Shared decision-making pediatric physical therapy: workflow

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.

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.

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.

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.

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.

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.