Designing a PT navigator role: AI-enabled qualitative analysis

Primary keyword: PT navigator role. The PLOS ONE study by Edward et al., published 7 August 2026 in PLOS ONE, used a two-round modified Delphi to define a physiotherapist navigator role for acute cancer care in Canada, providing concrete design choices and numeric consensus thresholds. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. Researchers, clinical leads, and implementation teams designing navigation or rehabilitation roles need clear role elements, measurable assessments, and fast synthesis of open-text feedback; this post explains how the PLOS ONE study (PLOS ONE) findings map to AI-enabled qualitative methods and practical next steps.

Key Takeaways

According to the PLOS ONE article by Edward et al. (published 7 August 2026) PLOS ONE, a two-round modified Delphi (Round 1 n = 34, Round 2 n = 18) reached consensus on a four-domain PT navigator role and produced actionable role changes that will be trialed in a pilot RCT.

34 participants completed Round 1 between 8 January and 19 March 2025, and 18 completed Round 2 between 2 April and 16 April 2025 (PLOS ONE).
The study reported a perceived usefulness score of mean 9.19/10 (SD 2.12) and a figure clarity mean 4.39/5 (SD 0.96) in Round 1 (PLOS ONE, published 7 Aug 2026).
Consensus rules were predefined: new items added if ≥10% of respondents suggested them, and items considered in consensus if mean ≥5.25/7 (i.e., 75%) in Round 2 (PLOS ONE).
Key role changes supported in June 2025 consensus meeting included longer initial appointments, patient self-referral, more objective testing, and emphasis on self-management rather than hands-on treatment (Edward et al., 2026).

What happened and how the Delphi measured consensus

Answer: The study ran a two-round online modified reactive Delphi, collected qualitative feedback in Round 1 and quantified agreement in Round 2 to produce a final role description (PLOS ONE).

Edward et al. used an initial role description derived from a 2025 scoping review and professional navigation frameworks, then opened Round 1 for 10 weeks (8 Jan to 19 Mar 2025) to collect open-text responses and two numeric ratings (PLOS ONE).

Round 2 was activated two weeks after Round 1 closed, ran for two weeks (2 Apr to 16 Apr 2025), included only Round 1 completers, and used 7-point Likert ratings where mean ≥5.25/7 (75%) defined consensus (PLOS ONE).

The research team analyzed open-text responses with duplicate content analysis, resolved coding disagreements by discussion, and added items suggested by ≥10% of participants to the Round 2 instrument (PLOS ONE).

Findings snapshot

Date	Metric	Value (from study)	Implication for role design
Jan 8–Mar 19, 2025	Round 1 completions	n = 34	Sufficient qualitative variation to surface 7 themes that informed Round 2 (PLOS ONE)
Apr 2–Apr 16, 2025	Round 2 completions	n = 18 (94.7% of those invited)	Quantitative consensus achieved across all items (≥75%) enabling finalization (PLOS ONE)
Round 1 (reported in study)	Perceived usefulness	mean 9.19/10; SD 2.12	High clinician-perceived utility supports pilot testing in clinical settings (PLOS ONE)
Round 1 (reported in study)	Figure clarity	mean 4.39/5; SD 0.96	Role process visualization was understandable but was refined per feedback (PLOS ONE)
June 2025	Consensus meeting attendees	n = 7	Final approval to trial the role with practical notes on follow-up timing and scope (PLOS ONE)

Implications for clinical researchers and implementation teams

Answer: The study gives a pragmatic, consensus-based job design that teams can pilot and measure, and researchers can use the role document as a pre-specified intervention in trials (PLOS ONE).

Designers should predefine consensus thresholds, as Edward et al. did (75% / mean ≥5.25/7) and report attrition: 55.9% of Round 1 participants consented to Round 2 contact (PLOS ONE).
Measurement plans should combine patient-reported outcomes and objective testing: the most frequent Round 1 suggestion was adding objective tests (10/34 respondents, 29.4%) to better detect impairments (PLOS ONE).
Implementation teams should expect variation by treatment type: the consensus meeting in June 2025 advised different follow-up intervals for surgery versus chemotherapy cycles (PLOS ONE).
Evaluations should include service-level metrics in addition to clinical outcomes, because the role aims to change referral patterns and access to rehabilitation (Edward et al., 2026, PLOS ONE).

How Evidano helps translate Delphi feedback into a trial-ready role

Problem: Large open-text surveys slow synthesis

Answer: Manual coding of open-ended Delphi responses delays role finalization and can miss cross-cutting patterns (PLOS ONE shows iterative qualitative feedback shaped the role).

