Beyond Numbers: Why Qualitative Data Belongs in Every PT's Toolkit

In a profession often driven by measurable outcomes, physical therapists can easily fall into the rhythm of tracking what can be counted such as range of motion, gait speed, balance scores, and strength grades. Yet, not all progress is visible through numbers. Qualitative data captures the why and how behind these metrics, offering insight into a patient’s lived experience, their beliefs, motivations, frustrations, and perceived progress.

While quantitative data tells us what has changed, qualitative inquiry reveals what that change means to the patient. A patient may show minimal improvement on a balance assessment but report feeling more confident walking to the mailbox. Another might surpass the minimal detectable change (MDC) on a gait measure yet still feel unsafe walking without an assistive device. Just as clinicians distinguish between MDC (a measure of test reliability) and MCID (the patient’s perceived meaningful change), understanding qualitative data respects that reliability does not always equal relevance for every individual.

Capturing the Human Experience

According to Kiger and Varpio (2020), qualitative data analysis, particularly thematic analysis, is a powerful yet flexible method that seeks to identify patterns of meaning within experiences, thoughts, or behaviors. In health research, it helps clinicians explore not just what patients do, but how they interpret what they do.

Data is often collected through interviews, focus groups, open-ended surveys, or clinical reflections, allowing participants to express their experiences in their own words. Thematic analysis, as described by Braun and Clarke and detailed by Kiger and Varpio, follows a six-step process.

1. Familiarizing yourself with the data

2. Generating initial codes

3. Searching for themes

4. Reviewing themes

5. Defining and naming themes

6. Producing the report

This process is recursive, not linear, it evolves as patterns emerge. Themes are not simply summaries of what patients say; they are interpretations that connect individual perspectives to broader concepts such as motivation, fear, self-efficacy, or trust. For example, a recurring patient statement like “I’m afraid of falling again” might lead to a theme around fear-driven avoidance that shapes both behavior and therapy engagement.

Kiger and Varpio emphasize that these themes can be developed inductively (emerging from the data itself) or deductively (guided by an existing theory), allowing clinicians and researchers to flexibly align their analysis with the study’s purpose.

Evaluating Qualitative Research

For all its strengths, qualitative research is not immune to misuse. Kiger and Varpio note that many studies suffer from imprecision and inconsistent terminology, a problem that has fueled skepticism about qualitative rigor in health research. Too often, papers report that data were “analyzed for themes” without explaining how those themes were generated or what philosophical framework guided the process.

This lack of clarity can make qualitative findings feel more like storytelling than science. Without an explicit description of the analytic steps taken (how codes were defined, how themes were reviewed, and what theoretical assumptions were made) clinicians cannot fully trust the conclusions.

To evaluate the quality of qualitative research, clinicians and readers should look for the following:

• Transparency: Are the analytic steps clearly outlined and justified?

• Alignment: Do the research questions, methods, and interpretation align under a consistent epistemological lens (e.g., constructivist, post-positivist)?

• Trustworthiness: Does the study provide an audit trail, use multiple coders, or offer participant quotes to support conclusions?

• Depth vs. Description: Does the analysis move beyond surface-level description into meaningful interpretation of context and experience?

Without these elements, even well-intentioned qualitative work risks becoming vague, biased, or anecdotal. As with quantitative data, poor methodology leads to poor conclusions. The difference is that in qualitative work, the flaws are often hidden beneath eloquent prose instead of faulty p-values.

When and How to Integrate Qualitative Insights in Practice

Functional outcome measures (10-meter walk tests, Berg Balance Scale scores, or DASH questionnaires) are essential for tracking objective progress. However, qualitative data offers the emotional and cognitive context behind those numbers.

By engaging in brief patient interviews, open-ended questions (“What changes have you noticed since starting therapy?”), or reflective journaling, clinicians can uncover discrepancies between measured and perceived improvement. These insights allow therapists to:

• Adapt interventions based on how patients interpret success or failure.

• Strengthen therapeutic alliance by validating patients’ lived experiences.

• Identify barriers such as fear, pain catastrophizing, or lack of confidence that may not appear in quantitative tests.

• Enhance shared decision-making, aligning treatment goals with what truly matters to the patient.

Integrating qualitative understanding doesn’t replace standardized measures, it amplifies their meaning. It helps clinicians bridge the gap between functional gains and patient satisfaction, ensuring therapy remains patient-centered rather than data-driven alone.

Parting Words

In physical therapy, numbers can guide our decisions, but stories give them context. Qualitative research, through methods like thematic analysis, offers a structured, transparent way to listen, interpret, and act upon patient narratives. But it’s not enough to quote feelings or themes; we must also demand methodological rigor. Just as MCID reminds us that change must feel meaningful to matter, qualitative inquiry reminds us that healing is not only measured in degrees and seconds but also in confidence, understanding, and empowerment. The challenge lies in doing it well and in recognizing when “themes” are built on solid analysis rather than soft interpretation.

References

1. Kiger ME, Varpio L. Thematic analysis of qualitative data: AMEE Guide No. 131. Med Teach. 2020;42(8):846-854. doi:10.1080/0142159X.2020.1755030

Disclaimer

I am a current Doctor of Physical Therapy (DPT) student sharing information based on my formal education and independent studies. The content presented in this newsletter is intended for informational and educational purposes only and should not be considered professional medical advice. While I strive to provide accurate and up-to-date information, my knowledge is based on my current academic and clinical rotations and ongoing learning, not extensive clinical practice.