How To Do Initial Coding
Initial coding is a crucial first step in the qualitative data analysis process, allowing you to break down your data into manageable, discrete excerpts.
Qualitative analysis can feel intimidating. You may feel overwhelmed by the amount of qualitative data you need to analyze. And perhaps you don’t know where to start. Thankfully, you can practice ‘initial coding’, an established approach that helps you take the first steps of analysis, and lay a solid foundation for later stages of coding.
In this blog, we will explore what initial coding entails, how it fits within the broader qualitative analysis process, the challenges you may encounter, and tools that can assist you in initial coding and beyond.
What is initial coding in qualitative research?
Initial coding, also known as “open coding,” is the first step of the coding process. In this initial pass, you break down your qualitative data into discrete excerpts and create codes to label them with.
The initial coding phase should be quick and spontaneous. Every code should be viewed as a work in progress that is expected to change as you evolve in your analysis.
Don’t put too much pressure on yourself to find the perfect code. Just code what you think it should be and know that you’ll come back to reevaluate it later.
These codes can range from descriptive to conceptual to theoretical, capturing a broad spectrum of insights.
Let the data guide you in unexpected directions. Whatever the initial codes are, expect it to change. It’s a constantly evolving process, which is why you want a flexible qualitative data analysis tool like Delve that can help store your initial codes and easily edit and refine them as you change them throughout your analysis process.
Where does initial coding fit in the qualitative analysis process?
Initial coding is the very first step in analyzing your data. Before reaching this stage, you will have already completed some data collection activities, such as conducting semi-structured interviews, and had those interviews transcribed to prepare for analysis.
Initial coding happens after you’ve recruited participants, gathered data, such as conducting semi structured interviews, got your interviews transcribed, and are ready for analyzing your data. Initial coding is the first step in analysis. Keep a log of your initial codes in a qualitative data analysis tool like Delve. After initial coding, you’ll do more rounds of coding and analysis before writing your final narrative.
The goal of initial coding will be to take this qualitative data and create a list of initial codes. While these early codes are valuable, they are often broad and unrefined first drafts. At this point, your codebook may appear somewhat disorganized, lacking a clear hierarchy or structure.
But don’t worry—this is perfectly normal! Initial coding is merely the first pass through your data, and not everything needs to be structured at this point. What's important is that you maintain a flexible system of managing your codes so that your codebook can evolve as your codes change. Keeping track of your codes using Delve’s codebook feature would be a solid way to maintain this necessary flexibility.
But the work you have done will be essential for the next steps in the process, where you refine these initial codes and uncover deeper connections.
We have several articles that guide you through these subsequent stages, each focusing on finding relationships between your initial codes:
Axial Coding: If you’re using Grounded Theory, axial coding follows initial coding. This step involves identifying central codes that connect and organize your initial codes.
Finding Themes: In Thematic Analysis, the next step involves grouping similar codes into broader themes, providing a more structured understanding of your data.
Pattern Coding: This approach groups your initial codes based on recurring patterns, helping to uncover underlying structures within the data.
After you build a foundation with initial coding, these methods help you more forward into a more coherent and insightful analysis.
Initial Coding Examples
Now that you know what initial coding is and where it fits into the qualitative analysis process. Now we’re going to cover how you actually do initial coding. First we’re going to talk about what you are going to code, then how to code it.
What should you code when conducting initial coding
When it comes to initial coding, there is no single prescribed method, allowing you the flexibility to engage with your data in a way that best suits your research objectives. Your approachcan depend on the nature of your data, your research questions, and your personal preferences. Below are some common techniques for initial coding, along with a sample transcript to illustrate how each method can be applied.
1. Line-by-Line Coding
Line-by-line coding involves coding every line of your data, making it one of the most detailed approaches. This method ensures that you don't miss any potential insights, as each line is scrutinized and coded individually.
After bringing your transcripts into a qualitative tool like Delve, highlight each line and apply an initial code to it.
2. Paragraph-by-Paragraph Coding
This approach involves coding larger chunks of data, such as entire paragraphs. It allows for a broader view of the data, where the focus is on the main ideas or themes that emerge from larger segments of text.
Qualitative analysis tools like Delve offers a quick shortcut for highlighting an entire paragraph at a time. Just highlight the paragraph, and apply a code.
Here, the entire paragraph is coded as a single unit, capturing the participant’s overall relationship with nature as a means of stress relief.
3. Coding Selectively
Coding selectively allows you to focus on coding only those excerpts that stand out as particularly interesting, surprising, or relevant to your research questions. This approach is less exhaustive but can be useful for honing in on the most significant data.
Initial coding should be a fluid and flexible process that sets you up for later stages in coding.
Regardless of the method you choose, you should keep be flexible as you code. Keep yourself open to new ideas and new patterns within your data. There is no hard fast rule of what sort of information that should be coded, but here are some types of quotes to pay attention to:
Anything that is interesting: Look for statements or ideas that catch your attention or seem particularly noteworthy.
