Reflexive thematic analysis har developed much since 2006, so I wonder why more current literature from B & C is not used to elaborate on the method, as themselves suggest so.
Please have a look in the video description, where I cite their 2021 update. The video is based on the original paper as well as the update from 2021. Best wishes :-)
I see that, but nevertheless I would recommend not using the 2006 paper as a reference anymore, but base the analysis on the 2022 textbook Thematic Analysis: A Practical Guide (Sage).
Hi! Thank you for the video! Would you recommend it to find out the best practices of how to mitigate price volatility in the supply department? My objective is to recommend those practices to a company. Thank you!!!!
Thank you for your comment. I am not sure if I can answer your question without knowing more about the context, research question, and so on. You can definitely derive practical implications such as recommendations to managers but make sure you also tackle a research problem (i.e. a theoretical problem or important research gap). Best of luck! 🤞
My research Questions actually state what "Barriers" and "Challenges" are being faced as well as what "Drivers" and "Advantages" there are... would I still not use these buckets?
Hey, thanks for your question. Your research question(s) and themes are two different things. You could keep the RQ(s) and then develop themes that are barriers and drivers etc. but those should not be coding buckets as I explained in the video. This would lead to having "a digital mindset" and "risk tolerance for innovation" (just random examples) inside one coding bucket - but what you want to do with the method is develop them as independent themes (with concrete data examples and subordinate codes for each). That's why these buckets should be avoided. One way to avoid asking about "disadvantages" and "advantages" etc. in research questions is by changing the question to a "how" question: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-hB-BS1xDU2M.html Best of luck! :-) Phil
This is the best video on what TA is and how to conduct, thank you! Are you using the term "category" just to mean "code" for the purpose of making it more understandable for those new to TA? or do you actually distinguish a bit?
Thanks! For TA it is sufficient to refer to codes and themes. Sometimes different authors use different labels although it is the same. The first method I Iearned was qualitative content analysis, where codes are „categories“. But Braun and Clarke don’t use that term so I would stick to the vocabulary that is used by the authors that you cite for a particular method. Best wishes, Phil
They can be. Let's say you ask: How do game developers create digital safe spaces for female gamers?, then a handful of themes that describe how these safe spaces are created can be a great answer to the RQ. But themes do not have to be the exact answer to a RQ. They can simply be the result of conducting the method of thematic analysis which is part of a larger study with a broader or multiple RQs. Best of luck!
Hi, thank you for your question. If you use predefined themes, you are using thematic analysis with a deductive (i.e. top-down) logic. Here, you can derive themes from an existing theoretical framework, for example. You can develop some additional themes or subthemes inductively (i.e. bottom-up) but then you are mixing two logics and need to be very deliberate in what you are doing. I would not advise you to take themes from your research questions - this is not exactly what the method intends to do. Have a look at the Braun and Clarke papers, they give great examples and then it will „click“ for you :) best of luck 🤞
This video was super useful, I've been avoiding step 3 for so long because I thought it was too complex for me to go further, this was very helpful and encouraging! When you say themes should be based on you data and categories, do you mean desktop research as well? Or should this be kept seperate? (I've done 9 interviews varying of 4-10 pages each if this is relevant to the question)
Hi Anna, thanks for your comment. I'm glad the video could help you a little bit. It depends on your research design. If you combine a (systematic) literature review and your interviews as your method, then I would analyse both separately with TA and report the results separately as well. Then merge what you found in the discussion. If you do a non-systematic literature review that is not part of your research design, then only analyse your interview data with TA and write a strong background section based on the literature you have collected and read. Best of luck! Philip
Hi, thanks for the video, very useful. Can you provide more information as to why and how to avoid using "thematic buckets", and basically what is wrong with advantages, disadvantages, barriers or challenges if we're using thematic analysis with a deductive approach? Thanks
Hi, thanks for your question. In a deductive approach, you would have your themes predefined by existing literature and/or theory. Nothing wrong with theses "buckets" here, but you need a good justification and enough literature that back these up. In inductive TA, buckets are more problematic because the interpretative element gets lost. You want a theme that represents the data and not a label that groups them. Best of luck!
Thanks for your comment. This will be a niche tutorial but I will give my best to cover it at some point. Producing these takes time, so in the meantime don't hesitate to ask specific questions here in the comments. Best of luck! Phil
Hi, you can ask me anything :) Yeah, I don't want you to get in trouble so when you use AI, please always disclose in your methods section how you used it. It is possible to use AI tools and many software tools for qualitative coding already have AI-powered plugins to support with coding. My take is that AI can be a great help on the first level of abstraction. This means assigning codes to a large body of text or other data. In principle, this part of thematic analysis and any other qualitative method is pretty mechanistic and does not require a lot of creativity - so its perfect for AI. Once you get to the higher levels of abstraction - in this case themes, I would move away from the AI and interpret the codes yourselves to create something new. The disadvantage if you use AI in the coding stage is that you do not familiarise yourselves with the data and this will make it harder to interpret it later. If you want to dive deeper into how to use AI I made a tutorial about ChatGPT and qualitative data analysis: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-CvCdERtCoC8.html best of luck! :) Phil
@@masteryourstudies Hello, thank you for your reply, my problem is that I am currently writing a memory (for my last years master in psychologie) with a qualitative analysis. I have 4 semi-structured interview groups of 6 each, which makes 24 interviews to analyze separately. I'm afraid that during my re-reading I won't be able to find the codes and themes easily. I find myself a bit lost and it's stressing me out, hence the AI question, as it seems more precise to me. What do you think? Many thanks
@@masteryourstudies In my semi-directive interview, I have 8 questions and each subject answers in a different way. I'm afraid I'll end up with a lot of codes, so what can I do? Is there a code-sub-code hierarchy system? Thank you for your answer.
