What Is Thematic Analysis: The Definition
Thematic Analysis is about finding patterns to understand the meanings behind what others think, feel, know, or value. It involves looking at a group of qualitative data you’ve gathered.
This method follows your research goals and questions. Focus on the important parts that relate to your research questions, instead of trying to find every possible theme in the data.
Keep in mind that your research questions, even though they’re crucial for thematic analysis and more, can change as you go along. As you work with coding and identifying themes, your research direction might shift because thematic analysis is an exploratory process.
When is Thematic Analysis Used?
There are lots of ways to analyze a bunch of information. Some popular methods include discourse analysis, narrative analysis, and content analysis. But theme analysis is unique because it helps you find the big ideas and patterns that run through all the information.
But why apply a theme?
Thematic Analysis is useful when you’re dealing with large amounts of data. It helps break down and organize this data to make it easier to understand. This method is particularly helpful when you’re looking for personal experiences, opinions, and viewpoints of participants. Thematic Analysis is commonly used with data from social media posts, open-ended survey questions, interviews, and discussions.
You can decide to use Thematic Analysis based on your research questions. For example, if your questions are like:
- What do dog walkers think about the policies on dog-friendly beaches?
- How have students felt about transitioning to online learning?
- What beliefs on the Hippocratic code do medical professionals have?
- What role does gender play in a high school classroom?
All these questions focus on the participants’ personal experiences and aim to understand their opinions. Thematic Analysis is a good approach for these kinds of questions.
In short, What is Thematic Analysis is a helpful method if you have a lot of data to organize, especially when you’re interested in understanding people’s personal experiences and viewpoints.
The Principles Of Thematic Analysis
What are the principal methods?
The two main methods of ‘what is thematic Analysis‘ are deductive and inductive. Dependent on the objectives and research questions. Your strategy will be determined by what makes the most sense. Let’s examine the available choices.
- Inductive thematic Analysis
Using an inductive approach means figuring out the meaning and themes without having preconceived ideas. It’s like looking at data and letting patterns emerge naturally, rather than going in with specific thoughts about what you expect to find.
For example, if you’re studying typical lunchtime conversations among university staff, using an inductive approach means not going in with pre-decided categories or ideas. You might have some general expectations, like talking about scholarly matters, but the idea is to let the actual data guide your analysis rather than relying on assumptions.
The inductive approach works well when there hasn’t been much research done on a topic, and when you’re exploring new questions or goals.
- Deductive thematic Analysis
In contrast to the inductive way, using a deductive approach means starting your research with a predetermined set of codes. This method is usually guided by existing theories, research, and what we already know, which you discuss in your literature review.
For example, if a researcher is studying how a specific psychological intervention affects mental health outcomes, they might use a pre-established theoretical framework. This framework could have predefined codes related to concepts like coping mechanisms, social support, and self-efficacy.
The deductive method is most effective when there is a lot of previous research on the topic and when the study’s goals and questions aim to confirm existing knowledge.
Whether you’re focusing on the surface level or the deeper meaning of the data—called the semantic or latent level—you’ll need to decide whether to use an inductive or deductive approach. Semantically focused approaches look at things on the surface, without delving into the underlying meaning of the data, and identify themes solely based on what is written or expressed verbally.
On the other hand, a latent-level focuses on the underlying meanings and examines the causes of semantic content. Moreover, a latent approach incorporates an element of interpretation—that is, meanings are theorised. In addition to taking the facts at face value—instead of the semantic system.
How do I know when to use what approach?
It really depends on what kind of information you’re dealing with and what you want to achieve in your research. For example, if you already know what details you’re looking for, like clear opinions in interviews based on past research, you might use a deductive method. This works well when you want to focus on the surface level of information.
On the flip side, if you’re trying to understand the deeper meaning of what people in a focus group are saying and you’re not sure what to expect, you might choose an inductive approach.
In the end, how you analyze themes in your research depends on the nature of your study—specifically, the questions, goals, and objectives you’ve set for it.
What Kinds Of Analyses Are There Based On Themes?
