Practical Guide to Grounded Theory Research

What is grounded theory?

Grounded theory is a qualitative method that enables you to study a particular phenomenon or process and discover new theories that are based on the collection and analysis of real world data.

Unlike traditional hypothesis-deductive approaches of research, where you come up with a hypothesis and then try to prove/disprove it, grounded theory is an inductive approach where new theories are derived from the data.

The process of data collection, data analysis, and theory development happen in an iterative process. Iterative data collection and analysis occurs until you reach theoretical saturation, the point at which additional data adds no additional insight into your new theory.

When should you use grounded theory?

You should consider using grounded theory when there is no existing theory that offers an explanation for a phenomenon that you are studying. It can also be used if there is an existing theory, but it is potentially incomplete as the data used to derive that theory wasn’t collected from the group of participants that you plan on researching.

Benefits of using grounded theory

Findings accurately represent real world settings

The theories you develop using grounded theory are derived directly from real world participants in real world settings using methods like in depth interviews and observation, so your findings will more accurately represent the real world. This is in contrast to other research approaches that occur in less natural settings like research labs or focus group tables.

Findings are tightly connected to the data

Because grounded theory primarily relies on collected data to determine the final outcome, the findings are tightly connected to that data. This is in contrast to other research approaches that rely more heavily on external research frameworks or theories that are further removed from the data.

Great for new discoveries

Grounded theory is a strong, inductive research method for discovering new theories. You don’t go in with any preconceived hypothesis about the outcome, and are not concerned with validation or description. Instead, you allow the data you collect to guide your analysis and theory creation, leading to novel discoveries.

Offers strategies for analysis

The process of grounded theory describes specific strategies for analysis that can be incredibly helpful. While grounded theory is a very open ended methodology, the analysis strategies enable you to stay structured and analytical in your discovery process.

Data collection and analysis are streamlined

Data collection and analysis are tightly interwoven. As you collect data, you analyze it, and as you learn from analysis, you continue to collect more data. This helps ensure that the data you collect is sufficient enough to explain the findings that arise from analysis.

Buffers against confirmation bias

Because data collection and analysis are tightly interwoven, you are truly following what is emerging from the data itself. This provides a great buffer against confirming preconceived beliefs about your topic.

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Limitations of grounded theory

Difficulty recruiting

Grounded theory relies on an iterative recruiting process called theoretical sampling where you continuously recruit and conduct new rounds of interviews with new participants and previous participants while you analyze data. The recruiting criteria also evolves and changes based on what you learn. Because the recruiting is not predefined, it can be challenging to continuously find the right participants for your study.

Time consuming to collect data

There is no way to know ahead of time how much data you will need to collect, so you need to be flexible with your time. With grounded theory, you continuously collect and analyze data until you reach theoretical saturation, which is the point at which new data does not contribute new insight to your evolving theory. This means that you are likely to conduct many rounds of data collection before your theory is complete.

Challenges in analysis

Data analysis occurs on a rolling basis and involves making constant comparisons between different excerpts of data. It can be challenging to keep track of your comparisons and findings as you go. It can be helpful to use a qualitative data analysis software like Delve to help you stay organized during your analysis.

History of grounded theory

Grounded Theory (GT) was first developed by Sociologist Barney Glaser and Anselm Strauss. During this period, they criticized the predominant approach to qualitative research, which they found to be very limited. Qualitative studies at this time were following traditional methods which basically involved coming up with a hypothesis and conducting research to validate it.

Glaser and Strauss pioneered a new methodology for discovering theory by taking an inductive approach to qualitative research. They formally presented their newly developed research method by publishing Discovery of Grounded Theory: Strategies for qualitative research (1967).

Since then, various evolutions of grounded to theory emerged, including Basics of Qualitative Research: Grounded Theory Procedures and Techniques (1990) by Strauss and Corbin. This shifted from the concept of the natural emergence of theory by designing an analytical coding framework for generating theories from data systematically.

In 1990s, Kathy Charmaz published a new approach called constructivist grounded theory, and argued that neither data nor theories are discovered but are constructed through the researchers' past and present experiences.

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How do you do grounded theory research?

This is an overview of how you can approach the process of grounded theory. Know that this isn’t the only way to approach grounded theory, but just a collection of tips and processes derived from various grounded theory resources that you can use to inspire your own grounded theory study.

Note: We adjusted some terminology and language from the original grounded theory papers in order to make this guide as practical as possible for anybody aiming to use grounded theory with qualitative data analysis software.
If you wish to gain more depth in your grounded theory knowledge, we highly encourage you to read the original papers from Glaser, Strauss, Corbin and Charmaz, which we link to in the references at the bottom of this page.

