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Shared decision-making pediatric physical therapy: workflow

Evidano6 min read

This post distills the June 30, 2026 PLOS ONE study on shared decision-making in pediatric physical therapy and gives researchers, clinicians, and UX/implementation teams a repeatable workflow to code, quantify, and operationalize those findings with AI. The study (focus groups June 30, 2023–Mar 5, 2024; n=66 total participants) found SDM should start at intake and goal-setting, run across evaluations, and requires training plus time allocation. Read the original study at PLOS ONE.

Key Takeaways

Evidano is an AI-powered qualitative data analysis platform that shortens the path from transcripts to deployable interventions by automating thematic coding, CFIR mapping, and visual reporting.

The June 30, 2026 PLOS ONE study (n=66) shows shared decision-making in pediatric physical therapy should begin at intake and goal-setting, continue across short-session checks and evaluations, and be supported by training and time allocation.

  • Primary data included 6 focus groups (adolescents n=11; parents n=9; pediatric PTs n=6) and a 46-respondent qualitative survey with a 90% response rate.
  • Key barriers identified were time constraints, balancing child/parent/therapist perspectives, and administrative load; key facilitators were adaptable SDM per family and supportive practice culture.
  • The recommended workflow maps inductive themes to CFIR domains and ERIC strategies, producing implementation actions like training, SDM tools, champions, and time allocation.

Findings snapshot

Date / PhaseInput / SampleMethodCore findingImplication
June 30, 2023–Mar 5, 2024 (Phase 1)Focus groups: adolescents n=11; parents n=9; PPTs n=66 focus groups; sensitizer task; verbatim transcriptionSDM begins at intake/goal setting; child involvement individualizedCapture quotes & map themes to SDM stages (prep → goal → choice → option → decision → evaluation)
Mar 22–Jul 3, 2024 (Phase 1 validation)Qualitative survey: 46 PPTs (response rate 90%)Open-question survey validating themes71% fully agreed; 29% added perspectivesUse survey responses to triangulate therapist barriers (time, admin)
Phase 2 / Published Jun 30, 2026Study synthesis + model adaptationAdapted goal-based SDM model; CFIR-ERIC mappingImplementation strategies: training, SDM tools, champions, time allocationDesign multifaceted implementation with measurement plan

What happened (plain English)

The study explored when and how to apply shared decision-making in primary-care pediatric physical therapy and then adapted a goal-based SDM model for that context while proposing CFIR-ERIC matched implementation strategies.

  • Primary data: 6 focus groups (adolescents, parents, pediatric PTs) plus a 46-respondent survey for validation.
  • Key barriers: time constraints, balancing multiple perspectives (child, parent, therapist), administrative load.
  • Key facilitators: adaptable SDM per family, supportive practice culture, home visits enabling contextualized plans.
  • Actions studied: start SDM at intake and goal-setting; revisit during short session checks and predetermined evaluations.

How to reproduce their qualitative-to-action workflow

Researchers and implementation leads can reproduce the paper's pipeline and replace manual bottlenecks with AI-enabled steps to speed coding and mapping.

  • 1) Ingest: collect transcripts, sensitizer assignments, and survey text into one corpus.
  • 2) Preprocess: pseudonymize PII, align timestamps, and tag participant role (adolescent/parent/PPT).
  • 3) Thematic coding: run inductive topic extraction, validate with double-coding on a 10% sample.
  • 4) Map to implementation constructs: link themes to CFIR domains and ERIC strategies.
  • 5) Deliver: create a 1-page implementation brief and share visualizations (co-occurrence, hierarchy of themes) with leadership.

Apply shared decision-making pediatric physical therapy with Evidano

Ingest & secure data

Evidano ingests interview transcripts, survey spreadsheets, and documents while supporting PII redaction and end-to-end encryption, keeping data private and not used to train third-party models.

Outcome: centralized, compliant corpus ready for analysis.

Automate thematic + CFIR mapping

Evidano provides thematic and hierarchical coding to reproduce the study's inductive themes and then runs a custom mapping to CFIR domains for barrier and facilitator triage.

Outcome: coded dataset you can filter by role (adolescent vs parent vs PPT) and stage (preparation, goal-talk, choice-talk, option-talk, decision, evaluation).

Quantify & visualize

Evidano produces frequency tables, co-occurrence networks, and subcode hierarchies to create evidence-packed visuals for leadership and training requests.

Outcome: visuals can show that, for example, "time constraints" co-occurred with "admin burden" in X% of therapist statements.

From insight to implementation

Evidano can export actionable lists matched to CFIR-ERIC strategies and support rapid piloting with AI avatar interviews for parent-facing materials and prompts.

Outcome: rapid pilot with quantitative tracking of adoption signals.

Two-week pilot checklist: run the study-to-practice loop

This two-week checklist converts qualitative findings into a clinic-ready SDM practice change.

  • Day 1: Upload transcripts and survey responses; enable PII redaction and set role tags.
  • Day 2–3: Run auto-thematic analysis; review top 12 themes and assign CFIR domains.
  • Day 4–5: Generate visualization pack (word cloud, co-occurrence, theme hierarchy) for the team meeting.
  • Week 2: Use exported implementation strategies to design a 1-hour training; deploy an AI avatar script to rehearse 'choice talk' with parents and adolescents.
  • End of pilot: collect quick PROMs or feedback forms and re-run cross-segment analysis to measure change.

Implications for implementation teams and researchers

Implementation teams and researchers should measure both process and outcome and design training and supports aligned to the study's findings.

  • Measure both process and outcome: track frequency of SDM steps (intake goal talk, periodic evaluations) and patient-reported goal attainment.
  • Design training that addresses capability (communication skills), opportunity (protected admin and training time), and motivation (local champions), aligning COM-B factors with CFIR as the paper recommends.
  • Leverage home-visit or remote-session notes to capture contextual barriers (space, time, materials) identified as crucial in the study.

Conclusion & next steps

The June 30, 2026 PLOS ONE study provides a concrete, goal-based SDM model for pediatric physical therapy and a matched set of implementation strategies for teams to adopt.

  • Read the original study at PLOS ONE.
  • Try Evidano for free to import transcripts, run CFIR-aligned thematic analysis, and produce stakeholder-ready visuals in days.

FAQ: shared decision-making pediatric physical therapy

What is the core finding of the June 30, 2026 PLOS ONE study?

The core finding is that shared decision-making in pediatric physical therapy should start at intake and goal-setting and continue across evaluations while being supported by training and time allocation.

The study synthesized focus groups and a validating survey to adapt a goal-based SDM model and propose CFIR-ERIC matched implementation strategies based on those qualitative themes.

When should SDM begin in pediatric physical therapy according to the study?

SDM should begin at intake and goal-setting, according to the study.

The research recommends revisiting SDM during short-session checks and predetermined evaluations to keep goals aligned with the child's and family's preferences.

What barriers and facilitators did the study identify for implementing SDM?

The study identified key barriers as time constraints, balancing multiple perspectives, and administrative load, and facilitators as adaptable SDM per family and a supportive practice culture.

The validating survey (46 respondents, 90% response rate) triangulated therapist barriers and informed CFIR-ERIC mapping for actionable strategies like training and champions.

How can a team reproduce the study's qualitative-to-action workflow?

A team can reproduce the workflow by ingesting transcripts, pseudonymizing data, running inductive thematic coding, mapping themes to CFIR domains, and delivering implementation briefs with visuals.

The post's stepwise runbook includes double-coding validation, CFIR-ERIC mapping, and a visualization pack for leadership to support rapid piloting.

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