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Methodology

• How to Do Thematic Analysis | Step-by-Step Guide & Examples

How to Do Thematic Analysis | Step-by-Step Guide & Examples

Published on September 6, 2019 by Jack Caulfield . Revised on June 22, 2023.

Thematic analysis is a method of analyzing qualitative data . It is usually applied to a set of texts, such as an interview or transcripts . The researcher closely examines the data to identify common themes – topics, ideas and patterns of meaning that come up repeatedly.

There are various approaches to conducting thematic analysis, but the most common form follows a six-step process: familiarization, coding, generating themes, reviewing themes, defining and naming themes, and writing up. Following this process can also help you avoid confirmation bias when formulating your analysis.

This process was originally developed for psychology research by Virginia Braun and Victoria Clarke . However, thematic analysis is a flexible method that can be adapted to many different kinds of research.

Table of contents

When to use thematic analysis, different approaches to thematic analysis, step 1: familiarization, step 2: coding, step 3: generating themes, step 4: reviewing themes, step 5: defining and naming themes, step 6: writing up, other interesting articles.

Thematic analysis is a good approach to research where you’re trying to find out something about people’s views, opinions, knowledge, experiences or values from a set of qualitative data – for example, interview transcripts , social media profiles, or survey responses .

Some types of research questions you might use thematic analysis to answer:

• How do patients perceive doctors in a hospital setting?
• What are young women’s experiences on dating sites?
• What are non-experts’ ideas and opinions about climate change?
• How is gender constructed in high school history teaching?

To answer any of these questions, you would collect data from a group of relevant participants and then analyze it. Thematic analysis allows you a lot of flexibility in interpreting the data, and allows you to approach large data sets more easily by sorting them into broad themes.

However, it also involves the risk of missing nuances in the data. Thematic analysis is often quite subjective and relies on the researcher’s judgement, so you have to reflect carefully on your own choices and interpretations.

Pay close attention to the data to ensure that you’re not picking up on things that are not there – or obscuring things that are.

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Once you’ve decided to use thematic analysis, there are different approaches to consider.

There’s the distinction between inductive and deductive approaches:

• An inductive approach involves allowing the data to determine your themes.
• A deductive approach involves coming to the data with some preconceived themes you expect to find reflected there, based on theory or existing knowledge.

Ask yourself: Does my theoretical framework give me a strong idea of what kind of themes I expect to find in the data (deductive), or am I planning to develop my own framework based on what I find (inductive)?

There’s also the distinction between a semantic and a latent approach:

• A semantic approach involves analyzing the explicit content of the data.
• A latent approach involves reading into the subtext and assumptions underlying the data.

Ask yourself: Am I interested in people’s stated opinions (semantic) or in what their statements reveal about their assumptions and social context (latent)?

After you’ve decided thematic analysis is the right method for analyzing your data, and you’ve thought about the approach you’re going to take, you can follow the six steps developed by Braun and Clarke .

The first step is to get to know our data. It’s important to get a thorough overview of all the data we collected before we start analyzing individual items.

This might involve transcribing audio , reading through the text and taking initial notes, and generally looking through the data to get familiar with it.

Next up, we need to code the data. Coding means highlighting sections of our text – usually phrases or sentences – and coming up with shorthand labels or “codes” to describe their content.

Let’s take a short example text. Say we’re researching perceptions of climate change among conservative voters aged 50 and up, and we have collected data through a series of interviews. An extract from one interview looks like this:

In this extract, we’ve highlighted various phrases in different colors corresponding to different codes. Each code describes the idea or feeling expressed in that part of the text.

At this stage, we want to be thorough: we go through the transcript of every interview and highlight everything that jumps out as relevant or potentially interesting. As well as highlighting all the phrases and sentences that match these codes, we can keep adding new codes as we go through the text.

After we’ve been through the text, we collate together all the data into groups identified by code. These codes allow us to gain a a condensed overview of the main points and common meanings that recur throughout the data.

Next, we look over the codes we’ve created, identify patterns among them, and start coming up with themes.

Themes are generally broader than codes. Most of the time, you’ll combine several codes into a single theme. In our example, we might start combining codes into themes like this:

At this stage, we might decide that some of our codes are too vague or not relevant enough (for example, because they don’t appear very often in the data), so they can be discarded.

Other codes might become themes in their own right. In our example, we decided that the code “uncertainty” made sense as a theme, with some other codes incorporated into it.

Again, what we decide will vary according to what we’re trying to find out. We want to create potential themes that tell us something helpful about the data for our purposes.

Now we have to make sure that our themes are useful and accurate representations of the data. Here, we return to the data set and compare our themes against it. Are we missing anything? Are these themes really present in the data? What can we change to make our themes work better?

If we encounter problems with our themes, we might split them up, combine them, discard them or create new ones: whatever makes them more useful and accurate.

For example, we might decide upon looking through the data that “changing terminology” fits better under the “uncertainty” theme than under “distrust of experts,” since the data labelled with this code involves confusion, not necessarily distrust.

Now that you have a final list of themes, it’s time to name and define each of them.

Defining themes involves formulating exactly what we mean by each theme and figuring out how it helps us understand the data.

Naming themes involves coming up with a succinct and easily understandable name for each theme.

For example, we might look at “distrust of experts” and determine exactly who we mean by “experts” in this theme. We might decide that a better name for the theme is “distrust of authority” or “conspiracy thinking”.

Finally, we’ll write up our analysis of the data. Like all academic texts, writing up a thematic analysis requires an introduction to establish our research question, aims and approach.

We should also include a methodology section, describing how we collected the data (e.g. through semi-structured interviews or open-ended survey questions ) and explaining how we conducted the thematic analysis itself.

The results or findings section usually addresses each theme in turn. We describe how often the themes come up and what they mean, including examples from the data as evidence. Finally, our conclusion explains the main takeaways and shows how the analysis has answered our research question.

In our example, we might argue that conspiracy thinking about climate change is widespread among older conservative voters, point out the uncertainty with which many voters view the issue, and discuss the role of misinformation in respondents’ perceptions.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Discourse analysis
• Cohort study
• Peer review
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias
• Social desirability bias

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• How it works

Thematic Analysis – A Guide with Examples

Published by Alvin Nicolas at August 16th, 2021 , Revised On August 29, 2023

Thematic analysis is one of the most important types of analysis used for qualitative data . When researchers have to analyse audio or video transcripts, they give preference to thematic analysis. A researcher needs to look keenly at the content to identify the context and the message conveyed by the speaker.

Moreover, with the help of this analysis, data can be simplified.  

Importance of Thematic Analysis

Thematic analysis has so many unique and dynamic features, some of which are given below:

Thematic analysis is used because:

• It is flexible.
• It is best for complex data sets.
• It is applied to qualitative data sets.
• It takes less complexity compared to other theories of analysis.

Intellectuals and researchers give preference to thematic analysis due to its effectiveness in the research.

How to Conduct a Thematic Analysis?

While doing any research , if your data and procedure are clear, it will be easier for your reader to understand how you concluded the results . This will add much clarity to your research.

Understand the Data

This is the first step of your thematic analysis. At this stage, you have to understand the data set. You need to read the entire data instead of reading the small portion. If you do not have the data in the textual form, you have to transcribe it.

Example: If you are visiting an adult dating website, you have to make a data corpus. You should read and re-read the data and consider several profiles. It will give you an idea of how adults represent themselves on dating sites. You may get the following results:

I am a tall, single(widowed), easy-going, honest, good listener with a good sense of humor. Being a handyperson, I keep busy working around the house, and I also like to follow my favourite hockey team on TV or spoil my two granddaughters when I get the chance!! Enjoy most music except Rap! I keep fit by jogging, walking, and bicycling (at least three times a week). I have travelled to many places and RVD the South-West U.S., but I would now like to find that special travel partner to do more travel to warm and interesting countries. I now feel it’s time to meet a nice, kind, honest woman who has some of the same interests as I do; to share the happy times, quiet times, and adventures together

I enjoy photography, lapidary & seeking collectibles in the form of classic movies & 33 1/3, 45 & 78 RPM recordings from the 1920s, ’30s & ’40s. I am retired & looking forward to travelling to Canada, the USA, the UK & Europe, China. I am unique since I do not judge a book by its cover. I accept people for who they are. I will not demand or request perfection from anyone until I am perfect, so I guess that means everyone is safe. My musical tastes range from Classical, big band era, early jazz, classic ’50s & 60’s rock & roll & country since its inception.

Development of Initial Coding:

At this stage, you have to do coding. It’s the essential step of your research . Here you have two options for coding. Either you can do the coding manually or take the help of any tool. A software named the NOVIC is considered the best tool for doing automatic coding.

For manual coding, you can follow the steps given below:

• Please write down the data in a proper format so that it can be easier to proceed.
• Use a highlighter to highlight all the essential points from data.
• Make as many points as possible.
• Take notes very carefully at this stage.
• Apply themes as much possible.
• Now check out the themes of the same pattern or concept.
• Turn all the same themes into the single one.

Example: For better understanding, the previously explained example of Step 1 is continued here. You can observe the coded profiles below:

Make Themes

At this stage, you have to make the themes. These themes should be categorised based on the codes. All the codes which have previously been generated should be turned into themes. Moreover, with the help of the codes, some themes and sub-themes can also be created. This process is usually done with the help of visuals so that a reader can take an in-depth look at first glance itself.

Extracted Data Review

Now you have to take an in-depth look at all the awarded themes again. You have to check whether all the given themes are organised properly or not. It would help if you were careful and focused because you have to note down the symmetry here. If you find that all the themes are not coherent, you can revise them. You can also reshape the data so that there will be symmetry between the themes and dataset here.

For better understanding, a mind-mapping example is given here:

Reviewing all the Themes Again

You need to review the themes after coding them. At this stage, you are allowed to play with your themes in a more detailed manner. You have to convert the bigger themes into smaller themes here. If you want to combine some similar themes into a single theme, then you can do it. This step involves two steps for better fragmentation. 

You need to observe the coded data separately so that you can have a precise view. If you find that the themes which are given are following the dataset, it’s okay. Otherwise, you may have to rearrange the data again to coherence in the coded data.

Corpus Data

Here you have to take into consideration all the corpus data again. It would help if you found how themes are arranged here. It would help if you used the visuals to check out the relationship between them. Suppose all the things are not done accordingly, so you should check out the previous steps for a refined process. Otherwise, you can move to the next step. However, make sure that all the themes are satisfactory and you are not confused.

When all the two steps are completed, you need to make a more précised mind map. An example following the previous cases has been given below:

Define all the Themes here

Now you have to define all the themes which you have given to your data set. You can recheck them carefully if you feel that some of them can fit into one concept, you can keep them, and eliminate the other irrelevant themes. Because it should be precise and clear, there should not be any ambiguity. Now you have to think about the main idea and check out that all the given themes are parallel to your main idea or not. This can change the concept for you.

The given names should be so that it can give any reader a clear idea about your findings. However, it should not oppose your thematic analysis; rather, everything should be organised accurately.

Does your Research Methodology Have the Following?

• Great Research/Sources
• Perfect Language
• Accurate Sources

If not, we can help. Our panel of experts makes sure to keep the 3 pillars of Research Methodology strong.

Also, read about discourse analysis , content analysis and survey conducting . we have provided comprehensive guides.

Make a Report

You need to make the final report of all the findings you have done at this stage. You should include the dataset, findings, and every aspect of your analysis in it.

While making the final report , do not forget to consider your audience. For instance, you are writing for the Newsletter, Journal, Public awareness, etc., your report should be according to your audience. It should be concise and have some logic; it should not be repetitive. You can use the references of other relevant sources as evidence to support your discussion.  

Frequently Asked Questions

What is meant by thematic analysis.

Thematic Analysis is a qualitative research method that involves identifying, analyzing, and interpreting recurring themes or patterns in data. It aims to uncover underlying meanings, ideas, and concepts within the dataset, providing insights into participants’ perspectives and experiences.

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• How It Works

What (Exactly) Is Thematic Analysis?

Plain-Language Explanation & Definition (With Examples)

By: Jenna Crosley (PhD). Expert Reviewed By: Dr Eunice Rautenbach | April 2021

Thematic analysis is one of the most popular qualitative analysis techniques we see students opting for at Grad Coach – and for good reason. Despite its relative simplicity, thematic analysis can be a very powerful analysis technique when used correctly. In this post, we’ll unpack thematic analysis using plain language (and loads of examples) so that you can conquer your analysis with confidence.

Thematic Analysis 101

• Basic terminology relating to thematic analysis
• What is thematic analysis
• When to use thematic analysis
• The main approaches to thematic analysis
• The three types of thematic analysis
• How to “do” thematic analysis (the process)
• Tips and suggestions

First, the lingo…

Before we begin, let’s first lay down some terminology. When undertaking thematic analysis, you’ll make use of codes . A code is a label assigned to a piece of text, and the aim of using a code is to identify and summarise important concepts within a set of data, such as an interview transcript.

For example, if you had the sentence, “My rabbit ate my shoes”, you could use the codes “rabbit” or “shoes” to highlight these two concepts. The process of assigning codes is called qualitative coding . If this is a new concept to you, be sure to check out our detailed post about qualitative coding .

Codes are vital as they lay a foundation for themes . But what exactly is a theme? Simply put, a theme is a pattern that can be identified within a data set. In other words, it’s a topic or concept that pops up repeatedly throughout your data. Grouping your codes into themes serves as a way of summarising sections of your data in a useful way that helps you answer your research question(s) and achieve your research aim(s).

Alright – with that out of the way, let’s jump into the wonderful world of thematic analysis…

What is thematic analysis?

Thematic analysis is the study of patterns to uncover meaning . In other words, it’s about analysing the patterns and themes within your data set to identify the underlying meaning. Importantly, this process is driven by your research aims and questions , so it’s not necessary to identify every possible theme in the data, but rather to focus on the key aspects that relate to your research questions .

Although the research questions are a driving force in thematic analysis (and pretty much all analysis methods), it’s important to remember that these questions are not necessarily fixed . As thematic analysis tends to be a bit of an exploratory process, research questions can evolve as you progress with your coding and theme identification.

When should you use thematic analysis?

There are many potential qualitative analysis methods that you can use to analyse a dataset. For example, content analysis , discourse analysis , and narrative analysis are popular choices. So why use thematic analysis?

Thematic analysis is highly beneficial when working with large bodies of data ,  as it allows you to divide and categorise large amounts of data in a way that makes it easier to digest. Thematic analysis is particularly useful when looking for subjective information , such as a participant’s experiences, views, and opinions. For this reason, thematic analysis is often conducted on data derived from interviews , conversations, open-ended survey responses , and social media posts.

Your research questions can also give you an idea of whether you should use thematic analysis or not. For example, if your research questions were to be along the lines of:

• How do dog walkers perceive rules and regulations on dog-friendly beaches?
• What are students’ experiences with the shift to online learning?
• What opinions do health professionals hold about the Hippocratic code?
• How is gender constructed in a high school classroom setting?

These examples are all research questions centering on the subjective experiences of participants and aim to assess experiences, views, and opinions. Therefore, thematic analysis presents a possible approach.

In short, thematic analysis is a good choice when you are wanting to categorise large bodies of data (although the data doesn’t necessarily have to be large), particularly when you are interested in subjective experiences .

What are the main approaches?

Broadly speaking, there are two overarching approaches to thematic analysis: inductive and deductive . The approach you take will depend on what is most suitable in light of your research aims and questions. Let’s have a look at the options.

The inductive approach

The inductive approach involves deriving meaning and creating themes from data without any preconceptions . In other words, you’d dive into your analysis without any idea of what codes and themes will emerge, and thus allow these to emerge from the data.

For example, if you’re investigating typical lunchtime conversational topics in a university faculty, you’d enter the research without any preconceived codes, themes or expected outcomes. Of course, you may have thoughts about what might be discussed (e.g., academic matters because it’s an academic setting), but the objective is to not let these preconceptions inform your analysis.

The inductive approach is best suited to research aims and questions that are exploratory in nature , and cases where there is little existing research on the topic of interest.

The deductive approach

In contrast to the inductive approach, a deductive approach involves jumping into your analysis with a pre-determined set of codes . Usually, this approach is informed by prior knowledge and/or existing theory or empirical research (which you’d cover in your literature review ).

For example, a researcher examining the impact of a specific psychological intervention on mental health outcomes may draw on an existing theoretical framework that includes concepts such as coping strategies, social support, and self-efficacy, using these as a basis for a set of pre-determined codes.

The deductive approach is best suited to research aims and questions that are confirmatory in nature , and cases where there is a lot of existing research on the topic of interest.

Regardless of whether you take the inductive or deductive approach, you’ll also need to decide what level of content your analysis will focus on – specifically, the semantic level or the latent level.

A semantic-level focus ignores the underlying meaning of data , and identifies themes based only on what is explicitly or overtly stated or written – in other words, things are taken at face value.

In contrast, a latent-level focus concentrates on the underlying meanings and looks at the reasons for semantic content. Furthermore, in contrast to the semantic approach, a latent approach involves an element of interpretation , where data is not just taken at face value, but meanings are also theorised.

“But how do I know when to use what approach?”, I hear you ask.

Well, this all depends on the type of data you’re analysing and what you’re trying to achieve with your analysis. For example, if you’re aiming to analyse explicit opinions expressed in interviews and you know what you’re looking for ahead of time (based on a collection of prior studies), you may choose to take a deductive approach with a semantic-level focus.

On the other hand, if you’re looking to explore the underlying meaning expressed by participants in a focus group, and you don’t have any preconceptions about what to expect, you’ll likely opt for an inductive approach with a latent-level focus.

Simply put, the nature and focus of your research, especially your research aims , objectives and questions will  inform the approach you take to thematic analysis.

What are the types of thematic analysis?

Now that you’ve got an understanding of the overarching approaches to thematic analysis, it’s time to have a look at the different types of thematic analysis you can conduct. Broadly speaking, there are three “types” of thematic analysis:

• Reflexive thematic analysis
• Codebook thematic analysis
• Coding reliability thematic analysis

Let’s have a look at each of these:

Reflexive thematic analysis takes an inductive approach, letting the codes and themes emerge from that data. This type of thematic analysis is very flexible, as it allows researchers to change, remove, and add codes as they work through the data. As the name suggests, reflexive thematic analysis emphasizes the active engagement of the researcher in critically reflecting on their assumptions, biases, and interpretations, and how these may shape the analysis.

Reflexive thematic analysis typically involves iterative and reflexive cycles of coding, interpreting, and reflecting on data, with the aim of producing nuanced and contextually sensitive insights into the research topic, while at the same time recognising and addressing the subjective nature of the research process.

Codebook thematic analysis , on the other hand, lays on the opposite end of the spectrum. Taking a deductive approach, this type of thematic analysis makes use of structured codebooks containing clearly defined, predetermined codes. These codes are typically drawn from a combination of existing theoretical theories, empirical studies and prior knowledge of the situation.

Codebook thematic analysis aims to produce reliable and consistent findings. Therefore, it’s often used in studies where a clear and predefined coding framework is desired to ensure rigour and consistency in data analysis.

Coding reliability thematic analysis necessitates the work of multiple coders, and the design is specifically intended for research teams. With this type of analysis, codebooks are typically fixed and are rarely altered.

The benefit of this form of analysis is that it brings an element of intercoder reliability where coders need to agree upon the codes used, which means that the outcome is more rigorous as the element of subjectivity is reduced. In other words, multiple coders discuss which codes should be used and which shouldn’t, and this consensus reduces the bias of having one individual coder decide upon themes.