Steps for grounded theory

Determine initial research questions
Recruit and collect data (theoretical sampling)
Break transcripts into excerpts (open coding)
Group excerpts into codes (open coding)
Group codes into categories (axial coding)
Analyze more excerpts and compare with codes
Repeat steps 2-6 until you reach theoretical saturation
Define the central idea (selective coding)
Write your grounded theory

Note: Approach your research iteratively

Grounded theory is not a linear process where you collect data, analyze it, and then you’re done. It is an iterative research methodology that involves cycling through the steps iteratively. Part of what made Grounded Theory revolutionary was that it mixed data collection with analysis. It emphasized going back to the field even after conducting some analysis. You will recruit some participants, gather data and analyse it, and go back into the field again with a different recruiting strategy and focus of inquiry. Then you’ll incorporate those findings into further rounds of analysis. Grounded theory is deliberately cyclical in nature.

1. Determine initial research questions

Start off with your initial research questions. Have an idea for what phenomenon you are trying to explain. These initial questions will help guide your first steps in recruiting and data analysis but know that the questions may evolve as you observe and learn more from the data you collect.

2. Recruit and collect data using theoretical sampling

With grounded theory, recruiting participants is iterative. Instead of pre-determining a specified recruiting criteria ahead of time, you will practice what is called theoretical sampling. With theoretical sampling, you start with recruiting a small group of participants loosely based on your initial research questions.

Once you have some data, such as recordings from in depth interviews, prepare that data for analysis by turning them into transcripts.

After you do some initial analysis of that data, which we detail in the following steps, you use what you learned from that analysis to determine who to recruit next.

3. Break up transcripts into excerpts using open coding

After you have collected some data, such as transcriptions from interviews*, you can begin open coding. Open coding is when you take your transcripts, and break it into individual excerpts. Then, take the excerpts and continuously compare and contrast them with other excerpts This act of comparison is part of a core grounded theory method called constant comparative method, which you will use throughout various phases of your analysis.

Notice similarities and differences between excerpts.

Compare different excerpts from the same person
Compare similar excerpts that occur between different people
Compare different peoples’ experiences within similar excerpts
Compare excerpts as they differ from one day to the next

For example, in a study about the COVID-19 lockdown in New York City, you may read an excerpt that describes a person having trouble sleeping. You should take that excerpt and compare that to other people who also experienced trouble sleeping. Take notice of any similarities or differences between those experiences.

*For the purpose of this article we will refer to collected data as ‘interview transcripts’ and ‘transcript excerpts’, but you can use any type of qualitative data such as observations, notes, etc.

Reflect on thoughts and contradictions by writing grounded theory memos during analysis

Reflect on your analytical thoughts and write them down in the form of memos. Think of memos as your “notes to self” to record your train of thought, and to keep a record of your reflections. These notes are an essential part of conducting grounded theory research and serve several important purposes:

Memo writing in grounded theory helps track your thought process: Analytical memos allow you to keep track of your thought process as you work through the data. They capture initial impressions, hunches, and emerging themes, which can help develop your coding scheme later on.
They promote reflexivity: Memos encourage you to reflect on any biases, assumptions, and preconceptions. By bracketing yourself, you are able to acknowledge how your own experiences and perspectives may be influencing your analysis.
They facilitate collaboration: Memos can be shared with other researchers to facilitate collaboration and improve inter-code reliability. By adding memos with tools like Delve’s memo feature, you can also streamline peer debriefing to improve the overall credibility of your research.
They support the development of theory: Memos are an important tool for developing theory in grounded theory research. By tracking emerging themes and patterns in memos, you can often develop more abstract concepts and theories that are grounded in the data.

In the end, memos are an intrinsic part of grounded theory research. They help you track your thought process, promote reflexivity, facilitate collaboration, and support the development of theory.

Learn more about analytical memos here.

4. Group excerpts together into codes using open coding

As you make comparisons between excerpts of data, look for sets of excerpts that represent the same central idea or concept, and group them together. You can use a “code” to encapsulate these groups of excerpts. Codes are like tags or labels that are assigned to excerpts of text.

For example, suppose you were comparing these excerpts:

“I just kept watching the news, even late into the night. And found myself having a harder and harder time falling asleep”
“Definitely was experiencing insomnia for a while…”
“I was so worried. The thoughts kept spinning in my head and I’d lay there with my eyes open for hours”

All of these represent the concept of “trouble sleeping”. So if you are using qualitative data analysis software, you can create a code called “trouble sleeping” and bring all of these excerpts under the code “trouble sleeping”.

Once you have a code called “trouble sleeping”, all future excerpts that you analyze should not only be compared to other excerpts, but they should also be compared to the code “trouble sleeping”, and any other code that you have.

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5. Group codes into categories using axial coding

As you gradually develop a list of codes that bring together sets of excerpts, you should also begin to also compare codes with other codes. When you find connections between multiple codes, you can group them together into a ‘category’. This step of grounded theory is called ‘axial coding’, where you find the axes that connect various codes together. If you are using qualitative data analysis software, these categories are represented by a series of ‘nested codes’ which are stacked in a hierarchy.