Anything that surprises you: Coding surprising or unexpected data points can lead to new insights or challenge existing assumptions.
Any patterns you see throughout the data: Identifying recurring patterns can set you up for success in later stages of analysis.
Know that these initial codes aren’t permanent. They will evolve and change over time. Qualitative data analysis tools like Delve enable you to store initial codes, and edit, delete, and evolve them as you go.
By applying these techniques, you can systematically and thoughtfully engage with your qualitative data, laying the groundwork for deeper analysis and more refined coding in later stages.
How Should You Create Codes as Part of Initial Coding?
"Initial coding" is an umbrella term encompassing various approaches to creating codes. Since initial coding doesn’t prescribe specific guidelines for how to create these codes, you can use different coding techniques to capture the essence of the data.
There are no right or wrong coding techniques. You should select the ones that feel most appropriate for your research.
In this section, we'll walk through some common coding techniques you can use during the initial coding phase.
1. Descriptive Coding
Descriptive coding involves summarizing the topic or content of the data in the form of a noun. This technique is useful for quickly categorizing large amounts of data by labeling what the data is about without delving too deeply into underlying meanings or implications.
In this example, the descriptive code "Restoration in nature" summarizes the primary focus of the sentence, which is the restorative effect of nature on the participant.
2. In Vivo Coding
In vivo coding involves using the actual words or phrases spoken by the participant as the codes. This technique is valuable for preserving the authenticity of the participant’s voice and highlighting language that may carry particular significance within the data.
3. Process Coding
Process coding focuses on capturing actions or processes described in the data. This technique is particularly useful for identifying sequences, activities, or behaviors that are central to understanding the participant's experiences.
In this example, the process code "Engaging with nature to restore balance" highlights the action or process the participant is describing—using sensory experiences in nature as a way to regain balance.
Descriptive coding, in vivo coding, and process coding are three examples of initial coding you can employ. But there are others including, emotion coding, structural coding, and values coding.
Challenges and Best Practices for Initial Coding
Now that you understand what initial coding is, let’s discuss common challenges you might face when tackling this process for the first time. Along with these challenges, we’ll provide best practices to help you overcome them and set yourself up for success in your qualitative analysis.
1. Being a perfectionist and overthinking each code
The initial coding phase should be loose and flexible. But it’s easy to overthink and ruminate too hard on each code, or put too much pressure for them to be perfect. Try not to get stuck or blocked. Knowing that codes are expected to change and evolve can free you to create some ‘bad’ codes that will be merged or deleted later.
Best Practice: Create the first codes that come to your mind as you see your data without overthinking it.
Use a tool like Delve qualitative software that allows you to flexibly delete, rename, or merge codes. Don’t use a tool that feels too permanent and unchangeable.
For example, use sticky notes that can be easily moved around, rather than paper where changes are difficult. Similarly, choose a qualitative data analysis tool that offers flexibility, like Delve, over older software like NVivo, which may not offer the same level of adaptability.
2. Having too many individual codes
While you want to be free in creating whatever codes come to mind, be careful about creating too many as they can be difficult to manage later ron. Don’t restrict yourself too much, but also strike a balance.
A common pitfall in initial coding is creating too many codes. Later stages of coding will involve grouping and finding relationships between codes, having too many individual codes can make this process more difficult and disorganized.
Best Practice: Once you’ve created around 20 codes, start critically evaluating each new code. Ask yourself: Does this relate to a code I already have? Can I adjust an existing code to encompass both ideas? This approach will help you consolidate your codes and create a more cohesive coding framework, which will be beneficial in later analysis phases.
Use a tool like the qualitative data analysis tool, Delve, that allows for easy updating and rearranging of codes. Flexibility is key—being able to quickly modify or merge codes as you progress will prevent you from getting stuck with decisions made early in your analysis.
3. Relying on just one coding technique
While it may be tempting to stick to one familiar coding tactic, such as descriptive or in vivo coding, overreliance on a single method can limit the depth and breadth of your analysis. Descriptive coding, while quick, often results in surface-level codes. In vivo coding, on the other hand, can lead to a fragmented list of quotes that may not translate well across different transcripts.
Best Practice: Diversify your coding approach by using multiple coding tactics from the outset. For instance, you might start with descriptive coding to capture the basics, then move on to process coding to uncover deeper insights. Over time, you’ll develop a sense of which coding methods work best in different scenarios, leading to a richer and more nuanced analysis.
By being mindful of these challenges and implementing these best practices, you can navigate the initial coding process with greater confidence and effectiveness. The key is to stay flexible, be open to refining your approach, and make use of tools that enhance your coding process.
4. Skipping the initial coding phase and creating themes too early
It’s easy to feel pressured to identify themes as soon as you start coding. After all, themes are what ultimately guide your analysis. However, trying to pinpoint themes too early can lead to superficial or ungrounded conclusions that don’t fully capture the complexity of your data.