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. Using Evidano, teams can import Round 1 open-text responses, run duplicate content analysis workflows, and export thematic codebooks to ensure reproducible tracking of suggested items like the 29.4% call for more objective testing (PLOS ONE).

Problem: Tracking consensus across rounds and segments

Answer: Delphi studies need transparent numeric tracking of who agreed with which items across rounds (Edward et al. used means, SD, and pre-specified thresholds in PLOS ONE).

Evidano supports cross-segment frequency and cross-tabulation analyses so research teams can compare responses by profession, province, or treatment focus and produce the tables needed for Round 2 instruments; see the Evidano features page for relevant tools (Evidano features).

Problem: Preparing role documents and visual figures for stakeholder review

Answer: The PLOS ONE team iterated on a process figure and improved clarity from mean 4.39/5 to a finalized figure after consensus (PLOS ONE).

Evidano can ingest draft role documents and figure captions to generate concise change logs and suggested edits that align with qualitative themes, speeding prep for consensus meetings and speeding movement to pilot RCTs.

FAQ: PT navigator role

What is a PT navigator role in acute cancer care?

Answer: A PT navigator role is a physiotherapist-positioned navigator who screens, triages, and coordinates rehabilitation for people receiving cancer treatment, aiming to detect functional impairment early and link patients to services (definition and role elements from Edward et al., PLOS ONE, 7 Aug 2026).

Edward et al. defined four domains for the role: process, assessment, triaging decisions, and duties/responsibilities and finalized the role after two Delphi rounds and a June 2025 consensus meeting (PLOS ONE).

How did the PLOS ONE study decide which items reached consensus?

Answer: The study pre-specified that items with a mean ≥5.25/7 (75%) in Round 2 would be considered to have reached consensus (PLOS ONE).

The team also added any new item to Round 2 if ≥10% of Round 1 participants suggested it, and used means, standard deviations, and duplicate content analysis to combine qualitative and quantitative evidence (PLOS ONE).

Can AI speed analysis of Delphi open-text feedback?

Answer: Yes, AI-assisted qualitative analysis can accelerate theme extraction, maintain audit trails, and quantify theme prevalence for Round 2 instrument design.

Evidano's workflows produce thematic codebooks, duplicate-review comparisons, and exportable tables that mirror the PLOS ONE study's need to synthesize 34 Round 1 responses into specific Round 2 items and to report frequencies like the 29.4% request for objective testing (PLOS ONE).

What limitations should teams expect when generalizing a PT navigator role defined by a Delphi?

Answer: Delphi samples may skew toward the professions represented and can underrepresent patient or managerial perspectives; Edward et al. noted most respondents were PTs and only one patient was on the consensus panel (PLOS ONE).

Teams should plan complementary stakeholder engagement, local feasibility checks, and pilot testing to assess cost-effectiveness and system fit before broad implementation (Edward et al., 2026, PLOS ONE).

Conclusion & Next Steps

The PLOS ONE modified Delphi study (Edward et al., published 7 August 2026) produced a consensus PT navigator role with clear domains, numeric thresholds, and design changes ready for a pilot RCT.

Clinical researchers should preregister consensus rules, plan mixed outcome measurement (patient-reported and objective tests), and include broader stakeholder input beyond professional networks, as the authors recommended (PLOS ONE).

Teams preparing to test or scale a PT navigator can use AI-assisted qualitative research to compress Round 1-to-2 cycles, produce reproducible codebooks, and generate the tables and figures needed for ethics and funder submissions.

If you want to accelerate role definition and reproducible synthesis of open-text Delphi feedback, Try Evidano for free.

Topics

pt navigator role
physiotherapist navigator role
AI qualitative research
Delphi qualitative analysis
cancer rehabilitation navigation

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Designing a PT navigator role: AI-enabled qualitative analysis

Key Takeaways

What happened and how the Delphi measured consensus

Findings snapshot

Implications for clinical researchers and implementation teams

How Evidano helps translate Delphi feedback into a trial-ready role

Problem: Large open-text surveys slow synthesis

Problem: Tracking consensus across rounds and segments

Problem: Preparing role documents and visual figures for stakeholder review

FAQ: PT navigator role

What is a PT navigator role in acute cancer care?

How did the PLOS ONE study decide which items reached consensus?

Can AI speed analysis of Delphi open-text feedback?

What limitations should teams expect when generalizing a PT navigator role defined by a Delphi?

Conclusion & Next Steps

Topics

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