Quick Recap: Thematic analysis approaches and types

To recap, the two main approaches to thematic analysis are inductive , and deductive . Then we have the three types of thematic analysis: reflexive, codebook and coding reliability . Which type of thematic analysis you opt for will need to be informed by factors such as:

• The approach you are taking. For example, if you opt for an inductive approach, you’ll likely utilise reflexive thematic analysis.
• Whether you’re working alone or in a group . It’s likely that, if you’re doing research as part of your postgraduate studies, you’ll be working alone. This means that you’ll need to choose between reflexive and codebook thematic analysis.

Now that we’ve covered the “what” in terms of thematic analysis approaches and types, it’s time to look at the “how” of thematic analysis.

Need a helping hand?

How to “do” thematic analysis

At this point, you’re ready to get going with your analysis, so let’s dive right into the thematic analysis process. Keep in mind that what we’ll cover here is a generic process, and the relevant steps will vary depending on the approach and type of thematic analysis you opt for.

Step 1: Get familiar with the data

The first step in your thematic analysis involves getting a feel for your data and seeing what general themes pop up. If you’re working with audio data, this is where you’ll do the transcription , converting audio to text.

At this stage, you’ll want to come up with preliminary thoughts about what you’ll code , what codes you’ll use for them, and what codes will accurately describe your content. It’s a good idea to revisit your research topic , and your aims and objectives at this stage. For example, if you’re looking at what people feel about different types of dogs, you can code according to when different breeds are mentioned (e.g., border collie, Labrador, corgi) and when certain feelings/emotions are brought up.

As a general tip, it’s a good idea to keep a reflexivity journal . This is where you’ll write down how you coded your data, why you coded your data in that particular way, and what the outcomes of this data coding are. Using a reflexive journal from the start will benefit you greatly in the final stages of your analysis because you can reflect on the coding process and assess whether you have coded in a manner that is reliable and whether your codes and themes support your findings.

As you can imagine, a reflexivity journal helps to increase reliability as it allows you to analyse your data systematically and consistently. If you choose to make use of a reflexivity journal, this is the stage where you’ll want to take notes about your initial codes and list them in your journal so that you’ll have an idea of what exactly is being reflected in your data. At a later stage in the analysis, this data can be more thoroughly coded, or the identified codes can be divided into more specific ones.

Step 2: Search for patterns or themes in the codes

Step 2! You’re going strong. In this step, you’ll want to look out for patterns or themes in your codes. Moving from codes to themes is not necessarily a smooth or linear process. As you become more and more familiar with the data, you may find that you need to assign different codes or themes according to new elements you find. For example, if you were analysing a text talking about wildlife, you may come across the codes, “pigeon”, “canary” and “budgerigar” which can fall under the theme of birds.

As you work through the data, you may start to identify subthemes , which are subdivisions of themes that focus specifically on an aspect within the theme that is significant or relevant to your research question. For example, if your theme is a university, your subthemes could be faculties or departments at that university.

In this stage of the analysis, your reflexivity journal entries need to reflect how codes were interpreted and combined to form themes.

Step 3: Review themes

By now you’ll have a good idea of your codes, themes, and potentially subthemes. Now it’s time to review all the themes you’ve identified . In this step, you’ll want to check that everything you’ve categorised as a theme actually fits the data, whether the themes do indeed exist in the data, whether there are any themes missing , and whether you can move on to the next step knowing that you’ve coded all your themes accurately and comprehensively . If you find that your themes have become too broad and there is far too much information under one theme, it may be useful to split this into more themes so that you’re able to be more specific with your analysis.

In your reflexivity journal, you’ll want to write about how you understood the themes and how they are supported by evidence, as well as how the themes fit in with your codes. At this point, you’ll also want to revisit your research questions and make sure that the data and themes you’ve identified are directly relevant to these questions .

Step 4: Finalise Themes

By this point, your analysis will really start to take shape. In the previous step, you reviewed and refined your themes, and now it’s time to label and finalise them . It’s important to note here that, just because you’ve moved onto the next step, it doesn’t mean that you can’t go back and revise or rework your themes. In contrast to the previous step, finalising your themes means spelling out what exactly the themes consist of, and describe them in detail . If you struggle with this, you may want to return to your data to make sure that your data and coding do represent the themes, and if you need to divide your themes into more themes (i.e., return to step 3).

When you name your themes, make sure that you select labels that accurately encapsulate the properties of the theme . For example, a theme name such as “enthusiasm in professionals” leaves the question of “who are the professionals?”, so you’d want to be more specific and label the theme as something along the lines of “enthusiasm in healthcare professionals”.

It is very important at this stage that you make sure that your themes align with your research aims and questions . When you’re finalising your themes, you’re also nearing the end of your analysis and need to keep in mind that your final report (discussed in the next step) will need to fit in with the aims and objectives of your research.

In your reflexivity journal, you’ll want to write down a few sentences describing your themes and how you decided on these. Here, you’ll also want to mention how the theme will contribute to the outcomes of your research, and also what it means in relation to your research questions and focus of your research.

By the end of this stage, you’ll be done with your themes – meaning it’s time to write up your findings and produce a report.

Step 5: Produce your report

You’re nearly done! Now that you’ve analysed your data, it’s time to report on your findings. A typical thematic analysis report consists of:

• An introduction
• A methodology section
• Your results and findings
• A conclusion

When writing your report, make sure that you provide enough information for a reader to be able to evaluate the rigour of your analysis. In other words, the reader needs to know the exact process you followed when analysing your data and why. The questions of “what”, “how”, “why”, “who”, and “when” may be useful in this section.

So, what did you investigate? How did you investigate it? Why did you choose this particular method? Who does your research focus on, and who are your participants? When did you conduct your research, when did you collect your data, and when was the data produced? Your reflexivity journal will come in handy here as within it you’ve already labelled, described, and supported your themes.

If you’re undertaking a thematic analysis as part of a dissertation or thesis, this discussion will be split across your methodology, results and discussion chapters . For more information about those chapters, check out our detailed post about dissertation structure .

It’s absolutely vital that, when writing up your results, you back up every single one of your findings with quotations . The reader needs to be able to see that what you’re reporting actually exists within the results. Also make sure that, when reporting your findings, you tie them back to your research questions . You don’t want your reader to be looking through your findings and asking, “So what?”, so make sure that every finding you represent is relevant to your research topic and questions.

Quick Recap: How to “do” thematic analysis

Getting familiar with your data: Here you’ll read through your data and get a general overview of what you’re working with. At this stage, you may identify a few general codes and themes that you’ll make use of in the next step.

Search for patterns or themes in your codes : Here you’ll dive into your data and pick out the themes and codes relevant to your research question(s).

Review themes : In this step, you’ll revisit your codes and themes to make sure that they are all truly representative of the data, and that you can use them in your final report.

Finalise themes : Here’s where you “solidify” your analysis and make it report-ready by describing and defining your themes.

Produce your report : This is the final step of your thematic analysis process, where you put everything you’ve found together and report on your findings.

Tips & Suggestions

In the video below, we share 6 time-saving tips and tricks to help you approach your thematic analysis as effectively and efficiently as possible.

Wrapping Up

In this article, we’ve covered the basics of thematic analysis – what it is, when to use it, the different approaches and types of thematic analysis, and how to perform a thematic analysis.

If you have any questions about thematic analysis, drop a comment below and we’ll do our best to assist. If you’d like 1-on-1 support with your thematic analysis, be sure to check out our research coaching services here .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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21 Comments

I really appreciate the help

Hello Sir, how many levels of coding can be done in thematic analysis? We generate codes from the transcripts, then subthemes from the codes and themes from subthemes, isn’t it? Should these themes be again grouped together? how many themes can be derived?can you please share an example of coding through thematic analysis in a tabular format?

I’ve found the article very educative and useful

Excellent. Very helpful and easy to understand.

This article so far has been most helpful in understanding how to write an analysis chapter. Thank you.

My research topic is the challenges face by the school principal on the process of procurement . Thematic analysis is it sutable fir data analysis ?

It is a great help. Thanks.

Best advice. Worth reading. Thank you.

Where can I find an example of a template analysis table ?

Finally I got the best article . I wish they also have every psychology topics.

Hello, Sir/Maam

I am actually finding difficulty in doing qualitative analysis of my data and how to triangulate this with quantitative data. I encountered your web by accident in the process of searching for a much simplified way of explaining about thematic analysis such as coding, thematic analysis, write up. When your query if I need help popped up, I was hesitant to answer. Because I think this is for fee and I cannot afford. So May I just ask permission to copy for me to read and guide me to study so I can apply it myself for my gathered qualitative data for my graduate study.

Thank you very much! this is very helpful to me in my Graduate research qualitative data analysis.

Thank you very much. I find your guidance here helpful. Kindly let help me understand how to write findings and discussions.

i am having troubles with the concept of framework analysis which i did not find here and i have been an assignment on framework analysis

I was discouraged and felt insecure because after more than a year of writing my thesis, my work seemed lost its direction after being checked. But, I am truly grateful because through the comments, corrections, and guidance of the wisdom of my director, I can already see the bright light because of thematic analysis. I am working with Biblical Texts. And thematic analysis will be my method. Thank you.

lovely and helpful. thanks

very informative information.

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Thank you for the insight. I am really relieved as you have provided a super guide for my thesis.

Thanks a lot, really enlightening

excellent! very helpful thank a lot for your great efforts

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• How to Do Thematic Analysis | Guide & Examples

How to Do Thematic Analysis | Guide & Examples

Published on 5 May 2022 by Jack Caulfield .

Thematic analysis is a method of analysing qualitative data . It is usually applied to a set of texts, such as an interview or transcripts . The researcher closely examines the data to identify common themes, topics, ideas and patterns of meaning that come up repeatedly.

There are various approaches to conducting thematic analysis, but the most common form follows a six-step process:

• Familiarisation
• Generating themes
• Reviewing themes
• Defining and naming themes

This process was originally developed for psychology research by Virginia Braun and Victoria Clarke . However, thematic analysis is a flexible method that can be adapted to many different kinds of research.

Table of contents

When to use thematic analysis, different approaches to thematic analysis, step 1: familiarisation, step 2: coding, step 3: generating themes, step 4: reviewing themes, step 5: defining and naming themes, step 6: writing up.

Thematic analysis is a good approach to research where you’re trying to find out something about people’s views, opinions, knowledge, experiences, or values from a set of qualitative data – for example, interview transcripts , social media profiles, or survey responses .

Some types of research questions you might use thematic analysis to answer:

• How do patients perceive doctors in a hospital setting?
• What are young women’s experiences on dating sites?
• What are non-experts’ ideas and opinions about climate change?
• How is gender constructed in secondary school history teaching?

To answer any of these questions, you would collect data from a group of relevant participants and then analyse it. Thematic analysis allows you a lot of flexibility in interpreting the data, and allows you to approach large datasets more easily by sorting them into broad themes.

However, it also involves the risk of missing nuances in the data. Thematic analysis is often quite subjective and relies on the researcher’s judgement, so you have to reflect carefully on your own choices and interpretations.

Pay close attention to the data to ensure that you’re not picking up on things that are not there – or obscuring things that are.

Prevent plagiarism, run a free check.

Once you’ve decided to use thematic analysis, there are different approaches to consider.

There’s the distinction between inductive and deductive approaches:

• An inductive approach involves allowing the data to determine your themes.
• A deductive approach involves coming to the data with some preconceived themes you expect to find reflected there, based on theory or existing knowledge.

There’s also the distinction between a semantic and a latent approach:

• A semantic approach involves analysing the explicit content of the data.
• A latent approach involves reading into the subtext and assumptions underlying the data.

After you’ve decided thematic analysis is the right method for analysing your data, and you’ve thought about the approach you’re going to take, you can follow the six steps developed by Braun and Clarke .

The first step is to get to know our data. It’s important to get a thorough overview of all the data we collected before we start analysing individual items.

This might involve transcribing audio , reading through the text and taking initial notes, and generally looking through the data to get familiar with it.

Next up, we need to code the data. Coding means highlighting sections of our text – usually phrases or sentences – and coming up with shorthand labels or ‘codes’ to describe their content.

Let’s take a short example text. Say we’re researching perceptions of climate change among conservative voters aged 50 and up, and we have collected data through a series of interviews. An extract from one interview looks like this:

In this extract, we’ve highlighted various phrases in different colours corresponding to different codes. Each code describes the idea or feeling expressed in that part of the text.

At this stage, we want to be thorough: we go through the transcript of every interview and highlight everything that jumps out as relevant or potentially interesting. As well as highlighting all the phrases and sentences that match these codes, we can keep adding new codes as we go through the text.

After we’ve been through the text, we collate together all the data into groups identified by code. These codes allow us to gain a condensed overview of the main points and common meanings that recur throughout the data.

Next, we look over the codes we’ve created, identify patterns among them, and start coming up with themes.

Themes are generally broader than codes. Most of the time, you’ll combine several codes into a single theme. In our example, we might start combining codes into themes like this:

At this stage, we might decide that some of our codes are too vague or not relevant enough (for example, because they don’t appear very often in the data), so they can be discarded.

Other codes might become themes in their own right. In our example, we decided that the code ‘uncertainty’ made sense as a theme, with some other codes incorporated into it.

Again, what we decide will vary according to what we’re trying to find out. We want to create potential themes that tell us something helpful about the data for our purposes.

Now we have to make sure that our themes are useful and accurate representations of the data. Here, we return to the dataset and compare our themes against it. Are we missing anything? Are these themes really present in the data? What can we change to make our themes work better?

If we encounter problems with our themes, we might split them up, combine them, discard them, or create new ones: whatever makes them more useful and accurate.

For example, we might decide upon looking through the data that ‘changing terminology’ fits better under the ‘uncertainty’ theme than under ‘distrust of experts’, since the data labelled with this code involves confusion, not necessarily distrust.

Now that you have a final list of themes, it’s time to name and define each of them.

Defining themes involves formulating exactly what we mean by each theme and figuring out how it helps us understand the data.

Naming themes involves coming up with a succinct and easily understandable name for each theme.

For example, we might look at ‘distrust of experts’ and determine exactly who we mean by ‘experts’ in this theme. We might decide that a better name for the theme is ‘distrust of authority’ or ‘conspiracy thinking’.

Finally, we’ll write up our analysis of the data. Like all academic texts, writing up a thematic analysis requires an introduction to establish our research question, aims, and approach.

We should also include a methodology section, describing how we collected the data (e.g., through semi-structured interviews or open-ended survey questions ) and explaining how we conducted the thematic analysis itself.

The results or findings section usually addresses each theme in turn. We describe how often the themes come up and what they mean, including examples from the data as evidence. Finally, our conclusion explains the main takeaways and shows how the analysis has answered our research question.

In our example, we might argue that conspiracy thinking about climate change is widespread among older conservative voters, point out the uncertainty with which many voters view the issue, and discuss the role of misinformation in respondents’ perceptions.

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How to do a thematic analysis

What is a thematic analysis?

When is thematic analysis used, braun and clarke’s reflexive thematic analysis, the six steps of thematic analysis, 1. familiarizing, 2. generating initial codes, 3. generating themes, 4. reviewing themes, 5. defining and naming themes, 6. creating the report, the advantages and disadvantages of thematic analysis, disadvantages, frequently asked questions about thematic analysis, related articles.

Thematic analysis is a broad term that describes an approach to analyzing qualitative data . This approach can encompass diverse methods and is usually applied to a collection of texts, such as survey responses and transcriptions of interviews or focus group discussions. Learn more about different research methods.

A researcher performing a thematic analysis will study a set of data to pinpoint repeating patterns, or themes, in the topics and ideas that are expressed in the texts.

In analyzing qualitative data, thematic analysis focuses on concepts, opinions, and experiences, as opposed to pure statistics. This requires an approach to data that is complex and exploratory and can be anchored by different philosophical and conceptual foundations.

A six-step system was developed to help establish clarity and rigor around this process, and it is this system that is most commonly used when conducting a thematic analysis. The six steps are:

• Familiarization
• Generating codes
• Generating themes
• Reviewing themes
• Defining and naming themes
• Creating the report

It is important to note that even though the six steps are listed in sequence, thematic analysis is not necessarily a linear process that advances forward in a one-way, predictable fashion from step one through step six. Rather, it involves a more fluid shifting back and forth between the phases, adjusting to accommodate new insights when they arise.

And arriving at insight is a key goal of this approach. A good thematic analysis doesn’t just seek to present or summarize data. It interprets and makes a statement about it; it extracts meaning from the data.

Since thematic analysis is used to study qualitative data, it works best in cases where you’re looking to gather information about people’s views, values, opinions, experiences, and knowledge.

Some examples of research questions that thematic analysis can be used to answer are:

• What are senior citizens’ experiences of long-term care homes?
• How do women view social media sites as a tool for professional networking?
• How do non-religious people perceive the role of the church in a society?
• What are financial analysts’ ideas and opinions about cryptocurrency?

To begin answering these questions, you would need to gather data from participants who can provide relevant responses. Once you have the data, you would then analyze and interpret it.

Because you’re dealing with personal views and opinions, there is a lot of room for flexibility in terms of how you interpret the data. In this way, thematic analysis is systematic but not purely scientific.

A landmark 2006 paper by Victoria Braun and Victoria Clarke (“ Using thematic analysis in psychology ”) established parameters around thematic analysis—what it is and how to go about it in a systematic way—which had until then been widely used but poorly defined.

Since then, their work has been updated, with the name being revised, notably, to “reflexive thematic analysis.”

One common misconception that Braun and Clarke have taken pains to clarify about their work is that they do not believe that themes “emerge” from the data. To think otherwise is problematic since this suggests that meaning is somehow inherent to the data and that a researcher is merely an objective medium who identifies that meaning.

Conversely, Braun and Clarke view analysis as an interactive process in which the researcher is an active participant in constructing meaning, rather than simply identifying it.

The six stages they presented in their paper are still the benchmark for conducting a thematic analysis. They are presented below.

This step is where you take a broad, high-level view of your data, looking at it as a whole and taking note of your first impressions.

This typically involves reading through written survey responses and other texts, transcribing audio, and recording any patterns that you notice. It’s important to read through and revisit the data in its entirety several times during this stage so that you develop a thorough grasp of all your data.

After familiarizing yourself with your data, the next step is coding notable features of the data in a methodical way. This often means highlighting portions of the text and applying labels, aka codes, to them that describe the nature of their content.

In our example scenario, we’re researching the experiences of women over the age of 50 on professional networking social media sites. Interviews were conducted to gather data, with the following excerpt from one interview.

In the example interview snippet, portions have been highlighted and coded. The codes describe the idea or perception described in the text.

It pays to be exhaustive and thorough at this stage. Good practice involves scrutinizing the data several times, since new information and insight may become apparent upon further review that didn’t jump out at first glance. Multiple rounds of analysis also allow for the generation of more new codes.

Once the text is thoroughly reviewed, it’s time to collate the data into groups according to their code.

Now that we’ve created our codes, we can examine them, identify patterns within them, and begin generating themes.

Keep in mind that themes are more encompassing than codes. In general, you’ll be bundling multiple codes into a single theme.

To draw on the example we used above about women and networking through social media, codes could be combined into themes in the following way:

You’ll also be curating your codes and may elect to discard some on the basis that they are too broad or not directly relevant. You may also choose to redefine some of your codes as themes and integrate other codes into them. It all depends on the purpose and goal of your research.

