How to Create a Cloud Scale for Reflexive Thematic Analysis (Full Transcript)

[00:00:00] Speaker 1: I'm going to use the Cloud Neo model to help me to create a scale, and that scale will also help me to analyze my qualitative data. So what is a scale? A scale is just an instruction that is installed in Cloud, and you can always refer to that instruction if you want to do the same, if you want the system to do the same task for you. So let's say you want a system to do reflective thematic analysis for you. So you develop a scale, and then you save it in the system, and then whenever you want the system to do thematic analysis, you make reference to that instruction, and then quickly the system uses that instruction to help you to analyze the data. So this is what we're going to try. I haven't tried it before. Fibbo just came today, so I'm just going to try it out and see how it works, and then we are going to learn together. So I have an article here. Let me show you the article. It provides step-by-step how to conduct reflexive thematic analysis, right? So you can see that there are six steps that you need to follow to complete a reflective thematic analysis. So what I'm going to do is I'm going to give this article to the system. First, I want the system to read the article and learn a little bit about it before I ask it to develop a scale that I can use to help me to analyze my qualitative data. So we go to Cloud AI, and then make sure that you have the new model, which is Fibbo05, and then I'm going to attach this article here about reflexive thematic analysis. So I'm going to type an instruction here for the system to review and learn more about this article before I ask it to create a task or create a scale. So this is an instruction that I've provided to the system. So I'm asking it, as an experienced qualitative researcher, can you review the attached article on reflexive thematic analysis, learning all the six phases, and share what you have learned. So let's see what the system will do. So it looks like the system has gone through the article and provided what it has learned. So it talks about a theoretical groundwork that needs to be taken into consideration if you want to take the steps of using reflexive thematic analysis. And then it provided all the six phases and gave an explanation concerning that. This is perfect. So the next one is to ask the system to create a scale that you can use to help you to analyze your data. Okay, so my next step is to prompt the system to develop a scale. So I said, based on what you have learned, can you create a scale MD? So it's called scale markdown, so MD, scale.md. Detailing the steps a qualitative analyst needs to take to complete analyzing qualitative data. So let's go. So the system is going to develop a scale. It will take some time for it to finish. And after that, we go ahead and use those scales to analyze our data. If you want to see all the scales that you have created, you go to your account, click on your account, and go to settings, and then you go to capabilities. And then you go down here, custom, and then you have all the scales that you have created. If you have created some, right, so you see all the scales, you can just click on them and see what you have done. You can also share the scale if anybody who can use cloud can also access your scale. If you don't want to share, you can disable it. So let's go back and see what is going on. So we're still working on creating the scale for us. Oh, perfect. It looks like we have the scale here. So as you can see here, they start with a brief introduction about what a scale is all about, right, and then it also gives details about the call stance, so things that it has to do and things that it doesn't have to do. So think about it as instructions whenever you want to analyze your data using reflective thematic analysis process. So you have your phase one and then phase two. It's always important for you to review. If you want to have any changes, you can always type here and ask the system to move something or add some information there for you to complete the scale. When you finish, the next step is to save the scale. So if you want to save the scale, you see here, save here. You can click on it to save. You can also see save here, right. If you don't see anything like save here, you can first download, right. So we download it and then it will be downloaded on your computer and then what you have to do is that you go to your account and go to settings and then go to capabilities and then you see you scroll down and go to customize under scale and then you'll be able to add a scale. You see here, add and then you can upload a scale. The one that you just downloaded. So you click on this one and then you check on your computer. You go to downloads and you see the scale, the reflexive thematic analysis scale. You select that. You open and then you have your scale here. So now you can use your scale. You can share if you want to share. Enable share so that other people can use. If you don't want to share, you can just disable it. When you are done, you go back to the main page, new chat, right, and this is where you can use the scale, right. So before we start using it, let me show you the data set I'm going to use. This is the data set I'm going to use about five participants. It's about burnout among primary healthcare physicians and then I just want to find out what are the causes of burnout. Let's try to answer the two questions, right, and then so what we're going to do is we're going to provide the system the purpose of the study and also the two questions that I want to answer and then let the system go through the process and then analyze the data for us. So whenever you want to start the analysis, you press on your keyboard, splash, right. When you press on splash, this is what you're going to see. All the scale will be shown here and then you look for the scale that you want. So we want the reflexive thematic analysis. We select that and then you start the process. Can you analyze the attached data using reflexive thematic analysis? And then what I'm going to do is that you always have to give the system a little bit of background of your study. What is your study about? What is the purpose of your study? Any information that will help the system to know more about your study is always good. Giving background information improves the results or improves the outcome. So I've provided a little bit of the background and then I also have my two research questions. As you can see, I say make sure you address the following research questions. I have my two research questions about the causes and solutions of burnout. So I'm going to attach the five transcripts. So let me see here. So I'll attach the five transcripts and then let me click on enter. It takes time for the system to finish this analysis because it has to first go back again and review the instructions, which is the scale, making sure that any action and decision is based on the scale and all the it has to also review all the transcripts and then follow all the six steps. So it takes some time, maybe about 10 to 15 minutes for it to finish the analysis. Okay, so it looks like everything is done now. So let's review and see what is provided to us so that we just have an understanding of what it did. So as a qualitative researcher, you always have to review the output, making sure that everything is right. And I always emphasize that