Having grasped the broad approaches to theme analysis, it’s now appropriate to examine the many forms of thematic Analysis that can be carried out. There are three “types” of thematic Analysis, broadly speaking:
- Reflexive Thematic Analysis that
- Thematic examination of codebooks
- Thematic examination of coding reliability
Let’s examine each of these in turn:
Using an inductive methodology, reflective thematic Analysis allows the codes and themes to surface from the data. The flexibility of this kind of thematic analysis lies in its ability to let researchers add, edit, and remove codes. As they go through the data. Reflexive thematic Analysis example, as the name implies, strongly emphasises the researcher’s active participation. Critically reflecting on their presumptions, biases, and interpretations, as well as how these may affect the Analysis.
Reflexive Thematic Analysis
Reflexive thematic analysis typically entails iterative and reflexive cycles of coding, interpreting, and reflecting on data. To produce nuanced and contextually sensitive insights into the research topic. At the same time, it recognises and addresses the subjective nature of the research process.
CodeBook Thematic Analysis
On the other hand, codebook thematic analysis is quite different. This analysis method uses organized codebooks with already-decided codes and follows a deductive approach. Typically, these codes bring together existing academic theories, research, and past information about a situation.
The aim of codebook what is thematic analysis is to produce reliable and consistent results. It is often used in studies where having a clear and set coding system is crucial to make sure the interpretation of data is thorough and consistent.
Coding dependability: Multiple coders are required for thematic Analysis example, and the design is specifically suited for research teams. Codebooks are usually fixed and rarely changed in this type of research.
Why Use Thematic Analysis
The advantage of this type of Analysis is that it introduces an element of intercoder reliability. By requiring coders to agree on the codes used. Which implies that the output is more rigorous because subjectivity is decreased. In other words, numerous coders debate which regulations should and should not be used. Causing this consensus removes the bias of having a single coder decide on themes.
Essential Steps To Do Thematic Analysis
Step 1: Get Knowledge of the data
To start analyzing your data in a what is thematic analysis, the first steps are to understand your data and find the main themes. This involves transcribing the information, turning spoken words into written text if needed.
Think about what you want to label or code in your data. Decide on the codes you want to use and choose ones that capture the main ideas. Consider your study topic and goals. For example, you could categorize data based on specific dog breeds mentioned, like border collies, labradors, and corgis. Also, pay attention to feelings or emotions when people talk about different dog breeds.
Keeping a reflective journal is a good idea. In this journal, describe how you’re coding the data, why you chose certain codes, and what results you’re getting from your coding. This journal will be helpful later in your analysis, allowing you to check if you coded accurately and if your codes and themes support your findings.
Having a reflexive diary helps you examine your data systematically and consistently, which makes your analysis more reliable. Take notes in your diary about your initial codes, and you can later refine them or break them down into more specific codes as your research progresses.
Step 2: Examine the codes for patterns or themes
You’re doing well! Now, in this phase, look for patterns or themes in your codes. It might be a bit challenging to shift from general ideas to specific details. As you get more used to the data, you might need to use different codes or themes for new things you discover.
For instance, if you’re studying a document about animals, you might find codes like “pigeon,” “canary,” and “budgerigar,” which are all related to birds.
While going through the data, you might notice smaller themes or parts of themes. These focus on a specific aspect of the main theme that is important to your research. For example, if you’re studying a university, your smaller themes could be different faculties or departments within that university.
Make sure your notes in your reflexive diary show how you interpreted and combined codes to create themes.
Step 3: Examine themes
Now, it’s important to really understand your codes, themes, and maybe smaller themes. At this point, you need to review all the themes you found thoroughly. Check to make sure each theme fits the data exactly. Confirm that all the themes you identified are actually in the data and that none are missing. With this done, you can confidently move on to the next step, knowing you’ve coded each theme thoroughly and correctly.
If you find that one theme is too broad and includes too much information, it might be helpful to break it down into smaller themes. This makes the analysis more precise.
In your reflexive diary, write down how you understood the themes, how the evidence supports them, and how the themes relate to your codes. Also, take a moment to review your research questions and make sure the data and themes are closely connected to what you’re trying to find out.
