Physical therapy teams collect patient-reported outcomes to understand symptoms, functioning, and treatment progress, but questionnaire burden can limit the value of that data. Qualitative analysis in physical therapy helps researchers explain why a measurement tool works, where workflows fail, and what patients and clinicians need before implementation can scale. A mixed-methods study published by PLOS One on November 13, 2026, examined Dutch-Flemish PROMIS computerized adaptive tests, or PROMIS CATs, in primary care physical therapy. The study combined a survey of 25 physical therapists with interviews involving 10 physical therapists and 9 patients across 14 practices. This article refracts those findings through AI-enabled qualitative research, showing how researchers can move from interview transcripts to defensible themes, barriers, and cross-segment comparisons more efficiently. The analysis remains research-focused and non-diagnostic.
Key Takeaways
According to the PLOS One study on PROMIS CAT feasibility, PROMIS CATs were generally feasible and useful in primary care physical therapy, but sustainable implementation depended on reducing duplicate questionnaires, improving score interpretation, and fitting the technology into clinical workflows.
AI-enabled qualitative research can help physical therapy researchers organize interview evidence around implementation domains, compare patient and clinician perspectives, and identify where survey results converge or diverge with lived experience.
- The November 13, 2026 PLOS One study covered 14 physical therapy practices, 25 surveyed physical therapists, 10 interviewed physical therapists, and 9 interviewed patients.
- The study found that 80% of surveyed physical therapists were interested in using PROMIS CATs, while only 28% reported regular use in daily practice in the 2022 survey.
- The study found that 100% of surveyed physical therapists considered PROMIS CATs easy to administer, but only 40% believed the CATs took little time and 24% believed patients found them time-efficient.
- The qualitative interviews showed that patients generally viewed PROMIS CATs as quick and relevant when results were used in consultations, while therapists wanted better training and item-level feedback.
- The study used hybrid inductive-deductive thematic analysis, with two researchers independently coding transcripts before resolving differences through consensus discussions.
What the PROMIS CAT Study Measured
The November 13, 2026 PLOS One study evaluated whether Dutch-Flemish PROMIS CATs could work in routine primary care physical therapy for adults with musculoskeletal conditions affecting the spine and upper extremities.
The researchers assessed four feasibility domains from Bowen’s framework: acceptability, demand, practicality, and implementation. The study combined descriptive survey analysis with semi-structured interviews, allowing quantitative patterns to be interpreted alongside patient and therapist experiences.
The study collected survey responses between May 2 and June 20, 2022, and conducted interviews between March 21 and November 23, 2022. Interviews lasted between 32 and 62 minutes, with a mean duration of 47 minutes.
PROMIS CATs selected subsequent questions according to each respondent’s previous answer. The study’s CATs administered at least 4 items and stopped at a maximum of 12 items when the precision threshold was not reached.
The researchers reported that PROMIS CATs supported focused discussions about symptoms and functioning, but simultaneous use of legacy PROMs created additional respondent burden. The study also identified portal problems, uncertainty about T-score interpretation, and concerns about the relevance of some items.
PROMIS CAT Findings Snapshot
| Date or period | Metric | Value | Implication for qualitative research |
|---|---|---|---|
| September 2021 to January 2023 | Physical therapy practices in the study | 14 | The PLOS One study examined implementation across multiple real-world practice settings. |
| May 2 to June 20, 2022 | Surveyed physical therapists | 25 | Survey results provided a quantitative baseline for interpreting interview themes. |
| March 21 to November 23, 2022 | Physical therapists interviewed | 10 | Therapist interviews revealed workflow, interpretation, and implementation barriers. |
| March 21 to November 23, 2022 | Patients interviewed | 9 | Patient interviews showed how perceived relevance and consultation use shaped willingness to complete PROMs. |
| 2022 survey | Physical therapists interested in PROMIS CAT use | 80% | High stated demand did not translate into equivalent routine adoption. |
| 2022 survey | Physical therapists reporting regular daily use | 28% | The gap between interest and use indicates implementation friction that qualitative analysis can explain. |
| 2022 survey | Physical therapists rating CAT administration as easy | 100% | The finding supports technical usability while leaving broader workflow burden as a separate issue. |
| 2022 survey | Physical therapists reporting that CATs took little time | 40% | The result suggests that administration time and total PROM workload should be coded separately. |
Implications for AI-Enabled Qualitative Research in Physical Therapy
AI-enabled qualitative research is most useful here when it separates usability from implementation, because the PLOS One study found that therapists could view PROMIS CATs as easy to administer while still experiencing workflow and interpretation barriers.
The PLOS One researchers reported that only 24% of surveyed physical therapists believed patients were satisfied with PROMIS CATs, while interviewed patients generally described the CATs as quick, simple, and relevant. That divergence is a valuable analytic signal rather than a contradiction to discard.
A qualitative analysis workflow can preserve that distinction by tagging evidence by participant segment, feasibility domain, instrument type, and implementation stage. Researchers can then compare themes such as questionnaire fatigue, portal access, score interpretation, item relevance, and consultation value across patients and physical therapists.