Best Practice: Give yourself time to explore the data without rushing to define themes. In the early stages, focus on understanding the data and let patterns emerge naturally. If you notice potential themes, jot them down in a reflexive memo rather than forcing them into your coding framework.
Remember, this is just the first step in the process. Allow your analysis to progress organically. As you continue coding, these initial observations will evolve and become more grounded, leading to themes that are both insightful and deeply connected to your data.
Tools for Conducting Initial Coding
Image from Delve Qualitative Data Analysis Tool.
Since initial coding is a fluid and evolving process, it’s essential to find the right tool that can accomodate this and make your process manageable. It’s also the first step of the qualitative analysis process, so you’ll want a tool that allows you to iterate your initial codes into high level themes in later phases.
Initial coding can be approached in various ways, ranging from traditional methods like pen and paper to digital tools like word processors and spreadsheets. Each of these methods offers a simple and accessible way to get started, making it easy to jump into your data by highlighting sections and writing memos. However, as you progress further into the initial coding process, the limitations of these methods become increasingly apparent.
1. Pen and Paper
Starting with pen and paper can feel natural and satisfying, allowing you to quickly jot down ideas and codes as you read through your data. The tactile experience of writing can help you engage deeply with the material. Pen and paper will feel flexible at first, however it quickly becomes cumbersome.
Challenges:
- Updating code names is difficult—once something is written in ink, changing it means crossing out or rewriting, which can lead to a cluttered and confusing codebook.
- Tracking how codes are applied across different transcripts is nearly impossible to do efficiently, making it hard to identify patterns or ensure consistency.
- Merging or adjusting codes as you refine your analysis is labor-intensive and error-prone.
2. Word Documents
Using word processors like Microsoft Word is another common approach, allowing for easy insertion of comments and memos directly in your transcripts. This method is slightly more flexible than pen and paper but shares many of the same drawbacks.
Challenges:
- Like with pen and paper, updating or merging codes across multiple documents becomes a tedious task, requiring significant manual effort.
- Understanding the distribution of codes across transcripts is difficult without a dedicated system to track them.
- As you progress to more complex stages of analysis, such as grouping codes into themes, the limitations of word documents become more apparent, hindering your workflow.
3. Excel Sheets
Spreadsheets like Excel offer some advantages over pen and paper or word documents. They allow for basic tracking of codes and can provide high-level statistics if set up correctly. However, the rigidity of spreadsheets can be a significant barrier during the fluid and exploratory phase of initial coding.
Challenges:
- Excel is not inherently designed for qualitative analysis, making it difficult to adjust codes, merge similar codes, or track nuanced patterns in the data.
- The process of changing code names or combining codes involves a lot of manual work, which can slow down your progress and lead to errors.
- As with the other methods, Excel does not easily support the transition from initial coding to more advanced stages, like thematic analysis.
4. Qualitative Analysis Tools
Recognizing the limitations of traditional methods, qualitative analysis tools were developed to facilitate the coding process. You want to choose a flexible and well designed qualitative tool like Delve which is easy to learn and simple to use.
Alternatively, many other qualitative tools, such as NVivo or MAXQDA are designed with a rigid structure that can impede the flexibility required during initial coding. The interfaces of NVivo and MAXQDA can feel cumbersome, putting a barrier between you and your data, and making the coding process more about managing the software than engaging with the material.
Delve software provides the flexibility required for initial coding
Delve qualitative tool stands out as an exception among qualitative analysis tools, offering the flexibility and ease-of-use that initial coding demands. Delve is built specifically to support the exploratory nature of initial coding, allowing you to:
Easily Update and Merge Codes: With Delve, you can quickly adjust code names, merge similar codes, and reorganize your codebook as your analysis evolves, without the hassle of manual updates.
Track Codes Across Transcripts: Delve provides a clear overview of how your codes are distributed across different transcripts, helping you identify patterns and ensure consistency throughout your analysis.
Support for Later Phases: Delve is designed to grow with your analysis. As you move from initial coding to more advanced stages like axial coding or thematic analysis, Delve’s features seamlessly support the transition, enabling you to group codes, explore relationships, and develop themes without missing a beat.
Leverage AI for Brainstorming Codes: Delve integrates AI capabilities that can suggest initial coding ideas based on your data, helping you brainstorm and overcome any initial hurdles in the coding process, while still allowing you to maintain full control over the final codes.
While traditional methods like pen and paper, word documents, and Excel sheets offer an easy entry point into initial coding, they often fall short as your analysis becomes more complex. Delve qualitative tool offers a powerful alternative, providing the flexibility and functionality needed to conduct effective initial coding and beyond, allowing you to focus on what truly matters—your data and the insights it holds.
References:
Saldaña, J. (2009). The coding manual for qualitative researchers. Sage Publications Ltd.
Cite This Blog Article:
Delve, Ho, L., & Limpaecher, A. (2024a, September 03). How To Do Initial Coding https://delvetool.com/blog/initialcoding