This is the stage where we check that the themes we’ve generated accurately and relevantly represent the data they are based on. Once again, it’s beneficial to take a thorough, back-and-forth approach that includes review, assessment, comparison, and inquiry. The following questions can support the review:

• Has anything been overlooked?
• Are the themes definitively supported by the data?
• Is there any room for improvement?

With your final list of themes in hand, the next step is to name and define them.

In defining them, we want to nail down the meaning of each theme and, importantly, how it allows us to make sense of the data.

Once you have your themes defined, you’ll need to apply a concise and straightforward name to each one.

In our example, our “perceived lack of skills” may be adjusted to reflect that the texts expressed uncertainty about skills rather than the definitive absence of them. In this case, a more apt name for the theme might be “questions about competence.”

To finish the process, we put our findings down in writing. As with all scholarly writing, a thematic analysis should open with an introduction section that explains the research question and approach.

This is followed by a statement about the methodology that includes how data was collected and how the thematic analysis was performed.

Each theme is addressed in detail in the results section, with attention paid to the frequency and presence of the themes in the data, as well as what they mean, and with examples from the data included as supporting evidence.

The conclusion section describes how the analysis answers the research question and summarizes the key points.

In our example, the conclusion may assert that it is common for women over the age of 50 to have negative experiences on professional networking sites, and that these are often tied to interactions with other users and a sense that using these sites requires specialized skills.

Thematic analysis is useful for analyzing large data sets, and it allows a lot of flexibility in terms of designing theoretical and research frameworks. Moreover, it supports the generation and interpretation of themes that are backed by data.

There are times when thematic analysis is not the best approach to take because it can be highly subjective, and, in seeking to identify broad patterns, it can overlook nuance in the data.

What’s more, researchers must be judicious about reflecting on how their own position and perspective bears on their interpretations of the data and if they are imposing meaning that is not there or failing to pick up on meaning that is.

Thematic analysis offers a flexible and recursive way to approach qualitative data that has the potential to yield valuable insights about people’s opinions, views, and lived experience. It must be applied, however, in a conscientious fashion so as not to allow subjectivity to taint or obscure the results.

The purpose of thematic analysis is to find repeating patterns, or themes, in qualitative data. Thematic analysis can encompass diverse methods and is usually applied to a collection of texts, such as survey responses and transcriptions of interviews or focus group discussions. In analyzing qualitative data, thematic analysis focuses on concepts, opinions, and experiences, as opposed to pure statistics.

A big advantage of thematic analysis is that it allows a lot of flexibility in terms of designing theoretical and research frameworks. It also supports the generation and interpretation of themes that are backed by data.

A disadvantage of thematic analysis is that it can be highly subjective and can overlook nuance in the data. Also, researchers must be aware of how their own position and perspective influences their interpretations of the data and if they are imposing meaning that is not there or failing to pick up on meaning that is.

How many themes make sense in your thematic analysis of course depends on your topic and the material you are working with. In general, it makes sense to have no more than 6-10 broader themes, instead of having many really detailed ones. You can then identify further nuances and differences under each theme when you are diving deeper into the topic.

Since thematic analysis is used to study qualitative data, it works best in cases where you’re looking to gather information about people’s views, values, opinions, experiences, and knowledge. Therefore, it makes sense to use thematic analysis for interviews.

After familiarizing yourself with your data, the first step of a thematic analysis is coding notable features of the data in a methodical way. This often means highlighting portions of the text and applying labels, aka codes, to them that describe the nature of their content.

The Art of Interpretation: A Journey through Thematic Analysis

Uncover the intricacies of thematic analysis with this comprehensive guide. Get useful step-by-step instructions and best practices.

Thematic analysis is a widely used qualitative research method that involves identifying patterns or themes in qualitative data. It is a flexible and versatile method that can be applied to a wide range of research questions and data types. It is commonly used in fields such as psychology, sociology, education, and healthcare to analyze data collected through methods such as interviews, focus groups, and open-ended surveys. In this article, we will provide an overview of thematic analysis, including its definition, main steps, and different approaches. We will also discuss the advantages and disadvantages of this method, as well as provide practical tips for conducting thematic analysis in research.

What is Thematic Analysis?

The thematic analysis involves systematically identifying, analyzing, and reporting patterns (or themes) within data that capture its essential meaning. The process of this method typically involves several stages, including data familiarization, generating initial codes, searching for themes, reviewing and refining themes, and defining and naming themes. During the analysis, the researcher aims to identify meaningful patterns within the data that help to answer the research question or explore a phenomenon of interest. 

Thematic analysis is a flexible and highly interpretive method that allows researchers to capture the complexity and richness of qualitative data. It can be used to generate new insights, identify patterns and trends, and provide a detailed and nuanced understanding of social phenomena.

When Should I Use Thematic Analysis?

Thematic analysis can be used when you want to gain an in-depth understanding of qualitative data and identify patterns and themes within it. Here are some situations where you might consider using thematic analysis:

Exploratory Research

By identifying themes within the data, researchers can generate new insights and hypotheses for further investigation. Thematic analysis is particularly useful in exploratory research, as it allows for a general understanding of a phenomenon or exploration of a topic that has not been extensively studied before.

Data-rich Research

When dealing with large amounts of qualitative data, such as from focus groups, interviews, or surveys, systematic analysis and organization of data becomes crucial. Thematic analysis can be applied to identify key themes and patterns that emerge across the data set, making it a particularly useful method.

Interpretive Research

Thematic analysis is a highly interpretive method that allows researchers to capture the complexity and nuance of qualitative data. It is well-suited to interpretive research, where the aim is to explore subjective experiences, meanings, and perspectives.

Cross-cultural Research

By identifying themes that are common across cultures, researchers can use thematic analysis to generate insights into cultural patterns and differences across different groups or contexts.

What Are The Advantages and Disadvantages of Thematic Analysis?

Thematic analysis has several advantages and disadvantages that researchers should consider when deciding whether to use this method. While it has advantages, such as flexibility and depth, it also has some disadvantages, such as subjectivity and time-consuming nature. Therefore, it is essential to weigh the pros and cons of thematic analysis carefully and consider whether this method is appropriate for the research question and data type. Here are some of the main advantages and disadvantages of thematic analysis:

Flexibility

It is possible to apply the flexible and adaptable method of thematic analysis to a variety of qualitative data types, such as interviews, focus groups, surveys, and other forms of qualitative data.

Through the use of thematic analysis, researchers are able to gain a deeper understanding of the data they are analyzing and uncover patterns and themes that may not be readily apparent using other methods.

The rigor and systematic approach of thematic analysis involves multiple stages of analysis, which can improve the reliability and validity of the findings, making it a valuable method in qualitative research.

Interpretive

The interpretive nature of thematic analysis enables researchers to capture the complex and nuanced aspects of qualitative data, leading to rich and detailed insights into various social phenomena, making it a valuable tool in qualitative research.

Disadvantages

Time-consuming.

A significant disadvantage of thematic analysis is its time-consuming nature when dealing with substantial amounts of data, which requires researchers to allocate adequate time and resources to conduct a comprehensive analysis.

Subjectivity

The subjectivity of thematic analysis can be a potential limitation, as it relies heavily on the researcher’s interpretations and may be influenced by their biases, preconceptions, and perspectives. This can affect the reliability and validity of the findings, and researchers need to acknowledge and address potential biases in their analysis.

Lack of Transparency

The lack of transparency in thematic analysis can be a potential disadvantage, as researchers may not always provide clear and detailed explanations of how themes were identified. This can limit the ability of others to replicate the study or assess the credibility of the findings.

Oversimplification

The reductionist nature of thematic analysis can be a potential drawback, as it may oversimplify the data and lead to the loss of important nuances and complexities that may be present in the data.

Step-by-Step Process of How To Do a Thematic Analysis

The thematic analysis involves familiarizing yourself with the data, generating initial codes, searching for themes, reviewing and refining themes, defining and naming themes, and finally analyzing and reporting the findings. Here is a step-by-step process for conducting a thematic analysis:

Step 1: Familiarization with the data

Start by thoroughly reading and reviewing the data to gain a general understanding of the content. This involves listening to or reading the data multiple times to identify important concepts, ideas, or recurring patterns. It is essential to take detailed notes throughout this stage to aid in the identification of themes.

Step 2: Generating initial codes

Begin coding the data by marking the text with relevant words or phrases that capture the essence of the content. The codes should be short, descriptive, and closely related to the content of the data. At this stage, it is essential to code all aspects of the data that relate to the research question.

Step 3: Searching for themes

After generating initial codes, start grouping them into potential themes that reflect the patterns and relationships in the data. It is essential to organize the codes into groups that make sense, even if some codes do not fit neatly into any category.

Step 4: Reviewing and refining themes

After identifying potential themes, review them to determine if they accurately capture the content of the data. Themes should be refined and clarified to make sure they reflect the essence of the data. Ensuring that the themes are relevant to the research question is also crucial.

Step 5: Defining and naming themes

Once themes have been reviewed and refined, define and name them. Themes should be named using a descriptive and meaningful label that accurately reflects the content of the data. It is essential to define each theme and outline the data supporting it.

Step 6: Analyzing and reporting

Finally, analyze the data by synthesizing the themes to provide a comprehensive account of the data. This involves interpreting the findings, drawing conclusions, and making recommendations based on the research question. It is important to report the findings in a clear, concise, and organized manner, using relevant examples from the data to illustrate each theme.

Different Approaches to Thematic Analysis

There are different approaches to thematic analysis, but the two main ones are Inductive Thematic and Deductive Thematic. Other approaches include Critical Thematic Analysis, Latent Thematic Analysis, and Semantic Analysis, among others. However, the Inductive and Deductive Thematic approaches are the most commonly used in research.

Inductive Thematic Analysis

In this approach, themes emerge from the data itself, without any preconceived ideas or theories. The researcher codes the data and identifies patterns and relationships, which are then grouped into themes. This approach is useful when there is no clear theoretical framework or when the aim is to generate new insights. It is particularly useful when the topic has not been extensively studied before, and the researcher wants to gain a broad understanding of the data without imposing preconceived categories or themes. 

Deductive Thematic Analysis

This approach begins with a pre-existing theory or framework that guides the analysis. The researcher begins by identifying the concepts and themes that are relevant to the research question and then searches for evidence of these in the data. This approach is useful when there is an existing theory that needs to be tested or when the aim is to confirm or refute hypotheses. A deductive approach is best suited to research when the researcher has a specific research question or hypothesis that they want to test using existing theory or previous research findings.

Semantic Thematic Analysis

In semantic thematic analysis, the focus is on the literal meaning of the words and phrases used in the data. Themes are identified by analyzing the explicit content of the data.

Latent Thematic Analysis

This approach goes beyond the surface level of the data to uncover underlying meanings and assumptions. The researcher identifies implicit or hidden meanings in the data, which are then grouped into themes.

Critical Thematic Analysis

This approach emphasizes the power dynamics in society and how they influence the data. The researcher analyzes the data to identify themes related to social justice, power, and oppression.

Reflexive Thematic Analysis

In this approach, the researcher is aware of their own biases and assumptions and actively reflects on how these might be influencing the analysis. The researcher may use a diary or other means of recording their thoughts and feelings during the analysis process.

These approaches are not mutually exclusive and can be used in combination to gain a more nuanced understanding of the data. The choice of approach depends on the research question, the data, and the researcher’s goals and perspective.

Tips for Thematic Analysis

Here are some tips for conducting thematic analysis in your qualitative research:

Familiarize yourself with the data: To conduct an effective thematic analysis, it’s crucial to familiarize yourself with the data. This means spending time reading and re-reading the data to get a sense of the content and themes that may emerge. This step helps researchers develop a good understanding of the data they are working with, which can lead to the identification of themes and patterns that may be missed otherwise.

Code systematically: Coding the data systematically and thoroughly ensures that all themes are captured. It involves systematically labeling or tagging data segments with relevant codes, which can be used to identify emerging themes. This step helps to keep the analysis organized and to identify emerging themes.

Engage in reflexivity: Reflexivity involves reflecting on your own biases and assumptions throughout the analysis process. This step is essential to minimize the impact of the researcher’s own beliefs and values on the analysis process. Researchers need to be aware of their biases and actively work to overcome them.

Create a clear coding scheme: Developing a clear and comprehensive coding scheme that captures all relevant themes is essential for effective thematic analysis. This step involves identifying all the relevant themes and creating a set of codes to label data segments related to each theme. A clear coding scheme helps researchers maintain consistency in their analysis and makes it easier to identify emerging themes.

Maintain transparency: Documenting the analysis process and providing clear explanations for how themes were identified and coded is crucial for maintaining transparency. It allows other researchers to follow the analysis process and assess the validity of the findings.

Validate findings: Using member checking or other methods to validate the findings and ensure accuracy is essential for ensuring the credibility of the analysis. Member checking involves sharing the analysis with the participants to validate whether the findings accurately represent their experiences or perspectives.

Examples of Thematic Analysis

Research Question: How do young adults perceive the impact of social media on their mental health?

Data Collection: In-depth interviews with 20 young adults (aged 18-25) who use social media regularly.

Data Analysis: The interviews were transcribed and analyzed using a thematic analysis approach. The following themes emerged:

• Negative self-comparison: Many participants discussed feeling inadequate or inferior when comparing themselves to others on social media. They described feeling pressure to present a certain image and the impact this had on their self-esteem.
• Fear of missing out (FOMO): Participants talked about feeling anxious or stressed when they saw posts from friends or acquaintances engaging in activities they were not part of. They described feeling pressure to stay connected and up-to-date on social media to avoid missing out.
• Cyberbullying: Some participants discussed experiences of being bullied or harassed on social media. They talked about feeling helpless and isolated when this happened and the impact it had on their mental health.
• Positive social connections: Despite the negative aspects, many participants also described how social media helped them stay connected with friends and family, especially during times of social distancing.
• Strategies for managing social media use: Participants discussed various strategies for managing the negative impact of social media on their mental health, such as setting limits on their use, unfollowing accounts that made them feel bad, and focusing on positive aspects of social media.

Conclusion: This thematic analysis suggests that social media use can have both positive and negative effects on young adults’ mental health. Negative self-comparison, FOMO, and cyberbullying emerged as significant negative themes, while positive social connections and strategies for managing social media use emerged as positive themes. These findings can inform interventions aimed at promoting healthy social media use among young adults.

Research Question: What are the key themes in teachers’ perceptions of the challenges and benefits of remote teaching during the COVID-19 pandemic?

Data Collection: Online survey of 100 K-12 teachers in the United States who were teaching remotely during the COVID-19 pandemic.

Data Analysis: The survey responses were analyzed using a thematic analysis approach. The following themes emerged:

• Technological challenges: Many teachers reported struggling with the technological aspects of remote teaching, such as unreliable internet connections and difficulties with online platforms.
• Student engagement: Participants discussed challenges related to engaging students in remote learning, such as difficulties with monitoring student progress and maintaining student motivation.
• Work-life balance: Several participants described struggling to balance their work and personal lives while teaching remotely, particularly due to the blurring of boundaries between work and home.
• Benefits of remote teaching: Despite the challenges, many participants also discussed the benefits of remote teaching, such as increased flexibility and opportunities for personalized learning.
• Support from colleagues and administrators: Some participants talked about the importance of support from colleagues and administrators in navigating the challenges of remote teaching.

Conclusion: This thematic analysis suggests that remote teaching during the COVID-19 pandemic presented a variety of challenges for teachers, particularly related to technology, student engagement, and work-life balance. However, participants also identified the benefits of remote teaching and the importance of support from colleagues and administrators. These findings can inform efforts to improve remote teaching practices and support teachers in navigating the challenges of remote teaching.

These are hypothetical examples created for the purpose of understanding thematic analysis. For more examples, access this website .

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How to Write a Thematic Essay: The Complete Guide

by  Antony W

September 12, 2022

In this guide, you'll learn exactly how to write a thematic essay step-by-step.

Thematic essays, or theme essays, require you to really examine a literary object such as a book, journal, paper, or other art form and pick out the main ideas (themes).

You will then explain how these themes are brought on and what literary devices are used to do that.

Key Takeaways 

To write an outstanding theme essay, you should: 

• Select a literary work to base your thematic analysis on.
• Choose a primary theme.
• Identify supporting evidence and literary devices   used.
• Plan and outline the essay.
• Write the first draft.
• Edit and proofread your work for submission.

What is a Thematic Essay? 

A thematic essay is a one in which you identify the main idea (theme) expressed in a chosen literary object and explore how the writer of that literature chooses to address that theme through various literary devices.

The devices can be metaphors, hyperbole, imagery, allegory, and many others.

Writing a thematic analysis essay is a great way to learn how to pick out themes in the literature you read as well as how to improve your writing skills.

A thematic essay will be at least five paragraphs long , but usually longer depending on the complexity of the work being reviewed.

You can write a thematic essay based on a book, a speech, a magazine article, a video, audio, or any other art form.

Choosing a Theme for a Thematic Essay 

Choosing the main idea or theme of such a work is not a straightforward process.

It is highly subjective, and what you consider the main theme in a book may not be somebody else’s.

You have to make sure that what you pick as your main theme is fully supported throughout the book and makes significant appearances in most chapters, if not all of them.

How to Write a Thematic Essay Step by Step 

Writing a thematic essay is easy. You just have to: 

1. Choose a Literary Object

If your instructor does not provide the topic, think back to a book or article that made a strong impression to you, or think about your favorite pieces of literature.

Another option is to brainstorm. Brainstorming hardly fails, especially if you incorporate the help of your friends and even your instructor.

Collect different ideas and be sure to write each of them down, no matter how unlikely they sound. From there, eliminate most of these the following criteria:

• The topic should be interesting and captivating. Avoid those that are too common and overly used in academia unless you can provide a fresh twist or insight.
• The topic needs to have one or more important themes running through.
• It should be a literary work that is relatively well known and in the public domain.
• Some of the shorter works are best because they guarantee your essay won’t be too long.

This process will likely leave you with one or two possible topics, but make sure to confirm with your instructor that what you choose to focus on is acceptable.

2. Find a Relevant Theme

A theme is a significant idea that recurs throughout the literary work you have chosen. You can think of it as the main message the author is trying to pass across. 

There are major and minor themes differentiated by how much attention the author gives to each.

For the best outcome, your theme should be one of the major themes addressed throughout the work.

There are a few things you can do to figure out what major themes are present: 

• As you read the work, note and write down what tone, setting, language styles, and characterization the writer is using.
• What is the plot of the book and what does it lead to? Think about what you would tell somebody else about the book.
• Identify who the protagonist (main character) is and what they represent. Do they change at all in the book? 

For example, in Harper Lee’s To Kill a Mockingbird, Atticus Finch does not change and represents morality, love, fairness, and good reason to the end.

• Put yourself in the author’s shoes and observe from their point of view. What message do you think they want to pass on as the most important?

3. Pick Material for the Essay

Read through the book again with the main theme in mind.

See how the author plays with it, what literary devices are used to highlight their thematic approach, and write down all these for reference.

What you are doing at this stage is a literary analysis.

The tools in the author’s hands include character development, mood, setting, irony, allegory, simile, alliteration, symbolism, metaphor, among many others.

Think about how effective these tools are in shining the light upon the main theme. It helps to read between the lines as well because sometimes the most important thing is what the author leaves unsaid.

4. Planning: Thematic Essay Outline 

A thematic essay is very simple and straightforward. Like most essays, it will have an introduction, body, and conclusion.

Each of these parts should be considered carefully in the planning stage and map out which ideas will go where.

