth participant and then I'm going to bring the fifth one. You also have to bring the second transcript with other participants. So I'm just copying and putting them here. So this is the last one I'm going to bring here. Okay. So I'm done. So when you are done, you go to Nest and here it's asking you to create a name for the demographic information. Right. So I can just type speakers or you can even type participants if you want. This one is just telling you that the system will be creating a case for each of the participants. So you click on finish. So it is saying that auto coding is complete. Let's go to cases and see whether we have all the, so you see here that we have all the participants, they have their cases here. Right. So that's perfect. And then when you go to codes, you don't have anything there. But when you go to speakers, you don't have, you have a list of participants or speakers, but you don't have their demographic information and the case classification. So what next? You have to bring their demographic information here. There are two ways to do this. You can manually enter participant demographic information. You see that I initially showed you that list of participants demographic information here. You can easily go bring that information by manually going here. And then what do you have to do is you right click, no, you right click here and click on new attributes. And the first attribute, maybe we can do the roles, their roles. So I'll type attributes is just like a variable. So you type role, and then you leave this one alone. It's test because you're going to type in their role, like are they innovators? Are they policymakers? Are they regulators? So you leave that place as test and then click on okay. And when you do that, this place, another column come here, and this is where you put the information here. You double click. And the first one is an innovator. So I'm going to copy the name, the label here, or you can even type, right? Double click there and type innovator. This person is also an innovator. And then the next one is also innovator. The next one is a policymaker. So you can just type policymaker, right? So that's what you're going to do. You first write it here and create a variable, right? In this case, role. And then you can put in the each participant information. I have a second option. The second option is that I already have, let me delete this one first. Let me go to the plus sign and delete that one. I'm deleting it because I'm going to import all the demographic information. So if you want to import the demographic information, you can have a table like this. The first column is participants. You see that the same information in the document and also the same information that you have given to each of the participants, the same thing. Because if you don't do that, the system may not be able to connect the demographic information to participants, right? So everything should be the same here. Speakers should be what the same kind of label that you have given to participants. Then the next one will be the role, the profession, age range, and other demographic variables that you have, right? Then so you can be able to import this one. So you close this one and go to import and go to classification and click on import classification sheet. You click on browse and then you look for that information. So let me look for it. So I have it here. Let me click on open and go to nest. You have to make sure that you change this one from file classification to case classification. Then you go to nest or you go to ask case. Let me click on sell it, but you don't do anything here. You just want to see whether all the participant information is here, the cases. And you go to nest and click on finish. So when you do that, you can see that all the demographic information is right here, right? And it has been connected to participant variable here, right? You see that this participant P4 came two times. There's a reason. The reason why it came two times is that you see the spelling here is different from government spelling is shorting from this one. So the system created a new one, right? To correspond to this one. So in this case, you have to make the necessary correction. So that's what I was telling you. Make sure that what you have here, the names should be the same thing under cases. So what we can do here is that we can even delete this one. And then what we can do is we look for, so these are nine participants now. What we can do is to right click on this government one and then go to classification. And then I think we can connect it to the speaker and see. So when you connect it to the classification sheet called speaker, it will appear here. And then now you manually enter that information. So let me look for this participant information and type it there. So this participant is P4. He is a policymaker and the profession, P4, it's a government. So that information is government policy analyst. You can type that information in or copy and paste. And then the age ranges from 40 to 50. 40 to 50. And the person is a female. So you see that you can manually go there and make the necessary corrections. Now that we are done, the next step is to create containers for the research question. So the reason why you have to create containers is that you want to code the data based on the research question and then develop codes under each of the research questions. So we have three research questions. So you first have to label your research question. So the label helps you to create a container for each of the research question. It doesn't have to be perfect. It's a label that can remind you of what this question represents. So what you're going to do is that you go to in vivo, go to codes, close here. You can also close these, right? And you go to codes and right click here, new code. And then the first research question is we have a label for it. It's about conceptualizing and applying principles of responsible innovation. So what you have to do is that you first have to type out Q1 and then give the label. And then you can also bring the research question under the description there, just to remind you that this is about a research question. So