before you ask the system to provide you any information in terms of data analysis, you also have to have the skill in analyzing the data because your role here is to review what the system has given you. And if you don't have a skill about maybe reflective thematic analysis, how will you know whether the system has done things right? Because it can make mistakes, it can hallucinate. So you always have to, you know, first have at least a basic understanding about the analysis before you try to use it to help you to make sense of your data. As I have an understanding of reflexive thematic analysis, so I'll be able to review, I know all the steps, I know what is required, and then assess. And also be ready to ask the system a question if you are not clear about anything. You always have to be skeptical. So let's start the process. I think I provided a long report about the steps and then what it did. So this is just giving you brief information about what kind of data it is. It was from seven structured interview transcripts from five participants. And then these are the two research questions that I was following. So the step zero. So the step zero is all about, you know, understanding the philosophical paradigm that informed the reflexive thematic analysis. This one provided some information that you can review. So the emphasis of constructivism. And then I can also see inductive and deductive. So most of that, it emphasized more about inductive process. So the inductive means that you allow the data to suggest goals and themes for you. So everything is based on the data. The themes or the goals that you come up with, they are all based on the data, right? Okay, so let's go here. The most important is the phases, right? The first phase is familiarizing yourself with the data, right? So the system read all the transcripts, making sure that it understands everything about what the participant is saying. And then it also took some notes based on what it read. So that's also about memory, reflexive memory, trying to capture all the things that come into mind as you're trying to understand what the participants are saying. So we move on to the next one, which is generating initial codes, right? So this is where you go through the data, identify information that has significant and develop codes that will help you to address your research questions. So you see that the significant information, any information that can address your research question, this one is more about the process of burnout and that was used. I personally think that this code is too long, right? A code, a good code should be in between two to five words, right? So that it can be easily consumed by your audience and also you as you go through the data. So I like the shorter version here, the first iteration one, because it's between two to five words. A longer one can be good, but I think it's long. It's not bad, but I was thinking that if I have the chance, I can review them to make sure that. So this, you go into all the participants, identify information that is significant. It looks like it's about 25 quotations and then it came up with codes and then it also provided memos, because it's all about reflexive, what goes into your mind, what is your understanding, what is the assumptions and then that will help you to further analyze the initial code so that you'll be able to develop themes. So the next phase is generating themes. So you can see that the system was able to categorize the codes and generating themes, right? So the candidate theme A, which is work that outgrows the working day. So that's addressing the research question one. And look at this definition of that theme and this second thing is like a potential themes, right? It's not a main theme yet, because the next step is to revise the theme so that you can have the final theme. So that's why maybe it's called candidate theme. So it's technically what the system did is what it categorized all the codes and then named the clusters, which is the candidate themes, right? I call it initial themes, right? Then it reveals the theme and then came up with a final theme, right? So reveal the themes and then came up with a final theme. So these are the themes and then for the research question one and also the resolution for the research question two. So the next step is to define the themes, right? So these are the themes, okay? And this addressing the first research question, it defines the theme and also provide quotation in supporting of the theme, right? So making sure that the themes are based on the data. So then the system did a second one with the second theme, carrying someone's expectation. And then it also has sub-themes. Interesting. It came up with sub-themes too, right? And then we have nothing left for home. It defines it and also provide the quotations and who are linked to the theme. And then this one is your theme four, team five, and then so which one? Okay, so this one is addressing research question two, this one is addressing research question two, this one is addressing research question one. So there are two themes addressing research question two and then we have three themes addressing research question one. So now I'm going to go to the next one, which is the report, right? Reporting the findings. So it has a narrative summary of the findings and then answer how the themes answer the research question. So it uses some of the themes to address the research question. The report is not all that long. If I have the option, I would have let the system provide more information about reports. You can even tell the system, can you enlarge your report? And also the themes are not a lot for me. So I will suggest to the system that can you break the themes for the research question two into about maybe four or five themes and the research question one to about four or five too, right? Because I think that when you have a small number of themes, two or one, you'll sometimes lose the richness of the data, right? So I always like that having about three, maybe four, five themes is very good so that all the theme can capture some of the rich information that you want to share to your audience. It did well, but I was thinking that if I want to further refine the information here, I would suggest to the system to develop more themes and then recategorize the codes and develop themes and also the report should be more detailed. So by so far, it did a very good job. It provided me detailed information about what it did and then the rationale, the reason behind each of the steps and also the strategies that it used, right? So let me know your thoughts. What do you think about it? I wish you can also do the same. I will put the link to the data set in the description so that you can also try it out and see what you will get after creating the skill and also using that to help you to analyze your data. So the same way that you created a skill, you can create different skills. You can create a skill that will review your document. You can create a skill that will help you with your writing. You can create a skill that will help you with your choosing the right methodology for your study. You can create a skill to develop a theoretical framework. You can create any skill that you want. Anything that you do it more than one time, creating a skill will be good. So whenever you want to do the task, you just refer to the skill. So this is what I have for you. Thank you for your time.