Step 4: Conclude Themes
Now, your analysis is starting to take shape. After going through and refining your themes in the last step, it’s time to label and finalize them. It’s important to note that moving on to the next step doesn’t mean you can’t go back and make changes to your themes if needed.
Unlike the previous step, finalizing themes means giving detailed descriptions of each theme. If you’re unsure, you can go back to step 3 to check if your themes still match your data and coding, or if you need to break them down into smaller themes.
When naming your themes, make sure the names accurately describe what they are about. For example, instead of “enthusiasm in professionals,” it’s better to be more specific, like “enthusiasm in healthcare professionals,” as it answers the question “Who are the professionals?”
At this point, make sure your themes align with your research goals and questions. When you finalize your themes, it means you’re getting close to wrapping up your analysis. Keep in mind that your final report, which we’ll discuss later, should align with the aims and objectives of your research.
Include a few sentences in your journal about reflexivity, explaining your themes and how you came up with them. Also, mention how each theme will impact your investigation’s results and what it means for your research questions and overall focus.
After this step, your themes will be complete, and you can start writing a report summarizing your findings.
Step 5: Write your report.
You’re almost finished! After you’ve looked at your data, it’s time to share what you found. A typical report for thematic analysis example has these parts:
- An introduction
- An explanation
- How you did your research
- Methods you used
- Your findings and results
- Sharing your thoughts
- Wrapping it up
When you’re writing your report, make sure to include enough information for someone to understand how carefully you did your analysis. This means explaining the specific steps you took and why. Use words like “what,” “how,” “why,” “who,” and “when” to guide you.
Answer questions like: What did you study? How did you study it? Why did you choose this way of studying? Who is your research about, and who took part? When did you do your analysis, collect data, and publish results? Your reflexive diary can help here because you’ve already listed, explained, and supported your themes.
For each theme, provide proof like quotes, examples, or numbers. Look at our guide on law dissertation help structure for more details on these sections.
When writing about your findings, use quotes to support everything you say. The reader should see that what you’re talking about is in the results. Also, connect your findings to your research questions. You want your reader to understand why your results matter. Make sure every result you share relates to your study topic and questions.
Types Of Thematic Analysis
Inductive and deductive techniques are the two main types of thematic Analysis.
Inductive Technique
An inductive technique is entering the study blindly. By allowing the data-capture results to influence and shape the analysis and theming. Consider it like induction heating: the data heats the results! Parachuting onto a client without knowing anything about their website and realising the checkout was difficult due to the number of individuals that brought it up.
This is an example of an inductive method. A simple theme!
Deductive Technique
On the other hand, a deductive technique entails addressing the data with certain preconceived concepts. Which you expect to find in qualitative data based on a theory. For example, suppose you believe your company’s website navigation is difficult because the writing is too small. You may browse for themes such as “small text” or “difficult navigation.”
To get even more specific, there are two forms of theme analysis: semantic and hidden thematic Analysis. These are more advanced, but we’ll include them in case.
Semantic Thematic Analysis
Semantic thematic Analysis example entails detecting data themes by analysing the phrasing of participant responses. Latent thematic Analysis identifies themes in data by analysing underlying meanings. As well as the actions taken but not necessarily declared by study participants. These two methodologies are powerful tools for user research. But latent Analysis is more popular because consumers frequently say things that are not true.
What is Thematic Analysis Limitations?
Thematic Analysis is a slow and hands-on way of sorting through lots of survey responses and putting them into categories, and it can take days or even weeks. This can be a problem for busy organizations that need quick results.
Because Thematic Analysis example takes a lot of time, usually one person does most of the work. According to Ajantha, this causes a problem at Art.com. Having only one person put together the insights report doesn’t make sure that everyone who needs to know about customer feedback really understands it.
Thematic Analysis often finds common themes, thinking that if something comes up a lot, it must be important. But assuming that just because something is mentioned a lot means it’s important isn’t always true. While this approach works well for hearing from current customers, it might not be the best for finding new ideas in research projects.
Finishing Up
Now you’re equipped with the basic tools of theme analysis! Whether you’re studying interviews, tweets, or even song lyrics, you can use this approach to find the heart of what matters. Go forth and uncover the hidden patterns in your data!