Introduction

The introduction serves to catch the reader’s interest, set the background, and mention what exactly you intend to discuss in the essay.

The first one or two sentences should be a hook, that is, a statement that will be intriguing enough to make the reader want to keep reading. It can be a clever observation, a surprising statement, or even a relevant question.

Second, provide a very brief background on which to build your essay.

However, you will be assuming that the reader has already read the literary work that is the subject of the essay. So you don’t have to give too much detail.

In winding up the introductory, write your thesis statement . This is a one-sentence statement that tells the reader what your essay is about.

However, don’t say it like this: “My thesis statement is ... “ Instead, let the introduction flow and link smoothly up to this point.

Body paragraphs

You will have three or more body paragraphs detailing your arguments about the main theme. In a thematic essay, each of the body paragraphs will be focusing on one literary device and how it is useful in presenting the theme message.

As with most essays, body paragraphs will follow the TEEL format. 

• Topic Sentence : The introductory sentence introduces the idea that the paragraph is about. Think of it as a mini-thesis statement. The rest of the paragraph will be explaining and supporting this one statement.
• Explanation:  Explain your topic idea clearly.
• Evidence : Give compelling evidence for your claims. It can be a quote, a direct observation, similar use of the same method elsewhere in the book, a citation from an authoritative work, etc.
• Link : Show how the idea you just described links with the rest of the essay and thesis statement. Again, you won’t say, “this idea relates to my thesis statement because …” Instead, let the whole paragraph flow smoothly and seamlessly.

The number of body paragraphs will depend on how much evidence you have collected. However, make sure to keep within the reasonable word count parameters as given by your instructor.

Recap the main arguments in your body and restate your thesis statement.

The purpose of the conclusion is to give your “take-home” argument, what you feel the reader should retain from the whole work.

Customize your theme essay outline accordingly; don’t make it as generic as this example here.

Fill it with details like what ideas you will include in your first paragraph, what your thesis statement will be, and what your introduction hook is. With this thematic essay format, you are now ready to do the write-up.

5. Write the Essay

With a good outline, writing a thematic essay becomes a piece of cake. You will simply be fleshing out the template.

6. Proofreading and Revision

Make sure to read through your essay at least twice.

Note how well your ideas flow, how the arguments and evidence presented link back to the thesis statement, and of course, clear any grammatical errors. 

Thematic Essay Writing Help 

If you don’t have the time to read your subject thoroughly and analytically, you can hire Help for Assessment’s  essay writing service .  We have a suitable writer that can help you get the assignment completed on time. 

Frequently Asked Questions 

1. how do you start a theme essay.

The introduction of your theme essay should be an intriguing hook about the subject you wish to discuss.

Ensure the hook is concise and strong enough to grab your reader’s attention.

2. What are the Elements of a Thematic Essay? 

The elements of a thematic essay are the introduction, body paragraphs, and the conclusion.

Ensure the introduction includes a thesis statement. The body paragraphs should support the thesis using relevant examples, evidence, and arguments.

Lastly, the conclusion should be logical enough to tie everything together at the end.

3. What is the Main Point of a Thematic Essay? 

The main point of a thematic essay is to identify themes from a source, present a theme statement, and address a specific issue within the requirement of the assignment. 

About the author 

Antony W is a professional writer and coach at Help for Assessment. He spends countless hours every day researching and writing great content filled with expert advice on how to write engaging essays, research papers, and assignments.

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Thematic Analysis – A 6-Step Guide for Academic Writing

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Thematic analysis is a methodolgy that helps scientific researchers understand unquantifiable, complex data with open-ended questions and transcripts. Applied analysis carefully examines qualitative prose statements (i.e. subject interviews, transcripts, documents) via a detailed, systematic 6-step schema. Recurring patterns are then identified, grouped, and picked apart for deeper insights.

Inhaltsverzeichnis

• 1 Thematic Analysis – In a Nutshell
• 2 Definition: Thematic Analysis
• 3 When is it relevant to use thematic analysis?
• 4 What questions can thematic analysis use?
• 5 Approaches to thematic analysis
• 6 Step 1 of thematic analysis: Familiarization
• 7 Step 2 of thematic analysis: Coding
• 8 Step 3 of thematic analysis: Constructing themes
• 9 Step 4 of thematic analysis: Reviewing themes
• 10 Step 5 of thematic analysis: Defining themes
• 11 Step 6 of thematic analysis: Writing a thematic analysis

Thematic Analysis – In a Nutshell

• Thematic analysis allows researchers to categorize subjective prose responses to open-ended questions from subjects in an understandable, usable way.
• It highlights recurring themes and thoughts on a topic.
• It’s often deployed wherever using statistical and numerical analysis wouldn’t give a clear picture or explanation of a topic.
• By following a fixed 6-step schema , thematic analysis is kept uniform, repeatable, and ordered.
• Highlighted categories and themes help researchers to identify complex factors and threads within a topic.

Definition: Thematic Analysis

Thematic analysis is fantastic for empirical humanitarian and scientific experimenters who want to explore highly subjective topics of interest. You might use thematic analysis to study ‘intangibles’ such as people’s experiences, perceptions, and nuanced opinions.

How does it work? By asking respondent(s) the same open-ended questions, common and unique themes reveal themselves. Qualitative conclusions can be formed without statistical tests for correlation and causation.

The analytical schema was first published as a 2006 paper by psychologists Virginia Braun and Victoria Clarke. They developed a straightforward, 6-step experimental method to simplify qualitative data analysis and add repeatability to test cycles.

When is it relevant to use thematic analysis?

Thematic analysis is ideal when your experimental research needs deeper insight into what a sampled group of people think. It’s a versatile, adaptable methodology that often opens up new areas of exploration.

Why? While it’s possible to poll public opinion quantitatively with formulaic questions (e.g. Do you approve/disapprove?), this may risk narrowing responses and leading participants. Cold statistics might also miss the depth behind controversial and subjective topics such as politics and religion.

Thematic analysis keeps more of an open mind as to what may get back from testing. By adopting a focus group , interview-led approach, observers can build clear, explanatory narratives from multiple samples.

What questions can thematic analysis use?

Thematic researchers typically ask a string of open, topical, yet focused questions that invite elaboration from the respondent. They may often start with phrases such as:

• What do you think…?
• What is your opinion…?
• What are your ideas…?
• What do you remember…?
• Why do you believe…?
• What should we do about…?

Questionable themes that fit systematic thematic analysis may be vast and diverse (e.g. cosmology) or ‘small’ and unique (e.g. specific event memories). Questions can be segued into additional, clarifying questions (if relevant).

Approaches to thematic analysis

Like most methodologies, the 6-step analysis contains polarized sub-approaches. These determine how the questioning proceeds and how the gathered qualitative data is processed. A single thematic study may also use a ‘hybrid’ approach.

Inductive vs. deductive thematic analysis

Semantic vs. latent thematic analysis

Step 1 of thematic analysis: Familiarization

After the interview phase, our researchers will collate and quickly review their initial findings. The prose within written transcripts is checked back for familiarity and errors. Researchers also transcribe any audio recordings into analyzable text.

Step 2 of thematic analysis: Coding

The coding phase sets out the common themes within the study and labels them via highlighted color coding.

Labeling common, linked statements codifies the subjects in play by dividing them into recurring themes. Any anomalies (i.e. unusual reactions) can also be flagged up for study.

Step 3 of thematic analysis: Constructing themes

Labeled codes are combined into broader, ‘umbrella’ themes that cover a wide range of recurring statements and opinions.

These themes generally identify recurring threads of thought that run through responses to the same question. As the study develops onward, several areas might be merged into a meta-category that better identifies and explains what’s happening.

• Climate Change Concern
• Positivity About the Future
• Knowing About Green News
• Environmentalist Thought
• Anti-NIMBY Attitudes
• Renewable Energy: Positivity

Step 4 of thematic analysis: Reviewing themes

As the study finalizes, researchers take a short introspective look at exactly how they’re categorizing what they have found.

On reflection, some labels might fit into different themes better than their first assigned category. Others might reflect a strand of thought that initially seemed relevant but lacked significant presence elsewhere. Smaller themes might require careful reflection on whether they justify an entire category.

The researchers also watch carefully for observer bias.

Researchers reviewing conclude that the label Anti-NIMBY Attitudes needs to be in another column.

While it’s still relevant to attitudes concerning Renewable Energy, further analysis of the labels Fossil Fuels and Local Spaces shows that it’s part of a more complex chain of thought on landscapes.

Anti-NIMBY is moved into Local Spaces as a solution.

Step 5 of thematic analysis: Defining themes

The penultimate step is reviewing category and theme names for clarity and accuracy.

Consistency, relevancy, and explanatory power are all given a second glance, as is each label’s succinctness. Titles are then changed, clarified, deleted, and merged as appropriate.

Step 6 of thematic analysis: Writing a thematic analysis

Once all the data’s been processed, categorized, and analyzed, it’s time to create the study’s final paper.

The written summary serves as an explanation of how the data was collected, the methodology used to divide it, and outlines what conclusions and arguments (if any) can be drawn from what was found. It may also detail theories and potential topics for future study.

Every final thematic analysis should always contain:

• An introduction, stating aims and prior knowledge
• A methodology outline, stating how and where data was gathered
• A results section, outlining findings, labels, and categories identified
• A conclusion, detailing what can be drawn from the above

What are the 6 key steps of Braun and Clarkes' schema?

Familiarization, coding, generating themes, Reviewing themes, defining themes, summarization (writing up).

How are themes divided for analysis?

Transcribed text from samples is browsed line-by-line for recurring patterns of thought, exposition, and opinion and marked.

Researchers often use colored boxes or highlighter pens to divide scripts.

Is there any data that's unsuitable for thematic analysis?

Yes. If your study exclusively gathers lots of repetitive, quantitative, numerical data, you might be better off using statistical analysis.

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How to Write a Thematic Essay

Every piece of writing ever written has its agenda. Whether it’s to teach a lesson or show the impact of a particular emotion or action, a central theme can be developed. The goal for us as readers is to uncover what the author was trying to tell us between the lines in their literature. When we do finally discover it, we’ve accomplished the first step of thematic essay writing! Let’s see below how to write a thematic essay with our papers writing service .

What Is a Thematic Essay?

Let’s look at the thematic essay definition; a thematic essay is a piece of writing in which an author develops the central theme in some literature using literary devices like foreshadowing, imagery, personification, etc.

A professional essay writer will uncover the primary subject, elaborate upon the literary devices employed, and express the overall significance of the theme. The primary challenge comes from the fact that although there are various subjects, finding the most meaningful and impactful one can be challenging.

Naturally, each person has their own varied interpretation, making it hard to agree on a central theme wholesomely. In short, a well written thematic essay comes from a healthy central idea that is conclusively proven via literary devices and logical arguments.

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How to Pick a Thematic Topic?

A crucial aspect of writing a good thematic essay is choosing a theme. Follow the hints listed below to help you create a thematic topic:

Brainstorm from your own experiences. Recall what you were talking about in class, with your mates or parents. Do some of these conversations remind you of some book, novel or another piece of literature?

Write down every idea that comes to mind. Sometimes, your most absurd ideas are the best way to go.

List your favourite literature pieces. Which literature piece was the most touching for you? Try to analyze its subject and problems the author built upon within the story; it might help you come up with your own ideas.

Look at the details of other literature pieces: You might find some interesting details within other literature that can help you come up with your theme.

Still have no idea what to write about? No worries, we have your back.

Thematic Essay Topics

• What is George Orwell’s deliberation in portraying a “Perfect Utopia” in his book 1984?
• What main idea is George Orwell painting about Communism in the book Animal Farm?
• What is Harper Lee saying about innocence in her novel To Kill A Mockingbird?
• What is John Steinbeck saying about loneliness and isolation in Of Mice and Men?
• What is F. Scott Fitzgerald saying about the American Dream in The Great Gatsby?

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How to Find and Explore the Central Theme

As stated before, uncovering the main subject and central theme respectively is the first significant step in a thematic paper. However, with so many things going on within the literature, it may be difficult to interpret the central theme accurately. To make sure you choose it correctly, follow these steps:

1. Summarize the literature: What main idea is the author trying to purvey? Usually, there will be many hints along the way, so choosing the right direction may not be so challenging.

2. Pick the most prevalent subject: One thing to note is the significant difference between a subject and a theme. A subject is the general topic of conversation—whether it be love, bravery, deception, etc. A theme is a specific point the author is making about said subject. So, find the talking point that is most commonly being brought up. This will be the focal point of the essay.

3. Read between the lines: After finding the most suitable subject, decipher what main point the author is trying to make. This will become clearer as you get deeper into the literature since clues and examples will appear frequently. After fully deciphering the central theme, there is one more significant step.

4. Overall significance: What is the overall significance that comes from the author’s point? What can be taken from this and applied to our personal lives? In other words, what is the lesson from all of this? What have we learned?

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Thematic Essay Outline

The thematic essay has several key components. First of all, it should be five paragraphs or more, depending on the depth of the theme. Next, it should have a concrete thesis statement, which, in other words, is the thematic statement that comes from the main subject. The introduction presents the reader with the subject and the thesis statement. The body paragraphs each discuss one literary element or more to defend the validity of your thesis, all the while providing many supporting details from the text itself. Lastly, the thematic essay conclusion summarizes the main points presented and finishes off with a statement of significance.

Follow the link to learn more about HOW TO CREATE A WINNING OUTLINE

The thematic essay introduction presents the main subject of discussion in a captivating way. The first sentence of the intro should be a hook statement that makes some intriguing claim about the subject of discussion. If done correctly, this will grab your reader's attention. Afterwards, provide any necessary background information from the literature that will help the audience understand your claims later on. Lastly, put together a well thought out thesis statement that reflects the central theme of the novel.

The body paragraphs follow a thematic essay format. Since each body paragraph’s purpose should be to present a literary device as evidence, the topic sentence should introduce the claim and gateway into the evidence. Every topic sentence must mention a literary device and its relationship to the literature.

Afterwards, to validate your claim, use examples from the book that strengthen the reasoning of your statement. These can be actions from the plot or quotations that are parallel with the central theme. It’s imperative to explain how the action/quote links back to your thesis statement, as it shows that you can support your logic.

Remember: each claim must use a literary device. It can not just be a random moment or inference. Thematic essays are all about proving thesis statements through the use of critical literary devices.

The thematic essay conclusion has three main objectives to complete before wrapping up the entire paper. It should not present any new information or facts, but should summarize the information already given. First of all, restate your thesis statement in a new way. Then, summarize the central claims you made within the body of your paper and their influence on the thesis statement. To finish off the entire work, present an overall concluding statement with a global analysis of the subject. Leave your reader with another hook, making him/her interested in digging deeper into the topic.

Try also read an article on poetry analysis essay , it could be useful and can give you new insights.

Thematic Essay Example

The best way to familiarise yourself with this type of writing is to learn from an example. ‍

Even though the ancient Greek cities of Athens and Sparta were geographically close to each other, they had very distinct cultures, lifestyles, values, and political systems that defined them. The following paper compares and contrasts the cultural impacts of the two cities by examining some of the duties and responsibilities of the citizenry as well as the different values that were deemed important. The paper further evaluates the impact of accomplishments that would have been left by both city-states on the history of western civilization.

Wrap Things Up

Before submitting your thematic essay, make sure to check a couple of things to correct any possible errors.

• Double-check and confirm that the central theme you have decided is the one that the author likely meant to focus on. Unless you can provide a secondary issue and present it strongly enough as a primary, validate the primary subject.
• Go through and proofread your entire paper. Nothing makes reading more irritating than grammatical mistakes, clean that stuff up as much as possible.
• Get a second pair of eyes to read through your paper. It’s best to ask a classmate for help, as they most likely have or had a similar assignment. Another great way to polish things up is to ask one of our writers to give you some helpful advice.

We also recommend reading about Jem Finch character traits , our readers find it very interesting.

Having a Trouble with Your Thematic Essay?

Having a hard time thinking up a proper topic to write about? Or, do you have one but are having a hard time deciphering the theme? Let our custom essay writing service do all the work for you. Check out our price calculator to estimate the cost of your assignment.

is an expert in nursing and healthcare, with a strong background in history, law, and literature. Holding advanced degrees in nursing and public health, his analytical approach and comprehensive knowledge help students navigate complex topics. On EssayPro blog, Adam provides insightful articles on everything from historical analysis to the intricacies of healthcare policies. In his downtime, he enjoys historical documentaries and volunteering at local clinics.

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Practical thematic analysis: a guide for multidisciplinary health services research teams engaging in qualitative analysis

• Related content
• Peer review
• Catherine H Saunders , scientist and assistant professor 1 2 ,
• Ailyn Sierpe , research project coordinator 2 ,
• Christian von Plessen , senior physician 3 ,
• Alice M Kennedy , research project manager 2 4 ,
• Laura C Leviton , senior adviser 5 ,
• Steven L Bernstein , chief research officer 1 ,
• Jenaya Goldwag , resident physician 1 ,
• Joel R King , research assistant 2 ,
• Christine M Marx , patient associate 6 ,
• Jacqueline A Pogue , research project manager 2 ,
• Richard K Saunders , staff physician 1 ,
• Aricca Van Citters , senior research scientist 2 ,
• Renata W Yen , doctoral student 2 ,
• Glyn Elwyn , professor 2 ,
• JoAnna K Leyenaar , associate professor 1 2
• on behalf of the Coproduction Laboratory
• 1 Dartmouth Health, Lebanon, NH, USA
• 2 Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth College, Lebanon, NH, USA
• 3 Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
• 4 Jönköping Academy for Improvement of Health and Welfare, School of Health and Welfare, Jönköping University, Jönköping, Sweden
• 5 Highland Park, NJ, USA
• 6 Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, MO, USA
• Correspondence to: C H Saunders catherine.hylas.saunders{at}dartmouth.edu
• Accepted 26 April 2023

Qualitative research methods explore and provide deep contextual understanding of real world issues, including people’s beliefs, perspectives, and experiences. Whether through analysis of interviews, focus groups, structured observation, or multimedia data, qualitative methods offer unique insights in applied health services research that other approaches cannot deliver. However, many clinicians and researchers hesitate to use these methods, or might not use them effectively, which can leave relevant areas of inquiry inadequately explored. Thematic analysis is one of the most common and flexible methods to examine qualitative data collected in health services research. This article offers practical thematic analysis as a step-by-step approach to qualitative analysis for health services researchers, with a focus on accessibility for patients, care partners, clinicians, and others new to thematic analysis. Along with detailed instructions covering three steps of reading, coding, and theming, the article includes additional novel and practical guidance on how to draft effective codes, conduct a thematic analysis session, and develop meaningful themes. This approach aims to improve consistency and rigor in thematic analysis, while also making this method more accessible for multidisciplinary research teams.

