Making Sense of Subjective Opinions: Analyzing and Discussing Q-Methodology Findings

By Stella Smith, Ph.D.
Introduction
So, you’ve completed your Q-sorts, collected all your data, and now you’re looking at a spreadsheet full of numbers, factor loadings, and ranked statements. You might be wondering—what now? How do you take all this and turn it into a compelling story?
That’s exactly what we’re unpacking in this post—how to make sense of your Q-Methodology data and use it to tell a story that highlights the different perspectives in your study.
This is Part 2 of my blog series on Q-Methodology. If you’re still getting familiar with the basics—like what Q-Methodology is, how to create your statement set (aka the “concourse”), and how the sorting process works—check out Understanding Q-Methodology: Bridging the Gap Between Qualitative and Quantitative Research. That post lays the foundation, and this one builds on it by diving into data analysis, interpretation, and discussion.
Step 1: Running the Factor Analysis (a.k.a. Finding the Patterns)
Once your participants have sorted the statements, the next big step is factor analysis. Sounds technical, but at its core, it’s just a way to figure out which people sorted the statements in similar ways. You can use free software like PQMethod or Ken-Q Analysis to do this part. The goal? To uncover “factors,” or groups of participants who share similar viewpoints.
Let’s say you’re studying teachers’ views on remote learning. After running your analysis, you might uncover something like this:
- Factor 1: The Flexibility Advocates – They see remote learning as a great way to give students and teachers more control over their time.
- Factor 2: The Structure Seekers – They value the routine and discipline that comes with in-person learning.
- Factor 3: The Tech Skeptics – They’re concerned that all this technology might be more distracting than helpful.
Now that you’ve got your factors, the next step is figuring out what they mean—and how to explain them.
Step 2: Defining and Interpreting the Factors (a.k.a. Telling Their Story)
Here’s where the real fun begins! Each factor represents a shared point of view, so your job is to describe what each group is thinking—and why.
Here’s how to do that:
Zoom in on defining statements – These are the statements that people in a particular factor either strongly agreed or strongly disagreed with.
Compare across groups – What makes one group stand out from another? Where do they align?
Use real voices – If you collected open-ended comments, use them! Quotes help bring each perspective to life.
Example:
For Factor 1 – The Flexibility Advocates, some key defining statements might be:
“Remote learning allows me to better balance my work and personal life.” (Strongly agree)
“I feel disconnected from my students when teaching online.” (Strongly disagree)
And for Factor 2 – The Structure Seekers:
“Students need face-to-face interaction to stay engaged in learning.” (Strongly agree)
“Technology makes learning easier and more efficient.” (Strongly disagree)
You can see how these groups have different priorities. That’s the beauty of Q—you get to spotlight those distinct viewpoints in a structured way.
Step 3: Discussing the Findings (a.k.a. So What?)
Now it’s time to step back and look at the big picture. You’ve identified the different viewpoints—now what do they mean for the real world?
Here are a few questions to guide your discussion:
What are the practical implications?
If most teachers are in the “Flexibility Advocates” group, maybe schools should explore more hybrid learning options.Were there any surprises?
Did you discover a group you didn’t expect? Maybe you thought most people would prefer remote learning, but many still believe in traditional classrooms.
How does this connect to other research?
Do your findings support what other researchers have said, or are you offering a fresh perspective?
What should happen next?
If your study is meant to inform policy, planning, or practice, what recommendations can you make?
Final Thoughts: Turning Data into Meaningful Insights
Q-Methodology isn’t just about crunching numbers—it’s about understanding how people think, what they care about, and why those viewpoints matter.
As you wrap up your findings and discussion section, keep these tips in mind:
Make sure each factor is clearly explained and easy to understand.
Use examples and quotes to make the perspectives feel real.
Highlight why your findings matter. What are we learning that we didn’t know before?
At the end of the day, Q-Methodology helps us go beyond simple surveys and get to the “why” behind people’s opinions. Whether you’re researching teachers, students, leaders, or community members, this method gives you a rich, nuanced look at human perspectives.
Want to know more?
Check out the full webinar on Q-methodology which is uploaded to the Research and Methodology Group Teams
site.
Schedule an office hours appointment
with a methodologist to discuss your Q-methodology design.
Review the Qmethod website and Operant Subjectivity - The International Journal of Q Methodology
References
Damio, S. M. (2016). Q Methodology: An Overview and Steps to Implementation. Asian Journal of University Education, 12(1), 105.
Herrington, N., &, Coogan, J. (2011). Q methodology: an overview. Research in Teacher Education, 1(2), 24-28.
Sandling, J. (2022). Q Methodology: Complete Beginner’s Guide.
Smith, S. (2024). Understanding Q-methodology: Bridging the gap between qualitative and quantitative research. University of Phoenix.
Stephenson W. The study of behavior: Q-technique and its methodology. Chicago: University of Chicago Press. 1953
Van Exel, J., & De Graaf, G. (2005). Q methodology: A sneak preview .

Stella Smith, Ph.D.
ABOUT THE AUTHOR
Dr. Stella Smith serves as the Associate University Research Chair for Center for Educational and Instructional Technology Research (CEITR). She is also an Assistant Professor of Qualitative Research at Prairie View A&M University. A qualitative researcher, Dr. Stella Smith's scholarly interests focus on the experiences of African American females in leadership in higher education; diversity, equity and inclusion of underserved populations in higher education, and P–20 educational pipeline alignment. Dr. Smith is a strong advocate for social justice and passionate about creating asset based pathways of success for underserved students.
Dr. Smith was recognized with a 2014 Dissertation Award from the American Association of Blacks in Higher Education and as part of the 2019 class of 35 Outstanding Women Leaders in Higher Education by Diverse Issues in Higher Education. Dr. Smith earned her PhD in Educational Administration with a portfolio in Women and Gender Studies from The University of Texas at Austin.