Commentary on News
Goal-based SDM: Qualitative analysis for pediatric PT
Evidano is an AI-powered qualitative data analysis platform that auto-transcribes interviews, redacts PII, extracts themes, and helps map codes to implementation frameworks like CFIR. Shared decision-making (SDM) in pediatric physical therapy is practical but under-implemented. This post refracts a June 30, 2026 PLoS ONE qualitative study into a repeatable qualitative analysis workflow you can run with Evidano. You’ll get: a succinct summary of findings (who, when, what), the main barriers and facilitators identified by adolescents, parents and therapists, and a 7-step Evidano playbook to extract themes, cross-segment differences, and implementation strategies from transcripts or survey responses. Use this to speed synthesis, produce stakeholder-ready visuals, and map quotes to CFIR domains for implementation planning. Ethics note: these insights are for research and quality improvement, not clinical diagnosis; always preserve consent and confidentiality.
In this article
- Key Takeaways
- Study snapshot: what the table shows
- Findings snapshot
- Fast take: why this matters (source)
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