Through qualitative methods, researchers can provide deep contextual understanding of real world issues, and generate new knowledge to inform hypotheses, theories, research, and clinical care. Approaches to data collection are varied, including interviews, focus groups, structured observation, and analysis of multimedia data, with qualitative research questions aimed at understanding the how and why of human experience. 1 2 Qualitative methods produce unique insights in applied health services research that other approaches cannot deliver. In particular, researchers acknowledge that thematic analysis is a flexible and powerful method of systematically generating robust qualitative research findings by identifying, analysing, and reporting patterns (themes) within data. 3 4 5 6 Although qualitative methods are increasingly valued for answering clinical research questions, many researchers are unsure how to apply them or consider them too time consuming to be useful in responding to practical challenges 7 or pressing situations such as public health emergencies. 8 Consequently, researchers might hesitate to use them, or use them improperly. 9 10 11

Although much has been written about how to perform thematic analysis, practical guidance for non-specialists is sparse. 3 5 6 12 13 In the multidisciplinary field of health services research, qualitative data analysis can confound experienced researchers and novices alike, which can stoke concerns about rigor, particularly for those more familiar with quantitative approaches. 14 Since qualitative methods are an area of specialisation, support from experts is beneficial. However, because non-specialist perspectives can enhance data interpretation and enrich findings, there is a case for making thematic analysis easier, more rapid, and more efficient, 8 particularly for patients, care partners, clinicians, and other stakeholders. A practical guide to thematic analysis might encourage those on the ground to use these methods in their work, unearthing insights that would otherwise remain undiscovered.

Given the need for more accessible qualitative analysis approaches, we present a simple, rigorous, and efficient three step guide for practical thematic analysis. We include new guidance on the mechanics of thematic analysis, including developing codes, constructing meaningful themes, and hosting a thematic analysis session. We also discuss common pitfalls in thematic analysis and how to avoid them.

Summary points

Qualitative methods are increasingly valued in applied health services research, but multidisciplinary research teams often lack accessible step-by-step guidance and might struggle to use these approaches

A newly developed approach, practical thematic analysis, uses three simple steps: reading, coding, and theming

Based on Braun and Clarke’s reflexive thematic analysis, our streamlined yet rigorous approach is designed for multidisciplinary health services research teams, including patients, care partners, and clinicians

This article also provides companion materials including a slide presentation for teaching practical thematic analysis to research teams, a sample thematic analysis session agenda, a theme coproduction template for use during the session, and guidance on using standardised reporting criteria for qualitative research

In their seminal work, Braun and Clarke developed a six phase approach to reflexive thematic analysis. 4 12 We built on their method to develop practical thematic analysis ( box 1 , fig 1 ), which is a simplified and instructive approach that retains the substantive elements of their six phases. Braun and Clarke’s phase 1 (familiarising yourself with the dataset) is represented in our first step of reading. Phase 2 (coding) remains as our second step of coding. Phases 3 (generating initial themes), 4 (developing and reviewing themes), and 5 (refining, defining, and naming themes) are represented in our third step of theming. Phase 6 (writing up) also occurs during this third step of theming, but after a thematic analysis session. 4 12

Key features and applications of practical thematic analysis

Step 1: reading.

All manuscript authors read the data

All manuscript authors write summary memos

Step 2: Coding

Coders perform both data management and early data analysis

Codes are complete thoughts or sentences, not categories

Step 3: Theming

Researchers host a thematic analysis session and share different perspectives

Themes are complete thoughts or sentences, not categories

Applications

For use by practicing clinicians, patients and care partners, students, interdisciplinary teams, and those new to qualitative research

When important insights from healthcare professionals are inaccessible because they do not have qualitative methods training

When time and resources are limited

Steps in practical thematic analysis

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We present linear steps, but as qualitative research is usually iterative, so too is thematic analysis. 15 Qualitative researchers circle back to earlier work to check whether their interpretations still make sense in the light of additional insights, adapting as necessary. While we focus here on the practical application of thematic analysis in health services research, we recognise our approach exists in the context of the broader literature on thematic analysis and the theoretical underpinnings of qualitative methods as a whole. For a more detailed discussion of these theoretical points, as well as other methods widely used in health services research, we recommend reviewing the sources outlined in supplemental material 1. A strong and nuanced understanding of the context and underlying principles of thematic analysis will allow for higher quality research. 16

Practical thematic analysis is a highly flexible approach that can draw out valuable findings and generate new hypotheses, including in cases with a lack of previous research to build on. The approach can also be used with a variety of data, such as transcripts from interviews or focus groups, patient encounter transcripts, professional publications, observational field notes, and online activity logs. Importantly, successful practical thematic analysis is predicated on having high quality data collected with rigorous methods. We do not describe qualitative research design or data collection here. 11 17

In supplemental material 1, we summarise the foundational methods, concepts, and terminology in qualitative research. Along with our guide below, we include a companion slide presentation for teaching practical thematic analysis to research teams in supplemental material 2. We provide a theme coproduction template for teams to use during thematic analysis sessions in supplemental material 3. Our method aligns with the major qualitative reporting frameworks, including the Consolidated Criteria for Reporting Qualitative Research (COREQ). 18 We indicate the corresponding step in practical thematic analysis for each COREQ item in supplemental material 4.

Familiarisation and memoing

We encourage all manuscript authors to review the full dataset (eg, interview transcripts) to familiarise themselves with it. This task is most critical for those who will later be engaged in the coding and theming steps. Although time consuming, it is the best way to involve team members in the intellectual work of data interpretation, so that they can contribute to the analysis and contextualise the results. If this task is not feasible given time limitations or large quantities of data, the data can be divided across team members. In this case, each piece of data should be read by at least two individuals who ideally represent different professional roles or perspectives.

We recommend that researchers reflect on the data and independently write memos, defined as brief notes on thoughts and questions that arise during reading, and a summary of their impressions of the dataset. 2 19 Memoing is an opportunity to gain insights from varying perspectives, particularly from patients, care partners, clinicians, and others. It also gives researchers the opportunity to begin to scope which elements of and concepts in the dataset are relevant to the research question.

Data saturation

The concept of data saturation ( box 2 ) is a foundation of qualitative research. It is defined as the point in analysis at which new data tend to be redundant of data already collected. 21 Qualitative researchers are expected to report their approach to data saturation. 18 Because thematic analysis is iterative, the team should discuss saturation throughout the entire process, beginning with data collection and continuing through all steps of the analysis. 22 During step 1 (reading), team members might discuss data saturation in the context of summary memos. Conversations about saturation continue during step 2 (coding), with confirmation that saturation has been achieved during step 3 (theming). As a rule of thumb, researchers can often achieve saturation in 9-17 interviews or 4-8 focus groups, but this will vary depending on the specific characteristics of the study. 23

Data saturation in context

Braun and Clarke discourage the use of data saturation to determine sample size (eg, number of interviews), because it assumes that there is an objective truth to be captured in the data (sometimes known as a positivist perspective). 20 Qualitative researchers often try to avoid positivist approaches, arguing that there is no one true way of seeing the world, and will instead aim to gather multiple perspectives. 5 Although this theoretical debate with qualitative methods is important, we recognise that a priori estimates of saturation are often needed, particularly for investigators newer to qualitative research who might want a more pragmatic and applied approach. In addition, saturation based, sample size estimation can be particularly helpful in grant proposals. However, researchers should still follow a priori sample size estimation with a discussion to confirm saturation has been achieved.

Definition of coding

We describe codes as labels for concepts in the data that are directly relevant to the study objective. Historically, the purpose of coding was to distil the large amount of data collected into conceptually similar buckets so that researchers could review it in aggregate and identify key themes. 5 24 We advocate for a more analytical approach than is typical with thematic analysis. With our method, coding is both the foundation for and the beginning of thematic analysis—that is, early data analysis, management, and reduction occur simultaneously rather than as different steps. This approach moves the team more efficiently towards being able to describe themes.

Building the coding team

Coders are the research team members who directly assign codes to the data, reading all material and systematically labelling relevant data with appropriate codes. Ideally, at least two researchers would code every discrete data document, such as one interview transcript. 25 If this task is not possible, individual coders can each code a subset of the data that is carefully selected for key characteristics (sometimes known as purposive selection). 26 When using this approach, we recommend that at least 10% of data be coded by two or more coders to ensure consistency in codebook application. We also recommend coding teams of no more than four to five people, for practical reasons concerning maintaining consistency.

Clinicians, patients, and care partners bring unique perspectives to coding and enrich the analytical process. 27 Therefore, we recommend choosing coders with a mix of relevant experiences so that they can challenge and contextualise each other’s interpretations based on their own perspectives and opinions ( box 3 ). We recommend including both coders who collected the data and those who are naive to it, if possible, given their different perspectives. We also recommend all coders review the summary memos from the reading step so that key concepts identified by those not involved in coding can be integrated into the analytical process. In practice, this review means coding the memos themselves and discussing them during the code development process. This approach ensures that the team considers a diversity of perspectives.

Coding teams in context

The recommendation to use multiple coders is a departure from Braun and Clarke. 28 29 When the views, experiences, and training of each coder (sometimes known as positionality) 30 are carefully considered, having multiple coders can enhance interpretation and enrich findings. When these perspectives are combined in a team setting, researchers can create shared meaning from the data. Along with the practical consideration of distributing the workload, 31 inclusion of these multiple perspectives increases the overall quality of the analysis by mitigating the impact of any one coder’s perspective. 30

Coding tools

Qualitative analysis software facilitates coding and managing large datasets but does not perform the analytical work. The researchers must perform the analysis themselves. Most programs support queries and collaborative coding by multiple users. 32 Important factors to consider when choosing software can include accessibility, cost, interoperability, the look and feel of code reports, and the ease of colour coding and merging codes. Coders can also use low tech solutions, including highlighters, word processors, or spreadsheets.

Drafting effective codes

To draft effective codes, we recommend that the coders review each document line by line. 33 As they progress, they can assign codes to segments of data representing passages of interest. 34 Coders can also assign multiple codes to the same passage. Consensus among coders on what constitutes a minimum or maximum amount of text for assigning a code is helpful. As a general rule, meaningful segments of text for coding are shorter than one paragraph, but longer than a few words. Coders should keep the study objective in mind when determining which data are relevant ( box 4 ).

Code types in context

Similar to Braun and Clarke’s approach, practical thematic analysis does not specify whether codes are based on what is evident from the data (sometimes known as semantic) or whether they are based on what can be inferred at a deeper level from the data (sometimes known as latent). 4 12 35 It also does not specify whether they are derived from the data (sometimes known as inductive) or determined ahead of time (sometimes known as deductive). 11 35 Instead, it should be noted that health services researchers conducting qualitative studies often adopt all these approaches to coding (sometimes known as hybrid analysis). 3

In practical thematic analysis, codes should be more descriptive than general categorical labels that simply group data with shared characteristics. At a minimum, codes should form a complete (or full) thought. An easy way to conceptualise full thought codes is as complete sentences with subjects and verbs ( table 1 ), although full sentence coding is not always necessary. With full thought codes, researchers think about the data more deeply and capture this insight in the codes. This coding facilitates the entire analytical process and is especially valuable when moving from codes to broader themes. Experienced qualitative researchers often intuitively use full thought or sentence codes, but this practice has not been explicitly articulated as a path to higher quality coding elsewhere in the literature. 6

Example transcript with codes used in practical thematic analysis 36

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Depending on the nature of the data, codes might either fall into flat categories or be arranged hierarchically. Flat categories are most common when the data deal with topics on the same conceptual level. In other words, one topic is not a subset of another topic. By contrast, hierarchical codes are more appropriate for concepts that naturally fall above or below each other. Hierarchical coding can also be a useful form of data management and might be necessary when working with a large or complex dataset. 5 Codes grouped into these categories can also make it easier to naturally transition into generating themes from the initial codes. 5 These decisions between flat versus hierarchical coding are part of the work of the coding team. In both cases, coders should ensure that their code structures are guided by their research questions.

Developing the codebook

A codebook is a shared document that lists code labels and comprehensive descriptions for each code, as well as examples observed within the data. Good code descriptions are precise and specific so that coders can consistently assign the same codes to relevant data or articulate why another coder would do so. Codebook development is iterative and involves input from the entire coding team. However, as those closest to the data, coders must resist undue influence, real or perceived, from other team members with conflicting opinions—it is important to mitigate the risk that more senior researchers, like principal investigators, exert undue influence on the coders’ perspectives.

In practical thematic analysis, coders begin codebook development by independently coding a small portion of the data, such as two to three transcripts or other units of analysis. Coders then individually produce their initial codebooks. This task will require them to reflect on, organise, and clarify codes. The coders then meet to reconcile the draft codebooks, which can often be difficult, as some coders tend to lump several concepts together while others will split them into more specific codes. Discussing disagreements and negotiating consensus are necessary parts of early data analysis. Once the codebook is relatively stable, we recommend soliciting input on the codes from all manuscript authors. Yet, coders must ultimately be empowered to finalise the details so that they are comfortable working with the codebook across a large quantity of data.

Assigning codes to the data

After developing the codebook, coders will use it to assign codes to the remaining data. While the codebook’s overall structure should remain constant, coders might continue to add codes corresponding to any new concepts observed in the data. If new codes are added, coders should review the data they have already coded and determine whether the new codes apply. Qualitative data analysis software can be useful for editing or merging codes.

We recommend that coders periodically compare their code occurrences ( box 5 ), with more frequent check-ins if substantial disagreements occur. In the event of large discrepancies in the codes assigned, coders should revise the codebook to ensure that code descriptions are sufficiently clear and comprehensive to support coding alignment going forward. Because coding is an iterative process, the team can adjust the codebook as needed. 5 28 29

Quantitative coding in context

Researchers should generally avoid reporting code counts in thematic analysis. However, counts can be a useful proxy in maintaining alignment between coders on key concepts. 26 In practice, therefore, researchers should make sure that all coders working on the same piece of data assign the same codes with a similar pattern and that their memoing and overall assessment of the data are aligned. 37 However, the frequency of a code alone is not an indicator of its importance. It is more important that coders agree on the most salient points in the data; reviewing and discussing summary memos can be helpful here. 5

Researchers might disagree on whether or not to calculate and report inter-rater reliability. We note that quantitative tests for agreement, such as kappa statistics or intraclass correlation coefficients, can be distracting and might not provide meaningful results in qualitative analyses. Similarly, Braun and Clarke argue that expecting perfect alignment on coding is inconsistent with the goal of co-constructing meaning. 28 29 Overall consensus on codes’ salience and contributions to themes is the most important factor.

Definition of themes

Themes are meta-constructs that rise above codes and unite the dataset ( box 6 , fig 2 ). They should be clearly evident, repeated throughout the dataset, and relevant to the research questions. 38 While codes are often explicit descriptions of the content in the dataset, themes are usually more conceptual and knit the codes together. 39 Some researchers hypothesise that theme development is loosely described in the literature because qualitative researchers simply intuit themes during the analytical process. 39 In practical thematic analysis, we offer a concrete process that should make developing meaningful themes straightforward.

Themes in context

According to Braun and Clarke, a theme “captures something important about the data in relation to the research question and represents some level of patterned response or meaning within the data set.” 4 Similarly, Braun and Clarke advise against themes as domain summaries. While different approaches can draw out themes from codes, the process begins by identifying patterns. 28 35 Like Braun and Clarke and others, we recommend that researchers consider the salience of certain themes, their prevalence in the dataset, and their keyness (ie, how relevant the themes are to the overarching research questions). 4 12 34

Use of themes in practical thematic analysis

Constructing meaningful themes

After coding all the data, each coder should independently reflect on the team’s summary memos (step 1), the codebook (step 2), and the coded data itself to develop draft themes (step 3). It can be illuminating for coders to review all excerpts associated with each code, so that they derive themes directly from the data. Researchers should remain focused on the research question during this step, so that themes have a clear relation with the overall project aim. Use of qualitative analysis software will make it easy to view each segment of data tagged with each code. Themes might neatly correspond to groups of codes. Or—more likely—they will unite codes and data in unexpected ways. A whiteboard or presentation slides might be helpful to organise, craft, and revise themes. We also provide a template for coproducing themes (supplemental material 3). As with codebook justification, team members will ideally produce individual drafts of the themes that they have identified in the data. They can then discuss these with the group and reach alignment or consensus on the final themes.

The team should ensure that all themes are salient, meaning that they are: supported by the data, relevant to the study objectives, and important. Similar to codes, themes are framed as complete thoughts or sentences, not categories. While codes and themes might appear to be similar to each other, the key distinction is that the themes represent a broader concept. Table 2 shows examples of codes and their corresponding themes from a previously published project that used practical thematic analysis. 36 Identifying three to four key themes that comprise a broader overarching theme is a useful approach. Themes can also have subthemes, if appropriate. 40 41 42 43 44

Example codes with themes in practical thematic analysis 36

Thematic analysis session

After each coder has independently produced draft themes, a carefully selected subset of the manuscript team meets for a thematic analysis session ( table 3 ). The purpose of this session is to discuss and reach alignment or consensus on the final themes. We recommend a session of three to five hours, either in-person or virtually.

Example agenda of thematic analysis session

The composition of the thematic analysis session team is important, as each person’s perspectives will shape the results. This group is usually a small subset of the broader research team, with three to seven individuals. We recommend that primary and senior authors work together to include people with diverse experiences related to the research topic. They should aim for a range of personalities and professional identities, particularly those of clinicians, trainees, patients, and care partners. At a minimum, all coders and primary and senior authors should participate in the thematic analysis session.

The session begins with each coder presenting their draft themes with supporting quotes from the data. 5 Through respectful and collaborative deliberation, the group will develop a shared set of final themes.

One team member facilitates the session. A firm, confident, and consistent facilitation style with good listening skills is critical. For practical reasons, this person is not usually one of the primary coders. Hierarchies in teams cannot be entirely flattened, but acknowledging them and appointing an external facilitator can reduce their impact. The facilitator can ensure that all voices are heard. For example, they might ask for perspectives from patient partners or more junior researchers, and follow up on comments from senior researchers to say, “We have heard your perspective and it is important; we want to make sure all perspectives in the room are equally considered.” Or, “I hear [senior person] is offering [x] idea, I’d like to hear other perspectives in the room.” The role of the facilitator is critical in the thematic analysis session. The facilitator might also privately discuss with more senior researchers, such as principal investigators and senior authors, the importance of being aware of their influence over others and respecting and eliciting the perspectives of more junior researchers, such as patients, care partners, and students.

To our knowledge, this discrete thematic analysis session is a novel contribution of practical thematic analysis. It helps efficiently incorporate diverse perspectives using the session agenda and theme coproduction template (supplemental material 3) and makes the process of constructing themes transparent to the entire research team.

Writing the report

We recommend beginning the results narrative with a summary of all relevant themes emerging from the analysis, followed by a subheading for each theme. Each subsection begins with a brief description of the theme and is illustrated with relevant quotes, which are contextualised and explained. The write-up should not simply be a list, but should contain meaningful analysis and insight from the researchers, including descriptions of how different stakeholders might have experienced a particular situation differently or unexpectedly.

In addition to weaving quotes into the results narrative, quotes can be presented in a table. This strategy is a particularly helpful when submitting to clinical journals with tight word count limitations. Quote tables might also be effective in illustrating areas of agreement and disagreement across stakeholder groups, with columns representing different groups and rows representing each theme or subtheme. Quotes should include an anonymous label for each participant and any relevant characteristics, such as role or gender. The aim is to produce rich descriptions. 5 We recommend against repeating quotations across multiple themes in the report, so as to avoid confusion. The template for coproducing themes (supplemental material 3) allows documentation of quotes supporting each theme, which might also be useful during report writing.

Visual illustrations such as a thematic map or figure of the findings can help communicate themes efficiently. 4 36 42 44 If a figure is not possible, a simple list can suffice. 36 Both must clearly present the main themes with subthemes. Thematic figures can facilitate confirmation that the researchers’ interpretations reflect the study populations’ perspectives (sometimes known as member checking), because authors can invite discussions about the figure and descriptions of findings and supporting quotes. 46 This process can enhance the validity of the results. 46

In supplemental material 4, we provide additional guidance on reporting thematic analysis consistent with COREQ. 18 Commonly used in health services research, COREQ outlines a standardised list of items to be included in qualitative research reports ( box 7 ).