The study’s participant quotations show why transcript context matters. Patient #5 said, "Answering the questions made me reflect on my symptoms and what I want help with." Physical therapist #3 said, "I can’t always link the questionnaire scores directly to my treatment choices." The two statements point to different forms of value: patient reflection and clinician decision support.
The PLOS One study also reported that one therapist described the adaptive questions as useful because "with one CAT you may replace several longer questionnaires." AI-assisted coding can help researchers test that implementation hypothesis against the full dataset rather than relying on a memorable quotation alone.
- Code patient and therapist transcripts separately before comparing shared themes.
- Distinguish perceived completion speed from total questionnaire burden caused by legacy PROMs.
- Track positive, negative, and conditional references to graphical feedback, especially concerns about labels such as "severe."
- Link implementation barriers to proposed solutions, including training, portal improvements, replacement of legacy PROMs, and item-level feedback.
- Use frequency and cross-segment analysis as prompts for deeper reading, not as substitutes for methodological judgment.
How Evidano Helps With PROMIS CAT Qualitative Analysis
Problem: Researchers must synthesize interviews and survey comments across participant groups
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Evidano can organize interview transcripts, survey responses, and study documents into thematic and cross-segment analyses. For a PROMIS CAT project, researchers could compare patient and therapist perspectives on burden, relevance, score interpretation, and clinical usefulness.
Researchers can explore the platform’s analysis capabilities through Evidano’s features.
Problem: Manual coding makes it difficult to move from quotations to a consistent code structure
Solution: Evidano’s thematic analysis can help researchers identify recurring themes and structure hierarchical codes and subcodes around feasibility domains such as acceptability, demand, practicality, and implementation.
Researchers can review the resulting evidence, refine codes, and use visualizations such as co-occurrence networks or hierarchical code structures to inspect relationships among barriers and facilitators.
Problem: Multilingual or sensitive healthcare interviews require careful preparation
Solution: Evidano supports transcription with custom dictionaries and PII redaction, along with translation using custom terminology. Those capabilities can help teams prepare interview data while preserving domain-specific language for physical therapy and patient-reported outcomes.
Healthcare researchers should still review transcripts, translations, redactions, and analytic outputs against the original recordings or source materials.
Problem: Researchers need to interrogate a large evidence set without losing source context
Solution: Evidano provides AI chat over uploaded documents and analyses, allowing researchers to ask targeted questions about themes, participant segments, supporting excerpts, and apparent contradictions.
Evidano states that data is encrypted and never used to train third-party models. Research teams should evaluate platform security and governance requirements against their own ethics approvals and data-management plans.
FAQ: Qualitative Analysis in Physical Therapy
What did the 2026 PROMIS CAT study find about physical therapy implementation?
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The November 13, 2026 PLOS One study found that PROMIS CATs were generally acceptable, practical, and clinically useful in primary care physical therapy, but routine implementation remained limited.
The study identified duplicate legacy PROMs, portal difficulties, uncertainty about score interpretation, financing, and limited organizational embedding as important barriers.
How many participants were included in the PROMIS CAT qualitative research?
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The study surveyed 25 physical therapists and interviewed 10 physical therapists and 9 patients across 14 practices.
The PLOS One researchers used the survey to describe therapist experiences and interviews to explore patient and therapist perspectives in greater depth.
Why did the study use mixed-methods qualitative analysis?
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The study used mixed methods to compare measurable patterns in the therapist survey with explanatory themes from interviews.
The PLOS One researchers classified findings as convergent, complementary, or divergent, which helped explain why therapist perceptions of patient satisfaction differed from patients’ own accounts.
What is the role of AI in qualitative analysis of physical therapy interviews?
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AI can accelerate transcript organization, thematic coding, cross-segment comparison, document questioning, and evidence retrieval, while researchers remain responsible for interpretation and validation.
For PROMIS CAT research, AI can help surface differences between patient and therapist accounts without collapsing those perspectives into one average result.
Can AI replace researchers in healthcare thematic analysis?
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AI should support, not replace, researcher judgment in healthcare thematic analysis.
The PLOS One study used independent coding, consensus meetings, a disagreement log, peer debriefing, and review by a third researcher, demonstrating why transparent human oversight remains important for sensitive qualitative research.
Conclusion and Next Steps for PROMIS CAT Research
The November 13, 2026 PLOS One study shows that PROMIS CATs can support patient-centered conversations in physical therapy, but adoption depends on more than technical ease of use. Qualitative analysis explains the conditions behind the numbers, including why interest can reach 80% while regular use remains 28%, and why patients and therapists may describe the same tool differently.
AI-enabled qualitative research gives healthcare teams a practical way to organize those perspectives, compare segments, trace themes to source evidence, and identify implementation priorities. Researchers can use Evidano to move from transcripts and open-ended responses to structured thematic and cross-segment insight, while retaining human review and research governance.
To analyze interviews, survey responses, and healthcare documents with Evidano, try Evidano for free.
Topics
- qualitative analysis in physical therapy
- AI-enabled qualitative research
- PROMIS CAT feasibility
- patient-reported outcomes analysis
- thematic analysis in healthcare
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