let me copy the research question and paste it here. Right. So this is a research question one. We've done and checked aggregate coding from children and I click on OK. Right click here to do the second research question. I have the label. It's about barriers to foster responsible innovation. I copy that. I put it here and then I'm going to also copy the research question and put it here. Right. And check aggregate coding from children. Click on OK. And let me do the next one. Right. Click new code. And then I bring the research question here under the description. And then I select and copy and paste there. Let me copy that. So this is for the third research question. Right. When you have done aggregate coding from children and click on OK. The reason why we check aggregate coding from children is that you are just telling the system that if I bring any codes under each of this research question, you should add everything up in terms of the number of significant information you have connected to each of the codes. Right. Add everything and aggregate them and put it up there corresponding to each of the research questions. So that's why I check aggregate coding from children. You may not understand it well until we create the codes and then you see what I'm talking about. Right. So now you have containers for the research question. The next process is to start a coding process. Right. I'm not going to go into much detail about a coding process. I have a lot of videos about coding, but I'm just going to give you a brief information. So the coding process started like this. You go to files and then double click on one of the transcripts. Let's open the first transcript. And then you click codes so that you bring all the containers on the left side. And you start a coding process. And coding is all about going through the data with research question in mind. And then you identify information that is significant. You make sure that you understand what the participant is saying. And then you also have to select that information and create a container or a label that represents that information and then drag and drop that information into the container. Right. So that's all about the coding. You identify information that is significant. You determine what code or label that you have to use. You go under their respective research question and create a code and drag and drop that information in there. So that's how the coding process is. Right. So it's a very simple process. This is what I want to emphasize. Don't treat coding focus group like coding individual interviews. For individual interviews, it's you and participants. You are having conversation with participants. And you are gathering that information. Sometimes participants will not elaborate upon what they have told you. Sometimes each of the responses is isolated. It's not really dependent on the previous statement. Right. But focus group is very different. Treat focus group as people coming together to construct knowledge. So you can see in focus group that an issue is brought up and people build on the issue. People elaborate. People go contrary to what the initial issue is. You have to look at conversational dynamics. Right. What is going on? Let's say you ask the participant a question. One of the participants has a question. They respond. Another person comes in. Maybe add more information to that or give an example. Right. Make that information personal or say something that is contrary. So you have to look at all the dynamics as you are going through the data. Right. Is information identified as significant? Add in value or more information to the previous statement participant has made. Was it a standalone statement? Is it built upon the previous one? Is it contrary to the previous conversation? Right. It is an example. You have to look at all these things as you go through the data. Right. Because think about it as people coming together to interact to construct knowledge. Right. And I think that's what is unique about focus groups. So you have to be aware of that as you go into the data. See how the pattern of conversation is happening. So that's how you have to think about it. Let me give you how the coding process happens so that you see what is really going on. Let's say you go into the data and you find something like this. Right. And you see that this one is more addressing research question one. Right. So what do you have to do? What do you have to do is first make sure that you understand what participant was saying. And then after understanding, you can also find out who's saying what. Right. Is it, you know, what was being said before? All these factors should be taken into consideration to better understand what participant is telling you. Now, if you understand what they're telling you, what do you have to do is that you have to come up with a label. Right. So let's say this one talks about equity and inclusion. Right. So what do you have to do is that you can go to research question one is because this one is addressing research question one, new code, and then you can put the type, the code there, and then you can check aggregate coding from children or you don't have to check. It's not required and click on OK. Now, as you can see here, we have created a container under the research question, but there's no information there. What you can do is you drag and drop that information into their code. So when you drag and drop, you see here that under file is one file connected to this one and also one statement. Right. There's another way of also doing this. Another way is you can right click on it and go to code selection, and then you can look for a container that can house this information. If there is no container, what you can do is you can click on the research question and then type here, click on child code and then type the label. So let's assume that this one is about community centered innovation. You type it and then make sure this one is highlighted or selected and then click on code selected to that code which is community centered innovation. When you do that, it will show here that this information has been coded. So there are two ways. One way is to create a container first, select and