Reporting in context

We note that use of COREQ or any other reporting guidelines does not in itself produce high quality work and should not be used as a substitute for general methodological rigor. Rather, researchers must consider rigor throughout the entire research process. As the issue of how to conceptualise and achieve rigorous qualitative research continues to be debated, 47 48 we encourage researchers to explicitly discuss how they have looked at methodological rigor in their reports. Specifically, we point researchers to Braun and Clarke’s 2021 tool for evaluating thematic analysis manuscripts for publication (“Twenty questions to guide assessment of TA [thematic analysis] research quality”). 16

Avoiding common pitfalls

Awareness of common mistakes can help researchers avoid improper use of qualitative methods. Improper use can, for example, prevent researchers from developing meaningful themes and can risk drawing inappropriate conclusions from the data. Braun and Clarke also warn of poor quality in qualitative research, noting that “coherence and integrity of published research does not always hold.” 16

Weak themes

An important distinction between high and low quality themes is that high quality themes are descriptive and complete thoughts. As such, they often contain subjects and verbs, and can be expressed as full sentences ( table 2 ). Themes that are simply descriptive categories or topics could fail to impart meaningful knowledge beyond categorisation. 16 49 50

Researchers will often move from coding directly to writing up themes, without performing the work of theming or hosting a thematic analysis session. Skipping concerted theming often results in themes that look more like categories than unifying threads across the data.

Unfocused analysis

Because data collection for qualitative research is often semi-structured (eg, interviews, focus groups), not all data will be directly relevant to the research question at hand. To avoid unfocused analysis and a correspondingly unfocused manuscript, we recommend that all team members keep the research objective in front of them at every stage, from reading to coding to theming. During the thematic analysis session, we recommend that the research question be written on a whiteboard so that all team members can refer back to it, and so that the facilitator can ensure that conversations about themes occur in the context of this question. Consistently focusing on the research question can help to ensure that the final report directly answers it, as opposed to the many other interesting insights that might emerge during the qualitative research process. Such insights can be picked up in a secondary analysis if desired.

Inappropriate quantification

Presenting findings quantitatively (eg, “We found 18 instances of participants mentioning safety concerns about the vaccines”) is generally undesirable in practical thematic analysis reporting. 51 Descriptive terms are more appropriate (eg, “participants had substantial concerns about the vaccines,” or “several participants were concerned about this”). This descriptive presentation is critical because qualitative data might not be consistently elicited across participants, meaning that some individuals might share certain information while others do not, simply based on how conversations evolve. Additionally, qualitative research does not aim to draw inferences outside its specific sample. Emphasising numbers in thematic analysis can lead to readers incorrectly generalising the findings. Although peer reviewers unfamiliar with thematic analysis often request this type of quantification, practitioners of practical thematic analysis can confidently defend their decision to avoid it. If quantification is methodologically important, we recommend simultaneously conducting a survey or incorporating standardised interview techniques into the interview guide. 11

Neglecting group dynamics

Researchers should concertedly consider group dynamics in the research team. Particular attention should be paid to power relations and the personality of team members, which can include aspects such as who most often speaks, who defines concepts, and who resolves disagreements that might arise within the group. 52

The perspectives of patient and care partners are particularly important to cultivate. Ideally, patient partners are meaningfully embedded in studies from start to finish, not just for practical thematic analysis. 53 Meaningful engagement can build trust, which makes it easier for patient partners to ask questions, request clarification, and share their perspectives. Professional team members should actively encourage patient partners by emphasising that their expertise is critically important and valued. Noting when a patient partner might be best positioned to offer their perspective can be particularly powerful.

Insufficient time allocation

Researchers must allocate enough time to complete thematic analysis. Working with qualitative data takes time, especially because it is often not a linear process. As the strength of thematic analysis lies in its ability to make use of the rich details and complexities of the data, we recommend careful planning for the time required to read and code each document.

Estimating the necessary time can be challenging. For step 1 (reading), researchers can roughly calculate the time required based on the time needed to read and reflect on one piece of data. For step 2 (coding), the total amount of time needed can be extrapolated from the time needed to code one document during codebook development. We also recommend three to five hours for the thematic analysis session itself, although coders will need to independently develop their draft themes beforehand. Although the time required for practical thematic analysis is variable, teams should be able to estimate their own required effort with these guidelines.

Practical thematic analysis builds on the foundational work of Braun and Clarke. 4 16 We have reframed their six phase process into three condensed steps of reading, coding, and theming. While we have maintained important elements of Braun and Clarke’s reflexive thematic analysis, we believe that practical thematic analysis is conceptually simpler and easier to teach to less experienced researchers and non-researcher stakeholders. For teams with different levels of familiarity with qualitative methods, this approach presents a clear roadmap to the reading, coding, and theming of qualitative data. Our practical thematic analysis approach promotes efficient learning by doing—experiential learning. 12 29 Practical thematic analysis avoids the risk of relying on complex descriptions of methods and theory and places more emphasis on obtaining meaningful insights from those close to real world clinical environments. Although practical thematic analysis can be used to perform intensive theory based analyses, it lends itself more readily to accelerated, pragmatic approaches.

Strengths and limitations

Our approach is designed to smooth the qualitative analysis process and yield high quality themes. Yet, researchers should note that poorly performed analyses will still produce low quality results. Practical thematic analysis is a qualitative analytical approach; it does not look at study design, data collection, or other important elements of qualitative research. It also might not be the right choice for every qualitative research project. We recommend it for applied health services research questions, where diverse perspectives and simplicity might be valuable.

We also urge researchers to improve internal validity through triangulation methods, such as member checking (supplemental material 1). 46 Member checking could include soliciting input on high level themes, theme definitions, and quotations from participants. This approach might increase rigor.

Implications

We hope that by providing clear and simple instructions for practical thematic analysis, a broader range of researchers will be more inclined to use these methods. Increased transparency and familiarity with qualitative approaches can enhance researchers’ ability to both interpret qualitative studies and offer up new findings themselves. In addition, it can have usefulness in training and reporting. A major strength of this approach is to facilitate meaningful inclusion of patient and care partner perspectives, because their lived experiences can be particularly valuable in data interpretation and the resulting findings. 11 30 As clinicians are especially pressed for time, they might also appreciate a practical set of instructions that can be immediately used to leverage their insights and access to patients and clinical settings, and increase the impact of qualitative research through timely results. 8

Practical thematic analysis is a simplified approach to performing thematic analysis in health services research, a field where the experiences of patients, care partners, and clinicians are of inherent interest. We hope that it will be accessible to those individuals new to qualitative methods, including patients, care partners, clinicians, and other health services researchers. We intend to empower multidisciplinary research teams to explore unanswered questions and make new, important, and rigorous contributions to our understanding of important clinical and health systems research.

Acknowledgments

All members of the Coproduction Laboratory provided input that shaped this manuscript during laboratory meetings. We acknowledge advice from Elizabeth Carpenter-Song, an expert in qualitative methods.

Coproduction Laboratory group contributors: Stephanie C Acquilano ( http://orcid.org/0000-0002-1215-5531 ), Julie Doherty ( http://orcid.org/0000-0002-5279-6536 ), Rachel C Forcino ( http://orcid.org/0000-0001-9938-4830 ), Tina Foster ( http://orcid.org/0000-0001-6239-4031 ), Megan Holthoff, Christopher R Jacobs ( http://orcid.org/0000-0001-5324-8657 ), Lisa C Johnson ( http://orcid.org/0000-0001-7448-4931 ), Elaine T Kiriakopoulos, Kathryn Kirkland ( http://orcid.org/0000-0002-9851-926X ), Meredith A MacMartin ( http://orcid.org/0000-0002-6614-6091 ), Emily A Morgan, Eugene Nelson, Elizabeth O’Donnell, Brant Oliver ( http://orcid.org/0000-0002-7399-622X ), Danielle Schubbe ( http://orcid.org/0000-0002-9858-1805 ), Gabrielle Stevens ( http://orcid.org/0000-0001-9001-178X ), Rachael P Thomeer ( http://orcid.org/0000-0002-5974-3840 ).

Contributors: Practical thematic analysis, an approach designed for multidisciplinary health services teams new to qualitative research, was based on CHS’s experiences teaching thematic analysis to clinical teams and students. We have drawn heavily from qualitative methods literature. CHS is the guarantor of the article. CHS, AS, CvP, AMK, JRK, and JAP contributed to drafting the manuscript. AS, JG, CMM, JAP, and RWY provided feedback on their experiences using practical thematic analysis. CvP, LCL, SLB, AVC, GE, and JKL advised on qualitative methods in health services research, given extensive experience. All authors meaningfully edited the manuscript content, including AVC and RKS. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: This manuscript did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Provenance and peer review: Not commissioned; externally peer reviewed.

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Home ➔ How to Write an Essay ➔ Thematic Essay

Thematic Essay Guide

Thematic writing is a staple of high school English and college writing courses. The idea behind thematic writing is to create a piece that uses a theme to tie together different ideas or topics. Thematic writing can be used for essays, short stories, novels, and even non-fiction pieces. In academic writing, thematic essays often center on a specific issue or theme and develop that theme throughout the essay.

Thematic essays are often assigned in high school English classes and college writing courses. They are also found on standardized tests such as the SAT and ACT.

If you need to refresh your memory regarding general essay writing, check our detailed guide: How to Write an Essay

There are a few different literary devices that are often used in thematic writing. These devices can help create a more cohesive essay or story and can also help emphasize the theme.

One literary device that is often used in thematic writing is symbolism. Symbolism is when an object, person, or place represents something else. For example, in the novel The Great Gatsby, the character Daisy Buchanan symbolizes wealth and shallowness. In the story “The Lottery” by Shirley Jackson, the black box that is used for the lottery represents tradition and the blind following of rules.

Definition and Purpose

A thematic essay is an essay that requires you to write about a particular question or theme. Thematic essays are often written in response to prompts that ask you to discuss a specific aspect of a larger topic.

The main point of a thematic essay is to show the development of a theme throughout a work of literature or to compare the way different authors or works deal with similar themes.

Essentials of a thematic essay:

• must be focused on a central theme
• must develop that theme with specific examples from the text(s)
• must synthesize several elements of the text(s), including plot, character, setting, style, tone, etc.
• must not be a mere plot summary
• must use evidence from the text(s) to support your argument
• must be well organized, with a clear introduction, body paragraphs, and conclusion

If you want to learn more about essays in general, we suggest you read this guide: Essay Definition

Pre-writing stage

Before you write a thematic essay, it is important first to understand the prompt and Rubric . The prompt will ask you to write about a specific theme, such as “Justice in Othello.” The Rubric will outline the specific requirements for the essay, including things like length, formatting, and the inclusion of outside sources.

So, before writing a thematic essay, you should carefully read the prompt and think about what you want to write about. Make sure that you understand what the prompt is asking you to do.

Some tips for pre-writing:

• Brainstorm possible themes or ideas that could be related to the prompt.
• Choose a central theme or idea you are interested in and think you can write about persuasively.
• Come up with specific examples from the text(s) that you can use to support your argument.
• Make a list of the different ways that the overall significance of the theme or idea can be developed.
• Decide on the main point you want to make about the theme or idea.
• Organize your thoughts and develop a thesis statement.

Analyzing the prompt and developing a thesis statement

To write a thematic essay, you need to analyze the prompt first. You will need to identify the task that the prompt is asking you to do, and you will need to identify the main idea of the passage.

For example, a prompt might ask you to write about the use of symbols in a work of literature. To answer this prompt, you would need to identify the different ways that symbols are used in the text. You also need to determine what the author is trying to communicate using symbols.

Literary theme analysis prompt example ( TKAM ):

How does Harper Lee use the symbol of the mockingbird to explore the theme of innocence in To Kill a Mockingbird?

When analyzing this prompt, consider what the mockingbird symbolizes in the novel and how this relates to the larger theme of innocence. You might discuss specific characters who embody innocence, such as Scout or Atticus, and how the events of the novel impact them. You might also discuss the impact of innocence on the town of Maycomb as a whole.

One example of how Harper Lee uses the symbol of the mockingbird to explore the theme of innocence is through the character of Scout. Scout is a young girl who is innocent and naive in many ways. She does not understand the prejudice and hatred that exists in her community. However, she can also see the good in people, even when they are not perfect. The mockingbird symbolizes this innocence.

Your thesis statement can look something like this:

The symbol of the mockingbird in To Kill a Mockingbird by Harper Lee is used to represent the innocence of characters like Scout and Atticus, as well as the innocence of the town of Maycomb as a whole.

Other examples of thematic essay topics:

• The Catcher in the Rye: How does J.D. Salinger use the character of Holden Caulfield to explore the theme of teenage angst and rebellion?
• Heart of Darkness: How does Joseph Conrad use the character of Kurtz to explore the theme of colonialism and its effects on the human psyche?
• All Summer in a Day: How does Ray Bradbury use the character of Margot to explore the theme of bullying and its effects on victims?
• The Great Gatsby: How does F. Scott Fitzgerald use the character of Daisy Buchanan to explore the theme of the American Dream?
• Metamorphosis: How does Franz Kafka use the character of Gregor Samsa to explore the theme of alienation?

Outlining your thematic essay

After you have analyzed the prompt and developed a thesis statement, you can begin to outline your essay .

Thematic essays usually have a standard structure and consist of five paragraphs. That typically requires you to include an introduction, three body paragraphs, and a conclusion.

Each body paragraph should discuss a different aspect of your thesis. For example, if you need to write a thematic essay about the use of symbols in a work of literature, you might discuss how symbols represent different themes in the novel.

Your thematic essay outline might look something like this:

Introduction:

• Provide a brief overview of the work of literature you will be discussing
• Introduce the main idea or central theme that you will be discussing
• Thesis: The symbol of the mockingbird in To Kill a Mockingbird by Harper Lee is used to represent the innocence of characters like Scout and Atticus, as well as the innocence of the town of Maycomb as a whole.

Body Paragraph 1: Symbols representing innocence

• The mockingbird symbolizes Scout’s innocence
• The mockingbird symbolizes Atticus’ innocence
• The mockingbird symbolizes the innocence of Maycomb

Body Paragraph 2: The loss of innocence

• Scout loses her innocence when she witnesses the trial
• Atticus loses his innocence when Mr. Ewell attacks him
• Maycomb loses its innocence when Tom Robinson is convicted

Body Paragraph 3: The importance of innocence

• Innocence is important because it allows people to see the good in others
• Innocence is important because it allows people to hope for a better future
• Innocence is important because it allows people to see the world in a more positive light

Conclusion:

• Restate your thesis statement
• Discuss the larger implications of your thesis statement
• Leave the reader with something to think about

You can also dedicate each body paragraph to one specific character or one specific event in the novel.

For example, you might discuss how Scout’s innocence is represented by the mockingbird symbol and how this innocence is lost when she witnesses the trial. In your second body paragraph, you could discuss how Atticus’ innocence is represented by the mockingbird symbol and how this innocence is lost when he is attacked by Mr. Ewell. In your third body paragraph, you might discuss how the innocence of Maycomb is represented by the mockingbird symbol and how this innocence is lost when Tom Robinson is convicted.

Writing the thematic essay

Once you have developed a clear thesis statement and created a thematic essay outline, you can begin writing. We complement each section with a thematic essay example part to better illustrate how it can look.

Introduction

The introduction of your thematic essay should briefly state what you will be discussing in your paper and provide background information. The introduction should also include your thesis statement, which is the main argument of your paper, at the end.

At the very start, you can also use a hook to grab the reader’s attention . A hook is usually a sentence or two that draws the reader in and piques their interest.

Introduction example of a thematic essay:

“Mockingbirds don’t do one thing but make music for us to enjoy. They don’t eat up people’s gardens, don’t nest in corncribs, they don’t do one thing but sing their hearts out for us. That’s why it’s a sin to kill a mockingbird.” This quote, spoken by Atticus Finch, perfectly encapsulates the symbol of the mockingbird in Harper Lee’s To Kill a Mockingbird. To Kill a Mockingbird by Harper Lee is a novel about the loss of innocence. The symbol of the mockingbird is used to represent the innocence of characters like Scout and Atticus, as well as the innocence of the town of Maycomb as a whole. The loss of innocence is an important theme in the novel, and it is represented in the characters of Scout, Atticus, and Maycomb.

Body paragraphs

Your body paragraphs should each be dedicated to one specific character or event in the novel and start with a topic sentence . After the topic sentence, you should use evidence to support it. You must analyze the evidence, not just merely state it. Lastly, end your body paragraph with a conclusion and transition to the next section.

A thematic essay body paragraph example:

One example of the loss of innocence is Scout. When the novel begins, Scout is an innocent child who does not understand the ways of the world. “‘Don’t you ever do that again,’ I said. ‘Don’t you ever do that again, it’s bad enough having Jem tell on me without you adding to it.’” (Lee 9). Scout is chastised by her father, Atticus, for fighting with her cousin, Francis. In this quote, Scout does not understand why fighting is bad and must be scolded by Atticus. However, by the end of the novel, Scout has learned the true evil that exists in the world and has lost her innocence. “It was then that I finally understood Mrs. Dubose’s courage, not because she had won, but because she had had the courage to fight and the strength to lose.” (Lee 281). Scout has come to understand that even though Mrs. Dubose lost her battle with addiction, she was still brave for fighting it. Mrs. Dubose’s courage has taught Scout that even in the face of defeat, there is still hope. Scout has lost her innocence because she has learned that the world is not a perfect place and that people are not always good.

Check our citation guide to learn more about using quotes in essay: How to Introduce a Quote

Your concluding statement should sum up the main points of your thematic essay and rephrase your thesis (restate it in different words). You can also discuss broader implications or give your opinion on the topic, but don’t add any new information.

A conclusion example of a thematic essay:

To Kill a Mockingbird is a novel about innocence—the loss of it, the destruction of it, and the fight to keep it. The characters of Scout, Atticus, and Maycomb all represent different aspects of innocence, and the novel explores how they each deal with the loss of their innocence. Scout loses innocence when she learns that the world is not perfect and people are not always good. Atticus loses his innocence when he realizes that sometimes the justice system does not work as it should. Maycomb loses its innocence when it is revealed that racism and prejudice are alive and well in the town. The loss of innocence is a sad but inevitable part of life, and To Kill a Mockingbird shows us that this loss can sometimes be for the better.

Final tips on thematic essay writing

Now that you know the main steps involved in the writing process of a decent thematic essay, here are some of the final tips and key takeaways that you should keep in mind when doing this task:

• Make sure to brainstorm first and develop a good thesis statement that will guide the rest of your essay.
• Create a thematic essay outline before starting to write the essay itself. This will help you stay on track and not miss any important points that you want to include.
• Start each body paragraph with a topic sentence that introduces the paragraph’s main point.
• Use concrete and specific examples to support your points.
• Pay attention to your grammar and spelling.
• Make sure to conclude your thematic essay in a strong way that ties everything together.
• Analyze the work, not just summarize it.
• Take your time, and don’t rush the essay.
• And lastly, proofread your work before submitting it.

By following these tips, you should be able to write a thematic essay that will impress your teacher or professor.

• Solano Community College – World Literature
• Jefferson State Community College – Literary Theme Analysis

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How to Write a Thematic Essay?