For example, in the previous step, we had a code called “trouble sleeping”. Suppose you also had another code, “experiencing panic attacks”. You may find that there is a relationship between these 2 codes and they can be grouped under a category called “Reacting negatively to the pandemic with anxiety”.
In qualitative data analysis software, this hierarchy would look like this:

[Reacting negatively to the pandemic with anxiety]
- [Trouble sleeping]
- [Experiencing panic attacks]

If you would like a more structured approach to finding ways to group codes together, you can learn more about Corbin and Strauss’s coding paradigm, which you can read more about here.

6. Analyze more excerpts using constant comparative method

Remember, grounded theory is a cyclical process! Even after you have created lists of codes, and grouped codes into categories, you should continue to analyze additional interview transcripts, and compare the new excerpts to your existing codes categories. Read more about constant comparative method here.

As you make comparisons between your new excerpts to your codes and categories, your excerpts will generally do one of three things: contradict, expand upon, or support your existing codes and categories. Here’s what you should consider in each scenario:

Contradiction: If your new excerpt contradicts a code, this may be a sign that you need to adjust that code or change it. It likely also means that you need to go back to step 2 and conduct more rounds of data collection through theoretical sampling to help explain the contradiction. Read more about how to handle contradictions in our article on negative case analysis.
Expansion: If your new excerpt expands upon your code, either by adding more description or explaining more facets of your code, this is a good sign that you are continuing to learn more and it means that you should continue to collect and analyze data until your new excerpts simply support your codes rather than expand upon them.
Support: If your new excerpt generally supports your code without adding additional information, this means that you may have reached theoretical saturation, which is the point at which more excerpts do not contribute any additional insight into your codes and you can move onto a later stage of your research.

With grounded theory, your goal is not to code or keep track of everything that occurs in every excerpt. For example, once you establish the category that people under COVID-19 lockdown were [Reacting negatively to the pandemic with anxiety], you don’t need to go back and code every single excerpt that refers to that category. However, if you come across an excerpt where a person did not [react negatively to the pandemic with anxiety], this may open the doors to expanding upon or changing your category.

7. Continue collecting data and analyzing until you reach theoretical saturation

With these iterative steps, when do you know that you have analyzed enough? How do you know when you should stop recruiting or analyzing additional data?

With grounded theory, you want to continue until you reach the point where additional transcript excerpts do not expand upon your codes and categories. In other words, if you are learning the same thing over and over again even with additional excerpts, that means that your codes and categories have become ‘theoretically saturated’. The excerpts you have collected so far address all relevant aspects of your codes and categories and there is no need to pursue further data collection or analysis for your particular codes and categories.

8. Define the core category using selective coding

Once you feel you have reached theoretical saturation in your codes and categories so far, it is time to pull your findings together with selective coding. With selective coding, you connect all your codes and categories together under one core category.

This core category represents the central thesis of your research, and is the core idea behind your theory. This core category can be an existing category that you derived earlier, or it can be a new category that you derive from all your existing findings so far.

This core category will be the basis for your new grounded theory.

For example, if you have a list of categories like

[Reacting negatively to the pandemic with anxiety]
[Feeling loneliness during lockdown]
[Virtual and in person socializaton]
[Mental health pre-COVID-19]
[Current housing set up not suited for lockdown]

You may use selective coding to define the central, core category as [Access to lockdown suitable housing, mitigated COVID-19 Anxiety during lockdown], to link all your existing categories together.

Learn more about selective coding here.

9. Write your grounded theory

Once you have determined your core category through selective coding, and are confident that you have reached theoretical saturation, it is time to construct your new theory.
Gather together your coded data, and series of memos and use them to describe your new theory.

State your new theory in just a couple words or sentences
Define the limits or boundary of your theory
Summarize and write a description of your theory
Use your coded data to validate the points you suggest in your theory
Write an accurate statement of what was studied, and construct your theory in a form that other researchers can use.

Grounded theory vs. grounded theory lite

The goal of grounded theory is to develop a formal theory, a set of interrelated concepts that explain a particular phenomenon. The process tends to be both time and resource intensive.

Pidgeon & Henwood (1997) refer to this intensive theory-building process as “full grounded theory.” They argue that many researchers who claim to use grounded theory in their research actually apply a simplified version, which they refer to as "grounded theory lite.”

What is grounded theory lite?

Grounded theory lite is a shortened, more “pragmatic approach to grounded theory” that focuses on gaining a preliminary understanding of a topic. It involves developing categories and concepts and understanding their relationships, without the need to generate formal theory.