drag and drop. Second way is select it and right click on it and go to code selection and you'll be able to follow the steps to code into a new code or you can code it into an existing code. Right. If you want to code into an existing code, it's very simple. You right click on that, you go to code selection and let's say I want to code it into equity and innovation. I select that and then click on code selection to that and then that information will be dropped there. Right. So that's how the coding process you go through. If this information is significant, you make sure that you understand what the participant is saying and then you can drag and drop it into existing container or you have to create a new one. Right. And then drag and drop that information or right click and go to code selection to follow the process so that you'll be able to put that information there. So this is the principle. The coding process is whenever, let me show you what is happening here. Let me see. I think I've coded. So as you can see here, I finished coding my data. Right. So you see all this information have been coded and then you can see that this research question, these are the containers of the code. Right. So what I did was that I go to files and I double click on the file I'm interested in and I start a coding process. Right. Select information that is significant, create a container. So after that, you have to go to code so that you show the codes here and then start a coding process. If this information is significant, you first right click on the respective research question and then come up with a label. This can be in between two to five words. Right. Representing that information and also addressing your research question. If you identify something and you already have a code there, you can just drag and drop that information in there. Right. You don't have to create a new code. So that's how the coding process is. If you want to learn more about InVivo, my two-day workshop will be very helpful for you. It's going to happen on March 9th to March 10th. It's six hours in all, three hours on March 9th and three hours on March 10th. You will learn a lot. It's going to be hands-on. You'll learn a lot from using the software, whether you have a Windows version or you have the Mac version. I'll provide you step-by-step how to analyze your data, whether it's an interview data, whether it's an open-ended survey, whether it's focus group data. I will show you step-by-step how to use InVivo. So if you are new to InVivo, the workshop will be very useful for you. I'll put a discount code in the description section. You're going to get 25% off if you use the discount code. So I'm looking forward to seeing you there and I'll be happy to address any questions that you have about using InVivo. As you can see, there is a lot of codes. So the next process is to categorize the code to develop themes. I have a video about how to categorize code and develop themes. I think I'll put it up there and you click on that. So this is where you can export all the codes. If you want to export, you can right click here, go to export and export link and it will be in the Excel spreadsheet. And then you'll be able to use Word documents to group them. So you can group them. You group them based on similarities. At the end, this is what you're going to see. You have all your themes and then you bring your themes back to InVivo. So how do you do that? It's very simple. You just create containers for the themes and drag and drop that information. So let me give you an example. Let's say I already decided about my themes. I spotted all the codes. I categorized the codes and I developed the themes. So let me show you, let's say for research question one, you right click on the research question, new code, and then you put the theme there. You check aggregate coding from children and click on OK. So you see, before I go on, you see here is zero and zero. This means that I did not check aggregate coding from children. For the research question three, I right click on it and you see here aggregate coding from children and everything will add up and put it on top there. So make sure you check that. Now I have my theme. Now I have to drag and drop codes that are connected to this theme. So based on my categorization, increase transparency through shared guidelines. Increase transparency. This one can be dragged and dropped into this theme. And the next one is empowerment, empowering public. It's about, yes, public participation. Drag. You drag and drop. We can just select and drag and drop. And there's also education and knowledge. Another way of doing that is instead of dragging and dropping, you can right click on the code and then cut and then right click on the theme and paste. Right. So that information will be there. After that, you can do the second theme. So I right click here and new code. And then it's about proactive and adaptive accountability mechanism. And you can check aggregate coding from children and check OK. And then you can drag and drop that information in there. When you do that, this is what you're going to see. So you see all the codes here and my themes for each of the research questions. So this is a very simple process that you can pass through to analyze your data. After that, you can do many visual representation. I have a video about how to do visual representation. Here, I just want to show you how to clean your focus group transcript, upload all of them into InVivo, create containers for your research question, go through the data and create codes, categorize the codes to develop themes. And don't forget, if you have demographic information, you always have to use auto coding to extract all participant names from the transcript or the label that you are giving to participants from the transcript. And then it will create cases for each of the participants so that you can bring your demographic information and connect your demographic information to what participants said. Right. So that you can do further analysis. So this is what I have for you. Let me know whether you have any questions. I'll be happy to address them for you. Don't forget to subscribe to my channel. Thank you for your time.