06 August, 2020

12 minutes read

Author:  Kate Smith

The road to graduation from any educational institution is lined with essays and written assignments – and the majority of these happen to be thematic essays, as they are supposed to demonstrate that the students understand the topic or material well. A thematic essay is almost as old as writing is, for it focuses on investigating a topic to provide detailed analysis and evidence of why a certain claim can be made.

What is a Thematic Essay?

Although this type of essay is commonly used to analyze some historical facts or a specific literary piece and its significance, a thematic essay can be assigned on a variety of subjects. It is also a traditional classroom essay that may be a part of different exams, so students may be required to craft a thematic essay within limited time, sticking to the topic provided. This is the main reason why they consider thematic essays difficult, but whenever there’s a longer deadline and a choice of topics, the writing process is easier.

However, there’s an important thing that everyone who’s wondering ‘what is a thematic essay?’ needs to know. This type of essay mainly lets the teacher determine your knowledge of the material, and it should demonstrate your comprehension of the topic that you can back up with solid arguments and relevant examples. But proper structure is just as essential to your writing as the scope of the topic. All of the points you want to make, as well as the supporting evidence must be organized in a clear, consecutive way. If your essay lacks focus or is illogical in its organization, your readers will not be able to recognize neither the thoroughness of your research, nor the significance of your critical thinking. They might even have trouble following what evidence you found to help you arrive at a certain conclusion.

How to Find and Explore the Central Theme?

To tackle this type of essay, you often have to narrow down a topic that’s too broad before getting started on your writing. A theme is what an author portrays in a literary work, or the specific point the author is making. Often, it is the most frequently discussed one, or it is a lesson of the greatest overall significance that can be derived from the work and applied to our lives. Thus, to effectively plan out how you are going to write a thematic essay, identify the theme first. Focus on the main point the author is trying to make about a particular subject, the message he is trying to convey, why it is relevant or important at the moment, and the way the reader can benefit from it.

That’s why having a place to start and an outline to follow lays the groundwork for your thematic essay. It is the most important step in the entire essay writing process.

Thematic Essay Outline

By using an outline to shape your essay, you have a format to follow that ensures knowledge of the topic, addressing all the questions of the assignment, and keeping all of the points you want to make well-organized. A thematic essay outline lets you effectively draw parallels between different facts, formulate a coherent and detailed evaluation of the topic, and see whether something in the essay is lacking or needs to be rearranged and revised.

Some essay types may have less rigid layouts and writing requirements, allowing for more creativity and freedom when it comes to formatting. However, this is not the case with instructions on how to write a thematic essay. Just as with other traditional essays, there should be at least five paragraphs in a thematic essay, including an introduction with a thesis statement, three body paragraphs that will support your thesis with relevant arguments and examples, and a logical conclusion to wrap everything up at the end.

Introduction 

Generally, to write a thematic essay you need to have an idea of what your thesis will be, how your body paragraphs will prove it, and how you are going to summarize all of the arguments detailed in the body of the essay in your conclusion. The introduction has to present the main subject of your essay as well as any necessary background information and your thesis statement. At the same time, it should be interesting enough to make the reader want to learn more about the topic. The opening sentence of the introduction is often referred to as a ‘hook’ because it is supposed to grab the reader’s attention. For this purpose, it can evoke anticipation, controversy, irony, or ask a question. The thesis statement is very important because it gives your topic a direction and a specific purpose.

The thesis statement lays the ground for further analysis, for answering a specific question, asserting an opinion or explaining how and why something works (or has worked/failed to produce an expected result). Think of your thesis statement as a compelling and concise headline that gives the reader a good idea of what the rest of the paper is about and what to expect next. It should be engaging, but not confusing to your audience. Have you ever been extremely disappointed by reading an article or watching a movie because it wasn’t what the headline, magazine cover or a movie trailer promised it to be? To make sure your reader doesn’t feel like that, you want your thesis to be integral to the essay and to all of the evidence that you provide in the following body paragraphs. Quite often, a thesis statement needs a few revisions to acquire more focus and clarity as you add the body paragraphs to your thematic essay.

Body paragraphs 

While the 5-paragraph structure gives you a basic layout to work with, it should have three body paragraphs because the thesis must be supported by at least three significant arguments. However, unless the essay has a required length, you can include more supporting facts or examples. There may be more body paragraphs than just three, depending on the details of the assignment or the points you are required to address, but keep in mind that your essay should be concise and devoid of wordiness. Usually, the essay writer should focus on one point or sub-topic per paragraph, but depending on the complexity of the topic, the quantity of paragraphs for validating each claim or explaining your reasoning may vary. 

You can think of body paragraphs as building blocks that include expert quotes or specific examples to add weight to them, as well as to your arguments. This is the ‘meat of your essay’ as long as you make sure that you explain the logic behind each quotation or evidence supporting your claim, and that it is in sync with your thesis statement. Such connections are essential as they tie not only the evidence and arguments, but an entire essay together. 

The conclusion is not simply a reiterated thesis, but a reinforced one. However, it’s important to keep in mind that it should not introduce any new facts not discussed in the body of a thematic essay. The conclusion has to summarize the information presented in the essay, briefly going over the main ideas or claims and explaining how they influence your thesis. Finally, it should wrap up your essay in the most meaningful way, emphasizing the significance and relevance of your topic.

Thematic Essay Examples

Check the examples of thematic essays to use as writing models:

https://www.template.net/business/essay/five-paragraph-essay-template/

Thematic essay topics

To sum up, reading some properly structured thematic essay examples may be the most helpful tip for understanding what your essay should look like, and how to organize your thoughts into a logical sequence. Besides, a list of the most commonly used thematic essay topics is a frequent search query along with ‘thematic essay examples’, as it helps students to get an idea of what to expect at exams.

US History Thematic Essay

In this essay, there will be fewer words that address the reader. The purpose of this writing is to present a balanced analysis of a topic based on facts, explaining a topic in a logical and straightforward manner.

US History thematic essay example topics:

• Major movements in U.S. history
• Major advances in U.S. history
• Significant government reforms
• U.S. Presidents and their major decisions 
• U.S. wars and conflicts

Global Regents Thematic Essay 

These topics are likely to feature broad concepts, but they usually include tasks and suggestions that are more specific. In your essay, you are supposed to address this detailed task and the issues, concepts or questions it prompts you to explain or interpret. Using examples from your course of global history or geography is also required in your thematic essay. 

Global Regents thematic essay example topics:

• Impact of colonizations on world history
• Migrations of people and their effects
• Major characteristics of world civilizations
• Cultures and their contributions
• Economic Systems
• Political Systems
• The turning points in history (revolutions, conflicts, wars)
• Revolutions and clashing of ideas
• Revolutions and new discoveries
• Scientific development
• Technological progress
• Human rights: impactful leaders and their ideas
• Human rights violations

Belief Systems Thematic Essay

A belief system is a way a group or an individual regards religious or philosophical principles. The beliefs that have formed major religions or a mainstay of a civilization may be similar or different, but each belief system has influenced the lives of its followers as well as the history, culture, politics, or economy of a specific nation or country.

Belief Systems thematic essay example topics:

• How belief systems influenced ancient civilizations?
• How did a belief form a religion?
• Cultures as systems of interconnections between humans
• The role of religion in Ancient Roman society
• The three major monotheistic religions: Judaism, Christianity and Islam
• Judaism: the first monotheistic religion
• The personal belief system and life values
• Compare Christianity to another religion. Are there more similarities or differences?
• Compare two struggles for religious freedom in different countries and time periods
• What makes all struggles for religious freedom similar?

The bottom line

While students often have difficulties writing thematic essays, these are not the most complicated tasks to complete within a certain course or subject. They just require making a detailed examination of the topic using relevant facts, examples or other evidence that you should be able to find in order to make your arguments more solid, and to show that you have gained a thorough understanding of the topic. However, you mustn’t just summarize the well-known facts or what you have learned from a course or book. In a thematic essay, you are supposed to identify and explain or compare issues, causes, patterns, outcomes, and connections between facts or events as well as their consequences or influences.

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General-purpose thematic analysis: a useful qualitative method for anaesthesia research

1 Centre for Medical and Health Sciences Education, School of Medicine, University of Auckland, Auckland, New Zealand

2 Department of Anaesthesia, Auckland City Hospital, Auckland, New Zealand

Learning objectives

By reading this article, you should be able to:

• • Explain when to use thematic analysis.
• • Describe the steps in thematic analysis of interview data.
• • Critique the quality of a study that uses the method of thematic analysis.
• • Thematic analysis is a popular method for systematically analysing qualitative data, such as interview and focus group transcripts.
• • It is one of a cluster of methods that focus on identifying patterns of meaning, or themes, across a data set.
• • It is relevant to many questions in perioperative medicine and a good starting point for those new to qualitative research.
• • Systematic approaches to thematically analysing data exist, with key components to demonstrate rigour, accountability, confirmability and reliability.
• • In one study, a useful six-step approach to analysing data is offered.

Anaesthesia research commonly uses quantitative methods, such as surveys, RCTs or observational studies. Such methods are often concerned with answering what questions and how many questions. Qualitative research is more concerned with why questions that enable us to understand social complexities. ‘Qualitative studies in the anaesthetic setting’, write Shelton and colleagues, ‘have been used to define excellence in anaesthesia, explore the reasons behind drug errors, investigate the acquisition of expertise and examine incentives for hand hygiene in the operating theatre’. 1

General-purpose thematic analysis (termed thematic analysis hereafter) is a qualitative research method commonly used with interview and focus group data to understand people's experiences, ideas and perceptions about a given topic. Thematic analysis is a good starting point for those new to qualitative research and is relevant to many questions in the perioperative context. It can be used to understand the experiences of healthcare professionals and patients and their families. Box 1 gives examples of questions amenable to thematic analysis in anaesthesia research.

Examples of questions amenable to thematic analysis.

• (i) How do operating theatre staff feel about speaking up with their concerns?
• (ii) What are trainee's conceptions of the balance between service and learning?
• (iii) What are patients' experiences of preoperative neurocognitive screening?

Alt-text: Box 1

Thematic analysis involves a process of assigning data to a number of codes, grouping codes into themes and then identifying patterns and interconnections between these themes. 2 Thematic analysis allows for a nuanced understanding of what people say and do within their particular social contexts. Of note, thematic analysis can be used with interviews and focus groups and other sources of data, such as documents or images.

Thematic analysis is not the same as content analysis. Content analysis involves counting the frequency with which words or phrases appear in data. Content analysis is a method used to code and categorise textual information systematically to determine trends, frequency and patterns of words used. 3 Conversely, thematic analysis focuses on the relative importance of ideas and how ideas connect and govern practices. Thematic analysis does not rely on frequency counts to indicate the importance of coded data. Content analysis can be coupled with thematic analysis, where both themes and frequencies of particular statements or words are reported.

Thematic analysis is a research method, not a methodology. A methodology is a method with a philosophical underpinning. If researchers report only on what they did, this is the method. If, in addition, they report on the philosophy that governed what they did, this is methodology. Common methodologies in qualitative research include phenomenology, grounded theory, hermeneutics, narrative enquiry and ethnography. 4 Each of these methodologies has associated methods for data analysis. Thematic analysis can be combined with many different qualitative methodologies.

There are also different types of thematic analysis, such as inductive (including general purpose), applied, deductive or semantic thematic analysis. Inductive analysis involves approaching the data with an open mind, inductively looking for patterns and themes and interpreting these for meaning. 2 , 4 Of note, researchers can never have a truly open mind on their topic of interest, so the process will be influenced by their particular perspectives, which need to be declared. In applied and deductive thematic analysis, the researcher will have a pre-existing framework (which may be informed by theory or philosophy) against which they will attempt to categorise the data. 4 , 5 , 6 For semantic thematic analysis, the data are coded on explicit content, and tend to be descriptive rather than interpretative. 6

In this review, we outline what thematic analysis entails and when to use it. We also list some markers to look for to appraise the quality of a published study.

Designing the data collection

Before embarking on qualitative research, as with quantitative research, it is important to seek ethical review of the proposed study. Ethical considerations include such issues as consent, data security and confidentiality, permission to use quotes, potential for identifying individuals or institutions, risk of psychological harm to participants with studies on sensitive issues (e.g. suicide or sexual harassment), power relationships between interviewer and interviewee or intrusion on other activities (such as teaching time or work commitments). 7

Qualitative research often involves asking people questions during interviews or focus groups. Merriam and Tisdell stated that, ‘The most common form of interview is the person-to-person encounter in which one person elicits information from the other’. 8 Information is elicited through careful and purposeful questioning and listening. 9 Research interviews in anaesthesia are generally purposeful conversations with a structure that allows the researcher to gather information about a participant's ideas, perceptions and experiences concerning a given topic.

A structured interview is when the researcher has already decided on a set of questions to ask. 9 If the researcher will ask a set of questions, but has flexibility to follow up responses with further questions, this is called a semi-structured interview. Semi-structured interviews are commonly used in research involving thematic analysis. The researcher can also use other forms of questioning, such as single-question interview. Semi-structured interviews are commonly used in anaesthesia, such as the studies from our own research group. 10 , 11 , 12

Interviews are usually recorded in audio form and then transcribed. For each interview or focus group, a single transcript is created. The transcripts become the written form of data and the collection of transcripts from the research participants becomes the data set.

Designing productive interview questions

The design of interview questions significantly shapes a participant's response. Interview questions should be designed using ‘sensitising concepts’ to encourage participants to share information that will increase a researcher's understanding of the participants' experiences, views, beliefs and behaviours. 13 ‘Sensitising concepts’ describe words in questions that bring the participants' attention to a concept of research interest. Examples of sensitising concepts include speaking up, teamwork and theoretical concepts (such as Kolb's experiential learning cycle or Foucauldian power theory in relation to trainee learning and operating theatre culture). 14 , 15 Specifically, the questions should be framed in such a way as to encourage participants to make sense of their own experience and in their own words. The researcher should try to minimise the influences of their own biases when they design questions. Using open-ended questions will increase the richness of data. Box 2 gives examples of question design.

How to design an interview question.

Alt-text: Box 2

Bias, positionality and reflexivity

Bias is an inclination or prejudice for or against someone or something, whereas positionality is a person's position in society or their stance towards someone or something. For example, Tanisha once had an inexperienced anaesthetist accidentally rupture one of her veins whilst they were siting an i.v. cannula in an emergency situation. Now, Tanisha has a bias against inexperienced anaesthetists. Tanisha's positionality —a medical anthropologist with no anaesthesia training, but working with many anaesthesia colleagues, including her director—may also inform that bias or the way that Tanisha interacts with anaesthetists. Reflexivity is a process whereby people/researchers proactively reflect on their biases and positionality. Biases shape positionality (i.e. the stance of the researcher in relation to the social, historical and political contexts of the study). In practical research terms, biases and positionality inform the way researchers design and undertake research, and the way they interpret data. It is important in qualitative research to both identify biases and positionality, and to take steps to minimise the impact of these on the research.

Some ways to minimise the influence of bias and positionality on findings include:

(i) Raise awareness amongst the research team of bias and positionality.

(ii) Design research/interview questions that minimise potential for these to distort which data are collected or how they are collected.

(iii) Researchers ask reflexive questions during data analysis, such as, ‘Is my bias about xxx informing my view of these data?’

(iv) Two or more researchers are involved in the analysis process.

(v) Data analysis member check (e.g. checking back with participants if the interpretation of their data is consistent with their experience and with what they said).

Before embarking on the study, researchers should consider their own experiences, knowledge and views; how this influences their own position in relation to the study question; and how this position could potentially introduce bias in how they collect and analyse the data. Taking time to reflect on the impact of the researchers' position is an important step towards being reflective and transparent throughout the research process. When writing up the study, researchers should include statements on bias and positionality. In quantitative research, we aim to eliminate bias. In qualitative research, we acknowledge that bias is inevitable (and sometimes even unconscious), and we take steps to make it explicit and to minimise its effect on study design and data interpretation.

Sampling and saturation

Qualitative research typically uses systematic, non-probability sampling. Unlike quantitative research, the goal of sampling is not to randomly select a representative sample from a population. Instead, researchers identify and select individuals or groups relevant to the research question. Commonly used sampling techniques in anaesthesia qualitative research are homogeneous (group) sampling and maximum variation sampling. In the former, researchers may be concerned with the experiences of participants from a distinct group or who share a certain characteristic (e.g. female anaesthesia trainees), so they recruit selectively from within the group with this shared characteristic to gain a rich, in-depth understanding of their experiences. Conversely, the aim with maximum variation sampling is to recruit participants with diverse characteristics to obtain a broad understanding of the question being studied (e.g. members of different professional groups within operating theatre teams, who have diverse ages, gender and ethnicities).

As with quantitative research, the purpose of sampling is to recruit sufficient numbers of participants to enable identification of patterns or richness in what they say or do to understand or explain the phenomenon of interest, and where collecting more data is unlikely to change this understanding.

In qualitative research, data collection and analysis often occur concurrently. This is because data collection is an iterative process both in recruitment and in questioning. The researchers may identify that more data are needed from a particular demographic group or on a particular theme to reach data saturation, so the next participants may be selected from a particular demographic, or be asked slightly different questions or probes to draw out that theme. Sample size is considered adequate when little or no new information emerges from interviews or focus groups; this is generally termed ‘data saturation’, although some qualitative researchers use the term ‘data sufficiency’. This could also be explained in terms of data reliability (i.e. the researcher is satisfied that collecting more data will not substantially change the results). Data saturation typically occurs with between 12 and 17 participants in a relatively homogeneous sampling, but larger numbers may be required, where the interviewees are from distinct groups or cultures. 16 , 17

Data management

For data sets that involve 10 or more transcripts or lengthy interviews (e.g. 90 min or more), researchers often use software to help them collate and manage the data. The most commonly used qualitative software packages are QSR NVivo, Atlas and Dedoose. 18 , 19 , 20 Many researchers use Microsoft Excel instead, or for small data sets the analysis can be done by hand, with pen, paper and scissors (i.e. researchers cut up printed transcripts and reorder the information according to code and theme). 21 NVivo and Atlas are simply repositories, in which you can input the transcripts and, using your coding scheme, sort the text into codes. They facilitate the task of analysis, rather than doing the analysis for you. Some advantages over coding by hand are that text can be allocated to more than one code, and you can easily identify the source of the segment of text you have coded.

Data analysis

Qualitative data analysis is ‘the classification and interpretation of linguistic (or visual) material to make statements about implicit and explicit dimensions and structures of meaning-making in the material and what is represented in it’. 22

Several social scientists have described this analytical process in depth. 2 , 6 , 22 , 23 , 24 , 25 For inductive studies, we recommend researchers follow Braun and Clarke's practical six-phase approach to thematic analysis. 26 The phases are (i) familiarising the researcher with the data, (ii) generating initial codes, (iii) searching for themes, (iv) reviewing themes, (v) defining and naming themes and (vi) producing the report. These six phases are described next.

Phase 1: familiarising the researcher with the data

In this step, the researchers read the transcripts to become familiar with them and take notes on potential recurring ideas or potential themes. They share and discuss their ideas and, in conjunction with any sensitising concepts, they start thinking about possible codes or themes.

Phase 2: generating initial codes

The first step in Phase 2 is ‘assigning some sort of short-hand designation to various aspects of your data so that you can easily retrieve specific pieces of the data’. 2 The designation might be a word or a short phrase that summarises or captures the essence of a particular piece of text. Coding makes it easier to summarise and compare, which is important because qualitative research is primarily about synthesis and comparison of data. 2 , 25 As the researcher reads through the data, they assign codes. If they are coding a transcript, they might highlight some words, for example, and attach to them a single word that summarises their meaning.