Here are some of the key features of grounded theory lite:

It is a less rigorous approach to grounded theory.
It does not require the development of a formal theory.
It can be completed in a shorter period of time.
It is often used in smaller research projects.

This table summarizes the key differences between grounded theory and grounded theory lite:

Feature
Grounded theory
Grounded theory lite


Rigor
Rigorous
Less rigorous

Time
Time-consuming
Less time-consuming

Resources
Resource-intensive
Less resource-intensive

Theory development
Develops a formal theory
Develops a preliminary understanding of a topic

Use
Used in large research projects
Used in smaller research projects

Feature	Grounded theory	Grounded theory lite
Rigor	Rigorous	Less rigorous
Time	Time-consuming	Less time-consuming
Resources	Resource-intensive	Less resource-intensive
Theory development	Develops a formal theory	Develops a preliminary understanding of a topic
Use	Used in large research projects	Used in smaller research projects

In other words, grounded theory lite is a more common approach to grounded theory, and it is often used when time or resources are limited. It is a less rigorous approach than full grounded theory, but it can still be a valuable tool for developing a preliminary understanding of a topic.

Here are some examples of when grounded theory lite might be used:

A small-scale research project that is limited by time or resources.
A research project that is exploratory in nature.
A research project that is used to generate hypotheses for further research.

The difference between grounded theory and grounded theory lite is mostly semantic as researchers tend to use the terms interchangeably. However, it helps to understand that both exist and that the main difference relates to formal theory development.

Tools for grounded theory coding

You can do your grounded theory coding by hand, using word processors and spreadsheets such as Microsoft Word and Microsoft Excel, or use Computer Assisted Qualitative Data Analysis Software such as Delve. There are pros and cons to each approach, and you should choose one based off what is most appropriate for your research. Read more about how to code qualitative data.

Try Delve, Software for Qualitative Coding

Online qualitative research software such as Delve can help streamline how you’re coding your qualitative coding. Try a 14 day free trial of Delve.

Grounded theory coding using pen and paper

You can use simple tools like pen, paper, scissors, and highlighters to code by hand. Just print out your transcripts, and do open coding by cutting up the transcripts into individual excerpts. The next steps are done by organizing those papers into piles, as you create your codes and categories.

This is a great way to organize data with your hands, but can be come very time consuming, especially with large data sets. And it can be challenging to keep track of your comparisons since you’d have to keep track of all your sheets of paper.

Grounded theory coding using a word processor

If you decide to use a word processor such as Microsoft Word or Google Docs, do your open coding round by highlighting excerpts. You can then code by adding comments to those excerpts. To create category, copy and paste excerpts into different documents labeled by the category name. This is a good way to keep your analysis in a digital format, but can feel cumbersome to continually copy and paste your

Grounded theory coding using qualitative data analysis software

Software such as the Delve qualitative data analysis software are designed to support processes like grounded theory. You can use Delve to help keep track of your excerpts and codes, and organize your thoughts as you do constant comparisons. The digital interface will help you manage large data sets and keep track of the many comparisons you will do. Additional features such as demographic filters and the ability to search across transcripts can also help streamline your grounded theory process.

Use Grounded Theory Software

Delve qualitative analysis tool is the best choice for grounded theory.

Make your life easier while doing grounded theory by using grounded theory software like Delve.

Codes and categories are constantly evolving during the grounded theory analysis process. Using pen and paper or spreadsheets to analyze qualitative data can get unwieldy and chaotic. In contrast, qualitative data analysis software like Delve helps you make sense of the mess and focus on finding your insights.

And don’t just take our word for it. Here’s what researchers say about using Delve:

“Being able to see and easily access all of my codes in one place was especially gratifying after finishing the process of coding and made data analysis much easier and more efficient. ” Noah W.

“Delve has made coding qualitative data so simple and fast. The user-friendliness makes it a must-have for any qualitative researcher” Khotso M.

“Delve was easy to use. I used it for my doctoral research and it helped me to organize my interview information into codes and categories.” David S.

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Try the Delve Software for Qualitative Coding

Online software such as Delve can help streamline how you’re coding your qualitative coding. Try a free trial or watch a demo of Delve.

References

Corbin, J., & Strauss, A. (1990). Grounded theory research: Procedures, canons, and evaluative criteria. Qualitative Sociology, 13, 3-21.
Charmaz, Kathy (2006). Constructing Grounded Theory: A practical guide through Qualitative Analysis. Thousand Oaks, California: Sage.
Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research.
Pidgeon, N., & Henwood, K. (1997). Using grounded theory in psychological research. In N. Hayes (Ed.), Doing qualitative analysis in psychology Press/Erlbaum (UK) Taylor & Francis.

Cite this blog post:

Delve, Ho, L., & Limpaecher, A. (2021, September 17). The Practical Guide to Grounded Theory. Practical Guide to Grounded Theory Research. https://delvetool.com/groundedtheory