You’re in the early stages of your thesis and have decided to conduct interviews to gather empirical data. But now comes the big question: how many interviews do you actually need? Five? Ten? Fifty?
This is one of the most common questions I get asked, and the answer is—it depends.
Don’t worry, though. In this article, I’ll walk you through how to determine the optimal number of interviews for your study.
Why Isn’t There a Single Correct Answer?
You might have heard the phrase, “There are no fixed rules in qualitative research.” But what does that really mean? Unlike quantitative research, where sample size is often determined using statistical calculations, qualitative research is more flexible. Each qualitative study has different goals and uses different methods. This variability means there’s no universal number of interviews that’s always right—just guidelines and recommendations.
Luckily, Wutich and colleagues (2024) tackled this exact question in their paper. They developed a step-by-step flowchart to help you figure out the right number of interviews for your study.
According to the authors, the number of interviews largely depends on your research goals and methods. So, the first step is to clearly define what you want to achieve with your study and what kind of insights you aim to uncover. The appropriate number of interviews will then be guided by your research goals and how deeply you want to dive into the topic.
Their paper introduces several recommendations to help you narrow down the number of interviews without fixating on a rigid number. One central concept is saturation—the point at which additional interviews no longer provide new information.
The Five Key Approaches to Determining the Number of Interviews
The flowchart begins with a fundamental question: What is your research goal? Depending on whether you aim for a broad overview or an in-depth analysis, you’ll need a different amount of data.
1. Theme (Data) Saturation
If your goal is to gain a general overview of the main themes in your research area, you should aim for theme saturation. This occurs when no new themes emerge, and you’ve identified all the key aspects of your research topic. Wutich et al. (2024) recommend about nine interviews or four focus groups for this type of saturation. Theme saturation is ideal for studies designed to provide an overview of central themes, such as identifying the main stress factors among students.
Example: Imagine you’re exploring the topic of “stress in university life” and asking students what they find stressful. If, after several interviews, responses like “exam pressure” and “time constraints” keep repeating without any new factors emerging, you’ve reached theme saturation.
2. Meaning Saturation
For studies aiming to capture not just themes but also the interpretations and meanings of these themes from the participants’ perspectives, meaning saturation is the focus. This type of saturation digs deeper into the details associated with a theme. According to Wutich et al. (2024), meaning saturation usually requires about 24 interviews or eight focus groups.
Example: You’re studying how students experience exam stress. Instead of just identifying stress factors, you aim to understand how they perceive this stress. For some, it might stem from perfectionism, while for others, it’s due to time pressure or lack of support. When you’ve captured all these perspectives and no new interpretations arise, you’ve reached meaning saturation.
3. Theoretical Saturation
This approach is common in Grounded Theory, where the goal is to develop a theory that provides new insights into a phenomenon. Theoretical saturation involves understanding patterns and connections between different themes and building a theoretical foundation. According to Wutich et al. (2024), achieving theoretical saturation typically requires 20–30 interviews or more, depending on the complexity of the theory being developed.
Example: Suppose you’re developing a process theory on stress management in university life, exploring how various strategies interact over time. To create a comprehensive theory, you need detailed data covering multiple perspectives and connections. Theoretical saturation is achieved when additional interviews no longer refine or improve your theory.
Once you reach this point, you can stop collecting data—whether it’s at 23, 35, or 42 interviews. What matters is the outcome, not the exact number of interviews.
4. Metatheme Saturation
The meta-theme analysis method was originally developed to study cultural differences in language. Over time, it evolved into a mixed-methods approach that identifies overarching themes from qualitative data. This method combines qualitative data with quantitative analyses of word meanings or codes.
In recent research, meta-theme analysis has shifted towards qualitative applications, focusing on identifying and comparing shared themes across datasets collected in different locations or cultures. Typically, 20–40 interviews per site are needed to develop a solid list of main themes and identify common variations within each site.
Example: You’re researching “stress in university life” and interviewing students in both Germany and the USA. To highlight differences and similarities between these countries, you conduct enough interviews for each group until the central themes in each group start to repeat.
5. Saturation in Salience
With saturation in salience the focus is on identifying the topics that are most important to participants. This type of saturation often uses a method called “free listing,” where participants list the topics or challenges that matter most to them. Salience saturation is reached when the participants’ lists begin to repeat. Wutich et al. (2024) suggest that 10 detailed free lists are often enough.
Example: If you ask students to list the biggest challenges in university life, and after about 10 lists, no new topics emerge, you’ve reached saturation in salience. This method is especially useful for quickly identifying the central issues that are most relevant to your participants.
Applying the Flowchart Step by Step
Now that you’re familiar with the five types of saturation, here’s a quick guide to using the flowchart to determine the number of interviews for your study:
- Define Your Research Goal
Decide whether you want an overview of a topic or deeper insights and connections, such as developing your own theory or model. - Choose the Right Type of Saturation
Select the type of saturation that aligns with your goal—for example, theme saturation for a broad overview or theoretical saturation for theory development. - Set an Initial Number of Interviews
Start with the recommendations from Wutich et al., such as nine interviews for theme saturation or 20–30 for theoretical saturation. - Analyze and Adjust
Analyze your data and check whether saturation has been reached. If new themes or meanings emerge, conduct additional interviews as needed. - Draw Conclusions
Once saturation is reached and no new insights are uncovered, you’ve identified the right number of interviews for your study.
Practical Tips for Deciding on the Number of Interviews
While the flowchart provides a solid framework, practical factors also come into play. For example, the limited time available to complete your thesis. Here are some tips for efficiently implementing the recommendations:
- Stay Flexible: Qualitative research is dynamic. You may need to adjust the number of interviews during data collection—whether because new themes emerge or many themes begin to repeat. Start with an approximate number and adapt as needed.
- Use Pilot Interviews: Pilot interviews are a great way to get an initial impression and test your questions. They also help you estimate how many interviews you’ll need to cover all the relevant themes.
- Plan Time and Resources: Conducting and analyzing interviews is time-consuming. Consider how many interviews you can realistically handle without compromising the quality of your work.
- Focus on Data Quality: A thorough analysis of fewer interviews can often be more valuable than a superficial analysis of many.
Source: Wutich, A., Beresford, M., & Bernard, H. R. (2024). Sample Sizes for 10 Types of Qualitative Data Analysis: An Integrative Review, Empirical Guidance, and Next Steps. International Journal of Qualitative Methods, 23, 1-14.