Researchers undertaking thematic analysis should iteratively develop a ‘coding scheme’, which is essentially a list of the codes they create as they read the data, and definitions for each code. 25 , 26 Code definitions are important, as they help the researcher make decisions on whether to assign this code or another one to a segment of data. In Table 1 , we have provided an example of text data in Column 1. TJ analysed these data. To do so, she asked, ‘What are these data about? How does it answer the research question? What is the essence of this statement?’ She underlined keywords and created codes and definitions (Columns 2 and 3). Then, TJ searched the remaining data to see if any more data met each code definition, and if so, coded that (see Table 1 ). As demonstrated in Table 1 , data can be coded to multiple codes.

Table 1

How to code qualitative data: an example

In thematic analysis of interview data, we recommend that code definitions begin with something objective, such as ‘participant describes’. This keeps the researcher's focus on what participants said rather than what the researcher thought or said.

There is no set rule for how many codes to create. 25 However, in our experience, effective manageable coding schemes tend to have between 15 and 50 codes. The coding scheme is iterative. This means that the coding scheme is developed over time, with new codes being created as more data are coded. For example, after a close reading of the first transcript, the researcher might create, say, 10 codes that convey the key points. Then, the researcher reads and codes the next transcript and may, for instance, create additional four codes. As additional transcripts are read and coded, more codes may be created. Not all codes are relevant to all transcripts. The researcher will notice patterns as they code more transcripts. Some codes may be too broad and will need to be refined into two or three smaller codes (and vice versa ). Once the coding scheme is deemed complete and all transcripts have been coded, the researcher should go back to the beginning and recode the first few transcripts to ensure coding rigour.

The second step in Phase 2, once the coding is complete, is to collate all the data relevant to each of these codes.

Phase 3: searching for themes

In this phase, the researchers look across the codes to identify connections between them, with the intention of collating the codes into possible themes. Once these possible themes have been identified, all the data relevant to each possible theme are pulled together under that theme.

Phase 4: reviewing the themes

After the initial collation of the data into themes, the researchers undertake a rigorous process of checking the integrity of these themes, through reading and re-reading their data. This process includes checking to see if the themes ‘fit’ in relation to the coded excerpts (i.e. Do all the data collected under that theme fit within that theme?). Next is checking if the themes fit in relation to the whole data set (i.e. Do the themes adequately reflect the data?) This step may result in the search for additional themes. As a final step in this phase, the researchers create a thematic ‘map’ of the analysis.

When viewed together, the themes should answer the research question and should summarise participant experiences, views or behaviours.

Phase 5: naming the themes

Once researchers have checked the themes and included any additional emerging themes they name the final set of themes identified. Each theme and any subthemes should be listed in turn.

Phase 6: producing the report

The report should summarise the themes and illustrate them by choosing vivid or persuasive extracts from the data. For data arising from interviews, extracts will be quotes from participants. In some studies, researchers also report strong associations between themes, or divide a theme into sub-themes.

Tight word limits on many academic journals can make it difficult to include multiple quotes in the text. 27 One way around a word limit is to provide quotes in a table or a supplementary file, although quotes within the text tend to make for more interesting and compelling reading.

Who should analyse the data?

Ideally, each researcher in the team should be involved in the data analysis. Contrasting researcher viewpoints on the same study subject enhance data quality and validity, and minimise research bias. Independent analysis is time and resource intensive. In clinical research, close independent analysis by each member of the research team may be impractical, and one or two members may undertake the analysis while the rest of the research team read sections of data (e.g. reading two or three transcripts rather than closely analysing the whole data set), thus contributing to Phase 1 and Phase 2 of Braun and Clarke's method. 2

The research team should regularly meet to discuss the analytical process, as described earlier, to workshop and reach agreement on the coding and emergent themes (Phase 4 and Phase 5). The research team members compare their perspectives on the data, analyse divergences and coincidences and reach agreement on codes and emerging themes. Contrasting researcher viewpoints on the same study subject enhance data quality and validity, and minimise research bias.

Judging the quality and rigour of published studies involving thematic analysis

There are a number of indicators of quality when reading and appraising studies. 28 , 29 , 30 , 31 In essence, the authors should clearly state their method of analysis (e.g. thematic analysis) and should reference the literature relevant to their qualitative method, for example Braun and Clarke. 2 This is to indicate that they are following established steps in thematic analysis. The authors should include in the methods a description of the research team, their biases and experience and the efforts made to ensure analytical rigour. Verbatim quotes should be included in the findings to provide evidence to support the themes.

A number of guides have been published to assist readers, researchers and reviewers to evaluate the quality of a qualitative study. 30 , 31 The Joanna Briggs Institute guide to critical appraisal of qualitative studies is a good start. 30 This guide includes a set of 10 criteria, which can be used to rate the study. The criteria are summarised in Box 3 . Within these criteria lie rigorous methodological approaches to how data are collected, analysed and interpreted.

Ten quality appraisal criteria for qualitative literature.31

• (i) Alignment between the stated philosophical perspective and the research methodology
• (ii) Alignment between the research methodology and the research question or objectives
• (iii) Alignment between the research methodology and the methods used to collect data
• (iv) Alignment between the research methodology and the representation and analysis of data
• (v) Alignment between the research methodology and the interpretation of results
• (vi) A statement locating the researcher culturally or theoretically (positionality and bias)
• (vii) The influence of the researcher on the research, and vice versa
• (viii) Adequate representation of participants and their voices
• (ix) Ethical research conduct and evidence of ethical approval by an appropriate body
• (x) Conclusions flow from the analysis, or interpretation, of the data

Alt-text: Box 3

Another approach to quality appraisal comes from Lincoln and Guba, who have published widely on the topic of judging qualitative quality. 28 They look for quality in terms of credibility, transferability, dependability, confirmability and authenticity. There are many qualitative checklists readily accessible online, such as the Standards for Reporting Qualitative Research checklist or the Consolidated Criteria for Reporting Qualitative Research checklist, which researchers can include in their work to demonstrate quality in these areas.

Conclusions

As with quantitative research, qualitative research has requirements for rigour and trustworthiness. Thematic analysis is an accessible qualitative method that can offer researchers insight into the shared experiences, views and behaviours of research participants.

Declaration of interests

The authors declare that they have no conflicts of interest.

The associated MCQs (to support CME/CPD activity) will be accessible at www.bjaed.org/cme/home by subscribers to BJA Education .

Biographies

Tanisha Jowsey PhD BA (Hons) MA PhD is a senior lecturer in the Centre for Medical and Health Sciences Education, School of Medicine, University of Auckland. She has a background in medical anthropology and has expertise as a qualitative researcher.

Carolyn Deng MPH FANZCA is a specialist anaesthetist at Auckland City Hospital. She has a Master of Public Health degree. She is embarking on qualitative research in perioperative medicine and hopes to use it as a tool to complement quantitative research findings in the future.

Jennifer Weller MD MClinEd FANZCA FRCA is head of the Centre for Medical and Health Sciences Education at the University of Auckland. Professor Weller is a specialist anaesthetist at Auckland City Hospital and often uses qualitative methods in her research in clinical education, teamwork and patients' safety.

Matrix codes: 1A01, 2A01, 3A01

The Guide to Thematic Analysis

• What is Thematic Analysis?
• Advantages of Thematic Analysis
• Disadvantages of Thematic Analysis
• Thematic Analysis Examples
• How to Do Thematic Analysis
• Thematic Coding
• Collaborative Thematic Analysis
• Thematic Analysis Software
• Thematic Analysis in Mixed Methods Approach
• Abductive Thematic Analysis
• Deductive Thematic Analysis
• Inductive Thematic Analysis
• Reflexive Thematic Analysis
• Thematic Analysis in Observations
• Thematic Analysis in Surveys
• Introduction

Interviews in qualitative research

Can you use thematic analysis for interviews, how to do thematic analysis of interviews.

• Thematic Analysis for Focus Groups
• Thematic Analysis for Case Studies
• Thematic Analysis of Secondary Data
• Thematic Analysis Literature Review
• Thematic Analysis vs. Phenomenology
• Thematic vs. Content Analysis
• Thematic Analysis vs. Grounded Theory
• Thematic Analysis vs. Narrative Analysis
• Thematic Analysis vs. Discourse Analysis
• Thematic Analysis vs. Framework Analysis
• Thematic Analysis in Social Work
• Thematic Analysis in Psychology
• Thematic Analysis in Educational Research
• Thematic Analysis in UX Research
• How to Present Thematic Analysis Results
• Increasing Rigor in Thematic Analysis
• Peer Review in Thematic Analysis

Thematic Analysis for Interviews

Thematic analysis is a widely used method in qualitative research for identifying, analyzing, and reporting patterns (themes) within data . It organizes and describes the data set in detail and interprets various aspects of the research topic. When applied to interview data, thematic analysis allows researchers to sift through large volumes of text and distill meaningful patterns relevant to their research questions.

This introductory guide provides a straightforward approach to conducting a thematic analysis of interview data . It outlines the key steps involved in the process, from data preparation to theme identification and analysis .

Interviews are a fundamental data collection method in qualitative research , offering deep insights into participants' perspectives, experiences, and motivations. They are particularly valuable for exploring complex issues, understanding individual experiences, and gathering detailed information that would be difficult to obtain through other methods.

In qualitative research, interviews can vary widely in structure, from highly structured interviews where specific questions are asked in a set order, to semi-structured interviews that allow for more flexibility and follow-up questions based on the respondent's answers. Unstructured interviews , on the other hand, are more like guided conversations and are the least restrictive.

Regardless of the format, the primary goal of using interviews in qualitative research is to gain a nuanced understanding of the topic at hand. Researchers can probe deeper into participants' responses, clarify ambiguities, and explore new avenues that emerge during the conversation. This depth and detail are what set interviews apart from other data collection methods like surveys or questionnaires, which may not allow for such in-depth exploration.

To ensure the effectiveness of interviews in qualitative research, researchers must be skilled in question formulation, active listening, and respondent engagement. They must also be adept at creating a comfortable environment for participants, encouraging them to share openly and honestly.

After conducting the interviews, the qualitative researcher faces the critical task of analyzing the collected data . Transcribing the interviews is typically the first step, transforming audio recordings into text for detailed analysis. The researcher then reads through these transcripts meticulously to identify themes and other data segments of interest, laying the groundwork for a thorough thematic analysis. Qualitative researchers may pursue other approaches like narrative analysis and discourse analysis depending on their research question and objectives, while converting transcripts into quantitative data may be useful for a content analysis .

Thematic analysis can be an effective method for analyzing interview data in qualitative research due to its ability to uncover, analyze, and report themes within complex datasets. When researchers use thematic analysis to scrutinize interview data, they engage deeply with the content, enabling a nuanced understanding of participants' experiences and perspectives.

This method is particularly adept at handling the rich, qualitative depth that interviews provide, allowing researchers to extract meaningful patterns and insights from the narratives shared by participants. Thematic analysis respects the detail and individuality of each respondent's contribution, translating intricate personal stories into broader insights that are relevant to the research question .

In the context of interviews, thematic analysis is beneficial because it is adaptable to a range of theoretical frameworks and research objectives, making it a versatile choice for many studies. It supports researchers in identifying not just the explicit content of what was said, but also the underlying ideas and themes that emerge across different interviews. This approach ensures a comprehensive understanding of the data, taking into account both the diversity and the commonalities of participants' experiences.

Furthermore, thematic analysis is a method that suits various levels of research expertise. It does not demand advanced methodological training, making it accessible while still providing robust and systematic guidance for analyzing complex data sets. This accessibility, combined with its analytical depth, makes thematic analysis an excellent choice for researchers aiming to derive meaningful themes from their interview data, thus ensuring a thorough and insightful analysis.

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Thematic analysis is a methodical process that allows researchers to identify, analyze, and report patterns within their interview data , offering a deep and nuanced understanding of the data's content. This approach requires a careful and detailed engagement with the textual data gathered from interviews, organized through a series of structured steps.

This section will guide you through the critical stages of this research process: starting from immersing yourself in the data to generate a profound understanding, moving on to coding the data to unearth initial insights, identifying overarching themes, and finally, reviewing themes to accurately reflect the data's depth. Each step is pivotal in transforming raw interview content into meaningful, actionable findings.

Familiarizing yourself with the data

The first crucial step in conducting thematic analysis on interview data is to familiarize yourself thoroughly with the material. This involves engaging deeply with the content of your interviews to ensure a comprehensive understanding of the data you will be analyzing.

Begin by listening to the audio recordings of your interviews several times, if available, to capture not just the words but also the nuances of how things are said, including tone, emphasis, and pauses. This can provide additional layers of meaning that are not always evident in a written transcript . Next, read and reread the transcripts meticulously. While reading, take detailed notes on your initial impressions, including any interesting or recurring themes that jump out at you.

During this stage, it's essential to approach your data with an open mind, setting aside any preconceived notions or theoretical assumptions. This openness ensures that you remain receptive to the data's inherent messages rather than imposing your interpretations. It also prepares you for the subsequent stages of analysis by helping you develop a nuanced understanding of the dataset as a whole.

For interview data, specifically, paying attention to the context in which statements were made is crucial. Reflect on the interview setting, the relationship dynamics between the interviewer and participant, and any external factors that might have influenced the responses. This contextual understanding can be invaluable when you later attempt to code the data and interpret its meaning.

Generating initial codes

Generating initial codes is a systematic and meticulous step in thematic analysis where you start segmenting and labeling your interview data to identify significant features and patterns. This phase is critical for organizing your data into meaningful groups that will later facilitate the identification of broader themes.

When coding interview data, you can approach each transcript line-by-line or paragraph-by-paragraph, assigning concise codes that capture the essence of each segment. These codes should reflect the content and context of what is being conveyed, staying as close to the data as possible. It is beneficial to use a mix of descriptive and in vivo codes—the former describing the content and the latter using key phrases spoken by the participants themselves.

As you progress through your interviews, compare and contrast your codes across different transcripts. This comparison helps to ensure consistency in your coding approach and allows you to start identifying patterns across the entire data set. Remember, the goal at this stage is not to force the data into pre-existing categories but to remain open to what the data reveals.

Searching for themes

After generating your initial codes, the next step in thematic analysis is to search for overarching themes that convey broader patterns in your interview data. This involves reviewing your codes to identify significant clusters of related or interconnected codes that suggest a higher level of conceptualization.

Begin by organizing your codes into potential theme categories, considering how individual codes combine to form a more comprehensive narrative. This categorization should not be purely based on the frequency of certain codes but should also take into account their relevance to your research questions and the overall data set. During this process, it's essential to remain flexible and open-minded, as themes may evolve or merge together.

For interview data, it's particularly important to consider the context in which responses were given. Reflect on how the themes relate to the broader socio-cultural context, the specific circumstances of the interview, and the interactions between interviewer and participant. These considerations can provide deeper insights into the significance and nuances of your emerging themes.

As you delineate these themes, create visual representations , such as thematic maps or charts, to help you conceptualize the relationships between codes and themes. These visualizations can aid in identifying the core essence of each theme and its connection to the overall story your data is telling.

Reviewing and defining themes

The phase of reviewing and defining themes is crucial for refining the preliminary themes you've identified and ensuring they accurately represent your interview data. This step involves a thorough examination and possible reconfiguration of your themes to ensure they are coherent, consistent, and distinct.

Begin by reviewing each theme in relation to the coded extracts to verify that they form a coherent pattern. This may require you to split broad themes into more nuanced sub-themes, combine closely related themes, or discard themes that lack sufficient evidence across the dataset. For interview data, it is particularly important to ensure that the themes reflect the participants' perspectives and experiences rather than the researcher's interpretations.

Next, define and name each theme. Provide a clear, concise, and descriptive name for each theme, capturing its essence. Then, develop a detailed analysis for each theme, explaining what it represents and how it contributes to the overall understanding of the data. Include illustrative quotations from your interviews to demonstrate how each theme is grounded in the participants' accounts.

Finally, ensure that your themes 'tell a story' about your data, addressing your research questions and offering insightful interpretations. The themes should provide a rich, detailed, and complex picture of the data, highlighting the depth and diversity of the participants' experiences and perspectives.

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How to Write a Thematic Analysis Essay Correctly: Expert Advice

So, a thematic analysis essay. This kind of essay might be not the most complicated one. However, it doesn’t mean that you have to be confident and peaceful. You aren’t a professional writer and being worried is a normal human condition. And this is normal. People are different.

There are people that don’t like writing, you know. There are people that like writing but don’t have much experience in doing that. As well, some people want to learn how to write. That’s why, we have selected the most useful tips, which will be extremely helpful if you decide to write your essay on your own. So, just check how to do it, how to write a thematic analysis essay, and do it!

What Is a Thematic Analysis Essay: Clear Definition

But first of all, let us check exactly what kind of paper you should write. So, the definition you can guess already from the title: a thematic essay is an essay about some themes or concepts. When you are working on this kind of essay, you should consider the following moments:

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• All your attention should be focused on ideas and themes that you should analyze.
• Provide not only your analyses but the reference to external sources, because the reader might want to check them.
• Every aspect of the task should be taken into consideration, if you are writing an analysis, just consider it.
• Provide enough details, but be specific; deviations aren’t good at this kind of paper, but being too short is not helpful either.

Thematic Analysis Essay Structure Follows the Standard

The thematic analysis essay structure is the same as for any other kind of essay. Make sure you follow the standard and don’t invent anything new. So, the general structure of a thematic analysis essay is the following:

• An introduction, where you introduce the theme and explain its importance.
• The main part, where you provide detailed information and all the opinions that you consider relevant.
• A conclusion, where you actually make a conclusion for your analysis, for all your work.

How to Start a Thematic Analysis Essay: Strong Introduction

Here, introduce your theme or concept. Make it as strong as possible — the impression should be unforgettable! Only then, your reader might consider reading it till the end just out of interest and give you a good grade. So, if you are thinking about how to start a thematic analysis essay efficiently, start it with a question or a personal story. Then, the introduction will rock! The thematic analysis essay introduction is one of the most important parts of your paper.

The Main Part

In the main part, analyze the given themes. Pay attention to all aspects of your theme or concept. Provide not only your opinions but the ideas and opinions of experts or even just some other people who have been working with the same topic.

How to End a Thematic Analysis Essay Impressively

Now, it is time to check how to end a thematic analysis essay. The rules are like everywhere, like any other conclusion. You should make the final statement, the conclusions based on your analysis. Well, your conclusion should be impressive, as well. You know, a weak conclusion of a thematic analysis essay can spoil the impression from the entire work, and that is definitely not what you are looking for.

Thematic Analysis Essay Outline Processing

The thematic analysis essay outline doesn’t differ much from a standard essay outline. The same parts, the same structure. Like in the case with any other essay, you should be precise, logical, and try to make all parts of your essay as strong and impressive as you can.

However, there are some writing tips that you shouldn’t ignore. For this kind of essay, the preparation process is essential. You cannot analyze a theme if you don’t know what experts think about it. How can you compare ideas and views, if you don’t know them?

So prepare yourself to the writing process very carefully. Select the most reliable sources. If they are recommended for schools and universities, it is perfect. But even if not, just make sure they provide reliable information. In most cases, they should be published in reputable journals or websites.

When you are writing a theme analysis essay, it is important to be very attentive to the smallest detail. That’s why it is an analysis essay, you know. Other than that, the essay is just like any different kind of paper. You give your opinions, discuss them, compare them with the opinions of other people and so on.