Thematic Analysis - Presentation101.pptx

sample

1. THEMATIC

2. What is thematic analysis? Thematic analysis is a qualitative data analysis method that involves reading through a data set (such as transcripts from in depth interviews or focus groups), and identifying patterns in meaning across the data to derive themes. Thematic analysis involves an active process of reflexivity , where a researcher’s subjective experience plays a central role in meaning making from data.

3. When should I use THEMATIC ANALYSIS ? You should consider using thematic analysis in the following scenarios. You want to identify patterns in data You are new to qualitative analysis You want to involve research participants in the analysis process

4. What are the advantages and disadvantages of thematic analysis ? Advantages of Thematic Analysis Thematic analysis is a flexible approach to qualitative analysis that enables researchers to generate new insights and concepts derived from data. One of many benefits of thematic analysis is that novice researchers who are just learning how to analyze qualitative data will find thematic analysis an accessible approach.  Disadvantages of Thematic Analysis Because thematic analysis is such a flexible approach, it means that there are many different ways to interpret meaning from the data set. It can feel intimidating  to interpret what data is or isn’t important to emphasize. Furthermore, since thematic analysis focuses on looking for patterns across interviews, phenomena that occur in only one individual account can be overlooked. Additionally, a limitation of thematic analysis is that you don’t use existing theoretical frameworks, which could limit the interpretive power of your analysis.

5. What is the step by step process of how to do thematic analysis ?

6. 1. Familiarize yourself with the data Get familiar with the data. If your data is in the form of audio files, transcribe them yourself or get them transcribed (see how to transcribe interviews). Read through the transcripts and actively observe meanings and patterns that appear across your data set. You won’t be formally creating codes yet, but you should jot down thoughts and memos about potential codes to create.

7. 2. Create your initial codes Now that you’re familiar with the data, practice thematic analysis coding, and create a set of initial codes that represent the meanings and patterns you saw in the data. Create a codebook to keep track of the codes. Read through your data again, and identify interesting excerpts and apply the appropriate codes to them. Excerpts that represent the same meaning should have the same code applied.

8. Sample Work-life balance: Struggle to separate work and personal life, longer work hours. Productivity: Increased productivity, distractions at home. Communication: Difficulty in team communication, frequent virtual meetings. Technology: Reliance on technology, technical issues . Mental health: Increased stress, feeling isolated.

9. 3. Collate codes with supporting data Now, group together all the excerpts associated with a particular code. If you’re using pen and paper, cut out the excerpts and group them together by code. If you’re using CAQDAS software like Delve , this thematic analysis software will automatically collate them together for you.

10. here is an example of collating initial codes with supporting data from interview excerpts: Work-life balance: "I find it hard to separate work and personal life; I'm often working late into the night." "My work hours have extended, and I feel like I'm always on the clock." Productivity: "I’ve noticed an increase in my productivity since I started working from home." "There are a lot of distractions at home, which sometimes make it hard to stay focused." Communication: "Communicating with my team has become more challenging; we don’t interact as much as we used to in the office." "We have frequent virtual meetings, which can be tiring and sometimes ineffective." Technology: "My work now heavily relies on technology, which can be a double-edged sword." "Technical issues often disrupt my workflow and cause frustration." Mental health: "I feel more stressed working from home, and the isolation is starting to affect my mental health." "Not having my colleagues around has made me feel quite isolated."

11. 4. Group codes into themes Now that you have a set of initial codes, sort the codes into potential themes. Themes in qualitative research are a powerful way to see trends and patterns in your data. See how various codes can be combined, and see if there are themes that can be made into sub-themes.

12. Based on the collated codes and supporting data, we can group them into broader themes. Here's how the initial codes might be organized into themes: Work-Life Integration: Work-life balance: Struggle to separate work and personal life, longer work hours. Family dynamics: Managing family interruptions, spending more time with family. Productivity and Efficiency: Productivity: Increased productivity, distractions at home. Flexibility: Enjoying flexible hours, managing time better. Communication and Collaboration: Communication: Difficulty in team communication, frequent virtual meetings. Technology: Reliance on technology, technical issues. Well-being: Mental health: Increased stress, feeling isolated. Physical health: Reduced physical activity, ergonomic issues.

13. 5. Review and revise themes Now that you have your initial set of themes, review and revise your themes. Ensure that each theme has enough data to support them and is distinct. Consider merging together themes that are similar, and removing themes that don’t have enough data to back them up. Begin formulating how your themes can come together into a narrative.

14. 6. Write your narrative Writing the narrative is the final step to tell the story of your data. You should have fully thought out themes, and now it’s your chance to communicate to your readers about the validity or your analysis. Make sure that your narrative tells a coherent story about your data, and choose vivid quotes from your data that help back up your points. Your narrative should go beyond just describing your data and should include your own interpretive analysis and make an argument for the claims you present.

15. Tips for thematic analysis

16. Interpret and analyze, don’t just paraphrase  It can be easy to get stuck in a loop of summarizing and paraphrasing your data. Instead you should use your own interpretive lens to derive meaning from the data.

17. Themes should be identified from the data, not your research questions Don’t fall into the trap of structuring your data according to research questions. This will lead to your themes just being representation of your research questions. Make sure you’re actively finding patterns and meaning from your data.

18. Ensure themes have enough data to be convincing Evaluate whether or not a theme has enough data to back it up. There isn’t a specific rule or number of excerpts to prove the existence of a theme, but make sure that you can make a convincing case to show that this is a recurring pattern.

19. Ensure data supports your themes, and your themes support your narrative Check to make sure that your themes are accurately represented in the data, and that your narrative is backed by your themes. Double check the connections between each step in your analysis and ensure that you weren’t making too many jumps between each step. 

20. " Now, let's engage in the activity comparing navigating software versus manual methods."